Eagles sign running back Jay Ajayi
PHILADELPHIA (AP) - The Philadelphia Eagles have signed running back Jay Ajayi, bringing back a key offensive player from their Super Bowl championship team two years ago.
Ajayi replaces Darren Sproles. The veteran was placed on injured reserve Friday because of a torn right hip flexor muscle.
Philadelphia’s leading rusher, Jordan Howard, has a shoulder injury and is questionable when the Eagles (5-4) host New England (8-1) on Sunday. Coach Doug Pederson said Ajayi could play despite not practicing with the team.
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Ajayi hasn’t played in the NFL since he tore an ACL last Oct. 7. He had 592 yards rushing in 10 games in 2017, including playoffs, after the Eagles acquired him from Miami midway through the season.
Ajayi ran for 57 yards in Philadelphia’s 41-33 win over the Patriots in the Super Bowl.
Wide receiver Alshon Jeffery and linebacker Nigel Bradham are out Sunday because of ankle injuries.
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Motif1DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.20042605631200472(MOR) 1.249283460465933(MSC) 5.683341106483349(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[G][HQ][F]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif2DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.17856731247477736(MOR) 0.8704059533179385(MSC) 8.031875259452868(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[S][ATP][C][G]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif3DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.22938523504337527(MOR) 0.6081985761213661(MSC) 8.014570637046589(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[G][PK][Q][YF]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif4DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.1412438279821262(MOR) 0.981941297245313(MSC) 8.03630042697607(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[VG][SAITF][C][Q]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif5DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.13152574095154174(MOR) 0.8573767998654211(MSC) 8.146441304840465(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[Q][F][Y][MF]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif6DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.1485683086736565(MOR) 0.7845038003723086(MSC) 7.073363041011472(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[R][AQV][C][VA]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif7DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.14492945503155175(MOR) 0.778554309602802(MSC) 7.00171668046504(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[SDERQ][V][IV][W]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif8DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.2179557699890428(MOR) 0.5145541189250954(MSC) 6.926155456385002(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[P][IQV][Y][TSAIMP]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif9DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.07370984551641643(MOR) 1.412916634189498(MSC) 6.7062838952246775(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[V][F][Q][KTR]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
Motif10DLocalMotif uses three scores. Motif Spatial confinement (MSC), Motif over-representation (MOR) and Motif relative-entropy (MRE) [
close ]
Motif spatial confinement (MSC) is a score that measures motif's enrichment within a sequence interval, relative to the region outside this interval [
close ]
Motif over-representation (MOR) is a statistical measure of abundance of instances of motif in a positive data set relative to background data. [
close ]
Motif relative entropy (MRE) is the information-theoretic uncertainty of a motif’s amino acid pattern relative to a background data. [
close ]
Motif Scores0.25722145463058804(MOR) 0.32968599539884835(MSC) 7.532148701302218(MRE)A motif can be defined with a regular expression (RE). All instances of a discovered motif are used to generated RE. These can be used to search a motif but not considered as an accurate way as compared to PSSM [
close ]
Regular Expression[ND][ASC][W][KR]DLocalMotif discovers anchored motifs (the motifs that co-occur with a sequence anchor). For simplicity, we assume C-terminal as a sequence anchor. [
close ]
Distance relative to anchor73.0 72.0 71.0 70.0 69.0 68.0 67.0 66.0 65.0 64.0 63.0 62.0 61.0 60.0 59.0 58.0 57.0 56.0 55.0 54.0 53.0 52.0 51.0 50.0 49.0 48.0 47.0 46.0 45.0 44.0 43.0 42.0 41.0 40.0 39.0 38.0 37.0 36.0 35.0 34.0 33.0 32.0 31.0 30.0 29.0 28.0 27.0 26.0 25.0 24.0 23.0 22.0 21.0 20.0 19.0 18.0 17.0 16.0 15.0 14.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 ↑(Anchor) The p-value is calculated by performing multiple correction on a binomial hypothesis. [
close ]
p-valueA motif is commonly represented in 'PWM format'. More details on PWM construction can be seen in our published paper. The 'PSPM format' represents the observed probability of each amino acid at each position in a motif. This information is used to generate the protein logos. The 'raw format' represents the protein sequences that were use to generate PSPM (i.e instances of discovered motif). [
close ]
Data Formats |
|
The discovered motif(s) are shown above (if any). For further information on DLocalMotif method please access http://bioinf.scmb.uq.edu.au/dlocalmotif/ |


Networks are very easy to create. All you have to do is specify an input
size and an output
size.
// Network with 2 input neurons and 1 output neuron
var myNetwork = new Network(2, 1);
// If you want to create multi-layered networks
var myNetwork = new architect.Perceptron(5, 20, 10, 5, 1);
If you want to create more advanced networks, check out the 'Networks' tab on the left.
Check out the train and evolve functions on their separate pages!
activate
Activates the network. It will activate all the nodes in activation order and produce an output.
// Create a network var myNetwork = new Network(3, 2); myNetwork.activate([0.8, 1, 0.21]); // gives: [0.49, 0.51]
noTraceActivate
Activates the network. It will activate all the nodes in activation order and produce an output.
Does not calculate traces, so backpropagation is not possible afterwards. That makes
it faster than the regular activate
function.
// Create a network var myNetwork = new Network(3, 2); myNetwork.noTraceActivate([0.8, 1, 0.21]); // gives: [0.49, 0.51]
propagate
This function allows you to teach the network. If you want to do more complex
training, use the network.train()
function. The arguments for
this function are:
myNetwork.propagate(rate, momentum, update, target);
Where target is optional. The default value of momentum is 0
. Read more about
momentum on the regularization page. If you run
propagation without setting update to true, then the weights won't update. So if
you run propagate 3x with update: false
, and then 1x with update: true
then
the weights will be updated after the last propagation, but the deltaweights of
the first 3 propagation will be included too.
var myNetwork = new Network(1,1); // This trains the network to function as a NOT gate for(var i = 0; i < 1000; i++){ network.activate([0]); network.propagate(0.2, 0, true, [1]); network.activate([1]); network.propagate(0.3, 0, true, [0]); }
The above example teaches the network to output [1]
when input [0]
is given and the other way around. Main usage:
network.activate(input); network.propagate(learning_rate, momentum, update_weights, desired_output);
merge
The merge functions takes two networks, the output size of network1
should be the same size as the input of network2
. Merging will always be one to one to conserve the purpose of the networks. Usage:
var XOR = architect.Perceptron(2,4,1); // assume this is a trained XOR var NOT = architect.Perceptron(1,2,1); // assume this is a trained NOT // combining these will create an XNOR var XNOR = Network.merge(XOR, NOT);
connect
Connects two nodes in the network:
myNetwork.connect(myNetwork.nodes[4], myNetwork.nodes[5]);
remove
Removes a node from a network, all its connections will be redirected. If it gates a connection, the gate will be removed.
myNetwork = new architect.Perceptron(1,4,1); // Remove a node myNetwork.remove(myNetwork.nodes[2]);
disconnect
Disconnects two nodes in the network:
myNetwork.disconnect(myNetwork.nodes[4], myNetwork.nodes[5]); // now node 4 does not have an effect on the output of node 5 anymore
gate
Makes a network node gate a connection:
myNetwork.gate(myNetwork.nodes[1], myNetwork.connections[5]
Now the weight of connection 5 is multiplied with the activation of node 1!
ungate
Removes a gate from a connection:
myNetwork = new architect.Perceptron(1, 4, 2); // Gate a connection myNetwork.gate(myNetwork.nodes[2], myNetwork.connections[5]); // Remove the gate from the connection myNetwork.ungate(myNetwork.connections[5]);
mutate
Mutates the network. See mutation methods.
serialize
Serializes the network to 3 Float64Arrays
. Used for transferring
networks to other threads fast.
toJSON/fromJSON
Networks can be stored as JSON's and then restored back:
var exported = myNetwork.toJSON(); var imported = Network.fromJSON(exported);
imported
will be a new instance of Network
that is an exact clone of myNetwork
.
standalone
Networks can be used in Javascript without the need of the Neataptic library,
this function will transform your network into a function accompanied by arrays.
var myNetwork = new architect.Perceptron(2,4,1); myNetwork.activate([0,1]); // [0.24775789809] // a string var standalone = myNetwork.standalone(); // turns your network into an 'activate' function eval(standalone); // calls the standalone function activate([0,1]);// [0.24775789809]
The reason an eval
is being called is because the standalone can't be a simply
a function, it needs some kind of global memory. You can easily copy and paste the
result of standalone
in any JS file and run the activate
function!
Note that this is still in development, so for complex networks, it might not be precise.
crossOver
Creates a new 'baby' network from two parent networks. Networks are not required to have the same size, however input and output size should be the same!
// Initialise two parent networks var network1 = new architect.Perceptron(2, 4, 3); var network2 = new architect.Perceptron(2, 4, 5, 3); // Produce an offspring var network3 = Network.crossOver(network1, network2);
set
Sets the properties of all nodes in the network to the given values, e.g.:
var network = new architect.Random(4, 4, 1); // All nodes in 'network' now have a bias of 1 network.set({bias: 1});
clear
Clears the context of the network. Useful for predicting timeseries with LSTM's. clear()
has little to no effecton regular NN, use on RNN's!
Each network only has a small number of properties.
input
Input size of the network
output
Output size of the network
nodes
Array of nodes
connections
Array of connections
gates
Array of gated connections
selfconns
Array of self connections


Herein we present agapo, a set of postscript examples to ease the task of drawing board game diagrams. You can download files for Go-like diagrams (also for hex boards), Othello-like diagrams, Hex-like diagrams, Checker-like diagrams (also for hex boards) , Mancala boards, Chess-like diagrams, Dominoes and Tesselations. These are text files (use your favorite text editor to open it). Each have two parts: (a) a set of routines (learn how to use them in the next sections) that handle the drawings (do not modify them before you learn a bit of PostScript) and (b) an example that you should change in order to make your own diagrams.AGAPO
Abstract Game PostScriptsby Cameron Browne and João Neto
OSTSCRIPT page description language provides a device independent standard for representing the printed page. [...] The POSTSCRIPT language is a programming language designed to convey a description of virtually any desired page to a printer. It possesses a wide range of graphic operators that may be combined in any manner. It contains variables and allows the combining of operators into more complex procedures and functions. [cited from "Postscript - Tutorial and Cookbook" - Adobe Systems].The P
Some PostScript interpreters may work better if the files end in .eps (Encapsulated PostScript) others with .ps. The internal code need not be changed.
There are the following routines:
Board
Usage: rows cols [true|false] Board
makes a GO board with size (rows+1) x (cols+1) with/without coordinates
Example: 4 7 false Board
White
Usage: row col White
draws a white stone at position (row,col)
Example: 2 3 White
Black
Usage: row col Black
draws a black stone at position (row,col)
Example: 2 3 Black
Grey
Usage: row col Grey
draws a grey stone at position (row,col)
Example: 2 3 Grey
Marker
Usage: row col [0-1] (string) Marker
draws a string (usually one character) at a given position. The 3rd argument
is the color (between 0=black and 1=white). The 4th argument defines two types
of presentation.
Example: 5 4 1 false (a) Marker
MarkerSm
Usage: row col [0-1] (string) MarkerSm
draws a string (usually two characters) at a given position.
Example: 5 4 1 false (12) MarkerSm
WhiteSpot
Usage: row col WhiteSpot
draws a white spot at position (row,col)
Example: 1 4 WhiteSpot
BlackSpot
Usage: row col BlackSpot
draws a Black spot at position (row,col)
Example: 2 3 BlackSpot
This example produces this image:
| 6 10 true Board 6 4 White 3 5 White 4 4 White 6 5 White 7 5 White 3 6 White 5 2 Black 5 3 Black 3 4 Black 5 4 Black 2 5 Black 4 5 Black 2 7 Black 1 1 Grey 5 4 1 false (12) MarkerSm 5 3 1 false (b) Marker 4 4 0 true (c) Marker 6 2 WhiteSpot 6 2 0 false (d) Marker 3 3 BlackSpot |
There are also the possibility of Rosette-like games (however, the labels are not automatic). This file does not have an automatic board routine. You'll need to place each hexagon. The coordinates are not orthogonal: changing x and maintaining y will produce a diagonal line of hexagons. There is also a 3rd coordinate z which places the stone at a vertex of that hex (0 is the top left vertex, and it goes clockwise, check the example). This is the diagram produced by rosette-template.eps:.
The methods are the same as in the previous section (except WhiteSpot and BlackSpot), including:
White2
Usage: row col White2
draws a second type of white stone at position (row,col)
Example: 2 3 White2
Black2
Usage: row col Black2
draws a second type of black stone at position (row,col)
Example: 2 3 Black2
| 6 6 true Board 6 4 White 3 5 White2 6 5 White 3 6 White 5 2 Black 3 4 Black 5 4 Black 2 5 Black2 2 1 Grey 5 2 1 true (a) Marker 6 5 0 false (12) MarkerSm 4 4 0 true (c) Marker 6 2 0 false (d) Marker |
Includes routines White, Black, Black2, Grey, Marker, MarkerSm and:
Hexagon
Usage: x y Hexagon
draws a hexagon at position (x,y)
Example: 2 3 Hexagon
Label
Usage: x y (string) Label
draws a string at position (x,y)
Example: 2 3 Label
This file does not have an automatic board routine. You'll need to place each hexagon. The coordinates are not orthogonal: changing x and maintaining y will produce a diagonal line of hexagons. This is the diagram produced by hex-template.eps:
Includes routines Marker, MarkerSm and:
Board
Usage: rows cols int-array [insert coordinates?] Board
The array presents all pieces onboard. Each cell have a number up to 5
digits that define the stack's structure.
1 is a white checker, 2 a black checker, 3 a grey checker; 4,5,6:
white,black,grey stones with dots.
White
Usage: row col height White
draws a white stone at position (row,col) with a certain height
Example: 2 3 2 White
Black
Usage: row col height Black
draws a black stone at position (row,col) with a certain height
Example: 2 3 0 Black
Grey
Usage: row col height Grey
draws a grey stone at position (row,col) with a certain height
Example: 2 3 1 Grey
There is also WhiteDot, BlackDot, GreyDot with the same arguments, but place a checker with a dot.
| 8 8 [ 0
0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23456 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1111 1231 13121 423 141 252 363 456 23 33 112 123 321 222 123 232 1 2 3 11 12 13 21 22 ] true Board y |
|
There is also another file for checker like pieces in hex boards:
There are the following routines:
Board
Usage: rows cols [boolean coord] [boolean houses] Board
makes a Mancala board with size rows x cols with/without coordinates and
with/without houses
Example: 2 6 false true Board
White1
Usage: row col White1
draws one white stone at position (row,col)
Example: 2 3 White1
Black1
Usage: row col Black
draws one black stone at position (row,col)
Example: 2 3 Black1
Similar functions: Black2, Black3, Black4, Black5, Black6 (and also White2 to White6) which places from 2 to 6 stones at a given cell. There is also Blacks (and Whites) to be used for cells with more than 6 stones. These last functions should be used with:
Marker
Usage: row col [0-1] (string) Marker
draws a string (usually one character) at a given position. The 3rd argument
is the color (in this case, is better to use color 0)
Example: 5 4 0 (7) Marker
MarkerSm
Usage: row col [0-1] (string) MarkerSm
draws a string (usually two characters) at a given position. The 3rd
argument is the color (in this case, is better to use color 0).
Example: 5 4 0 (12) MarkerSm
| 2 6 false false Board 1 1 Black4 1 2 Black4 1 3 Black4 1 4 Black4 1 5 Black4 1 6 Black4 2 1 Black4 2 2 Black4 2 3 Black4 2 4 Black4 2 5 Black4 2 6 Black4 |
|
| 3 7 true true Board 2 3 White1 2 4 Black1 2 5 Black2 1 2 Black3 1 4 Black4 1 6 Black5 2 6 Black6 3 6 Blacks 3 7 Blacks 3 6 0 (7) Marker 3 7 0 (13) MarkerSm |
This postscript needs this font (on Windows you may need to put it on folder \Windows\Fonts).
There are the following routines: Board, Marker, MarkerSm
Board
Usage: rows cols int-array [insert coordinates?] Board
The array presents all pieces onboard. 1,2,3,4,5,6 means white pawn, knight,
bishop, rook, queen and King. A minus signal on those numbers represent black
pieces. Add 10 to invert white pieces, subtract 10 to invert black pieces.
| 8 8 [ -4 -2 -3 -5 -6 -3 -2
-4 -1 -1 -1 -1 -1 -1 -1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 4 12 3 5 6 3 2 4 ] true Board |
|
There are the following routines: DominoUp, DominoRight, Sq
DominoUp & DominoRight
Usage: rows cols dot-number1 dot-number-2 Domino[Up/Right]
Sq
Usage: rows cols north-bold-line? east-bold-line? south-bold-line?
west-bold-line? dot-number Sq
If the dot-number is negative, it rotates 90º.
Here is an example using dominoes-template.eps:
| 7 0 4 2 DominoRight 7 2 2 3 DominoRight 6.5 4 3 3 DominoUp 7 5 3 6 DominoRight 5.5 1.5 false false true true 2 Sq |
|
Polygon
Usage: xx yy rotation n-sides Polygon
draws a polygon at (x,y) with n sides and a certain rotation (between 0-359)
Example: 1 0 TriXY 0 3 Polygon
There are a set of routines that help to pinpoint the exact position for each polygon (Hex, Tri, Square, Octo, Dode). Check the source file to see how the following examples are designed:


Game Haven is the place for middle school students to sharpen their skills in mathematics and problem solving. The games on our site are designed to incentivise independent mathematics learning through engaging mini-games and the opportunity to win tickets to theme parks.
A school disrict should enroll their students in Game Haven if they require a means of delivering incentivised and monitored education to students over summer break and through the academic year.


The other day I couldn’t get a head massage at my barber’s because the masseuse wasn’t in. So I asked for the refund equivalent. I laughed at his witty response: “to compensate, next time you’ll get a longer massage.”And just like that he had retained the sale in full. The issue here isn’t about denying customers a refund they genuinely deserve. No. That’s plain good customer service and should be exalted. What I’m on about is acquiescing to a price reduction, terrified of negotiating, all for fear of losing a sale.
Experienced buyers are known to force concessions with every aspect of the transaction. A 2% off here and a 3.5% off there may look small but cumulatively will considerably change the package. Learning to negotiate therefore becomes part of the stock-in-trade for the salesperson- like my barber promising me a longer massage (I’m still tickled by this). I once read somewhere that price is what you pay, but value is what you get. And value is a perception. When a prospect is asking for a price reduction he most probably does not perceive its value. This is one reason why prospects negotiate. The salesperson is not to be dragged down with the price but to rise up to the occasion and demonstrate the value equivalent.
How? As the column has averred, selling is an emotional exercise camouflaged in logic. And emotion cannot be grasped-just like perception. However, emotion (an experience) can be regenerated, and in that instant, vividly relieved. Like my getting tickled every time I think about the “longer massage”, or, suddenly feeling deeply saddened when one remembers the loss of a loved one a decade ago. In practice therefore, if the prospect wants to buy a new computer and you establish from him that it’s because the one he has is slow, don’t stop at slow-that’s logic and relative. Instead, let him describe his latest computer nightmare. As he relives the frustration (emotion) every time his computer drags (or crashes) you will vividly see the pain on his face and hear it in his voice. NOW he appreciates value-and his need to negotiate the price that will take away this pain will most likely fade away.
Negotiations also happen because it is in our culture. Dukawallas will pre-empt negotiations (bargaining) by stating, “The price of the tire is Kes. 10,000 but I give you discount, so you pay only Kes.8,500”; or, the stall owner, “bei ni ya kuongea (price is negotiable).” This knowledge should energize the salesperson to approach negotiating from a point of strength-not fear.
Yet another reason to be confident in negotiations is because prospects smell insecurity in the salesperson. And because Sunday school moments are rare in the field, like a predator smelling the prey’s fear, prospect’s circle in and lunge for the jugular. Value is only valued is the valuer values it. Highly valuing your own value is the beginning of successfully handling negotiations. It also enables you have the strength to do the ultimate in negotiations-walk way because your lower threshold has been breached.
Admittedly, there are instances where the salesperson stoops to conquer- like accepting an alteration in the package today, which is obviously hindering more profitable business tomorrow. And that is fine-after all, even this is a form of negotiation.
The whole purpose of negotiating isn’t to win. No. That’s myopic. Negotiations must aim for both the seller and buyer coming out feeling that value was derived.


Why R
R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.
The R Foundation
R is a versatile programming language that is particularly widespread between statistician community. For this reason, there are many web pages devoted to explaining how to install and use it. Moreover, there are thousands of blogs, forums and discussion platforms where users can find answers to the most common questions.
R is open-source software that is freely available for the most common platforms, like Windows, Mac e several Linux distributions.
For example, we can find countless tutorials on how to install R on our platform and a simple Google query returns millions of pages.
In our case, we will follow divide the installation of R in two steps:
- install R;
- install an interface.
We are going to install the latest version, released the 2019-07-05.
Install R
Let’s proceed with the installation.
Download R
We can retrieve the R releases in the cran site, where we can select the closest server to proceed with the download. For example, we can select the Università di Padova server and download the package for our platform.
R is open-source, thus not only we can download the installers but we can also download the source code, modify it and compile it. However, for the end of this course, we will just choose the right installer for our OS (operative system) and proceed with the installation. In the figures, you can see the case of a Mac.
From this page, we can also download older versions of R. We will see this into details later, but just remember that this is particularly important if we are working with R extensions, called packages. Sometimes some packages are not available for the latest release, so we may need to install a previous one.
In this tutorial, we install the version 3.6.1. of R.
Please note that if you are installing R on Mac, you may need to install XQuartz.
Some older computer may support the latest version of R. In that case, you can install the version 3.3.3.
Install R
Once the correct package for your platform is downloaded, the actual installation is a standard procedure on Windows and Mac. Double click on the installer and follow the instructions.
Install R on Ubuntu is particularly convenient using the command line. It is sufficient to type the following commands in the terminal.
sudo apt-get update
sudo apt-get install r-base
Use R
Once we installed R, we can already test its functionality. Going into the Applications or Program folder, we can already see it. By clicking the icon, we can run the R console, which is a basic interface. Even if it is basic, it already allows us to use all the R functions.
For example, we can already use the console as a calculator, however, this is just a small part of the R potential.
2+2
or
3*5
Even though we could run all our examples and script using the console, we will use different software, which is a complete graphic interface for R, called RStudio.
Install RStudio
Just like R, RStudio is freely available for users, even though, commercial versions for companies require a fee. At the link we can download the installer for Windows, Mac and some Linux distributions.
Once we download the installers, the automatic installation procedure should easily install the software in all the platforms.
Use RStudio
After the installation of RStudio, we can run it and we can see the initial page:
In the RStudio graphic interface, we can see three main windows. On the right, we can access the R console, which is the same we opened after the installation of R, on the left we have the windows with Environment and History and the one with Files, Plots, Packages, Help e Viewer.
After the installation, we can check if all the pre-installed packages are updated. To do this, we go to Tools
If there are updates available, let’s install them. Otherwise, RStudio should warn us that there is nothing to update.
Script
A script is a text file that contains (multiple) lines of code. It is the easiest way to save and execute more commands in RStudio.
We can open a new script in RStudio by selecting File|New File|R Script. In this way, RStudio opens a new window where we can edit and run our commands.
Now, let’s spend some time familiarizing with the studio interface and the commands in R!
Useful links
- Here we can find some notes on R, including many commands we will use during the course.
- Here we can find some notes on R (in Italian).
- At the link we can find some notes that contains many R commands divided by topic (in Italian).
© 2017-2019 Federico Reali


Coffee in my mug. Baby boy in my arms. Ruby on Rails on my computer. Wife and preschooler still asleep. Life is good.
5/21/2011, 9:53:59 AM
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Coffee in my mug. Baby boy in my arms. Ruby on Rails on my computer. Wife and preschooler still asleep. Life is good.
5/21/2011, 9:53:59 AM
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Stock Ticker Symbol:
Year: *If no year is inputted it defaults to the first year on record
Opening price
Closing price
Range High/Low
For a thorough description of the database see www.quandl.com/data/WIKI


NetFreak Platform is about shortest the path between normal citizen and media and & give great opportunity to person who want to develop their carrier into digital Media as a jounarlist.
Getting reports from local citizen and upload on the media main site is completely based on business model.
Citizen & media both will need to login with their aadhar and organization code respectively.
Platform is different from social media because require authentication from aadhar so accuracy of news report is more.
citizen/journalist report
A citizen upload only their visualized reports in their local area.
A single news may have many content by different users.So this filtering done through layered filtering based on their content.
Platform will provide the best title for interaction of the reports.
Reports will be taken by any media site for upload on their site.
Based the likes, views, content & feedback journalist will get populated.
Reports can also contain images, cartoons, cartoon videos, 3dimages.


This demo renders the Voronoi diagram for a moving set of points using a brute force technique.
Note: the C++ source code of this demo is available in the Native Client SDK (examples/demo/voronoi).
FPS: 0


Gecode::IntSet Class Reference
[Integer variables, Set variables]
Integer sets. More...
#include <int.hh>
Classes | |
| class | MinInc |
| Sort ranges according to increasing minimum. More... | |
Related Functions | |
(Note that these are not member functions.) | |
| template<class Char , class Traits > | |
| std::basic_ostream< Char, Traits > & | operator<< (std::basic_ostream< Char, Traits > &os, const IntSet &s) |
| Print integer set s. | |
Predefined value | |
|
| |
| static const IntSet | empty |
| Empty set. | |
Constructors and initialization | |
|
| |
| IntSet (void) | |
| Initialize as empty set. | |
| IntSet (int n, int m) | |
| Initialize as range with minimum n and maximum m. | |
| IntSet (const int r[], int n) | |
| Initialize with n integers from array r. | |
| IntSet (const int r[][2], int n) | |
| Initialize with n ranges from array r. | |
| template<class I > | |
| IntSet (I &i) | |
| Initialize with range iterator i. | |
| template<class I > | |
| IntSet (const I &i) | |
| Initialize with range iterator i. | |
Range access | |
|
| |
| int | ranges (void) const |
| Return number of ranges of the specification. | |
| int | min (int i) const |
| Return minimum of range at position i. | |
| int | max (int i) const |
| Return maximum of range at position i. | |
| unsigned int | width (int i) const |
| Return width of range at position i. | |
Entire set access | |
|
| |
| bool | in (int n) const |
| Return whether n is included in the set. | |
| unsigned int | size (void) const |
| Return size (cardinality) of set. | |
| unsigned int | width (void) const |
| Return width of set (distance between maximum and minimum). | |
| int | min (void) const |
| Return minimum of entire set. | |
| int | max (void) const |
| Return maximum of entire set. |
Detailed Description
Integer sets.
Integer sets are the means to specify arbitrary sets of integers to be used as domains for integer variables.
Definition at line 170 of file int.hh.
Constructor & Destructor Documentation
| Gecode::IntSet::IntSet | ( | void | ) | [inline] |
Initialize as empty set.
Definition at line 43 of file int-set-1.hpp.
| Gecode::IntSet::IntSet | ( | int | n, | |
| int | m | |||
| ) | [inline] |
Initialize as range with minimum n and maximum m.
Note that the set is empty if n is larger than m
Definition at line 106 of file int-set-1.hpp.
| Gecode::IntSet::IntSet | ( | const int | r[], | |
| int | n | |||
| ) | [inline] |
Initialize with n integers from array r.
Definition at line 101 of file int-set-1.hpp.
| Gecode::IntSet::IntSet | ( | const int | r[][2], | |
| int | n | |||
| ) | [inline] |
Initialize with n ranges from array r.
For position i in the array r, the minimum is r[i][0] and the maximum is r[i][1].
Definition at line 96 of file int-set-1.hpp.
| Gecode::IntSet::IntSet | ( | I & | i | ) | [inline, explicit] |
Initialize with range iterator i.
Initialize integer set with iterator.
Definition at line 85 of file int-set-1.hpp.
| Gecode::IntSet::IntSet | ( | const I & | i | ) | [inline, explicit] |
Initialize with range iterator i.
Initialize integer set with iterator.
Definition at line 91 of file int-set-1.hpp.
Member Function Documentation
| int Gecode::IntSet::ranges | ( | void | ) | const [inline] |
Return number of ranges of the specification.
Definition at line 130 of file int-set-1.hpp.
| int Gecode::IntSet::min | ( | int | i | ) | const [inline] |
Return minimum of range at position i.
Definition at line 111 of file int-set-1.hpp.
| int Gecode::IntSet::max | ( | int | i | ) | const [inline] |
Return maximum of range at position i.
Definition at line 117 of file int-set-1.hpp.
| unsigned int Gecode::IntSet::width | ( | int | i | ) | const [inline] |
Return width of range at position i.
Definition at line 123 of file int-set-1.hpp.
| bool Gecode::IntSet::in | ( | int | n | ) | const [inline] |
Return whether n is included in the set.
Definition at line 136 of file int-set-1.hpp.
| unsigned int Gecode::IntSet::size | ( | void | ) | const [inline] |
Return size (cardinality) of set.
Definition at line 157 of file int-set-1.hpp.
| unsigned int Gecode::IntSet::width | ( | void | ) | const [inline] |
Return width of set (distance between maximum and minimum).
Definition at line 163 of file int-set-1.hpp.
| int Gecode::IntSet::min | ( | void | ) | const [inline] |
Return minimum of entire set.
Definition at line 145 of file int-set-1.hpp.
| int Gecode::IntSet::max | ( | void | ) | const [inline] |
Return maximum of entire set.
Definition at line 151 of file int-set-1.hpp.
Friends And Related Function Documentation
| std::basic_ostream< Char, Traits > & operator<< | ( | std::basic_ostream< Char, Traits > & | os, | |
| const IntSet & | s | |||
| ) | [related] |
Print integer set s.
Definition at line 232 of file int-set-1.hpp.
Member Data Documentation
const IntSet Gecode::IntSet::empty [static] |
The documentation for this class was generated from the following files:
- gecode/int.hh
- gecode/int/int-set-1.hpp
- gecode/int/int-set.cpp


Who are we, and what do we do? We are Iotop (=iotop) a team of 3 and we are currently working on a solution to a problem related to plants. The problem with plants is that most people don't know how to take care of them. There are already solutions available, but they have a big problem: UX. They connect via Bluetooth to sensors which adds a barrier between users and their plants.
We want to solve this problem by connecting the sensor to the wifi so it sends data all the time and the user can retrieve it with a mobile app all the time, even when not at home, so that they can take care of their plants.
This is just a rough overview of the project but stay tuned for more information and check out our blog. Also, you can subscribe to our newsletter to don't miss out on any blog post we make. Have fun reading and if you have any questions, don't hesitate to write us an e-mail. 🌱


{% extends "layout.html" %} {% block content %}
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Soccer
问题描述 :
For each game played, a team wins if it scores more goals than its opponent. A team loses a game if it scores fewer goals. When both teams score the same number of goals, we call it a draw. A team earns 3 points for each win, 1 point for each draw and 0 point for each loss. Teams are ranked according to the number of points earned (more points result in a higher ranking). Teams that are tied are given the same rank. For example, if two teams are tied and have the next highest point total after the 3rd place team, then they are both ranked 4th (and the next team is ranked 6th). In real life, factors such as goal differences and goals scored are used to break ties, but we will not consider these for this problem.
You are given a list of soccer teams and a list of matches in a season. You may assume that every team will play the same number of games at the end. Some of the matches have been played and the results are known.
输入:
team1 vs team2: x y
with team1 and team2 being the names of two different teams, and x and y are non-negative integers (or both are -1), indicating that in the game between team1 and team2, team1 scores x goals and team2 scores y goals. If both x and y are -1, then the game has not yet been played. At most 12 games will not have been played yet.
The input is terminated with n = m = 0.
输出:
team1 vs team2: x y
with team1 and team2 being the names of two different teams, and x and y are non-negative integers (or both are -1), indicating that in the game between team1 and team2, team1 scores x goals and team2 scores y goals. If both x and y are -1, then the game has not yet been played. At most 12 games will not have been played yet.
The input is terminated with n = m = 0.
样例输入:
4 6 ManUnited Arsenal Chelsea Tottenham ManUnited vs Arsenal: 3 1 Chelsea vs Arsenal: 2 2 ManUnited vs Chelsea: 1 0 Tottenham vs ManUnited: -1 -1 Tottenham vs Chelsea: 0 4 Tottenham vs Arsenal: -1 -1 0 0
样例输出:
Team ManUnited can finish as high as 1st place and as low as 1st place. Team Arsenal can finish as high as 2nd place and as low as 4th place. Team Chelsea can finish as high as 2nd place and as low as 3rd place. Team Tottenham can finish as high as 1st place and as low as 4th place.
简单的dfs 但繁琐的可以了 0.0
#include<cstdio> #include<cstring> #include<algorithm> using std::sort; int n,m,cnt=0; struct team { char s[50]; int low,up,d,f; }; team a[30]; struct match { int x,y,re; bool operator < (const match &p) const { return re < p.re; } }; match b[2000]; int find(char *s) { for(int i = 0; i < n; i++) if(strcmp(a[i].s, s) == 0) return i; return -1; } void cc(int w) { for(int i = 0; i < n; i++) a[i].f = a[i].d; for(int i = 0; i < w; i++) if(b[i].re == 1) { a[b[i].x].f += 1; a[b[i].y].f += 1; } else if(b[i].re == 2) a[b[i].x].f += 3; else a[b[i].y].f += 3; for(int i = 0; i < n; i++) { int rank=1; for(int j = 0; j < n; j++) { if(j != i && a[j].f > a[i].f) rank++; } if(rank > a[i].low) a[i].low = rank; if(rank < a[i].up) a[i].up = rank; } } void dfs(int cur,int w) { if(cur == w) cc(w); else { for(int i = 1; i <= 3; i++) { b[cur].re = i; dfs(cur+1, w); } b[cur].re = 0; } } void show(int a) { if(a == 1) printf("1st "); else if(a == 2) printf("2nd "); else if(a == 3) printf("3rd "); else printf("%dth ", a); } void show(team a) { printf("Team %s can finish as high as ",a.s); show(a.up); printf("place and as low as "); show(a.low); printf("place.\n"); } int main() { while(scanf("%d%d",&n,&m) && m+n) { if(cnt++) printf("\n"); int p,q; char u[100],v[100]; for(int i = 0; i < n; i++) { scanf("%s",a[i].s); a[i].d = a[i].low = 0, a[i].up = 50; } for(int i = 0; i < m; i++) { scanf("%s vs %s%d%d",u,v,&p,&q); v[strlen(v)-1] = '\0'; b[i].x = find(u); b[i].y = find(v); int &re = b[i].re; if(p==-1 && q==-1) re = 0; else if(p == q) re = 1; else if(p > q) re = 2; else re = 3; } sort(b, b+m); int j = 0; for(j = 0; j < m; j++) if(b[j].re != 0) break; for(int i = j; i < m; i++) if(b[i].re == 1) { a[b[i].x].d += 1; a[b[i].y].d += 1; } else if(b[i].re == 2) a[b[i].x].d += 3; else a[b[i].y].d += 3; dfs(0, j); for(int i = 0; i < n; i++) show(a[i]); } return 0; }
版权声明：本文为博主原创文章，未经博主允许不得转载。
参考：http://blog.csdn.net/xlc2845321/article/details/9935503
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
你要是柯震东的粉丝 知道了他吸毒你会怎么做 封杀他 可笑
不同的编译器，printf(),执行的顺序不同，所以结果也就不同，建议不要那么写
很好的模板
上面的评论很起劲，为什么我看不懂啊
welcome!
多谢提醒
红绯鱼：
牛逼牛逼
递归还真是一门学问，学习了
学算法中的数据结构学到一定程度会乐此不疲的，比如其中的2－3树，类似的红黑树，我甚至可以自己写个逻辑文件系统结构来。
感觉这里的评分标准没啥作用阿，反而显得显得赘余，还不如直接去掉好了。
正解，应该是200！
Good task for the group. Hold it up for every yeara??s winner. This is a excellent oppotunity for a lot more enhancement. Indeed, obtaining far better and much better is constantly the crucial. Just like my pal suggests on the truth about ab muscles, he just keeps obtaining much better.
很好的方法，学习了


Package org.apache.nutch.plugin
The Nutch
Plugin
System.
The Nutch Plugin System provides a way to extend nutch functionality. A large part of the functionality of Nutch are provided by plugins: All of the parsing, indexing and searching that nutch does is actually accomplished by various plugins.
In writing a plugin, you're actually providing one or more extensions
of the existing extension-points (hooks). The core Nutch extension-points
are themselves defined in a plugin, the nutch-extensionpoints
plugin.
Each extension-point defines an interface that must be implemented by the
extension. The core extension-points and extensions available in Nutch are
listed in the Pluggable
interface.
-
Interface Summary Interface Description Pluggable Defines the capability of a class to be plugged into Nutch. -
Class Summary Class Description Extension AnExtension
is a kind of listener descriptor that will be installed on a concreteExtensionPoint
that acts as kind of Publisher.ExtensionPoint TheExtensionPoint
provide meta information of a extension point.Plugin A nutch-plugin is an container for a set of custom logic that provide extensions to the nutch core functionality or another plugin that provides an API for extending.PluginClassLoader ThePluginClassLoader
is a child-first classloader that only contains classes of the runtime libraries setuped in the plugin manifest file and exported libraries of plugins that are required plugins.PluginDescriptor ThePluginDescriptor
provide access to all meta information of a nutch-plugin, as well to the internationalizable resources and the plugin own classloader.PluginManifestParser ThePluginManifestParser
provides a mechanism for parsing Nutch plugin manifest files (plugin.xml
) contained in aString
of plugin directories.PluginRepository The plugin repository is a registry of all plugins.URLStreamHandlerFactory This URLStreamHandlerFactory knows about all the plugins in use and thus can create the correct URLStreamHandler even if it comes from a plugin classpath. -
Exception Summary Exception Description CircularDependencyException CircularDependencyException
will be thrown if a circular dependency is detected.MissingDependencyException MissingDependencyException
will be thrown if a plugin dependency cannot be found.PluginRuntimeException PluginRuntimeException
will be thrown until a exception in the plugin managemnt occurs.


|
NeuralSharp
1.0
NeuralSharp is a FOSS C# library for neural networks.
|
Represents a random convolution. More...
Inherits NeuralSharp.Convolutional.IImagesLayer.
Public Member Functions | |
| RandomConvolution (int inputDepth, int inputWidth, int inputHeight, int depth, int kernelSide, int stride, bool padding, bool createIO=false) | |
| Creates an instance of the More... | |
| void | Feed (bool learning=false) |
| Feeds the layer forward. More... | |
| void | BackPropagate (Image outputError, Image inputError, bool learning) |
| Backpropagates the error trough the layer. More... | |
| void | UpdateWeights (float rate, float momentum=0.0F) |
| Updates the weights of the layer. Does nothing. More... | |
| void | SetInputAndOutput (Image input, Image output) |
| Sets the input image and the output image of the layer. More... | |
| Image | SetInputGetOutput (Image input) |
| Sets the input image of the layer and creates and sets the output image. More... | |
| virtual ILayer< Image, Image > | CreateSiamese () |
| Creates a siamese of the layer. More... | |
| virtual ILayer< Image, Image > | Clone () |
| Creates a clone of the layer. More... | |
| int | CountParameters (List< object > siameseIDs) |
| Computes the amount of parameters of the layer. More... | |
| Public Member Functions inherited from NeuralSharp.ILayer< Image, Image > | |
| int | CountParameters (List< object > siameseIDs) |
| Counts the amount of parameters of the layer. More... | |
| void | Feed (bool learning=false) |
| Feeds the layer forward. More... | |
| void | UpdateWeights (float rate, float momentum=0.0F) |
| Updates the weights of the layer. More... | |
| void | BackPropagate (TOut outputError, TIn inputError, bool learning) |
| Backpropagates the given error trough the layer. More... | |
| void | SetInputAndOutput (TIn input, TOut output) |
| Sets the input object and the output object of the layer. More... | |
| TOut | SetInputGetOutput (TIn input) |
| Sets the input object of the layer and creates and sets the output object. More... | |
| ILayer< TIn, TOut > | CreateSiamese () |
| Creates a siamese of the layer. More... | |
| ILayer< TIn, TOut > | Clone () |
| Clones the layer. More... | |
Protected Member Functions | |
| RandomConvolution (RandomConvolution original, bool siamese) | |
| Either creates a siamese of the given More... | |
| float | ActivationFunction (float input) |
| The activation function. More... | |
| float | ActivationDerivative (float output) |
| The activation function derivative. More... | |
Properties | |
| Image | Input [get] |
| The input image. More... | |
| Image | Output [get] |
| The output image. More... | |
| int | InputDepth [get] |
| The depht of the input of the layer. More... | |
| int | InputWidth [get] |
| The width of the input of the layer. More... | |
| int | InputHeight [get] |
| The height of the input of the layer. More... | |
| int | OutputDepth [get] |
| The depth of the output of the layer. More... | |
| int | OutputWidth [get] |
| The width of the output of the layer. More... | |
| int | OutputHeight [get] |
| The height of the output of the layer. More... | |
| int | KernelSide [get] |
| The kernel side. More... | |
| int | Stride [get] |
| The stride. More... | |
| int | Parameters [get] |
| The parameters. More... | |
| object | SiameseID [get] |
| The siamese identifier of the layer. More... | |
| Properties inherited from NeuralSharp.Convolutional.IImagesLayer | |
| int | InputDepth [get] |
| The depth of the input of the layer. More... | |
| int | InputWidth [get] |
| The width of the input of the layer. More... | |
| int | InputHeight [get] |
| The height of the input of the layer. More... | |
| int | OutputDepth [get] |
| The depth of the output of the layer. More... | |
| int | OutputWidth [get] |
| The width of the output of the layer. More... | |
| int | OutputHeight [get] |
| The height of the output of the layer. More... | |
| Properties inherited from NeuralSharp.ILayer< Image, Image > | |
| TIn | Input [get] |
| The input object of the layer. More... | |
| TOut | Output [get] |
| The output object. More... | |
| int | Parameters [get] |
| The amount of parameters of the layer. More... | |
| object | SiameseID [get] |
| The siamese identifier of the layer. More... | |
Represents a random convolution.
|
protected |
Either creates a siamese of the given
RandomConvolution
instance or clones it.
| original | The original instance to be created a siamese of or cloned. |
| siamese | true false |
| NeuralSharp.Convolutional.RandomConvolution.RandomConvolution | ( | int | inputDepth, |
| int | inputWidth, | ||
| int | inputHeight, | ||
| int | depth, | ||
| int | kernelSide, | ||
| int | stride, | ||
| bool | padding, | ||
| bool | createIO = false |
||
| ) |
Creates an instance of the
RandomConvolution
class.
| inputDepth | The input depth. |
| inputWidth | The input width. |
| inputHeight | The input height. |
| depth | The output depth. |
| kernelSide | The kernel side. |
| stride | The stride. |
| padding | Whether padding is to be used. |
| createIO | Whether the input image and the output image of the layer are to be created. |
|
protected |
The activation function derivative.
| output | The output of the activation function. |
|
protected |
The activation function.
| input | The input. |
| void NeuralSharp.Convolutional.RandomConvolution.BackPropagate | ( | Image | outputError, |
| Image | inputError, | ||
| bool | learning | ||
| ) |
Backpropagates the error trough the layer.
| outputError | The output error to be backpropagated. |
| inputError | The image to be written the input error into. |
| learning | Whether the layer is being used in a training session. |
Creates a clone of the layer.
| int NeuralSharp.Convolutional.RandomConvolution.CountParameters | ( | List< object > | siameseIDs | ) |
Computes the amount of parameters of the layer.
| siameseIDs | The siamese identifiers to be excluded. |
Creates a siamese of the layer.
| void NeuralSharp.Convolutional.RandomConvolution.Feed | ( | bool | learning = false | ) |
Feeds the layer forward.
| learning | Whether the layer is being used during a training session. |
Sets the input image and the output image of the layer.
| input | The input image. |
| output | The output image to be set. |
Sets the input image of the layer and creates and sets the output image.
| input | The input image. |
| void NeuralSharp.Convolutional.RandomConvolution.UpdateWeights | ( | float | rate, |
| float | momentum = 0.0F |
||
| ) |
Updates the weights of the layer. Does nothing.
| rate | The learning rate to be used. |
| momentum | The momentum to be used. |
|
get |
The input image.
|
get |
The depht of the input of the layer.
|
get |
The height of the input of the layer.
|
get |
The width of the input of the layer.
|
get |
The kernel side.
|
get |
The output image.
|
get |
The depth of the output of the layer.
|
get |
The height of the output of the layer.
|
get |
The width of the output of the layer.
|
get |
The parameters.
|
get |
The siamese identifier of the layer.
|
get |
The stride.


Hernan's Silent H Hangman Game
Each answer has a silent "H" somewhere in the word. Just like Hernan!
Guess The Word!
(click or type a letter)
img
Letters Guessed
Letter Buttons


G.I. JANE (Hollywood) Starring: Demi Moore, Viggo Mortensen, Anne Bancroft. Screenplay: Danielle Alexandra and David Twohy. Producers: Ridley Scott, Demi Moore, Roger Birnbaum and Suzanne Todd. Director: Ridley Scott. MPAA Rating: R (profanity, adult themes, violence) Running Time: 125 minutes. Reviewed by Scott Renshaw.
 After all, here's the film-maker behind THELMA & LOUISE directing the story of a female naval lieutenant named Jordan O'Neil (Demi Moore) who tries to break into the heretofore all-male Navy SEALs. Imagine their chagrin when they realize that Ridley Scott has pulled a fast one on them. G.I. JANE is actually a gruntin', sweatin', shootin' and fightin' guy movie with a message as politically incorrect as they come.  This is the story of a woman who succeeds in a male dominated environment by turning into a man.
No, I'm not referring to Ms. Moore's much-publicized shaven pate, nor to the cigar-smoking, take-no-b.s. real-life persona she brings to every one of her projects. Such masculinisms may not hurt G.I. JANE's he-man quotient, but they don't define it either. The pivotal transgender moment occurs two-thirds of the way through the film, as Lt. O'Neil nears the end of her SEAL training. During a war game exercise, O'Neil's team is captured and subjected to P.O.W. treatment. That treatment includes an extended sequence during which the Master Chief (Viggo Mortensen) physically and psychologically abuses O'Neil, and in fact prepares to rape her. Just when we think O'Neil is beaten, she rouses herself and -- ahem -- suggests that the Master Chief "suck my [anatomical feature usually associated with the male of the species]." Suddenly, with the rousing cheers of her comrades ringing in her ears, she is an outsider no longer. She is one of the boys, metaphorical genitalia and all, ready to trade whisky shots and lusty cries of "Hoo-yah."
It's the perfect climax to a film which continues the morphing of Ridley Scott and his brother Tony into a single two-headed film-making organism dedicated to celebrating manly men at their manliest. Ridley once had a sense of style, something Tony could never claim, but that style has all but vanished in recent duds like 1492: CONQUEST OF PARADISE and WHITE SQUALL. In G.I. JANE, Ridley spends most of the film pointing his camera at men (and Moore) straining their way through the rigors of SEAL boot camp while drill instructors shout insults at them. It's a tired device in movies about soldiers -- after FULL METAL JACKET, the initiation ritual has been done as well as anyone is ever going to do it -- which runs on and on until you may be ready yourself to ring the bell which allows the recruits to bail out. G.I. JANE is a one-note film just waiting for the inevitable moment when Lt. O'Neil makes her profane statement that the best woman for the job is a man.
I noted that that scene is the perfect climax for G.I. JANE, but in truth it only _should have been_ the climax. The film actually rambles on for another half-hour, allowing O'Neil to butt heads with a duplicitous senator (Anne Bancroft, in a wonderfully oily performance full of matter-of-fact sleaze) before butting heads with Libyan soldiers in her first real mission. That mission is necessary, of course, as a real test of O'Neil's mettle, so that she can earn the much-desired respect of the Master Chief who beat her insensible and sexually assaulted her. Sure Jordan O'Neil makes it through the program. It's the way she makes it through which could have plenty of viewers cringing. When G.I. JANE isn't monotonous or ridiculous (turning O'Neil's personal training into an excuse for sweaty T&A close-ups), it's just plain insulting. There's no danger or eroticism to the scene where the Master Chief interrupts O'Neil while she's taking a shower. After all, she doesn't have anything he hasn't seen before in the men's shower. Hoo-yah.
On the Renshaw scale of 0 to 10 SEALs of disapproval: 3.
Visit Scott Renshaw's MoviePage http://www.inconnect.com/~renshaw/ *** Subscribe to receive new reviews directly by email! See the MoviePage for details, or reply to this message with subject line "Subscribe".
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
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belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
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Related links: index of all rec.arts.movies.reviews reviews


Nature, Poem 28: Autumn
by Emily Dickinson
from The Poems of Emily Dickinson: Series One
The Morns are meeker than they were
To poets, autumn often symbolizes change, maturity, wisdom, or the harvest. Explore many interpretations of Autumn in this collection of poetry by Emily Brontë, Emily Dickinson, Paul Lawrence Dunbar, Ellen Robena Field, Henry Wadsworth Longfellow, Edgar Allan Poe, William Shakespeare, Robert Louis Stevenson, and Richard Henry Wilde.
The Morns are meeker than they were
"When the bees are humming in the honeysuckle vine"
"Oh, wind of the spring–time, oh, free wind of May,"
Besides the autumn poets sing
Going to heaven!
The author contemplates the cyclical and temporary nature of life.
The poet muses on fires.
The travels of a tattered and worn songbook
Words of sympathy are offered.
In these rapid, restless shadows, Once I walked at eventide,
To me fair friend you never can be old
How like a winter hath my absence been
A poem describing “The Fall of the Year” or Autumn.
"From childhood's hour I have not been"
A poem centered around Autumn and nature.
"The November sun invites me,"
"You bid me hold my peace"
"On a summer’s day as I sat by a stream,"
"It’s all a farce,—these tales they tell"
"Underneath the autumn sky,"
"The wind told the little leaves to hurry,"
A poem admiring the beauty, differences, and changes in seasonal weather.


{% extends "base.html" %} {% block content %} Deleting your content Currently destroying all your public content made before {{ job.started }}. Starting the process Waiting for final confirmation Validating that we got good data Deleting Comments 0 Deleting Submissions 0 Process completed Take me to the homepage! {% endblock %} {% block js %} {{ block.super }} {% endblock %}
Currently destroying all your public content made before {{ job.started }}.


Provides the URL class which encapsulates information about a database connection specification.
The URL object is created automatically when create_engine() is called with a string argument; alternatively, the URL is a public-facing construct which can be used directly and is also accepted directly by create_engine().
Represent the components of a URL used to connect to a database.
This object is suitable to be passed directly to a create_engine() call. The fields of the URL are parsed from a string by the module-level make_url() function. the string format of the URL is an RFC-1738-style string.
Attributes on URL include:
Construct a new URL.
Return the SQLAlchemy database dialect class corresponding to this URL's driver name.
Translate url attributes into a dictionary of connection arguments.
Returns attributes of this url (host, database, username, password, port) as a plain dictionary. The attribute names are used as the keys by default. Unset or false attributes are omitted from the final dictionary.
Optional, alternate key names for url attributes:
# return 'username' as 'user' username='user' # omit 'database' database=None


- ASP.NET MVC
- Essential Grid
- Essential Schedule
- Essential Tools
- Essential Chart
- Essential Diagram
- Silverlight
- Essential Tools
- Essential Gauge
- Essential Chart
- Essential Grid
- WPF
- Essential Grid
- Essential Schedule
- Essential Tools
- Essential Chart
- Essential Diagram


Source directory
Browse
Destination directory
Browse
Load!
A - YES, copy that image
L - NO, skip that image


--- layout: post title: "Kindle Singles" external-url: http://www.amazon.com/b?ie=UTF8&node=2486013011 ---
As a relatively new Kindle user and lover and a big fan of essay style writing I couldn’t be more excited about this.


Welcome to my Github website !
Last update on : GMT
These images are from a program running on a server
that automatically checks the most used words on Twitter.
It's created by myself.
You can check the Python code of these images on the pzim-devdata GitHub page !
Feel free to
contact
me !
<<<<<<< HEAD
On the Thursday 01 Jul 2021, the value of the CAC40 is 6546.6201171875 points at 11h23 GMT +1.
The CAC40 increased by +80.25% from its lowest point on Monday 16 Mar 2020.
The CAC40 has varied by -2.15% since its highest point in the last 5 years from Friday 18 Jun 2021.
Since the year 2000, the value of the CAC40 has dropped to 2401.14990234375 points on Wednesday 12 Mar 2003.
Over the past 15 years, the value of the CAC40 has fallen to 2465.4599609375 points on Monday 09 Mar 2009.
Over the past 10 years, the value of the CAC40 has fallen to 2693.2099609375 points on Friday 23 Sep 2011.
In the past 5 years, the value of the CAC40 has fallen to 3632.06005859375 points on Monday 16 Mar 2020.
=======
On the Friday 09 Jul 2021, the value of the CAC40 is 6501.68994140625 points at 15h20 GMT +1.
The CAC40 increased by +79.01% from its lowest point on Monday 16 Mar 2020.
The CAC40 has varied by -2.85% since its highest point in the last 5 years from Friday 18 Jun 2021.
Since the year 2000, the value of the CAC40 has dropped to 2401.14990234375 points on Wednesday 12 Mar 2003.
Over the past 15 years, the value of the CAC40 has fallen to 2465.4599609375 points on Monday 09 Mar 2009.
Over the past 10 years, the value of the CAC40 has fallen to 2693.2099609375 points on Friday 23 Sep 2011.
In the past 5 years, the value of the CAC40 has fallen to 3632.06005859375 points on Monday 16 Mar 2020.
>>>>>>> bbb29ffadb4a69ff0e15b47a116f47de65c2c556
This text comes from a program running on a
server which automatically checks the CAC40 share price.
It was created by myself.
You can check the Python code of this self-generated text on the GitHub page of pzim-devdata !
Feel free to
contact
me !
MIT licence
Copyright (c) 2020 pzim-devdata


CCB developer_test_server - Egleston
Some simple links to demonstrate server
All Films
First 20 Films (default order)
Next 20 Films (default order)
First 20 Films (ordered by length)
Films with 'the' in title
Films rated 'PG'
Films that are a 'Comedy'
Films with 'the' in title rated 'PG'
Films 'the' in title that are a 'Comedy'
Information about film #223
Information about film #997
Toggle
pretty-print of JSON
Some error conditions
Information about film #123456


--- layout: post status: publish published: true title: Dead Hard Drive author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 580 wordpress_url: http://winterdom.com/2003/12/deadharddrive date: '2003-12-21 18:07:12 +0000' date_gmt: '2003-12-21 18:07:12 +0000' categories: - Personal tags: [] comments: [] ---
Around tuesday last week, my laptop's 20 gig harddrive started making really ugly noises (thumping really hard). I'd have the feeling it would be dead soon for a while, because of a few errors I'd spotted on the event log, so it came as no surprise. It was rather sad, though.
Anyway, I decided not too wait until it was fully dead, so I immediately backed up important files (yet again), and then went on and bought a new drive. I ended up getting a new 40 gig drive, so it was all not that bad, as I can use the extra space, but boy, these 2.5 inched drives are expensive!
Since I'm really lazy, and I had all kind of things installed, I decided to try something before replacing the original drive: imaging it. For that, I decided to use Ghost4Unix, which allows you to upload a compressed image of the entire drive unto an FTP server, and later download to the drive again. I'm happy to say it worked nicely, and Windows Server 2003 booted right away from the new drive as if nothing had changed. Simply added a new 18 gig partition, and I was set to go.
Needless to say, uploading and downloading the images can take quite a few hours, given the size...


| 002:028 Khan | : |
How can you disbelieve in Allah?      Then you will return to His Presence. |
| 002:028 Shakir | : |
How do you deny Allah and you were dead and He gave you life?  You were without life and HE gave you life, and then HE will cause you to die, then restore you to life, and then to HIM shall you be made to return. |
| 002:028 Yusufali | : |
How can ye reject the faith in Allah?- seeing that ye were without life, and He gave you life; then will He cause you to die, and will again bring you to life; and again to Him will ye return. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > إليه ترجع الأمور Pillars of Islam> Islamic> Oneness of Allah>All Matters Return to Him(for decision) أركان الإسلام > التوحيد > توحيد الله تعالي > وجوده Pillars of Islam> Islamic> Oneness of Allah> His Existence أركان الإسلام > التوحيد > توحيد الله تعالي > وحدانيته Pillars of Islam> Islamic> Oneness of Allah> Singularity and Being Unique أركان الإسلام > التوحيد > توحيد الله تعالي > يحيي ويميت Pillars of Islam> Islamic> Oneness of Allah> Gives Life and Death الإيمان > اليوم الآخر > البعث Faith> The Hereafter> The Resurrection الإنسان والعلاقات الاجتماعية > الإنسان > شرفه ودنوه Man and The Social Relations>Man>When Honourable and When Unhonourable الإنسان والعلاقات الاجتماعية > الرجل والمرأة Man and The Social Relations>Man and Woman العلوم والفنون > الحقائق العلمية و الإشاة إلى وقائع أيدتهاالإكتشافات العلمية > الإنسان وخلقه Science and Art> The Scientific Facts and the Indication to Facts which have been supported by the Scientific Discoveries>Man and his Creation العلوم والفنون > الحقائق العلمية و الإشاة إلى وقائع أيدتهاالإكتشافات العلمية > سرعة النور Science and Art> The Scientific Facts and the Indication to Facts which have been supported by the Scientific Discoveries>Light Speed
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


autotext
autotext()
Generates random text from an XML-document. Autotext is a very powerful feature once you learn how to use it. NodeBox has a built-in implementation of the Kant Generator Pro. XML-files for the Kant Generator have a specified structure. Further information can be found at http://diveintopython.org/xml_processing/
|
txt = autotext("kant.xml")
text(txt, 10, 10, width=100) |
a string containing automatically generated text


Liquid drops and prevention of coalescence
Star
github.com/cselab/aphros
|
wasm
This simulation needs JavaScript
[space] pause, [click] draw a drop
coalescence
gravity
surface tension
viscosity
demos:
electrochemistry
|
explorer
videos:
waves
|
waterfall
|
coalescence


I am not sure which patch of BBlog broke this feature, but now when I enter in a filter name that is the same as an existing one, it creates a new filter with that name instead of overwriting the pre-existing one.
I have sort of been avoiding the filtersets feature since this started happening. Hope it will be fixed!
BrainFooLong
Administrator
It was never as you mention.
You can add 100 entries with the same name.
Replacing was never integrated. You need to add a new and remove the old.
ORFK
Global Moderator
but i remember me too that if i saved a setting with an existing name it has overwritten the old one.
and i'm 100% sure that it was like this :-/
BrainFooLong
Administrator
Maybe this was a "bug" before 3.0 that only one entry of a unique name was shown.
And than it was pure luck that the newest entry was that one that was displayed.
Since 3.0 there no changes at this feature.
Delete the old entry, it's not a big deal i guess. Replacing function need some more coding and is not i high prio task for me at the moment.
ORFK
Global Moderator
alright, thx for answer.
but i think it was a good bug =)
Post edited 1 x times, last by
BrainFooLong
Administrator
BrainFooLong
Administrator
ORFK wrote:
alright, thx for answer.
but i think it was a good bug =)
As the "platoon image upload bug" on battlelog :-)
Topicstarter
KKoNcept
Sorry to break taboo and to correct an admin =/
But this feature wasn't a bug since when clicking save for a filterset it literally states "Enter a name for your set. If set exists, it would be overriden."
 Is that right?
If the developer don't know what he has developed, some vacation should be good :-)
But, fact is, that it's actually not integrated and a workaround exist (delete and add)


Total cases confirmed, recovered, and deaths
The data we are using for this visualization has already been aggregated to indicate the total counts per day.
- check_circleA single RDS API query
- check_circleNo more parsing various data files
- check_circleNo need to keep up with the data each time it changes
- check_circleSwitching charting libraries is as simple as changing one paramter
Try a different charting library, it's easy!
Chart Type
RDS Explorer
Use our powerful and feature-packed interface to easily view, search, and examine data. Filter, package, and download custom sub-views in popular data formats.
RDS Tabulation Engine
Create custom cross tabulations with the RDS Tabulation Engine. Filter, weight, and organize the table how you want in our easy-to-use interface.


% include('base.html', title="Add Contest")
| List Of Questions |
|---|
| Question | Question Statement | Author | Time submitted | Selection |
| Download Question | {{question["question_statement"]}} | {{question["username"]}} | {{question["created_date_time"].strftime("%d-%m-%Y %H:%M")}} |


<?php /* * This file is part of the Symfony package. * * (c) Fabien Potencier<EMAIL_ADDRESS>* * For the full copyright and license information, please view the LICENSE * file that was distributed with this source code. */
namespace Symfony\Component\Console\Tester; use Symfony\Component\Console\Application; use Symfony\Component\Console\Input\ArrayInput;
/** * Eases the testing of console applications. * * When testing an application, don't forget to disable the auto exit flag: * * $application = new Application(); * $application->setAutoExit(false); * * @author Fabien Potencier<EMAIL_ADDRESS>*/ class ApplicationTester { use TesterTrait; private $application; private $input; private $statusCode; public function __construct(Application $application) { $this->application = $application; } /** * Executes the application. * * Available options: * * * interactive: Sets the input interactive flag * * decorated: Sets the output decorated flag * * verbosity: Sets the output verbosity flag * * capture_stderr_separately: Make output of stdOut and stdErr separately available * * @return int The command exit code */ public function run(array $input, array $options = []) { $this->input = new ArrayInput($input); if (isset($options['interactive'])) { $this->input->setInteractive($options['interactive']); } if ($this->inputs) { $this->input->setStream(self::createStream($this->inputs)); } $this->initOutput($options); return $this->statusCode = $this->application->run($this->input, $this->output); } }


4 April 2003
Disease Outbreak Reported
Data just received from the Chinese Ministry of Health have changed the cumulative number of reported cases posted earlier today at the WHO SARS web site.
The new data have been submitted as the start of daily electronic reports of cases and deaths nationwide, broken down by Province. Data submitted today report cases for 1 and 2 April and show an increase of 30 cases, with 3 deaths, when compared with the previous cumulative total for 31 March.
For 1 April, 10 cases, with 1 death, occurred in Guangdong Province, and 7 cases and no deaths were reported in Shanxi Province. For 2 April, 10 cases, with 1 death were reported in Guangdong Province, 2 cases and no deaths in Shanxi Province, and 1 case and 1 death in Hunan Province.
The new data increase the cumulative number of cases in China, up to 2 April, from 1190 to 1220 cases, and from 46 to 49 deaths.
Today’s table showing cumulative cases and deaths for all countries reporting suspected cases is being updated to reflect the new figures.
Update on cases and countries
As of today and including the new data from China, a cumulative total of 2353 SARS cases and 84 deaths have been reported from 16 countries. This represents an increase of 83 cases and 5 deaths compared with yesterday. The deaths occurred in Canada (1), China (3), and Singapore (1).
New cases were reported in Canada (7), China (30), Hong Kong SAR (27), Taiwan, China (1), Singapore (2), and the United States of America (15).
Situation in Hong Kong SAR
The Department of Health has reported that 27 additional patients with symptoms of atypical pneumonia were admitted to public hospitals today. The new patients include five health care workers and eight residents of the Amoy Gardens housing estate. The remaining 14 were new patients and contacts of patients with atypical pneumonia.
Of the 26 new patients reported yesterday, two were health care workers, two were residents of Amoy Gardens, and 22 were new patients and contacts of patients with atypical pneumonia.
Health authorities are current investigating sewage samples at a construction site adjacent to Block E apartment building in Amoy Gardens, which has been the source of a large cluster of new SARS cases. New cases have been associated with vertically linked apartments.
A second line of investigation is concentrating on a burst sewage pipe in block E that may have epidemiological links with a visitor to Amoy Gardens which was subsequently admitted to Hong Kong’s Prince of Wales Hospital in early March and was said to have been symptomatic at the time of his visit.


V CREDIT SYSTEM
Student Login
Please enter your email and password
Forgot password?
Login
"A-Block Payments"
Fees, I-card refill, Student Chapter payments
"V-Lounge"
CCD, Breakfast, Lunch
"Stationary"
Black file, Drawing sheets, photocopy
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Example FlexBox CSS3
Example of FlexBox CSS3 framework applications.
-
Flex Direction in row
-
Flex Direction in column
-
Flex Direction in row reverse
-
Flex Direction in column reverse
-
Flex Row no Wrap (no break)
-
Flex Row Wrap (break)
-
Flex Row Wrap Reverse (break)
-
Flex Row Justify Content Start
-
Flex Row Justify Content End (Top - Right)
-
Flex Row Justify Content Space Around
-
Flex Row Justify Content Space Between
-
Flex Row Content Vertical Align Items - Flex Start
-
Flex Row Content Vertical Align Items - Flex End
-
Flex Row Content Vertical Align Items - Center
-
Flex Row Content Vertical Align Items - Strech (Same height)
-
Flex Row Content Vertical Align Items - Baseline (Content-based alignment)
-
Flex Items Order
-
Flex Items (Grow, Shrinks, Basis)
Useful links
Flex Direction in row
Flex Direction in column
Flex Direction in row reverse
Flex Direction in column reverse
Flex Row no Wrap (no break) - width 500px
Flex Row Wrap (break) - width 500px
Flex Row Wrap Reverse (break) - width 500px
Flex Row Justify Content Start (Top - Left)
Flex Row Justify Content End (Top - Right)
Flex Row Justify Content Space Around
Distributed based on the width of the first element.
Flex Row Justify Content Space Between
Distributes starting from the center to the ends.
Flex Row Content Vertical Align Items - Flex Start
Flex Row Content Vertical Align Items - Flex End
Flex Row Content Vertical Align Items - Center
Flex Row Content Vertical Align Items - Strech (Same height)
Flex Row Content Vertical Align Items - Baseline (Content-based alignment)
Flex Items Order
Flex Items (Grow, Shrinks, Basis)
01 - Grow
02 - Basis with 65px
03 - Basis with 65px
04 - Basis with 65px


{% extends "guides/base.html" %} {% from "guides/repo.html" import render_repo with context %} {% block title %}Searching Data{% endblock %} {% block subtitle %}Learn how to find new repo on GitHub.{% endblock %} {% block container %}
You can search for data with the GitHub API using the services/github.py
module. This makes it easier to make the authenticated request. We are making a request to the /search/repositories
endpoint.
A GET request to this endpoint using the github.py
module looks like:
github = GitHub(access_token=session['access_token'])
results = github.get('/search/repositories')
As a result, you will see your starred repositories below:
You can use the search bar above to find new projects.
{% else %}Cannot find a repository that matches that input. Please try again.
{% endif %}


JOHNNY SWIM, a folk-soul bluesy duo comprised of Abner Ramirez and wife Amanda Sudano, daughter of the late Disco Queen Donna Summer will captivate attendees during Westobou’s signature musical event on the historic Parade Grounds at the Old Academy of Richmond County. The duo, described as a hybrid of Lauryn Hill and John Mayer have recently garnered national attention with the release of their latest album Heart Beats, in addition to the first ever position as VH1's You Oughta Know: Artists On the Rise. Such an accolade has aided in driving their new releases to respectable positions on the Billboard charts and appearances on Late Night with Jay Leno, The Today Show and Spoleto Festival USA.
Dead Confederate front man T. Hardy Morris is slated to take the Westobou Stage for a free concert at the Parade Grounds at the Old Academy of Richmond County. Singer/songwriter Ruby the Rabbitfoot will be opening for him. On July 30th, Hardy released his debut solo album Audition Tapes and completed a coveted summer position as artist in resident on Sirius-XM’s The Loft. While recording his album, Hardy began pursuing a project in collaboration with acclaimed filmmaker Jason Thrasher. The project, Places In Peril, is a musical-film series that investigates abandoned historical landmarks throughout the state of Georgia. Screenings of Thrasher and Morris’ Places In Peril videos will be shown at the Klacsmann Gallery at the Old Academy of Richmond County during gallery hours.


var canvasElement = document.getElementById('maincanvas');
sheetengine.scene.init(canvasElement, {w:900,h:500});
To create a scene we first create some BaseSheets with the following syntax. Parameters are: location, orientation, size. Use the color property to define base color:
var basesheet = new sheetengine.BaseSheet({x:0,y:0,z:0}, {alphaD:90,betaD:0,gammaD:0}, {w:200,h:200});
basesheet.color = '#5D7E36';
Then we add some regular sheets. You can access a sheet's canvas using the context property (a sheet is basically a small HTML5 canvas):
var sheet1 = new sheetengine.Sheet({x:150,y:20,z:20}, {alphaD:0,betaD:0,gammaD:0}, {w:40,h:40});
sheet1.context.fillStyle = '#FFF';
sheet1.context.fillRect(0,0,40,40);
Full alpha colors are supported so you can easily define arbitrary shapes (like the pine tree you see above) simply by drawing shapes on the sheet canvas. To draw the sheets on the main canvas we first do some necessary calculations and then draw everything. Use the true parameter to indicate we are drawing the full scene and not just updating regions that have changed before last drawing:
sheetengine.calc.calculateAllSheets();
sheetengine.drawing.drawScene(true);


Before Change
return torch.from_numpy(tensor[None, ...])
else:
// Channel axis is in already
return torch.from_numpy(tensor)
elif self.dimensionality == 1:
// We"re dealing with a vector - it has to be 1D
assert tensor.ndim == 1
return torch.from_numpy(tensor)
After Change
def tensor_function(self, tensor):
assert isinstance(tensor, (list, np.ndarray)), "Expected numpy array or list, got %s" % type(tensor)
if isinstance(tensor, np.ndarray):
return self._to_batch(tensor)
else:
return [self._to_batch(elem) for elem in tensor]


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Full Stack Developer and Freelancer
Hackerrank | Solution of Migratory Birds in Golang
In this one we will solve question migratory birds from hackerrank in golang. This one wraps a logic which can be used to solve many questions. Let's dive right into it.
Hackerrank | Solution of Divisible Sum Pairs in Golang
In this one we will solve question divisible sum pairs from hackerrank in golang. Let's get right into it.
From The AGC to Smartphones and Beyond
Today, space technology has evolved to an extent that mankind can envisage a future where space tourism could be a thing. In contrast, not even five decades ago, a single space expedition was a near to impossible task. The journey has been a historic one, much of which has been made possible by the power of modern computers, the foundation for which was laid in the 1960's.
Hackerrank | Solution of Birthday Chocolate in Golang
In this one we will solve question birthday chocolate from hackerrank in golang. Sweet one, let's dive right into it.
Hackerrank | Solution of Breaking the Records in Golang
In this one we will solve question breaking the records from hackerrank in golang. Let's dive right into it.
Hackerrank | Solution of Between Two Sets in Golang
In this one we will discuss the solution of Between two sets in Golang. It wraps good amount of logic, will be fun solving it. Let's dive right into it.
New Mornings New Subscribers
It's been a month since I started writing and uploading youtube videos. Just taking a minute to thank everyone for their support and sharing some stats for this month.
They Can Smell What You are Cooking
In this post we will discuss some of the privacy concerns that we will face while we browse the internet. Have a safe browsing!!!.
Hackerrank | Solution of Apple and Orange in Golang
In this post we will solve question apple and orange from hackerrank implementation section. A very easy one, let's dive right into it.
PUBG: A New Gaming Sensation
I know I am late late to the party, still a bit about PUBG.
Older Posts
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Euan Cochrane
Digital Preservation & Information Management Consulting
For inquiries please use the form below:
© 2018 Retrospective Digital


DefaultParentItem()
Default implementation of ChildItem
Author Camerash
See Also
ChildItem
ChildAdapter


{% load staticfiles %} {% include "pta/siteCss.html" %}
Progress in Post Traumatic Amnesia assessments for {{patient.first_name}} {{patient.last_name}}


Welcome to my userpage.
This page is actually built with Bootstrap since it looks good.
There's even documentation for bootstrap that everyone can use.
Dark mode? Yes, since it is easy for the eyes.
This page is actually built with Bootstrap since it looks good.
There's even documentation for bootstrap that everyone can use.
Dark mode? Yes, since it is easy for the eyes.


Mask.ControlVariables Class
Stores the variables used in step evaluators
Item Index
Methods
Methods
clear
()
Clear the control variables collection
get
(
Any
-
name
Gets a variable value
Parameters:
-
name
StringThe variable name
Returns:
Any:
The variable value
getNameValuePair
(
Object
-
name
Gets a pair with name and value
Parameters:
-
name
StringThe variable name
Returns:
Object:
A pair with the variable name and value
isDefined
(
Boolean
-
name
Checks if some variable is already defined
Parameters:
-
name
StringThe variable name
Returns:
Boolean:
A boolean indicating if the variable is already defined
remove
(
Object
-
name
Remove some variable from the control variables collection
Parameters:
-
name
StringThe variable name
Returns:
Object:
A pair with the removed variable name and value


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