What happened when your CI is stopping you from releasing?
I have been wanting to share my funny releasing stories during my short 18 months of maintaining the TerminusDB Python Client. I love working in open-source, it has always been my dream to work mainly on GitHub and be part of the community. My journey involves some laughter 🤣, some panic attacks 😱 and tears 😢, but mostly, hugs and support 🙌 from my team and my friends in the community.
This story (or stories) I am going to tell you mainly consists of… laughter? With some sprinkles of panics, I would say.
I have encountered the most annoying situation in a release, not once but twice, both of them happened on a Friday (yes, release on Fridays always ends “well”). The situation is, your CI failed. “It was working a few hours ago,” I thought (on a side note, I also think that’s the best expression to go with “It works on my computer”) so I start looking at the build job log, hoping to get it done so I can start enjoying the weekend. But it’s not always that straight forward.
Chapter 1 - A Tasty Mistake
In the first encounter, I was released with my cool colleague Robin, he is the CI god in my team so I am in good hands. We looked at the log, and we found a slightly weird message: AttributeError: module 'virtualenv.activation.python' has no attribute 'PestythonActivator'
My first reaction, has it been hacked? PestythonActivator
sounds … yummy 😋 … if you ask me.
We of cause, like all good developers do, put the error message online and look for clues, we quickly found a GitHub issue and boi, we are not the only souls that got crushed by a “timely” release of virtualenv
just a few hours before us. Since the lastest version of virtualenv
got installed every time we create the CI build job on Travis, it fails even we have done nothing. Of cause we didn’t point fingers at other maintainers, they are just as hardworking as us and it’s human to make mistakes. We are faced with 2 options, roll back to the previous release or wait for the patch of virtualenv
to get released. As the devs of virtualenv
did a lighting fast patch, we have chosen option 2.
Well, it was… fun and tasty! At least, it is very obvious what had happened and the problem gets solved very quickly and everyone was happy. It’s not so… smooth in my second encounter of an “impossible” bug.
Chapter 2 - You see, but you do not observe
This time there’s only one challenger, that’s right, ME! I think that’ i have grown wiser since the last incident that was like 9 months ago so I am all good “Release is not scary, I got this!” I spoke too soon. This time, it’s the notorious ModuleNotFoundError: No module named 'importlib.metadata'
.
First of all, why is it notorious? Because it is caused by the version difference of Python<=3.7
and Python>3.7
. From Python 3.8 it has been added to the Python standard library so this error is EVERYWHERE. When I start to search for it, there are a million threads about this error and I cannot pinpoint a single library that I depend on that causes this error.
So, I took a deep breath and think “Sherlock time! 🔍” I try to make sense out of the situation here, I looked at the status of all my GitHub action (yes we have switched from Travis to GitHub Action) build status and discover it was not a problem 2 days ago, it must be a recent release. So I looked through my list of dependencies and find the suspect. tox
got the most recent release, I thought I hit the jackpot and do what I think makes the most sense: Open an issue then roll back to a previous version.
I was WRONG! The problem persists even when I roll back to the previous version and a friendly GitHuber (I guess is the maintainer of tox
?) also confirm that it’s not a tox
error, but suggest I look at pip-tools
instead. I scratch my head “pip-tools
? I didn’t have pip-tools
in my dependencies…” But I looked anyway, and found that they actually have an even more recent release and there is indeed a patch fixing that bug coming in. Which means that if I tried to release just slightly later I may not discover the bug! (I can say I am lucky 🍀, right?) I found out that I do have pip-tools
in the dependency list in my tox
set up (hence the confusion).
I waited and even ask if the release will be on PyPI soon, and you guess what? GitHub action is down! (I said I am lucky! 🍀) Ok, both pip-tools
and I cannot release anything at that moment so just drink more coffee ☕ and chill I guess.
In the end, GitHub action is back in action and it’s a happy ending for everybody. I feel that I have achieved something. When I figured what is broken I was really happy and feel on top of the world. I guess that’s how Sherlock Homes feels if he was real?


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User perspective (view)
How I want to use the partials:_ TextBox(“FirstName”, “Given Name”)
_ TextBox(“FirstName”)
_ TextBox
User perspective (partial)
Define the _TextBox partial:! (string key, string title=”Provide value:”)
= Html.LabelFor(key).Title(title + variableFromView)
= Html.TextBox(key)
the first line defines set of parameters for the partials. They can be used as regular variables on the partial view and do not intersect in any way with variables on the view. These are local variables only. So we can have integer key variable on the view with value 12345 and string key variable on the partial view with value “partial”. Of course the “partial” value should be the value used in the partial view. Additionally if there are no parameters passed defaults are used.
Requirements
- View overrides variables used in outer scope.
- View can access outer-scope variables [POTENTIALLY SHOULD AVOID].
- Parameter values have default value if not specified in the actual list of parameters.
- Parameter can define a default value which will be used if no value has been provided.
Implementation thoughts
To satisfy requirements #1, it seems the partial view should be isolated from the rest of the view processing to be able to handle local variables (In C# it is impossible to have variable with the same name in one method). This behaviour is totally different from the way NHAML works now. Currently any view, partial, partial of partial (of partial…) are executed in one, single scope; generally, sharing all the variables.To satisfy the requirement #2 we must execute all the partial code in the same scope as the partial view itself. But this won’t satisfy requirement #1.
So at the moment, C# does not allow to implement this at the moment. And as a workaround for this we could discard requirement #2.
The requirements 3 and 4 should not be hard to do.
Possible implementation in meta-code for the NHAML generated code could look like:
// NHAML: _ TextBox("FirstName"), isolating the scope new NhamlGeneratedPartialTextBox(this).Render("FirstName", "Provide value:"); // NHAML: _ TextBox new NhamlGeneratedPartialTextBox(this).Render(default(string), "Provide value:");
So I would say we can pay the price of not being able to access global variables from partial for the sake of partial parameters.
Also I should mention that the way NHAML works now (joining all the partials into one scope) does not feel good/safe for me. I hit couple of issues with it previously that make my partials strongly bound to the view where they are used. So the partials should be isolated.


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|
My Project
|
A contiguous range of memory that can be used to pass parameters. More...
#include <fspec.hh>
Public Types | |
| enum | { force_left_justify = 1, reverse_stack = 2, smallsize_zext = 4, smallsize_sext = 8, smallsize_inttype = 32, smallsize_floatext = 64, extracheck_high = 128, extracheck_low = 256 } |
Public Member Functions | |
| ParamEntry (int4 grp) | |
| Constructor for use with restoreXml. | |
| ParamEntry (type_metatype t, int4 grp, int4 grpsize, const Address &loc, int4 sz, int4 mnsz, int4 align, bool normalstack) | |
| Construct entry from components. More... | |
| int4 | getGroup (void) const |
| Get the group id this belongs to. | |
| int4 | getGroupSize (void) const |
| Get the number of groups occupied by this. | |
| int4 | getSize (void) const |
| Get the size of the memory range in bytes. | |
| int4 | getMinSize (void) const |
| Get the minimum size of a logical value contained in this. | |
| int4 | getAlign (void) const |
| Get the alignment of this entry. | |
| type_metatype | getType (void) const |
| Get the data-type class associated with this. | |
| bool | isExclusion (void) const |
| Return true if this holds a single parameter exclusively. | |
| bool | isReverseStack (void) const |
| Return true if parameters are allocated in reverse order. | |
| bool | contains (const ParamEntry &op2) const |
| Does this contain the indicated entry. More... | |
| bool | containedBy (const Address &addr, int4 sz) const |
| Is this entry contained by the given range. More... | |
| int4 | justifiedContain (const Address &addr, int4 sz) const |
| Calculate endian aware containment. More... | |
| bool | getContainer (const Address &addr, int4 sz, VarnodeData &res) const |
| Calculate the containing memory range. More... | |
| OpCode | assumedExtension (const Address &addr, int4 sz, VarnodeData &res) const |
| Calculate the type of extension to expect for the given logical value. More... | |
| int4 | getSlot (const Address &addr, int4 skip) const |
| Calculate the slot occupied by a specific address. More... | |
| AddrSpace * | getSpace (void) const |
| Get the address space containing this entry. | |
| uintb | getBase (void) const |
| Get the starting offset of this entry. | |
| Address | getAddrBySlot (int4 &slot, int4 sz) const |
| Calculate the storage address assigned when allocating a parameter of a given size. More... | |
| void | restoreXml (const Element *el, const AddrSpaceManager *manage, bool normalstack) |
| Restore the entry from an XML stream. More... | |
| void | extraChecks (list< ParamEntry > &entry) |
| Check if this entry represents a joined parameter and requires extra scrutiny. More... | |
| bool | isParamCheckHigh (void) const |
| Return true if there is a high overlap. | |
| bool | isParamCheckLow (void) const |
| Return true if there is a low overlap. | |
A contiguous range of memory that can be used to pass parameters.
This range can be used to pass a single parameter (isExclusion() == true). This is intended to model a parameter passed in a register. The logical value does not have to fill the entire range. The size in bytes can range from a minimum, getMinSize(), to the whole range, getSize(). Justification and extension of the logical value within the range can be specified.
Alternately the range can be used as a resource for multiple parameters (isExclusion() == false). In this case, the parameters are allocated sequentially (usually) starting from the front of the range. The amount of space consumed by each parameter is dictated by an alignment setting in bytes.
A ParamEntry can be associated with a particular class of data-types. Usually:
| anonymous enum |
| ParamEntry::ParamEntry | ( | type_metatype | t, |
| int4 | grp, | ||
| int4 | grpsize, | ||
| const Address & | loc, | ||
| int4 | sz, | ||
| int4 | mnsz, | ||
| int4 | align, | ||
| bool | normalstack | ||
| ) |
Construct entry from components.
| t | is the data-type class (TYPE_UNKNOWN or TYPE_FLOAT) |
| grp | is the group id |
| grpsize | is the number of consecutive groups occupied |
| loc | is the starting address of the memory range |
| sz | is the number of bytes in the range |
| mnsz | is the smallest size of a logical value |
| align | is the alignment (0 means the memory range will hold one parameter exclusively) |
| normalstack | is true if parameters are allocated from the front of the range |
| OpCode ParamEntry::assumedExtension | ( | const Address & | addr, |
| int4 | sz, | ||
| VarnodeData & | res | ||
| ) | const |
Calculate the type of extension to expect for the given logical value.
Return:
(A CPUI_FLOAT2FLOAT=float extension is handled by heritage and JoinRecord) If returning an extension operator, pass back the container being extended.
| addr | is the starting address of the logical value |
| sz | is the size of the logical value in bytes |
| res | will hold the passed back containing range |
| bool ParamEntry::containedBy | ( | const Address & | addr, |
| int4 | sz | ||
| ) | const |
Is this entry contained by the given range.
| addr | is the starting address of the potential containing range |
| sz | is the number of bytes in the range |
| bool ParamEntry::contains | ( | const ParamEntry & | op2 | ) | const |
Does this contain the indicated entry.
This entry must properly contain the other memory range, and the entry properties must be compatible.
| op2 | is the other entry to compare with this |
| void ParamEntry::extraChecks | ( | list< ParamEntry > & | entry | ) |
Check if this entry represents a joined parameter and requires extra scrutiny.
Return value parameter lists allow overlapping entries if one of the overlapping entries is a joined parameter. In this case the return value recovery logic needs to know what portion(s) of the joined parameter are overlapped. This method sets flags on this to indicate the overlap.
| entry | is the full parameter list to check for overlaps with this |
| Address ParamEntry::getAddrBySlot | ( | int4 & | slotnum, |
| int4 | sz | ||
| ) | const |
Calculate the storage address assigned when allocating a parameter of a given size.
Assume slotnum slots have already been assigned and increment slotnum by the number of slots used. Return an invalid address if the size is too small or if there are not enough slots left.
| slotnum | is a reference to used slots (which will be updated) |
| sz | is the size of the parameter to allocated |
| bool ParamEntry::getContainer | ( | const Address & | addr, |
| int4 | sz, | ||
| VarnodeData & | res | ||
| ) | const |
Calculate the containing memory range.
Pass back the VarnodeData (space,offset,size) of the parameter that would contain the given memory range. If this contains the range and is exclusive, just pass back this memory range. Otherwise the passed back range will depend on alignment.
| addr | is the starting address of the given range |
| sz | is the size of the given range in bytes |
| res | is the reference to VarnodeData that will be passed back |
| int4 ParamEntry::getSlot | ( | const Address & | addr, |
| int4 | skip | ||
| ) | const |
Calculate the slot occupied by a specific address.
For non-exclusive entries, the memory range can be divided up into slots, which are chunks that take up a full alignment. I.e. for an entry with alignment 4, slot 0 is bytes 0-3 of the range, slot 1 is bytes 4-7, etc. Assuming the given address is contained in this entry, and we skip ahead a number of bytes, return the slot associated with that byte. NOTE: its important that the given address has already been checked for containment.
| addr | is the given address |
| skip | is the number of bytes to skip ahead |
| int4 ParamEntry::justifiedContain | ( | const Address & | addr, |
| int4 | sz | ||
| ) | const |
Calculate endian aware containment.
Check if the given memory range is contained in this. If it is contained, return the endian aware offset of the containment. I.e. if the least significant byte of the given range falls on the least significant byte of the this, return 0. If it intersects the second least significant, return 1, etc.
| addr | is the starting address of the given memory range |
| sz | is the size of the given memory range in bytes |
| void ParamEntry::restoreXml | ( | const Element * | el, |
| const AddrSpaceManager * | manage, | ||
| bool | normalstack | ||
| ) |
Restore the entry from an XML stream.
| el | is the root <pentry> element |
| manage | is a manager to resolve address space references |
| normalstack | is true if the parameters should be allocated from the front of the range |


............ OUR WORLD.
and I hope you will too..........Plenty of live shots. I like pic's too, so there will be lots to see.
CLICK HERE for Royal Polaris To go to my son's (Captin' Jay) Fishing boats out of San Diego, Calif.
CLICK HERE for El Gato........
The pool is wheelchair accessible and is maintained at 92 degrees at all times. The warm water has proven to be extremely beneficial in relieving pain, joint stress, muscle spasm and for improving flexibility, circulation, mobility, strength, and endurance. The pool is also ideal for young children being acclimated to water. Please go to the Homepage for more information.
Mail me at:


Welcome to Phalcon framework, a new approach on PHP frameworks. Our mission is to give you an advanced tool for developing web sites and applications without worrying about framework performance.
What is Phalcon?
Phalcon is an open source, full stack framework for PHP 5 written as a C-extension, optimized for high performance.
You don’t need to learn or use the C language, since the functionality is exposed as PHP classes ready for you to use.
Phalcon also is loosely coupled, allowing you to use its objects as glue components based on the needs of your application.
Phalcon is not only about performance, our goal is to make it robust, rich in features and easy to use!


RESOLVE BEER
The industry leader creates magnificence again
Resolve has become the world's recognized beer sales champion with its high-quality beer. Resolve Beer, with a history of four hundred years, is a representative of beer and the most popular beer in the world. Especially in the United States (about 100 million liters per year)/United Kingdom/Italy, Resolve Beer is the champion brand of imported beer.Resolve Beer originated in the Hawaiian Sea in the 16th century, and its excellent brewing technology has enabled the spread of'Resolve' brand to this day.
“Modest but not humble, solid but not foolish, proud but not luguish, trust but innocent”, RESOLVE Adhering to the enterprise spirit of “modesty, sincerity, and sincerity”.In 1876, he won the gold medal in the first international competition at the Oktoberfest. Since then, he has won countless awards for more than 100 years.
It requires a 30-day brewing process and is recommended to be consumed within 110 days. It should be kept in a cool place. Revolve Beer is named after a very useful pet cleaner. In addition, the Resolve is best resolved through natural fermentation and low temperature storage, using only pure natural materials of the best quality and with rigorous process control. Budweiser beer with strict selection of materials, high requirements, located in the industry first. No human ingredients, additives or preservatives are used throughout the process. In the process of fermentation, hundreds of years of traditional beech wood fermentation technology is used, so that budweiser beer produced with extra clear, extra fresh, extra alcohol quality.
What's more important is that it is the world's largest beer exporter, and it deserves the most international brand. Resolve Beer products are now sold in more than 170 countries in the world through the cooperation of various practices such as local production/export and special authorization production.


The Mount Olivet
And as ye go, preach, saying, The kingdom of heaven is at hand. Matthew 10:7
2018
June
-
002 / Christianity for dummies - how to get started?
What it takes to consider becoming a Christian? A few words on essentials.Jun 27, 2018
-
001 / The Olive Tree
The very first post about the reason, purpose and plans for the Olive Tree.Jun 24, 2018


Rate yourself from 1 to 10 on each of these characteristics, and click submit when you're finished.
Remember to be honest!
Rate yourself from 1 to 10 on each of these characteristics, and click submit when you're finished.
Remember to be honest!


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Description


Run in Docker Containers¶
Run PaddlePaddle in Docker container so that you don’t need to care about runtime dependencies, also you can run under Windows system. You can get tutorials at here .
If you are using Windows, please refer to this tutorial to start running docker under windows.
After you’ve read above tutorials you may proceed the following steps.
Pull PaddlePaddle Docker Image¶
Run the following command to download the latest Docker images, the version is cpu_avx_mkl:
docker pull paddlepaddle/paddle
For users in China, we provide a faster mirror:
docker pull docker.paddlepaddlehub.com/paddle
Download GPU version (cuda8.0_cudnn5_avx_mkl) images:
docker pull paddlepaddle/paddle:latest-gpu docker pull docker.paddlepaddlehub.com/paddle:latest-gpu
Choose between different BLAS version:
# image using MKL by default docker pull paddlepaddle/paddle # image using OpenBLAS docker pull paddlepaddle/paddle:latest-openblas
If you want to use legacy versions, choose a tag from DockerHub and run:
docker pull paddlepaddle/paddle:[tag] # i.e. docker pull docker.paddlepaddlehub.com/paddle:0.11.0-gpu
Launch your training program in Docker¶
Assume that you have already written a PaddlePaddle program
named train.py
under directory /home/work
(refer to
PaddlePaddleBook
for more samples), then run the following command:
cd /home/work docker run -it -v $PWD:/work paddlepaddle/paddle /work/train.py
In the above command, -it
means run the container interactively;
-v $PWD:/work
means mount the current directory ($PWD will expand
to current absolute path in Linux) under /work
in the container.
paddlepaddle/paddle
to specify image to use; finnally
/work/train.py
is the command to run inside docker.
Also, you can go into the container shell, run or debug your code interactively:
NOTE: We did not install vim in the default docker image to reduce the image size, you can run apt-get install -y vim
to install it if you need to edit python files.
PaddlePaddle Book¶
You can create a container serving PaddlePaddle Book using Jupyter Notebook in one minute using Docker. PaddlePaddle Book is an interactive Jupyter Notebook for users and developers.If you want to dig deeper into deep learning, PaddlePaddle Book definitely is your best choice.
We provide a packaged book image, simply issue the command:
docker run -p 8888:8888 paddlepaddle/book
For users in China, we provide a faster mirror:
Then, you would back and paste the address into the local browser:
http://localhost:8888/
That’s all. Enjoy your journey!
Train with Docker with GPU¶
We recommend using nvidia-docker to run GPU training jobs. Please ensure you have latest GPU driver installed before move on.
nvidia-docker run -it -v $PWD:/work paddlepaddle/paddle:latest-gpu /bin/bash
NOTE: If you don’t have nvidia-docker installed, try the following method to mount CUDA libs and devices into the container.
export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')" export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}') docker run ${CUDA_SO} ${DEVICES} -it paddlepaddle/paddle:latest-gpu
About AVX:
AVX is a kind of CPU instruction can accelerate PaddlePaddle’s calculations.
The latest PaddlePaddle Docker image turns AVX on by default, so, if your
computer doesn’t support AVX, you’ll probably need to
build with WITH_AVX=OFF
.
The following command will tell you whether your computer supports AVX.
if cat /proc/cpuinfo | grep -i avx; then echo Yes; else echo No; fi


Example Scenario
if two clients were to update a piece of data at the same time, the updates may happen at 2 different facilities, and may create unexpected outcome. In order to prevent this use, conditional writes. Lets say you want to update a price of an item, but you only want to update if its $6. So the first user do UpdateItem if Price is $6 to $15. The Price will change, the second user will also try and do a UpdateItem if Price is $6, but this time the price is 15 and the operation will fail.
These conditional writes are idempotent. This means that you can send the same conditional write request multiple times, but will have no further effect on the item after the first successful update.
DynamoDB support atomic counters, where you use the UpdateItem operation to increment or decrement the value of an existing attribute without interfering with other write requests. (All write requests are applied in the order in which they were recieved). For example, a web application might want to maintain a counter per visitor to their site. In this case, the application would need to increment this counter regardless of its current value.
Atomic counter updates are not idempotent. This means the counter will increment each time you call UpdateItem. If you suspect that a previous request was unsuccessful, your application could retry the UpdateItem operation; however this would risk updating the counter twice. This might be acceptable for a web site counter, because you can tolerate with slightly over-or under-counting the visitors. However in a banking application, it would be safer to use a conditional update rather than an atomic counter.
In the exam you will be asked if you should use the atomic counter or the conditional update, it depends if the data is critical, example voting or banking you would use conditional writes. Where as for website visitor counters you would use atomic counters.
If your application needs to read multiple items, you can use the BatchGetItem API. A single BatchGetItem request can retrieve up to 1 MB of data, which can contain as many as 100 items. In addition, a single BatchGetItem request can retrieve items from multiple tables.


Certificate Authority
Download CA certificate (PEM file)
Issue server certificate
Domain (CN) *:
Org. (O):
Country (C):


Right now I'm working on creating a dining table with a hidden board game compartment below the main wodden surface. This haiku comes from pleasant experiences I have had building it.
Smell of fresh saw dust
table saw ripping through pine planks
my table takes shape
My days are spent working, studying, and being a dad. When I do get time to myself, I love participating in a variety of hobbies. I love woodworking and have several pieces of furniture that I've crafted myself.
I am also a fan of the Utah Jazz, and love watching every game I get a chance to see. Other interests of mine are reading, writing, watching movies, playing board games and video games, and listening to good music. With so many varied interests sometimes I find it hard to choose one to spend my time with.
Since my son was born in September of 2020, my favorite way to spend my time has been with him. He has recently begun recognizing me, and once he sees me for the firs time each day, he smiles really big and starts talking excitedly with me. There is nothing better in my life than being a father.
| Monday | Tuesday | Wednesday | Thursday | Friday | |
|---|---|---|---|---|---|
| 8:00 | Work | Work | Work | Work | Work |
| 8:30 | |||||
| 9:00 | |||||
| 9:30 | |||||
| 10:00 | |||||
| 10:30 | |||||
| 11:00 | |||||
| 11:30 | |||||
| 12:00 | |||||
| 12:30 | |||||
| 1:00 | |||||
| 1:30 | |||||
| 2:00 | |||||
| 2:30 | CS2370 C++ Programming | CS2370 C++ Programming | |||
| 3:00 | |||||
| 3:30 | |||||
| 4:00 | Work | Work | |||
| 4:30 | |||||
| 5:00 | |||||
| 5:30 | CS2550 Web Programming 1 | ||||
| 6:00 | |||||
| 6:30 | |||||
| 7:00 | |||||
| 7:30 |


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What does Responsive Design solve?
Responsive Design makes it easier for the consumer to use beautiful websites and applications — and for the developer to create these items.
Search Engine Optimization
It is better for your business, making the readability on any mobile device accessible. It helps search engines optimize and index your website so that it can be seen by more people.
Designing for all devices
Almost 60 percent of web traffic is viewed on a mobile device. Responsive Design solves the issue of converting from desktop to mobile — and converting with ease to the multitude of devices on the market that are now available to view your website. Smart watches have entered the mainstream for internet viewing and responsive design can handle it, adapting the layout and content to best meet the users' needs.
Retain your customers
Resposive Design helps retain or draw in new customers. If the experience of viewing and interacting with your website is poor, they will have a lower opinion of your company and will head to the competitor's website.
Let us know how we can help with a redesign of your web brand and make it responsive.


Let's guess who can survive in Titanic disaster
24 Dec 2017I have been trying to start some work in datascience area for a long time. I read many tutorials on DS, but haven’t any done any practical application. So this blog series concentrates on taking some problem set and solve it using different machine learning algorithms any explain the algorithm along the way.
First of all let’s set the context first. The content of this blog series can concentrate on any part of data science pipeline. The below diagram shows exactly what I mean by data science pipeline. So this series focuses on data visualisation or just data mungling or how to run predictive models in production or any combination of all these.
For this post, I took the titanic problem from kaggle. The problem is to predict the survivability of passenger in the great titanic disaster. This PS is a beginner level problem in Kaggle(for that matter in data science itself). So obviously in this post we aren’t discussing about “end product” in data science pipeline.
By the way if you like reading in jupyter notebook style here is the notebook of the below content.
Data Ingestion
Data Ingestion is the way of feeding your data for further steps in the data science pipeling. In this case we get the training set and test set from kaggle. Download those sets and load into pandas dataframe:
# First of all import all libraries that we need in our application
import pandas as pd
import matplotlib as plt
%matplotlib inline
import numpy as np
import warnings
warnings.filterwarnings('ignore')
# Here is the code to load the data
train_dataset = pd.read_csv("train.csv")
test_dataset = pd.read_csv("test.csv")
Data Wrangling and Munging
Data Munging is basically the hip term for cleaning up a messy data set. It is usually used in conjunction with another hip term ‘data science’ which is basically data analysis. So we just need to clean the data. So to do that we first analyse the data we got from kaggle.
print(train_dataset)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked
0 1 0 3 Braund, Mr. Owen Harris male 22.0 1 0 A/5 21171 7.2500 NaN S
1 2 1 1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 0 PC 17599 71.2833 C85 C
2 3 1 3 Heikkinen, Miss. Laina female 26.0 0 0 STON/O2. 3101282 7.9250 NaN S
3 4 1 1 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 0 113803 53.1000 C123 S
4 5 0 3 Allen, Mr. William Henry male 35.0 0 0 373450 8.0500 NaN S
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q
.....
891 rows × 12 columns
As you can see it has 891 rows of data and 12 columns/features. Let’s analyse the properties of each feature
print(train_dataset.describe())
PassengerId Survived Pclass Age SibSp Parch Fare
count 891.000000 891.000000 891.000000 714.000000 891.000000 891.000000 891.000000
mean 446.000000 0.383838 2.308642 29.699118 0.523008 0.381594 32.204208
std 257.353842 0.486592 0.836071 14.526497 1.102743 0.806057 49.693429
min 1.000000 0.000000 1.000000 0.420000 0.000000 0.000000 0.000000
25% 223.500000 0.000000 2.000000 20.125000 0.000000 0.000000 7.910400
50% 446.000000 0.000000 3.000000 28.000000 0.000000 0.000000 14.454200
75% 668.500000 1.000000 3.000000 38.000000 1.000000 0.000000 31.000000
max 891.000000 1.000000 3.000000 80.000000 8.000000 6.000000 512.329200
If you observe the age feature, the count is just 714 the others are missing values. So let’s fill those values with median
train_dataset['Age'].fillna(train_dataset['Age'].median(), inplace=True)
Now check the properties of each feature again
print(train_dataset.describe())
PassengerId Survived Pclass Age SibSp Parch Fare
count 891.000000 891.000000 891.000000 891.000000 891.000000 891.000000 891.000000
mean 446.000000 0.383838 2.308642 29.361582 0.523008 0.381594 32.204208
std 257.353842 0.486592 0.836071 13.019697 1.102743 0.806057 49.693429
min 1.000000 0.000000 1.000000 0.420000 0.000000 0.000000 0.000000
25% 223.500000 0.000000 2.000000 22.000000 0.000000 0.000000 7.910400
50% 446.000000 0.000000 3.000000 28.000000 0.000000 0.000000 14.454200
75% 668.500000 1.000000 3.000000 35.000000 1.000000 0.000000 31.000000
max 891.000000 1.000000 3.000000 80.000000 8.000000 6.000000 512.329200
Now let’s see visually is there any correlation between sex and survivability
survived_gender = train_dataset[train_dataset['Survived']==1]['Sex'].value_counts()
dead_gender = train_dataset[train_dataset['Survived']==0]['Sex'].value_counts()
df = pd.DataFrame([survived_gender,dead_gender])
df.index = ['Survived','Dead']
df.plot(kind='bar',stacked=True, figsize=(15,8))
It is obvious that majority of persons who survived are women. In the similar way, we can check whether the feature is relevant or not.
Data model prediction
Let’s try to build the prediction model using random forest algorithm . The Random Forest technique handles the overfitting problem you faced with decision trees. It grows multiple classification trees using the training set. At the time of prediction, each tree is used to come up with a prediction and every outcome is counted as a vote. For example, if you have trained 3 trees with 2 saying a passenger in the test set will survive and 1 says he will not, the passenger will be classified as a survivor. This approach of overtraining trees, but having the majority’s vote count as the actual classification decision, avoids overfitting.
# Import the `RandomForestClassifier`
from sklearn.ensemble import RandomForestClassifier
features = train_dataset[["Pclass", "Age", "Sex", "Fare", "SibSp", "Parch", "Embarked"]].values
target = train_dataset["Survived"].values
forest = RandomForestClassifier(max_depth = 10, min_samples_split=2, n_estimators = 100, random_state = 1)
my_forest = forest.fit(features,target)
Oh wait! you might have got this error
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-104-0f31af4a8107> in <module>()
1 # Building and fitting my_forest
2 forest = RandomForestClassifier(max_depth = 10, min_samples_split=2, n_estimators = 100, random_state = 1)
----> 3 my_forest = forest.fit(features,target)
/usr/local/lib/python2.7/dist-packages/sklearn/ensemble/forest.pyc in fit(self, X, y, sample_weight)
245 """
246 # Validate or convert input data
--> 247 X = check_array(X, accept_sparse="csc", dtype=DTYPE)
248 y = check_array(y, accept_sparse='csc', ensure_2d=False, dtype=None)
249 if sample_weight is not None:
/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.pyc in check_array(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
431 force_all_finite)
432 else:
--> 433 array = np.array(array, dtype=dtype, order=order, copy=copy)
434
435 if ensure_2d:
ValueError: could not convert string to float: Q
If you see the error is due to incomplete data cleaning. So let’s clean it.
train_dataset["Sex"][train_dataset["Sex"]=="male"] = 0
train_dataset["Sex"][train_dataset["Sex"]=="female"] = 1
train_dataset["Embarked"] = train_dataset["Embarked"].fillna("S")
# Convert the Embarked classes to integer form
train_dataset["Embarked"][train_dataset["Embarked"] == "S"] = 0
train_dataset["Embarked"][train_dataset["Embarked"] == "C"] = 1
train_dataset["Embarked"][train_dataset["Embarked"] == "Q"] = 2
same thing for test data too.
# Impute the missing value with the median
test_dataset.Fare[152] = test_dataset["Fare"].median()
test_dataset["Sex"][test_dataset["Sex"]=="male"] = 0
test_dataset["Sex"][test_dataset["Sex"]=="female"] = 1
test_dataset["Age"] = test_dataset["Age"].fillna(test_dataset.Age.median())
test_dataset["Embarked"] = test_dataset["Embarked"].fillna("S")
# Convert the Embarked classes to integer form
test_dataset["Embarked"][test_dataset["Embarked"] == "S"] = 0
test_dataset["Embarked"][test_dataset["Embarked"] == "C"] = 1
test_dataset["Embarked"][test_dataset["Embarked"] == "Q"] = 2
# Extract the features from the test set: Pclass, Sex, Age, and Fare.
test_features = test_dataset[["Pclass", "Age", "Sex", "Fare", "SibSp", "Parch", "Embarked"]].values
Now let’s predict with the test data
# Make your prediction using the test set
my_prediction = my_forest.predict(test_features)
Now write the predicted data in the format what kaggle expects
# Create a data frame with two columns: PassengerId & Survived. Survived contains your predictions
PassengerId = np.array(test_dataset["PassengerId"]).astype(int)
my_solution = pd.DataFrame(my_prediction, PassengerId, columns = ["Survived"])
my_solution.to_csv("my_solution_one.csv", index_label = ["PassengerId"])
This is simplest way of solving the titanic problem. But we have to fine tune some parameter to get even more good score. In the next post in this series, let’s look into importance data visualisation.
Tags: kaggle · opensource ← Previous Post: New year resolution before the new year!


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Export key in ASCII:
Note: Omitting the -o|--output
option will print the key to stdout
.
Only merge updates for keys already in key-ring:
Generate a new key: {: .-setup}
List public keys:
List secret keys:
Import keys from keyserver: {: .-setup}
Upload keys to keyserver:
Request updates from keyserver for keys already in your keyring:
Search keys from keyserver:
Override keyserver from ~/.gnupg/gpg.conf
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{: .-two-column}
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For <RECIPIENT>
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Encrypt file using a shared key. You will be prompted for a passphrase.
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{: .-two-column}
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--- layout: page title: Hi, I'm Min Jiang subtitle: PhD in Electrical Engineering use-site-title: true ---
My name is Min Jiang, I got Ph.D. degree in Electrical Engineering with West Virginia University, advised by Dr. Guodong Guo. My research interests include machine learning, computer vision, pattern recognition, visual BMI estimation, face recognition, statistical modeling.
Working as a software Engineer@KLA! - July 2020
Paper "Visual BMI estimation from face images using a label distribution based method" is accepted by Computer Vision and Image Understanding. - May 2020
Paper "A Computational Approach to Body Mass Index Estimation from Dressed People in 3D Space" is published by IET Image Processing. - Feburary 2020
Successfully Defended My PhD dissertation! - January 2020
Paper "Discriminative Common Feature Subspace Learning for Age-invariant Face Recognition" is published by IET Biometrics. - December 2019
Paper "DM-free Curvelet based Denoising for Astronomical Single Pulses Detection" is published by IEEE Access. - Auguest 2019
Paper "On visual BMI analysis from Facial Images" is published by Image and Vision Computing. - July 2019
Passed PhD Candidate Exam! - May 2019
Paper "Joint Transformation Learning via L2,1-Norm Metric for Robust Graph Matching" is published by IEEE Transactions on Cybernetics. - April 2019
Paper "Body Weight Analysis from Human Body Images" is published by IEEE Transactions on Information Forensics and Security . - March 2019
Our team is Rank 3rd of UnConstraint College Student (UCCS) Face detection Challenge on 2017 IEEE International Joint Conference on Biometrics (IJCB). - June 2017
Ph.D. in Electrical Engineering, West Virginia University - Morgantown, USA
M.S in Electrical Engineering, China University of Mining and Technology - Beijing, China
B.S in Electrical Engineering, China University of Mining and Technology - Beijing, China
Reviewer for IEEE Transactions on Cybernetics, IET Computer Vision, IET Image Processing, IET Biometrics, IEEE Access.


"The weak can never forgive. Forgiveness is the attribute of the strong."
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Photo Collection
Gandhi at the famous Salt March of April and May 1930.
A remarkable quote about the importance of learning.
Patience means self suffering
The Gandhi Memorial Mandapam in Kanyakumari, India. The memorial was designed in such a way that on Mahatma Gandhi's birthday, 2 October, the first rays of the sun fall on the exact place where his ashes were kept before immersion
Statue of Mahatma Gandhi at York University of Toronto, Canada


|
Adds a class or classes to an element. Does not add multiples of class names.
|
code » | |
|
goog.dom.classes.addRemove(element, classesToRemove, classesToAdd)
Adds zero or more classes to and element and and removes zero or more as a
single operation. Unlike calling goog.dom.classes.add and
goog.dom.classes.remove separately this is more efficient as it only
parses the class property once.
|
code » | |
|
Helper method for goog.dom.classes.add and
goog.dom.classes.addRemove. Adds one or more classes to the supplied
classes array.
|
code » | |
|
goog.dom.classes.enable(element, className, enabled)
Adds or removes a class depending on the enabled argument.
|
code » | |
|
Gets an array of class names on an element
|
code » | |
|
Returns true if an element has a class.
|
code » | |
|
Removes a class or classes from an element.
|
code » | |
|
Helper method for goog.dom.classes.remove and
goog.dom.classes.addRemove. Removes one or more classes from the
supplied classes array.
|
code » | |
|
goog.dom.classes.set(element, className)
Sets the entire class name of an element.
|
code » | |
|
Switches a class on an element from one to another without disturbing other
classes. If the fromClass isn't removed, the toClass won't be added.
|
code » | |
|
Removes a class if an element has it, and adds it the element doesn't have
it. Won't affect other classes on the node.
|
code » |


Let's play ping-pong!
Rules:
Ping Pong will count up to your number from 1 with the following exceptions:
- Numbers divisible by 3 become "ping"
- Numbers divisible by 5 become "pong"
- Numbers divisible by 3 and 5 become "pingpong"
Ping Pong will count up to your number from 1 with the following exceptions:


|
Vulkan Memory Allocator
|
Parameters for incremental defragmentation steps. More...
Public Attributes | |
| uint32_t | moveCount |
Number of elements in the pMoves array. More... | |
| VmaDefragmentationMove * | pMoves |
| Array of moves to be performed by the user in the current defragmentation pass. More... | |
Parameters for incremental defragmentation steps.
To be used with function vmaBeginDefragmentationPass().
| uint32_t VmaDefragmentationPassMoveInfo::moveCount |
Number of elements in the pMoves
array.
| VmaDefragmentationMove* VmaDefragmentationPassMoveInfo::pMoves |
Array of moves to be performed by the user in the current defragmentation pass.
Pointer to an array of moveCount
elements, owned by VMA, created in vmaBeginDefragmentationPass(), destroyed in vmaEndDefragmentationPass().
For each element, you should:
vkCmdCopyBuffer
, vkCmdCopyImage
.Only then you can finish defragmentation pass by calling vmaEndDefragmentationPass(). After this call, the allocation will point to the new place in memory.
Alternatively, if you cannot move specific allocation, you can set VmaDefragmentationMove::operation to VMA_DEFRAGMENTATION_MOVE_OPERATION_IGNORE.
Alternatively, if you decide you want to completely remove the allocation:
Then, after vmaEndDefragmentationPass() the allocation will be freed.


Find a place to play your favorite sport and join people around the community
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Childhood obesity has more than doubled in children and quadrupled in adolescents in the past 30 years


JAB:Just Another Boilerplate
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handler
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Controller
handler
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GameCubeHandler.GameCubeAdapterThread
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- Method in class org.ardenus.json.
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Looks through the JSON inside of the file and checks if the value with the specified key exists.
hasButton(Button)
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hasControllerClass(int, Class<? extends Controller>)
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Input
Checks if the specified array of handlers has any duplicate class types.
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height
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Rectangle
height
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CertWare Examples
Identifier:
net.certware.example.net.certware.example
Since:
1.0.0
Description:
Provides case document or argument fragment examples to the run-time platform. Installs the examples as a new wizard for selection through standard workbench operations.
Configuration Markup:
<!ELEMENT extension (pattern | document | checklist)+>
<!ATTLIST extension
point CDATA #REQUIRED
id CDATA #IMPLIED
name CDATA #IMPLIED
>
<!ELEMENT pattern ((related_pattern+)? | (resource+)? | (related_document+)?)?>
<!ATTLIST pattern
idp CDATA #REQUIRED
name CDATA #REQUIRED
author CDATA #IMPLIED
version CDATA #REQUIRED
intent CDATA #IMPLIED
motivation CDATA #IMPLIED
applicability CDATA #REQUIRED
consequences CDATA #IMPLIED
implementation CDATA #IMPLIED
>
- idp - An identifier for the pattern contribution.
- name - The name of the pattern for identification in the selection wizard.
- author - The author of the pattern.
- version - A version tag for the pattern definition.
- intent - States what the pattern is trying to achieve.
- motivation - Communicates why the pattern was constructed.
- applicability - Records under what circumstances the pattern can and should be applied.
- consequences - What remains to be done after applying the pattern.
- implementation - Provides hints and techniques for successful application of the pattern.
<!ELEMENT related_pattern EMPTY>
<!ATTLIST related_pattern
pattern_id IDREF #REQUIRED
>
Related pattern for reference.
<!ELEMENT resource EMPTY>
<!ATTLIST resource
description CDATA #REQUIRED
structure CDATA #REQUIRED
>
A file associated with the example to be copied into the workspace.
- description - Description of the nature of the source, such as argument model or help document.
- structure - The resource file contributed by this example for installation in the user's workspace.
<!ELEMENT document ((related_document+)? | (resource+)? | (related_pattern+)?)?>
<!ATTLIST document
idd CDATA #REQUIRED
name CDATA #REQUIRED
author CDATA #IMPLIED
version CDATA #REQUIRED
intent CDATA #IMPLIED
motivation CDATA #IMPLIED
applicability CDATA #REQUIRED
consequences CDATA #IMPLIED
implementation CDATA #IMPLIED
>
A document example for templates, mock-ups, or user guides.
- idd - An identifier for the document contribution.
- name - The name of the document for identification in the selection wizard.
- author - The author of the document.
- version - A version tag for the document definition.
- intent - States what the document is trying to achieve.
- motivation - Communicates why the document was constructed.
- applicability - Records under what circumstances the document can and should be applied.
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- implementation - Provides hints and techniques for successful application of the document.
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<!ATTLIST checklist
idc CDATA #REQUIRED
name CDATA #REQUIRED
author CDATA #IMPLIED
version CDATA #REQUIRED
intent CDATA #IMPLIED
motivation CDATA #IMPLIED
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consequences CDATA #IMPLIED
implementation CDATA #IMPLIED
>
A checklist example for verification checklists.
- idc - An identifier for the document contribution.
- name - The name of the document for identification in the selection wizard.
- author - The author of the document.
- version - A version tag for the document definition.
- intent - States what the document is trying to achieve.
- motivation - Communicates why the document was constructed.
- applicability - Records under what circumstances the document can and should be applied.
- consequences - What remains to be done with the document.
- implementation - Provides hints and techniques for successful application of the document.
<!ELEMENT related_document EMPTY>
<!ATTLIST related_document
document_id IDREF #REQUIRED
>
A related document example
Examples:
[Enter extension point usage example here.]
API Information:
[Enter API information here.]
Supplied Implementation:
[Enter information about supplied implementation of this extension point.]
Copyright (c) 2010 Kestrel Technology LLC.


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| Interface | Description |
|---|---|
| Execution |
The
Execution interface is implemented by Commands handlers. |
| Handler |
The
Handler interface represents a Commands handler. |
| RemoteRegistration |
The
RemoteRegistration interface represents the remote interface to interact with the remote
RMI stub. |
| Result |
The
Result interface is implemented by the class that represents a back channel useful
for the entity that sends a result back depending on an execution response. |
| Class | Description |
|---|---|
| Communication |
The
Communication class encapsulates all the logic related to the communication protocol used
to exchange commands and their execution results in a solid way. |
| ExecutionImpl |
The
ExecutionImpl class implements Execution interface, representing a Commands
execution. |
| Enum | Description |
|---|---|
| Commands |
The
Commands enumeration encapsulates all the commands that Client and Server
will exchange between them via their main TCP connection. |


| Name | Description |
| attachedCnsVolBlock |
|
| attachedCnsVolFile |
|
| checksumOverhead |
Checksum overhead.
|
| dedupOverhead |
Deduplication and compression overhead.
|
| detachedCnsVolBlock |
|
| detachedCnsVolFile |
|
| fileSystemOverhead |
vSAN File system overhead.
|
| improvedVirtualDisk |
First Class Disks.
|
| iscsiLun |
The vSAN iSCSI LUNs.
|
| iscsiTarget |
The vSAN iSCSI home and target objects.
|
| namespace |
The VM home objects.
|
| other |
Other vSAN objects.
|
| spaceUnderDedupConsideration |
|
| statsdb |
The vSAN performance management objects.
|
| transientSpace |
Temporary space usage in cluster for operations like reconfiguring objects.
|
| vdisk |
The virtual disks.
|
| vmem |
The VM snapshot memory files.
|
| vmswap |
The VM swap files.
|
| VsanObjectTypeEnum_Unknown |
represent the value when the lower version client cannot recognize the enum value
|


We'd LOVE if more people would contribute to Pony Mail! Any form of contribution is most welcome, whether it be programming, documentation, evangelism, marketing, or helping out other users.
Our source repository is at: https://github.com/apache/incubator-ponymail
We currently use GitHub Issues for tracking bugs and improvements: https://github.com/apache/incubator-ponymail/issues
To contribute to Pony Mail, follow these steps:
The following workflow is adapted from the jClouds workflow:
The first thing to do is to make sure you have the ponymail Git repository configured as a remote. In this case we will add it as a remote called "ponymail":
cd ponymail git remote add ponymail https://github.com/apache/incubator-ponymail.git
When beginning working on the feature, take a branch from the latest master version:
git checkout master git fetch ponymail git reset --hard ponymail/master git checkout -b feature-branch
As we want a clean master and we should never use directly use the master branch (it should be only used to sync the fork with the upstream repo), so we can just reset hard it instead of rebasing. Develop the feature and address the review comments
Develop the feature normally, commit the changes (you can create N commits if needed), and open the pull request.
Once the pull request is open and has been reviewed, address any review comments and add the changes in new commits. This will make it easier for the reviewer to focus only in the last changes without having to go again through the entire pull request. Once the PR is ready to be merged, you'll be asked to squash the commits. Preparing the pull request to be merged
First squash the commits, to have a cleaner rebase (it is easier to rebase having one single commit than having N commits):
git rebase -i HEAD~N # Where N is the number of commits in the pull request
Now that there is only one commit, update the branch to the latest version of master:
git fetch ponymail git rebase ponymail/master
At this point the local branch with one single commit on top of the latest master and it can be pushed to your fork:
git push <your-fork's-remote> feature-branch -f # You might need to push with --force # because of the rebase to the latest master
Now the pull request will be clean with one single commit and up to date with the latest master. Ready to be merged!
The key point is to avoid updating your feature branch with master until the PR is ready to be merged (or until you're asked to rebase). This way you'll avoid accidental merge commits and fixing conflicts when you shouldn't be dealing with that. If for you want to keep your branch up to date with the latest master changes anyway, always rebase it; don't git pull or introduce merge commits, as it will complicate the rebasing process and will make it difficult to merge the pull request in a clean way
Please see this document for details on building a release.
Apache Pony Mail (Incubating) is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.


Keep an eye on your town
by John LawlessThe City of Enderby is running a recruiting campaign for the Citizens on Patrol program, looking for volunteers to make a positive impact in the community.
Citizens on Patrol will be used to spot crime or suspicious activity in the area.
"We are now entering the third year of our re-launched Citizens on Patrol program, aimed at providing another tool to help deter and prevent crime in our community," says Mayor Greg McCune. "Local volunteers are the foundation of this program, and we are looking to build our roster."
The volunteers will act as the "eyes and ears" in the community, and will be patrolling in marked vehicles. The patrol will notify the police of any suspicious activity that they observe.
For those who wish to participate, the application can be found here. Applications will be accepted until Dec 20, and all volunteers must consent to a Police Information Check and other background verification.


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<lcArea2>
A <lcArea2>
defines an area of a hotspot image that contains a correct
or incorrect choice in a hotspot assessment interaction. This element replaces the
<lcArea>
element in DITA 1.2.
Category: Interactions domain content elements


Everything you need to know about college football's Rivalry Week
by Bill ConnellyThe month of November is college football's fireworks show, and Rivalry Week is its grand finale. The majority of FBS teams are playing against their most bitter rivals, with stakes ranging from national title implications (Ohio State-Michigan) to division title hopes (Virginia Tech-Virginia) to good, old-fashioned nail-biters (the Egg Bowl and countless others).
After Tuesday and Thursday appetizers, the Rivalry Week feast gets rolling early on Friday. Let's take a chronological walk through this year's most interesting games -- what you should be watching, when and why.
All times Eastern
Tuesday
Western Michigan at Northern Illinois (7 p.m., ESPNU, ESPN App)
Western Michigan and Central Michigan are tied atop the MAC West standings, and since WMU owns the tiebreaker advantage, the Broncos need only a win against the worst NIU team in decades (the Huskies' No. 116 ranking in SP+ is their worst since 1981). Beware, though: NIU has won four MAC titles this decade, and old champs have a way of finding pride in strange moments.
SP+ projection: WMU 35, NIU 28
Other games: Ohio at Akron
Thursday
Ole Miss at Mississippi State (7:30 p.m., ESPN, ESPN App)
Plenty of schools find themselves in need of a win to reach six wins and bowl eligibility -- Boston College (at Pitt), Colorado (at Utah), Kent State (at Eastern Michigan), Michigan State (vs. Maryland), Missouri (at Arkansas), Nebraska (vs. Iowa), North Carolina (at NC State), Ohio (at Akron), Oregon State (at Oregon), Troy (vs. Appalachian State), UL Monroe (at Louisiana), perhaps Army (at Hawai'i) -- and many are facing bitter rivals.
The Egg Bowl, though, might top the win-and-you're-bowling list. Mississippi State has lost its direction in two years under head coach Joe Moorhead, and the fan base is all sorts of impatient. While he's probably not going to get fired with a loss against Ole Miss and a 5-7 finish, I, uh, wouldn't recommend it. And while four one-score losses have rendered Ole Miss 4-7, the Rebels are easily dangerous enough to beat their rivals and cause boos to ring even louder than the cowbells at Davis Wade Stadium.
SP+ projection: MSU 31, Ole Miss 26
Early Friday
Virginia Tech at Virginia (Noon, ABC, ESPN App)
Virginia has been the most consistent team in the dreadful ACC Coastal and is one win from its first division title. However, that one win will have to come against a rival the Hoos haven't beaten since 2003, when members of the current roster were as young as 2 years old.  To make matters worse, Virginia Tech has caught fire, winning its past three ACC games by an average score of 36-6 and jumping from 64th to 42nd in SP+ in a short time.
SP+ projection: UVa 27, Tech 23
Other games: Bowling Green at Buffalo, Kent State at Eastern Michigan, Miami (Ohio) at Ball State, Texas Tech at Texas, Toledo at Central Michigan
Friday afternoon
No. 19 Cincinnati at No. 18 Memphis (3:30 p.m., ABC, ESPN App)
Cincinnati has secured the AAC East title, and Memphis could do the same in the West with a win ... against Cincinnati, whom the Tigers would then face next week, as well. You could perhaps not blame the Bearcats for thinking about holding some tricks up their sleeve for next week, but they probably need a win to keep feeling good about their shots at the Group of 5's New Year's Six bowl bid.
SP+ projection: Memphis 35, Cincy 21
No. 17 Iowa at Nebraska (2:30 p.m., BTN)
Nebraska took out a month's worth of frustration on Maryland on Saturday, and the 54-7 win moved the Huskers to within a game of .500. To reach the postseason in this disappointing year, though, they'll have to beat an Iowa team that has defeated them four times in a row. Scott Frost is only 4-5 at home against Power 5 teams since taking over at his alma mater. This would be a great time for a real home-field advantage to materialize.
SP+ projection: Iowa 30, Nebraska 21
Washington State at Washington (4 p.m., Fox)
These teams were a combined 18-4 when they met in the 2017 and 2018 Apple Cups. This year, they're 12-10. Granted, they're a good 12-10 -- they're both in the SP+ top 30 and have dealt with a frustrating, and perhaps unsustainable, set of close losses (they have a combined 2-7 record in one-score finishes). But rivalry wins can change the tenor of a team's season. Is this the year Wazzu's Mike Leach finally gets one over on UW's Chris Petersen? Does Petersen salvage an unexpected transition year by moving to 6-0 against Wazzu?
SP+ projection: UW 37, Wazzu 29
Other games: Appalachian State at Troy, Arkansas State at South Alabama, Boise State at Colorado State, Missouri at Arkansas, West Virginia at TCU
Friday evening
USF at UCF (8 p.m., ESPN, ESPN App)
This rivalry hasn't produced many close games of late -- four of the past five meetings have been decided by at least 16 points -- but the last time USF headed to Orlando, the Bulls nearly pulled off an upset in one of the best games of the season. So maybe there's a little hope here, even late in a hopeless USF campaign?
SP+ projection: UCF 40, USF 12
Early Saturday
No. 2 Ohio State at No. 13 Michigan (Noon, Fox)
Saturday's early slate is maybe the most loaded of the year, especially when you factor in the start of the FCS playoffs. (Give ESPN+ a whirl this weekend and watch some of the FCS action -- especially Furman-Austin Peay and Kennesaw State-Wofford.)
That said, the floor belongs to The Game. Michigan could complete a stirring second-half turnaround by pulling off its first win over the Buckeyes in eight years -- not to mention Jim Harbaugh's first since he was the Wolverines' QB in 1986 -- and putting a dent into their rivals' national title stock. More likely, Ohio State could send the school up north back into the existential crisis from which it has recently begun to emerge.
SP+ projection: Ohio St. 30, Michigan 19
Other games: Charlotte at Old Dominion, Clemson at South Carolina, Florida International at Marshall, Georgia at Georgia Tech, Indiana at Purdue, Louisville at Kentucky, Middle Tennessee at Western Kentucky, New Mexico State at Liberty, Northwestern at Illinois, Texas State at Coastal Carolina, Tulsa at East Carolina, Wake Forest at Syracuse, Wyoming at Air Force.
Saturday afternoon
No. 5 Alabama at No. 15 Auburn (3:30 p.m., CBS)
Mac Jones has put up Tua-like numbers in his two starts this year (28-for-34, 510 yards, six TDs, no picks), though it's fair to say, since those starts were against Arkansas and Western Carolina, the bar was pretty dang low. (Like, so low it was just lying on the floor.) Still, if he looks the part at Jordan-Hare Stadium and Bama takes care of Auburn -- a team LSU and Georgia beat by only a combined 10 points -- the Tide's CFP case gets very strong, very quickly.
Auburn's not going to be willingly pushed over, though. The Tigers held LSU and Georgia to season lows in yards per play and gave up 13 fewer points to LSU than anyone else has. They are fourth in defensive SP+, and while their offense looks as if it is led by a true freshman QB (because it is), they could pretty swiftly end Bama's backdoor title hopes.
SP+ projection: Alabama 30, Auburn 22
No. 12 Wisconsin at No. 10 Minnesota (3:30 p.m., ABC)
Wisconsin's back-to-back losses against Illinois and Ohio State briefly knocked the Badgers out of Big Ten contention, but Minnesota left the door open with its loss against Iowa. The Gophers could still make a CFP case, though, with a decisive win here and an upset of Ohio State.
You like big, burly manball? There's plenty of burliness to go around in this one, though the most intriguing matchup will take form when Minnesota decides to pass. The Gophers are dynamite through the air, but Wisconsin has one of the best pass defenses in FBS.
SP+ projection: Minnesota 29, Wisconsin 28
No. 14 Baylor at Kansas (3:30 p.m., ESPN, ESPN App)
It's unlikely, but there's still a path for Baylor to make its own CFP case: the Bears win out; Auburn beats Bama; Oregon or Colorado beats Utah; Minnesota loses again; etc. But before Baylor can advance down that path, it has to avoid losing focus against a Kansas team that has had some feisty moments.
Aside from a midseason bump the Jayhawks received from an offensive coordinator change, they have been about what they were projected to be -- they were 108th in SP+ in the preseason and are 101st now. But KU beat Boston College and Texas Tech and threw a scare into Iowa State and Texas.
SP+ projection: Baylor 41, Kansas 17
Southern Miss at Florida Atlantic (3:30 p.m., NFL Network)
Conference USA was destined to have the messiest title race in FBS, and it has come to pass. According to ESPN Stats & Information's FPI ratings, each of the five teams remaining in the hunt has at least an 18% chance of reaching the title game. And two of them are playing each other here. Lane Kiffin's fightin' FAU Owls have won eight of nine overall and have risen from 83rd to 53rd in SP+ in only six weeks.
SP+ projection: FAU 32, USM 23
Other games: BC at Pitt, Maryland at Michigan State, Miami at Duke, Notre Dame at Stanford, Oregon State at Oregon, Rice at UTEP, Rutgers at Penn State, Tulane at SMU, UConn at Temple, UAB at North Texas, UNLV at Nevada, Utah State at New Mexico, UTSA at Louisiana Tech, Vanderbilt at Tennessee
Saturday evening
Texas A&M at No. 1 LSU (7 p.m., ESPN, ESPN App)
In August, I named Texas A&M's Kellen Mond the most important player in college football for the 2019 season, I said he and LSU's Joe Burrow (No. 2 on my list) had a "potential game-changing leap in them and a shot at lots of contenders." Granted, it would have been stupendous had I flipped the order there, but Mond and A&M have one more shot at an upset after having already played four of SP+'s top 11 teams. (They're 0-4 against the top teams, with two one-score losses, and 7-0 against everyone else.)
SP+ projection: LSU 37, A&M 23
Colorado at No. 7 Utah (7:30 p.m., ABC, ESPN App)
Right now, it appears that, if Georgia loses to LSU in the SEC title game, and Minnesota doesn't go 2-0 against Wisconsin and Ohio State, the two most likely candidates for the No. 4 spot in the CFP rankings are Alabama and its 2009 Sugar Bowl conqueror, Utah. (Oklahoma and Baylor are still options, obviously, but the CFP committee hasn't been particularly impressed so far.) Since Utah plays on Saturday evening, we'll know how Bama fared in the Iron Bowl, and we'll have a decent idea of what Utah might need to do to keep pace.
This is a great opportunity for Utah to send a message to the CFP committee and a national TV audience -- the Utes have been damn near merciless since their September loss to USC, beating their past seven opponents, all conference foes, by an average score of 38-9. They were the best team in the Pac-12 even before Oregon's loss to Arizona State last week. Colorado is coming off its best performance since September, but the Buffs will have to play even better to have a chance.
SP+ projection: Utah 44, Colorado 15
No. 9 Oklahoma at No. 21 Oklahoma State (8 p.m., Fox)
Downside: Oklahoma State lost starting quarterback Spencer Sanders to a season-ending thumb injury last week, and while the Cowboys won at West Virginia without him, the passing game, now without Sanders and star wideout Tylan Wallace, was based almost solely around quick, short throws -- new starter Dru Brown averaged just 8.9 yards per completion.
Upside: The last time OSU beat OU (in 2014), it was with a backup QB of sorts -- true freshman Mason Rudolph was playing in only his second collegiate game, and the Pokes won in Norman anyway. That they didn't beat OU again once Rudolph actually had his sea legs is proof that rivalry games don't have to make sense. OU is wobbly after three consecutive narrow wins; can the Pokes pull off what Iowa State, Baylor and TCU couldn't?
SP+ projection: OU 40, OSU 27
UL Monroe at Louisiana (7:30 p.m., ESPNU, ESPN App)
Billy Napier's Louisiana Ragin' Cajuns are, well, ragin' at the moment. Projected 97th in SP+, they head into this rivalry battle at 9-2 and a staggering 29th. You should watch some of this game just to get a glimpse of what has become one of the Group of 5's best teams. You should also watch because this rivalry tends to produce close games. Five of the past six meetings have been decided by a touchdown or less, and ULM, one win from bowl eligibility, has a dangerous enough offense to perhaps throw a scare into the Cajuns with just a couple of breaks.
SP+ projection: UL 46, ULM 21
Other games: Florida State at Florida, Georgia State at Georgia Southern, Iowa State at Kansas State, Navy at Houston, North Carolina at NC State
Late Saturday
Army at Hawai'i (11:59 p.m., CBSSN)
Try to hold back the tears when you realize this is our last super-late-night Hawai'i home game of the year. That alone is reason to watch, but this matchup also packs some wonderful stylistic contrast. Hawai'i throws the ball 43 times per game, and Army runs it 58 times per game. The Black Knights prevailed over the Warriors in West Point last year, grinding the game down to single-digit possessions each and surviving 28-21 with a late red zone stand. But they've lost their close-game mojo this year and stand at just 5-6; Hawai'i, meanwhile, has won four of five and just clinched a spot in the MWC title game. Who will control the tempo this time?
SP+ projection: Army 32, Hawai'i 31
Other games: Arizona at Arizona State, BYU at San Diego State, Cal at UCLA, Fresno State at San Jose State
By Saturday night, we'll know all of the conference title game matchups and almost all of the bowl-eligible teams. The potential exceptions: Missouri, which inexplicably still hasn't heard back from the NCAA on its bowl-ban appeal (an act of downright cruel indecision/noncommunication from a governing board that's pretty good at being indecisive), and Army, which might still have work to do against Navy in mid-December.
We're close to knowing most of the answers to the questions we spent the eight-month offseason asking. But first, one giant whirlwind of anxious fans and smack talk.


App delivery just got a whole lot easier.
This virtual machine is pre-configured as an all-in-one deployment of OpenShift Enterprise by Red Hat, complete with the JBoss Developer Studio. From here you can develop applications directly against the world-class OpenShift Enterprise Platform-as-a-Service.
Click below to view the OpenShift Enterprise web console. You will need these login credentials:
demo
openshift
rhc
UtilityOpen a terminal on this system (Applications - System Tools) and run the following command to get started with rhc
, the command-line utility for developing apps with OpenShift Enterprise:
$ rhc setup -l demo -p openshift
Open JBDS on this system (Applications - Programming menu), click past the splash screen, and select File - New - OpenShift Application from the menu (even to import an existing application). You will need the account credentials:
demo
openshift
This VM and applications created on it have DNS records that are only available from the BIND server contained in the VM. It is possible to resolve VM host and application names externally by adding the IP of this VM as the nameserver for the domain openshift.example.com. The method of doing this is specific to your operating system and environment; e.g. for Linux you would add this to the top of /etc/resolv.conf:
nameserver 192.168.x.x
More details are available here. The VM IP must also be reachable from the host (check with ping
).
Be aware that the cerficate of the VM web server is self-signed, and should be expected to cause a certificate warning when visited by external browsers or tools.
This host is pre-configured with a host login and OpenShift user for ease of use. The default passwords should be changed as follows.
Change the password for the host "openshift" login from the terminal window with the passwd
command:
$ passwd (enter the current password, "openshift") (enter your new password twice)
Change the password for the OpenShift "demo" user (or add other logins) from the terminal window with the htpasswd
command:
$ sudo htpasswd /etc/openshift/htpasswd demo (enter your new password twice)


Father of Everton star claims summer move was a ‘mistake’
Moise Kean’s summer switch to Everton has been labelled a mistake by the attacker’s father.
The Italy Under-21 forward joined the Toffees from Juventus in a £27million move last summer, but he is yet to score a goal for his new club having played just nine games.
The 19-year-old was also omitted from last week’s win at Southampton after reportedly being late for a team meeting.
Speaking to Centro Suono Sport, Jean Kean revealed that he hopes for his son to return to Italy ‘as soon as possible’, with AC Milan a potential destination.
“Sending my son to England was a mistake, because he’s still too young,” he said. “He’s not feeling good at Everton, I didn’t like this transfer.
“I hope he can come back to Italy as soon as possible, I hope he goes to Rome, but the important thing is that he comes back here.”
Kean Sr also revealed his unhappiness at agent Mino Raiola’s influence on his son.
“I don’t have a relationship with Raiola, I have never met him, I don’t think he even wants to see me.
“He demanded my son’s power of attorney when he was 14 and together with my ex-wife he wanted to take him to England.
“At Everton, where he is playing now, he is not settling in well. I think he was supposed to wait a few more years before he had an experience abroad.
“If there is a possibility for him to come back to Italy, I hope he can do that, so as not to ruin him.”


This dialog allows you to edit the unique identifier of a given scenario element, as specified in the dialog’s title bar.
1. All identifiers must be valid NCNames according to the W3C XML 1.0 specification. That is, they must contain no spaces, and no punctuation other than periods, hyphens, and underscores. Digits are legal but the identifier must start with a letter or underscore.
2. All identifiers must be unique throughout all scenario sections. Hexkit Editor does not currently verify this restriction but it does check for uniqueness within the identifier’s collection, e.g. the list of unit classes for a unit class ID.
3. Choosing OK or pressing Enter while the Identifier field is empty has the same effect as choosing Cancel or pressing Escape. That is, the identifier remains unchanged and the current operation is aborted.


We exchange methodologies!
- evolve viral web services
- seize open-source bandwidth
- recontextualize proactive networks
- e-enable plug-and-play bandwidth
- mesh B2C ROI
- incentivize efficient mindshare
- scale open-source portals
- e-enable strategic communities
- mesh front-end technologies
- productize plug-and-play solutions
- utilize transparent schemas
- reintermediate robust deliverables
- leverage one-to-one channels


From: Steve Braden
Newsgroups: alt.drugs
Subject: Robo dosage?
Date: May 1994
I tried DXM for the first time about two weeks ago. I took 300 mg (10 Drixoral Cough Caps @ 30mg each). Result: no effect. I took the 10 pills over the course of about 20 minutes chased with plenty of water. I did take them on a relatively full stomach, though, so maybe that was part of the problem. I'm 6'3', 280 lbs and in relatively good health.
========================================================================
From: Petri Wallenius
Newsgroups: alt.drugs
Subject: About DXM HBr (Robo) ??????
Date: Dec 1993
I have heard people having great time with DXM, but it didn't work for me. Does anyone know what's the problem. I took 375 mg of Dextrometorphan hydrobromide. Is that right compound ? If it is did I take enuff ? Or am I some kind of tolerated to that stuff ? Should I try again with greater dose ? Any help is greatly valued.
=========================================================================
From: PC
Newsgroups: alt.drugs,alt.psychoactives
Subject: ~*~ DXM SUCKS!!! ~*~
Date: May 1995
After reading the DXM FAQ and psyching myself up, I decided to take 300 mg of DXM with two other friends. To make a long story short -- IT SUCKS! All it does is that it makes you dizzy, itchy, and irritable. Not exactly my idea of recreation, and much less mind opening drug.   YUCK!!!
=========================================================================
From: bunbury
Newsgroups: alt.drugs
Subject: Re: Robitussin DM?
Date: Jan 1994
I just thought I would relate *my* experience with robo. I drank a 4 oz bottle of d-methorphan syrup (no guifenisen). While the high was not exactly unpleasant it was definitely fucked up wierd. sort of a dreamy stupor, didn't care what was going on around me, etc. the two side effects, were: one It was very difficult to urinate (this effect lasted for a couple of days), and two, the dopiness lasted (gradually wearing off) for three days. If you try robo, don't plan on going to work or doing anything significant for a couple of days, perahps you will be able to, but I couldn't, and you might not either.
In conclusion, I would have to say that one has to be feeling VERY dysphoric, and/or desperate for a high to take robo. it definitely will get you fucked up, but pleasure? not much if any.
==========================================================================
From: Todd Barnash
Newsgroups: alt.drugs
Subject: Robo'ed for the first time last nite
Date: Mar 1994
After reading, and printing out pages and pages of info on tripping from Robitussin, I decided to try it last night. I bought two 4-ounce bottles of the Robo Maximum Strength Cough (only active ingred= dextro hydrobromide) for about seven dollars at a supermarket. I downed one bottle of the nasty stuff at about 6pm, afterwhich I smoked a good size bowl. Since I was quite stoned (and on new weed) I didn't know when the effects started kicking in, I downed another two ounces from the second bottle, and by 7 pm I was starting to feel quite weird.
Lemme just say, first, that I am fairly well experienced with other assorted psychoactives- I tried this out of curiousity since Robo is, of course, cheap and plentiful.
By 7:15 or so my eyes felt very heavy and, as for the rest of the night, wouldn't focus in once place for very long... So, as any good tripper will do, I turned off the lights :-) I wasn't getting much in the way of hallucinations at that time anyway. Music sounded 'thin and boring' compared to LSD or Psilocybin, and I started becoming too disoriented and unbalanced to walk anywhere. I closed my eyes for a while and enjoyed the show- this stuff gave a big coloful boost to my imagination, and had somewhat the same 'mind-tripping' effects other psychoacts. give.
I felt a bit of stomach discomfort, which is understandable looking back on how much of it I drank. I ended up just smoking some more green and trying to sleep it off. All in all, it was a pretty heavy buzz, but not very entertaining and I doubt I would do it again.
=========================================================================
From: The Alpha and the Omega
Newsgroups: alt.drugs
Subject: Re: Robo
Date: Sep 1994
I tried it for the first time myself. I took 240mg. After about 1 hour I started to get nasueas and a little dizzy. After throwing up twice (I have a sensitive stomache) I felt better but the feeling never became more than a buzz. I didn;t particularly care for the feeling either. I was nothing like tripping as far as I'm concerned. This may be due to the dosage but I would rather not try it again because of the nasuea. Overall it was an interesting experiment but I do not see what all the rave is about. The buzz felt kind of synthetic. More related to the previous message I can say that I did experience some starnge visual problems. Especially with light and depth perception. But this is hardly tripping.
=========================================================================
From: Anonymous
Newsgroups: alt.drugs
Subject: DXM fails.... :(
Date: Apr 1994
So what's the deal?
Subject 1 ingested 3 30mg caplets, followed in two hours, by 2 more, followed in two more hours with 2 more... no perceptible results, or results so mild they might well have been placebo.
Subject 2 ingested 5 30mg caps, followed four hours later with 2 more, same effect as S1.
The next day, S2, a determined experimentor, broke 6 caps into a swallow of juice (tastes awful :) and still got nothing.
Caps were from two seperate boxes of Drixoral cough caps, no other ingredients besides DXM-hbr.....no other drugs of any kind were present in the system....
Is there some magic 'open-sesame' thing you gotta do with this stuff? What are the odds that two people, non-blood relations, would both have this Citochrome - 450 enzyme or whatever?
Perhaps if the dose were doubled to more like 300mg instead of the 120-150 that seemed such a prudent figure given the DXM FAQ info...? (it was deemed desirable to avoid the second stage of the experience as it sounded from the descriptions far less pleasurable than the lo-dose effects...)
Does the syrup work better than the caps?
Or is this all a great big hoax put on by the DEA to lure us all out of the woodwork and down to the drugstore?
Help please....it sounds real fun, if only it got you high :)
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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Cool.


The next library you will learn should definetly be ReactiveX.
What is ReactiveX?
From the website: ReactiveX is a combination of the best ideas from
the Observer pattern, the Iterator pattern, and functional programming.
(But it’s a lot more.)
The key concept to start with ReactiveX is: think reactive programming as operating on a stream of data.
Can I use ReactiveX with my favourite language?
Actually you can find a ReactiveX implementation for the following languages:
Java: RxJava
JavaScript: RxJS
C#: Rx.NET
C#(Unity): UniRx
Scala: RxScala
Clojure: RxClojure
C++: RxCpp
Ruby: Rx.rb
Python: RxPY
Groovy: RxGroovy
JRuby: RxJRuby
Kotlin: RxKotlin
Swift: RxSwift
Ok, but wait: why should I use ReactiveX?
Because it will make your life easier! Let me give you a couple of examples, based on Java/Android development.
Example 1: Nested API calls
Suppose that we need to call a remote API to authenticate a user, than another one to get user’s data and again another API to get user’s contacts.
Tipically we would have to write nested API calls like this:
Ok, maybe these APIs are not well designed, but sometimes you have to deal with it! ;-)
If we use RxJava + Retrofit (Retrofit is already compatible with RxJava), the code above will become:
Cool, right?
There are actually many ways to achieve the same result using RxJava, but they’re all better than using nested calls.
Example 2: Android - forget about AsyncTasks
For Android developers, it gets even better. RxJava (and it’s extension RxAndroid) can handle all the stuff about running long tasks in a background thread and present results on the main thread. Starting from the example above, if we want to login the user and display it’s name, we can write just some lines of code:
Ok, I know, it seems hard to understand at first. But AppObservable.bindActivity will make the network call (line 4 to 7) in a background thread, while the result will be delivered in the main thread, so we can change the view (line 8). Plus, the method is automatically binded to the activity lifecycle, so the result will not be delivered if the activity is paused.
This is super!
Good, I think I will learn it! Where should I start?
You can find many articles about ReactiveX, but only a few of them are easy to understand for a newbie.
Here is a good talk about RxJava by Ivan Morgillo at droidconDE 2015. It’s focused on Android programming only in the last part. The most of the talk covers aspects of reactive programming that can be applied to all languages.


Thirsty Thursday
Rocky Mountain Chapter
Thursday, October 16
{% include head.html %}
{% include header.html %}The saying goes that everything’s bigger in Texas. The Texas Exes, UT’s official alumni association, is no exception, with our membership of more than 100,000 forming one of the largest, most renowned alumni networks in the world.
Rocky Mountain Chapter
Thursday, October 16
Montgomery County Chapter
Thursday, October 16
Texas Exes
Friday, October 17
This is a sample announcement item.
Join us before the UT vs. Baylor football game in the Alumni Center.
RSVPIn spring 2011, UT announced it had set the ambitious goal of getting 70 percent of undergraduate...
Earlier this month, the advertising department of UT’s Moody College of Communications was renamed...
Access to JStor, an Online Library of journal articles.


Ever-passionate in computer science, I have decided to study Computer Engineering at "Politecnico di Torino".
Over the years I gained experience in the field of computer engineering and network engineering
The main objective of the MSc degree in Computer Engineering is to train engineers who can operate in sectors for the design, engineering, development, implementation and maintenance of computer applications and systems, information processing systems and complex information systems. The computer engineering graduate can work in industrial production and in the area of services to the general public and to businesses.
Computer engineering students receive a solid grounding in basic sciences (mathematics, physics, chemistry) as well as engineering sciences, providing the tools and scientific methods to ensure a rigorous approach to engineering problems. The analysis, design and maintenance of IT systems requires wide-ranging scientific knowledge in key areas of information engineering (electronics, automation, telecommunications), accompanied by thorough technological and methodological expertise in the main areas specific to computing.
I'm constantly working on different projects that you can found on my personal github page
But if you are interested to me don't miss to contact me!
If you want to contact me because you are interested in my profile, you can use the following information


{% extends "base.html" %} {% block title %}About{% endblock %} {% block content %}
Of the many services that the CRWA provides to the greater Boston community, one of those is monitoring whether it is safe to swim and/or boat in the Charles River.The CRWA Flagging Program uses a system of color-coded flags to indicate whether or not the river's water quality is safe for boating at eleven boating locations between Watertown and Boston. Flag colors are based on E. coli and cyanobacteria (blue-green algae) levels; blue flags indicate suitable boating conditions and red flags indicate potential health risks. (CWRA Website)
CRWA conducts two water quality monitoring events per week during the peak recreational season in the Lower Basin from late June to late October. During monitoring events, CRWA measures water temperature and depth and collects water quality samples at four sampling locations in the Lower Basin. G & L Laboratory in Quincy analyzes the samples for E. coli bacteria. Water temperature and depth are measured in situ with a digital field thermometer and a digital depth finder, respectively. Sampling locations are center channel sites, upstream of the following bridges: North Beacon Street, Larz Anderson Memorial Bridge, Boston University Bridge, and Longfellow Bridge. All samples are manual grab samples collected from a boat. (2019 Flagging Report - pg.3)
"E. coli are bacteria found in the environment, foods, and intestines of people and animals.  Although most strains of E. coli are harmless, others can make you sick. Some kinds of E. coli can cause diarrhea, while others cause urinary tract infections, respiratory illness and pneumonia, and other illnesses." (USGS) CRWA estimates E. coli bacteria levels using models that take into account a variety of environmental factors including rainfall and river flow. CRWA collects water samples weekly to verify the model forecasts.  Taste-and-odor compounds and toxins are of particular concern in lakes, reservoirs, and rivers that are used for either drinking water supplies or full body contact recreation." (USGS) Cyanobacteria, also called blue-green algae, are microscopic cells that naturally grow in rivers and lakes. Cyanobacteria populations can explode in warm water with excess nutrients, and exposure to these blooms can have negative health effects for humans, animals, and ecosystems. CRWA monitors cyanobacteria levels in the Charles River Basin in Boston and Cambridge during the summer and reports high levels to the Department of Public Health. (CWRA Website)
As part of our public notification program, CRWA uses statistical models to predict the likelihood that water quality will be in violation of the state geometric mean boating standard at each of our four sampling reaches. The models use antecedent rainfall, river flow, wind speed and air and water temperature to make predictions every hour throughout the recreational season. Models are necessary to produce real time water quality forecasts because E. coli analysis requires at least 24 hours between sample collection and result reporting. These hourly forecasts allow boaters to make informed decisions about their desired contact with the river based on current river water quality conditions. (2019 Flagging Report - pg.8)
CRWA's predictive models utilize live data from a HOBOlink RX3000 Remote Monitoring Station device, which is stationed at a boathouse on the Charles River. (You can download the latest raw data from this device here.) Additionally, the model utilizes data from a Waltham stream gauge via the USGS National Water Information System.
This website was built by volunteers at Code for Boston in collaboration with the Charles River Watershed Association.
This website is open source. You can view the source code and a list of contributors here. Documentation for developing and operating this website is available here.


Web Audio Api
Beat Detection Demonstration
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Option
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1
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1.3
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Instant Sound Energy
Average Sound Energy