Forensic Image Analyzer Results
The enhancement and analysis of file
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Image Colourization
Image Classification Results
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Image Details
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{{ key.title() }}
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Generated on {{ timestamp }}


-Coding in Java, C/C++/C#, Python, HTML, Javascript, CSS, SQL
-Complex World-building
-Character Design:
(Done in Paint/Paint.net)
-Story Creation:
Am currently working on several stories and have an Excel document to record any and all.
Here are a few examples:
"Super Kid: Dream Team": A story of intrigue, mystery, and adventure with a legendary hero thrown in.
"Legends of Ages": Stories of heroes, villains, and legendary items across time and space.
"Super Kid: Dimension Chaos": A story of heroes from other worlds and about their grand adventure to put their homes back to normal.
"Blazing Rails": A story of an engineer and one fateful day where his life would change forever.
"Super Kid Journeys": The legacy of a hero and his adventures.


The contradiction between dynamic user traffic and fixed data plans has drawn increasing attention in the field of mobile applications. We build a data plan sharing system named INDAPSON to consider a scenario where some smartphone users have surplus data traffic and are willing to help others download data. Virtual credits can be gained as reward, which can be used to ask for future help in downloading. To realize this model, we make the following contributions:
The paper about this system has been published in the 33rd Annual IEEE International Conference on Computer Communications (INFOCOM, 2014).
There have been many traffic light control systems around the globe, but the high cost of infrastructure and maintenance hinders their wide deployment. However, speed-advisory systems enabled by on-vehicle devices are much cheaper and easier to deploy. The first challenge of such systems is to get the traffic signal schedule in complex intersections. The second challenge is to get map information and calculate the distance.
Facing these challenges we devise and implement a speed-advisory driving system called CityDrive, which harnesses the sensor and GPS data from a wide participation of smartphones to suggest proper speed for drivers so that they arrive at intersections in green phase. CityDrive first generates a road map and then infers traffic signal schedules, using only smartphones and a server. CityDrive does not eliminate stops at intersections, but it tries to maximize the probability that vehicles cruise through intersections in green phase. Both simulation and real test show that this continuous speed advisory service effectively smoothes traffic flow and significantly reduces energy consumption.
The paper about this system has been published in the 33rd Annual IEEE International Conference on Computer Communications (INFOCOM, 2014).
Taxi dispatching systems have received intense concern in practical usage. However, these systems are usually 1) unable to give a real-time response if drivers or passengers breach the contract 2) inefficient in energy saving because of the first-come-first-serve scheme. These defects may lead to some consequences such as more energy waste and trust crisis.
We propose and implement a mobile computing system called SmartTaxiNet, which not only solves the driver-passenger matching problem efficiently but also provides other strategies, e.g. a skipper detection scheme, to raise clients' contentment. The CabMatch algorithm is designed and applied in the system to perform driver-passenger matching within a complexity of O(n2 log n). Meanwhile, based on the analysis of the accumulated matching data, the system can also estimate potential passenger locations and traffic patterns.
Indoor localization for Unmanned Aerial Vehicles (UAVs) such as quadrotors has attracted much attention. However, the low-cost Wi-Fi RSS-based localization has not been applied on the quadrotors mainly because the high-speed flight reduces the number of times for RSS measurement. Moreover, the workload of collecting RSS training data is huge for 3-D indoor localization.
In this study, we build HiQuadLoc, a new RSS-based indoor localization system for high-speed quadrotors. The key idea is leveraging the historical localization results and the motion information of the quadrotors to improve accuracy. During the RSS training data collection, we use interpolation to estimate the probability distributions of different RSS values.
Our main contributions are:
We have implemented a prototype system of HiQuadLoc. Experimental results demonstrate that HiQuadLoc reduces the average location error by more than 50% compared with normal RSS-based systems, and the workload of RSS training data collection is reduced by more than 80%.
Indoor localization based on Wi-Fi fingerprints has been an active research topic in the recent years. However, existing approaches do not consider the instability of unreliable Wi-Fi access points (APs), particularly the ones deployed by individual users. This instability impacts the localization accuracy severely, due to the unreliable or even wrong Wi-Fi fingerprints. Ideally, the localization should be done using only the welldeployed APs (e.g., deployed by the facility team of a building). However, in many places the number of these APs is too few to achieve a good localization accuracy.
To solve this problem, we leverage emerging smart APs equipped with multi-mode antennas, and build a new indoor localization system called SAPLOC to reduce the number of necessary APs. The key idea is controlling the modes of AP antennas to generate more fingerprints with fewer APs. Consequently, SAPLOC achieves a good accuracy using fewer APs, compared to existing approaches.
To address the challenges in switching antenna modes, we design:
We have implemented a prototype system of SAPLOC using smart APs and commercial smartphones. Experimental results demonstrate that SAPLOC is able to reduce the number of necessary APs by 50%, and maintain the same localization accuracy.
Fingerprint matching is adopted by a large family of indoor localization schemes, where collecting fingerprints is inevitable but all consuming. While the increasingly popular crowdsourcing based approach provides an opportunity to relieve the burden of fingerprints collecting, a number of formidable challenges for such an approach have yet been studied.
In this study, we propose a crowdsourcing based fingerprints collecting mechanism for indoor localization systems, where the important challenges including the large data amount, device heterogeneity and real time response are studied and resolved. With our approach, massive raw fingerprints will be divided into small clusters while diverse devices' uploaded fingerprints will be merged to overcome device heterogeneity, both of them will contribute to reduce response time. We build a mobile cloud testbed to verify our proposed scheme, and comprehensive real-world experiment results indicate that our scheme provides comparable localization accuracy.
Sina-Weibo produces a mass of microblogs every day. These data are very helpful for research with respect to anthropology, social networks, urban planning and other aspects.
Our purpose is to investigate whether there exists a hierarchical structure about the crowd's attention on a site or a region which is similar with the ego networks proposed by an anthropologist named Dunbar. The result can be used in studying human behavior and applied to a recommender system such as a friend recommender system which recommends friends that have the same interest.
The smart cars are equipped with XILINX FPGA. The main control components are ZEDBORAD（XILINX Zynq 7000 FPGA，CORTEX-A9）or NEXYS3 （XILINX Spartan-6 FPGA， ARM CORTEX-M0）.Camera, wireless router, supersonic detector are also available. Functions such as video capture, video transmission, smartphone control can also be easily realized.
The size and weight of a four-rotor aircraft in our experiment system can be changed by restructuring. Flight controllers are used to operate the algorithm of flight attitude control. The aircrafts can act as the carriers for camera, acceleration sensor and other wireless sensors.
Multiple-Input Multiple-Output (MIMO) technology has become an efficient way to improve the capacity and reliability of wireless networks. Traditional MIMO schemes are designed mainly for the scenario of contiguous spectrum ranges. However, in cognitive radio networks, the available spectrum is discontiguous, making traditional MIMO schemes inefficient for spectrum usage. This motivates the design of new MIMO schemes that apply to networks with discontiguous spectrum ranges.
We propose a scheme called VSMC MIMO, which enables MIMO nodes to transmit variable numbers of streams in multiple discontinuous spectrum ranges. This scheme can largely improve the spectrum utilization and meanwhile maintain the same spatial multiplexing and diversity gains as traditional MIMO schemes. To implement this spectral-efficient scheme on cooperative MIMO relays in cognitive radio networks, we propose a joint relay selection and spectrum allocation algorithm and a corresponding MAC protocol for the system. We also build a testbed by the Universal Software Radio Peripherals (USRPs) to evaluate the performances of the proposed scheme in practical networks. The experimental results show that VSMC MIMO can efficiently utilize the discontiguous spectrum and greatly improve the throughput of cognitive radio networks.
The paper about this system has been published in the 34rd Annual IEEE International Conference on Computer Communications (INFOCOM, 2015).
The Session Initiation Protocol (SIP) is used for controlling communication sessions such as voice and video calls over Internet Protocol (IP). However, most of existing SIP services are implemented over Internet Protocol v4 (IPv4). As the increasing deployment of Internet Protocol v6 (IPv6) network, it is becoming more urging to implement SIP that is compatible with both IPv4 and IPv6. This project designs a network architecture of SIP service, and proposes a way to implement SIP over IPv6 while at the same time keeping compatible with the IPv4. RTPProxy server in the network reencapsulates IPv6 traffic within IPv4 networks and vice versa, which does not require any modification on the user agent and is easy to be implemented.
The hot videos on the Internet can be pushed to mobile terminals via CMMB. When a user wants to watch a video on his/her terminal, our app checks if the very video has been pushed by CMMB. If so, the local video will be played. Otherwise the terminal will play the video on line via cellular networks such as 3G or LTE. For the case that the file of video received through CMMB is corrupted, only the lost data segments will be downloaded through cellular network, and thus the data traffic is saved. It can be expected that the combination of CMMB and cellular networks can improve user experience significantly.
We have the ability to perform spectrum sensing, channel measurement in the frequency range IEEE802.11a/b/g (including MIMO channel), and wireless data transmission. These can support the cognitive wireless communication experiment in corresponding frequency band.
Real-time online simulator can be directly connected to the computer through the USB interface, performing some functions such as code downloads, online debugging.
This device consists of ARM embedded development borad, RFID reader module, GSM/GPRS module and WIFI network card, which can be used to recognize labels such as ISO15693, ISO14443, Tag-ItTM. This device has multi-tag reading ability, as well as being able to trafer data, authenticate user and download information through GSM/GPRS/WiFi networks automatically/manually. Based on this device, we can be further developed with multimode IntelliSense WPAN and WMAN interface Terminal and Verify that the Terminal model for CR.
We set up a tri-mode terminal which has WiFi / WiMAX / GPRS three network access capability. We develop the basic communication protocol support software , basic network selection function , and the completion of a WiFi network physical layer, MAC layer , network layer information extraction.
The Space-Air-Ground networks covers space communications, high-altitude communications and ground communications. It consists of static backbone networks and dynamic non-backbone networks. In the field of ground networks, our college has gotten a lot of practical experience. Cooperating with HUAWEI, a composite network named "Innovative Wireless Campus Networks" has been built in our campus.
In the areas with no infrastructure, our multi-hop ad-hoc networks can be applied to provide transmission between different nodes. The transmission rate can be higher than 10 Mbps, and the transmission range of a single hop is larger than 30 km. The network is self-organized, and nodes can be replaced at any time without impacting the stability of our network. With all the features above, our system can still work well in a complicated environment.


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Home
Menu
Music
Jobs
Specialty Coffee and Tea
Bagels, Muffins, and Organic Snacks
Music and Poetry Readings
Open Mic Night
12312 Main
Mountain Home, CA 93923
1-888-555-5555


This is a quick outline on what to expect to have learnt by the end of day two in Moringa prep full-time course.
Ojectives of the course outline;
*Note:All that was learnt on tuesday will apply to what is done in Wednesday while learning JS.
My moringa experience has taught me how to use HTML, CSS, using Git to commute files across other developers and how to use the terminal to code using Vim and navigating through the computers directory.


MvcContrib latest release now with SubController support
One of the items that many people I know have requested are
subcontrollers. Most non-trivial web applications require many things
happening on a single screen. Even if it's only the current shopping cart
displayed on multiple screens, the MVC Framework needs a mechanism of screen
decomposition so that web applications can scale with complexity.
WebForms has the Control model where markup and logic live together and can be
composed easily.
With the MVC Framework CTP 5, a single action method has to make decisions for the entire screen. There are ActionFilters that can do some logic, but those are attributes, and attributes are not conducive to logic decomposition. Furthermore, ActionFilters do not work with partial views.
RenderPartial also doesn't do the job because the main view still has to know the partials.
If you haven't looked at MvcContrib's SubController support, have a look at the latest release and check out the samples. The samples show many uses for SubControllers for GETs, POSTs, and unlimited nesting of SubControllers. Each SubController has its own view, and it uses Action methods with all the same built-in dynamicism as regular controllers. In Fact, SubController inherits from Controller, so a SubController IS a Controller.
We (Headspring) are using MvcContrib SubControllers in real projects, and they are paying strong dividends.
I'm still hoping SubControllers will make it into the ASP.NET MVC Framework, but if they don't, I'm happy using this implementation.
You can follow


Spoonacular is a food management system which tries to combine search engine, meat planner and shopping companion functionalities.
It's API is used in FoodSearcher for ingredient search and displaying many recipes!
"Minty" Bootstrap theme
Bootswatch is a site which distributes many Bootstrap themes on a MIT license.
The site was made by Thomas Park.
FontAwesome icons
FontAwesome distributes many icons for web apps and websites!
Without them, this site would be very bland.


{% extends 'layout.html' %} {% block content %}
This page lists the apps installed on this server.


wtftitle
This is a static website generated using the Node.js-powered Metalsmith and various published and custom plugins.
This is a demonstration rather than a recommended way to build a static site. Your requirements will be different. Please use any part of the code as you wish.
Where could you use Metalsmith?
Metalsmith could be used to create:
- a fast static website with minimal server-side requirements
- technical documentation
- an eBook
- application prototypes
- build tools or project scaffolding


| PostgreSQL 9.4devel Documentation | ||||
|---|---|---|---|---|
| Prev | Up | Chapter 42. PL/Perl - Perl Procedural Language | Next |
PL/Perl can be used to write event trigger functions. In an event trigger function, the hash reference $_TD contains information about the current trigger event. $_TD is a global variable, which gets a separate local value for each invocation of the trigger. The fields of the $_TD hash reference are:
The name of the event the trigger is fired for.
The command tag for which the trigger is fired.
The return value of the trigger procedure is ignored.
Here is an example of an event trigger function, illustrating some of the above:
CREATE OR REPLACE FUNCTION perlsnitch() RETURNS event_trigger AS $$ elog(NOTICE, "perlsnitch: " . $_TD->{event} . " " . $_TD->{tag} . " "); $$ LANGUAGE plperl; CREATE EVENT TRIGGER perl_a_snitch ON ddl_command_start EXECUTE PROCEDURE perlsnitch();


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extremely low
very low
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medium
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<^Y>IMAGED
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Level of confidence that token is an accurately-transcribed word
extremely low
very low
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undetermined
medium
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Psalms 18:37
I have pursued mine enemies, and overtaken them: neither did I turn again till they were consumed.


TestEnum
enum TestEnum : Int, EnumAsSettingProtocol
Undocumented
-
Undocumented
Declaration
Swift
case One = 0
-
Undocumented
Declaration
Swift
case Two
-
Undocumented
Declaration
Swift
case Three
-
Undocumented
Declaration
Swift
var displayName: String { get }


Tuesday November 27, 2012
A strong part of the open source community is working with others. I have had the good fortune to be in a position to work closely with another applicant over the last week.
Shruti (who blogs here) lives in India and is currently a student. She found out about the GNOME Outreach Program for Women through her love of OpenStack (via Facebook) and had contacted the same mentor as myself, Iccha. Iccha introduced us via email and we have been working together as a team since that introduction.
It was funny the way it worked out, we met each other the day prior to American Thanksgiving, which Iccha being in the US celebrates and neither Shruti or I do (I'm in Canada). So there we were, neither Shruti or I really knowing what we were doing, trying to get devstack working. Off to IRC we go.
I had previously met jpich on IRC and introduced her and Shruti. We had a lively interaction understanding various error messages and reading documentation trying to get operational environments on our respective systems.
Now had Shruti or I approached a different mentor or had Iccha not introduced us, I may have spent my time flailing away by myself waiting for Iccha to resurface after her holidays. By introducing us to each other and leaving us to figure it out on our own, we filled in the gaps ourselves and continued to work away, asking questions, having doubts, making mistakes, reading documentation and having success. Success is nicer when you have someone to share it with.
I'm not sure if this is quite the way the GNOME Outreach Program for Women is supposed to work, but this is how it is working for us. We have a daily email thread where Shruti and I share with Iccha our initial topic for the day with intended next steps. This allows for feedback and suggestions from the other two. When one of us is unavailable perhaps the other can offer something supportive if only an ascii smile.
We have good conversations with other OpenStack mentors and OpenStackers not involved in the program at all. Turns out they are genuinely nice even if they don't know we are applicants.
I also think we encourage each other. Having another applicant to work with is a better gauge of accomplishment than comparing ones work with the mentor. I think it heartens me to work with another applicant and I am glad it is Shruti. She is friendly and intelligent and a hard worker.
I really like the energy we have created between and amongst us during the application process and I hope we can continue to grow and expand it during the execution of the program.
Thanks for reading,
Anita Kuno.


PlatformName
@available(*, deprecated, renamed: "Device")
enum PlatformName : String
Enum that represents an iOS platform
-
the platform is notAvailable
Declaration
Swift
case notAvailable = "notAvailable"
-
the platform is an iPhone2G.
Declaration
Swift
case iPhone2G = "iPhone2G"
-
the platform is an iPhone3G.
Declaration
Swift
case iPhone3G = "iPhone3G"
-
the platform is an iPhone3GS.
Declaration
Swift
case iPhone3GS = "iPhone3GS"
-
the platform is an iPhone4.
Declaration
Swift
case iPhone4 = "iPhone4"
-
the platform is an iPhone4S.
Declaration
Swift
case iPhone4S = "iPhone4S"
-
the platform is an iPhone5.
Declaration
Swift
case iPhone5 = "iPhone5"
-
the platform is an iPhone5C.
Declaration
Swift
case iPhone5C = "iPhone5C"
-
the platform is an iPhone5S.
Declaration
Swift
case iPhone5S = "iPhone5S"
-
the platform is an iPhoneSE.
Declaration
Swift
case iPhoneSE = "iPhoneSE"
-
the platform is an iPhone6.
Declaration
Swift
case iPhone6 = "iPhone6"
-
the platform is an iPhone6Plus.
Declaration
Swift
case iPhone6Plus = "iPhone6Plus"
-
the platform is an iPhone6S.
Declaration
Swift
case iPhone6S = "iPhone6S"
-
the platform is an iPhone6SPlu.
Declaration
Swift
case iPhone6SPlus = "iPhone6SPlus"
-
the platform is an iPhone7.
Declaration
Swift
case iPhone7 = "iPhone7"
-
the platform is an iPhone7Plus.
Declaration
Swift
case iPhone7Plus = "iPhone7Plus"
-
the platform is an iPhone8.
Declaration
Swift
case iPhone8 = "iPhone8"
-
the platform is an iPhone8Plus.
Declaration
Swift
case iPhone8Plus = "iPhone8Plus"
-
the platform is an iPhoneX.
Declaration
Swift
case iPhoneX = "iPhoneX"
-
the platform is an iPhoneXS.
Declaration
Swift
case iPhoneXS = "iPhoneXS"
-
the platform is an iPhoneXSMax.
Declaration
Swift
case iPhoneXSMax = "iPhoneXSMax"
-
the platform is an iPhoneXR.
Declaration
Swift
case iPhoneXR = "iPhoneXR"
-
the platform is an iPhone11.
Declaration
Swift
case iPhone11 = "iPhone11"
-
the platform is an iPhone11Pro.
Declaration
Swift
case iPhone11Pro = "iPhone11Pro"
-
the platform is an iPhone11ProMax.
Declaration
Swift
case iPhone11ProMax = "iPhone11ProMax"
-
the platform is an iPodTouch1G.
Declaration
Swift
case iPodTouch1G = "iPodTouch1G"
-
the platform is an iPodTouch2G.
Declaration
Swift
case iPodTouch2G = "iPodTouch2G"
-
the platform is an iPodTouch3G.
Declaration
Swift
case iPodTouch3G = "iPodTouch3G"
-
the platform is an iPodTouch4G.
Declaration
Swift
case iPodTouch4G = "iPodTouch4G"
-
the platform is an iPodTouch5G.
Declaration
Swift
case iPodTouch5G = "iPodTouch5G"
-
the platform is an iPodTouch6G.
Declaration
Swift
case iPodTouch6G = "iPodTouch6G"
-
the platform is an iPodTouch6G.
Declaration
Swift
case iPodTouch7G = "iPodTouch7G"
-
the platform is an iPad.
Declaration
Swift
case iPad = "iPad"
-
the platform is an iPad2.
Declaration
Swift
case iPad2 = "iPad2"
-
the platform is an iPad3.
Declaration
Swift
case iPad3 = "iPad3"
-
the platform is an iPad4.
Declaration
Swift
case iPad4 = "iPad4"
-
the platform is an iPad5.
Declaration
Swift
case iPad5 = "iPad5"
-
the platform is an iPad6.
Declaration
Swift
case iPad6 = "iPad6"
-
the platform is an iPad7.
Declaration
Swift
case iPad7 = "iPad7"
-
the platform is an iPadMini.
Declaration
Swift
case iPadMini = "iPadMini"
-
the platform is an iPadMini2.
Declaration
Swift
case iPadMini2 = "iPadMini2"
-
the platform is an iPadMini3.
Declaration
Swift
case iPadMini3 = "iPadMini3"
-
the platform is an iPadMini4.
Declaration
Swift
case iPadMini4 = "iPadMini4"
-
the platform is an iPadMini5.
Declaration
Swift
case iPadMini5 = "iPadMini5"
-
the platform is an iPadAir.
Declaration
Swift
case iPadAir = "iPadAir"
-
the platform is an iPadAir2.
Declaration
Swift
case iPadAir2 = "iPadAir2"
-
the platform is an iPadAir3.
Declaration
Swift
case iPadAir3 = "iPadAir3"
-
the platform is an iPadPro9Inch.
Declaration
Swift
case iPadPro9Inch = "iPadPro9Inch"
-
the platform is an iPadPro10Inch.
Declaration
Swift
case iPadPro10Inch = "iPadPro10Inch"
-
the platform is an iPadPro11Inch.
Declaration
Swift
case iPadPro11Inch = "iPadPro11Inch"
-
the platform is an iPadPro12Inch.
Declaration
Swift
case iPadPro12Inch = "iPadPro12Inch"
-
the platform is an iPadPro12Inch2.
Declaration
Swift
case iPadPro12Inch2 = "iPadPro12Inch2"
-
the platform is an iPadPro12Inch3.
Declaration
Swift
case iPadPro12Inch3 = "iPadPro12Inch3"
-
the platform is an simulator.
Declaration
Swift
case simulator = "simulator"


This is designed to test onlytopic.in.map=true. If this file was copied from src/ then the test fails, and the copied content will not match this file.


Watch it.
Shop it:
Collection Autumn / Winter 2020.
You like what you see?
You can buy the
Products from the video
right here.
Boots
brown
149,90 €
Shop now
Shoes
139,90 €
Shop now


ThisBest Buy.com has ReCore Xbox One Digital Download) on sale for $19.99. Note: A Best Buy account is required. Instructions to redeem are usually emailed within 1 hours. However, if you prefer a physical copy, Best Buy.com has ReCore w/ Bonus Skin (Xbox One) on sale for $19.99 or less $15.99 for Gamer's Club Unlocked Members. Shipping is free. Alternatively, Amazon.com also has ReCore (Xbox One) on sale for $19.99. Shipping is free with Prime or if you spend $49 or more.

Cipher7
Yesterday at 04:06 AM
PC not working?
kinglet179
Yesterday at 04:22 AM
Quote from Cipher7
PC not working?
Just bought one for PC 10 mins ago. I probably bought the last copy for $19....


Why a retreat?
We are all gathering in Bali for one week to work together in better environment. These are not holidays, see it as a more relaxed company time in a different environment.
The main goal of the retreat is to get to know the whole team. Make sure you do not always stay with your usual collegues and mingle. Do not be afraid, none of them bite!
We will also have activites, some optional, some mandatory. Come and join as many as you want and let's have a blast!
Make sure to let the Operations team know if you need anything. We are not here to nurse you, but we can try to help!
Schedule
Here is the schedule for the week of the retreat.
-
8:30 PM
Travel - Office to PVG airport
Ops have arranged a bus.
-
7:10 AM
Arrival in Bali
Get your passport and documents ready. -
8 AM
Travel - Airport to hotel
Ops have arranged a bus. -
10 AM onwards
Arrival at the hotel / Free time
Settle down and enjoy the rest of the day.
-
7 AM
Breakfast
Make sure to remember your room number. -
11 AM - 5:30 PM
Team building & Team lunch
Attendance is mandatory. -
8 PM onwards
Free time
Just enjoy Bali!
-
7 AM
Breakfast
Make sure to remember your room number. -
8 AM - 5:30 PM
Team building & Team lunch
Attendance is mandatory. -
5:30 PM onwards
Free time
Just enjoy Bali!
-
7 AM
Breakfast
Make sure to remember your room number. -
9 AM - 12 PM
Work time
To be decided by each team. -
12 PM onwards
Free time
Just enjoy Bali!
-
7 AM
Breakfast
Make sure to remember your room number. -
9 AM - 12 PM
Work time
To be decided by each team. -
12 PM onwards
Free time
Just enjoy Bali!
-
7 AM
Breakfast
Make sure to remember your room number. -
9 AM - 12 PM
Work time
To be decided by each team. -
12 PM onwards
Free time
Just enjoy Bali!
-
7 AM
Breakfast
Make sure to remember your room number. -
9 AM - 12 PM
Work time
To be decided by each team. -
12 PM onwards
Free time
Just enjoy Bali!
-
7 AM
Breakfast
Make sure to remember your room number. -
9 AM - 12 PM
Work time
To be decided by each team. -
12 PM onwards
Free time
Just enjoy Bali!
-
7 AM
Breakfast
Make sure to remember your room number. -
12 PM
Check out
You can still leave the luggage at the hotel. -
4 PM
Travel - Hotel to airport
Ops have arranged a bus.
-
7:05 AM
Arrival in Shanghai
Note: Arrange transportation on your own.
FAQ
A few things that are important for you to make the stay of the team as awesome as it can.
- Bus (Oct 24, office to airport, Nov 2, hotel to airport)
- Flight (Oct 24, Shanghai - Bali, Nov 2, Bali - Jakarta - Shanghai)
- Travel insurance
- Hotel & Breakfast (Oct 25 - Nov 2)
- Team building & Team lunch (Oct 26)
- Team building & Team lunch (Oct 27)
- Passport with minimum validity of 6 months
- A return ticket or through ticket
- Proof of accommodation arrangements
- Disembarkation card for foreigner
Item 4 should be handed out onboard or be found in Bali airport.
Activites
Take a peek at the activities you can enjoy in Bali.


plotters.deep package¶
Submodules¶
plotters.deep.pca module¶
-
plotters.deep.pca.
apply_pca
(X: numpy.ndarray, pca: sklearn.decomposition.pca.PCA)¶ To apply PCA, this method can be used. Parameters ———- X: numpy.ndarray, required
This is the matrix, however, note that it is user’s (caller’s) responsibility to assure that if there was any normalization involved in the computation of the PCA, the same normalization should have already been applied to this parameter before applying this function. Otherwise, the output will be unreliable.
- pca: sklearn.decomposition.PCA, required
The PCA to be applied
- output: numpy.ndarray
The output matrix after applying the pCA
-
plotters.deep.pca.
get_pca_transform
(X: numpy.ndarray, number_of_components: int = 2, normalization: str = None) → sklearn.decomposition.pca.PCA¶ The
get_pca_transform()
returns the PCA transform on this data, using the Sci-Kit learn PCA functionalities. Parameters ———— X: numpy.ndarray, requiredThe data which is a two-dimensional matrix, in which each row is a feature-vector.
- number_of_components: int, optional (default=2)
The number of components in the PCA.
- normalization: str, optional (default=None)
The normalization type, which is either None which means no normalization, or minmax or zscore.
- pca: sklearn.decomposition.PCA
The PCA for this data.
plotters.deep.tsne module¶
-
class
plotters.deep.tsne.
TSNEAgent
(configurations=None)¶ Bases:
object
The
TSNEAgent
helps with providing the user with the t-sne related functionalities, allowing mechanisms such as making tsne movies, etc. This work is highly inspired by the t-SNE tutorial by oreillymedia in https://github.com/oreillymedia/t-SNE-tutorial.-
find_tsne_projections
(X: numpy.ndarray, perplexity: float = None) → numpy.ndarray¶ The
find_tsne_projections()
helps with building the projections of tsne. Parameters ———- X: numpy.ndarray, requiredThe data as a numpy array of shape: (number_of_data, element_dimension)
- perplexity: float, optional (default=None)
If this value is provided, the perplexity determined by the configuration will be overrided. This parameter is here because it is probable for the user to try to have multiple perplexities tested, as it is a natural thing to do when it comes to t-SNE.
The output of this function is a numpy.ndarray which has the shape equal to the number of points times the number of t-SNE components, as specified beforehand in the configurations.
-
make_a_tsne_movie
(X: numpy.ndarray, y: numpy.ndarray, movie_path: str) → None¶ The
make_a_tsne_movie()
helps with making a t-SNE movie. This is essentially useful when we have a slow-converging process, and having a movie can help shedding light on the path from bad locations to possibly good ones in the space. Parameters ———- X: numpy.ndarray, requiredThe data as a numpy array of shape: (number_of_data, element_dimension)
- y: numpy.ndarray, required
The one-dimensional array of labels.
- movie_path: str, required
The filepath to the movie. Note that the folder should exist and the image should be in .gif format.
The output of this function is a numpy.ndarray which has the shape equal to the number of points times the number of t-SNE components, as specified beforehand in the configurations.
-
process_configurations
() → None¶ This function looks through the configuration file and finds the preferences and/or sets defaults
-
set_random_state
(seed: int) → None¶ The
set_random_state()
can be used to set the random state of the class. Parameters seed: int, requiredan integer to set the random seed for this module. It is better to fix a random seed in order to be able to recreate results.
-


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{% include "includes/account-name-number.html" %}Review an apprenticeship
Add the details of your apprenticeship below. If you don't have the information now you can leave it blank and add it later
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Training code:
9267
Level:
2
Change training
Mechatronics technician
Training code:
4563
Level:
4
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Oh the places you'll go!! Here's a comprehensive list of Kelsey and Alex's favorite places to go!! Enjoy"
Click here for more information!
Thanks for viewing our recommendations!!


Among the many publications, Massimo Menichinelli has also authored, edited or co-authored several books.
Mention, A.-L., & Menichinelli, M. (Eds.). (2021). From Research to Innovation: Exploring the Translation Journey with OpenInnoTrain (1st ed.). RMIT University Press. https://doi.org/10.5281/zenodo.5536932
How can we transform research insights into innovation and impact? This is the first book from the OpenInnoTrain H2020 MSCA-RISE project about this topic.
This book is published in English.
Menichinelli, M. (2020). Open and collaborative design processes—Meta-Design, ontologies and platforms within the Maker Movement. Aalto University. http://urn.fi/URN:ISBN:978-952-64-0091-4
How can participants in distributed systems collaboratively work together through tools and platforms for the designing and managing of collaborative processes? This book is the doctoral dissertation of Massimo Menichinelli for his doctorate in New Media at Aalto University - School of Arts, Design and Architecture - Department of Media - Aalto Media Lab.
This book is published in English.
Download it here.
Watch the video of the doctoral defense here; slides available here. Press release is here.
Menichinelli, M., Bosqué, C., Troxler, P., Raspanti, C., Schaub, A., & Neves, H. (2015). Fab lab : la révolution est en marche. (M. Menichinelli, Ed.). Paris: Editions Pyramyd.
The book details the emergence of Fab Labs, the philosophy behind them, and their commercial aspects, as well as the techniques, methods and processes used. A real-world example is presented in depth, and then 27 noteworthy projects and products are featured. Finally, it contains the interviews to early pioneers of the global community.
The first edition of this book was published in French; two further edition have been published, in English and Japanese.
You can read more about the French edition here.
Menichinelli, M. (Ed.). (2017). Fab Lab. Revolution Field Manual. niggli Verlag.
You can read more about the English edition here.
マッシモ・メニキネッリ, & 田中浩也. (2020). ファブラボのすべて イノベーションが生まれる場所 (高崎拓哉, Trans.). ビー・エヌ・エヌ新社.
You can read more about the Japanese edition here.
Menichinelli, M. (2016). Fab Lab e maker. Laboratori, progettisti, comunità e imprese in Italia. Macerata: Quodlibet.
This book details the history of the Fab Lab and Maker Movement, globally and in Italy. It explains the phisolophy, tools, techniques of Fab Labs and Digital Fabrication, exploring the social, economic and organizational dimensions of the global and Italian community. Furthermore, the book contextualized the work done by makers and Fab Labs within the most recent trends in design practice and research.
This book is published in Italian.
Read more here.
Menichinelli, M., & Ustarroz Molina, M. (Eds.). (2018). Understanding Collective Awareness Platforms with the Maker Movement. Results, reflections and future strategies from the Horizon 2020 MAKE-IT project (1st edition). Barcelona: Institute for Advanced Architecture of Catalonia. Retrieved from http://make-it.io/book/
MAKE-IT is a Horizon 2020 European research project focused on how the role of Collective Awareness Platforms (CAPS) enables the growth and governance of the Maker movement, particularly in relation to ICT, using and creating social innovations and achieving sustainability. This book collects results, reflections from the project and strategies for keeping the work and exploitation of the results in the future.
This book is an introduction of the work done during 2016 and 2017 within the MAKE-IT project.
This book is published in English.
Download it here.
Bianchini, M., Menichinelli, M., Maffei, S., Bombardi, F., & Carosi, A. (2015). Makers’ Inquiry. Un’indagine socioeconomica sui makers italiani e su Make in Italy. Milano: Libraccio Editore. Retrieved from http://makersinquiry.org/
The idea of the Makers' Inquiry is simple: it is an open and replicable research format, aiming at exploring the condition of makers who operate in a certain geographical reality. The first edition was tested in Italy during 2014. Then other researchers could carry out the survey in their own countries. Therefore, in this way, it would be possible to extend over time the database and compare the results at international level.
This book is published in Italian.
Download it here.


--- layout: post title: SCaLE 13x date: '2015-02-16' author: Lomeli12 categories: - conventions tags: - scale ---
Just wanted to make a quick post and annouce that I'll going to SCaLE (Southern California Linux Expo) this year, so if you happen to also be going, you might see me (though how you would do that when I haven't shown my face is beyond me)
If you want to know more about SCaLE and perhaps even want to go yourself, you can find more info at: http://www.socallinuxexpo.org/scale/13x


Measure recognizing 1915 events as 'genocide' blocked again in US Senate
by DAILY SABAH WITH AFPA Republican lawmaker on Thursday blocked a US Senate resolution recognizing the 1915 events as "Armenian genocide," the second time in a week.
Senator David Perdue prevented a bipartisan effort to pass the resolution by unanimous consent, arguing that its passage during a sensitive period "would undermine the administration's commitment to overcoming real challenges in our bilateral relationship with Turkey."
The move angered Senate Democrat Robert Menendez, whose effort had been rebuffed the previous week after Republican lawmakers met with visiting Turkish President Recep Tayyip Erdogan.
"It is amazing to me that the greatest superpower on the face of the earth just can't speak truth of history," Menendez fumed.
"I'm not going to relent," he said.
Turkish officials have condemned the House resolution, while Turkish Foreign Ministry summoned U.S. Ambassador David Satterfield to express Ankara's strong opposition to the bill.
Turkey objects to the presentation of the 1915 incidents as a "genocide," rather calling them a tragedy in which both Turks and Armenians suffered casualties in the heat of World War I.
Ankara has repeatedly proposed the creation of a joint commission of historians from Turkey and Armenia under the supervision of international experts to examine the issue.


Functional Specification¶
Background¶
Natural resource assessments, such as inventory or monitoring campaigns, typically involve sampling a relatively limited portion of the landscape of interest. Traditionally, these samples are statistically extrapolated across a landscape based on a simple random or stratified random sampling design. However, the emergence of remote sensing systems has fueled a growing interest in imputation models built to use remotely-sensed data and field plots as training examples. The models, which are increasingly applying machine learning algorithms for the task, can be applied to generate wall-to-wall maps that “fill in the gaps” between forest plots measured on the ground based on remotely-sensed predictor variables.
Misalignment between field-measured plots and remote sensing data introduces error into predictive models trained to classify or quantify forest conditions. More precise and accurate co-registration of field plots with remotely sensed data can thus help reduce the error introduced into predictive models approach and increase the precision with which varying forest conditions across the landscape can be distinguished.
The primary goals of this project are:
- Providing a set of functions that generate 3D point clouds representing trees based on tree measurements that are commonly collected in the field
- Interactive 3D visualization of a list of measured trees
- Implementation of an optimization algorithm which minimizes misalignment of trees simulated from ground-based measurements with a point cloud collected by an airborne laser scanner (lidar)
- Reporting goodness-of-fit and corresponding model parameters from the optimization
- 3D visualization of the optimization process
User Profile¶
The user is a forest manager interested in forest inventory or forest stand mensuration. They understand parameters usually measured during forest inventories, including tree species, diameter at breast height, height to live crown, etc. They also have an intuition for reasonable forms of trees and common differences between different species and sizes of trees.
The user knows how to browse the web, and can download, install, and run software packages if a clear set of reproducible instructions are provided. They probably cannot program in Python. They would probably be able to execute a Jupyter Notebook if the setup of the computing environment can be handled for them (e.g., using Binder to host a Jupyter Notebook).
Data Sources¶
There are two types of data used in this project:
- Field-based measurements of forest plots and trees, identifying plot location, stem location, tree diameter, tree height, species, etc. These will be formatted as text files containing lists of trees with associated parameters, and list of plots with associated parameters. Example plot data (stem maps and associated tree measurements) have been gathered from publicly-available sources for the Wind River Experimental Forest and HJ Andrews Experimental Forest.
- Lidar point clouds collected from airborne laser scanning which overlap the forests where field measurements have been collected. These point clouds are generally formatted as LAS (or compressed as LAZ) files produced by lidar vendors. Example lidar point clouds from publicly-available sources have been gathered from the HJ Andrews and Wind River forest areas.
Use Cases¶
A. Checking Format of a User-Provided Data¶
Objective: The user wants to check whether a treelist they have prepared conforms with formatting requirements for 3D modeling and optimization using this package.
Interactions:
- The user opens a Jupyter Notebook named
01_Check Data Formats.ipynb
. - The user reads instructions in the Notebook directing them to execute cells one-at-a-time in the Notebook.
- Into a Jupyter Notebook cell, the user types in a path to the treelist saved as a textfile or stored in memory as a Pandas DataFrame. (Optional ->) The user types in a path to the lidar point cloud file saved as a LAS or LAZ file). These are assigned to Python objects when the user executes this cell.
- The user executes the next Jupyter Notebook cell which calls a function that loads the inputs and checks their formatting, including whether coordinates of trees in the tree list fall entirely within the footprint of the lidar point cloud. The function returns a message indicating whether the user’s tree list (and point cloud) conform to the formatting requirements for this package.
- If the user-provided tree list (and/or point cloud) did not meet specifications, the function returns an error message indicating the source of non-compliance and documentation or links to documentation with formatting requirements including field names and formats.
B. Inspecting Parameters of the 3D TreeModel, Visualizing a Single Tree¶
Objective: The user wants to see which parameters are involved in the generation of the 3D TreeModel, and manipulate those parameters interactively to change the shape of a tree.
Interactions:
- The user opens a Jupyter Notebook named
02_Visualize a Single Tree in 3D.ipynb
. - The user reads instructions in the Notebook directing them to run all the cells in the Notebook.
- The user executes all cells in the Notebook.
- The user is presented with a 3D graphic using default 3D TreeModel parameter settings. Slider widgets are laid out with the graphic labeled for each 3D TreeModel parameter.
- The user moves a slider widget for a 3D TreeModel parameter.
- The graphic reacts to user inputs, updating the 3D TreeModel (near-)instantaneously.
- The user grabs, rotates, etc. the 3D graphic to visually inspect the tree’s shape.
C. Drawing a Forest Plot in 3D¶
Objective: The user wants to visualize a list of several measured trees in 3D. Optionally, they may also want to see how this visualization of their tree list compares with a lidar point cloud.
Interactions:
- The user opens a Jupyter Notebook named
03_Visualize a Forest Plot in 3D.ipynb
. - The user reads instructions in the Notebook directing them to execute cells one-at-a-time in the Notebook.
- In a Jupyter Notebook cell, the user types in a path to a text file containing a list of trees or the name of a Pandas DataFrame containing a list of trees. (Optional ->) The user also types in a path to a lidar point cloud file saved as a LAS or LAZ file. The treelist (and optionally, point cloud) are assigned to Python objects when the user executes this cell.
- The user executes the next Jupyter Notebook cell, which calls a function that checks if the tree list (and lidar point cloud) is formatted correctly, returning an appropriate error message if not. If the input data are formatted correcly, the cell returns an interactive graphic showing the 3D model of the tree list, optionally overlaid with a lidar point cloud.
- The user grabs, rotates, etc. the 3D graphic to visually inspect the plot.
D. Co-registering a Tree List with a Lidar Point Cloud¶
Objective: The user wants to estimate the location of a field-measured tree list within a lidar point cloud covering the same area.
Interactions:
- The user opens a Jupyter Notebook named
04_Co-register a Tree List with a Lidar Point Cloud.ipynb
. - The user reads instructions in the Notebook directing them to execute cells one-at-a-time in the Notebook.
- In a Jupyter Notebook cell, the user types in a path to the tree list text file or the name of a Pandas DataFrame, as well as a path to the lidar point cloud file. These are assigned to Python objects when the user executes this cell.
- The user executes a Jupyter Notebook cell which runs a function to check the input formatting and begins the optimization routine if the inputs are formatted correctly. The optimization routine provides graphical or text updates during the optimization process, such as the number of simulations to be conducted and the value of the objective function at periodic increments.
- When the optimization is completed, the user executes another Jupyter Notebook cell, which produces a table output summary of the optimization results.
- The user executes another Jupyter Notebook cell, which produces a 3D visualization showing the optimal co-registration of the simulated 3D TreeModels for their treelist and the point cloud they provided.
- (Optional) The user executes another Jupyter Notebook cell, which produces a 3D visualization where they can see how the simulated 3D TreeModels changed over time during the optimization.


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Course Details:This Quiz tests your basic knowledge in JavaScript.It contains 5 question,each 2marks and there is no time limit.Maximum Score(10marks)
You shall get your results immediately you submit your work.Let's Begin!
1.Which is NOT a primitive data type in JavaScript?
2.How would one declare a string variable?
3.Which of these will throw a syntax error?
4.What is the difference between a while loop and a do...while loop?
5.Which method of an Array object adds and/or removes elements from an array?


[days2]
[days1][days0] :
[hours1]
[hours0] :
[mins1]
[mins0] :
[secs1]
[secs0]
[days] : [hours] : [mins] : [secs]


Grading
Turning in work and late policy
Late work will
receive no credit. You will turn in project milestones
via email or canvas (TBD).
Cheating policy
I have a no tolerance policy on cheating, which includes
copying from friends and plagarism. If you get caught
cheating, you will get an F in this class and I will
turn you into the univerisity's academic integrity
group.
Quizzes
I will give you full credit on your
lowest quiz grade for the quarter. That way, if you need
to miss a class and there is a quiz, you won't be
penalized. If you take all of the quizzes, I will
replace your lowest quiz score with full credit.
Leading a lecture
My goal is for all of you to
get full credit for leading a lecture! Here's how I will
break down the points for your grade when you lead a
lecture:
-
(8 points) -- pick meaningful optional
reading. Should have 2-3 optional reading items.
-
(9 points) -- The presentation itself (should be
15-20 minutes long) that goes over (1) background on
the required reading, (2) a balanced view of the
issue at hand, and (3) a summary of the optional
reading and why you picked it.
-
(8 points) -- In class discussion. Create good
questions, make sure there is a lively discussion.
As a challenge to the entire class: come prepared to
class so that you can discuss the topics in a lively
debate. Since your grade depends on it, please do make
sure that you come to class prepared to debate.
Grade breakdown
Your grade will be composed of
the following items:
| Item |
Percent |
Description |
| Quizzes | 25% |
Five quizzes worth 5% each
|
| Research project | 50% |
Pick topic and group 5%, proposal 5%, midterm
report 5%, final presentation 15%, final report
and results 20%
|
| Presentations | 25% |
|
Grade scale
I grade on a straight grade scale. Although most of the
points in this class will come towards the end of the
quarter, the milestones will help give you a sense of
how well you are doing on the final project.
| Grade |
Score |
| A | [93, 100] |
| A- | [90, 93) |
| B+ | [87, 90) |
| B | [83, 87) |
| B- | [80, 83) |
| C+ | [77, 80) |
| C | [73, 77) |
| C- | [70, 73) |
| D | [60, 70) |
| F | [0, 60) |


Welcome to the National Pulse, you can now see what is trending in the U-report community.
Loading National Pulse... Please wait, This may take a while.
{% extends "base.html" %} {% load static %} {% load i18n %} {% block national-pulse-active %}current-page{% endblock %} {% block content %}


{{ partial "analytics" . }}
{{ replace .Site.Copyright "{year}" now.Year }} Generated by HUGO with ❤


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/string_lt.20doesn't.20match.20its.20spec.html ---
@Gabriel Ebner @Sebastian Ullrich I started trying to prove that string.lt
is a total order, and then I discovered it's not true:
#eval to_bool ([1, 2] < [2, 1]) -- tt #eval to_bool ([2, 1] < [1, 2]) -- tt
Surely this is a bug?
Even worse, it behaves differently (correctly) on actual strings:
#eval to_bool ("ab" < "ba") -- tt #eval to_bool ("ba" < "ab") -- ff #reduce to_bool ("ba" < "ab") -- tt example : "ba" < "ab" := dec_trivial
I'm using this in mathlib:
inductive lex (r : α → α → Prop) : list α → list α → Prop | nil {} {a l} : lex [] (a :: l) | cons {a l₁ l₂} (h : lex l₁ l₂) : lex (a :: l₁) (a :: l₂) | rel {a₁ l₁ a₂ l₂} (h : r a₁ a₂) : lex (a₁ :: l₁) (a₂ :: l₂)
Feel free to poach
Right, an inductive definition is certainly nicer here
here's the decidability proof, although it needs rejiggering for core:
instance decidable_rel [decidable_eq α] (r : α → α → Prop) [decidable_rel r] : decidable_rel (lex r) | l₁ [] := is_false $ λ h, by cases h | [] (b::l₂) := is_true lex.nil | (a::l₁) (b::l₂) := begin haveI := decidable_rel l₁ l₂, refine decidable_of_iff (r a b ∨ a = b ∧ lex r l₁ l₂) ⟨λ h, _, λ h, _⟩, { rcases h with h | ⟨rfl, h⟩, { exact lex.rel h }, { exact lex.cons h } }, { rcases h with _|⟨_,_,_,h⟩|⟨_,_,_,_,h⟩, { exact or.inr ⟨rfl, h⟩ }, { exact or.inl h } } end
Last updated: Apr 24 2020 at 19:02 UTC


This sample app demonstrates using assets
to transfer LWM2M Data over AirVantage. It's also a working utility to provide info about apps running on a remote target.
To use this app, you should understand how to Connect to AirVantage.
You also need to understand how to Install apps over AirVantage.
There's more detailed info on Assets in the cdef
docs available.
The AirVantage sample apps aren't installed with the framework by default. Use AirVantage to install and start/stop the sample app: Install apps.
The app presents the following info over AirVantage for each installed app:
Copyright (C) Sierra Wireless Inc. Use of this work is subject to license.


The process of building reports and dashboards is iterative. As data is constantly refreshed and business requirements change, it is expected that your reports and dashboards might also change; both in what filters or slicers you might have and also in what report elements, charts, and cards you have. For this reason, it is crucial that Power BI supports this iterative process. Through Power BI's innate functionality to pin live report pages to a dashboard, you can ensure that you aren't using old data and the visuals on your dashboards reflect changes live.
To continue the module scenario, you have built a few reports for Tailwind Toys. Several months go by, and the business requirements in the Sales team change, where they want you to change and add a few more visuals to the reports. When deploying your reports to Power BI service and creating dashboards, you want to ensure that you won't have to keep publishing new reports and dashboards every time a change occurs. You want to make sure that your changes are shown live. By using the pinning live reports to a dashboard feature from Power BI, you can complete this task in an intuitive manner.
When you pin a visual, you can add it to a new or an existing dashboard. You can do the same with entire reports; when you pin a report page, all visuals on the report will be pinned to a dashboard and they are also live, meaning that any changes you make on the report will be immediately reflected on the dashboard that you have pinned the report to.
Pinning a live page is a simple way to pin all visuals at once so that you don't have to do any reformatting on the dashboard. To pin a live page, select the ellipsis (...) on the navigation bar of the report and then select Pin a live Page.
After you have made the selection, you can choose whether you want to pin this report to a new dashboard or an existing one. For this scenario, you want to pin your report to a new dashboard called Sales Figures.
After selecting Pin live, you will be redirected to a new window where you can see your dashboard. On the dashboard, you can modify the visuals as needed. Note that all your slicers and filters still work and that the visuals have the same data as in the report.
Any changes that you make to the tickets report will automatically show on the dashboard when the page is refreshed. In Power BI Desktop, you can make changes to your visuals or data as needed and then deploy to the appropriate workspace file, which will update the report and simultaneously update the dashboard as well.
You have now learned how to pin visuals as individual tiles and as entire live report pages. A word of caution: Dashboards are intended to be a collection from various sources, not just as a "launching pad" for reports. We recommend that you pin at the tile level first and foremost, and if needed, the entire report page can also be pinned. Seeing an entire report page in a dashboard tile can be difficult.
For more information, see Pin an entire report page.


Bot development
Reduce costs by having 1 Bot 24/7 instead of 10 community managers
Bot Integration
Integrate your services with an instant messenger
Chatbot for CRM
Use chatbot to get notifications about your external inquiries
Bot development
Have one chatbot instead of 10 community managers
Bot Integration
Quick access to all messengers' data
Chatbot for CRM
Notifications about new requests and inquiries


The class to access PostgreSQL database. All other functionality of libpq save the large object to a file.
For example, to send query to the database on the localhost.
require "postgres" conn = PGconn.connect("localhost", 5432, "", "", "test1") res = conn.exec("select * from a;")
Object
connect(pghost,
pgport, pgoptions,
pgtty, dbname, login,
passwd)
new(pghost,
pgport, pgoptions,
pgtty, dbname, login,
passwd)
On failure, it raises PGError
exception.
db
host
user
options
port
tty
error
finish
close
reset
trace(port)
untrace
exec(sql)
PGError
exception.
query(sql)
async_exec(sql)
PGError
exception.
async_query(sql)
get_notify
insert_table(table,
array)
getline
putline(string)
endcopy
set_client_encoding
client_encoding
lo_import(file)
PGError
exception.
lo_export(oid, file)
lo_create([mode])
PGError
exception.
lo_open(oid, [mode])
PGError
exception. If mode omitted, the default is "INV_READ"
lo_unlink(oid)
The class to represent the query result tuples. The object of this class is created as the result of every query. You may need to invoke clear method for the finished object for better memory performance.
Object
status
result
fields
num_tuples
num_fields
fieldname(index)
fieldnum(name)
type(index)
size(index)
-1
if the field is variable sized.
getvalue(tup_num, field_num)
getlength(tup_num, field_num)
cmdstatus
clear
The class to access large objects. The object of this class is created as the result of lo_import, lo_create, and lo_open.
Object
open([mode])
close
read([length])
write(str)
seek(offset, whence)
tell
unlink
oid
size
export(file)


2 Kings 17:19
Also Judah kept not the commandments of the LORD their God, but walked in the statutes of Israel which they made.


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Category
The Category menu contains special case Category pane queries and allows you to create custom menu options for your Browser. By default, DIScover offers a list of entity categories in the Category pane. If you want to display additional entity categories, such as operators or something custom, you can use the Category menu to do so.
Category menu options include:
• Create presents a dialog box where you can type a string that specifies the name and search action for a custom Category pane query.
• Operators executes a search for overloaded operators in the selected project and displays results in the Elements pane.
• Constructors executes a search for constructors in the selected project and displays results in the Elements pane.
• Cname match displays a dialog box where you can type a search string that specifies the cname pattern you want to match. Matches display in the Results column.


About Propranolol
Propranolol belongs to a group of medicines called beta blockers. It's used to treat heart problems, help with anxiety and prevent migraines.
If you have a heart problem, you can take propranolol to:
- treat high blood pressure
- treat illnesses that cause an irregular heartbeat, like atrial fibrillation
- prevent future heart disease, heart attacks and strokes
- prevent chest pain caused by angina
Propranolol can help reduce your symptoms if you have too much thyroid hormone in your body (thyrotoxicosis). You'll usually take it together with medicines to treat an overactive thyroid.
This medicine is only available on prescription. It comes as tablets, capsules, or as a liquid to swallow
Page last reviewed: 8 August 2017
Next review due: 8 August 2020


Version Control to Major Tom:
A Stellar Coding Adventure
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How to Reach Me
My LinkedIn Profile
GitHub: Fork This!
My Intermittent Twitter Thoughts
Do You Really Want to Friend Me? Think Twice
News Clips


For the fig-swirl: Melt butter over medium heat in a saucepan. Add brown sugar and stir to dissolve. Halve all of the figs and toss in the saucepan with water and lemon juice. Cook over medium heat, stirring frequently, until you have a chunky-jammy mixture. Add salt with one or two stirs, set aside and let cool completely.
Ice cream: In a small pot over medium heat, combine milk, and granulated sugar until sugar is completelydissolved and the milk is just barely lukewarm. Whisk in the egg yolks. Set mixture in the fridge and wait until the fig mixture is cooled.
Using an ice cream machine, pour liquids into the frozen basin and process according to manufacturer instructions, i.e., let spin and thicken for 20 minutes before adding mascarpone, fig jam mixture, and the nuts. Continue to process for +/- 10 minutes. poursemi-frozen mixture into a pyrex dish or glass tupperware. Freeze for at least two hours before serving.


My name is Kirsti, and I am a business graduate and aspiring web and software developer. I have a passion for creating and playing with anything technology related. When I’m not studying, I spend my time improving my development skills, most recently diving into the worlds of both ActionScript game design and Android application development. If I’m not on my computer, you’ll probably find me out snowboarding, wakeboarding, or on a volleyball court. Send me a message to learn more about me, or for a copy of my resume.
✓ JavaScript
✓ JQuery
✓ Microsoft Office Suite
✓ Ruby
✓ Python
✓ PHP
✓ HTML5
✓ CSS3
✓ C#
✓ Java
✓ Bootstrap
✓ MySQL
✓ English
✓ French
Computer Applications Development, Co-op
Post-Graduate Certificate
Conestoga College, Doon Campus
Kitchener, ON
2014-Current
Honours Bachelor of Business Administration
Insurance and Risk Mangement Specialization
Wilfrid Laurier University, Waterloo ON
2010-2014
Customer Service Representative
Liquor Control Board of Ontario
Cambridge, ON
2014(Summer)
Data Entry/General Assistant
WutzWhat
Toronto & Waterloo ON
2013(Summer)
Administrative/Office Assistant
Tench-MacDiarmid Insurance Brokers Ltd.
New Liskeard, ON
2008-2012(Summer)
Check out my GitHub!


Time in is required
Time out is required
Amount of male serves is required
Amount of female serves is required


Info
Welcome to the generated API reference. Get Postman Collection
Users
APIs for users
api/v1/register
Example request:
curl -X POST \
"http://<IP_ADDRESS>:8000/api/v1/register" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
const url = new URL(
"http://<IP_ADDRESS>:8000/api/v1/register"
);
let headers = {
"Content-Type": "application/json",
"Accept": "application/json",
};
fetch(url, {
method: "POST",
headers: headers,
})
.then(response => response.json())
.then(json => console.log(json));
HTTP Request
POST api/v1/register
api/v1/login
Example request:
curl -X POST \
"http://<IP_ADDRESS>:8000/api/v1/login" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
const url = new URL(
"http://<IP_ADDRESS>:8000/api/v1/login"
);
let headers = {
"Content-Type": "application/json",
"Accept": "application/json",
};
fetch(url, {
method: "POST",
headers: headers,
})
.then(response => response.json())
.then(json => console.log(json));
HTTP Request
POST api/v1/login
api/v1/verify_access_code
Example request:
curl -X POST \
"http://<IP_ADDRESS>:8000/api/v1/verify_access_code" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
const url = new URL(
"http://<IP_ADDRESS>:8000/api/v1/verify_access_code"
);
let headers = {
"Content-Type": "application/json",
"Accept": "application/json",
};
fetch(url, {
method: "POST",
headers: headers,
})
.then(response => response.json())
.then(json => console.log(json));
HTTP Request
POST api/v1/verify_access_code
api/v1/home
Example request:
curl -X GET \
-G "http://<IP_ADDRESS>:8000/api/v1/home" \
-H "Content-Type: application/json" \
-H "Accept: application/json"
const url = new URL(
"http://<IP_ADDRESS>:8000/api/v1/home"
);
let headers = {
"Content-Type": "application/json",
"Accept": "application/json",
};
fetch(url, {
method: "GET",
headers: headers,
})
.then(response => response.json())
.then(json => console.log(json));
Example response (200):
{
"status": 0,
"message": "Authorization Token not found"
}
HTTP Request
GET api/v1/home


Join our Bristol Bears WhatsApp service for the latest news and updates
Bristol Bears rugby writer John Evely will send you stories about the club as soon as they are live on our website
by John EvelyAre you mad about Bristol Bears?
If so, you could receive the latest club news straight to your phone by signing up to our WhatsApp service.
Join the hundreds who have already signed up.
Our website covers Bristol Bears news and views every day, but if you want to be the first to hear about it, here is your chance.
Bristol Bears rugby writer John Evely will send you links to the breaking stories, direct to your mobile, via the easy-to-use app.
Among the things you can expect are transfer news, interviews, match reports, injury updates, team news and live blogs. You could even use it to ask him a question.
If you would like to sign up, save the number 07715 770289 to your phone (you must do this to receive our messages), then send BRISTOL BEARS in a message to that number via WhatsApp.
We recommend saving the contact to your mobile as 'Bristol Bears News'. To unsubscribe at any time, just send STOP BATH RUGBY via WhatsApp to the same number and you will be removed from the service.
Your number will not be used for any purpose other than to update you on all things Bristol Bears.


PARADOX
Current Timeline
(current)
Login
Time Lines
Original Timeline
2 Histories Ago
Previous History
Account
Directions
FAQ's
DIRECTIONS


Insert User Details to filter for
Originating User
Username
Email
Insert log details to filter for
Log Type
Operation:
All Operations
Time of log
After:
Before:
Submit


Recent Updates (Sept. 13, 2020)
- Heavy Traffic Alert With the start of the Fall Term traffic on Runestone is extremely high. I have brought a second
server online to handle the load. This new server doubles our capacity!
- Runestone 5.1 - is live - with the ability to create competency based exams. Mmore to come on that!
Support Runestone
Did you know that over 31,000 students have registered on Runestone Academy since August 1 2020!? At $100 a textbook we have
saved students over $3.8 million! Thats a lot of students and a lot of savings. Please consider a donation
to help pay for server costs and the ongoing development needed to keep runestone online.


Browse loans credit-worthy borrowers by FICO score, rating and term.
Select individual loans, or use our Auto Invest tool to build ypur target portfolio based on your criteria.
 Subject to KYC and AML screening.
Alchemy has been seen in
| Highest Grade Credit | Aaa |
| Very High Grade Credit | Aa1, Aa2, Aa3 |
| High Grade Credit | A1, A2, A3 |
| Good Credit Grade | Baa1, Baa2, Baa3, Baa4 |
| Speculative Credit Grade | Ba1, Ba2, Ba3 |
| Very Speculative Credit | B1, B2, B3 |
* Demo images from Splmd.me


So you are interested in talking to us, that's great!
Welcome to The Next Company, {{ yourName }}! Together we will change the future! What's your company name?
What do you have in hands?
{{ companyName }} is just an idea, which is fine, but we are looking for ideas that have become companies already, so we suggest you come back here once you transform your idea into a company and became and entrepreneur.
Don’t take us wrong, but The Next Company needs to be a company.
{{ companyName }} is a keynote presentation, not a company yet. Once The Next Company supports new startups, we suggest you keep working on your studies and plans and come back when you are already running your company. We would love to look at all desks and presentations, but we don’t have staff for that, so we ask you to come back later when you’ve started your company. There are several good articles on how to move in the start, this one from Inc is especially simple and to the point.
{{ companyName }} is a two or more years old startup, which means you are a survivor on the entrepreneurial jungle! Congrats. The Next Company was created to support the early moments of a startup, which is not your case. What would you be expecting to get from us and why?
We’ve got your explanation. We will take a look, but as we said, we normally support early stage startups, don’t be too optimistic.
{{ companyName }} is a startup and this is exactly what we are looking for. Would you consider {{ companyName }} a disruptive startup?
Which area {{ companyName }} will disrupt?
This is ok. Which area is {{ companyName }}?
{{ companyName }}'s differentiation is about
and will create a
and creates a new business opportunity because of
in .
If you had to describe {{ companyName }} in 140 characters, one tweet:
Now we have a few questions for you so we can understand more of {{ companyName }} and also how we can help you.
*All fields are mandatory


| Recorded Crime Offences (Number) by Garda Station, Type of Offence and Year |
|||||||
|---|---|---|---|---|---|---|---|
| 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | ||
| Coolock, D.M.R. Northern Division | 03 ,Attempts/threats to murder, assaults, harassments and related offences | 165 | 105 | 136 | 131 | 189 | 206 |
| 04 ,Dangerous or negligent acts | 114 | 91 | 88 | 78 | 66 | 63 | |
| 07 ,Burglary and related offences | 327 | 270 | 312 | 373 | 328 | 270 | |
| 08 ,Theft and related offences | 932 | 904 | 1051 | 845 | 862 | 730 | |
| See Background Notes |


{% extends "base.html" %} {% block title %}
Medieval catalogues > REGISTRUM ANGLIE > Union catalogue by author and title, early 14th cent.
{% endif %}1 identified entry found.
All data was derived from the List of Identifications by Professor Richard Sharpe.
{% if not printing %}
A key to codes used in the List is available (opens in new tab).{% endif %}


Pushsafer adapter settings |
| Private Key: | Private or Alias Key from your Pushsafer.com account | |
Notification settings |
||
| Title: | ||
| Device: | Device ID or Device Group ID | |
| Icon: | Icon number 1-98 | |
| Time to Live: | Integer number 0-43200: Time in minutes, after which message automatically gets purged. | |
| Vibration: | ||
| Sound: | ||
| Priority: | ||
| Retry: | Integer 60-10800 (60s steps): Time in seconds, after a message should resend. | |
| Expire: | Integer 60-10800: Time in seconds, after the retry/resend should stop. | |
| Answer: | ||


Our Services
We provide many services to interact with IoT devices easily.
Our Projects
We are starting with the project to integrate IoT devices and manage them.
-
Document
We have clear, intuitive presentation documents to help programmers easily program the device.
-
Technology
With cloud technology developed today, we can easily control the device with just a few taps.
-
Pricing
The service is completely free in the first year and will be very preferential if you join us.
Our Pricing
We are starting with the project to integrate IoT devices and manage them.
Basic
Free
We provide some free APIs to query and deal with your IoT devices.
Standard
$10/months
We will provide cloud services to make log storage easier with unlimited storage and bandwidth.
Professional
$69/months
We will support consultancy and installation of IoT devices completely free and will be online 24/24.
Our Teams
We are a team of passionate technology people with extensive experience in software development.
Nguyen Minh Giau
Frontend / IoT Developer
Quan Kien Minh
Mobile / IoT / Backend Developer
Tieu Minh Khuong
Backend Developer / System Administrator


Merge your branch locally, delete old branch and pull from upstream for much win!
Your pull request has been merged! Now, since you know that you definitely want those updates in your forked version, and your branch is in good working order, merge it into the main branch on your forked repository, in this case, 'gh-pages'.
First, move into the branch you want to merge into — in this case, branch 'gh-pages'.
$ git checkout gh-pages
Now tell Git what branch you want to merge in — in this case, your feature branch that begins with "add-".
$ git merge <BRANCHNAME>
Tidy up by deleting your feature branch now that it has been merged.
$ git branch -D <BRANCHNAME>
You can also delete the branch from your fork on GitHub:
$ git push <REMOTENAME> --delete <BRANCHNAME>
And last but not least, if you pull in updates from the original (since it now shows you on the home page) you'll be up to date and have a version too, live at: yourusername.github.io/patchwork.
To pull from the original upstream:
$ git pull upstream gh-pages
You've created local repositories, remote repositories, worked with a collaborator, pushed, pulled and joined the millions of others developing and enriching open source!
Visit jlord.github.io/patchwork to see your name incorporated!
git-it verify
git-it
$ git merge <BRANCHNAME>
$ git checkout <BRANCHNAME>
$ git branch -D <BRANCHNAME>
$ git push <REMOTENAME> --delete <BRANCHNAME>
$ git pull <REMOTENAME> <BRANCHNAME>


---
layout: component-layout
title: How to add Kudos?
link-title: Kudos
category: Reports
url: /uvdemo/reports/kudos.html
tags: [Kudos, Add Kudos,New Kudos, Adding Kudos]
---
UVdesk - How to add Kudos?
What is Kudos?
Kudos is all about the ratings of "Agents" profile whether they have got a good response or the bad one from the customers.
UVdesk – It also displays whether the agent is a star performer or a mediocre one.
Steps for adding kudos-
- Login to your UVdesk Support Panel.
- On the Dashboard, you will see "Reports" menu and under it, you will find "Kudos".
- Click on the "kudos" Icon and then you will be redirected to a new page.
- In the Kudos section within the Reports, the owner or the agent can see the ratings provided by the customers for their support.
- The agent or the owner can see Ticket Id, Customer Name, Customer Email, Timestamp on which Kudos Rating is provided by the customer.
- In the Filter View, the owner or the agent can see the Kudos Rating by selecting any particular Agent, Group, Team, Type, Priority, customer, source.


bingetv
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Contact Us:
Address:
Nanawadi,Savagaon Road,
590001,
Karnataka,
India
Phone:
+91 10-0908-07060
Email:
contact@vegetablecart.co.in


Previous Demo
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Caption Hover Effects
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Effect 2
Effect 3
Effect 4
Effect 5
Effect 6
Effect 7
Safari
Jacob Cummings
Take a look
Game Center
Jacob Cummings
Take a look
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Jacob Cummings
Take a look
Settings
Jacob Cummings
Take a look
Camera
Jacob Cummings
Take a look
Phone
Jacob Cummings
Take a look


Chinese spy defects to Australia with trove of intel: report
Sydney: A Chinese spy has defected to Australia with a trove of intelligence on China's political interference operations in Hong Kong, Taiwan and elsewhere, according to a media report Saturday.
The Nine network newspapers said the defector, named as Wang "William" Liqiang, had given Australia's counter-espionage agency the identities of China's senior military intelligence officers in Hong Kong and provided details of how they funded and conducted operations in Hong Kong, Taiwan and Australia.
Wang said he was personally involved in infiltration and disruption operations in all three territories, according to the report, published in Nine's The Age and Sydney Morning Herald newspapers.
Wang "revealed in granular detail" how Beijing covertly controls listed companies to fund intelligence operations, including the surveillance and profiling of dissidents and the co-opting of media organisations, the report stated.
Wang is currently living in Sydney with his wife and infant son on a tourist visa and has requested political asylum, it said.
China fears
Wang said in an interview to be aired Sunday night on Nine's TV news program 60 Minutes that he would be executed if he returned to China.
"Once I go back, I will be dead," a youthful and bespectacled Wang said through a translator in a clip from 60 Minutes shown on Nine's websites Saturday.
Wang was also shown holding his son and walking with his wife along Sydney harbour beside the popular Luna Park amusement centre.
According to the news organisation, Wang gave a sworn statement to the Australian Security Intelligence Organisation (ASIO) in October saying: "I have personally been involved and participated in a series of espionage activities".
This allegedly included infiltrating Taiwan under an assumed identity and with a South Korean passport to run local operatives in efforts to meddle in 2018 municipal elections and presidential polls due next year.
He said the operation used local media executives to influence the election campaigns and defeat candidates seen as hostile to Beijing.
He also claimed to have coordinated a "cyber army" to shift political opinion, similar to Russia's interference in the 2016 US presidential election.
"Our work on Taiwan was the most important work of ours - the infiltration into media, temples and grassroots organisations," he was quoted as saying.
It was his fear of being discovered by Taiwan's counter-espionage authorities working to influence next year's elections that led Wang to seek asylum in Australia, he reportedly said.
In Hong Kong, Wang said he was part of an intelligence operation hidden within a listed company which infiltrated Hong Kong's universities and media to counter the pro-democracy movement.
He said his role in the clandestine organisation including infiltrating all Hong Kong universities and directing bashings and cyber attacks against dissidents.
"They (his recruits) found out information about those pro-independence activists... and made public all their personal data, their parents' and family members'," he was quoted as saying.
He added that the goal was "to make all troublemakers in Hong Kong terrified".
Kidnappings
Wang also said he personally helped organise the October 2015 kidnapping of Lee Bo, owner of the Causeway Bay Bookshop, which Beijing said distributed dissident materials.
Four other bookshop employees were also spirited away to the mainland that year.
Other operatives planted in Hong Kong, he said, included a senior manager at a major Asian television network who was actually "a current military cadre with a Division Commander rank".
Wang also reportedly said he had met a high-ranking intelligence operative he believed was conducting spy operations in Australia via a front company in the energy sector.
"He told me at the time he is based in Canberra. I know his position is very important," he was quoted as saying.
The report did not provide additional details on operations in Australia, but is likely to exacerbate already high alarm over Chinese espionage and influence operations in the country.
ASIO warned earlier this year that the threat of foreign interference was "unprecedented" and that the number of foreign spies in Australia was higher than during the Cold War.
The agency has never publicly named China in its warnings.
But the former head of the agency, Duncan Lewis, who retired in September, said in an interview published Friday that China wanted to "take over" Australia's political system with an "insidious" and systematic campaign of espionage and influence-peddling.
Read also
Read More
IS-linked Philippine militant behind suicide attacks killed
Philippine military officials say troops have killed a "high-value” Filipino militant who acted as a key link of the Islamic State group to local jihadists and helped set up a series of deadly suicide attacks in the south that have alarmed the region.
Read More
Joyous scenes as Bougainville independence vote starts
Joyous voters in the Pacific island chain of Bougainville cheered and sang as they flocked to the polls Saturday at the start of a long-awaited referendum on independence from Papua New Guinea.
Read More
Pregnant woman punched, kicked in Australian Islamophobic attack
A Sydney man has been charged for punching and stomping on a heavily pregnant woman unprovoked, in what was described as an "Islamophobic" attack by a leading Australian Islamic association.


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|
Algorithms
|
Search Algorithms Interface. More...
Go to the source code of this file.
Data Structures | |
| struct | _SequentialSeachST_node |
| Definition of Node in Sequential search symbol table UnorderST. More... | |
| struct | _SequentialSearchST |
| UNORDERED SEQUENTIAL SEARCH SYMBOL TABLE This data structure is single link list, with each node as key-value pair. More... | |
| struct | _OrderedArrayElement |
| The Element type used to create array of OrderedST. More... | |
| struct | _OrderedArrayST |
| ORDERED SEQUENTIAL SEARCH SYMBOL TABLE. This uses the array data-structure to store (key, value) pair in ascending order. More... | |
| struct | _Binary_search_tree_node |
| The definition of the Binary Search tree node. More... | |
| struct | _Binary_search_tree |
| BINARY SEARCH TREE SYMBOL TABLE. This symbol table implementation uses binary search tree to store key value pair. More... | |
Typedefs | |
| typedef struct _SequentialSeachST_node | UnorderST_node |
| Definition of Node in Sequential search symbol table UnorderST. More... | |
| typedef struct _SequentialSearchST | UnorderST |
| UNORDERED SEQUENTIAL SEARCH SYMBOL TABLE This data structure is single link list, with each node as key-value pair. More... | |
| typedef struct _OrderedArrayElement | Element |
| The Element type used to create array of OrderedST. More... | |
| typedef struct _OrderedArrayST | OrderedST |
| ORDERED SEQUENTIAL SEARCH SYMBOL TABLE. This uses the array data-structure to store (key, value) pair in ascending order. More... | |
| typedef struct _Binary_search_tree_node | BST_node |
| The definition of the Binary Search tree node. More... | |
| typedef struct _Binary_search_tree | BST |
| BINARY SEARCH TREE SYMBOL TABLE. This symbol table implementation uses binary search tree to store key value pair. More... | |
Functions | |
| int | binary_search (int *array, int length, int key) |
| BINARY SEARCH. More... | |
| void | UnorderST_init (UnorderST *st) |
| This funtion initial the symbol table with NULL pointer for head and size 0, in UnorderST. More... | |
| void | UnorderST_put (UnorderST *st, int key, char *value) |
| This function puts the (key, value) pair in the symbol table. More... | |
| char * | UnorderST_get (UnorderST *st, int key) |
| This function gets the value corresponding to give key. More... | |
| void | UnorderST_delete (UnorderST *st, int key) |
| This function deletes the given node with (key, value) pair. More... | |
| bool | UnorderST_contains (UnorderST *st, int key) |
| This function checks if given key is in symbol table. More... | |
| bool | UnorderST_isEmpty (UnorderST *st) |
| This function checks if symbol table is empty. More... | |
| int | UnorderST_size (UnorderST *st) |
| This function returns the size of symbol table. More... | |
| void | UnorderST_show (UnorderST *st) |
| This function iterates the symbol table and display all the key-value pair. More... | |
| void | UnorderST_destroy (UnorderST *st) |
| This function deletes all the entries of symbol table and free memory to heap. More... | |
| void | OrderedST_init (OrderedST *ost, int capacity) |
| int | OrderedST_rank (OrderedST *ost, int key) |
| char * | OrderedST_get (OrderedST *ost, int key) |
| void | OrderedST_put (OrderedST *ost, int key, char *value) |
| void | OrderedST_delete (OrderedST *ost, int key) |
| bool | OrderedST_contains (OrderedST *ost, int key) |
| bool | OrderedST_isEmpty (OrderedST *ost) |
| int | OrderedST_size (OrderedST *ost) |
| int | OrderedST_min (OrderedST *ost) |
| int | OrderedST_max (OrderedST *ost) |
| int | OrderedST_floor (OrderedST *ost, int key) |
| int | OrderedST_ceiling (OrderedST *ost, int key) |
| int | OrderedST_select (OrderedST *ost, int k) |
| int | OrderedST_no_of_keys (OrderedST *ost, int low_key, int high_key) |
| void | OrderedST_deleteMin (OrderedST *ost) |
| void | OrderedST_deleteMax (OrderedST *ost) |
| void | OrderedST_show (OrderedST *ost) |
| void | OrderedST_destroy (OrderedST *ost) |
| void | BST_init (BST *tree) |
| This function initializes the Binary search tree BST. More... | |
| char * | BST_get_recursive (BST *tree, int key) |
| This function get the value corresponding to given key in tree BST. It use the recursive implementation. More... | |
| char * | BST_get_iterative (BST *tree, int key) |
| This function get the value corresponding to given key in tree BST. It use the iterative implementation. More... | |
| int | BST_get_min_key (BST *tree) |
| This function gets the minimum key in tree BST. It use the recursive implementation. More... | |
| int | BST_get_max_key (BST *tree) |
| This function gets the maximum key in tree BST. It use the recursive implementation. More... | |
| void | BST_insert_recursive (BST *tree, int key, char *value) |
| This function insert the (key, value) pair in tree BST. It use the recursive implementation. More... | |
| void | BST_insert_iterative (BST *tree, int key, char *value) |
| This function insert the (key, value) pair in tree BST. It use the iterative implementation. More... | |
| void | BST_delete_min_recursive (BST *tree) |
| This function deletes the minimum key and corresponding value and node in tree BST. It use the recursive implementation. More... | |
| void | BST_delete_min_iterative (BST *tree) |
| This function deletes the minimum key and corresponding value and node in tree BST. It use the iterative implementation. More... | |
| void | BST_delete_max_recursive (BST *tree) |
| This function deletes the maximum key and corresponding value and node in tree BST. It use the recursive implementation. More... | |
| void | BST_delete_max_iterative (BST *tree) |
| This function deletes the maximum key and corresponding value and node in tree BST. It use the iterative implementation. More... | |
| void | BST_delete_recursive (BST *tree, int key) |
| This function deletes the given key and corresponding value and node in tree BST. It use the recursive implementation. More... | |
| int | BST_tree_height (BST *tree) |
| This function calculates the height of the tree BST. It use the recursive implementation. Root node is treated as level 0, subsequent levels are increased, as node increase downward. More... | |
| void | BST_show (BST *tree) |
| This function display the tree BST, in ascending order (INORDER traversal). More... | |
| void | BST_destroy (BST *tree) |
| This function deletes all the nodes of BST, reset value of tree root to NULL. More... | |
Search Algorithms Interface.
It covers following search algorithms:
Definition in file search.h.
| typedef struct _Binary_search_tree BST |
BINARY SEARCH TREE SYMBOL TABLE. This symbol table implementation uses binary search tree to store key value pair.
| typedef struct _Binary_search_tree_node BST_node |
The definition of the Binary Search tree node.
| typedef struct _OrderedArrayElement Element |
The Element type used to create array of OrderedST.
| typedef struct _OrderedArrayST OrderedST |
ORDERED SEQUENTIAL SEARCH SYMBOL TABLE. This uses the array data-structure to store (key, value) pair in ascending order.
| typedef struct _SequentialSearchST UnorderST |
UNORDERED SEQUENTIAL SEARCH SYMBOL TABLE This data structure is single link list, with each node as key-value pair.
| typedef struct _SequentialSeachST_node UnorderST_node |
Definition of Node in Sequential search symbol table UnorderST.
| int binary_search | ( | int * | array, |
| int | length, | ||
| int | key | ||
| ) |
BINARY SEARCH.
Time Complexity: all cases : O(lgn)
| array | Pointer to array of integers. |
| length | Length of array of integers. |
| key | The integer value to search in array. |
| void BST_delete_max_iterative | ( | BST * | tree | ) |
This function deletes the maximum key and corresponding value and node in tree BST. It use the iterative implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| void BST_delete_max_recursive | ( | BST * | tree | ) |
This function deletes the maximum key and corresponding value and node in tree BST. It use the recursive implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| void BST_delete_min_iterative | ( | BST * | tree | ) |
This function deletes the minimum key and corresponding value and node in tree BST. It use the iterative implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| void BST_delete_min_recursive | ( | BST * | tree | ) |
This function deletes the minimum key and corresponding value and node in tree BST. It use the recursive implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| void BST_delete_recursive | ( | BST * | tree, |
| int | key | ||
| ) |
This function deletes the given key and corresponding value and node in tree BST. It use the recursive implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| key | the key to be deleted. |
| void BST_destroy | ( | BST * | tree | ) |
This function deletes all the nodes of BST, reset value of tree root to NULL.
Time Complexity : O(n)
| tree | passing the address of the BST tree. |
| char* BST_get_iterative | ( | BST * | tree, |
| int | key | ||
| ) |
This function get the value corresponding to given key in tree BST. It use the iterative implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| int BST_get_max_key | ( | BST * | tree | ) |
This function gets the maximum key in tree BST. It use the recursive implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| int BST_get_min_key | ( | BST * | tree | ) |
This function gets the minimum key in tree BST. It use the recursive implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| char* BST_get_recursive | ( | BST * | tree, |
| int | key | ||
| ) |
This function get the value corresponding to given key in tree BST. It use the recursive implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| void BST_init | ( | BST * | tree | ) |
| void BST_insert_iterative | ( | BST * | tree, |
| int | key, | ||
| char * | value | ||
| ) |
This function insert the (key, value) pair in tree BST. It use the iterative implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| key | the integer key to be inserted in BST. |
| value | the string value corresponding to key. |
| void BST_insert_recursive | ( | BST * | tree, |
| int | key, | ||
| char * | value | ||
| ) |
This function insert the (key, value) pair in tree BST. It use the recursive implementation.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| key | the integer key to be inserted in BST. |
| value | the string value corresponding to key. |
| void BST_show | ( | BST * | tree | ) |
| int BST_tree_height | ( | BST * | tree | ) |
This function calculates the height of the tree BST. It use the recursive implementation. Root node is treated as level 0, subsequent levels are increased, as node increase downward.
Time Complexity : worst_case = O(n) Best and Avg case = O(lgn)
| tree | passing the address of the BST tree. |
| int OrderedST_ceiling | ( | OrderedST * | ost, |
| int | key | ||
| ) |
| bool OrderedST_contains | ( | OrderedST * | ost, |
| int | key | ||
| ) |
| void OrderedST_delete | ( | OrderedST * | ost, |
| int | key | ||
| ) |
| void OrderedST_deleteMax | ( | OrderedST * | ost | ) |
| void OrderedST_deleteMin | ( | OrderedST * | ost | ) |
| void OrderedST_destroy | ( | OrderedST * | ost | ) |
| int OrderedST_floor | ( | OrderedST * | ost, |
| int | key | ||
| ) |
| char* OrderedST_get | ( | OrderedST * | ost, |
| int | key | ||
| ) |
| void OrderedST_init | ( | OrderedST * | ost, |
| int | capacity | ||
| ) |
| bool OrderedST_isEmpty | ( | OrderedST * | ost | ) |
| int OrderedST_max | ( | OrderedST * | ost | ) |
| int OrderedST_min | ( | OrderedST * | ost | ) |
| int OrderedST_no_of_keys | ( | OrderedST * | ost, |
| int | low_key, | ||
| int | high_key | ||
| ) |
| void OrderedST_put | ( | OrderedST * | ost, |
| int | key, | ||
| char * | value | ||
| ) |
| int OrderedST_rank | ( | OrderedST * | ost, |
| int | key | ||
| ) |
| int OrderedST_select | ( | OrderedST * | ost, |
| int | k | ||
| ) |
| void OrderedST_show | ( | OrderedST * | ost | ) |
| int OrderedST_size | ( | OrderedST * | ost | ) |
| bool UnorderST_contains | ( | UnorderST * | st, |
| int | key | ||
| ) |
This function checks if given key is in symbol table.
Time complexity : O(n)
| st | pointer to symbol table structure UnorderST. |
| key | Key to be checked in symbol table. |
| void UnorderST_delete | ( | UnorderST * | st, |
| int | key | ||
| ) |
This function deletes the given node with (key, value) pair.
Time complexity : O(n)
| st | pointer to symbol table structure UnorderST. |
| key | Key to be deleted from the symbol table. |
| void UnorderST_destroy | ( | UnorderST * | st | ) |
This function deletes all the entries of symbol table and free memory to heap.
Time complexity: O(n)
| st | pointer to symbol table structure UnorderST. |
| char* UnorderST_get | ( | UnorderST * | st, |
| int | key | ||
| ) |
This function gets the value corresponding to give key.
Time complexity : O(n).
| st | pointer to symbol table structure UnorderST. |
| key | Key to be inserted in symbol table. |
| void UnorderST_init | ( | UnorderST * | st | ) |
This funtion initial the symbol table with NULL pointer for head and size 0, in UnorderST.
| st | pointer to symbol table structure UnorderST. |
| bool UnorderST_isEmpty | ( | UnorderST * | st | ) |
This function checks if symbol table is empty.
Time complexity: O(1)
| st | pointer to symbol table structure UnorderST. |
| void UnorderST_put | ( | UnorderST * | st, |
| int | key, | ||
| char * | value | ||
| ) |
This function puts the (key, value) pair in the symbol table.
Time complexity: O(1), as it just append the node in front.
| st | pointer to symbol table structure UnorderST |
| key | Key to be inserted in the symbol table. |
| value | Value to reference corresponding to the key. |
| void UnorderST_show | ( | UnorderST * | st | ) |
This function iterates the symbol table and display all the key-value pair.
Time complexity: O(n)
| st | pointer to symbol table structure UnorderST. |
| int UnorderST_size | ( | UnorderST * | st | ) |
This function returns the size of symbol table.
Time complexity: O(1)
| st | pointer to symbol table structure UnorderST. |


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