PALMETTO (Columbia/Castle Rock) Starring: Woody Harrelson, Elisabeth Shue, Gina Gershon, Chloe Sevigny, Michael Rapaport. Screenplay: E. Max Frye, based on the novel "Just Another Sucker" by James Hadley Chase. Producers: Matthais Wendlandt and Al Corley. Director: Volker Schlondorff.  Reviewed by Scott Renshaw.
A wronged man. A femme fatale. A body. A deception. Avarice and alcohol. Sweat, sex, cigarettes and shadows. These are the little things of which the contemporary film noir mystery is made, so predictably that the genre has descended into the kind of ridiculous self-parody of which direct-to-video Mickey Rourke vehicles are made. With too many film-makers content to keep re-making DOUBLE INDEMNITY and BODY HEAT, there doesn't seem to be anywhere to go but subversion.
For a while, that looks like where PALMETTO is headed. The obligatory sucker is a former reporter named Harry Barber (Woody Harrelson) who has learned the hard way that honesty is not necessarily the best policy. After threatening to expose corrupt government officials and refusing to accept hush money, Harry found himself framed, convicted and sitting in jail for two years. Now released and understandably bitter, Harry becomes the perfect target for Rhea Malroux (Elisabeth Shue), the trophy wife of an ailing millionaire. Rhea invites Harry to participate in a scam to fake the kidnapping of Malroux's teenage daughter Odette (Chloe Sevigny) and share in a $500,000 ransom. Harry finds the offer too tempting to pass up, but the deal begins to sour when bodies start turning up at inconvenient times, with a trail that keeps pointing directly at Harry.
Standard noir stuff, to be sure, tag-teaming with a sultry South Florida setting to create some major deja vu. Then screenwriter E. Max Frye (working from James Hadley Chase's novel "Just Another Sucker") pulls out some of the expectation-twisting tricks he showed off in his script for Jonathan Demme's SOMETHING WILD. The oddball touches start popping up with regularity: Harry lighting a cigarette which flares up in his face; Harry running face first into a post; Harry fumbing with a tape recorder as he tries to catch his accomplices scheming; Harry "seducing" Rhea with all the romantic subtlety of a stud horse. Suddenly PALMETTO seems to be coming from a slightly different place, one where the protagonist isn't just an ordinary guy led into a bad situation by his zipper. Harry appears to be hopelessly inept, portrayed by Harrelson with his impressive gift for convincing ineptitude.
Sadly, PALMETTO soon veers from goofiness to predictable over-complexity to twisty-turny absurdity. The plot twists become ever more elaborate and ever more unnecessary, burying a few sturdy sequences like Harry's efforts to keep a cop from spotting a body in his car's trunk. Since there's never any real attempt to establish the relationships, it's hard to care much about how Harry will explain his actions to his artist girlfriend Nina (Gina Gershon), or what exactly Harry might learn from his ordeal. Finally, the whole film goes completely mental in a finale which finds Harrelson suspended over a vat of acid, Gershon tied to a chair and Shue vamping around in a black pixie-cut wig. I half expected the story to be concluded next week, same Bat-time, same Bat-channel.
I suppose at the very least PALMETTO succeeds at avoiding the film noir rut where only the names change from one film to the next. It's just bizarre enough that it might have been entertaining, if only it made an ounce of sense. Credit Harrelson and Frye with providing a brief, faint hope that noir might have a few more miles left in it, provided somebody remembers to bring along a steering wheel.
On the Renshaw scale of 0 to 10 sweaty palms: 5.
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Author: Oliver Kiss, Lukas Fryc
Level: Intermediate
Technologies: JPA, Arquillian
Summary: The tasks
quickstart includes a persistence unit and sample persistence code to demonstrate how to use JPA for database access in JBoss EAP.
Target Product: JBoss EAP
Source: https://github.com/jboss-developer/jboss-eap-quickstarts/
The tasks
quickstart demonstrates how to use JPA in Red Hat JBoss Enterprise Application Platform.
It includes a persistence unit and some sample persistence code to demonstrate database access in enterprise Java.
It does not contain a user interface layer. The purpose of the project is to show you how to test JPA with Arquillian.
Note: This quickstart uses the H2 database included with Red Hat JBoss Enterprise Application Platform 7.1. It is a lightweight, relational example datasource that is used for examples only. It is not robust or scalable, is not supported, and should NOT be used in a production environment!
Note: This quickstart uses a *-ds.xml
datasource configuration file for convenience and ease of database configuration. These files are deprecated in JBoss EAP and should not be used in a production environment. Instead, you should configure the datasource using the Management CLI or Management Console. Datasource configuration is documented in the Configuration Guide for Red Hat JBoss Enterprise Application Platform.
The application this project produces is designed to be run on Red Hat JBoss Enterprise Application Platform 7.1 or later.
All you need to build this project is Java 8.0 (Java SDK 1.8) or later and Maven 3.3.1 or later. See Configure Maven for JBoss EAP 7.1 to make sure you are configured correctly for testing the quickstarts.
In the following instructions, replace EAP7_HOME
with the actual path to your JBoss EAP installation. The installation path is described in detail here: Use of EAP7_HOME and JBOSS_HOME Variables.
For Linux: EAP7_HOME/bin/standalone.sh
For Windows: EAP7_HOME\bin\standalone.bat
This quickstart provides Arquillian tests. By default, these tests are configured to be skipped as Arquillian tests require the use of a container.
mvn clean verify -Parq-remote
You can also let Arquillian manage the JBoss EAP server by using the arq-managed
profile. For more information about how to run the Arquillian tests, see Run the Arquillian Tests.
Maven prints summary of the 8 performed tests to the console.
-------------------------------------------------------
T E S T S
-------------------------------------------------------
Running org.jboss.as.quickstarts.tasks.UserDaoTest
Tests run: 3, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 1.084 sec
Running org.jboss.as.quickstarts.tasks.TaskDaoTest
Tests run: 5, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 2.31 sec
Results :
Tests run: 8, Failures: 0, Errors: 0, Skipped: 0
SQL statements generated by Hibernate are written into the server log.
Note: You will see the following warnings in the server log. You can ignore these warnings.
WFLYJCA0091: -ds.xml file deployments are deprecated. Support may be removed in a future version.
HHH000431: Unable to determine H2 database version, certain features may not work
Creating the database schema:
INFO [stdout] (ServerService Thread Pool -- 104) Hibernate: drop table Task if exists
INFO [stdout] (ServerService Thread Pool -- 104) Hibernate: drop table User if exists
INFO [stdout] (ServerService Thread Pool -- 104) Hibernate: create table Task (id bigint generated by default as identity, title varchar(255), owner_id bigint, primary key (id))
INFO [stdout] (ServerService Thread Pool -- 104) Hibernate: create table User (id bigint generated by default as identity, username varchar(255), primary key (id))
INFO [stdout] (ServerService Thread Pool -- 104) Hibernate: alter table Task add constraint FK46hwvn8nayomwr7k7h13l0uxe foreign key (owner_id) references User
INFO [stdout] (ServerService Thread Pool -- 104) Hibernate: alter table User add constraint UK_jreodf78a7pl5qidfh43axdfb unique (username)
Generating ID for a new entity and inserting the entity into the database:
INFO [stdout] (default task-83) Hibernate: select user0_.id as id1_1_, user0_.username as username2_1_ from User user0_ where user0_.username=?
INFO [stdout] (default task-88) Hibernate: select user0_.id as id1_1_, user0_.username as username2_1_ from User user0_ where user0_.username=?
INFO [stdout] (default task-90) Hibernate: insert into User (id, username) values (null, ?)
INFO [stdout] (default task-90) Hibernate: select user0_.id as id1_1_, user0_.username as username2_1_ from User user0_ where user0_.username=?
You can also start the server and deploy the quickstarts or run the Arquillian tests from Eclipse using JBoss tools. For general information about how to import a quickstart, add a JBoss EAP server, and build and deploy a quickstart, see Use JBoss Developer Studio or Eclipse to Run the Quickstarts.
If you want to debug the source code of any library in the project, run the following command to pull the source into your local repository. The IDE should then detect it.
mvn dependency:sources


The majestic landscapes the Pacific Northwest are home to thousands of hiking trails that offer a remarkable diversity of experiences. From the beaches of the Pacific coast, to the peaks of the Cascades, to the high desert of eastern Oregon, it can be a little overwhelming to decide where to go next.
The hikepnw.us project serves as your guide to the many hiking gems in the Pacific Northwest. Think of it as having an expert making hiking trail recommendations that are personalized to you! By using hikepnw.us to plan your next outdoor adventure, you'll spend less time searching and more time out on the trail!
The data behind hikepnw.us consists of trail information, trail ratings, and trail reviews from AllTrails®. More than 150,000 reviews from over 60,000 users are harnessed to make expert recommendations across over 3,200 hiking trails tailored to the specific interests of individual users.
Hiking trail recommendations are determined using a hybrid recommendation algorithm called LightFM. Using this hybrid model, latent embedding for new and existing users are learned in concert with user representations, collaborative filtering from user ratings, and a Weighted Approximate-Rank Pairwise loss function through stochastic gradient descent. User representations are determined by extracting key trail-descriptors from user reviews. The bridging principal is that users old and new who share similar vocabularies and who use similar descriptors are more likely to desire similar outdoor experiences. For example, some users are looking for 'epic' hikes that are 'cool' and 'challenging', while others might be looking for hikes that are 'peaceful', 'relaxing', and 'family friendly'.
To help refine recommendations, a couple of "must have" trail filters are applied based on trail features. This makes sure that recommended trails are truly personalized to the interests of the user.
The backend of the application was built using the Flask microframework and the data were handled using the Python modules pandas, NumPy, SciPy, and SQLAlchemy. All data are stored in a PostgreSQL database. The application is hosted on an Amazon Web Services Ubuntu microinstance and served using nginx and gunicorn. The user interfaces for the site were constructed using HTML, CSS, bootstrap, and fastselect.
The hikepnw.us web app project was created by me, Andy Upton. I built this app as a Data Science Fellow at Insight. I love hiking with my wife and puppy-dog. When we recently moved to Portland, OR it was hard to figure out where to hike next!
I am finishing up a Ph.D. in a Anthropology from Michigan State University, and I love to solve complex problems related to human behavior using approaches from social network analysis, statistics and machine learning.
You can find out more about me by visiting my personal website andyupton.net or my LinkedIn. You can see other examples of my work on GitHub.


History of Mobile Library
A first bookmobile in the world was horse-drawn and operated in 1857 in Cumbria county in North West England. It was aimed to increase the lending of its books to enthusiastic local patrons. Since that time the beautiful pictures of libraries on wheels populated our minds and memories. We associate them with passionate librarians, who, in many cases, came as a rescue to people who were eager to learn more and get smarter. Wait, don`t get too nostalgic. Vehicles that offer access to books are definitely not something from the past. Just the opposite.  The vehicles listed in this article are not always bookmobiles in the strict sense. Sometimes they are mobile libraries you can check out books at. Sometimes they are book fairs or bookshops. And, eventually, you`ll find here vehicles that offer books at no charge. No matter where and how they travel, these book vehicles have three things in common: passion, creativity, and determination of men who originate and operate them.
Mobile Library in INDIA
Now INDIA is also coming forward with mobile library. Rural areas of India are getting so much benefit with it. Lots of schools in villages all around the India can access the study materials .
Rural Mobile Library
A healthy reading habit can transform a person and access to books and reading material relevant to the target group can transform a community. DLF Mobile Rural Libraries is our endeavor to overcome the lack of access to schools or libraries, especially in the rural areas. We reach the reading material the people need to their doorsteps. We believe if India is to progress, every constituent, every citizen must have the opportunity to keep themselves well informed. Through these Rural Mobile Libraries rural folks are keeping themselves abreast of latest news, happenings around the world, information`s regarding modern agricultural techniques and government programmes which directly benefit them. Our Rural Mobile Libraries cater to all age groups and the initiative has received a very encouraging response. The adults have taken to reading with great enthusiasm while adolescents and children too have shown encouraging participation.


Safe Routes is a team committed to creating safer transportation experiences for users of all modes of transportation.


{% load static %}
Add team members to your organization or join an organization to begin collaborating.
Start a team| Name | Analyses | Status | |
|---|---|---|---|
| 1,001 | Lorem | ipsum | sit |
| 1,002 | amet | consectetur | elit |
| 1,003 | Integer | nec | Praesent |
| 1,003 | libero | Sed | ante |
| 1,004 | dapibus | diam | nisi |
| 1,005 | Nulla | quis | at |


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I will not spend a single minute, trying to define what data science is. I will say just this, there can never data science with out data. And if there is data, there can never be trusted data withouth a refined data quality process. While data quality enables business decision makers the opportunity to make decision with confidence. Archieving this without proper mechanisms that clean the data of unwanted outliers and inconsistencies is impossible. One should never rush to analytics or even machine learning exercises, unless they can prove that their data qualityis above reproach. The above statement affords us to make a bold statement, data science is the science dedicated to providing meaningful conclusions on clear, clean and high quality data. Once the data is in an acceptable state, some of the following strides can be archieved:


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A reluctance with the Tellinen hysteresis model. The major hysteresis loop is defined by the hyperbolic tangent function.
The Tellinen hysteresis model is a simple model to describe the magnetic hysteresis behavior of ferromagnetic materials. It only uses the rising (hystR) and falling (hystF) branch of the major hysteresis loop and their derivatives der(hystR) and der(hystF). See Fig. 1 and the following equations for a short description of the Tellinen hysteresis model.
diffHyst = hystF - hystR; dhR = hystF - b; dhF = b - hystR;
if the magnetic field intensity increases (der(h)>0)
der(b) = dhR/diffHyst * der(hystR);
if the magnetic field intensity decreases (der(h)<0)
der(b) = dhF/diffHyst * der(hystF);


The Wolak Research Group was well represented at Destination STEM this year and I think the event was a great success! About 1,100 students from 18 middle and high schools near Auburn, came to the AU Coliseum to explore, interact, and learn about STEM fields.
Our own Molly Caldwell was on hand as part of the table by the COSAM Women in Sciences and Mathematics, where she had some fabulous outreach animals to share in collaboration with Debbie, her mother and Professor Emeritus!
Our group’s own table hosted a hands-on experience measuring turtle shells to illustrate an example of what evolutionary ecologists do (at least the fun, fieldwork parts!). We combined this activity with a quantitative genetic video game! The game is based on selection acting on between-individual differences in size. Progress through the game results in evolutionary responses to selection! Jake did a tremendous effort coding a breeding value based quantitative genetic individual based model and then spent many a late night turning a boring terminal simulation into a game that has the look and feel of the original Super Mario Bros.
Feedback from the students was positive, so stay tuned as we continue to work on the game; including efforts to make it available through a website!


Free useable Icons for anything
Checkmark in circle - Wireframe
Curved line in grid (easein) - Wireframe
Curved line in grid (easeout) - Wireframe
Headphones - Solid
Headphones with X through the center - Solid
Pause in circle - Wireframe
Magnifying Glass - Wireframe
Microphone with small dots on top - Wireframe
House with chimney- Solid
Question mark surrounded within circle - Wireframe
Return Arrow in circle - Wireframe
Gear with in circle - Wireframe
1 - 2 - 3 - 4 - 5 … 23


Attributes¶
Attributes are declarations that change script metadata, and allow for some useful features when correctly used. Visit this page to know more about attributes.
These attributes should make it easier to organize the inspector without much effort or any learning curve. Some aren’t aesthetic-related, but rather quality-of-life features that will improve workflow, reducing the amount of times you’ll have to switch windows.
AESTHETIC¶
Warning
These attributes override all other aesthetic attributes, no matter the order of execution. This means they are incompatible with Range and Header, and likely Tooltip, but not SerializeField, for example.
BigHeader¶
Affects: Variables
Creates a big header above the target variable.
Parameters
Type |
Name |
Description |
|---|---|---|
string |
title |
The header’s title. |
string |
subtitle |
The sub-header to go underneath the header. Leave blank for none. |
IMAGE GOES HERE
Label¶
Affects: Variables
Changes the variable’s name in the inspector. It won’t affect the script itself.
IMAGE GOES HERE
Splitter¶
Affects: Variables
Creates a line above the target variable with custom coloring and thickness (optional).
Parameters
Type |
Name |
Description |
|---|---|---|
int |
thickness |
The line’s thickness. Default value is 1. |
int |
r |
The red value of the line’s color. |
int |
g |
The green value of the line’s color. |
int |
b |
The blue value of the line’s color. |
int |
a |
The alpha value of the line’s color. |
Type |
Name |
Description |
|---|---|---|
int |
thickness |
The line’s thickness. Default value is 1. |
Color |
color |
The line’s color. |
IMAGE GOES HERE
SubHeader¶
Affects: Variables
Creates a smaller header above the target variable.
Parameters
Type |
Name |
Description |
|---|---|---|
string |
title |
The sub-header’s title. |
FUNCTIONAL¶
SetExecutionOrder¶
Affects: Classes
Sets the script’s execution order on the Execution Order settings for you. You only have to provide a value. A number below zero indicates the script will run before Default Time. A value greater than zero means it’ll run after Default Time.
Setting it to zero is likely to change nothing.
This attribute is applied in the NutCoreBootstrap.cs file.
IMAGE GOES HERE
GET HELP¶
Join this Discord server to get help, suggest new features, and vote on future updates!
See also


Sorry, this game requires support for canvas element. And probably some other things too. Try with a modern browser maybe?


Much of Europe's railway infrastructure is approaching the end of its technical lifetime. However, there are clear environmental and financial incentives for prolonging the life span of infrastructure such as bridges. The key to safely extending a bridge's lifetime is monitoring. Traditional monitoring consists of inspections carried out at intervals of several years. Advanced Bridge Monitoring (ABM) allows both road and rail bridges to be monitored continuously: both in terms of their condition and the traffic they carry. Together with preventive maintenance and traditional inspection techniques, advanced monitoring techniques extend bridge life and avoid the disruption caused by unplanned maintenance.
A significant proportion of European railway bridges are more than 60 years old. Since they were built, the load models on which they were designed have changed. For much of this period, the projected loads were overestimates: we may expect many bridges to comfortably exceed their design lifetime. More recently however, increases in goods transport have caused projected loads to be adjusted upwards. Furthermore, changes in regulation and increasing international trade mean that the loads to which a bridge is subjected are more diverse than in the past. The uncertainty associated with future loads reinforces the need for measurement. A detailed and up to date knowledge of a bridge's condition, and its load history, will allow us to predict the future condition of the bridge with greater certainty and to anticipate and pre-empt safety issues.
Traditional monitoring is based on regular physical inspection of the structure for incipient cracks. Typically, the bridge is fully inspected every six years, with smaller investigations every two years. Advanced monitoring complements these inspections; it has three components:
Structural health monitoring is the long term, low frequency, observation of a set of representative characteristics of the bridge. It is appropriate for monitoring, for instance, tilting caused by soil slides; deformation caused by loading, and corrosion caused by the bridge's environment. The choice of properties to be measured will vary with the nature of the bridge. However, generally, deformation of the bridge at midspan is the most informative parameter. No matter which measurements are chosen, for this type of monitoring it is not the absolute value of a parameter, but its change over time, that is the critical factor. The challenge is therefore to be able to resolve an extremely small effect (of the order of milliradians in the case of deformation) from spurious long-term trends such as sensor drift.
Bridge weigh in motion, in contrast, is the high frequency measurement of the load applied to the bridge. The greatest danger for bridges is fatigue, i.e. cumulative damage caused by dynamic loads. Fatigue damage is a function of a load and the number of cycles for which it was applied. For railway bridges a fatigue event can be the arrival of the train—but it can also be the cyclic loading induced as each axle crosses the bridge. Because a train may consist of carriages from several countries—which follow different axle load rules—it may be necessary to identify a given axle as an abnormal load. A BWIM system must operate with sufficient speed to be able to resolve individual axles.
Since it runs continuously, taken over time, BWIM can produce very large data sets. However, this information is only useful if the correct analytical techniques are applied. The third component of an advanced monitoring system is its analytical toolbox. In the case of BWIM, a significant amount of pattern recognition and structural modelling is required to extract high resolution loading and fatigue information. SHM produces far more modest volumes of data, however, these too are meaningless without the correct analytical tools. For SHM, acquired data are combined with structural models in a stochastic framework to develop risk predictions. These allow the client to evaluate the likelihood of various scenarios. PSP has developed several software applications, running on a central server, that integrate seamlessly with our field measurement devices to produce rigorous risk analyses.
The actual hardware of an advanced bridge monitoring system can be split into two parts: a local device (or cluster of devices) mounted on, or near, the bridge; and a central server at a remote location. The local device captures data from multiple sensors, performs pre-processing and data caching before passing the data to a central server. A typical device has 10 sensor channels which, in the case of BWIM, are sampled at up to 3kHz. The devices must be sufficiently robust to operate in a hostile environment at location that may not be easily accessed. The units are designed for low maintenance and can be powered with photovoltaic cells.
For SHM applications, we typically use one local device per bridge. This will take a few measurement-sets a day and will report these to a server once a day. For BWIM applications we use one device per railway track—clusters of devices form a LAN. One of the devices is designated as a master: this collects data from the others for each train event and passes the data to the server in near-real-time.
The second physical component of the system, the server, carries most of the computational load. This has an internet connection with the local device and so may be placed at a convenient central location. The server has several tasks: most importantly the computationally demanding data analysis and data-driven simulation. However, it is also responsible for the preparation of reports and the archiving of data. Together the local device and the server allow high resolution data to be acquired from remote locations, and analyzed using complex numerical methods.
Railway bridges are chokepoints for any industrial society. It is vital that they either remain in operation, or at worst are withdrawn from service in a planned manner. Knowledge of a bridge's condition and its load history allow informed decisions to be made about the use of the bridge and its maintenance. This is particularly important in Europe with its relatively mature stock of bridges.
Advanced bridge monitoring is made possible by the availability of three enabling technologies. Reliable, low power, embedded systems make it feasible to acquire data from physically remote locations. Cheap computational power makes it possible to undertake complex analyses and simulations using the acquired data. Finally, the spread of internet technologies makes it possible to easily link these two technologies. The combination of these technologies means that it is now possible to deploy systems that dramatically improve both the bridge instrumentation and its analysis.


Here at Again, we unlock opportunity across the entire customer lifecycle through continuous experimentation.
We partner with curious and ambitious brands helping them engage their customers and obtain stable and predictable revenue
We help brands realise their potential, grow their recurring revenue and unleash their growth.
Is your brand ready?Working with Again has been really beneficial for us to gain insights into how our audience responds. We are learning that small changes can have a big impact.
Seema Kumari, Digital Marketing & CRM DirectorAgain are invaluable. The +14% uplift in donations YoY (from the quick fixes alone) meant that the project paid for itself many times over.
Eoghan Beecher, Digital Fundraising ManagerThey will uncover the things you never knew you needed to know about your customers. They are, quite simply, the best partner I've ever had.
Peter Gray, VP of Product OptimisationTheir team of experts has allowed our business to be more nimble, responsive and to create more fulfilling experiences throughout our acquisition flow.
Firstname Lastname, 118 MoneysWorking with Again has been really beneficial for us to gain insights into how our audience responds. We are learning that small changes can have a big impact.
Seema Kumari, Digital Marketing & CRM DirectorAgain are invaluable. The +14% uplift in donations YoY (from the quick fixes alone) meant that the project paid for itself many times over.
Eoghan Beecher, Digital Fundraising ManagerThey will uncover the things you never knew you needed to know about your customers. They are, quite simply, the best partner I've ever had.
Peter Gray, VP of Product OptimisationWe’ve been in the game for a long time. 17 years in fact. If that’s taught us one thing, it’s what to do when confronted with a challenge: evolve to meet it
We understand customers today crave deeper experiences and brands yearn for predictable and stable revenue streams.
We've taken the bold move to evolve our name and proposition.
We despise assumptions. We want to know for certain. We dive deep into consumer psychology and research, delivering ROI from the get-go, kicking off with experimental forecasting which ties directly into your bottom line.
Service examples
Collaboration = success. We work with you to go from actionable insights to a strategic roadmap. A meaningful approach which whch helps inform a long-term commercial strategy.
Service examples
Pushing boundaries, rejecting shortcuts and refusing to take the easy way, that's how we roll. We craft transformative experiences which not only delight your customers but crucially: they convert.
Service examples
Our mantra is simple: we succeed when you do. We're always learning and collaborating, feeding our insights into the entire customer lifecycle - and your entire business.
Service examples


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We invite you to celebrate the largest technomanagement event in the city
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove
"A leader is one who knows the way, goes the way, and shows the way."
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>Due to inundating creativity and thirst for innovation of our students and with the constant guidance of our unparalleled faculty, Technovanza was born in 2000.
Keeping in mind our core values of working as a team with integrity and professionalism and the ultimate aim of “Taking Technology to the Society”, Technovanza has grown over the last 18 years to become one of the most popular and awaited techno-management events in the country.
Reaching out to students, industry and the society in general, Technovanza 2018 promises to be bigger than ever!


I chose Babson College because I was impressed by Babson's entrepreneurial mindset, especially its FME courses, and I wanted to learn how to be a successful entrepreneur at Babson. Babson is known for its specialized entrepreneurship courses, great diversity of international students, rich resources of connections and various opportunities for networking. I was attracted by these aspects of Babson and finally decided to choose Babson over other schools. After I graduate from Babson, I plan to pursue master degree in business, preferably in West Coast, and explore more into technology field by getting to know more people who work in this field. I want to work in this industry for a couple of years to build my own connections and hopefully can launch my own business related to artificial intelligence in a few years.
My favorite sport is swimming. I learned swimming since I was very young and I swim on a regular basis no matter in what season. Swimming is the self-propulsion of a person through fresh or salt water, usually for recreation, sport, exercise, or survival. Locomotion is achieved through coordinated movement of the limbs, the body, or both. Humans can hold their breath underwater and undertake rudimentary locomotive swimming within weeks of birth, as an evolutionary response. Swimming is consistently among top public recreational activities,and in some countries, swimming lessons are a compulsory part of the educational curriculum. As a formalized sport, swimming features in a range of local, national, and international competitions, including every modern Summer Olympics.


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The inaugural edition of Refactor Camp was held on Saturday, March 3, 2012 at the San Francisco Zoo. The goal for this inaugural edition was to talk about the idea of "scratching your own itch" as a way of figuring out interesting lifestyles and projects for yourself. The idea behind holding the event at a zoo was to catalyze some creative thinking about the interplay between generativity and captivity in pursuing itch-scratching impulses.


The Carnival in Vitória are performed one week before Carnival, more precisely in Sambão do Povo. The schools are responsible for choosing their own themes, which usually revolve around historical happenings or some sort of cultural or political movement.
The most famous (and usually the winners) samba schools are Unidos de Jucutuquara, MUG, Andaraí, Independentes de Boa Vista, and Novo Império.
More than the traditional school parade, the carnival in Espirito Santos includes a large set of attractions, especially in the beach areas of the state, from north to south.
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Incorporates feedback mechanisms in agricultural development projects
to build an evidence base that improves decision-making, adoption, and impact!
5Q explores Knowledge, Attitudes, and Skills (KAS) to understand farmers' perceptions.
Knowledge is the first step to adopt a new agricultural innovation. Attitudes towards new practices depend on a combination of the individual’s belief that it will lead to the desired outcome (outcome belief) and the values he or she attributes to those outcomes (social norm). KAS identifies people's perception of a new practice, technology, or service. Understanding cognitive barriers and drivers for adoption is essential for knowledge transfer strategies in agricultural development projects. Skill for subsumption knowledge transfer into farmer practice is the last and main desirable change, and it generally occurs because of previous changes in knowledge, skills, and attitude toward a practice or service.
Smart
Question Trees
__
Simple sets of five questions that query changes in Knowledge, Attitudes, and Skills (KAS) form the basis of the 5Q approach. A logic-question-tree structure is used to keep it simple and smart.
Internet
Communication Tools
__
ICT channels facilitate more cost-effective data collection. Feedback about project success and KAS of beneficiaries is crowd-sourced at a low cost.
Data
Science
__
Iterative, descriptive analytics from raw data and customizable reports are used to enable fast sharing of insights.
Decision
Making
__
The key to institutionalizing feedback systems is making the results publicly available in real-time. Therefore, quick and easy visualization of changes is used to provide findings for decision-making.
| Less is More: The 5Q Approach | CGSpace | Download |


This is a very basic example of MoViS can be used. In this case, there
are two rectangles that fade in and out alternatively.
The "Change state" button is only changing the state value that is stored in the
global movis object. The attached listeners are then called for synchronizing
the view component.
The "Undo last change" button is using the "undoState" function of the
movis object to undo the last change that has been made to the state.