Reviewerly/exHarmony huggingface dataset:
Colleagues of William M. Jackson

ADVERTISEMENT RETURN TO ISSUEPREVSpecial Issue Prefac...Special Issue PrefaceNEXTColleagues of William M. JacksonWilliam M. JacksonWilliam M. JacksonMore by William M. Jacksonhttp://orcid.org/0000-0002-1961-9466Cite this: J. Phys. Chem. A 2019, 123, 10, 1914–1915Publication Date (Web):March 14, 2019Publication History Published online14 March 2019Published inissue 14 March 2019https://doi.org/10.1021/acs.jpca.8b12224Copyright © 2019 © William M. JacksonRIGHTS & PERMISSIONSArticle Views201Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (165 KB) Get e-AlertsSUBJECTS:Clay,Students Get e-Alerts
Programming with Implicit Values, Functions, and Control (or, Implicit Functions: Dynamic Binding with Lexical Scoping)

We introduce two new language features, called implicit functions and implicit control. Both generalize implicit values (or parameters) which are a typed implementation of dynamic binding. Implicit functions are bound dynamically but evaluated in the lexical scope of their binding. We show how this small generalization from regular implicit values leads to better abstraction. In particular, implicit functions encapsulate (side) effects at the definition site, as opposed to leaking them to the call site. Implicit control further generalizes implicit functions by adding the ability to return into the lexical scope of the binding or to resume to the call-site. We formalize the new features as an extension to Moreau’s calculus of dynamic binding (1998). Unifying all three language features in one framework guarantees that the interaction between implicit values, functions, and control is well-defined. We also show how our semantics correspond to a macro-translation into algebraic effect handlers.
How To Make Your Study Schedule To Get Best Grades In A-Levels

At this stage of education, you need to make an effective study plan.   You should ask A- Level teacher about good grades. He will give
The Public Image of Vietnamese Public Administration Services on Social Media – A Comparison Between Structured and Unstructured Data

Because of the nature of public administration services, people often provide irrelevant information on the fact of service experience for public agents to improve their services in surveys. However, Vietnamese Facebook users could give more insights to show their dissatisfaction via their posts, comments, status. We assumed that PAPI 2016 results (Vietnam Provincial Governance and Public Administration Performance Index – the joint collaboration between Vietnamese governmental agents and UNDP) showed the positive public image of Vietnamese pubic administration services with five dimensions: (1) Participation at Local levels, (2) Transparency, (3) Vertical Accountability, (4) Control of Corruption in the Public Sector and the unstructured information from Facebook big data mining in the same period could reveal the negative images. The combination then map a comprehensive image of five characteristics of Vietnamese public administration services. Our findings showed that there are many negative insights of Facebook users’ posts which reflect a part of the other side public image of public service agencies.Keywords: text mining data, big data, Facebook, public image, public administration services.
Gradient Descent Analysis: On Visualizing the Training of Deep Neural Networks

We present an approach to visualizing gradient descent methods and discuss its application in the context of deep neural network (DNN) training. The result is a novel type of training error curve (a) that allows for an exploration of each individual gradient descent iteration at line search level; (b) that reflects how a DNN’s training error varies along each of the descent directions considered; (c) that is consistent with the traditional training error versus training iteration view commonly used to monitor a DNN’s training progress. We show how these three levels of detail can be easily realized as the three stages of Shneiderman’s Visual Information Seeking Mantra. This suggests the design and development of a new interactive visualization tool for the exploration of DNN learning processes. We present an example that showcases a conceivable interactive workflow when working with such a tool. Moreover, we give a first impression of a possible DNN hyperparameter analysis.
Bias detection in Philippine political news articles using SentiWordNet and inverse reinforcement model

Not all information posted on the internet is deemed 'trustworthy.' Some articles, especially those related to politics, seem to display traces of bias, whether they be for or against the Philippine administration. This research aims to determine if a news article—and by extension, a news outlet—is biased based on its sentiments and use of lexica. Data were harvested from chosen websites and news outlets provided by Alexa. These data underwent pre-processing and were scored based on their sentiments with the use of SentiWordNet. The resulting scores were then fed into the Inverse Reinforcement Model, which determined whether an article is biased or not. With the use of Inquirer, Philstar, Manila Bulletin, The Manila Times, and Journal Online news articles, the system was able to detect bias with an accuracy rating of 0.89, precision of 1, recall of 0.60 and F-Measure of 0.75.
Tips to protect yourself from a cyber attack

According to a recent study, did you know that on average a person touches their phone 2,617 times per day? As some of the biggest online users in the world, Canadians visit more sites and spend more time on the internet than any other country. Within the last 24 hours, how many times have you checked your bank account through an online app? Checked your social networking sites (Facebook, Twitter, etc.) or used email? Downloaded or shared a file? Shopped online? While we do this everyday without giving it a second thought, it’s important to realize that everything we do online puts us at risk for a cyber attack, or being “hacked”.<
Deep Random Splines for Point Process Intensity Estimation

Gaussian processes are the leading class of distributions on random functions, but they suffer from well known issues including difficulty scaling and inflexibility with respect to certain shape constraints (such as nonnegativity). Here we propose Deep Random Splines, a flexible class of random functions obtained by transforming Gaussian noise through a deep neural network whose output are the parameters of a spline. Unlike Gaussian processes, Deep Random Splines allow us to readily enforce shape constraints while inheriting the richness and tractability of deep generative models. We also present an observational model for point process data which uses Deep Random Splines to model the intensity function of each point process and apply it to neural population data to obtain a low-dimensional representation of spiking activity. Inference is performed via a variational autoencoder that uses a novel recurrent encoder architecture that can handle multiple point processes as input. We use a newly collected dataset where a primate completes a pedaling task, and observe better dimensionality reduction with our model than with competing alternatives.
TEACHING INFORMATICS IN A PEDAGOGICAL UNIVERSITY TAKING INTO ACCOUNT FOREIGN LANGUAGE STUDENTS

The emergence of an increasing number of foreign students in Russian universities indicates the importance of the Russian higher education system in the world community. At the same time, a new problem emerged on the agenda — how to train foreigners from abroad with high quality, taking into account their different readiness in mastering the Russian language and different subject training. The article describes the problems that foreign students face when studying informatics at a pedagogical university. The combined profiles, including “Informatics”, of the Faculty of Physics and Mathematics of Mordovian State Pedagogical Institute named after M. E. Evsevjev were the experimental research site. On the example of the “Theoretical Foundations of Informatics” discipline, the ways of teaching informatics are shown. Examples of assignments, including tasks for independent work, for teaching foreign students to informatics at the specified university are given.
Is your business protected from cyberattacks

Cybersecurity may seem like an intimidating term and a daunting process. However, protecting your business from breaches should be a top priority, and it’s not as complicated as you may think. A few preventive measures can help keep your office secure from debilitating, costly cyberattacks and spare you more than a few headaches. Here are a few steps you can start taking today.<
Towards the Automatic Processing of Language Registers: Semi-supervisedly Built Corpus and Classifier for French

Language registers are a strongly perceptible characteristic of texts and speeches. However, they are still poorly studied in natural language processing. In this paper, we present a semi-supervised approach which jointly builds a corpus of texts labeled in registers and an associated classifier. This approach relies on a small initial seed of expert data. After massively retrieving web pages, it iteratively alternates the training of an intermediate classifier and the annotation of new texts to augment the labeled corpus. The approach is applied to the casual, neutral, and formal registers, leading to a 750 M word corpus and a final neural classifier with an acceptable performance.
Adversarial attack on Speech-to-Text Recognition Models

Recent studies have highlighted audio adversarial examples as a ubiquitous threat to state-of-the-art automatic speech recognition systems. Thorough studies on how to effectively generate adversarial examples are essential to prevent potential attacks. Despite many research on this, the efficiency and the robustness of existing works are not yet satisfactory. In this paper, we propose~\textit{weighted-sampling audio adversarial examples}, focusing on the numbers and the weights of distortion to reinforce the attack. Further, we apply a denoising method in the loss function to make the adversarial attack more imperceptible. Experiments show that our method is the first in the field to generate audio adversarial examples with low noise and high audio robustness at the minute time-consuming level.
Mixed Formal Learning

This paper presents Mixed Formal Learning, a new architecture that learns models based on formal mathematical representations of the domain of interest and exposes latent variables. The second element in the architecture learns a particular skill, typically by using traditional prediction or classification mechanisms. Our key findings include that this architecture: (1) Facilitates transparency by exposing key latent variables based on a learned mathematical model; (2) Enables Low Shot and Zero Shot training of machine learning without sacrificing accuracy or recall. (Abstract)
A Real Estate and Landed Property Blockchain Distributed Ledger for Elimination of Double Dealing

In the real estate sector of the national economy land racketeering and property double selling have risen to a higher level due to activities of malicious land agents and those that abetted their dubious activities within the government.In this paper a Blockchain of Real Estate and Landed Property transaction ledger system is developed to record property transactions in a distributed ledger that makes double dealing by the criminal land agents impossible.This will prevent the selling of properties to more than one person by land agents and double dealers and will publish transactions in a public ledger in a transparent way.The system is designed using object-oriented analysis and design methodology and the Blockchain was built directly from the cryptographic system.The result of the system development show that the system was able to produce crypto blocks which can be mined and stored in the chain to both produce the data and the reward system for the real estate industry to use in protecting itself from double dealing and from the criminals.The work is implemented using public key cryptography and Python programming language.The system will bust the real estate sector and bring to minimum the malicious activities of the land agents and their collaborators who commit crime by swindling unsuspecting land buyers and property developers of their fund by double selling and dealing on properties that does not belong to them.
Extending the Limits of the Random Exploration Graph for Efficient Autonomous Exploration in Unknown Environments

The autonomous construction of environment maps using mobile robots is a fundamental problem of robotics; this is because virtually all tasks performed by robots need a representation of the working environment to operate. Although many works have addressed this problem known as SLAM, it still remains open; since most of the solutions do not consider a planner that allows the robot to explore autonomously the working environment or the works that consider it, they have developed slow algorithms that do not guarantee a total coverage of the environment or an optimal development of the exploration, which may result in maps of poor quality or definitely not usable given this lack of information. Thus, this work presents a new exploration method based on the random exploration graph (REG), which, unlike its predecessor, defines a systematic analysis of the next positions to be explored eliminating randomness in decision-making and thus minimizing the amount of movements that the robot must make to reach them and the time required to achieve total coverage of the environment. Additionally, a series of tests carried out on the proposed method are presented, and the results obtained in classical variables such as time and distance allow to validate the efficiency of our approach.
WORLDSKILLS CHAMPIONSHIP AND ITS ROLE IN IMPROVING THE PROFESSIONAL LEVEL OF FUTURE TEACHERS

Today education system is being modernized to meet the requirements of modern times, reflected in educational and professional standards. Platforms for working out the requirements are various contests. The article describes one of the most popular competitions — WorldSkills, in which competitions for professions are organized, including the profession of a teacher in secondary and high schools. Also the scenario of the lesson proposed by the author at the final of WorldSkills Russia 2017 is presented in the article.
Research Guides: Library System Migration: Students

Information about the January 2019 migration from the ALEPH Library System to the ALMA Library System. Information for students about the migration
Emotional Stress Assessment Using Facial Thermal Imprint

Thermal imaging is one of the most promising methods of probing the psychological status of human beings because of its non-invasiveness. This study develops a new method of assessing the emotional stress status in real time. The differential temperature between philtrum and forehead (DTPF) algorithm is developed to extract stress-induced thermal imprints. The correlation between the extracted thermal imprints and established stress markers is significant. Experimental result demonstrates that DTPF has the capacity to classify stress and baseline status.
PKM Kelompok Petambak Udang Dalam Upaya Memantau dan Menjaga Kualitas Tambak di Kecamatan Mlonggo Kabupaten Jepara

Gumuk Mas and Udang Lestari is a group of shrimp farmers in the Kec. Mlonggo Kab. Jepara. in checking water quality still uses traditional methods, namely by seeing the shrimp floating on the surface of the pond. if there is, the shrimp lacks oxygen, is prone to disease and will interfere with its breeding. when approaching the harvest time the shrimp farmers turn on the waterwheel continuously every day so that the shrimp does not lack DO (Dissolved Oxygen), even if the waterwheel continues then it will result in excess DO and wasteful electricity. Therefore we need a solution for checking water quality and waterwheel control. this activity proposes two main activities, namely training and farm management skills well related to monitoring and control of Dissolved Oxygen. this activity so that shrimp farmers can monitor the quality of shrimp pond water at any time. if water quality is lacking or exceeds the limit, prevention activities can be carried out as soon as possible and can increase crop yields and the welfare of shrimp farmers
Politeness Maxims used in the Dialogue of America’s Presidential Candidates Debate between Donald Trump and Hillary Clinton

The undergraduate thesis entitled “Politeness Maxims Used in the Dialogue of America’s Presidential Candidates Debate between Donald Trump and Hillary Clinton” mainly aims at observing the violation of Politeness Maxims in the dialogue’s debate between Donald Trump and Hillary Clinton. The study is directed to answer two basic questions; kinds of violation of politeness maxims in the dialogue of the America’s Presidential Candidates Debate and the implicatures of those dialogues. There are two aims of this study; to describe the kinds of violation of politeness maxims in the dialogue of the America’s Presidential Candidates Debate and to explain the implicature of those dialogues. The data were collected through the observation and documentation methods in which the data were taken on YouTube and the transcription found on the internet. The data were analyzed using the qualitative method based on the theory of politeness maxims proposed by Geoffrey Leech. The study explained about the violation of maxims in the term of politeness maxims. The findings that the writer obtained from the analysis were many expressions were used to violate the politeness maxims. There were two data found in the dialogue that violated Tact Maxims, nine data that violated Approbation Maxim, ten data that violated Modesty Maxim, and nine data that violated agreement maxims. While Generosity and Sympathy Maxim were not found in those dialogues. Based on the violation of the politeness maxims that parts of the dialogue contain, the writer can obtain the form of implicature from it. Thus, politeness maxims became the main theory to analyze the violation of politeness maxims and implicature in parts of the dialogues.
Crime research agenda

The Crime Research Agenda sets out the crime research priority areas of the Queensland Government Statistician’s Office. The agenda was developed through consultation with key stakeholders and advice from the Crime Research Reference Committee which includes representation from criminal justice agencies, academics and other government agencies.
Silhouette Photo Style Transfer

Silhouette photography is popular among photographers. However, it is hard for ordinary users to shoot this kind of photos because of the limitations of cameras, weather and skills. In this work, we propose an automatic photo style transfer approach that can generate realistic silhouette images. First we present a sky segmentation method to divide an input image into an object foreground and a sky background. Then, for the background, we implement a statistic color transfer method using a specified sky photo. Finally, in order to generate natural results, we develop an adaptive approach to adjust the color of the object foreground considering the ambient color computed from the stylized background. The experimental results show that our methods can achieve satisfactory sky segmentation results and generate aesthetically pleasing silhouette photos.
A Tale of Two Tasks: Designing and Validating Secure Software

Presented on March 8, 2019 at 12:00 p.m. in the Klaus Advanced Computing Building, Room 1116.
HOW FRECKLES CORRESPOND TO BLOOD GROUPING

The objective of present study was to co-relate blood grouping with freckles.  A total of 172 subject participated in present studies. The subjects were the students in Bahauddin Zakariya University Multan, Pakistan. I investigate the blood group of these subjects and then ranked them in relation with their blood type. I made the questionnaire and asked them they have any freckles on their faces or not during sampling of the subject. It was concluded from the present study that A+ people have more freckles on their faces and B+ are the least.
Towards Privacy-aware Software Reuse

As software becomes more complex, reusing and integrating artifacts from existing projects that may be taken from open or organization-proprietary repositories is becoming an increasingly important practice. This practice requires an in-depth understanding of the projects to be reused and particularly their common and variable features and their non-functional requirements. Different approaches have been suggested to analyze similarity and variability of different kinds of artifacts (mainly, requirements and code), e.g., clone detection and feature mining. These approaches, however, mainly address functional aspects of the software artifacts, while mostly neglecting aspects dictated by non-functional requirements. The recent progress with the General Data Protection Regulation (GDPR) highlights the importance of handling privacy concerns in software development. However, existing approaches do not directly refer to privacy challenges in software reuse. In this paper we propose integrating these two lines of research and introduce a privacy-aware software reuse approach. Particularly, we suggest to extend VarMeR – Variability Mechanisms Recommender – which analyzes software similarity based on exhibited behaviors and recommends on polymorphism-inspired reuse mechanisms, with privacy awareness considerations. These considerations are reflected in “privacy levels” of the reused artifacts.
Photo Aesthetic Scoring Through Spatial Aggregation Perception DCNN on a New IDEA Dataset

The aesthetic quality assessment of image is a challenging work in computer vision field. The recent research work used the deep convolutional neural network to evaluate the aesthetic quality of images. However, the score of image data sets has a strongly normal distribution, which makes the training of neural network easy to be over-fitting. In addition, traditional deep learning methods usually pre-process images, which destroy the original aesthetic features of the picture, so that the network can only learn some superficial aesthetic features. This paper presents a new data set what images distributed evenly for aesthetics (IDEA). This data set has less statistical characteristics, which is helpful for the neural network to learn the deeper features. We propose a new spatial aggregation perception neural network architecture which can control channel weights automatically. The advantages and effectiveness of our method are proved by experiments in different data sets.