Reviewerly/exHarmony huggingface dataset:
Conservative Offline Distributional Reinforcement Learning

Many reinforcement learning (RL) problems in practice are offline, learning purely from observational data. A key challenge is how to ensure the learned policy is safe, which requires quantifying the risk associated with different actions. In the online setting, distributional RL algorithms do so by learning the distribution over returns (i.e., cumulative rewards) instead of the expected return; beyond quantifying risk, they have also been shown to learn better representations for planning. We propose Conservative Offline Distributional Actor Critic (CODAC), an offline RL algorithm suitable for both risk-neutral and risk-averse domains. CODAC adapts distributional RL to the offline setting by penalizing the predicted quantiles of the return for out-of-distribution actions. We prove that CODAC learns a conservative return distribution -- in particular, for finite MDPs, CODAC converges to an uniform lower bound on the quantiles of the return distribution; our proof relies on a novel analysis of the distributional Bellman operator. In our experiments, on two challenging robot navigation tasks, CODAC successfully learns risk-averse policies using offline data collected purely from risk-neutral agents. Furthermore, CODAC is state-of-the-art on the D4RL MuJoCo benchmark in terms of both expected and risk-sensitive performance.
LibGuides: Student Career Pathways: Jobs for Students

Look for information on jobs for high school students, as well as future career opportunities.
Formalising Solutions to REST API Practices as Design (Anti)Patterns

REST APIs are nowadays the de-facto standard for Web applications. However, as more systems and services adopt the REST architectural style, many problems arise regularly. To avoid these repetitive problems, developers should follow good practices and avoid bad practices. Thus, research on good and bad practices and how to design a simple but effective REST API are essential. Yet, to the best of our knowledge, there are only a few concrete solutions to recurring REST API practices, like “API Versioning”. There are works on defining or detecting some practices, but not on solutions to the practices. We present the most up-to-date list of REST API practices and formalize them in the form of REST API (anti)patterns. We validate our design (anti)patterns with a survey and interviews of 55 developers.
Distinct Actions Classification Using Human Action Tracker Technique in Sports Videos

Recognizing human action in sports is difficult task as various sequences of activities involved in every scene. Identifying each action individually without overlapping of movements is a tedious process due to continuous change of frames within short duration. So proper tracking of human movements for each action is important. Hence new structure-based human action recognition and tracker technique (HART) is proposed. It uses joint trajectory images and visual feature to design each human action. At first, a structural based method employed to extract human skeleton data points from RGB (Red Green Blue) videos. Next, a Multitude Object Tracker (MOT) is proposed which uses the trajectory of human skeleton joints in an image space for identification of actions. Then, Histogram of Oriented Gradients (HOG) combined with Support Vector Machine (SVM) is applied to extract physical body shape and action information. Finally, the action label and interconnected keypoints in humans is jointly detected as end result. The proposed HART technique effectively performed well with the accuracy of about 82% over the other activity recognition methods.
The Beginning of the Glass Age with Holographic Game Technology

The development of technology has now begun to shift to society 5.0, this technology has helped many human activities. The development of technology is also followed by the development of games, games in holographic form have been made by several developers, however, there are not many games in the holographic form that are marketed and played by many players. Hologram technology is a technology that is starting to develop at this time. There have been several games made from holograms, in fact, there are already tools to view or display holographic shapes. This paper explains that the creation and development of games using holographic technology has been around for decades. The development of the times has slowly begun to expand and develop knowledge about hologram technology by making hologram games and adding or developing ways of interacting with these hologram games. Keywords—Hologram Game Technology, 3D Hologram, Hologram for Game, Modern Technology
LibGuides: Future Production: Mining: Upcoming events

This guide was designed to support research. This Guide contains useful library and information resources and services provided by CSIR Information Services (CSIRIS). Click on the tabs above or the quick navigation side panel on the left to find resources
MS\^2: Multi-Document Summarization of Medical Studies.

To assess the effectiveness of any medical intervention, researchers must conduct a time-intensive and manual literature review. NLP systems can help to automate or assist in parts of this expensive process. In support of this goal, we release MSˆ2 (Multi-Document Summarization of Medical Studies), a dataset of over 470k documents and 20K summaries derived from the scientific literature. This dataset facilitates the development of systems that can assess and aggregate contradictory evidence across multiple studies, and is the first large-scale, publicly available multi-document summarization dataset in the biomedical domain. We experiment with a summarization system based on BART, with promising early results, though significant work remains to achieve higher summarization quality. We formulate our summarization inputs and targets in both free text and structured forms and modify a recently proposed metric to assess the quality of our system’s generated summaries. Data and models are available at https://github.com/allenai/ms2.
Computational method for football stadium renovation: A computational method for the renovation of football stadiums to facilitate designers into making decisions

A growing trend is present nowadays towards the renovation of football stadiums with the main objectives of enhancing the capacity of the venues and of mproving the user experience of the spectators. The stadium design process requires to blend multiple components together, while evaluating different performances and complying with several requirements. In addition, the complexity of the process is increased in case of a renovation by considering the constraints and the components of the existing stadium. Hence, the decision-making process of the designer results to be difficult and it is likely to produce few inefficient designs. The introduction of computational methods can facilitate the decision-making process, allowing the designer to explore multiple solutions and to produce more efficient designs. This study explores how a computational method can be developed for stadium renovation to support the designer into making decisions in the early design phase, allowing them to explore multiple solutions that improve the initial performances of the stadium. A digital workflow was developed to generate different existing stadiums and to evaluate the performances related to the viewing quality and the roof structure. The study highlights how a designer is able to identify the portions to be kept based on the performances of the stadium and to develop a concept for the renovation, from which multiple design alternatives can be produced in the optimization process. Inefficient designs can be identified quickly and discarded, allowing to concentrate on more efficient concepts for the renovation, which will be further developed in the subsequent phases of the design process.
Blockchain Technology: An Overview

Change is inevitable in the field of technology and it is what has kept us going to for so long. Digitization has made lifestyle faster, easier and much more efficient. Organizations developed technologies with much higher productivity than their traditional methods. Let us consider the data collection, storage and transmission methods. It provided a much consistent and dependable database management system over the traditional file system. And every day the technology keeps on advancing to a better version of itself. Blockchain Technology is such an example of advanced technological innovation that has provided a whole new branch of technical solutions with much higher productivity. It also introduced a new style of business with cryptocurrencies that have high security due to advanced cryptography.
A REQUIREMENT ENGINEERING IN REPORTING AND COUNSELING-BASED ASSISTANCE APPLICATION FOR VICTIMS OF VIOLENCE AGAINST WOMEN

Requirements engineering is the initial phase of the software development life cycle it is a critical aspect of application development since it has a significant impact on the results of the product being created. This article focuses on the engineering requirements of the web-based application development process for reporting and assisting victims of violence against women using the Loucopoulos and Kanakostas Iterative Requirements Engineering Process Model. The application was created to contribute to the solution of the problem of violence against women in Indonesia, where violence against women is an iceberg phenomenon because not all incidents are reported. Furthermore, victims of violence against women require support in receiving emotional support in the form of counseling, which can be done online via chat or video calls. The results of these requirements engineering are alternative solutions, application feature design, database design, system modeling using UML, and application architecture design. The validation of requirements engineering was carried out using a low fidelity prototype
Can a Decoy Affect Consumer’s Decision Process? A Case on Multi-Stage Decision Making Model

A decoy is an object which supposedly has an advantage. When a decision making was still in process, could a decoy influence and alter the decision? Particularly did it influence universal set, retrieval set, consideration set and choice? The study purported to explore the effect of a decoy in multi-stage decision making when the process was still lasting. A sample consisting of 125 graduate and post-graduate students was withdrawn through judgment and convenience technique. Data submitted by questionnaires, employing Likert scale, ranging from 1= completely disagree to 5= completely agree. An Amos 22.0 and SPSS 21.0 were exercised to analyze data. The finding showed that there was an effect of a decoy on universal set and retrieval set. In addition, there was an influence of retrieval set on consideration set and consideration set on choice.
Blatant Disregard of Human Rights during the Time of the Global Pandemic - A Study

Literates and illiterates are classified in the whole world when education is to be considered. At least if a person knows how to put his signature on paper in any form and any language, he is called literate. Mother is the first teacher to the child in the house later teachers of the class will start.
Changes in the Regional Structure of China's Domestic Market and Implications

In response to intensifying conflict with the United States and the shock of Covid-19, China reinforced its strategy to expand domestic demand. China's domestic market is an important factor affecting Korea's exports and economic growth. Accordingly, a large body of research has been conducted in Korea on China's expansion policy and changes in its domestic market. However, most studies have analyzed changes in China's consumer market, import market and imported items, limiting the overall understanding of China's domestic economy. In addition, most studies on China's regional domestic market have analyzed the market segmented by region.Recognizing this gap, this study expanded the scope of analysis of the domestic market in China to the entire domestic final demand, and analyzed inter-regional trade relations and other economic relations based on an inter-regional input-output analysis, which has rarely been attempted in analyses of the Chinese domestic market.In addition, the changes in the regional structure of the Chinese import market and Korea's competitiveness were analyzed using Chinese trade statistics. In particular, by synthesizing the changes after the global financial crisis, a turning point in China's economic structure, we project future changes in the regional economic structure of China, which emphasizes the independence of its domestic economy. In addition, in the era of US-China conflict, the study aimed to select regional markets meaningful to Korea, and to present strategic directions toward China focusing on regional cooperation and approaches into the domestic market.
Hybrid model in accounting education: The experience of management simulation course

Due to the COVID-19 pandemic and its effects on education, he transformation of didactics and technological methods was necessary to promote students’ self-learning and motivation, alongside teachers’ tutoring, guiding students’ academic journey. This paper aims to investigate the effect of COVID-19 on digitalization accounting in higher education and explores the students’ perception of the adapted hybrid model. The study follows a qualitative approach and rely on the final-year students of the accounting and management degree of Accounting and Business of Porto Polytechnic School. Data were collected through a questionnaire from students who experienced both distance and face-to-face education and completed the course of Management Simulation. The study highlights the digitalization of accounting teaching and the pandemic’s effect on the future of digital accounting education. In sum, the hybrid model meets the needs of this practical course and can be a model to be applied in the future.&#x0D; Keywords: Accountant; Digitalization Accounting Education; Digital Hybrid Pedagogy; Digital Education; Human Skills.&#x0D; &#x0D; &#x0D;
THE IMPACT OF EDUCATION ON THE DEVELOPMENT OF THE DIGITAL ECONOMY

The article discusses the features of the education system in the formation of the digital economy. The essence of the concept of digital economy, information and communication technologies, as well as the result of their use in the pedagogical process. The main directions of implementation of information technologies in the education system, the pedagogical goals of using information and computer technologies in the learning process. The topic of state regulation and provision of digitalization of the education sector was touched upon, the main directions were highlighted. The problem of organizing network interaction from the perspective of joint activities within the framework of e-learning and distance educational technologies is considered. It is indicated that one of the conditions for the formation of a harmoniously developed personality in modern society is an active the use of information and communication technologies in the pedagogical process. Their role in the formation of more comfortable conditions for the work of a teacher was also noted.
Research on English Classroom Teaching System Based on K-means Clustering Algorithm in Modern Information Technology Environment

The classroom teaching concept of modern information technology has become a new direction of college English teaching reform in China. At present, under the information technology environment, China's college English teaching reform is facing new opportunities and challenges. In this paper, according to the actual situation and development trend in English classroom teaching, Struts framework technology is used to design and implement the system. According to the general specification of software engineering design, a set of English classroom teaching assistant system is designed and implemented, and requirements analysis, overall design, database design and source code are given. This paper mainly introduces the classical K-means algorithm, and establishes a teaching video retrieval model based on text clustering. In this model, the video text is used as the index to search and optimize the search results, and the search results are optimized and classified. This system can well adapt to the actual characteristics of English open teaching and meet the needs of auxiliary functions in English teaching.
Video based Human Face Mask Recognition System for Access Control

Face mask recognition is the most basic and important security method for identifying people. The most important objective of this research is to apply this method at school entrances, airports, hospitals, and workplaces, where the risk of COVID -19 spreading via contagion is quite significant. According to the report, wearing face masks while at work significantly lowers the risk of transmission. It's an issue of object detection and classification with two classes (With Mask and Without Mask). For identifying masks, a hybrid model that combines deep and conventional machine learning is used. This face mask detector is made using Python, OpenCV, Tensor Flow, and Keras and is based on an information set. Everyone should check their face before entering the ant location to ensure they have a mask with them. If someone is discovered without a facemask, a beep alarm will be triggered. As all of the establishments open, the number of cases continues to rise throughout the nation. It may be brought to a close if everyone adheres to the safety and security procedures. As a result, we anticipate that this module will assist in identifying masks when people come to figure out.
Text Structure Teaching on the Development Of Persuasive Writing Skills for High School Students in the United Arab Emirates

espanolEl estudio tuvo como objetivo revelar la eficacia de la ensenanza de la estructura del texto en el desarrollo de habilidades de escritura persuasiva para estudiantes femeninas de octavo grado en las escuelas de Abu Dhabi. Se prepararon pruebas para medir el desempeno del personal de estudio en los departamentos de redaccion persuasiva, y se desarrollo un estandar para medir el desempeno en la prueba. El estudio revelo la presencia de una diferencia estadisticamente significativa entre los promedios aritmeticos del desempeno de los miembros del estudio, en cada uno de los cuatro departamentos de escritura persuasiva. Este estudio debe estar colectivamente a favor del grupo experimental. EnglishThe study aimed to reveal effectiveness of teaching the text structure in developing persuasive writing skills for female student of 8th grade in Abu Dhabi schools. Tests were prepared to measure the performance of study personnel in persuasive writing departments, and a standardwas developed for measuring performance in the test. The study revealed the presence of a statistically significant difference between the arithmetic averages of the performance of the study members in each of the four departments of persuasive writing. This study should collectively be in favor of the experimental group.
Combining Clustering and Regression Models for Recommending Researchers

Due to the increase in scientific production, especially in recent years, management and decision support challenge also increase significantly. The task of recommending researchers, for example, to a project is not simple. Even with the proper amount of data, ranking and recommending researchers becomes a challenging process. Despite the different methods, what can happen is that the datasets of an institution or research areas do not have a ranking value, that is, a value that can be used to assess the position of a researcher. Even having a necessary dataset, there is no ranking information for these researchers, and this process of obtaining data for training a model can be costly. We propose to use clustering techniques to support the ranking process, reducing the human effort to obtain examples for models training. Then, we used this dataset to train the regression models and Mean Squared Error (MSE) and Normalized Discounted Cumulative Gain (nDCG) to evaluate them. Tests demonstrate that our solution can support the researchers' recommendation process in an adaptive process to the needs of an organization.
A study of the water resources management and division of the groundwater heat pump system construction in Anyang

Considering the occurrence condition and water resources management, this paper studies the zoning of the groundwater heat pump system in the city of Anyang in Henan, makes the combination of technology and management and improves the evaluation standard, which is of good practicability. The evaluation of groundwater resources management and division is established by synthetically analyzing the hydrogeological, hydrodynamic and hydrochemical conditions of Anyang. The first-level evaluation is carried out by using the improved analytic hierarchy process of cloud model. The second-level evaluation is completed by using GIS spatial analysis function, dividing the groundwater heat pump system into three grades in the study area. The results show that the suitable development area for the groundwater heat pump system is 117.45 km2, which mainly distributes in the strong groundwater-abundant area in the center of the alluvial-proluvial fan of the Anyang River and partially distributes in the peripheral area at the fan edge. The restricted development area covers an area of 459.26 km2, which distributes in the hilly weak groundwater-abundant areas in southwest and north of the fan margin with the groundwater level drawdown funnel in the center of the fan body. The forbidden development area is of 24.02 km2 and distributes crossly, covering the water source area, the protected area of the South-to-North Water Transfer Project, along the railway and expressway. It is more comprehensive and reasonable to take the groundwater resources management and division into account on the basis of the suitability zoning, which may provide references for the scientific layout and rational development and utilization of the groundwater heat pump system.
Value-aware Approximate Attention

Following the success of dot-product attention in Transformers, numerous approximations have been recently proposed to address its quadratic complexity with respect to the input length. However, all approximations thus far have ignored the contribution of the *value vectors* to the quality of approximation. In this work, we argue that research efforts should be directed towards approximating the true output of the attention sub-layer, which includes the value vectors. We propose a value-aware objective, and show theoretically and empirically that an optimal approximation of a value-aware objective substantially outperforms an optimal approximation that ignores values, in the context of language modeling. Moreover, we show that the choice of kernel function for computing attention similarity can substantially affect the quality of sparse approximations, where kernel functions that are less skewed are more affected by the value vectors.
Blokzincir Halk Sağlığının Geleceğini Şekillendiren Bir Yapı Mı? COVID-19 Üzerinden Bir Değerlendirme

This year, the world was introduced to the covid-19 pandemic. COVID-19 has emerged as a major public health problem. It has affected not only health, but also the economy, social life and digital technology. Digital transformation in the world has also accelerated. Blockchain also continues to develop as an important technology. Public health solutions are also evolving in line with the changing world. Here, the uses of blockchain technology in the field of public health are evaluated. Solutions at many different points, such as medical records, supply chains, have been studied. An attempt has been made to demonstrate the contribution that blockchain technology can make to the fight against COVID-19.