Reviewerly/exHarmony huggingface dataset:
A Social Network Scrum Framework for Software Development under COVID 19 Pandemic

This research proposes a framework for social network scrum meeting that serves as an alternate means for work continuation under the COVID-19 pandemic. Conventional agile and scrum methods that require in-person meeting on daily basis, as well as scrum process become impractical under stringent ‘social lockdown’ mandates. To prevent any disruptive discontinuity, the proposed framework sets up an online meeting to replace the in-person stand-up meeting and scrum. Some supporting practices are also established to adjust both agile and scrum event flows that suit this online encounter. They are production development setup and social network meeting. The former offers industrial practices that are well entrenched and proven, while the latter has been used extensively in this digital age. The proposed method is tested with computer science student’s projects. Students are able to continue their meeting, discussion, and some outputs rather than being isolated with no fruitful outcome. The proposed method does establish some ground work to be explored for future software development environments that will suit to the imminent digital technological advancement.
KEMAMPUAN MENENTUKAN UNSUR INSTRINSIK CERPEN “MERDEKA” KARYA PUTU WIJAYA PADA SISWA KELAS VII SMP KARTIKA II-2 BANDAR LAMPUNG

In short story learning activities, students are not only directed to understand theories such as recognizing short story characteristics, intrinsic elements of literary work (short stories), but literary learning is directed to how students are able to find intrinsic elements contained in short stories such as, plot, setting, point of view, theme, mandate, language style, characters and others. This study used a descriptive qualitative method that was normative. The population in this study were all Grade VII Students of the Even Semester Semester SMP Kartika II-Bandar Lampung in the 2019/2020 Academic Year totaling 184 students consisting of 5 (five) classes. The sampling technique was carried out using the Stritified Proportional Random Sampling technique. Samples were taken as many as 16% of 184 students, as many as 30 students. Analysis of the ability to determine the intrinsic element of the short story "merdeka" by Putu wijaya then the results obtained from the aspects of the theme get a rating of 67% with enough criteria, flow aspects get a rating of 61% with sufficient criteria, setting aspects get a rating of 55% with less criteria, aspects of characterizations get an assessment 77% with good criteria, aspects of the perspective get 70% assessment with sufficient criteria, aspects of language style get an assessment of 85% with criteria Very good, mandate aspects 83% get an assessment with criteria Very Good.
Doc2Vec based Question and Answer Search System

E-learning interaction acts as a positive factor, such as improving learning commitment and learning effect and reducing the dropout rate. As an important function of e-learning interaction, if a learner queries a content that is difficult to understand during learning, a question-and-answer bulletin board that responds to the question is provided by a professor. In the way that the instructor directly answers the learner's questions, real-time feedback is difficult, and the instructor's fatigue increases. The purpose of this study is to achieve the goal of reducing answering time and reducing answering costs by developing a question-and-answer search system that automatically searches for and provides answers to questions created by learners during learning. To this end, this study designed and implemented a question-and-answer search system that provides the most similar query answers to learners by analyzing questions and answers based on Doc2Vec, one of the word embedding technologies, which is a natural language processing technology. By applying the results of this study to the question-and-answer system, it is expected that the learning effect can be enhanced by providing an immediate answer to the learner's question. In addition, organizations that pay response fees through the national budget, such as the Korea Educational Broadcasting Corporation, will be able to focus more on investments such as improving content quality through budget reduction.
Power Attack and Protected Implementation on Block Cipher BIG

BIG is a new Feistel structured block cipher. Compared with other block ciphers, in terms of hardware or software implementation, it has a wider range of usage scenarios and is optimized in terms of encryption/decryption, throughput-to-area ratio (TP/A). Although extensive research has been conducted on its theoretical security, almost no effort has been made to analyze its implementation security, such as side-channel attack protection. In this article, we first present related power attacks and their experiments on BIG. Then, for side channel attacks, a mask protection scheme for software BIG is proposed. Its implementation shows that the protected BIG only costs 120.6%, 187.1% and 106.5% of the code, time and RAM.
New experimental methods with two modes squeezed light: from quantum reading to quantum conformance test

The protocol of quantum reading refers to the quantum enhanced retrieval of information from an optical memory, whose generic cell stores a bit of information in two possible lossy channels. In the following we analyze the case of a particular class of optical receiver, based on photon counting measurement, since they can be particularly simple in view of real applications. We show that a quantum advantage is achievable when a transmitter based on two-mode squeezed vacuum (TMSV) states is combined with a photon counting receiver, and we experimentally confirm it. In this paper, after introducing some theoretical background, we focus on the experimental realisation, describing the data collection and the data analysis in detail.
LibGuides: Remote Course Support from University Libraries: College of Education

A Guide for University faculty to the library resources from Texas State University Libraries to support remote teaching.
A conceptual IR chatbot framework with automated keywords-base

This paper proposes a conceptual remodel of Information Retrieval (IR) chatbot framework designed to eliminate the need for large Question-Answer (QA) pair dataset in chatbot's machine learning training and knowledge base development. Within ten proposed framework's components, we describe Ans2Q: a Neural Network model for question type approximation, and HR6: an IR score ranking calculation based on Ans2Q output. Fundamentally, these two components are the variance in which the proposed framework differs from others. Together with process flow explanation, we also provide several related formulas that hopefully can be used to implement this framework. Our general aim with this framework is to provide a tool that can be used to develop close domain chatbot with small knowledge and no readily available QA pair datasets.
DISCIPLINE "ECONOMIC POLITICAL SCIENCE" AS A COMPONENT OF THE BACHELOR TRAINING PROGRAM

The article discusses the features of teaching the academic discipline "Economic Political Science". Its place in the educational process, its relationship with other disciplines, main goals, objectives and learning outcomes are shown. The most important problems of the key topics of the discipline are revealed. Special attention is paid to such discipline categories as "power", "politics", "economics", "entrepreneurship" in the context of all the complexity and multidimensionality of their relationship. Methodological recommendations are given for their consideration in lectures and practical classes, the use of interactive teaching methods, in particular, discussions, brainstorming, etc.
Superconducting nanowires for single-photon detection and cryoelectronics

Superconducting nanowires and nanostrips have been used extensively in single-photon detection and have recently demonstrated the capability for photon-number resolution. These devices can also find use for microwave analog and digital superconducting electronics for purposes such as signal processing and multiplexing, and potentially for applications to readout of superconductive quantum computing. This talk will discuss novel electronics and photodetection devices based on superconducting nanowires.
Wavelet Scattering Transform and Ensemble Methods for Side-Channel Analysis.

Recent works in side-channel analysis have been fully relying on training classification models to recover sensitive information from traces. However, the knowledge of an attacker or an evaluator is not taken into account and poorly captured by solely training a classifier on signals. This paper proposes to inject prior information in preprocessing and classification in order to increase the performance of side-channel attacks (SCA). First we propose to use the Wavelet Scattering Transform, recently proposed by Mallat, for mapping traces into a time-frequency space which is stable under small translation and diffeomorphism. That way, we address the issues of desynchronization and deformation generally present in signals for SCA. The second part of our paper extends the canonical attacks over byte and Hamming weight by introducing a more general attack. Classifiers are trained on different labelings of the sensitive variable and combined by minimizing a cross-entropy criterion so as to find the best labeling strategy. With these two key ideas, we successfully increase the performance of Template Attacks on artificially desynchronized traces and signals from a jitter-protected implementation.
A survey on recommender system techniques and their applications

Recommender systems are web-based systems which help in the reduction or eradication of information overload in an information system. Recommender systems study the characteristics of a system user by identifying their ratings, purchases or other demographic attributes and then use the information gathered on the user to subsequently provide recommendation of items to the user. The design of the recommender system has to do with the use of various techniques such as the collaborative filtering technique, the content-based technique, and the hybrid technique. The collaborative filtering technique involves knowing the similarity between users and how they correlate with each other as a result of their activities on the platform. The content based filtering involves the identification of the contents and attributes of various items provided to the users while the hybrid technique involves the combination of both the collaborative and content based filtering techniques. The application of any of these techniques depends on the dataset available, area of application and also the performance expected of the design. This paper provides an extensive study on these techniques, stating their applications, their advantages and disadvantages. The outcome presented researchers with choices while implementing recommender systems.
Global social transformations and Modern World

Researched is the process of global social changes in the process of transformation of the content of education in the modern world. Presented are principal vectors of development of that process. Also elaborated are various possible directions in development of that process as to the nearest and the more further perspective of development.
Design Method of Intelligent Questionnaire for the Automatic Assessment of Educational Informatization Level

Educational informatization is the process of effectively applying information technology to teaching management and teaching research. Quantitative assessment of educational informatization level is an important means to promote education reform and development. With the comprehensive advancement of education modernization, traditional static and discrete assessment methods of educational informatization level have been difficult to meet the needs of dynamic update and process processing of assessment applications. The seamless integration of assessment questionnaire design, survey data collection and automatic assessment data calculation has become a basic requirement for educational informatization assessment system. This paper proposes a design method of intelligent questionnaire for automatic educational informatization assessment. It supports the parametric design of the assessment questionnaire by enriching the semantic expression of the data model of assessment questionnaire, supports the automatic collection as well as automatic analysis of the questionnaire data by enhancing the information interaction ability between each node of the assessment process, and eventually realizes the automatic processing of educational informatization assessment.
Field Service Case Study: WPI Experiences Seven-Figure Claim Recovery Savings with MSI’s Service Pro

Customer satisfaction and technician efficiency improves with switch to all-in-one field service management software With nearly 100 years of ...
Study on Challenges and Suggestions of College English Teachers’ Professional Development

English teachers’ professional development; Challenges; Causes; Suggestions
ROLE PEFORMANCE LIBRARIAN IN THE ERA OF INDUSTRIAL REVOLUTION 4.0 : OPTIMIZING PUBLIC LIBRARY SERVICE QUALITY IMPROVEMENT IN ORDER TO FULFILL INFORMATION NEEDS IN A SOCIOLOGICAL PERSPECTIVE

The research intends to describe the role of librarians in meeting the information needs of society. The object of research is focused on analyzing studies based on a comprehensive, detailed discussion of content is very urgent, is a fundamental investigation of the role of librarians in improving the quality of public library services to fulfill user satisfaction, given that information needs are increasingly developing with very rapidly.The research has the scope of in-depth analysis, based on the focus of the study of optimizing the improvement of the quality of public library services in order to fulfill user satisfaction with information, which is felt to have increased rapidly and information search has turned digital. Research analysis requires realistic but critical thinking, applying a concept in the historical period in the past or is happening, then it is appropriate to apply the historical approach, characterized by the dominance of critical investigation of the development of a thought or term. Primary information sources are empowered as primary data. Collecting data utilizes a research library, through reading various literatures on the subject of the role of public libraries, service quality, and community information needs. Qualitative descriptive analysis is based on the analysis of various theoretical reading materials, research and non-research. Research dominates very evaluative descriptions of factual facts, for solutions to problematic solutions to social phenomena, the role of public libraries in meeting community needs. Research validity is realized, bypassing content analysis, analyzing the meaning of important concepts. Observations of librarian performance activities in public libraries are used to support theory construction. The results showed that librarians have a strategic position and play an active role in improving the quality of information services to meet community needs. Automatically, librarian's role performance is highly expected by the library users, able to be realized by librarians so that they can take an active role in carrying out excellent public library services.
LibGuides: Evaluating and Selecting Resources: Citation Tools

Use this guide to learn how to evaluate different types of resources and determine their value.
Tempramen Analysis In The novel Catatan Juang by Fiersa Besari (Ludwig Klages Personality)

This study aims to describe the temperament of characters in the Fighting Notes novel by using Ludwig Klages's personality theory. The focus of this research is on the temperament of the characters contained in the Note Juang by Fiersa Besari. Tempramen is a trait that a person has in him when he will do something, Klages divides the temprament into two parts, namely sangraminis tempraments and pleghmatic tempraments. This study uses descriptive qualitative research methods which means a research method that does not use numbers or calculations, this qualitative approach is used with the aim of producing word form descriptions from research that has been observed, in addition this study uses library techniques to get data on research observed. Data analysis in this study used hermeutic analysis with several stages, namely reading objects, marking data found on objects, coding data and analyzing all data with Ludwig Klages's personality theory. The results of this research in the Notes Fighting can be concluded that there are sangunis and pleghmatis tempraments but are inclined to sangunis tempraments that are experienced by many Suar figures.
An Optimized Deep Vision Framework

DEEP VISION (DETECTRON) is a project that is intended to be useful for many other computer vision research institutions. It takes desired neural schema and training data as input and creates high quality deep learning models for computer vision requirements. User doesn’t necessarily need a lot of knowledge of machine learning, rather he can just annotate his input images for training and give his desired neural schema and DETECTRON takes care of rest. Apart from creating desired Deep Learning models, it can provide shorter and faster neural networks using our reliable optimization algorithm. Mainly the whole project/system is divided into 5 major modules:
Comparison of deep reinforcement learning algorithms: Path Search in Grid World

Deep reinforcement learning is being used to teach robots elaborate and complex tasks, and recently, it has gained successful results in various fields of robotics. However, there is still a limit to directly applying the existing deep reinforcement learning algorithms due to the continuous and high-dimensional states and actions inherent in the robot, and a method of inducing correct learning through proper expression of the environment in which the robot will work is required. As a way to enable the robot to recognize the work environment, there is observation through a camera, and a mapping from this to the grid world is a way to express the work environment. This allows us to considerably reduce the dimensions of state and action and find the optimal policy for the path search problem using deep reinforcement learning algorithms. In this paper, we compare the simulation results of various deep reinforcement learning algorithms for path search, which is a representative problem depicted as a grid world, and present the environment, model architecture and parameters used in the simulation.
Pengaruh tingkat literasi media terhadap tingkat self-esteem pada peserta didik di SMP Negeri 214 Jakarta

The media has a very important function in providing information needs for each individual. Media that contains content that is negative to the community can have an adverse effect on the formation of people's perceptions in decision making. Regarding this, mass media users need other options in order to be protected from the various influences of mass media and require individuals to be smarter using media. This study aims to determine the level of media literacy on the self-esteem of students at 214 Public Middle Schools Jakarta. The method used in this study is a quantitative method with a clause associative approach. Data analysis technique is done by tabulating data according to students' answers to the questionnaire, then calculated using the Simple Linear Regression formula. The results of the study concluded that Media Literacy influences students' self-esteem, this is evidenced through hypothesis testing which is known to have a significance value of less than <0.05 with a value of 0.009, in addition it is known that the R Square value of 0.091. This value means that the influence of Media Literacy (X) on Self-Esteem (Y) is 9.1%. From the results of the hypothesis test, it can be concluded that media literacy has a positive effect of 9.1%, which means increasing student media literacy will affect the increase in self-esteem
응급구조학과 비대면 실습 강의에서 360° 가상현실 영상과 1인칭 시점 영상의 만족도, 흥미도, 경험인식 비교

Purpose: This study aimed to establish effective training strategies and methods by comparing the effects of 360° virtual reality video and first-person video in non-face-to-face practical lectures. Methods: This crossover study, implemented May 18–31, 2020, included 27 participants. We compared 360° virtual reality video and first-person video. SPSS version 25.0 was used for statistical analysis. Results: The 360° virtual reality video had a higher score of experience recognition (p=.039), vividness (p=.045), presence (p=.000), fantasy factor (p=.000) than the first-person video, but no significant difference was indicated for satisfaction (p=.348) or interest (p=.441). Conclusion: 360° virtual reality video and first-person video can be used as training alternatives to achieve the standard educational objectives in non-face-to-face practical lectures.
From Black-box to White-box: Examining Confidence Calibration under different Conditions.

Confidence calibration is a major concern when applying artificial neural networks in safety-critical applications. Since most research in this area has focused on classification in the past, confidence calibration in the scope of object detection has gained more attention only recently. Based on previous work, we study the miscalibration of object detection models with respect to image location and box scale. Our main contribution is to additionally consider the impact of box selection methods like non-maximum suppression to calibration. We investigate the default intrinsic calibration of object detection models and how it is affected by these post-processing techniques. For this purpose, we distinguish between black-box calibration with non-maximum suppression and white-box calibration with raw network outputs. Our experiments reveal that post-processing highly affects confidence calibration. We show that non-maximum suppression has the potential to degrade initially well-calibrated predictions, leading to overconfident and thus miscalibrated models.
Fuzzy C-Means (Fcm) Clustering And Adaptive Network-Based Fuzzy Inference System (Anfis) For Dynamic Background Subtraction

Background subtraction is a procedure for isolating out frontal area components from the background and is finished by creating a closer view veil. This strategy is a typical technique for extricating closer foreground focuses in video groupings. It has been generally utilized in the discovery of an item which is moved from a constant scene. The author proposed a new fuzzy methodology for Background subtraction utilizing fuzzy histograms based on Fuzzy C-Means (FCM) clustering as well as Adaptive Network-based Fuzzy Inference System (ANFIS) classifier, because of the vulnerability in the arrangement of the pixels in the closer foreground with background. The worldly pixels qualities were portrayed by a fuzzy histogram utilizing the FCM algorithm. This histogram is embraced to build the replica for Background, as well as the ANFIS classifier of a pixel is determined to recognize whether the pixel of video has a place with the frontal area or background. The threshold of segmentation is determined adaptively by the appropriation of the classifier of the respective pixel. Fuzzy versatile Background support is embraced out of the framework background update. At last, make use of the historical information patterns to change the threshold. The judgment thresholds of each channel are refreshed powerfully as indicated by the circulation of the historical information. To check the exhibition of the proposed technique, seek the help from the dynamic background videos from changedetection.net (CDnet2014) and Stuttgart Artificial Background Subtraction (SABS) helps to test the strategy. The exploratory outcomes exhibit that the proposed strategy and other existing strategies are estimated with respect to the precision, recall, F-measure, False Positive Ratio (FPR) and False Negative Ratio (FNR).