Reviewerly/exHarmony huggingface dataset:
Customer Data Electronic Archives Management in Data Management Division at Pt Telkom Indonesia Bekasi City Branch

1st WoW-SAIPIS 2021 is an article writing workshop centered on social sciences and education, open and welcoming contributions from various disciplines and approaches that meet at intersections. We are interested in scholarship that crosses disciplinary lines and speaks to readers from a variety of theoretical and methodological perspectives. In other words, 1st WoW-SAIPIS 2021 will be a forum for scholars as they speak to a wider audience of our many sub-fields and specialties, rather than a location for narrower conversations that are more appropriate in more specialized conferences. We suggest the following broad areas of research: Social Sciences and Laws History and Cultural Studies Interdisciplinary Studies Moral and Humanities Policy, Politics, and Communication Education The proceedings represent the latest in research, development, deployment and projects on a range of topics presented at the International Conference of Social Science and Education. The papers published under each conference are sorted according to the themes and topics defined under each event. Papers are published according to the events at which they were presented by the authors. They can be searched by theme,
Analysis of Comparative Opinions

Apart from directly expressing positive or negative opinions about an entity and/or its aspects, one can also express opinions by comparing similar entities. Such opinions are called comparative opinions (Jindal and Liu, 2006a, 2006b). Comparative opinions have different semantic meanings from regular opinions as well as different syntactic forms. For example, a typical regular opinion sentence is “The voice quality of this phone is amazing,” and a typical comparative opinion sentence is “The voice quality of Moto X is better than that of iPhone 5.” This comparative sentence does not say that any phone’s voice quality is good or bad, but simply states a relative ordering in terms of voice quality of the two smartphones. Like regular sentences, comparative sentences can be opinionated or not-opinionated. The preceding comparative sentence is clearly opinionated because it explicitly expresses a comparative sentiment, while the sentence “Samsung Galaxy 4 is larger than iPhone 5” expresses no sentiment, at least not explicitly.
First Impressions: A Visual Catalogue for Understanding Interactions with Novel Interfaces in Augmented Reality

Although Augmented Reality (AR) has become increasingly common, the design of AR interfaces has predominantly relied on importing traditional 2D digital GUI interface elements. These do not always translate successfully to novel, three-dimensional, AR interfaces. To understand how users develop a folk understanding of AR interfaces, we conducted six workshops with participants to investigate their initial interactions with off-the-shelf puzzle interfaces, across three modes: tangible, handheld tablet, and head-mounted display (HMD) AR systems. We captured multiple points-of-view video data and co-analyzed it with participants. Our study (1) presents a catalogue of interactional gestures across the three modes; (2) highlights how errors are perceived as features in AR systems; (3) analyzes the evolution of gestures; and (4) identifies implications of occlusion and spatial judgement errors.
Fostering and nurturing a diverse community of CI Professionals (NSF)

Federal Grants & ContractsVolume 46, Issue 6 p. 3-3 Grants alerts Fostering and nurturing a diverse community of CI Professionals (NSF) First published: 12 February 2022 https://doi.org/10.1002/fgc.32215Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume46, Issue617 February 2022Pages 3-3 RelatedInformation
Philological Approaches

Three students of the classicist Piero Vettori turned to the study of vernacular language at midcentury and therafter: Benedetto Varchi, Girolamo Mei, and Vincenzio Borghini. Mei circulated his writings only in manuscript; he wrote especially on metrics and rhyme, and referred to the recently available writings of Aristoxenus of Taranto as well as Aristotle’s Poetics to discuss perception and judgment. Varchi acknowledged Bembo’s immense contributions but like Borghini, felt he had conflated the study of language with literature. Varchi used Aristotelian tools to analyze languages. They distinguished between literature as art and language as natural to humans; hence, its variation follows rules that are subject to rational analysis. Borghini devoted attention to the fourteenth-century vernacular, including an edition of Boccaccio’s Decameron that could withstand the Index of Forbidden Books. He also proposed a plan for teaching vernacular language in Florence’s schools.
Negotiating to Buy an Economy Car, KIA: A Mind Genomics Cartography of Sales Messages and Dealer Concessions

qualifying question), the study worked with a cross-sectional group of respondents, selecting in the end one or approximately four respondents would, when shown vignettes about KIA, rated at least one vignette '9' (definitely buy), and one vignette '1' (definitely not buy). How Mind Genomics Works, and Differs from Conventional Attitude ResearchMind Genomics studies present respondents with combinations of messages, so-called vignettes, acquire the respondent's reactions to these vignettes, and show the link between each element in the study, and the response which is engenders.Side analyses are also feasible and often illuminating, especially when the respondent assigns two types of ratings to the same vignette.In this study the respondent rated both purchase intent and amount of monetary concession from the dealer required to drive a rating of the vignette to 'definitely buy.' The Mind Genomics study is really an 'experiment' , although couched in the form of an online research study, almost a survey although quite different from the classical surveys.The approach has been successfully implemented to create landing pages, and marketing messages for museums [6,7].The approach provides a general way to understand the different points of view in the negotiation [8].The overarching world-view of Mind Genomics is to create a usable, searchable, and
DESIGNING READING MATERIAL BASED ON BATAKNESE FOLKLORE

Abstract&#x0D; &#x0D; &#x0D; The low level of reading comprehension and interest affects their learning motivation at school. Many students are not interested in reading, because they think it is boring. To overcome these problems, this research aims: first, to develop Batak folklore. Second, to determine the effect of Batak folklore on reading comprehension and student motivation. This study takes 3 Batak folklore including 1) The Legend of Pohon Aren, 2) The Legend of Aek Situmandi, 4) The Legend of Air Soda.&#x0D; This type of research is a qualitative descriptive obtained in writing to describe the moral values and character formation contained in the 3 Batak folk tales. The data of this research were taken from students of SMK Telkom Medan. Data collection is done by reading the story text over and over again. From the research, it can be concluded that Batak folklore can increase students' interest in reading and can be a motivation for every student.&#x0D; &#x0D; &#x0D; Keywords: Batak folklore, motivation, reading interesting&#x0D; &#x0D;
Reflections and Elaborations

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Realization – Generalized

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A Novel Heuristic Method for Linear Nearest Neighbour Realization of Reversible Circuits

With the advancement of technological footprints, high-end computation techniques, like quantum computation, have made significant progress in the design industry. Although quantum computation has proved itself as the next-generation computing paradigm, it is facing several design challenges, and one such design issue is in the form of the Nearest Neighbour (NN)t. This much-talked NN property demands the qubits in operating quantum gates to be adjacent, and a circuit should satisfy this NN property to be eligible for implementation. Considering the importance of NN enforcement in implementing circuits, we introduce a synthesis approach for the efficient transformation of reversible circuits to equivalent LNN representations. Our main focus in this work is to minimize the use of SWAP gates in designing NN-satisfied MCT-based reversible circuits. Towards transforming input circuits to LNN architecture, we have exploited a template matching scheme followed by two-qubit reordering policies, global and local, to improve the NN designs and reduce SWAP utilization. In finding the global solution, here we have used a dynamic programming algorithm where the initial order of qubit lines gets changed, while a heuristic-based SWAP placement function is used for finding a local qubit order sequence. The proposed synthesis workflow has been tested over an extensive set of benchmark functions, and comparison with the reported design approaches showed a substantial reduction in cost parameters.
CPS Modeling and Analysis Method of Power Grid Based on Graph Computing

With the development of the energy Internet, the increasing coupling degree and huge data complexity of the cyber-physical system (CPS) of the power grid have put forward higher requirements for the efficiency of analysis and calculation. Graph database and graph computing technologies are new databases and computing technologies that have emerged in recent years that can be based on massive data-parallel processing, which can intuitively express the power grid topology and perform efficient processing and calculations. This paper proposes a CPS dynamic analysis tool based on graph database and graph calculation. Firstly, based on the graph database, the data is combed and modeled from the component level to the topology network level on the physical side of the power grid and the associated features are extracted, described and stored. Secondly, a fusion graph model that can be used for dynamic analysis is built for the power grid CPS system, and a visual display platform that can nest business scenario analysis and calculation functions is developed. Based on the graph database model and the graph computing technology, the component attribute status query is realized. The network topology area identification, dynamic feature analysis, hybrid calculation and other visualization functions are also realized. Through the test in the 62-node CPS network, the results show that this analysis tool can significantly improve the equipment operation monitoring and network optimization control efficiency of the CPS system.
Introduction

Review of International EconomicsVolume 29, Issue 3 p. 485-486 INTRODUCTION Introduction Makram El-Shagi, Makram El-Shagi makram.elshagi@gmail.com Search for more papers by this author Makram El-Shagi, Makram El-Shagi makram.elshagi@gmail.com Search for more papers by this author First published: 25 January 2021 https://doi.org/10.1111/roie.12516Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume29, Issue3August 2021Pages 485-486 RelatedInformation
Linear Algebra

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
History

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A Study of Illumination Filtering and Movement Detection in Video Streaming Processing

We study a movement detection scheme for video streaming data using time series analysis. We employ simple scalar quantities such as (i) the Frobenius norm trajectory of a forward difference matrix and (ii) the Auto-correlation function to analyze the time series and detect movements in the video sequences. To remove the background interruptions, such as the change of lights, we study the performance of two filters, (1) SVD filter and (2) SVD combined with the Butterworth filter, to repress data disruptions. From the example, we identify the best filter and the best statistical quantity to detect movement in the disrupted data. By using the background subtraction filters as well as the Frobenius norm trajectory of data, we can distinguish the movements and light disruptions at various time points in the video sequences. The combo filter is found to be the best as it completely removes the light interruption while maintaining the movements data unaffected and smooths other static artifacts.
Existing AAL Products

In this chapter, several technological, or to be more detailed, robotic solutions from different companies and developers will be presented. This allows an overview of the state of Ambient/Active Assisted Living (AAL), which can be categorized into home care (for independent living in old age), social interaction, health and wellness, interaction and learning, working, and mobility.
An Efficient HEVC Intra Frame Coding Based on Deep Convolutional Neural Network

High efficiency video coding (HEVC) is a very popular video coding standard. The HEVC can achieve high coding efficiency with a lower bitrate for intra frame coding. However, it still needs many bits to finish best rate-distortion (R-D) curve. Since there are only 35 directions prediction modes provided in intra prediction module (IPM), HEVC occurs a large distortion when the image contents are out of these prediction directions. In order to obtain a better R-D curve, Zhang et al. [3] recently proposed a simple convolutional neural network (S-CNN) to improve the encoding performance of HEVC. However, S-CNN has to consume more time to encode intra frame coding since it needs to perform more CNN enhancement mode. In order to further speed up S-CNN based intra frame coding, we propose an early termination algorithm to skip CNN. Because the natural images are generally homogenous, we find the mean square errors (MSE) of reconstructed CTU exist high spatial correlation at HEVC encoder. Therefore, a dynamic threshold of MSE is set according to three neighboring encoded CTU blocks to evaluate whether the current reconstructed CTU is useful for the CNN enhancement mode. Simulation results show that the proposed method can achieve faster HEVC encoding process than S-CNN by reducing time increase ratio (TIR) about 12% on an average.
North Korea s Cyber Terrorism and Countermeasures

The threat of state-sponsored terrorism by North Korea has a long history, dating back to the time when South Korea gained independence from Imperial Japan on August 15, 1945. North Korea s cyber-terrorism started at its Mirim University, established in 1981 under the direction of the deceased Kim Il-sung, and currently, the five-year based university, renamed Kim Il Military University, has produced about 100 cyber-terrorists every year, who have been appointed as a military officer in places such as automated staff of each military unit, cyber warfare command system establishment department, Labor Party Secretariat Investigation Department Room 35 and Liaison Department, People’s Armed Forces Reconnaissance Bureau Unit 121, and the psychological warfare unit of the Maneuvering Unit of Enemy Disintegration and are working as a cyber warfare or cyber terror agent. In addition, the threat is even greater because they have or are likely to commit cyber terrorism toward South Korea using China s three northeast provinces as a base. And the technology in the software field is evaluated at a world-class level. And since such cyber terrorism in North Korea cannot be expected to have the effect of ex post prevention, this study focused on countermeasures in legal, institutional, and technical perspectives for prevention.
Visual Analysis of Multilayer Networks

The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting c
Enhancing Recruitment Process Using Semantic Matching

This article presents a recommender system that enhances e-recruitment. The main capability of this system consist on recommending pertinent job offers posted by recruiters to job seekers. First, the data is collected from job websites using web-scraping techniques. The result of the data extraction is made up of noisy and unstructured text. Therefore, it is cleaned and prepared using preprocessing techniques to get it in a structured format. The selected attributes such as job titles and job skills are meaningful features that will be transformed into vectors of real numbers using vectorization algorithms in order to save the semantic of the words and to facilitate similarity calculation. Deep learning techniques such as Recurrent Neural Network (RNN) are used for classification of job profiles. The degree title, the owned skills and previously held job could reveal meaningful information to be used for matching with job posting similar attributes. To get better result scores are given to the selected features before providing an ordered list of job recommendations.
Control and Maintenance System with Augmented Reality for a Stone Counter

In recent years technology has increased rapidly, and virtual environments and their applications in daily and industrial life are among the most developed fields. Augmented Reality (AR) is a technology that connects the real and digital worlds and adds information generated digitally on elements of a real environment, maximizing and enriching real-time information. This paper presents the development of a control and monitoring system using databases and maintenance using AR for a stone counter. The hardware used is low cost and free software is also used for easy access, in this way the system can be replicated by small companies. It is used the Unity software for creating the application, a microprocessor for the control, and a Bluetooth module for wireless communication with the application in the Android device. The control from the application provides additional and friendly information to the user; in addition, it enables higher control of the machine, and the status of the raw material is known through the database for better planning and optimization, achieving a reduction of costs.
Goal-conditioned Behavioral Cloning with Prioritized Sampling

Imitation learning is a promising approach to extract knowledge from human’s demonstrations. In traditional imitation learning methods like behavioral cloning, human demonstration transitions were uniformly sampled from replay buffer regardless of their different values. In addition, agent trained by this method is limited to solve a specific task. In this paper, we extend traditional behavioral cloning method with a prioritized sampling technique. To make our method more general, we introduce an additional element goal which is the difference between last state of demonstration trajectory and current state to original framework. Our method is simple to implement with one assumption that small amount of expert demonstration is available. We show that our method outperforms common reinforcement learning algorithms on some image-based and hierarchical tasks in Minecraft environment. Further, we illustrate that it has potential to perform better than human level policy when combining our method with reinforcement learning algorithms.
Decomposing neural networks as mappings of correlation functions

Understanding the functional principles of information processing in deep neural networks continues to be a challenge, in particular for networks with trained and thus non-random weights. To address this issue, we study the mapping between probability distributions implemented by a deep feed-forward network. We characterize this mapping as an iterated transformation of distributions, where the non-linearity in each layer transfers information between different orders of correlation functions. This allows us to identify essential statistics in the data, as well as different information representations that can be used by neural networks. Applied to an XOR task and to MNIST, we show that correlations up to second order predominantly capture the information processing in the internal layers, while the input layer also extracts higher-order correlations from the data. This analysis provides a quantitative and explainable perspective on classification.
Virtual Surgical Training

Any media innovation brings fundamental questions like: What essentially is learning? How do we monitor learning? What is the proper criterion for mastery? etc. The 3D spatial environments for practicing surgical skills triggered considerations like: At what stage in skill progress should students resume the interaction with the full human body?
A Comparison of One-Way Passenger Flow in Subway Channels Based on DaSiam-RPN and Deep-Sort Algorithm

The subway has become the main commuting tool in most cities, and its large passenger flow has become the norm in urban rail transit. Accurate and real-time statistics of passenger flow in stations can provide scientific basis for subway management and control. Currently, it is difficult to count the one-way passenger flow in the two-way passenger flow video in the current statistical methods commonly used in the field. In this paper, two algorithms, DaSiam-RPN and Deep-Sort, which are effective in target tracking, are selected for subway passenger transportation. Real-time one-way passenger flow statistics are carried out on the two-way passenger flow in the channel scene in the station, and the accuracy, real-time and performance of the two algorithms are compared.
Touchless Computing for Everyone

Abstract Touchless technologies are going through a revival. Sheena Visram tells Johanna Hamilton AMBCS about this new era in inclusive and intuitive touchless computing.