Reviewerly/exHarmony huggingface dataset:
Nonlinear Dissipative Particle Swarm Algorithm and Its Applications

A nonlinear dissipative particle swarm algorithm is proposed for the problem of poor search accuracy by the particle swarm algorithm, especially for the optimization of high-dimensional functions. The algorithm dissipates the particles in a nonlinear increasing way: avoiding a large amount of unnecessary dissipation at the beginning of the iteration and putting more effort into dissipation at the end of the iteration, which improves the operation efficiency and global search ability of the algorithm. On this basis, the inertia weights are adjusted with a nonlinear decreasing strategy, which improves the search ability of the algorithm when there is no dissipation. The experimental results show that the nonlinear dissipative particle swarm algorithm has superior performance when dealing with high-dimensional function optimization problems and mobile robot path planning problems.
Webservice Learning Preparation Report Polytechnic Indonusa Surakarta

Polytechnic Indonusa Surakarta is a private university that has various study programs available. Some of the study programs must report learning preparation reports every semester which must be submitted and validated directly by Deputy Director I as an academic field. At first these activities were carried out manually and not yet computerized so as to facilitate program studies in conducting consultations and Deputy Director I who had a busy schedule but had to validate manually. This system was created with the aim of making it easier for Polytechnic Indonusa Surakarta side in collecting file, conducting consultation, signing signatures, and making learning preparation reports. Data collection methods used include the method of literature study, observation, interviews and documentation. This system will use a MySQL database with the PHP programming language with the Laravel framework. The method used in making this web service is the waterfall method. The result of the webservice learning preparation report is that the webservice system can facilitate both study programs in submitting and conducting consultations and Deputy Director I in conducting validation, consulting, and preparing learning preparation reports. This system will store data from reports that are entered into the webservice database
Ground plane detection for wearable assistive devices for the visually impaired

Assistive devices developed for visually impaired users help them understand the environment so they can navigate with minimum additional help. Such devices greatly rely on image processing techniques to distinguish essential features from the input images. The ground surface represents one key element that needs to be detected. The user can move freely on the ground surface but also obstacles are usually located on this surface. As assistive devices need to provide information in real time, any designed algorithm must achieve real time results. In this paper, we present a novel algorithm to detect the ground plane in video sequences. The sequences are acquired by a stereo camera worn by a visually impaired user. Our algorithm uses a V-disparity map approach and it is tailored for the challenges that arise from the fact that the stereo camera has six degrees-of-freedom. We evaluate the accuracy of our algorithm using multiple real life scenarios. An evaluation of the performances of the algorithm was also performed to prove its accuracy and speed. We also discuss a possible speed up of the proposed algorithm but at a minor cost of accuracy.
Artistas en el aula, una experiencia de enseñanza artística mediada por tecnologías digitales

This article presents the Artists in the Classroom program of Plan Ceibal and describes some categories of analysis in relation to art, school education and digital media. The article seeks to recover the experience where artists, teachers and students find themselves in a particular device in which a creative process mediated by various languages and technologies is carried out. The program is part of a training strategy developed in Plan Ceibal (Uruguay) that explores new ways of linking with art and artists.
Implementación de un repositorio para profesores de la academia de ecología de una escuela preparatoria de Pachuca

El articulo tiene como finalidad la creacion de un repositorio que permita a los docentes de la asignatura de Ecologia de la Escuela Preparatoria Numero Uno, incorporar las herramientas necesarias para el uso de las Tecnologias de la Informacion y Comunicacion (TIC), en sus estrategias de ensenanza-aprendizaje. Se retomaron aportaciones de diversos autores en relacion al uso y aplicacion de las TIC y se definio la estructura de dicho repositorio. Como una forma de poder conocer algunos resultados del proyecto se procedio a realizar una prueba piloto en los docentes de la academia de Ecologia, los cuales aplicaron las herramientas sugeridas en la plataforma, y en un tiempo aproximado de cuatro semanas, los docentes, compartieron en la plataforma, evidencias del uso de dichas herramientas, llegando a resultados positivos como la apropiacion y aplicacion de las TIC en las estrategias pedagogicas de los docentes, lo que permitira considerar la viabilidad del proyecto una vez que lo autoricen las autoridades de la institucion. Palabras clave: Tecnologia, educacion, repositorio, TIC. ABSTRACTThe purpose of the article is to create a repository that allows teachers of the Ecology subject of the Preparatory School Number One, to incorporate the necessary tools for the use of Information and Communication Technologies (ICT), in their strategies of teaching-learning. Contributions from various authors were taken up in relation to the use and application of ICT and the structure of said repository was defined. As a way of being able to know some results of the project, a pilot test was carried out in the teachers of the Ecology academy, who applied the tools suggested in the platform, and in an approximate time of four weeks, the teachers shared in the platform, evidence of the use of these tools, reaching positive results such as the appropriation and application of ICT in the pedagogical strategies of teachers, which will allow considering the viability of the project once authorized by the institution's authorities.Keywords: Technology, education, repository, TIC.
WaDGAN-AD를 이용한 전력 소비 패턴의 비지도 학습 기반 이상 탐지

Anomaly detection in time series is essential because it can detect outlying patterns such as a breakdown in machines and fraudulent customers. Among many anomaly detection domains, detecting abnormal patterns in energy consumption is used to detect technical breakdown in factories, general buildings, or energy theft in households. To overcome the limitations of previous studies, this paper suggests WaDGAN-AD, which combines generative adversarial network (GAN) and Long Short-Term Memory (LSTM) and applies two structural improvements. WaDGAN-AD has stacked discriminator LSTM layers to more precisely learn feature representations of time series data. Also, it has different numbers of hidden units in each hidden layer of LSTM to consider multiple cycles appearing in a single time-series data. Experimental results based on synthetic datasets and real datasets show that WaDGAN-AD can better detect abnormal energy consumption than benchmark methods.
Internet of Things (IoT) Based Smart Health Monitoring System – A Case Study

A new corona virus has heightened awareness of the need of health care in every country. IoT-based health monitoring systems are the greatest option in this regard. In particular, health care researchers are increasingly interested in the Internet of Things (IoT). Remote health care monitoring has grown at such a rapid pace due to the increasing usage of wearable sensors and smart phones. Even if a doctor is far away, IoT health monitoring can assist prevent the spread of disease and provide an accurate diagnostic of the status of health. Authorized individuals can access this data saved on any IoT platform and diagnose illnesses based on these values obtained from a distance using the suggested remote health monitoring system
The Analysis and Review of the Study Trends of Empathy Using Arts Media in Youth Counseling

The purpose of this study is to analyze and consider research trends on empathy theory based on studies using various arts media in the field of youth counseling.First, the research trend of empathy theory using art media in youth counseling is the subject word of 'Adolescent Empathy' and 'Adolescent Empathy Arts among academic journal papers registered in KCI on RISS (Academic Research Information Service) from 2010 to April 2021 a total of 78 articles were retrieved.Among them, 'Adolescent Empathy' and 'Adolescent Empathy Arts were searched for in 9 academic journal areas, and 32 papers containing 'Empathy' in the thesis title were finally selected and analyzed.As a result of the study, the status of adolescent empathy papers by year was 3 in 2010, 3 in 2012, 3 in 2013, 1 in 2014, 6 in 2015, 3 in 2017, 7 in 2018, 4 in 2019, and 2020 was reported as one in a year and one in 2021, The age division of the group was confirmed as early adolescents, middle school students, high school students, middle and high school students, late adolescents, and adolescent-related adults.Also, as for group design, single-experimental group studies were the most common, and there were many studies using quantitative analysis.Among them, research related to arts therapy using arts media was found to be very incomplete with a total of 4 out of 32 papers.Therefore, based on the research result that the number of empathy studies using art media in youth counseling is very limited and insufficient, future research is expected to be utilized as basic data to verify the effectiveness of arts as a therapeutic tool.
LibGuides: Brown University Library Alma Implementation: Training Team Guide for All Staff: Brown Library Libguide for Scholarly Resources / Technical Services

This guide has been created by the Training Team of the Brown University Library Alma Implementation in order to assist all library staff members in learning how to use the new Alma and Primo systems.
Semantic-Based Self-Critical Training for Question Generation

Question generation is a conditioned language generation task that consists in generating a context-aware question given a context and the targeted answer.Train language modelling with a mere likelihood maximization has been widely used while suffering from exposure bias and the discordance between the training and the test metrics.In the way of addressing this issue, The presented work portrays a fully Transformer-based reinforcement learning generator-evaluation architecture for neural question generation.To edge the flexibility of the generation, a semantic-based reward score was externally infused during the training to drive the training of the language model.The global architecture is laid out in a generator-evaluator fashion optimized directly to n-gram and semantic-based metrics.Evaluation metrics for language modelling only based on ngram overlapping do not consider semantic relations between reference and candidate sequences.To improve the evaluation step, a two-fold evaluation was carried out.On the one side, an n-gram overlapping evaluation using the BLEU score.On the other side, a semantic-based assessment using BERTScore and NUBIA.The results were corroborated by a binary human evaluation of the semantic relatedness of the generated question and the ground truth.The results obtained showed that use a semantic-based REINFORCE algorithm for the question generation syntactically reshapes the generated questions while preserving their underlying semantic meaning.Many downstream applications can be drawn from a successful question generation including the enlargement of question answering datasets, the improvement of conversational systems, the enhancement of autonomous educational assessment systems, and so forth.
Robot Path Planning System in Populated Dynamic Environment using Dynamic Wave Expansion Neural Network Techniques

In heavily crowded dynamic situations robot navigation faces numerous problems. The path planning approaches for navigation robots in dense situations are presented in this work. In terms of planning and temperament, the route planning of independent mobile robots in the navigation architecture is separated into local path planning and global path planning. About the scope, preparation, and capacity for the implementation, we have presented in this article a neural network model that implements a dynamic version of the route length transformation process (used a stationary domain for path planning). With this new version of path generation extremely dynamic environment is possible. The neural network operates in discrete time, is locally linked, and hence is extremely fast. The planning procedure does not need any early findings of the state of the world. The neural-activity landscape, which creates a dynamically updated topographic map across a distribution representing the robot's arrangement space, is used to generate paths. The network dynamics ensure local adaptations and give stringent criteria for selecting a robot's future route step. With a standards, planned pathways are likely to be optimum, because of these principles. The efficiency of the suggested model is demonstrated by simulating the results inside a set of tests for diverse dynamical conditions.
가짜뉴스 탐지를 위한 엔터티가 추가된 어텐션 네트워크 개발

With the rapid development of social networks, fake news, ich is generated maliciously is spreading rapidly online. As it easily distorts public opinion and promotes biased thinking, it has emerged as an important social issue. In this context, it is necessary to detect fake news automatically. Most of the existing methods propose fake news detection models using only news contents. However, since news contents only represent the distributional patterns, not general knowledge, there is still a limitation of reliability by bias of the dataset. To overcome the limitation, we propose a self-attention network model using the original news contents with the entities, which are derived by a knowledge graph. As a result, we can expect to detect fake news more reliably. To prove the superiority of our method, we perform the experiments.
RANCANG BANGUN SISTEM PENGAMANAN GEDUNG YANG DIKONTROL MELALUI APLIKASI ANDROID BERBASIS IoT

Building or home security systems at this time are needed because there are still many security systems that can trigger crime, one of which is the use of padlock or conventional door locks and security that has not worked automatically. A security system is needed which has a high level of security and is automatic so that it does not bother users.&#x0D; Security systems are often a problem, namely the low level of security, how to use is not easy, and not automatic. The way to overcome this problem is to create a security system that has tight security, easy to use, works continuously automatically and can be connected to the user's mobile phone.&#x0D; Based on research that has been made this security system shows one of the security systems that have a high level of security because it is equipped with an infrared sensor that serves to detect the presence of humans, the camera takes pictures if the infrared sensor detects humans, a fingerprint sensor that functions as access to open the door and all The sensor works automatically and continuously and can be connected to mobile phones through the internet, this security system works well and can be relied upon.
Beyond Scattered Applications

As a decentralised digital ledger, blockchain has become a buzzword in the recent years, due to its advantageous characteristics. The application of blockchain has been associated with different implications, ranging from trust generator to increased efficiency. Recently, blockchain application has gained momentum by being implemented by different governments and public bodies, as a solution for tackling different issues, with the intent of providing more efficient public policies. Different blockchain-based systems and platforms have been increasingly introduced as a more secure and orderly alternative of delivering various public functions and services. Given the expansion of use cases in different countries and the scattered information in this regard, this chapter develops a taxonomy of blockchain outcomes in the public domain by identifying the emerging patterns and subcategories. The proposed taxonomy can support decision makers and researchers to better identify the various blockchain applications, alongside their benefits, implications, and possible associated risks.
IMPLEMENTATION OF INNOVATIVE FORMS OF TEACHING IN THE TEACHING OF PEDAGOGICAL DISCIPLIN

This article is devoted to the description of the experience in the development and implementation of innovative forms of organizing training in the course of teaching pedagogical disciplines. Based on the analysis of the Federal State Educational Standard of Higher Professional Education in the direction “Pedagogical education” and “Pedagogical education (with two training profiles)” and the survey conducted, the author substantiates the need to introduce new forms of work with students at the university. Among them, the educational games “A journalist for myself”, “Find a problem and a solution” are distinguished; using infographic techniques and designing book trailers. The games considered in the article are copyrighted, the rest of the methods are modified in accordance with the objectives of the study and the specifics of the taught discipline. As a result of the study, the author concludes that work in this direction is promising and the influence of the considered forms of organizing training on the formation of educational independence.
Security in Agile Development, use Case in Typeform

Software development methodologies have evolved during the last years to reduce the time to market to the minimum possible. Agile is one of the most common and used methodologies for rapid application development. As the agile manifesto defines in its 12 principles, one of its main goals is to satisfy the customer needs through early and continuous delivery of valuable software. Significantly, that none of the principles refers to security. In this paper, we will explain how Typeform integrates security activities into the whole development process, reducing at the same time the phases on the S-SDLC to reduce friction and improve delivery while maintaining the security level.
Existence of the Literacy Community "Gerakan Musi Membaca" and Children's Reading Interest in Musibanyuasin

This study aims to reveal the existence of the literacy community "Gerakan Musi Membaca" and the implications of its existence in the development of children's reading interest in Musi Banyuasin. This research is a qualitative study, the primary source of which comes from literacy actors and school children in Musi Banyuasin. Data collection techniques used were interviews and direct observation in the research field. The results showed that the literacy community of the Musi Reading Movement was a community that moved to increase the reading interest of the surrounding community. To support and attract visitors, the Literacy Movement reading literacy community provides a variety of books. The existence of this literacy community is very helpful to the community in improving reading, by planning the procurement of a book collection in the form of activities to formulate the objectives of the program to be held, determine the techniques to be used, and identify the collection of readings. There are several obstacles in this activity namely the surrounding environment still often looks at odd people who spend time reading for example while waiting in line, or just sitting in a city park while reading.
A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles.

In this survey, we systematically summarize the current literature on studies that apply reinforcement learning (RL) to the motion planning and control of autonomous vehicles. Many existing contributions can be attributed to the pipeline approach, which consists of many hand-crafted modules, each with a functionality selected for the ease of human interpretation. However, this approach does not automatically guarantee maximal performance due to the lack of a system-level optimization. Therefore, this paper also presents a growing trend of work that falls into the end-to-end approach, which typically offers better performance and smaller system scales. However, their performance also suffers from the lack of expert data and generalization issues. Finally, the remaining challenges applying deep RL algorithms on autonomous driving are summarized, and future research directions are also presented to tackle these challenges.
The EFFECT OF TEACHER PERFORMANCE ON STUDENT LEARNING MOTIVATION IN DISTANCE LEARNING DURING COVID-19 PANDEMIC AT SMP NEGERI 20 BEKASI

This study aims to reveal the effect of teacher performance (X) on student’s learning motivation (Y) in distance learning during the pandemic. The research method used is a quantitative method with data management using the SPSS 16.0 application. Analysis of the data used is simple regression analysis. The research sample is 53 students of SMP Negeri 20 Bekasi. The conclusion of the research revealed: (1) The significance test of the regression line equation was found that Fhit = 46,345 with a significance level of = 0,00 < 0,05 or Ho was rejected, then the regression model could be used to predict the participation variable. Thus, the Y or X regression is significant or the teacher’s performance has an effect on student’s learning motivation. (2) The significance test of correlation coefficient obtained the magnitude of the correlation coefficient, namely  0,690 and Fhit = 46,345 with p-value = 0,00 <0,05. This means that Ho is rejected, meaning that the correlation coefficients of X and Y are significant. While the percentage of the influence of the independent variable (teacher’s performance) on the dependent variable (student’s learning motivation) which is called the coefficient of determination is 0,476, which implies that the influence of teacher’s performance on student’s learning motivation is 47,6%.
Image processing based off-line signature recognition and verification system

Even in today’s age signature is one of the most important and used forms of proof to identify a person. Signature is a unique offline way to recognize any person. Signatures are used in almost all documents such as financial services, legal services, letters, cheques, security documents, etc. Illegal acts like forgery are a great concern in our daily life. Negligence of signature verification leads to forgery. This paper is a novel approach for offline signature verification. In this project, signature verification is done using Image Processing, where the signature is kept manually on paper and is acquired using a scanner or a camera, and is kept in an image format. For verification of the signature, the proposed method depends on geometrical and statistical uprooting of attributes and then the database, where the attributes are trained. In this, the reference signature is compared with the investigation signature and determines if the signature is genuine or forged.
Question Answering System Model Based on Multi Granularity Semantic Representation

Aiming at the problems of polysemy and overflow words in traditional vector representation methods such as word2vec and glove in question answering system, this paper introduces Elmo language model, char-CNN and traditional natural language features, and makes a complete semantic representation of the original corpus text from multiple language granularity levels A neural network model for multi granularity semantic representation. Experiments on the squad dataset show that the proposed model is superior to the classical bidaf model in terms of accurate matching rate and F1 value.