Reviewerly/exHarmony huggingface dataset:
PECULIARITIES OF USING THE PROJECT METHOD IN TEACHING EDUCATIONAL COMPONENTS OF THE COMPETENCE OF COMPUTER SCIENCE

The introduction of a learning model into the educational process, which combines the advantages of classroom organizational form of learning and project methods and differs from existing ones by using educational tasks (projects), quite long in time and aimed at comprehensive personal development in the information society, is a promising area of ​​research practices. The substantiated technique of application of a method of projects at teaching of disciplines of a specialty “Computer sciences” based on integration of scientific approaches to the maintenance of training and on priority of studying of programming, problems of the maintenance of project tasks on kinds of activity, partnership interaction of project participants) logical communication. It is proved that the use of the methodology allows to carry out competency-based learning on the basis of integration of scientific approaches. The experimentally confirmed tendency to increase the level of formation of information and communication competence of experimental groups by increasing the minimum level of knowledge, skills, their attitude to mastering the content of informational educational component of learning, their motivational and reflexive readiness to use digital technologies and software environment for independent work and communication.
Sistem Informasi Pelaporan Status Gizi Balita Berbasis Web di Puskesmas Banjarsengon

Recording and reporting nutritional status at the Banjarsengon Community Health Center is still manual and uses Excel. The report also includes the process of determining or calculating the nutritional status of children under five. The use of Excel has many limitations such as the absence of a password for toddlers data security, the process of rearranging the Excel sheet for printing and so on. The purpose of this study was to design and create a web-based nutritional status reporting information system for children under five in the Banjarsengon Health Center using the waterfall method. Data collection is done by interview, observation, and documentation. The results of this study are web-based nutritional status reporting information systems with several advantages, in addition to focusing on calculating the nutritional status of children under five, this information system can also make detailed nutritional status reports for toddlers. The detailed report in question is a toddler report which is grouped based on nutritional problems experienced by toddlers and their solutions. This information system is expected to make it easier for nutrition workers at the Banjarsengon Health Center to carry out their duties.
Book Reviews

This book on Blockchain for distributed systems security is one of the timely books available on this topic. It summarizes the research efforts done in the area of distributed systems security with particular emphasis on Blockchain. Experienced researchers who have vast experience in distributed systems security edited this book. Researchers who are working in this area of Blockchain security including post-graduate students will find this book useful. The topics covered in this book are interesting for readers in the area of Blockchain security and privacy. The main feature of this book is that it contains three chapters that are in fact top voted blockchain research papers. This book has 14 chapters that are organized into four parts: . The first part covers the basic topic of Blockchain; the second part of this book focuses on presenting Blockchain solutions for distributed systems security; the third part of this book discusses Blockchain security; and the fourth part discusses Blockchain implementation.
Increasing Usability in Variable Brightness Situations

As computing moves more the to mobile sphere, we are seeing more and more screen usage outside. As phone displays are not ideal for use in full brightness or even full darkness, we seek to find UI techniques that developers can utilize, such as specific colors and design techniques, that will maximize usability in all situations.
How Much!? Determining the Cost of an Assignment in an Organic Chemistry Class

Students in Organic Chemistry for Majors were required to write a paper as the culminating course assignment. Prior to completing this assignment, students could attend a library instruction session covering relevant databases and resources. Upon submission of their papers, bibliographies from 53 students were collected. Calculations were made to attempt a holistic account of costs associated with completing the assignment. Factors such as the cost of journals, databases, and librarian time were all included in the overall cost estimate, totalling $7,189.22 for this single assignment.
Correction of Shading Effects on Different Components of Solar Radiation

There have been many published articles describingshading effect algorithms for solar irradiation mapping indifferent components, that enabling scientists to gain experiencewith new techniques at low cost. The maps for diffuse, direct and global Solar irradiation havebeen calculated in combination satellite image data (Input data insystem) for a shorter period of one day. structured together usingthe “Inverse distance to a power” interpolation method.The Global and Diffuse irradiation maps were calculated with analgorithm based for correcting shading effects related to theorography estimated in Horizontal Plane and evaluate it on anyinclined plane using the sky brightness and clearness index andthe relative optical attenuation factor of the atmosphericthickness. The Direct irradiation is mapped as the combinationbetween global and diffuse irradiation. The tests of this methodwere carried out on several large sites, and showed good results.Keyword: Direct and global irradiation, Diffuse circumsolar andisotropic, index of shading effect
Machine Learning for Classification of Emotion in Speech

The naturalness of the speech in any human being comes from his or her emotions. All human beings deliver and construe the messages with heavy use of emotions. So there is a need to develop a speech interface through which emotions embedded in the speech signal can be analyzed and processed. There are many speech translation systems developed with intent to interpret the inherent emotions in the speech signals but lack in processing the embedded emotions in the speech as because there is a lacuna in their modeling and depiction. The main objective of any speech processing system is to retrieve interesting information from speech like features, models so that the retrieved knowledge of interest can be further used in various speech processing applications. The scope of the present paper is to travel around the attributes of speech and its respective models with a goal to distinguish emotions by imprisoning precise information about emotion. This paper also studied various sources like source of excitement, vocal track system’s silhouettes and its sequence, attributes of supra- segment to obtain a rich source of emotional information of a speech. The paper end with a final conclusion saying that source of excitation and its characteristics may be be single handedly enough for efficient acknowledgment of emotions.
Quality Improvement Program for Colocation Data Center Services Using Quality Function Deployment (QFD)

When a product is launched, it's always been expected by the company that the product is going to be sold out in the market. But, after three years of selling XYZ colocation data center services, the sales of this product still hasn't achieve its target. Therefore, an evaluation is needed to know how costumers value the product in the market and what's needs to be done to improve its value. XYZ Data Center Management has conducted a preliminary analysis through discussion with customers, a comparative study with competitors, and discussion with internet service provider association. It's concluded that there is quality in XYZ Data Center, both in features and services that don't satisfying enough. Further analysis then conducted with Quality Function Deployment or QFD as a research method. The reason behind the use of QFD is because of its ability to identify what customers want, and translate it into the company's need in terms of technical responses. The result obtained from this research is the attributes that customers need and the technical responses required to answer it. Examples of attributes are the availability of the working room, the availability of site visit procedure, the accuracy of time needed for installation, etc. And for technical response, the examples are making a portal for trouble handle monitoring in integration with a call center, an improvement on IT Hall layout building a portal for installation monitoring, etc.
A Bicolano-to-Tagalog Transfer-Based Machine Translation System

The Bicolano-Tagalog Transfer-based Machine Translation System is a unidirectional machine translator for languages Bicolano and Tagalog. The transfer-based approach is divided into three phase: Pre-Processing Analysis, Morphological Transfer, and Sentence Generation. The system analyze first the source language (Bicolano) input to create some internal representation. This includes the tokenizer, stemmer, POS tag and parser. Through transfer rules, it then typically manipulates this internal representation to transfer parsed source language syntactic structure into target language syntactic structure. Finally, the system generates Tagalog sentence from own morphological and syntactic information. Each phase will undergo training and evaluation test for the competence of end-results. Overall performance shows a 71.71% accuracy rate.
ANFIS for Tamil Phoneme Classification

Phoneme recognition is an intricate problem lying under non-linear systems. Most research in this area revolve around try to model the pattern of features observed in the speech spectra with the use of Hidden Markov Models (HMM), various types of neural networks like deep recurrent neural networks, time delay neural networks, etc. for efficient phoneme recognition. In this paper, we study the effectiveness of the hybrid architecture, the Adaptive Neuro-Fuzzy Inference System (ANFIS) for capturing the spectral features of the speech signal to handle the problem of Phoneme Recognition. In spite of a wide range of research in this field, here we examine the power of ANFIS for least explored Tamil phoneme recognition problem. The experimental results have shown the ability of the model to learn the patterns associated with various phonetic classes, indicated with recognition improvement in terms of accuracy to its counterparts.
The Role of Educational Technology in Fostering 21st Century Learning Skills in Social-Emotional Learning

Technology is transforming P-12 education. Student-driven inquiry and thirst for technology are gradually pushing out the traditional, teacher-centered classroom. Technology is seen as a powerful tool to integrate in the curriculum to create more student-centered learning and more personalized learning for students. Acknowledging that we are all living in a digital age as well as recognizing the students who are in our present-day schools are 21st century learners, educators are examining their own mindsets of what it means to be 21st century teacher. They are assessing and considering new pedagogical methods that integrate technology to further promote collaboration, communication, critical thinking, and creativity in and outside of the classroom.
Pengertian Administrasi Sarana dan Prasarana Pendidikan

this article contains the importance of administration of facilities and infrastructure in schools to support success in achieving the goals of education
Efficient Text Mining Model with Conceptual Informative Relational Measure using Semantic Ontology

The problem of text mining has been well studied and numerous approaches are analyzed towards their performance in text mining. The existing methods suffer to achieve higher performance as they consider only content of document and the term features available. Also, they measure the similarity between documents on the term features to identify the class of any document. This affects the performance of text mining and produces poor accuracy and generates higher irrelevancy. To improve the performance, a Conceptual Informative Relational Model (CIRM) is presented in this paper. Unlike previous methods, the method considers both conceptual and informative relations in measuring the similarity between the documents. The method preprocesses the text documents by eliminating the stop words, stemming and identifies list of root words or nouns. The root words extracted has been used to measure the conceptual relation and informative relation according to the taxonomy of classes and semantic meanings. Based on the value of relational measures, the method identifies the class of the document and produces result set. The proposed method improves the performance of text mining and reduces the irrelevancy.
Anisotropic Image Restoration Based on Image Inpainting with Diffusion Enhancement

Reconstructing the damaged images and improving the quality of an image, results in image restoration. Here anisotropic diffusion based iterative inpainting developed to minimise the noise level in the colour images and enhancing the image boundaries, this approach observed on speckle, Gaussian and shot noise. To reduce noise and topological defects from images, 3D- anisotropic diffusion used to decompose the image into high frequencies and low frequencies and protects the image from losing the information, to enhance the image quality, image inpainiting was used. In this process most of the high frequency decomposed sections got damaged with noise and appears as there is information available at those pixels, therefore the complete restoration process was done on all the high frequency decomposed components so this results in achieving better restored images in mean time. The two effects on images can be reduced by the mixed fusion algorithm i.e., noise reduction by using anisotropic diffusion and distance based neighbourhood image inpainting for restoring the damaged parts. So, this results in reconstructing the damaged image and enhancing the boundaries of the image.
PREDATORY JOURNALS ARE INDEXING IN REPUTED DATABASES: A CASE STUDY OF UNSOLVED ISSUES

The aim of this study is to identify the features of fraudulent journals. Fraudulent and clone journals wasted valuable manuscripts when scholars and authors publish their works in these journals. Fraud journals publish the articles without reviewing process with a high rate of fee while the name and ISSN of clone journals are identical to the original journals. Purposive sampling technique as well as document analysis method have been used to conduct this research. Two clone versions and two fraud journals of the SCOPUS indexing journals have been selected for reviewing their articles. Based on the discussion of this study, researchers found some characteristics of predatory/fraud/ clone journals that will help the scholars to avoid publishing on fake journals.
Classification based Credibility Analysis on Twitter Data

Twitter is an important place to get access to breaking news and information. So, it is necessary to check the trustworthiness of tweets. Credibility is used to assess the quality of being believable or worthy of trust. Credibility analysis refers to attempt to an ascertain truthfulness in short lie detection. In this work, credibility of the twitter data can be assessed using centrality measures. First the tweets are preprocessed using the preprocessing techniques. The preprocessing techniques on tweets: a stop word removal, stemming, pos tagging etc. are used to improve the performance. Preprocessed twitter data can be used to identify the tweet and author features. Then the centrality measures are applied to the preprocessed dataset. The proposed centrality measures used in this work are Betweeness centrality, Eigenvector centrality, Degree centrality and Closeness centrality. The centrality measures are used to find out the trust between the users and it will be given as input to classifiers. The classifiers like Naïve Bayesian, Support Vector Machine and K Nearest Neighbor are used to classify the tweets based on credibility.
IMPROVING STUDENT’S SPEAKING SKILL BY USING STORY COMPLETION TECHNIQUE AT SMP N SATAP WARINGIN

This research aims to determine the use of story completion techniques in improving students'speaking skills of SMP N Satap Waringin. This independent variable was the story completiontechnique, and the dependent variable was the students' speaking skills. This research populationwas the second-grade students of SMP N Satap Waringin academic years 2020/2021, consistingof 90 students. The sample of the research consisted of 26. The sample was chosen by using alottery. The instrument used in this research was the test. The test was used in the pre-test andpost-test. Hypothesis test showed that there was significance value ɑ = 0,000 &amp;lt; ɑ = 0.05 it meantthat Hi was accept. It can be concluded that using story completion was increasing students’speaking skills of the SMP N Satap Waringin.
News from the Field

2019 ACRL Value of Academic Libraries Travel ScholarshipsJohns Hopkins University Press partners with AltmetricLYRASIS and Duraspace announce mergerNISO publishes updated Transfer Code of PracticeEBSCO releases Music Index with Full TextResources for College Libraries call for reviewersDraft ACRL Impactful Scholarship and Metrics Framework feedback
Improving Efficiency of CNN using Octave Convolution

In recent years, the Convolutional neural networks (CNN) has been active in various Artificial intelligence applications as well as computer vision tasks. We suggested an effective technique in this study to decrease the number of duplicates in feature maps of CNN. Proposed a novel convolution scheme Octave convolution (Octconv) to minimize the duplicates in the feature maps and boost the CNNs performance. The principle concept of this method is to separate the Convolutional filters into a higher frequency and lower frequency sections. In this report, we made an attempt for minimizing the spatial redundancy directly from output feature maps of CNN using the following 3 steps: First, divide the channels into higher and lower frequency parts depending on the information of the image using Multi-scale representation. Second, reduce the number of FLOPs from the low frequencies. Third, before sending the output to combine both the higher frequency and lower frequency information of the image. The key purpose of this abstract is to improve CNNs efficiency by reducing spatial redundancy in the feature maps of the convolution layer.
Meningkatkan Keterampilan Membaca Kritis Buku Teks dalam Belajar Sejarah Melalui Metode Search, Solve, Create and Share (SSCS)

Students’ critical reading skill is being decreasing, especially in learning history. In the other hand, students’ reading skill during learning history is important and has its significance to be developed. The indications can be seen from the ability on finding and comparing reading sources, analyzing readings, making notes from reading results, and sharing information from reading analysis results. Due to the significance of this research, author formulates some problems taken, those are: first, how to develop history learning using methods Search, solve, create, and share (SSCS). Second, how to implement the search, solve, create, and share methods (SSCS). Third, how to increase learning using the search, solve, create, and share methods (SSCS). Fourth, the efforts to overcome the obstacles arisen in the application of search, solve, create, and share (SSCS) method. This study aims to improve critical reading skills of student's history textbook during learning history. This study uses a classroom action research model with Kemmis and Taggart design consisting of planning, implementation, observation, and reflection. This study aspects of the textbook's Critical reading skills are selecting information from the historical textbook that corresponds to the discussion, finding information from the history textbooks, analyzing the content of the reading in the history textbooks, asking questions to the teacher or friends about the learning materials in the history textbooks, making notes based on the readings from the history textbook, sharing the work based on the reading results. Based on the results, this search, solve, create, and share (SSCS) may improve Students’ critical reading skill in history learning . This is indicated by the increase in the critical reading skill on textbook of the learning process in each cycle.
Big Data and Artificial Intelligence for E-TOLL

Commuting in Indonesia, an archipelago country, with its geographic location is quite challenging especially when the infrastructure is not well developed in many suburban areas. Land commuter will have to take the toll road to travel to different areas and it requires e-toll card with enough balance to pay. Mostly, problem occurs when the e-toll card is out of balance while the commuters are still in the middle of the toll road and the e-toll machine is not facilitated to offer top up feature where usually the commuter need to wait and borrow the e-toll card from the next commuter to pay at the toll gate and still more. Therefore, this paper will discuss more on the research to solve this problem. The goal of this research is to utilize Big Data and Artificial Intelligent to facilitate the E-Toll system in Indonesia to become better and hopefully keep improving the e-toll service to all land commuters. With the utilization of Artificial Intelligent ability to do the work and modelling human thought process and Big Data with a diversity of high data sources, it needs to be managed by many methods and assistive devices with an appropriate performance. In addition, it aims to determine the constraints that commuters feel while using automated toll gates especially in suburban areas of Indonesia. Methods of research using Systematic Literature Review (SLR). The results of the research will show the ability of these two things in updating the E-Toll system before into a better version continuously.
Monte Carlo Approach Towards Evaluating Random Number Generators Based on Mathematical Schemes Driven from Chua's Circuit

The philosophical nature of randomly generated quantities is widely discussed in the realms of chaos theory. Although, the fundamental premise of the chaos theory does not assume any random behavior in the resulting series and considers them deterministic however highly dependent of the initial conditions of the system, one could address the problem of randomness, by using the output of a chaotic system, as the input of a mathematical function, aiming for the generation of randomly distributed values. For that matter, the voltages of the two capacitors in the classic configuration of a Chua's circuit have been measured. Having defined eight mathematical schemes for manipulating the inputted data set, the current manuscript focuses on the pragmatic and engineering criteria of the resulting data, in terms of randomness, and spectral distributions; hence proposing methods of random data generation. The ranking of schemes has been proceeded through a geometrical manifestation of the Monte Carlo Integration. And the suggested eight schemes are compared with the commercially common timer-based random generators. As the geometrical domain in the Monte Carlo Integration has defined in such a way that the most randomly distributed data set would result in a closer estimation of the number Pi, the suggested scheme working based on 'frequency indicator' is evaluated as the highest-ranked scheme in that regard, with the estimated numerical value of 3.1424 for Pi.