Reviewerly/exHarmony huggingface dataset:
A Study on Number Gesture Recognition using Neural Network

A natural way of counting is with the use of hands.As hand gesture recognition is becoming more recognized through its growing applications, this paper focuses on recognizing the number shown by the hand gesture.The code used in this study is developed by Makeshkha.This system uses an extraction feature which extracts the parts of the image of the hand gesture which is to be used by the system, and a neural network.This system has been trained for numerous iterations with the use of different input images.The network is then used in the recognition of hand number gestures.The system works by first prompting the user for an image to be used for input.The next process is the extraction of the features which goes by the reprocessing of the image through the removal or addition of noise in order to extract the required shape and form of the hand.Lastly, the Artificial Neural Network then scans the database for similarities in the image, with regards to the extracted features, from the input image.The experimental results of the study showed that the system has a considerable percentage of accuracy in the recognition of hand number gestures.
The Development of University Library - Complex of Strategic Decisions

The purpose of the article is to highlight the peculiarities of the libraries` work at higher education institutions in the information environment of Ukraine and the information and educational community of the Kyiv National University of Culture and Arts, determining the improvement priority directions in the context of uninterrupted modernization. The methodology of the research is based on the use of general scientific and determined methods, such as analysis of library documentation, observation, experiment, content analysis, systematic approach and comparative analysis of library statistics indexation, structuring the readers' reviews on the library work and planning events. The scientific novelty consists in covering ways of solving the problems of university library development, applied in the Scientific Library of the Kyiv National University of Culture and Arts` work, determining the place of strategic management in defining and designing development priorities. There are examples of the library work in the areas of culture and education, information technologies, fund conservation, and PH management, which in practice confirm the flexibility of the situational approach in management. Conclusions. The results of the study made it possible to establish that current society trends have a significant impact on the libraries` work at higher education institutions and determine the goals and objectives of its development. A team of professional staff creates new forms of library work to meet the information, scientific, and cultural needs of users totally, thereby during the period of dynamic changes in society, the university library is an intellectual space, a structured social and communications complex. The main library work and learning activity are a common link in the teaching of highly skilled professionals who are able to solve complex scientific and production tasks. The learning activity is subject to the constant development and transformation of the socio-economic and technical situation in the world, so the library should respond to these changes. Consequently, the creation and use of its own strategy bring significant results in improving the work of the Scientific Library of the Kyiv National University of Culture and Arts.
Research on College English Teaching in China Based on Production Function Theory

There are many problems such as high input but low output in college English teaching in China at present.In this paper, the relationship between input and output in the process of college English teaching is analyzed based on the production function, the variable of the production function is analyzed, and reasonable suggestions for improving the efficiency of college English teaching are given.
Facial Emotion Recognition Using Eigenface and Feature Optimization

There is lot of communications between individuals using emotions as it plays important role in information transferring.Broad studies are carried out to explore the dealings between human sentiments and machine interactions.In this paper an efficient approach using feature extraction and optimization is proposed for facial emotion acknowledgment in the form of Eigenfaces.It is an adjusted strategy which begins with the human vision as a standard reference point -by making utilization of the standard database and processes the look contained by the picture of a test confront.It is a novel approach which specifically orders a test picture as having a place with one of the five standard expressions -anger, fear, happy, sad or surprise in a precise manner.In this paper, exploratory verification was given in terms of accuracy, false acceptance rate, false rejection error rates and exchange on further approaches to enhance it.
Emoji Identification and Prediction in Hebrew Political Corpus

Aim/Purpose: Any system that aims to address the task of modeling social media communication need to deal with the usage of emojis. Efficient prediction of the most likely emoji given the text of a message may help to improve different NLP tasks. Background: We explore two tasks: emoji identification and emoji prediction. While emoji prediction is a classification task of predicting the emojis that appear in a given text message, emoji identification is the complementary preceding task of determining if a given text message includes emojies. Methodology: We adopt a supervised Machine Learning (ML) approach. We compare two text representation approaches, i.e., n-grams and character n-grams and analyze the contribution of additional metadata features to the classification. Contribution: The task of emoji identification is novel. We extend the definition of the emoji prediction task by allowing to use not only the textual content but also meta-data analysis. Findings: Metadata improve the classification accuracy in the task of emoji identification. In the task of emoji prediction it is better to apply feature selection. Recommendations for Practitioners: In many of the cases the classifier decision seems fitter to the comment content than the emoji that was chosen by the commentator. The classifier may be useful for emoji suggestion. Recommendation for Researchers: Explore character-based representations rather than word-based representations in the case of morphologically rich languages. Impact on Society: Improve the modeling of social media communication. Future Research: We plan to address the multi-label setting of the emoji prediction task and to investigate the deep learning approach for both of our classification tasks
MOODLE LMS Resources Prediction: Exponential Moving Average Approach

Learning Management System (LMS) is a software that helps higher education institution provide their services to teachers and students.Every year intakes in the university aim to take more students to register.This phenomenon impacts LMS data storage capacity.University has to find a strategy in identifying how much size they need to prepare.One way to identify it is by using an exponential moving average method to predict storage that needed in the further semester.Tested with a web forecasting application and Universitas Multimedia Nusantara's Moodle dataset, exponential moving average was giving a big error measurement number.This means that the exponential moving average was not quite fit to predict the resources in LMS.
Specifics of soft skills development of IT-students by the means of educational scrum projects

The article raises a problem of finding relevant and effective methods for the development of soft skills of future specialists in the area of informational technologies. As the starting point of the research the author defines a project work during which an independence and skills of solving problems in the subsequent professional activities are formed. The first section of the work examines the essence of soft skills and provides their classification. The author also highlights the most significant soft skills of an IT employee, including creativity, conflict management, critical thinking, presentation, leadership, communicative skills, flexibility, and gives a brief description of each of them. In the next section the author examines both monolith and agile types of software development methodologies, used in modern IT companies, making an accent on how the soft skills of professionals are implemented in the process of work. Particular attention is paid to the Scrum methodology, which is considered as the best polygon of development of non-technical skills of a specialist. The article also contains a description of the processes and project roles in Scrum. The last section of the work contains a detailed analysis of the use of soft skills at each stage of the Scrum methodology, confirming the effectiveness of it as a form of developing the soft skills of future IT specialists
Technology in the Classroom: Teachers’ Technology Choices in Relation to Content Creation and Distribution

Aim/Purpose: Teachers are being asked to integrate mobile technologies into their content creation and distribution tasks. This research aims to provide an understanding of teachers taking on this process and whether the use of technology has influenced their content creation and distribution in the classroom. Background: Many claim that the use of technology for content creation and distribution can only enhance and improve the educational experience. However, for teachers it is not simply the integration of technology that is of prime concern. As teachers are ultimately responsible for the success of technology integration, it is essential to understand teachers’ viewpoints and lived technology experiences. Methodology: The Task-Technology Fit (TTF) model was used to guide interpretive case study research. Six teachers were purposively sampled and interviewed from a private school where a digital strategy is already in place. Data was then analysed using directed content analysis in relation to TTF. Contribution: This paper provides an understanding of teachers’ mobile technology choices in relation to content creation and distribution tasks. Findings: Findings indicate that teachers fit technology into their tasks if they perceive the technology has a high level of benefit to the teaching task. In addition, the age of learners and the subject being taught are major influencers. Recommendations for Practitioners: Provides a more nuanced and in-depth understanding of teachers’ technology choices, which is necessary for the technology augmented educational experience of the future. Recommendations for Researchers: Provides an unbiased and theoretically guided view of mobile technology use with content creation and distribution tasks. Impact on Society: Teachers do not appear to use technology as a de facto standard, but specifically select technology which will save them time, reduce costs, and improve the educational experiences of their learners. Future Research: A mixed-method approach, including several diverse schools as well as learners would enrich the findings. Furthermore, consideration of hardware limitations and lack of software features are needed.
Bit Level Encryption Algorithm Using Chaos Version 1.0(BLEAUC-1.0)

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Implementation of Digital Signature Using a SWOT Analysis to Improve Information Security

At present in the digitalization era, online transactions continue to grow as well as digital signatures are becoming known to the public. Renewal of research and improvements continues to be made to improve the implementation of digital signatures in Indonesia. There needs to be research to find out the differences between the providers of electronic certificates that are developing in Indonesia. Digital signatures are expected to be able to simplify the administrative process and be implemented properly at Perum LKBN Antara. The application of digital signatures is protected by Ministerial Regulation No. 11 of 2018 and Government Regulation No. 82 of 2012 concerning the implementation of systems and electronic transactions (PSTE). In this study using the SWOT analysis (Standard, Weakness, Opportunities, Threat) as a problem solving method. There are 4 criteria assessed, namely the ease, security, work system and speed of the system category. In-depth discussion using the privyID application system. The application of using privyID is classified as good at Perum LKBN Antara.
PENERAPAN MODEL PEMBELAJARAN CONCEPT ATTAINMENT UNTUK MENINGKATKAN AKTIVITAS MATEMATIKA SISWA SMP

AbstrakPenelitian ini bertujuan untuk mengetahui cara penerapan model pembelajaran concept attainment sehingga dapat meningkatkan aktivitas belajar matematika siswa kelas VII SMP Negeri 1 Pondok Kelapa. Jenis penelitian yang dilaksanakan adalah Penelitian Tindakan Kelas (PTK) dengan teknik pengumpulan data melalui lembar observasi aktivitas siswa. Subjek dalam penelitian ini adalah siswa kelas VII 2 SMP Negeri 1 Pondok Kelapa tahun ajaran 2017/2018 yang berjumlah 28 orang. Hasil penelitian ini menunjukkan penerapan model pembelajaran concept attainment dapat meningkatkan aktivitas belajar siswa. Peningkatan aktivitas dapat dilihat dari skor rata-rata observasi siswa siklus I, II, dan III secara berturut-turut yaitu 27,875 (cukup aktif); 36,75 (aktif); dan 43,75 (sangat aktif).Kata kunci: aktivitas belajar, model pembelajaran concept attainment. AbstractThe aim of this research was to know how to implement concept attainment learning model in order to improve student’s activity of grade VII class at Junior High School Number 1 Pondok Kelapa. The type of research was Classroom Action Research (CAR) with collecting data technique by using observation sheet of student’s activity. The Subject in this research was 28 students of class VII 2 Junior High School 1 Pondok Kelapa even semester of academic year 2017/2018. Amount of the subject in this research was 28 students. This research showed that the implementation of concept attainment learning model can improve student’s activity. The activity improvement can be seen from mean scores of student’s observation on first, second and third cycle respectively which were 27,875; 36,75; and 43,75 with their criteria that include quite active, active, and very active. Key terms: learning activity, concept attainment learning models
Spatial Variability of Heavy Metals in Surface Water and Sediment in the Kolo Creek Water Body in the Niger Delta of Nigeria and Geochemical Factors that Influence their Interactions Using Geo-accumulation Index

The Kolo Creek is an inland water body in the Niger Delta receiving organic and chemical wastes arising from anthropogenic activities within the catchment area. This study was therefore carried out to investigate the spatial variabilities of heavy metals in surface and sediment and their geochemical factors that influence their presence along the Kolo Creek in 2018 using Geo-accumulation index and pollution load index to extrapolate the level of heavy metal contraction in the two medium. Sediment and Water samples were collected for five (5) months and assessed from eight sampling points (A-h) for seven (7) heavy metals such as Copper (Cu), Lead (Pb), Iron(Fe), Camium (Cd), Manganese (Mn), Nickel (Ni) and Mercury (Hg). All the heavy metals had geo-accumulation indices below zero which indicates no pollution except Fe which had geo-accumulation index in the range 3.327 in surface water and 7.751 in sediment, furthermore, the pollution load index revealed a toxicity of 0.664 times in surface water as against 1.501 times in sediment exceeding the background concentration in the Kolo Creek. Hence, poor ecological ethics and culture should be discouraged to keep the Kolo Creek water under check for safe domestic water use.
Analysis of Evaluated Sentiments; a Pseudo-Linguistic Approach and Online Acceptability Index for Decision-Making with Data: Nigerian Election in View

Sentiments measured properly always give direction to future occurrences.Without an expression through feelings plus sensitive statements, it would be difficult to predict future occurrence.But when feelings are expressed through spoken languages or written texts, a projection of future event can be evaluated to an extent.Nigeria is blessed with intellectuals and over 48% of the population are actively involved in social media.The beauty of this great nation is in its diversity and practice of democracy.Since independence, they have experienced variations in handling their hard-earned democracy.The goal of this paper is to compare analyzed sentiments from the Nigerian people across the 6 geopolitical zones and the aftermath of the Nigerian election in 2019.Data is retrieved from the social media using python programming language across 2 major platforms twitter and Facebook.A word cloud is introduced later to differentiate various sentiments using a spiral loop to map the various artifacts into corpora.Vader machine learning system called Sentiment Intensity Analyzer was used to the analyze each statement to retrieve positive and negative sentiments.This study employs two methodologies, quantitative and qualitative methods with significant levels of descriptive approach in data analysis.The researchers explore the results of the analysis to verify whether significant decisions can be made in the future from data generated from social media, using the 2019 Nigerian election as a case study.A dashboard was developed to plot the different feelings and how they influenced the general election outcome.PHP and JavaScript were used to achieve this.It is recommended that stakeholders in the 'digital humanities and arts' explore the findings in this paper especially if the result comes at least close to 80% of the real result.
A blockchain based framework for information system integrity

A blockchain based system integrity (BCSI) framework for assuring the integrity of information system processes is presented. BCSI is well suited for a broad class of large scale real-world information systems. Under the BCSI framework, the integrity of any information system I is assured by executing the finite state machine model for system I processes in a blockchain network. The BCSI framework is compared and contrasted with the Clark-Wilson (CW) system integrity model, and existing blockchain based frameworks like Ethereum.
Equiprobable mappings in weighted constraint grammars

We show that MaxEnt is so rich that it can distinguish between any two different mappings: there always exists a nonnegative weight vector which assigns them different MaxEnt probabilities.Stochastic HG instead does admit equiprobable mappings and we give a complete formal characterization of them.We compare these different predictions of the two frameworks on a test case of Finnish stress.
A Cellular Ant Colony Algorithm for Path Planning Using Bayesian Posterior Probability

In order to solve the problem of slow convergence rate in traditional ant colony algorithm for UAV path planning, a new cellular ant colony algorithm is proposed. First, we construct a sector prediction area in grid environment map. Then we build heuristic and obstacle repulsion functions of target nodes in the prediction area. Using these functions, we can get the Bayesian conditional probability and posterior estimation of target nodes. In the end, we select the node with the largest posterior estimation as the next path node. The simulation results show that the new algorithm has better global search ability. Furthermore, using the sector prediction area makes the planned path more consistent with the UAV flight characteristics. And the designed functions in the sector prediction area speeds up the path search process.
Analisis Forensics Untuk Mendeteksi Pemalsuan Video

The current technology is proving that the ease with which crimes occur using computer science in the field of video editing, in addition from time to time more and more video editing software and increasingly eassy to use, but the development of this technology is widely misused by video creators to manipulate video hoaxes that cause disputes, so many video cases are spread which cannot be trusted by the public. Counterfeiting is an act of modifying documents, products, images or videos, among other media. Forensic video is one of the scientific methods in research that aims to obtain evidence and facts in determining the authenticity of a video. This makes the basis of research to detect video falsification. This study uses analysis with 2 forensic tools, forevid and VideoCleaner. The result of this study is the detection of differences in metadata, hash and contrast of original videos and manipulated videos.
Implementasi Metode Fuzzy Tsukamoto Untuk Pendeteksian Varitas Unggul Pada Tanaman Jagung

Zea mays or corn is one of the carbohydrate-producing plants that most Indonesian people consume as a staple food. Based on data from the agriculture ministry in 2016, corn production in Indonesia, during the last 5 years, corn production has increased by 14% to reach 28.9 million tons per year. Increased corn production in Indonesia will be highly proportional to the increase in food yields and Indonesia's national income. Based on the above problems, the question in this study is how to implement the Tsukamoto method to determine the superior variety of corn. One method that can select and differentiate varieties of corn is the Tsukamoto method. This method can recommend the best varieties among several other good varieties. Keywords: Corn, Tsukamoto Method, Decission Support Systems.
Vulnerabilities Detection via Static Taint Analysis

Due to huge amounts of code in modern software products, there is always a variety of subtle errors or ﬂaws in programs, which are hard to discover during everyday use or through conventional testing. A lot of such errors could be used as a potential attack vector if they could be exploited by a remote user via manipulation of program input. This paper presents the approach for automatic detection of security vulnerabilities using interprocedural static taint analysis. The goal of this study is to develop the infrastructure for taint analysis applicable for detection of vulnerabilities in C and C++ programs and extensible with separate detectors. This tool is based on the Interprocedural Finite Distributive Subset (IFDS) algorithm and is able to perform interprocedural, context-sensitive, path-insensitive analysis of programs represented in LLVM form. According to our research it is not possible to achieve good results using pure taint analysis, so together with several enhancements of existing techniques we propose to supplement it with additional static symbolic execution based analysis stage, which has path-sensitivity and considers memory region sizes for ﬁltering results found by the ﬁrst stage. The evaluation of results was made on Juliet Test Suite and open-source projects with publicly known vulnerabilities from CVE database.