Reviewerly/exHarmony huggingface dataset:
MEDIA PENGENALAN ORGAN TUBUH MANUSIA DALAM BAHASA LATIN UNTUK SISWA SMP BERBASIS ADOBE AFTER EFFECT

Making media on the introduction of human body organs in Latin based on Adobe After Effect is aimed at junior high school students with the aim and purpose that junior high school students are more interested getting to know the human organs in Latin with this 2D animated video. Making media introduction to human organs in Latin based on Adobe After Effect through three applications, the Adobe After Effect application is used for making animation, Adobe Illustrator to draw all of characters, background settings or other ambience and Adobe Audition as audio editing manager before being combined into Adobe After Effect. The process of making this animation requires a story idea, scene and storyboard. There are several steps to make an animated object to become a 2D animation video, modeling or depiction of background characters and other ambience, audio editing and animation. The result of this animation research is a learning medium for human body organs in Latin for junior high school students which aims to provide information about animation the body organs in the human body along with an explanation.
Tow matching localization algorithm for short fiber bunched tow based on global-local images

In a system that detects tension in polyester fibers on a circuit, If the tension of the tow is to be detected, the position of the tow must be precisely located. this paper proposes a matching localization algorithm for short fiber bunches based on global-local dual images to achieve the precise positioning of polyester fiber tow. This algorithm mainly uses the characteristic difference of the polyester filament beam to match the same polyester fiber tow in the local and global filament beam images. Furthermore, the positioning of the polyester fiber tow to be tested for tension in the local polyester fiber image is realized in the global polyester fiber tow image. The algorithm has good real-time performance and high accuracy.
Parallel HAIFA Hashing Algorithm Based on Lorenz Chaos

Aiming at the inefficiency under parallel environment or large data computation, HAIFA hash function based on Lorenz chaos is constructed in parallel, and a parallel hash function based on Lorenz chaos is proposed. The algorithm compresses each message block independently and can be executed concurrently. After the hash value of each message block is obtained, every two hash values are combined. The odd-numbered rounds are combined with modular addition and right loop operation, while the even-numbered rounds are combined with XOR and left loop operation. The difference of each round of operation further enhances the anti-collision and anti-forgery attacks of the algorithm. The new parallel algorithm is tested for safety analysis and efficiency. The results show that the parallel modified algorithm has good performance and high efficiency, which has certain reference significance for the safety construction of parallel chaotic hash algorithm.
Structural Characteristics of Africa and Its Place in the International Arena

Decades after gaining independence, most African states depend on their relations with their past colonisers to ensure continuity in terms of economy and legitimacy. Further they depend on developed states foreign aid and foreign institutions to maintain their structural integrity. This had created an element of dependency that even with the reality that states in Africa have vast and wealthy resources, which if well used can drive them to global economic standards, they still fail to be self sufficient and fail to provide tailor made solutions to their needs.This is more so evident in Africa's economic integration. States in Africa have established regional economic blocks such as COMESA, SADC, ECOWAS etc. and instead of promoting intra linkages between themselves, these blocks have looked to create vertical linkages with Western economies in terms of trade and investments.Further, the heavy dependence on foreign aid and the operations of multinational firms in Africa derive an element of neo colonialism. Such European franchises and corporations are economically exploiting African states while introducing cultural domination.
An Efficient Network Classification Based on Various-Widths Clustering and Semi-Supervised Stacking

Network traffic classification is basic tool for internet service providers, various government and private organisations to carry out investigation on network activities such as Intrusion Detection Systems (IDS), security monitoring, lawful interception and Quality of Service (QoS). Recent network traffic classification approaches have used an extracted and predefined class label which come from multiple experts to build a robust network traffic classifier. However, keeping IP traffic classifiers up to date requires large amounts of new emerging labeled traffic flows which is often expensive and time-consuming. This paper proposes an efficient network classification (named Net-Stack) which inherits the advantages of various widths clustering and semi-supervised stacking to minimize the shortage of labeled flows, and accurately learn IP traffic features and knowledge. The Net-Stack approach consists of four stages. The first stage pre-processes the traffic data and removes noise traffic observations based on various widths clustering to select most representative observations from both the local and global perspective. The second stage generates strong discrimination ability for multiview representations of the original data using dimensionality reduction techniques. The third stage involves heterogeneous semi-supervised learning algorithms to exploit the complementary information contained in multiple views to refine the decision boundaries for each traffic class and get a low dimensional metadata representation. The final stage employs a meta-classifier and stacking approach to comprehensively learn from the metadata representation obtained in stage three for improving the generalization performance and predicting final classification decision. Experimental study on twelve traffic data sets shows the effectiveness of our proposed Net-Stack approach compared to the baseline methods when there is relatively less labelled training data available.
Exploration of College English Teaching Reform in the New Period

In the new era, with the rapid development of my country's economy, reform and opening up has entered a new stage of development, and the quality of development of all walks of life is continuously improving. Under such circumstances, people’s emphasis on education is constantly increasing, and society’s requirements for education reform are becoming more urgent. In the current college English teaching, due to the deepening of reforms, the quality of teaching is constantly improving. However, English teaching in some remote areas is still lagging behind and cannot meet the needs of current economic development for talents. Therefore, comprehensively promoting the reform of college English teaching and promoting the balanced and comprehensive development of education in all regions play a very important role in cultivating comprehensive talents and promoting economic development. This article discusses and explains in detail the exploration of college English teaching reform in the new era.
Co-link analysis as a monitoring tool : A webometric use case to map the web relationships of research projects

This study explores the societal embeddedness of the websites of research projects. It combines two aims: characterizing research projects based on their weblink relationships, and discovering external societal actors that relate to the projects via weblinks. The study was based on a set of 121 EU-funded research projects and their websites. Domains referring to the websites of the research projects were collected and used in visualizations of co-link relationships. These analyses revealed clusters of topical similarity among the research projects as well as among referring entities. Furthermore, a first step into unveiling potentially relevant stakeholders around research projects was made. Weblink analysis is discussed as an insightful tool for monitoring the internal and external linkages of research projects, representing a relevant application of webometric methods.
Managing Students & Employees Through College Information Management System (Cims) – A Case Study: Shinas College of Technology (Shct), Oman

Purpose: The objectives of the study were to critically analyze the effectiveness of CIMS in completing the registration / academic advising process at Shinas College of Technology and to critically analyze the effective functions of the CIMS to fulfill the role played by the CIMS. Design/methodology/approach: For this research study, Simple random sampling method in selecting the samples of the survey. 180 samples were collected which include the faculty, students and users of the College Information Management System (CIMS) from Shinas College of Technology (ICT). The collected data underwent analysis using the SPSS and the findings were interpreted. Findings: The study reveals that CIMS is characterized by its multiple functions; is user-friendly and flexible. CIMS has met the expectations of most of the users, despite the presence of a few technical problems requiring improvement.Educational Technology Center (ETC) ensures smooth, secure, safe and fast access. CIMS is subject to continuous assessment through periodic follow up by the Educational College Center from any external attacks etc. which is a welcoming feature. Research limitations/Implications: The study suggests that CIMS users should be given training on the updates and necessary training to the CIMS maintenance crew. Social implications: The study suggests thatthere is only a small group of individuals who handles and manages the entire program - installation of CIMS and periodic follow-up etc. and technical expertise is needed at the college level.
The Experience of Green Technology in Malaysia and its Role in Enhancing Sustainable Development

AbstractGreen technology is one of the modern concepts that has received the attention of many countriesbecause it clearly affected the perception of people about the environment and the negative effectthey leave on that environment and the results out of the unwise use of its resources. Thus, greentechnology has its ability to improve the environmental performance and decrease the negativeeffects of the human activities in what contributes to enhancing the sustainable development throughencouraging and incentivizing clean energy production and its uses, green housing, greentransportation, and waste recycling. This research aims at exploring the ongoing developments in greentechnology indicators and indicesThe most important findings that this study reached is that Malaysia has done very noticeable progressin using modern technologies in many walks of life like health, education, energy, and transportation.The studied walks have witnessed a noticeable increase as well.
A Text Difficulty Analysis of English Textbooks for Senior High School and the College Scholastic Ability Test in South Korea Using Coh-Metrix

AbstractThis study aimed to examine the text difficulty of English textbooks for senior high school and the Englishreading section of the College Scholastic Ability Test (CSAT) in South Korea. By analyzing the degree oftheir text difficulty, this study attempted to predict how effectively public education can prepare for theCSAT. Five types of high school English reading and writing textbooks representing the new 2015curriculum, as well as reading passages from the 2019-2020 CSAT English section, were chosen to createa corpus. The text difficulty was compared with linguistic features measured from Coh-Metrix, acomputational language analysis tool on: descriptive indices, word information, lexical diversity, syntacticcomplexity, standard readability, and cohesion. An independent sample t-test is employed to determinewhether there are any statistically significant differences in terms of linguistic aspects between thetextbooks and the CSAT. In conclusion, except for the syntactic complexity and semantic cohesion,textbooks and the CSAT indicate statistically significant differences in 10 of the 13 Coh-Metrixmeasurements: the number of syllables in words, the mean number of words in sentences, age ofacquisition, word frequency, concreteness, imaginability, type-token ratio, Flesch Reading Ease, FleschKincaid Grade Level, and co-referential cohesion. This finding implies that students who follow the schoolcurriculum and rely on textbooks would have difficulty achieving their CSAT goals. A balance betweenthe difficulty of textbooks and the CSAT should be established to accomplish the CSAT's purpose ofnormalizing public education and relieving the strain of excessive learning
시스템사고를 활용한 포스트 코로나 시대 정보화 정책 도출 과정에 관한 연구: 2018∼2022년 전라북도 정보화 기본계획을 중심으로

(Purpose) Through this study, the process of deriving informatization policies can be viewed more systematically and in three dimensions. This allows to consider factors that affect every step of policy development in greater depth.(Design/methodology/approach) After reviewing the previous research, it examines the informatization policies of major countries. Afterwards, the structure of the master plan for Jeollabuk-do informatization is analyzed and new methods are applied to analyze using systems thinking and causal loop diagram analysis by System Dynamics.(Findings) Conventional informatization policies followed a standardized framework and followed the way in which they were applied in order (from a linear thinking). As a result, the main elements of prior research that were reviewed in advance were excluded and only highly practicable policies remained. Thus, the feedback process through systems thinking and causal loop diagram analysis was applied in this study, which allowed us to derive policies that are more faithful to the original vision.(Research implications or Originality) The informatization policy for the post-corona era is derived through this study, it will be possible to present countermeasures by looking at the overall structure of policy environment.
Vector quantization for selecting the number of neurons

The paper deals with the strategy of selecting the number of neurons based on vector quantization methods. Two methods based on neural networks are analyzed: self-organizing map and neural gas. A method of selecting the number of neurons according to the specifics of the data analyzed is presented.
Improving Contact Tracing Phone Apps

Several challenges limit the use of phone apps designed to enhance the speed and reach of COVID-19 contact tracing, according to a recent Government Accountability Office (GAO) report. The agency also found limited ability to determine whether the apps are effective.
The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF

Today, consumers are faced with an abundance of information on the internet; accordingly, it is hard for them to reach the vital information they need. One of the reasonable solutions in modern society is implementing information filtering. Some researchers implemented a recommender system as filtering to increase customers’ experience in social media and e-commerce. This research focuses on the combination of two methods in the recommender system, that is, demographic and content-based filtering, commonly it is called hybrid filtering. In this research, item products are collected using the data crawling method from the big three e-commerce in Indonesia (Shopee, Tokopedia, and Bukalapak). This experiment has been implemented in the web application using the Flask framework to generate products’ recommended items. This research employs the IMDb weight rating formula to get the best score lists and TF-IDF with Cosine similarity to create the similarity between products to produce related items.
Managing a Secure Refresh Token Implementation with JSON Web Token in REST API

JSON Web Token (JWT) is a compact and self-contained mechanism, digitally authenticated and trusted, for transmitting data between various parties. They are mainly used for implementing stateless authentication mechanisms. The Open Authorization (OAuth 2.0) implementations are using JWTs for their access tokens. OAuth 2.0 and JWT are used token frameworks or standards for authorizing access to REST APIs because of their statelessness and signature implementation and JWT tokens are based on JSON and used in new authentication and authorization protocols in OAuth 2.0 because of their small size. When refresh tokens are stored in cookies, the size limit of a cookie or URL may be quickly exceeded. There may be refresh tokens for accessing users and getting the refresh token is a bit more complicated and refresh tokens in the browser require additional security measures and the attacker steals a refresh token and attempts to use it after the application has already used it. This implies that the attacker was able to steal a refresh token from the application. If the refresh token can be stolen, then so can the access token, even short token lifetimes can still lead to major abuse scenarios. In this article, we discuss the security properties of refresh tokens in the browser and the pattern to secure JWT tokens in the web front-end better. We propose a Backend for Frontend (BFF) pattern, where the token handling is deferred to the server-side component to a secure token that provides a lot of flexibility to the client-side.
Students’ Perspective toward English Learning for Non-EFL Students in Higher Education

English course should provide concrete evidence in supporting skills in various fields of science. This research aims to determine the extent of the material provided by lecturer of English courses in teaching non-EFL students. This research was descriptive qualitative research. Data was collected through questionnaires and interviews on research subjects. The subjects of this research were students at the Faculty of Sports Science, Universitas Negeri Makassar, consisting of 4 (Four) study programs: Sports Coaching Education, Physical Education. Recreation and Health, Elementary School Physical Education, and Sports Science. Researcher randomly selected ten (10) students from each study programs using purposive random sampling. Based on data from the results, twelve students (30%) thought that the most material needed in teaching English Material was Vocabulary. Ten (25%) students who thought that the most material needed was Speaking. Six (15%) students who thought that the most material needed was Listening. Five (12.5%) students who thought that the most material needed was Grammar.  Three (7.5%) students who thought that the most material needed was Writing.  Three (7.5%) students who thought that the most material needed was Reading. One (2.5%) student who thought that the most material needed was Pronunciation.
Key Go Aspects

In this chapter the Go programming language will be examined in more depth, covering many key aspects of the language. Examples comparing Go to Java will be used to show similarities and differences.
Rethinking Authority Reconciliation Process

Entity identity management and name reconciliation are intrinsic to both Linked Open Data (LOD) and traditional library authority control. Does this mean that LOD sources can facilitate authority control? This Emblematica Online case study examines the utility of five LOD sources for name reconciliation, comparing design differences regarding ontologies, linking models, and entity properties. It explores the challenges of name reconciliation in the LOD environment and provides lessons learned during a semi-automated name reconciliation process. It also briefly discusses the potential values and benefits of LOD authorities to the authority reconciliation process itself and library services in general.
Infinite Graphs – Toolbox

In this chapter we extend the theory of the key concepts introduced in the previous chapter. In particular, we collect various tools that are needed at later parts of the book and provide further conceptual insights.
Learning from Image Sequences

Many processes are divided into a certain number of stages. The proper diagnostic decisions can be taken on intermediate process stages and only their junction provides a proper result.
Aerial pictures semantic segmentation applying deep learning

An obvious expansion in the measure of satellite dataset accessible lately has made the translation of this information a difficult issue at scale.Determining helpful insights from such pictures requires a rich comprehension of the data present in them.AI is currently utilized for keeping up precise automated regional maps to react to real time, natural and catastrophe recuperation challenges.These assignments need close to continuous, precise, mechanized planning straight from aerial and satellite pictures.In this project, we apply Mask-RCNN and Conditional Adversarial Network techniques for extracting building footprint.The problem is viewed as a supervised learning problem.We try different things with learning parameters and algorithms, apply data augmentation, use transfer learning, utilizing RGB data and to accomplish high precision results.The resulting pipeline incorporates image pre-processing algorithms that permits it to adapt to input pictures of fluctuating quality, resolution and channels.
Topological Relational Learning on Graphs

Graph neural networks (GNNs) have emerged as a powerful tool for graph classification and representation learning. However, GNNs tend to suffer from over-smoothing problems and are vulnerable to graph perturbations. To address these challenges, we propose a novel topological neural framework of topological relational inference (TRI) which allows for integrating higher-order graph information to GNNs and for systematically learning a local graph structure. The key idea is to rewire the original graph by using the persistent homology of the small neighborhoods of nodes and then to incorporate the extracted topological summaries as the side information into the local algorithm. As a result, the new framework enables us to harness both the conventional information on the graph structure and information on the graph higher order topological properties. We derive theoretical stability guarantees for the new local topological representation and discuss their implications on the graph algebraic connectivity. The experimental results on node classification tasks demonstrate that the new TRI-GNN outperforms all 14 state-of-the-art baselines on 6 out 7 graphs and exhibit higher robustness to perturbations, yielding up to 10\% better performance under noisy scenarios.
A Discussion of Election Security, Cryptography, and Exceptional Access With Michael Alan Specter

Blakley: Welcome to episode two of Over the Rainbow, an IEEE podcast on the future of security and privacy.Today, Lorrie and I are very happy to have with us
Music Lessons: The Collège de France Lectures

"Music Lessons: The Collège de France Lectures." Music Reference Services Quarterly, 25(1), pp. 36–37