Reviewerly/exHarmony huggingface dataset:
A URL Shortening Service by Using Flask Framework Based on Base-62 Algorithm

In this paper, we have shown the importance of URL shortening at the time of sharing on various platforms. URLs appear to be long, unattractive, on most of the social platforms. They often get broken when shared on social media platforms like e-mail and short URLs can come in handy during these times. To shorten an Internet Long URL, we proposed a URL shortening service that will take a long Web URL/address and creates a shorter URL that will not break when we share on different platforms and make them more manageable by using flask framework base62 algorithm. In this paper, we have also provided a way that helps during digital marketing, social campaigning, and posting by giving the stats of the number of clicks made to the shortened URL as it shows the number of people interested in clicking the URL.
Implementation of The RAD Method to Build an Android-Based Garbage Recycling Application

Abstract:Garbage is a leading problem polemic that always exists in the surrounding environment, with the amount of garbage the more pollution that causes disasters, one of which is flooding. Garbage itself is divided into organic waste and non-organic waste. Organic waste itself can be processed into compost, while non-organic waste can be recycled, one of which is handicrafts. The purpose of this research is to create an android-based application that is used to provide information and procedures for recycling waste. The method used is RAD, namely planning, design, and implementation. The results obtained in this study are an application that contains information that can be used by the community in recycling waste.
Artificial Intelligence in Libraries and Users Satisfaction in Higher Institutions in Nigeria

The study adopted a correlational research design to find out the relationship between Artificial Intelligence in Libraries and Users Satisfaction in Higher Institutions in Nigeria. The study covered six higher institutions with twelve Departments in Nigeria. The population of the study comprises of 300 lecturers and 3, 200 students from twelve Departments of different levels. A random sampling technique was adopted and Krejcie and Morgan method was used to determine the sample size of 346. A selfdesigned instrument was used with a four point scale. Based on the findings of this study, it is concluded that there was high level of roles played by artificial intelligence in the delivering of libraries services and high level of satisfaction by the users of artificial intelligence in the libraries of higher institutions in Nigeria. Among other things, the study recommends that libraries should intensify efforts in adopting artificial intelligence in the delivery of libraries services for libraries users to gain very high level satisfaction.
Taekwondo Action Recognition Method Based on Partial Perception Structure Graph Convolution Framework

Action recognition in Taekwondo competitions and training is an important task, which can provide a very valuable reference factor for technicians, athletes, and coaches. We propose a graph convolution framework with part of the perception structure to recognize, decompose, and analyze Taekwondo actions. Taking advantage of the long short-term memory of a part of the perception structure, the recognized Taekwondo actions are marked in time series, and then features are extracted from the graph convolution level to obtain the spatial and temporal associations between joints. Predict the action category and perform score matching based on the manual tag database. Finally, it is verified on our self-made Taekwondo competition data set. Our method has an average accuracy of 90% in action recognition, and an average action score matching rate of 74.6%. The accuracy of action recognition is high, which provides great assistance to Taekwondo e training and competitions.
Task-based Evaluation of Sentiment Visualization Techniques

Sentiment visualization is concerned with visual representation of sentiments, emotions, opinions, and stances typically detected in textual data, for example, charts or diagrams representing negative and positive opinions in online customer reviews or Twitter discussions.Such approaches have been applied for the purposes of academic research and practical applications in the past years.But the question of usability of these various techniques still remains generally unsolved, as the existing research typically addresses individual design alternatives for a particular technique implementation only.This work focuses on evaluation of the effectiveness and efficiency of common visual representations for low-level visualization tasks in the context of sentiment visualization.More specifically, we describe a task-based within-subject user study for various tasks, carried out as an online survey and taking the task completion time and error rate into account for most questions.The study involved 50 participants, and we present and discuss their responses and free-form comments.The results provide evidence of strengths and weaknesses of particular representations and visual variables with respect to different tasks, as well as specific user preferences, in the context of sentiment visualization.
The Use of Code Switching in Responding to “Viral” Status on Instagram

The popularity of Instagram really affects Indonesian people which anyone can share their pictures, videos, or words as status.Some of the status become viral and make thousands of comments come in responding to the viral status.Indonesian people usually switch their language in their communication online and offline.The researcher is interested in analyzing the comments of Indonesian people in responding the viral status on Instagram.The data focuses on comments of two viral scandal status uploaded on Instagram that have code switching.The function of code switching such as lack of facility, lack of register, mood of speaker, to show identity with a group and so on are found in the comments under three kinds of code-switching: tag-switching, intersentential code switching, and intrasentential code switching.This findings indicates that Indonesian people will switch their language to express their minds as well as feelings and make variation in their language.
Exploration of the Path to Improve the Innovative Quality and Ability of College and University Students

The improvement of college and university students’ innovative quality and ability is necessary for colleges and universities to carry out the fundamental task of establishing moral education and cultivating innovative talents for the Party and the country. At present, there are several problems in the innovation of college and university students, including imperfect system and mechanism, incomplete integration of resources, insufficient understanding of themselves, and so on. In view of these problems, this study actively explores the path to enhance the innovative quality and ability of college and university students by improving the system and mechanism at the macro level, integrating resources to form synergy at the meso level, and motivating college and university students to engage in the process of ascending at the micro level.
Social education of students in the conditions of electronic learning

The purpose of the article is to analyze the essence of the process of social education in the process of transforming the ideas of elegiac. Methodology: the article presents analysis of social education at the university. An electronic survey among students made it possible to identify significant elements for social interaction and the student's realization as a qualified specialist in cyberspace. Results: the article reveals the socializing potential of constructive use of electronic, remote, information and communication technologies. Organization of social education process in the context of e-learning contributes to training of specialists who are ready to implement effective interaction in order to achieve personal and professional results.
Face and trust: A semiotic inquiry into influencers, money, and amygdala

After the cultural explosion of Web 2.0, digital culture reveals an apparently semiotic paradox associated with the incredibly widespread use of images of faces, while at the same time the reason to trust in the authenticity of these faces is constantly declining. This is because graphic technology has made the sophisticated manipulation of images both possible and easy. After a review of the existing semiotic models and considerations of trust, I am proposing a new approach which emphasizes the value-generating properties of trust by analogy with the money sign, seen as “trust inscribed”. Research from the neurosciences supports the hypothesis that the trustworthiness of the face is judged pre-reflexively and primordially. This, therefore, means that a trustworthy face is a premise for more successful communication than an untrustworthy one, notwithstanding the object of discussion and the cultural context. An example concerning social media influencers serves to show that in the internet-dominated globalizing culture, trustworthy faces are a multipurpose communicative asset that makes a difference.
Arrhythmia Classification Using Fractal Dimensions and Neural Networks

According to statistics, there has been a big increment in death in consequence of failures worldwide.Electrocardiogram was chosen as a possible implement for diagnosing cardiovascular diseases, it is a test that records the electrical activity given by the heart muscle and how it contracts.In this vein, our work is reported to analyze this low-cost and widely available signal.One of major issues that arise during the analysis of the electrical activity in the heart is noise reduction in electrocardiogram signals.The best bothersome noise sources have frequency components within the electrocardiogram spectrum.Thus, noises are difficult to take away using standard filtering procedures.Indeed, we show how wavelets can be used to denoise such signals.For this reason, electrocardiogram signal is considered as a selfsimilar object.As a result, fractal analysis can be used to make better use of the information gathered.The fractal dimension is considered the best explanation of the electrocardiogram signal that can account for its hidden complexity.This paper uses the fractal dimension to introduce a new technique for the simple classification of arrhythmias from electrocardiogram signals.We used neural networks to improve our classification results, as variety is one of the most active research and application areas for neural network
Geometry-Inspired Top-k Adversarial Perturbations

The brittleness of deep image classifiers to small adversarial input perturbations has been extensively studied in the last several years. However, the main objective of existing perturbations is primarily limited to change the correctly predicted Top-1 class by an incorrect one, which does not intend to change the Top-k prediction. In many digital real-world scenarios Top-k prediction is more relevant. In this work, we propose a fast and accurate method of computing Top-k adversarial examples as a simple multi-objective optimization. We demonstrate its efficacy and performance by comparing it to other adversarial example crafting techniques. Moreover, based on this method, we propose Top-k Universal Adversarial Perturbations, image-agnostic tiny perturbations that cause the true class to be absent among the Top-k prediction for the majority of natural images. We experimentally show that our approach outperforms baseline methods and even improves existing techniques of finding Universal Adversarial Perturbations.
Adjacency Maps and Efficient Graph Algorithms

Graph algorithms that test adjacencies are usually implemented with an adjacency-matrix representation because the adjacency test takes constant time with adjacency matrices, but it takes linear time in the degree of the vertices with adjacency lists. In this article, we review the adjacency-map representation, which supports adjacency tests in constant expected time, and we show that graph algorithms run faster with adjacency maps than with adjacency lists by a small constant factor if they do not test adjacencies and by one or two orders of magnitude if they perform adjacency tests.
DESAIN DAN IMPLEMENTASI RESTful WEB SERVICES UNTUK INTEGRASI DATA DAN APLIKASI

Industry (business) in the culinary field in Indonesia is a business that is experiencing very rapid growth. Improving the quality of service in a business will have implications for the maximum profit obtained. The right technology to connect various platforms is web services. Geprek Chicken Dinner management uses two different applications for its business processes. This of course hampers business processes and requires time and energy which causes business processes to be not optimal. Therefore, the purpose of research on the design and implementation of RESTful web services at Geprek Chicken Dinner. This research produces RESTful web services applications with access token and API key features as a security system with extreme programming development methods. the black box method involves auditors and IT experts getting successful conclusions from various types of tests. This application is expected to be able to serve as a base for all processed data and as a liaison between applications that will be used by management, so that the applications used are integrated with each other.
Two Stay Two Stray Strategy on the Students’ Reading Comprehension: The Effectiveness and the Students’ Perspectives

This study was aimed to find out the effectiveness of using Two Stay Two Stray (TSTS) strategy on the students' reading comprehension achievement of the first semester students of English department at Universitas Pamulang, and to know the students’ perspective in applying TSTS. A quantitative approach was conducted in this research by applying Independent T-test calculation. To obtain the data, the writers selected the sample comprised 60 students (30 students in experimental class and 30 students in control class) by having random sampling. The experimental class was taught by using Two Stay Two Stray (TSTS) strategy and the control class was taught by using conventional method. To collect the data, the writers used two kinds of instruments: a reading test and a questionnaire. These instruments were administered to answer stated research questions. A reading test was used to find out the effectiveness of TSTS strategy by SPSS calculation, and the questionnaire was distributed to find out the students’ perspectives in applying TSTS in reading activity. The research findings indicated the result of hypothesis based on Mann-Whitney U test the Sig 2-tailed value 0.019 &lt; 0.05 which means that the Null Hypothesis (H0) is rejected and Alternative Hypothesis (Ha) is accepted. Therefore, it can be inferred that the Two Stay Two Stray (TSTS) strategy has effectiveness in learning reading comprehension of the students. Furthermore, students assume that Two Stay Two Stray (TSTS) strategy is more enjoyable than the previous strategy (7.7%), they guess the main ideas of the text on the basis of pictures, charts or figures (7,4), and they understand my reading comprehension text before straying to another group (7.3%). Therefore, it shows the Two Stay Two Stray strategy shares the beneficial encouragement on the students reading comprehension.
Transfer Learning via Test-time Neural Networks Aggregation

It has been demonstrated that deep neural networks outperform traditional machine learning. However, deep networks lack generalisability, that is, they will not perform as good as in a new (testing) set drawn from a different distribution due to the domain shift. In order to tackle this known issue, several transfer learning approaches have been proposed, where the knowledge of a trained model is transferred into another to improve performance with different data. However, most of these approaches require additional training steps, or they suffer from catastrophic forgetting that occurs when a trained model has overwritten previously learnt knowledge. We address both problems with a novel transfer learning approach that uses network aggregation. We train dataset-specific networks together with an aggregation network in a unified framework. The loss function includes two main components: a task-specific loss (such as cross-entropy) and an aggregation loss. The proposed aggregation loss allows our model to learn how trained deep network parameters can be aggregated with an aggregation operator. We demonstrate that the proposed approach learns model aggregation at test time without any further training step, reducing the burden of transfer learning to a simple arithmetical operation. The proposed approach achieves comparable performance w.r.t. the baseline. Besides, if the aggregation operator has an inverse, we will show that our model also inherently allows for selective forgetting, i.e., the aggregated model can forget one of the datasets it was trained on, retaining information on the others.
Доказування у кримінальному провадженні на підставі електронних доказів

Dehtiarova O. Evidence in criminal proceedings on the basis of electronic evidence. The scientific article reveals the process of proving with the help of electronic evidence, their place among other sources of evidence (testimony, documents, physical evidence, expert opinions) is investigated. Evidence is a mandatory stage of the investigation and includes the collection, evaluation, verification of information, documents. Electronic evidence is digital objects that were a means or instrument of committing a criminal offense, preserved electronic and digital traces of a criminal offense, were the subject or object of a criminal offense. Signs of electronic evidence include: intangible form; created by man; the result of the information system; exists in the electronic network; research with the help of hardware and software; requires a special procedure for collection, inspection, evaluation; remote modification of electronic evidence and their removal. There is no official definition of electronic evidence in the criminal procedure legislation, the procedure for working with them is not regulated, which causes difficulties during the investigation and trial. The scientific article examines the opinions of scientists: D. Alekseeva- Pratsyuk, A. Antonyuk, P. Antonyuk, K. Bolgareva, M. Gutsalyuk, I. Kalancha, A. Kovalenko, O. Kozytska, O. Metelev, L. Pertsova-Todorova, V. Rusetska, O. Sirenko, A. Stolitniy, G. Tatarenko, D. Tatarenko, V. Khakhanovsky, V. Shkolnikov, who study the issue of proving criminal offenses with the help of electronic evidence. During the study of the use of electronic evidence, it was concluded that the development of a unified approach to the collection, investigation and use of electronic evidence with further enshrinement in regulations is a way to resolve inconsistencies and create conditions for investigators.
Feature Classification-Based Inclination Measurement for Industrial Assembly Platform

This paper proposed a method to realize inclination measurement for the industrial Internet of Things (IIoT) assembly platform by utilizing deep learning technology. Because the existence of inclination angle of platform will introduce slight damages to the products during the assembly process, our research group designed a system to tackle this problem by replacing the motion estimation algorithm with a classification mechanism. In other words, by classifying the image of the installation platform, it is capable to determine which inclination angle (image class) an input image belongs to. From the analysis of evaluation experiments, the proposed system for inclination measurement mechanism is proved effective when tackling the problems mentioned above. In addition, the proposed IoT system costs less computation power and achieves relatively higher measurement accuracy.
High School Students’ Foreign Language Vocabulary Acquisition in the Era of Artificial Intelligence

The development of artificial intelligence technology has a profound impact on foreign language teachers, learners, teaching mode and methods, the ways of evaluation, etc.In order to explore how much the artificial intelligence technology has influenced on foreign language vocabulary acquisition in classroom setting, the researcher implemented an experimental study between two classes in a high school.The results showed that the class using the artificial intelligence technology had outperformed the one using traditional word-formation vocabulary teaching in reading comprehension, gap filling and matching items.The study also proved that the application of artificial intelligence devices in classroom setting can make full use of learners' existing knowledge structure and promote their cognitive growth and information processing ability.The research simultaneously implicates that the existing application of artificial intelligence technology in foreign language teaching is far from satisfaction.The improvement of current situation needs the efforts from whom it may concern.
Document Marking System for Leak Investigations

This paper presents a confidential text documents leakage investigation system, focused on leak channels by documents printing and screen photographing. Internal intruders may print confidential document, take paper copy out of protected perimeter, make document image by scanner and perform anonymous leak. Also, intruders may take a photo of printed confidential document or displayed on workstation screen using personal mobile phone. Described leakage channels are weakly covered by traditional DLP systems that are usually used by enterprises for confidential information leak protection. Digital watermark (DWM) embedding is chosen as a document protection mechanism by implying changing of document image visual representation. In case of confidential document anonymous leak embedded DWM would enable the employee to determine what leak intentionally or by security protocol violation. System architecture consists of different type components. Employees’ workstation components provide DWM embedding into documents, which are sent for printing or displayed on screen. Information about watermark embedding is sent to a remote server that aggregates marking facts and provides it to security officer during investigation. Text document marking algorithms are developed, which embed DWM into printed and displayed on screen documents. Screen watermark is embedded into interline space interval, information is encoded by sequence of lightened and darkened spaces. DWM embedding into printed documents is implemented by three algorithms: horizontal and vertical shift based, font fragments brightness changing based. Algorithms testing methodology is developed in view of the production environment, that helped to evaluate the application area of algorithms. Besides, intruder model was formulated, system security was evaluated and determined possible attack vectors.