Reviewerly/exHarmony huggingface dataset:
Image Specular Highlight Removal using Generative Adversarial Network and Enhanced Grey Wolf Optimization Technique

Image highlight plays a major role in different interactive media and computer vision technology such as image fragmentation, recognition and matching.The original data will be unclear if the image contains highlights.Moreover, it may reduce the robustness in non-transparent as well as glassy objects and also it reduces accuracy.Hence, the removal of highlights is an extremely crucial thing in the dome of digital image enhancement.This is to develop the enhancement of the texture in imageries, and video analytics.Several state-of-art methods are used for removing highlights; but they face some difficulties like insufficient efficacy, accuracy and producing less datasets.To overcome this issue, this paper proposes an optimized GAN technology.The Enhanced Grey Wolf Optimization (EGWO) technique is employed for feature selection process.Generative Adversarial Network is a machine learning (ML) algorithm.Here, two neural networks that will compete among themselves to produce better calculations.The algorithm generates realistic data, especially images, with great practical results.The investigational outcome reveals that the future algorithm has the ability to verify and eliminate the illumination spotlight in the image so that real details can be obtained from the image.The effectiveness of the proposed work can be proved by comparing the proposed optimized GAN with other existing models in highlight removal task.The comparison outcome gives better accuracy with 99.91% compared to previous existing methods.
DEVELOPMENT OF A USER AUTHENTICATION METHOD BASED ON KEYBOARD HANDWRITING

In this research paper, a study of user authentication by keyboard handwriting when entering a passphrase is performed. Based on the analysis and development of a mathematical function for the distribution of ""own"" and ""foreign"" areas, a module for filtering the author's input was created. To authenticate a user by keyboard handwriting when entering a passphrase, it is necessary to recognize the speed and dynamics of input (gaps between keystrokes and their retention). The time intervals between keystrokes and the period of keystroke hold allow us to characterize the user's handwriting on the keyboard quite unambiguously, which is confirmed by a number of experiments conducted during the study of user authentication features. In addition, the authentication method based on keyboard handwriting can be used to protect against fraudsters trying to gain unauthorized access to the system and for remote authentication when users are at a distance from the server. The results of the study and the developed software module can be used to create a hybrid access control system that combines two authentication methods - password and biometric. Thus, the final control system will provide an enhanced authentication procedure compared to classical password authentication. The keyboard handwriting authentication method has great potential for use in the field of cybersecurity and can be used as an effective tool to ensure system security.
Unusual Human Behavior Detection System in Real-Time Video Systems

Abnormal behavior detection, in terms of importance, has become a necessity in real-time visual systems.The main problem is the ambiguity in the difference between the characteristics of abnormal and normal behavior, which its definition is usually different according to the previous context of images.In this research, three approaches are used.In the first approach, a standard Convolutional Automatic Encoder (CAE) is used.After evaluation, it was found that the standard CAE problem is that it does not take into account the temporal aspect of the image frames sequence.The second method involves automatic encoding to learn the dataset's spatio-temporal structures.In the third approach, the complex LSTM cells are used for further improvement.The outcomes of the test display that the proposed methods have better performance compared to many of the previous conventional methods, and their efficiency in identifying abnormal behavior is very competitive compared to previous methods.
Query-Focused Multi-document Summarization Survey

With the exponential growth of textual information on the web and in multimedia, query-focused multi-document summarization (QFMS) has emerged as a critical research area.QFMS aims to generate concise summaries that address user queries and satisfy their information needs.This paper provides a comprehensive survey of state-of-the-art approaches in QFMS, focusing specifically on graph-based and clustering-based methods.Each approach is examined in detail, highlighting its advantages and disadvantages.The survey covers ranking algorithms, sentence selection techniques, redundancy removal methods, evaluation metrics, and available datasets.The principal aim of this paper is to present a thorough analysis of QFMS approaches, providing researchers and practitioners with valuable insights into the field.By surveying existing techniques, the paper identifies the challenges and issues faced in QFMS and discusses potential future directions.Moreover, the paper emphasizes the importance of addressing coherency, ambiguity, vague references, evaluation methods, redundancy, and diversity in QFMS.Performance standards and competing approaches are also discussed, showcasing the advancements made in QFMS.The paper acknowledges the need for improving summarization coherence, readability, and semantic efficiency, while balancing compression ratios and summarizing quality.Additionally, it highlights the potential of hybrid methods and the integration of extractive and abstractive techniques to achieve more humanlike summaries.
Towards Path Planning Algorithm Combining with A-Star Algorithm and Dynamic Window Approach Algorithm

In the Automated Guided Vehicle (AGV) warehouse automatic guided vehicle system, the path planning algorithm for intelligent logistics vehicles is a key factor to ensure the stable and efficient operation of the system.However, the existing planning algorithms have problems such as single designing a route and the inability to intelligently evade moving barriers.The academic community has proposed various solutions to these problems, although they have improved the efficiency and quality of path planning to some extent, they have not completely solved problems such as poor safety in planning, the high number of path inflection points, poor path smoothness, easily getting stuck in deadlocks, and have not fully considered the running cost and practical implementation difficulty of algorithms.To address these issues, the article deeply researched traditional A* scheme and Dynamic Window Approach (DWA) technology and proposed designing a route method according to the fusion of the A* algorithm and DWA technology.The algorithm improved the A algorithm by introducing a sub-node optimization algorithm to solve problems for instance poor global path planning safety and easy deadlock.Moreover, the algorithm reduced the amount of global route reversal locations and increased path consistency by improving the evaluation function and removing redundant points of the A algorithm.Finally, by integrating the DWA algorithm, the intelligent logistics vehicle achieved dynamic obstacle avoidance capabilities for moving objects in the real world.Our simulations-based results on MATLAB framework show that the algorithm significantly improves path smoothness, path length, path planning time, and environmental adaptability compared to traditional algorithms, and basically meets the path planning requirements of the AGV system for intelligent logistics vehicles.
Ensuring Information Security of Web Resources Based on Blockchain Technologies

This project examines how blockchain technology can enhance data security and reliability for web applications.In this article, ways to improve data security on online course platforms that utilize blockchain technology are explored.To clarify, online course platforms are web-based applications that enable users to access course materials online.These platforms often deal with sensitive data which, if compromised, can cause significant harm to users.Unfortunately, this information is often the target of fraudulent operations and illegal actions aimed at stealing personal data that can be used for authentication on various platforms.This article identifies the weaknesses of these sites and discusses the importance of using complex technologies to safeguard web resources effectively.This research explores how blockchain technology can protect from common web application attacks, which are often aimed at the user authorization process involving the transmission of identification and authentication data from the user to the website database.The study outlines the key components of blockchain technology, including hash function, hash value, data structure, and blockchain classification.Additionally, the study presents a transaction block model for a web course developed using blockchain technology.
Turn Taking Strategy Used by Donald Trump and Joe Biden in the First Presidential Election Debate 2020

This research investigated the turn taking strategies that occurred in the first American Presidential Debate in 2020 between Donald Trump and Joe Biden. The aim was to identify the kinds of turn taking strategies used in the first American Presidential Debate in 2020 between Donald Trump and Joe Biden, as well as to classify the functions of the turn taking that occur in the first American Presidential Debate in 2020 between Donald Trump and Joe Biden. The researcher employed a descriptive qualitative approach because the data were derived from Donald Trump's and Joe Biden's utterances on YouTube video, which was transcribed and analyzed using Sterntörm's (2014) theory of turn taking strategy; taking the turn strategy, holding the turn strategy, and yielding the turn strategy. The data were analyzed by determining the context, categorizing the data based on the theory, analyzing and interpreting the data, then draw conclusion based on the findings. The findings revealed 35 data from Donald Trump’s utterances, with the most strategy used was alert that occurred twelve times, while he never used hesitant start strategy. On the other hand, 20 data were obtained from Joe Biden’s utterances. In fact, Joe Biden also employed alert strategy as the most utilized strategy which was the same as Donald Trump, but the occurrence was only for five times. In addition, Joe Biden did not apply four turn taking strategies which were hesitant start, metacomment, silent pause, and appealing. One important point to note is that both candidates utilized alert as the most used strategy, which has the function to interrupt the other speaker with raising the tone of his voice in order to attract the attention of the interlocutor.
Development of Flip Book-Based Economics Teaching Materials To Improve The Economic Learning Outcomes of Students In Class Xi Man 2 Deli Serdang In Academic Year 2021/2022

The purpose of this study was to (1) determine the feasibility of flip book-based economics teaching materials in improving economic learning outcomes for class XI MAN 2 Deli Serdang students. (2) Knowing the effectiveness of flip book-based economics teaching materials in improving economic learning outcomes for class XI MAN 2 Deli Serdang students. This type of research is R &amp; D research using the Borg and Gall development model. The subjects of this study consisted of two material experts, one learning media expert, one learning model expert, and 60 students of class XI MAN 2 Deli Serdang. As an object in this study, students' responses to learning media and student learning outcomes tests. The results showed (1) the expert test of learning materials was in the very good classification (94.44%), (2) the learning media expert test was in the very good classification (96.00%), (3) the expert test of the learning model was very good classification (95.18%). Based on the results of the learning tests, it is known that the average value of the control class is 67.69 and that of the experimental class is 85, and the two classes have a difference in value of 17.7. The results of the submission of the hypothesis prove that (1) Flipbook-Based Economics Teaching Materials to Improve Economic Learning Outcomes of Class XI MAN 2 Deli Serdang Academic Year 2021/2022 are appropriate for use (2) there is a significant difference between student learning outcomes using flipbook-based economics teaching materials with the learning outcomes of students who use textbooks. This is indicated by the results of data processing on the results of the post test obtained tcount = 10.691. At a significant level (? = 0.05) with dk 58 obtained ttable = 1.167 so that tcount &gt; ttable. The average effectiveness of learning outcomes in the use of flipbook-based economics teaching materials is 85%, while the group of students who use textbooks is 68%. From this data it proves that the use of flip book-based economics teaching materials is more effective in increasing students' knowledge and competence in learning national income than without using flip book-based economics teaching materials
IMPLEMENTASI TEKNIK SEO (SEARCH ENGINE OPTIMIZATION) UNTUK OPTIMASI WEBSITE PENJUALAN DI LESTARI JAYA MEBEL

The background of this research is to help Micro, Small and Medium Enterprises (MSMEs) which need promotional media in the form of websites. Therefore the author has an idea to implement SEO (Search Engine Optimization). SEO (Search Engine Optimization) is a technique for improving a website in the search results of search engines such as Google, Bing, etc. SEO (Search Engine Optimization) is an important marketing strategy for increasing the visibility of a website and the number of organic visitors to the intended site. This research uses quantitative methods. Data collected by online survey and interview techniques. Toko Lestari Jaya Mebel has not been ranked optimally enough on search engines or search engines, with the implementation of SEO (Search Engine Optimization) techniques it is hoped that it can improve the website's position on search engines. So that the site can be easily found and compete with competitors, and is expected to increase sales.
Development of Interactive Learning Media In Basic Programming Subjects Based on Learning Management System (LMS)

Interactive Learning Media has a very important role in the process of teaching and learning activities (KBM) in schools, especially during a pandemic, where KBM activities must be carried out online (in a network). To streamline online learning activities are stored in the Learning Management System (LMS), which is a web-based software program for management, documentation, monitoring, reporting, administration and distribution of educational content, training programs, technical manuals, instructional videos or digital library materials, and projects learning and development. Interactive Learning Media is a multimedia-based tool that can describe messages or information from teacher to students in which active two-way communication occurs between multimedia and users (students) so that it can facilitate the online learning process. This study used the Multimedia Development Life Cycle (MDLC) method with six stages, namely: concept, design, material collecting, assembly, testing, and distribution. The research objective is to create interactive learning media for basic programming subjects using Articulate Storyline software. The results of designing learning media are in the form of a scom application that can be integrated into the school's Learning Management System (LMS) and can be accessed by students anywhere and anytime via a laptop or smartphone.
VISUALIZATION AS A MEANS OF INCREASING THE EFFICIENCY OF MASTERING THE COURSE OF ALGORITHMS AND DATA STRUCTURES

In the modern world, visualization of information plays an important role in all spheres of life, because visual information is perceived and assimilated much better than sound or text. The analysis of modern research made it possible to find out that the visualization of educational materials is one of the effective ways to improve the quality of education in universities. This issue became especially relevant after the transition of Ukrainian educators to distance education, which was initially caused by the COVID-19 pandemic, and later by martial law due to full-scale Russian aggression. Under such circumstances, teachers faced the need to find new forms of presenting educational materials to students. In order to increase the interest of future IT-specialists and improve the results of their mastering the "Algorithms and Data Structures" course, a software complex of dynamic data structures and algorithms visualization was developed.
The Implementation of Role Play-Learning Model to Enhance Understanding and Speaking Skills in English Among 11th-Grade Students at Ma Swasta Hubbulwathan Duri

Children prefer to communicate in Indonesian rather than English at home and at school, which is a challenge teachers face when teaching English. This research aims to help students of class XI at Hubbulwathan Duri Private MA overcome the challenges of learning English, specifically to improve their understanding of role-playing. The quantitative method that the authors use in this study considers the facts determining how to evaluate students for role-playing lessons in class. According to research findings, role-playing in class can motivate students to participate in their education actively. Applying the role-play learning model can improve students' English speaking skills by up to 20% and succeed with learning mastery reaching 75%. Furthermore, it can be concluded that applying the role-play learning achievement model can minimize students' speaking errors.
Metode Presentasi Lintas Kelas Berkelompok: Alternatif Pembelajaran Menulis Karya Ilmiah Siswa Kelas XI MAN Demak

One of the purposes of “Best Practice” is to describe a method of cross-class presentation in groups as an alternative in learning to write scientific papers for the senior students of MAN Demak in the academic year of 2017-2018. Besides that, “Best Practice” is also used to find out the results or impact of the implementation of the cross-class presentation method in groups as an alternative in learning to write scientific papers for the senior students of MAN Demak in the academic year of 2017-2018. The results or impact of the implementation of the cross-class presentation method are, a) increasing student interest and motivation, b) Increasing student teamwork, c) Increasing student critical thinking and problem-solving skills, d) Improving student communication, e) Increasing student self-confidence, f) Student work in the form of scientific writings.
Mining user's navigation structure by filtering impurity nodes for generating relevant predictions

Web Navigation Prediction (WNP) has been popularly used for finding future probable web pages. Obtaining relevant information from a large web is challenging, as its size is growing with every second. Web data may contain irrelevant noise, and thus cleaning such data is essential. In this paper, we emphasize the identification and elimination of noisy information from user-navigated web pages. The pruning of user browsed sessions by removing noisy webpages and their relations can help in the development of high-performing prediction models with fewer prediction errors. To minimize the prediction errors, we have proposed four pruning models namely PM3ER, PM3EN, PM3GI, and PM3EP which remove noisy web pages and their relations from the model consisting of varied simple and complex navigations. The study reveals that PM3ER is effective in prediction for websites with complicated structures resulting in complex navigations, and PM3EN is effective in predicting websites with a simple tree-like structure resulting in simple navigations. PM3ER has shown an improvement in predictions by up to 3% whereas PM3EN has attained improvement up to 5.45%.
A new method to improve the efficiency and accuracy of incremental singular value decomposition

Singular value decomposition (SVD) has been widely used in machine learning. It lies at the root of data analysis, and it provides the mathematical basis for many data mining techniques. Recently, interest in incremental SVD has been on the rise because it is well suited to streaming data. In this paper, we propose a new algorithm of incremental SVD that is designed to improve both efficiency and accuracy during computation. More specifically, our proposed algorithm takes advantage of the special structures of arrowhead and diagonal-plus-rank-one matrices involved in updating SVD models to expedite the updating process. Moreover, because the singular values are computed independently, the proposed method can be easily parallelized. In addition, as this paper shows, increasing rank can lead to more accurate singular values in the updating process. Experimental results from synthetic and real data sets demonstrate gains in efficiency and accuracy in the updating process.
Matt Frisbie on Browser Extensions

In Episode 552 of “Software Engineering Radio,” Matt Frisbie, author of Building Browser Extensions, speaks with host Kanchan Shringi about browser extensions and where they’ve been successful. They examine tools for building extensions and applicaton programing iterfaces they use, cross-browser compatibilities when developing extensions, preventing security vulnerabilities, and emerging platforms and possibilities. We provide summary excerpts below; to hear the full interview, visit http://www.se-radio.net or access our archives via RSS at http://feeds.feedburner.com/se-radio. —Robert Blumen