Reviewerly/exHarmony huggingface dataset:
PENDAMPINGAN KEGIATAN OLIMPIADE SISWA NASIONAL BIDANG KOMPUTER PADA SISWA SMA NEGERI 1 PRAMBANAN SLEMAN

The National Student Olympiad (OSN) is an academic competition held annually by the Indonesian Ministry of Education and Culture for high school students. As one of the public schools in Sleman, SMA Negeri 1 Prambanan always sends students to the OSN. Preparatory efforts are always made so that students can be maximised in participating in the OSN. The OSN mentoring activity for the SMA Negeri 1 Prambanan team in 2023, especially in the computer field, was held at the AKPRIND Institute of Science &amp; Technology computer laboratory. This activity aims to make students have an overview of OSN questions and the process of solving answers, especially programming questions. By discussing OSN material, the expected benefits include, among others, increasing student learning motivation. By understanding the types of questions and the process of solving them, students can feel more prepared and motivated to take part in the OSN. The mentoring was carried out with a training method by explaining the material and discussing OSN questions in 2022. The training material provided starts from basic computer theory, programming logic to programming material using the C++ language. The results of the activity, students have an overview of OSN questions and the process of solving answers, especially programming questions. Students' understanding, especially programming questions, increased and students' understanding of OSN questions and the process of solving answers, especially programming questions, can provide positive benefits for learning abilities and student achievement.
Analysis of the Influence of Parents Educational Level on Students Test Scores Based on Decision Tree

Under the background of the double reduction policy promulgated in July 2021 and the Peoples Republic of China Family Education Promotion Law promulgated in January 2022, improving family education and promoting home-school cooperation have become the focus of Chinas education reform and the key to improve the quality of students. The dataset of this paper comes from the Kaggle website. By using data visualization technology and ID3 algorithm of decision tree, the influence of various indicators on the accuracy of the decision tree prediction model is compared, and the relationship between parents education level and students test scores is further explored. The final results show that the education level of parents has a certain correlation with the test scores of children, and the students whose parents have higher education level generally have better scores.
Analysis of College English Phonetic Learning

Improving students speaking ability is one of the fundamental requirements for English teaching. However, some English majors have few chances in oral English learning and lack the motivation to practice phonetics, moreover, teachers may face challenges to teach them phonetics. Therefore, in order to discuss the problems in English phonetics teaching and improve the efficiency of it. This paper analyzes the current situation and problems of college students' phonetic learning by utilizing questionnaire investigation. The students attitudes, difficulties, methods of English phonetics learning are analyzed based on the linguistic. Furthermore, the corresponding teaching and learning are put forward. The investigation shows that nowadays, college students pay more attention to their English phonetics. There are three influence factors contributing to their dissatisfaction with it, including the negative influence of language transfer, low attention to English phonetics teaching, and lack of expertise in phonetics. Based on the analysis of these contributors, this paper purposes corresponding methods: Teachers should know the similarities and differences between English and Chinese in pronunciation, add English tests as a part of students English final exam, and colleges should conduct systematic phonetic training for English teachers.
Enhancing Cardiac MRI Segmentation via Classifier-Guided Two-Stage Network and All-Slice Information Fusion Transformer

Cardiac Magnetic Resonance imaging (CMR) is the gold standard for assessing cardiac function. Segmenting the left ventricle (LV), right ventricle (RV), and LV myocardium (MYO) in CMR images is crucial but time-consuming. Deep learning-based segmentation methods have emerged as effective tools for automating this process. However, CMR images present additional challenges due to irregular and varying heart shapes, particularly in basal and apical slices. In this study, we propose a classifier-guided two-stage network with an all-slice fusion transformer to enhance CMR segmentation accuracy, particularly in basal and apical slices. Our method was evaluated on extensive clinical datasets and demonstrated better performance in terms of Dice score compared to previous CNN-based and transformer-based models. Moreover, our method produces visually appealing segmentation shapes resembling human annotations and avoids common issues like holes or fragments in other models’ segmentation.
Clinical Trial Histology Image Based End-to-End Biomarker Expression Levels Prediction and Visualization Using Constrained GANs

The gold standard for diagnosing cancer is through pathological examination. This typically involves the utilization of staining techniques such as hematoxylin-eosin (H &E) and immunohistochemistry (IHC) as relying solely on H &E can sometimes result in inaccurate cancer diagnoses. IHC examination offers additional evidence to support the diagnostic process. Given challenging accessibility issues of IHC examination, generating virtual IHC images from H &E-stained images presents a viable solution. This study proposes Active Medical Segmentation and Rendering (AMSR), an end-to-end framework for biomarker expression levels prediction and virtual staining, leveraging constrained Generative Adversarial Networks (GAN). The proposed framework mimics the staining processes, surpassing prior works and offering a feasible substitute for traditional histopathology methods. Preliminary results are presented using a clinical trial dataset pertaining to the CEACAM5 biomarker.
Energy Efficient Approach for Virtual Machine Placement Using Cuckoo Search

Context: Virtualization technology has facilitated the entire cloud computing scenario it has manifested the computing environment in varied ways. It enables to create small instances which are provisioned for execution of user application. These small virtual instances are employed for perceiving the potential throughput. However, there arises a need for efficaciously placing the virtual machines providing services, thereby increasing the resource utilization. This placement of virtual machines to the tangible devices or the physical machine is known as Virtual Machine Placement Problem (VMPP). In VMPP numerous VMs are consolidated on fewer physical machines so as to have energy efficient computing. Problem: The problem is to design an optimized technique for resolving the Virtual Machine Placement Problem and achieve reduction in the power consumption and number of VM migrations without violating the SLA. Objective and Focus: To achieve and propose an effective solution for dynamic Virtual Machine Placement Problem considering initial allocation and reallocation. The primary focus is by employing meta-heuristic algorithm, and thereby obtaining the robust solution and achieving the associated QoS parameters. Method: The proposed method is inspired by the peculiar behaviour of cuckoos, where cuckoos search optimal nest for laying its eggs. An algorithm integrated with machine learning has been devised and evaluated with other meta-heuristic algorithms. Result: The proposed optimization algorithm effectively optimizes virtual machine placement and migrations. For instances of 50 to 500 virtual machines, the performance has been evaluated, where for 500 virtual machines, the power consumption is 55.0660916 kW, SLA-V is 0.00208696, and the number of migrations is 36. Conclusion: To sum up, the proposed optimization algorithm, when compared with two competent and recent meta-heuristic algorithms, exhibits exceptional performance in terms of power consumption, SLA-V, and several migrations. Thus, evaluation proves the strength of the proposed algorithm.
National Survey of Victimization: Another Trend-Crime Mapping Tools

The concept of the "dark figure" refers to the discrepancy between the actual occurrence of criminal activities and the quantity of reported incidents received by the criminal justice system, particularly law enforcement agencies. The term "dark figure of crime" pertains to unreported criminal incidents that are not captured inside the criminal justice system. Inclusion of these unreported crimes in official crime statistics would result in a significant amplification of the overall crime figures. To address the disparity between police records, namely police crime statistics, and the actual occurrence of crimes, many regions have initiated efforts to incorporate victims as the focal point of their investigations. In Indonesia, surveys of victims are generally carried out by private groups, and relate to certain types of crimes. The hesitancy exhibited by victims in reporting their experiences might provide challenges for law enforcement officials in their efforts to uphold societal stability. Victim surveys can extend beyond individuals who have directly experienced crime, encompassing tertiary victims (i.e., indirect victims) who harbour concerns about potential victimisation. Victim surveys can also be utilised to examine victims' perspectives within the complex framework of the criminal justice system, particularly in cases involving many victimisation incidents. Keywords: crime, survey, victims
Keypoint-Based Copy-Move Area Detection

Identifying which part of the image has been manipulated in real-world photo is a challenging research area. Generally, images are tampered using image editing tools to hide the information from pictures and to mislead people by providing wrong information intentionally. The authenticity of images becomes crucial to check for whether the image has been tampered before extracting meaningful information from images. In his paper, copy-move forgery area detection, one of several tampering techniques, has been presented based on identifying Scale-Invariant Feature Transform (SIFT) keypoints in an image. Preprocessing is done using fuzzy contrast enhancement. Features are extracted using SIFT algorithm and identical portions are clustered using Density-Based Spatial Clustering Application with Noise (DBSCAN) clustering. The experiments are performed on MICC-F220 dataset and results obtained are compared with other methods in the literature.
Studying the theoretical framework of organisational citizenship behaviour of teachers

Organisational citizenship behaviours are discretionary behaviours that go beyond one's official role and are intended to help others in the organisation or demonstrate devotion and support for the organisation. Organisational citizenship behaviours in the educational context in the study of Z. Donglong, et al. (2020) [1], there are other characteristics of lecturers. The 3 main tasks of university lecturers include research, teaching, and serving students. The quality of lecturer’s teaching and student service may depend on their enthusiasm, or willingness to participate, but these cannot be found in official job descriptions. Other tasks such as participating in department activities or spending private time with students are typical examples of off-duty behavior of lecturers. Therefore, university lecturers' organisational citizenship behaviours can be an important indicator for evaluating the quality of job performance. It is critical to understand the factors that motivate faculty to engage in activities beyond the requirements of their job role. Based on those studies, the author of the article has built a research model on factors affecting lecturers' OCB in the current context of educational innovation.
An Application-Oriented Review of Blockchain-Based Recommender Systems

Recommender systems (RS) have been around us since the beginning of the new age of technology, consisting of artificial intelligence, machine learning, the Internet of things (IoT), etc. The RS provides a personalized touch to the customers, thus helping them in decision-making. It also helps the business improve sales; hence, big tech companies like Netflix, amazon, etc. rely hugely on their RS to gain more sales. Many studies are focused on improving the accuracy of the RS but little on the security aspects of RS. Blockchain technology is the epitome of security and privacy. Hence, this research focuses on integrating blockchain with recommender engines and their advantages and challenges.
A Survey on Blockchain-Based Key Management Protocols

With the increased security benefits provided by blockchain, it has made its place in domains other than cryptocurrency, namely, Internet of Things (IoT), supply chain, health care, Unarmed Aerial Vehicles (UAVs), mobile ad hoc networks (MANETs), and what not. In today's technologically advanced world, cryptographic key management is an essential component of communication security. An efficient and secure key management is a challenge for any cryptographic system because an intruder could be present anywhere in the system. This paper has visualized a novel concept where blockchain-based different key management schemes have been studied across five domains and this is one of the first efforts in this manner. Several schemes have been proposed in the past and it is further being research upon because a particular scheme is not profound to every domain when it comes to security, performance, and scalability challenges.
Estimation Approaches of Machine Learning in Scrum Projects

It is impossible for a prosperous IT sector to avoid underestimating the amount of work, the amount of money, and the amount of time their projects would take. The introduction of Agile, (PBPM)principle-based process models, such as Scrum, brought about a substantial shift in the industry. This shift in culture proves to be extremely beneficial in terms of enhancing the collaboration that exists between the customer and the developer. In Agile development, estimation has always been difficult since requirements are subject to change. This motivates researchers to work on developing more accurate methods of effort estimation. The disparity between the amount of work that was estimated and the amount that was actually done. In this publication, a review was conducted of the work done by a large number of authors and potential researchers who were striving to close the gap between the real and estimated amount of effort. A thorough literature analysis led to the conclusion that machine learning models outperformed traditional estimation methods and methods that did not incorporate machine learning.
Content Moderation System Using Machine Learning Techniques

With the ever so growing internet, its influence over the society has deepened, and one such example is social media as even children are quite active on social media and can be easily influenced by it, social media can be a breeding ground for cyberbullying, which can lead to serious mental health consequences for victims. To counter such problems, content moderation systems can be an effective solution. They are designed to monitor and manage online content, with the goal of ensuring that it adheres to specific guidelines and standards. One such system based on natural language processing is described in the following paper, and various algorithms are compared to increase accuracy and precision. After testing the application, logistic regression yielded maximum precision and accuracy among the other algorithms.
Handwritten Digit Recognition for Native Gujarati Language Using Convolutional Neural Network

Computer vision's most active area of research is handwritten digit recognition. Numerous applications essentially motivate to build of an effective recognition model using computer vision that can empower the computers to analyze the images in parallel to human vision. Most efforts have been devoted to recognizing the handwritten digits, while less attention has been paid to the recognition of handwritten digits in resource-poor languages such as Gujarati is a native language in India mainly due to the morphological variance in the writing style. We used a CNN-based model for digit recognition and a Convolution Neural Network for classification in this paper to propose a customized deep learning model for the recognition and classification of handwritten Gujarati digits. This work makes use of the 52,000 images in the Gujarati handwritten digit dataset, which was made from a scanned copy of the Gujarati handwritten digit script. The proposed method outperforms the current state-of-the-art classification accuracy of 99.17%, as demonstrated by extensive experimental results. In addition, the precision, recall, and F1 scores were calculated to assess the classification's effectiveness.
The Research on Criminal Legislation of Cyber Violence

With the rapid development of the Internet, cyber violence occurs frequently, and the social harm caused by it cannot be ignored. In current practice, cyber violence cases are usually regulated by civil law and administrative law, but its regulatory effect on cyber violence that causes serious consequences is not obvious. In order to effectively control cyber violence, it should be regulated by criminal legislation, which is a more powerful means. This paper uses the research method of normative analysis to explain the dilemma faced by Chinas current criminal legislation to regulate cyber violence. Chinas existing criminal law provisions cannot be connected with cyber violence. Meanwhile, Chinas existing criminal legislation has many deficiencies in the regulation of cyber violence. This paper also analyzes the reasons why cyber violence needs to improve the regulation of criminal legislation. Thats because cyber violence has serious harm and other legal regulation means lack of regulation. Meanwhile, Chinas Current Criminal Regulation of Cyber Violence Started Late and is Difficult to Apply. In order to create a more secure,civilized and orderly cyberspace, this paper puts forward some suggestions for improving the path to solve this problem including the addition of judicial interpretation and the addition of cyber violence crime.
Intrusion into Computer Information System: Criminal Law Rule Based on Different Judicial Recognition Perspectives of State Affairs

Cybercrime refers to a new form of crime generated with the application and prevalence of computer technology. In China, there are increasingly more instances of unauthorized access to computer systems every year, which has severely affected network security and the property security of the people, and even national security. This paper delves deeper and more methodically into the problems surrounding the criminal act of unlawful access to computer information systems. The ambiguous definition and limited reach of the criminal object make Chinas punishment for unauthorised access to computer systems less effective., the crossover of the criminal law system caused by the contradiction of legislative logic, as well as the insufficient prevention of too lenient penalties. Based on the above legislative deficiencies, it is imperative to improve the criminal law system, expand the protection scope of the first clause of Article 285 of the Criminal Law, Increase the number of cases that are investigated and prosecuted, explain computer information systems in the context of state affairs, expand the definition of state affairs computer information systems, and strictly regulate the amount of crime that is legal. Additionally, it is essential to establish an independent status for data crimes by adding provisions on data security protection concerning the three major computer information systems; increasing the intensity of punishment, raising the range of statutory penalties, and adding property penalties, thereby imposing a comprehensive regulation on illegal intrusion into computer information systems.
Advertorial Chemie Ingenieur Technik 11/2023

Chemie Ingenieur TechnikVolume 95, Issue 11 p. 1684-1686 Advertorial Advertorial Chemie Ingenieur Technik 11/2023 First published: 24 October 2023 https://doi.org/10.1002/cite.202371106AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume95, Issue11Special Issue: Prof. Dr. rer. nat. Jörg Kärger zum 80. Geburtstag gewidmetNovember 2023Pages 1684-1686 RelatedInformation
Advertorial Chemie Ingenieur Technik 11/2023

Chemie Ingenieur TechnikVolume 95, Issue 11 p. 1687-1689 Advertorial Advertorial Chemie Ingenieur Technik 11/2023 First published: 24 October 2023 https://doi.org/10.1002/cite.202371107AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume95, Issue11Special Issue: Prof. Dr. rer. nat. Jörg Kärger zum 80. Geburtstag gewidmetNovember 2023Pages 1687-1689 RelatedInformation
Perspective Chapter: Using Augmented Reality (AR) in the Education of Medical Bioengineers

Augmented reality (AR) is a technology that combines the real world with virtual elements, providing users with an enhanced interactive experience. AR has been used in a variety of fields, including medicine and bioengineering. In terms of training medical bioengineers, augmented reality can play a significant role in improving the learning process and understanding of human anatomy, medical procedures, and medical devices. Using AR technology, medical bioengineers can benefit from the following advantages in their training: three-dimensional visualization and interaction, medical procedure simulation, real-time guidance, collaboration and communication, medical device innovation and development. Using these technologies in the training of medical bioengineers, they can practice and become familiar with performing these procedures in a safe and controlled virtual environment. This can help increase confidence and practical skills before working in real life.