Reviewerly/exHarmony huggingface dataset:
Design Patterns of Vue.js 3

In Chap. 1 , we explained that framework design is the art of trade-offs, and there are trade-offs, such as the trade-off between performance and maintainability, runtime and compile time, etc. In Chap. 2 , we discussed several core elements of framework design in detail. Some elements must be considered by framework designers, while others are considered from the perspective of professionalism and improving development experience. Framework design pays attention to the control of the overall perspective. No matter how big a project is, there is a core idea and it is developed around the core. In this chapter, we will understand the design idea, working mechanism, and important components of Vue.js 3 from a global perspective. We can treat these components as independent functional modules and see how they cooperate with each other. In subsequent chapters, we will dive into each functional module to understand how they work.
Identification and Countermeasures of Network Defamation Crime: Present Situation, Supervision Status, and Criminal Applications

The network defamation crime presents a serious legal quandary in the digital age. This paper delves into the identification, supervision, criminal applications, and countermeasures of the network defamation crime. First, we clarify the constitutive requirements of the crime and propose a meticulous standard to balance freedom of speech with safeguarding individuals’ rights and interests. Second, we establish an effective onus of proof, thereby alleviating the plaintiff’s load and expediting the judicial process. Simultaneously, we emphasize combating false information to uphold the integrity of cyberspace and further explore the intricate impact of network environments’ anonymity and virtuality on evidence collection, as well as the balance between freedom of speech and individual rights. Finally, this paper puts forward the establishment of transnational cooperation mechanisms and the oversight of social media platforms as a comprehensive strategy to effectively tackle the global challenges in the network defamation crime and contributes valuable insights and suggestions for the wholesome development of cyberspace through detailed discussion.
THE DEEP NEURAL NETWORK-A REVIEW

Deep neural networks are considered the backbone of artificial intelligence, we will present a review of an article about the importance of neural networks and their role in other sciences, their characteristic, networks architecture, types, mathematical definition of deep neural networks, as well as their applications.
Developing chatbot simulations of patient interviews for history taking education

To develop a prototype chatbot which simulates a patient to allow dental students to practice history taking skills as part of the patient interview for treatment planning. An existing patient case used in the first year of the Doctor of Dental Medicine program at the University of Sydney was adapted as the chatbot patient on the Google Dialogflow platform. Chatbot design targeted a specific learning outcome – to familiarize students with the Sydney Dental School patient interview protocol via interacting with the chatbot patient, Pia Patel. The prototype was tested by a range of academics, both clinicians (general dental practitioners) and non-clinical academics, from which their documented feedback informed further development throughout a period of six months. The chatbot prototype of Pia Patel was successfully created, tested by academics and updated over a period of six months. A significant issue faced was programming the chatbot to respond consistently to the multitude of ways a single question can be asked. Overall feedback was generally positive, in terms of platform usability and authenticity of chatbot interactions. The use of chatbot patients in dental schools is an opportunity to improve foundational clinical skills through repeated exposure. The next steps include student trials of the chatbot to assess qualitative (feedback) and quantitative (student performance) data, the addition of more cases and the use of alternative platforms such as ChatGPT. Our results indicate the potential of artificial intelligence, particularly the usage of chatbots to improve student learning outcomes and subsequently patient care.
Unique factorization theorem for pure quantum states

In this paper we establish a unique factorization theorem for pure quantum states expressed in computational basis. We show that there always exists unique factorization for any given N-qubit pure quantum state in terms of the tensor product of non-factorable or ``prime'' pure quantum states. This result is based on a simple criterion: Given N-qubit pure quantum state in computational basis can be factorized as the tensor product of an m-qubit pure quantum state and an n-qubit pure quantum state, where (m + n) = N, if and only if the rank of the certain associated matrix is equal to one. This simple criterion leads to a factorization algorithm which when applied to an N-qubit pure quantum state factorizes that state into the tensor product of non-factorable or ``prime'' pure quantum states. This paper shows that for any given N-qubit pure quantum state the said factorization always ``exists'' and is ``unique''. We demonstrated our work here on a computational basis. PACS Number: 03.67.Mn, 03.65.Ca, 03.65.Ud
“Infogypsy” as a Destructive Phenomenon of the Modern Society

This article deals with the problem of the growing popularity of the phenomenon of “infocyganism”. The tasks, methods and target audience of this direction are presented. The issue of danger and harmfulness of marathons and courses of sellers of information products is considered.
KEMAMPUAN RAMAL SISTEM PERKIRAAN IKLIM MUSIMAN MENGGUNAKAN FENOMENA ENSO DI KABUPATEN LOMBOK TENGAH, NUSA TENGGARA BARAT

Lombok Island, particularly the southern central part of Lombok, often experiences droughts that result in failed cultivation or harvests due to the El Nino and Southern Oscillation (ENSO) phenomena. Therefore, the objective of this research is to determine the forecasting skill or predictive ability of a seasonal climate prediction system using the ENSO indicator in the Central Lombok regency, West Nusa Tenggara Province. This study employs a descriptive method by comparing the average rainfall in El Nino years with non-El Nino years. The research is conducted in the Central Lombok regency, which is divided into the northern and southern parts. The data used includes monthly precipitation recorded by BMKG for approximately 50 years (1970-2019) in all districts of Central Lombok. The SOI data is accessed at http://www.bom.gov.au/climate/current/soi2.shtml. The results of this study indicate that the use of the ENSO indicator to forecast seasonal rainfall patterns in the Central Lombok regency shows high consistency and significant predictive ability. There is no significant difference in the predictive ability and consistency of the forecast results between the northern and southern parts of Central Lombok. In general, the predictive ability during the dry season exhibits higher consistency (25%) compared to the rainy season (14%).
CHILD PROTECTION MEASURES ON BULLYING IN SPECIAL EDUCATION SCHOOLS

Bullying is a destructive social problem in schools that needs attention. Schools have the responsibility to create a safe place where students can learn without fear of being bullied. The purpose of the study was to explore child protection measures against bullying in selected special education schools in Luapula province. This study was guided by a Constructivist Paradigm, in keeping with the research paradigm, a qualitative intrinsic case study design was employed because the case study outcomes were intended to tell the researcher something that is solely about the case itself. In this case, the child with disability and special education school was of primary interest in the study. The sample size comprised of 38 participants consisting of 2 head teachers, 12 teachers, 12 parents and 12 learners from the two selected special education schools. Purposive critical case sampling was used to select head teachers, expert sampling was used on teachers and criterion sampling was used to select learners and parents. Data from head teachers and teachers were collected using a semi-structured interview guide and focus group discussions guide (FGD) were used on learners and parents. Data were analysed by thematic analysis. The study revealed that children with disabilities were protected from bullying in special education schools using the 3R’s (Recognizing, Responding and Reporting) bullying prevention strategies for learners with special educational needs. The findings established that Recognizing bullying prevention strategies included recognizing the statistics or acts of bullying in the school, recognizing the warning signs of victims and stereotypes of bullies and routine checking to stop harassment and bullying acts. The study also revealed that Responding bullying prevention strategies included holding meetings that reinforce positive behaviour expectations, providing guidance and counselling on how to respond to bullying, punishing learners using discriminatory language or derogatory remarks, formulation of anti-bullying programs, formation of support groups to sensitize learners, training staff members on how to recognizing incidents of bullying and teach anti-bullying social skills. Other strategies identified include the Reporting bullying prevention strategies which included reporting all forms of ill-treatment, reporting bullying incidence in school settings, reporting any form of harassment, and bullying acts. These bullying prevention strategies enabled the teachers in the school to protect learners with disabilities in schools. Based on these findings, the study recommends that the school should be on the lookout for incidences of bullying, respond to bullying quickly and effectively and document and report all actions taken when recognizing and responding to bullying.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0056/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
INDONESIAN EFL LEARNERS’ ERRORS IN IDIOMATIC EXPRESSIONS: TEACHERS’ &amp; STUDENTS’ PERSPECTIVES

&lt;p&gt;In an Indonesian setting, writing proper idiomatic expressions poses significant challenges for the majority of EFL students. Oftentimes, the idiomatic meanings deviate from the literal meanings and students are affected by their own first language and cultural contexts in usage. Therefore, this study explores the erroneous mistakes made by Indonesian EFL students and offers insights into teachers’ and students’ perspectives. This research will primarily examine the factors that influence university-level Academic Writing class students in incorrectly translating idiomatic expressions from the source language to the target language. The data for analysis was retrieved from students of Academic Writing classes from two different universities in West Java and Central Java to provide a comparative context in analyzing their mistakes. A comparative descriptive approach was applied, as this was deemed more appropriate for a study on semantic and translation strategies. The research results revealed that the study participants primarily experienced L1 interference, insufficient linguistic and grammatical knowledge, and a lack of lexical knowledge. Another obstacle was the students’ tendency to not heed cultural aspects in their writing and translating. Consequently, it is essential for EFL learners to be able to properly understand and translate idiomatic expressions in their writing to improve their target-language proficiency. Thus, instructors and students play crucial roles in successfully traversing this linguistic endeavor. Through proper instruction and active engagement, EFL learners can improve their linguistic mastery and cultural fluency, facilitating them to write more naturally in English.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0069/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
DISTANCE EDUCATION AND DIGITAL TECHNOLOGIES IN ADULT EDUCATION DURING THE COVID-19 PANDEMIC: VIEWS OF POSTGRADUATE STUDENTS IN HELLENIC OPEN UNIVERSITY, GREECE

Distance education has always been an important pillar of Hellenic Open University, through which undergraduate, postgraduate, and short programs’ students participate in. Before the pandemic crisis education in HOU had been characterized as synchronous and asynchronous with a choice of face-to-face classes. Under the new circumstances, due to the pandemic crisis, a lot of educational institutes all over the world had to adjust and offer a flexible synchronous and asynchronous electronic way of learning. This new, unprecedented situation came up as an emergency, as well as an opportunity, not only for the students, but also for the institutions so that they could evolve electronic distance education with the use of communication and collaboration online platforms. In this regard, HOU modulated the teaching in electronic form with the basic tool of teleconference for the group meetings and exams electronic platform. In this paper, there has been an attempt to research about the students’ satisfaction level, concerning the group meetings and exams changes, the main difficulties they dealt with, in which way their smooth attendance was influenced, and finally their agreement level about ways to reinforce their digital education in HOU with suggested ways deriving from literature. The conducted survey was quantitative out of 125 participants’ sample, with the use of a personal online questionnaire. It was found that the majority of participants had been satisfied with the changes in HOU, mainly with the communication they had with the counselor-teacher in online group meetings. Moreover, their attendance remained undisturbed, not only to their assignments, but also to their success in the exams, and regarding the difficulties they faced, their main ones were a feeling of stress or insecurity due to the unanticipated changes, a problem with their online connection and with the available time to answer the exams’ questions. It is also interesting their high level of agreement with the suggested ways to reinforce their digital education since the majority of the participants are in favor of those mentioned.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0099/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
THE STUDY OF PAST EMOTIONS AS A BASIS FOR EMOTIONAL EDUCATION IN MUSIC EDUCATION TODAY

The two main areas of focus in this paper are (a) the intense relationship between music and emotions and (b) the increasing interest in emotions in education and in many fields of social life over recent years. It is suggested that music could be used in music education and in general education in relation to emotional education. This is not a new idea but should be critically rethought in relation to the aims of emotional education as well as reflecting on the main way in which it conceals the social roots and power relations in the experience and expression of emotions. The basis of this consideration is a brief review of the study of the history of emotions so that emphasis is given to the fact that emotions are also a social product. It is the hope that by at least moving into the field of music education and making some proposals, teachers and students will be able to gain more free space to experience and express emotions.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0072/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
IMPLEMENTASI MODEL RELATING,EXPERIENCING,APPLYING,COOPERATING,TRANSFERING TERHADAP PENINGKATAN LITERASI SISWA SD

The low interest in reading students in Indonesia is also in line with the low interest in writing. Interest in reading and writing is actually a foundation for someone to be able to improve their literacy skills. Interest in reading and writing is actually a foundation for someone to be able to improve their literacy skills. The purpose of the study was to find out how the REACT model could be applied to improve the literacy of elementary school students. With this model, it can train students to develop literacy skills because in learning students are required to understand a concept based on the given problem relating it to the experience and prior knowledge of students. This research is a type of descriptive research using a qualitative approach. The subjects involved in this study were teachers and students of grade VI SD. Data collection in the study was carried out by interview, observation, and documentation methods. The data obtained in this study were then analyzed using qualitative descriptive analysis and focused on the stages of data reduction, presentation, and drawing conclusions. The results of the research analysis showed that the increase in student literacy showed a very good improvement with the REACT model by inviting students to read stories, create written works, analyze text content, describe analytical inferences on texts, criticize texts and present creatively. Where all these activities have been able to be followed well by students with the REACT approach, which is to directly relate students to meaningful learning experiences.
Pseudo-Boolean Polynomials Approach to Edge Detection and Image Segmentation

We introduce a deterministic approach to edge detection and image segmentation by formulating pseudo-Boolean polynomials on image patches. The approach works by applying a binary classification of blob and edge regions in an image based on the degrees of pseudo-Boolean polynomials calculated on patches extracted from the provided image. We test our method on simple images containing primitive shapes of constant and contrasting colour and establish the feasibility before applying it to complex instances like aerial landscape images. The proposed method is based on the exploitation of the reduction, polynomial degree, and equivalence properties of penalty-based pseudo-Boolean polynomials.
OSI Model

The International Organization for Standardization, better known by its abbreviation OSI Model, is an organization that establishes the fundamental communication protocols for computer networks. We refer to the OSI Model in multiple places since the problems fall into one of its seven models. The highest level of abstraction in the OSI architecture is the OSI Reference Model. The primary building sections used to create the network model are initially described in the release..
A SURVEY ON AIR WRITING CHARACTER RECOGNITION AND TRANSLATION

Computer systems are increasingly using airwriting recognition since it can be done quickly and intelligently. The term "air-writing acknowledgment apparatus" refers to the use of a stylus to draw an articulated character or expression in free space. This study presents a simple yet effective convolutional neural network-based air-writing recognition method (CNN). It is suggested to use a plausible algorithm tracking hands to reward air-writing circles captured through a web camera. This study provides a straightforward but efficient method for recognizing air-writing that uses deep convolutional neural networks (CNNs). With the aid of hand motions, users can write characters in the air that are subsequently translated into written text using an air writing character recognition and translation technology. Convolutional neural networks (CNN), which are trained to recognise and decipher human hand gestures, power this technology. The device uses a camera to record the hand movements and then runs the data through CNN to identify the characters being typed. The identified characters are then converted into text that may be presented on a screen using text-to-speech technology.
Multi Object Detection

Abstract: In the realm of computer vision, the ability to accurately detect and comprehend objects within images and videos is of paramount importance. This research is dedicated to advancing the field of object detection, a critical component of computer vision, with a particular focus on leveraging Convolutional Neural Networks (CNNs) to enhance accuracy. CNNs have revolutionized object recognition tasks, outperforming traditional methods like Viola-Jones, SIFT, and HOG. The study explores the underlying architecture of CNNs, elucidating how convolution, pooling, and flattening layers enable efficient image processing and object identification. Object detection holds immense practical significance, spanning applications such as autonomous vehicles, surveillance, and medical imaging. By delving into the intricacies of CNNs and their role in object detection, this research contributes to the ongoing evolution of computer vision, promising advancements in diverse sectors of industry and technology.
MONITORING AND REMOVAL OF FAKE PRODUCT REVIEW USING MACHINE LEARNING (ML)

The employment of Natural Language Processing (NLP) as a means for identifying and eliminating counterfeit products from a dataset is a significant endeavor. The current project employs a Machine Learning (ML) Algorithm to discern fraudulent customer reviews within a given dataset. The algorithm leverages predictive modeling techniques to estimate the authenticity of such reviews, and subsequently assess their validity. The prominence of product reviews as a critical determinant of consumer purchasing behavior in the realm of electronic commerce has led to a concerning escalation in the frequency of counterfeit reviews on websites and applications. It is imperative for the prominent Ecommerce firms to confront the issue of counterfeit product reviews, prior to engaging in the procurement of commodities from established entities. The utilization of this particular approach facilitates the rectification process concerning counterfeit product evaluations, thereby eliminating the prevalence of spammers. This proactive measure works to ensure that there is no potential compromise of trust among users of Ecommerce platforms. Through implementation of this initiative, the enterprise's administration can identify spurious evaluations and subsequently implement appropriate measures directed towards their resolution. The present model has been constructed employing the Naïve Bayes Algorithmic approach. By implementing the algorithm, it is possible to discern spam reviews from those that are legitimate, on websites or applications. To tally the individuals who engage in fraudulent online practices, a dataset is necessary. In our study, the "Amazon Academic Dataset" serves as the fitting reference point to prepare the model and can potentially increase the precision and adaptability of the results.
Merge, Explain, Iterate: A Combination of MHS and MXP in an ABox Abduction Solver

Minimal Hitting Set (MHS) is a well-known and complete method to compute all minimal explanations of an ABox abduction problem in Description Logics (DL). MHS is NP-complete and generally recognized as inefficient. We leverage on MergeXplain (MXP) which is fast but incomplete – by combining it with MHS in a hybrid algorithm MHS-MXP to regain completeness. In this paper, we describe: (a) the underlying theory to establish the completeness of MHS-MXP and show its relevant properties; (b) a class of inputs on which MHS-MXP has the greatest advantage; (c) an experimental implementation; (d) an empirical evaluation on both favourable and unfavourable inputs.