Reviewerly/exHarmony huggingface dataset:
Cyber Crime and Cyber Law’s In India: A Comprehensive Study with Special Reference to Information Technology

The rapid evolution of information technology has brought about significant advancements in various sectors, but it has also given rise to new challenges, particularly in the realm of cyber security. This study aims to provide a comprehensive overview of cybercrime and cyber laws in India, with a special emphasis on the Information Technology Act, 2000. The research begins by defining cybercrime and elucidating its various forms, including hacking, identity theft, phishing, and other malicious activities conducted in the digital domain. A detailed examination of the cyber threat landscape in India is presented, highlighting the increasing frequency and sophistication of cyber-attacks and their impact on individuals, businesses, and the government. The study then delves into the legislative framework governing cyber activities in India, primarily focusing on the Information Technology Act, 2000, and its subsequent amendments. It explores the legal definitions of cybercrimes, jurisdictional issues, and the powers conferred upon law enforcement agencies to investigate and prosecute offenders. Special attention is given to recent legal developments and case studies that illustrate the application of cyber laws in real-world scenarios. Furthermore, the research scrutinizes the role of government agencies, such as the Cyber Crime Cells, in combating cyber threats and promoting cyber security awareness. The study also assesses the effectiveness of international collaborations and treaties in addressing transnational cybercrimes, considering the borderless nature of cyber threats. The research investigates the role of Information Technology policies, standards, and best practices in India. It analyses the measures adopted by organizations to safeguard their digital assets and sensitive information, highlighting the importance of cyber security awareness and education. The study synthesizes the findings to provide recommendations for strengthening the existing cyber laws, enhancing cyber security infrastructure, and fostering a collaborative approach among stakeholders to mitigate the challenges posed by cybercrime. The research aims to contribute to the understanding of the dynamic landscape of cyber threats in India and serve as a valuable resource for policymakers, legal professionals, and academia involved in the field of information technology and cyber security.
A Novel Approach for Detecting Outliers by Using Isolation Forest with Reducing Under Fitting Issue

The effectiveness of machine learning for a particular activity depends on a variety of parameters. The incident database's description and validity come first and primary. Information retrieval even during the training cycle is more challenging if there is a lot of repetitious, unimportant information or incomplete information available. It is good knowledge that running time for ML tasks is significantly impacted by conditions as follows and sorting stages. To increase the accuracy of any model data cleansing is essential. Without sufficient data scrubbing, no predictive model accuracy can begin. EDA, or exploratory data analysis, is the name of this procedure. In this study, we discussed outlier identification, one of many EDA processes for complete perfect data. In this research, we attempted to use the isolation forest approach to calculate the outlier factor. Then a model known as an outlier finding model is created. The problem of outlier detection leads to a collection of connected supervised learning for binary classification. We carry out in-depth tests on various datasets and demonstrate that in our latest outlier finding technique compare with the old way. Our approach yields superior outcomes in terms of accuracy, precision, recall &amp; F-1 score. Additionally, we successfully lowered the machine learning algorithms' under fitting issue.
Training In Writing Abstracts of Scientific Works at Jam’iyah Mahmudiyah Islamic High School (STAI-JM), Tanjung Pura, Langkat District

Jam'iyah Mahmudiyah Islamic College (STAI-JM) is located in Tanjung Pura, Langkat district, which has five fields of study. At this high school there has never been any training in writing scientific works, either from within the high school itself or from outside the school. One form of writing scientific works is writing abstracts. An abstract is a short summary of scientific work (such as a thesis, dissertation, or research article). The abstract is a very important part of writing scientific works. The abstract form can be packaged nicely and attractively, so that readers can understand the entire contents of the research. The aim of the community service team (PKM) program activities is to practice writing abstracts of scientific work so that students are able to create abstracts from the results of their research briefly, clearly and measurably. The approach used is to collaborate with partners, the Government and STAI-JM teaching staff with training activities and mentoring methods for writing abstracts of scientific papers. This training was considered successful in increasing partners' knowledge and skills in writing abstracts.
Argumentation Mining System for Corpus-based Discourse Analysis based on Structured Arguments

An Argumentation mining system can analyze a large volume of text data through a variety of sources. Nowadays it is highly useful in the areas of business, economics, and finance with digital marketing being the most promising field along with social media. It is the study of corpus-based discourse analysis that involves the automatic identification of argumentative structure in text. Initially, AM talks about extracting structured arguments from natural text, often unstructured or noisy text. Theoretical approaches of AM and pragmatic schemes that satisfy the needs of social media generated data, recognizing the need for adapting more flexible and expandable schemes, capable of adjusting to argumentation conditions that exist in social media. In this scenario it is a very challenging argumentation scheme able to identify the distinct sub-task and capture the needs of social media text, revealing the need for adopting a more flexible and extensible framework. Corpus-based Machine Learning of linguistic annotations has enabled researchers to identify repetitive linguistic patterns of language use and to uncover hidden meaning in all areas of Natural Language Processing.
"Sukhomlinsky’s Practical Innovation and Enlightenment to School Labor Education"

Read Sukhomlinsky’s articles on labor and labor education, consult his important discussion on the status, value and organization of labor education, and find that Sukhomlinsky put forward in the teaching practice of labor education in primary and secondary schools that education should be combined with all-round development, that students should be promoted in collective labor, that long-term extracurricular group activities should be carried out, and that professional teachers should be equipped. At present, labor education in primary and secondary schools in China can learn from the practical enlightenment of Sukhomlinsky, such as labor education should be combined with production and all-round development, pay attention to collective, long-term and according to local conditions, and pay attention to multi-channel specialization to promote the construction of teachers. Sukhomlinsky’s exploration in labor education has the role of leading labor education practice, in the new era of China’s primary and secondary school labor education, seriously study Sukhomlinsky’s labor education thought content, China’s primary and secondary school labor education is still of practical significance.
Improving Cybersecurity Awareness and Basics in Vocational Education and Training

Vocational Education and Training (VET) are oriented to achieving skills and teaching of knowledge related to a specific occupation or vocation in which learner will participate. It is done at an educational institution, as part of secondary or tertiary education, or within initial training during employment, (as a combination of formal education and workplace learning). Digital transformation has introduced new business opportunities for companies, but at the same time also new risks. Cybersecurity is a big concern for companies, especially for small and medium-sized enterprises (SMEs) that are much more vulnerable, first of all from their organization, not having an internal IT department that also deals with security, on the other hand part of the lack of necessary skills, their staff and management not being used to face cyber risks and giving us attention to this sector. It is essential that SME management understands the need to put in place appropriate IT security policies and provide adequate staff training. It is known that technology as well as cyberattacks evolve rapidly more than people and organizations were aware of. Therefore also, within VET it is necessary that educators/trainers and students are equipped with cybersecurity awareness and have some cybersecurity basic knowledge about reasons why cyberattacks happen and tools to act against them. Results show that the education sector is leading when it comes to suffering cyberattacks (July 2022 to August 2022). It means that the education sector of a country needs more protection and knowledge in this context. This article is based on the experience of the authors within the Erasmus+ project “InCyT - Interdisciplinary Cyber Training.”
Augmented Reality (AR) Application Usage Training to Improve Teacher Digital Literacy at SMP Negeri 1 Jeneponto

SMPN 1 Jeneponto get help a total of 63 Gadget Units (Tablets) brands evercoss from government with goal to get used by internal teachers learning. However Not yet utilized with ok. this because internet network at school the No support and digital literacy teachers greatly low. Solution from problem the is increase teacher 's ability deep digital literacy utilization of Gadgets (Tablets) for learning media both offline and online with implementing Augmented Reality (AR) for optimizing Gadgets (tablets) as learning media in form activity training and mentoring. Activity results training This is there is enhancement about understanding importance teachers' ICT literacy and understanding of AR as a learning medium innovative by 95.6%. Enhancement Teacher's Digital Literacy is 87% and deep teacher skills using AR of 78.2%. This result proves that existing training and mentoring can increase teacher digital literacy at SMP Negeri 1 Jeneponto. Through activity, it is expected that the teachers are up to date on development technology and make an effort to increase one of them is professionalism through understanding Digital Literacy and implementing it in activity learning
Unmanned Aerial Systems as a Driving Force in the Digital Information Age

Unmanned Aerial Systems (UAS), while no longer viewed as a disruptive technology, are still in their infancy regarding how this form of technology fits within the digital information age. This commentary review examines the history of UAS technology and how the rapid growth of UAS driven primarily by hardware in the form of centralized controllers, IMUs, and GPS, getting smaller, lighter, and cheaper. While the growth of UAS demonstrates itself as an outcome of the modern digital age, we argue that it now has the potential to drive the information age forward in four primary areas: cloud-based technology, Internet of Things, Artificial Intelligence, and Big Data.
One (innovation) flew over the law’s head: The intersection of artificial intelligence and copyright

This article analyses South African copyright laws, with reference to artificial intelligence (AI). It deals specifically with the authorship of copyrightable works as contained in the Copyright Act 98 of 1978. The Act provides that authorship vests differently, depending on the type of work in question ie a work recognised by s 2 of the Act. The article seeks to provide insight into the existing jurisprudence surrounding AI and copyright in the South African context. Moreover, it relies on prevailing local jurisprudence to show that South Africa may lack an adequate legal structure to tackle the future implications of conferring authorship on non-human entities. The article also briefly explores resolutions in other regions such as China and draws on Ginsburg’s legal tests for authorship. The article’s focus is primarily on South African law in its current state, with reference to other legal jurisdictions and the future.
Shifting digital media ecologies and how copyright law should adjust and adapt to journalism

Digital Age misappropriation and plagiarism of published online news content by some South African media proprietors are negatively affecting professionalism and integrity in journalism. Such infringements invariably lead to great tension, harmful competition patterns and dwindling revenues. Frequently, digital news misappropriation creates factual distortions, impairing the democratic functions of journalism and healthy national discourse motivated by legitimate public interest considerations. A 2019 Reuters Institute Digital News Report revealed that, globally, South Africans spend the greatest number of hours browsing online, with 36% of the population enjoying sharing news content, while 40% enjoy commenting on news via social media or news websites. While the Digital Age has generated many forms of active players in journalism, this paper is limited to digital infringement conflicts and contestations between accountable and established media proprietors or competitors. This qualitative contribution proposes that media proprietors collectively seek an alternative dispute resolution approach to copyright infringements through a comprehensive ‘Media Arbitration Copyright Infringements Code’ with incorporated ‘Hot News Misappropriation Doctrine’ provisions to regulate the conduct of the media and to address proliferating digital infringements. The Media Code should also guide the proposed ‘Media Copyright Tribunal’ operating within a commercial arbitration framework in dispute adjudication and resolution. This paper argues that the Media Code with the Misappropriation Doctrine is a more viable approach for addressing media copyright disputes because it largely protects facts contained in published news content. Furthermore, a Media Code that is drafted addressing media copyright digital infractions using the ethical benchmarks set by the ‘Press Code of Ethics and Conduct for South African Print and Online Media’ editorial guidelines interpreted through a flexible informal commercial arbitration framework that expedites dispute resolution is desirable. This paper is largely concerned with the court’s findings in Moneyweb (Pty) Limited v Media 4 Limited and Another, and the fact that it took about three years for the dispute to be resolved. Moreover, this paper argues that the current Copyright Act 98 of 1978 is less effective in dealing with the ethical quandary faced by journalism in the Digital Age.
Training on Utilization of Based Learning Media Virtual Reality for City Science Teachers Jeneponto

Activity devotion to community (PkM) aim to: (1) provide introduction to science teachers at Jeneponto Junior High School regarding Virtual Reality learning media as an alternative learning media IT based, and (2) to train science teachers at Jeneponto Junior High School For capable use learning media based on Virtual Reality. Activity done with method training carried out during 3 stages, stage First training related introduction to various learning media used in accordance with development Revolution Industry 4.0 is one of the media used as a learning medium based on Virtual Reality. Training stage two with material about training use of learning media Deep Virtual Reality based learning as well as stage third do evaluation and strengthening. Activity training carried out responses positive of the teachers indicated with enthusiasm during activity as well as attitude positive for applied learning media Deep Virtual Reality based activity learning in accordance with development technology Information in the Age of Revolution Industry 4.0. The training participants were very interesting and enthusiastic in participating in the training activities. Participants also gain knowledge, skills and motivation by using Virtual Reality-based learning media. Participants responded positively to training activities and were able to apply various learning media in the learning process so as to improve the quality of learning.
3D Printing Basic Knowledge and Skills Training for Teachers of SMAN 2 Palopo

3-Dimensional printing is a manufacturing technique used to create 3-dimensional products. The tool used is a 3D printer with constituent materials such as plastic, metal and powder. This community service activity uses a 3D printer made from plastic because it is considered more practical and effective for laboratory scale. The training participants were teachers at SMAN 2 Palopo, with the presenters being lecturers at Cokroaminoto University, Palopo. The aim of this community service activity is to introduce and provide training to SMAN 2 Palopo teachers in using 3D printer machines. The training participants provided basic material: using a 3D printer machine, how to install the tool, create a design, transfer the design file to the printer, and so on printing the 3D design. The evaluation process is grouped into four categories, namely understanding the concept, installation and use, machine maintenance and desire for further study. Participants' understanding increased by 1.7 points after attending the training. In the skills of installing and using and maintaining machines, the participants' pretest scores were quite low (1.8 and 2.1 points respectively) and increased quite sharply by 2.5 and 2.1 points after training. Meanwhile, the pretest score for wanting to know 3D printing technology reached 3.4 points and increased after participating in the training to 4.5 points. The evaluation results show that 3D printing technology is not yet well known by the public, especially educational institutions. With this existing training, it is hoped that teachers at SMAN 2 Palopo will be able to know and master 3D printing technology which was developed according to their respective knowledge. Furthermore, these skills can be taught to students through seminars, extracurricular activities or can be included in curricular learning materials.
Interpretability machine learning models: A critical analysis of techniques and applications

In the rapidly evolving landscape of machine learning, the demand for interpretable models has become paramount to ensure transparency, accountability, and user trust. This review paper critically examines various techniques and applications associated with interpretable machine learning models. The burgeoning complexity of black-box models, such as deep neural networks, has underscored the need for understanding and explaining model decisions, especially in domains where critical decisions impact human lives, such as healthcare, finance, and criminal justice. The paper begins by exploring the motivations behind the surge in interest in interpretable machine learning, elucidating the challenges posed by inherently opaque models. Subsequently, it provides an in-depth analysis of popular interpretable model techniques, ranging from traditional linear models to modern approaches like LIME (Local Interpretable Model-Agnostic Explanations) and SHAP (SHapley Additive ex Planations). By dissecting the strengths and limitations of each technique, the paper aims to empower practitioners and researchers to make informed choices based on their specific use cases and requirements. Furthermore, the review delves into real-world applications where interpretable models play a pivotal role. Examples include healthcare diagnostics, where the interpretability of a model's decisions is crucial for gaining the trust of medical professionals and ensuring patient safety. Similarly, in the financial sector, interpretable models aid in risk assessment and regulatory compliance. The paper critically examines these applications, shedding light on instances where interpretable models offer tangible benefits over their opaque counterparts. The review also addresses the ongoing challenges in the field, such as the interpretability-accuracy trade-off and the need for standardized evaluation metrics. It emphasizes the importance of developing universally accepted benchmarks to objectively assess the interpretability of different models. Moreover, the paper discusses emerging trends and future directions in interpretable machine learning, including the integration of domain knowledge and the incorporation of interpretability as an integral part of the model development process.
The impact of computer vision on home security

Artificial intelligence and machine learning are subfields of computer vision. Its goal is to assist computers in seeing and comprehending the content of digital photographs. In this paper we are proposing a system which will detect a person at the main gate of the property. The gate will automatically open if the system recognises the person (i.e., if the person is known by the house owner). Otherwise, information will be sent via email to the house owner, who will decide whether or not to unlock the gate. If the house owner does not answer within a certain amount of time, we will collect personal information such as a phone number and transmit it to the owner for future use.
Quantum machine learning: A theoretical overview of quantum computing applications

Quantum computing has demonstrated remarkable prowess in addressing factorization issues and unordered search problems, showcasing its quantum parallelism capabilities that enable exponential speed-up for specific computational challenges. However, the seamless integration of classical and quantum computing to harness accelerated computation speed presents unique challenges. This paper delves into the intricacies of this integration, focusing on the current state of quantum machine learning (QML) and evaluating the performance of classical and quantum algorithms in terms of accuracy. To address these challenges, we conducted experiments utilizing three datasets for binary classification, implementing both classical Support Vector Machine (SVM) and Quantum SVM (QSVM) algorithms. Our investigations reveal that the QSVM algorithm consistently outperforms its classical counterpart on complex datasets. Notably, the performance gap between quantum and classical models widens with increasing dataset complexity, shedding light on the susceptibility of simple classical models to overfitting when confronted with intricate datasets.Despite the ongoing development required for quantum hardware with ample resources, our findings underscore the significant potential of quantum machine learning, particularly in unsupervised learning and generative models. As we move forward, it is imperative to channel more efforts into exploring novel quantum learning models capable of harnessing the inherent power of quantum mechanics to overcome the constraints of classical machine learning. This research contributes to the ongoing discourse on the future of quantum computing, emphasizing the need for continued exploration and innovation in quantum machine learning methodologies.