Volume 12 | Issue 11 |

 Abstract

Artificial intelligence is the ability of a system to understand and interpret external data through algorithms or machines or systems to solve problems. This AI term is used for knowledge based system, text mining, pattern recognition, language processing, natural language, decision making and knowledge based system etc. Today it is being used in environment, defense, technology and security. This article attempts to understand the opportunities and challenges of AI. It focuses on policies that are designed to ensure the development and deployment of AI-based systems.

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 Keywords

AI, Challenges, Opportunity, Abuse, Law

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Due to the development of modern technology, academic cheating, and plagiarism have become a serious issue in the education systems of almost all countries. Students can easily access information from the internet and using it without acknowledging the source and harming the reputation of academic institutions. AI tool is promoting high tech plagiarism violating the established rules and regulation governing academic dishonesty. Cheating could be the result of cooperation between student, teacher and administrators; therefore universities should initiate major changes in the examination management process. Cheating and plagiarism shifts the focus of teachers and students away from learning behaviour so the secure hosting of exams, automatically identifying cheating in assessments, and preventive measures like punishment and supervision should be ensured. In this article, the role of technology in the detection and prevention of cheating and plagiarism is highlighted.

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 Keywords

Index term: Higher education, Cheating, Plagiarism, Artificial intelligence, Technology.

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Cissus quadrangularis and Bryophyllum pinnatum, members of the Crassulaceae family, are notable for their medicinal properties and diverse applications in traditional medicine. This paper explores the pharmacological activities, chemical composition, and therapeutic potential of Bryophyllum pinnatum, highlighting its roles in treating conditions such as kidney stones, diabetes, and various wounds. The paper delves into the herb's Ayurvedic properties, detailing its actions, doshaghata, and efficacy against specific diseases, alongside its morphological characteristics. The investigation further assesses the plant's antileishmanial, anticancer, anti-diabetic, anti-ulcer, and antihelmintic properties, supported by experimental studies. Despite the promising results, the necessity for further research and clinical validation is emphasized to enhance understanding and integration of Bryophyllum pinnatum in contemporary medical practices. This comprehensive review of Bryophyllum pinnatum underscores its potential as a valuable herbal remedy, while also addressing the need for standardization and clinical assessments to ensure safety and efficacy in therapeutic applications.

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 Keywords

Antihelmintics ,Bryophllum pinnatum, Taxonomy,Triterpenoids, Glycosides, Xeromorphic, Vata and kapha

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Abstract The Core-Periphery Model is a theoretical framework used to describe the uneven distribution of economic activities and development within a region. This model highlights how core areas become centers of economic growth and industrial activity, while peripheral areas remain less developed and dependent on the core for resources and opportunities. In the context of the Upper Subarnarekha Basin, located in Jharkhand, the model is useful for analysing how economic activities are concentrated in urban and industrial hubs, while surrounding rural and tribal areas experience slower development. This study examines the core-periphery dynamics in the Upper Subarnarekha Basin by analysing the spatial distribution of resources, infrastructure, and economic activities between urban centers (core) and rural areas (periphery). The objective is to understand how these dynamics contribute to socio-economic disparities and environmental changes in the region.

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 Keywords

Core-Periphery Model, Development, Resource, Opportunities, Economic growth.

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Forensic medicine can be defined as forensic pathology and forensic science. It is the use of medicine in support of the law. The role of forensic medicine in the process of crime detection cannot be overlooked because it gives the law enforcement agency a detailed picture of the events which led to the trauma, death and any other medical concern related to crime as soon as the personnel is on the crime scene. Forensic medicine and genetics forming a new emerging focus a new emerging focus also give witness to some of the most cutting-edge progress in crime in the modern world with the criminals' impunity being brought to an end. There are also expectations to technological developments in the future that will require careful assessment as to how far the ethics of science can be stretched. Another essential aspect of the above is that if evidence is handed over in any litigation case, no document or object handed over should before the completion of the case process leave any person's possession without any proper documentation including a detailed explanation and why it was withdrawn to preserve its authenticity and admissibility in court. Privacy issue: Genetic information contains sensitive moral issues involving the problem consent, data security and improper expectations regarding the collection, preservation and utilization of DNA which are sources to be neglected in ones jurisdiction. This is about the law in every jurisdiction, Laws vary in how they prescribe the manner of collection and retention of DNA.

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 Keywords

Forensic Genetics, DNA Profiling, Privacy Concerns, Informed Consent, Data Security, Ethical Considerations, Familial DNA Searching, Adverse Drug Reactions, Genetic Variations, Cytochrome P450 Enzymes, False positives, Public DNA Databases, Discriminations, Ethical use of Genetic Information, Biological Relationships, Accuracy and Reliability, Court Admissibility, Idiosyncratic Reactions, Risk Assessment, Cultural Sensitivity, Legel Implications, Genetic Testing, Public Trust, Individu

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Artificial Intelligence (AI) is the driving force behind most of the applications we use in our daily lives, and this necessitates advancements in human-AI interaction to go beyond basic functionalities. Through this article, we want to propose a novel methodology, the Sentient AI Framework (SAIF), that prioritizes the integration of emotional intelligence in AI systems, which makes them work in the better interest of humans by interpreting and responding while keeping human emotions into consideration. By integrating SAIF with intelligent systems like chatbots, virtual assistants, and robots, user interactions can be made more natural and engaging. This article discusses how SAIF can be developed and deployed to cultivate a sense of connection based on emotions such as trust and empathy, paving the way for the future where AI can be easily integrated into society and policy-making processes. Moreover, it discusses the key ethical aspects such as privacy, bias, explainability, and transparency to be considered. By developing such emotionally intelligent systems in collaboration with scholars, ethicists, and policymakers, we can ensure the ethical development and utilization of SAIF, thereby enhancing well-being and cultivating a better society.

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 Keywords

Artificial Intelligence, Emotional Intelligence, Human-AI Interaction, Trustworthy Artificial Intelligence, Sentient AI Framework

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As electric vehicles (EVs) continue to be embraced by users, a more efficient power management system at EV charging stations has become more necessary, hence the importance of demand forecasting. The present work deals with the prediction of the energy demand at EV charging stations by making use of machine learning and time series models. Also, models such as SARIMA, Random Forest, XGBoost, and H2O.ai's AutoML have been evaluated in forecasting energy consumption in relation to fleet size, the time of the day, respective weather conditions, and the grid load. Our research attempts to illustrate the advantages and disadvantages of each model in question on the market while noting that SARIMA model was the most precise, as it produced best scores based on explained models such as Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood values. The research elaborates on how the non-linear data relationships, the high computation requirements and seasonality present challenges and also emphasizes the need for the models to be interpretable and scalable due to the rise of the EV market. This paper also addresses the issue of how these models can be utilized within charging infrastructure in a smarter way and ways of integrating such charging infrastructure as involved predictive analytics into a smart grid system, aiming at efficiency enhancement, especially with regards to adoption of renewables. Findings lead to the conclusion that these efficiency-enhancing measures are also beneficial in enhancing the quality of energy predictive procurement processes.

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 Keywords

Electric Vehicles, Energy Consumption, Charging, Demand, Forecast, Model

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This study seeks to create a smart system that offers farmers up-to-date and precise information to improve their farming methods and decision-making. By employing Natural Language Processing (NLP) methods, the chatbot analyzes user questions and provides appropriate answers from a set of agricultural knowledge resources. We employed the Natural Language Toolkit (NLTK) for text manipulation and the Term Frequency Inverse Document Frequency (TFIDF) vectorizer to convert text into numerical data. Cosine similarity is then applied to compare user questions with sentences in the knowledge base, ensuring the most pertinent information is retrieved. The entire development process includes several essential steps such as Data Collection, Data Preprocessing, Encoding, Obtaining Response, TFIDF, Cosine Similarity, and Generating Responses for the chatbot to display to users. This system empowers farmers by providing them with convenient access to crucial agricultural information, thereby aiding their efforts to boost productivity and sustainability. By incorporating sophisticated NLP methods, the system improves the accessibility and relevance of agricultural knowledge, leading to the overall empowerment and advancement of the agricultural community. The results show the chatbot's effectiveness in providing accurate and relevant agricultural information, significantly enhancing the farmers' decision-making process and resulting in improved agricultural results.

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 Keywords

Natural Language Processing (NLP), Natural Language Tool Kit (NLTK), Term Frequency Inverse Document Frequency (TFIDF), Cosine Similarity.

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Creative Commons Attribution 4.0 and The Open Definition

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Fluoride contamination in drinking water is a global health concern, especially in regions where groundwater is the primary source of potable water. Elevated fluoride levels lead to health issues such as dental and skeletal fluorosis. This study focuses on the development and analysis of ferrite-based composite materials for efficient water defluoridation. Ferrite composites have garnered attention due to their unique magnetic, chemical, and adsorptive properties, making them promising candidates for environmental remediation. This paper presents a detailed synthesis process of ferritebased composites, evaluates their structural and chemical characteristics, and analyzes their fluoride removal efficiency from aqueous solutions.

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Ferrite-based composites, water defluoridation, fluoride removal, adsorption, co-precipitation, magnetic separation.

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 Abstract

Acquiring knowledge is a phenomenon, where the owner of it gains through different mechanisms-through experience, external factors, internal factors, formal, informal, etc. and it may be tacit or implicit or explicit. Some knowledge is such that it is confined to some special group/clans or very much intervened/mingled with lifestyle or functional life/culture of the community. And such knowledge is mostly undocumented which hinges around the community and pass on generations to generations orally or through practice, legends, myths, taboos, poetry, etc. Such a treasure of knowledge is known as the indigenous knowledge or traditional knowledge. The beauty and pride of such knowledge is incomparable. Some communities are well known for their indigenous knowledge they retains. In the contemporary world, if modern technology and indigenous knowledge are simultaneously capitalized then some of the unaddressed problems related to every realm of life may be mitigated in more effective and efficient manner. Indigenous knowledge are very rich in nature but it is vanishing from its existence because these kind of knowledge is usually not documented, possessors are not willing to share, and not practiced. So, through this paper author attempts to highlight the issues and challenges confronted in the process of its documentation and dissemination of the same to reap full advantage

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 Keywords

Local knowledge, indigenous knowledge, documentation, dissemination, management model, AYUSH

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Creative Commons Attribution 4.0 and The Open Definition