This paper delves into the profound advancements of Large Language Models (LLMs), epitomized by GPT-3, in natural language processing and artificial intelligence. It explores the epistemological foundations of LLMs through the lenses of Aristotle and Kant, revealing apparent distinctions from human learning. Transitioning seamlessly, the paper then delves into the ethical landscape, extending beyond knowledge acquisition to scrutinize the implications of LLMs in decision-making and content creation. The ethical scrutiny, employing virtue ethics, deontological ethics, and teleological ethics, delves into LLMs' (...) behaviours and decisions, necessitating the exploration of novel ethical paradigms tailored to machine intelligence. The paper also addresses biases in data, privacy concerns, copyright implications, and intellectual property rights, emphasizing the need to adapt frameworks for both human and machine creators. The paper concludes by advocating for interdisciplinary dialogue between philosophers, cognitive scientists, and AI researchers to foster a balanced and ethically grounded integration of LLMs into the evolving landscape of artificial intelligence. Continuous reflection on the evolving relationship between human cognition and artificial intelligence emerges as a crucial aspect for shaping a harmonious and responsible future in this domain. (shrink)

Abstract—Smart homes and Wireless Home Automation Networks (WHAN) face several challenges in terms of cost, scalability, reliability, delay, energy consumption and many others. Smart homes typically have huge number of communicating devices. Efficient management of network resources is a major challenge in such environments. This paper provides insights on how to improve the MAC layer in smart home networks to fulfil the requirements of the different smart home applications. It provides a classification of the different smart home applications and identifies (...) the main requirements and challenges regarding the MAC layer in this environment. It also provides insights for MAC protocols designers by highlighting the main issues in designing MAC schemes for smart home environment. Based on the analysis, the paper highlights adaptability as the most critical and challenging feature for smart home MAC protocols. (shrink)

Health policy changes in Nepal displayed struggles against a poor political, geographical, and economic setting; Millennium Development Goal #4 demanded improved infant and child mortality, as well as adequate measles vaccine coverage by the year 2015. Research in this report presents progress and direction of child health care policy across more than a decade of time in attempts of attaining MDG #4 and general child health care advancements. Subsequent observations and suggestions were delineated and offered. Progress since the 1990’s up (...) to 2012 was analyzed by review of serial national survey and report data. Trends and variations between regions were mostly analyzed amongst various child health care determinants. Results indicated many improved factors; Nepal will likely achieve MDG regarding child under-5 mortality, but may not achieve measles vaccine coverage or infant mortality goals. Furthermore, severe regional disparities were evident within Nepal, particularly in the Mid and Far-Western regions. A call for integrated community-based primary health care (CB-PHC) for infants and children became an ultimate ideal. A comprehensive, multidisciplinary, and community based primary care delivery service would address many of the deficits identified as well as reach rural and remote areas that still suffered. Risk and data-based resource allocation promise improved utilization, but also demands more frequent and better data reporting. Coordinated, multi-sector health policy initiatives have been underway; this demonstrated a strong direction in improving child health care from urban to every village. (shrink)

Papaya is a tropical fruit with a green cover, yellow pulp, and a taste between mango and cantaloupe, having commercial importance because of its high nutritive and medicinal value. The process of sorting papaya fruit based on maturely is one of the processes that greatly determine the mature of papaya fruit that will be sold to consumers. The manual grading of papaya fruit based on human visual perception is time-consuming and destructive. The objective of this paper is to the status (...) classification of papaya fruits if it's mature or partially matured or unmatured. A deep learning technique that was extensively applied to image recognition was used. The trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. Classification model of VGG16 achieved a 100% accuracy and 112 seconds of training time. (shrink)

Abstract: Artificial Intelligence (AI) is transforming organizational dynamics by reshaping both structures and processes. This paper examines how AI-driven innovations are redefining organizational frameworks, ranging from shifts in hierarchical models to the adoption of decentralized decision-making. It explores AI's impact on key processes, including workflow automation, data analysis, and decision support systems. Through case studies and empirical research, the paper illustrates the advantages of AI in enhancing efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges posed (...) by AI integration, such as resistance to change, ethical concerns, and data security issues. The paper concludes with insights into future trends and implications for organizations navigating the evolving landscape of AI-driven change. (shrink)

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid (...) sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios. (shrink)

The bruxism is a medical sleep syndrome it is the remedial span for crushing the tines and gritting the jowl. Human rarely chore their tines and jowl, slightly than crushing their teeth lacking it producing any signals. The symptoms of bruxism are arduousness in the jowl joint, breakable teeth, headache, earache and difficulty in open in mouth etc. The causes of bruxism are snooze sickness, pressure and nervousness. The REM is a rapid eye movement it's a stages of sleep. The (...) EEG signal are used in the measurement of neuron, the alpha, beta, gamma, theta and delta wave are used in the prognostic of bruxism syndrome. It's used in MATLAB coding by the six steps in prognostic in bruxism. Md Belal Bin Heyat | Faijan Akhtar | Shadab Azad "Comparative Analysis of Original Wave & Filtered Wave of EEG signal Used in the Prognostic of Bruxism medical Sleep syndrome" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-1 , December 2016,. (shrink)

The transition of C. albicans from unicellular yeast form to filamentous form i.e., pseudohyphae and hyphae is referred to as morphogenesis. C. albicans has the ability to respond to environmental conditions and accordingly changing its cell morphology. Three main morphological forms of C. albicans are unicellular yeast, pseudohyphae and hyphae. The effect of different growth media (Horse serum medium, RPMI-1640, MSGB), incubation temperatures (34˚C, 37˚C, 40˚C) and pH values (5.4, 6.4, 7.4) on germ tube production by C. albicans was evaluated. (...) Horse serum medium noticeably promotes filamentation while RPMI-1640 medium shows moderate filamentation and MSGB media shows moderately low filamentation. The germ tube of C. albicans developed early in 1.5 hr at high temperature i.e., 40˚C. Incubation temperature of 37˚C was associated with highest germ tube formation while 34˚C shows low filamentation. A pH of 5.4 also induces low filamentation, pH 6.4 gives moderately lower than pH 7.4. A pH of 7.4 was best suited for germ tube induction. The peak of mycelium production appears between 1.5 and 6 hr after inoculation of C. albicans culture. These results suggested that environmental factors are important in selectively favoring yeast or hyphal form, most important being the growth medium, incubation temperature and external pH value. (shrink)

This special issue consists of four articles, contributed by David Owen; Désirée Lim, Sahar Akhtar and (as co-authors) Mollie Gerver, Miranda Simon, Patrick Lown and Dominik Duell. These contributions address issues related to migration policies with the aim of bringing normative theories of migration and discrimination into dialogue. These theories describe the various types of discrimination inherent in the domestic and global migration systems, as well as assess arguments, pro et contra, about whether these forms of discrimination are permissible.