Aspects Of Artificial Intelligence Research Articles

Role Of Artificial Intelligence in Big Database Management

This exploration article digs into the significant effect of (artificial intelligence) AI, on big Data base management in the field of computer science by utilizing the broad abilities of artificial intelligence AI technologies, this study investigates different strategies to improve the oversight and administration of huge information bases. Through an exhaustive assessment of existing academic works, itemized contextual investigations, and master experiences, the article disentangles the mind-boggling combination of Ai’s integration and its important impacts on database management rehearses. Covering an extensive variety of artificial intelligence aspects, for example, AI, regular language handling, and profound realizing, this academic request plans to explain the complex job of computer-based intelligence in the domain of big database management. As a critical commitment to scholarly talk, this research article fills in as an original work, planning the groundbreaking excursion of Ai transformative into the center of data base management system, introducing another time of development and productivity in the computerized scene.

The dark side of artificial intelligence: threats to tourism workers

PurposeThis study aims to conduct research by making use of studies investigating the negative effects of artificial intelligence on the future careers and work motivation of tourism employees.Design/methodology/approachIn this research, a literature review, which is one of the qualitative research methods, was used. The study was completed by using a total of 13 articles and two book chapters investigating the negative aspects of artificial intelligence in the research data Science Direct and Web of Science databases as the main references.FindingsIn the articles examined as a result of the research, it was predicted that the entry of artificial intelligence into the tourism sector poses a threat to the future careers of many tourism employees, and this will cause tourism employees to lose their focus and motivation at work. Another conclusion reached as a result of the research is that many tourism workers will be unemployed in the future due to artificial intelligence-supported information systems and robots.Originality/valueWhen the literature was reviewed, there was no research that directly examined the negative effects of artificial intelligence on tourism sector employees. Therefore, this research is unique and important in this respect.

Prediction of Engineering Students Learning Outcomes using Machine Learning

Data science and machine learning, over the years have proven very well-organized and significant in many sectors including education. Machine learning is an aspect of artificial intelligence in which a computing system can able to learn from data and make conclusions. The recent development in education sector provides assessment tools to predict the student performance by exploring education data using machine learning and data mining techniques. Student performance assessment is an important measurement metrics in education which affects the university accreditation. Student performance improvement plan must be implemented in those universities, by counselling the low performer students. It helps both students and teachers to overcome the problems experienced by the student during studies and teaching techniques of teachers. In this review paper, different student performance prediction literature related to find out low performer student. The survey results indicated that different machine learning techniques are used to overcome the problems related to predicting student at risk and assessment of student performance. Machine learning techniques plays an important role in progress and prediction of student performance, thus improving student performance prediction system

A Systematic Review of the Application of Computational Technology in Microtia.

Microtia is a congenital and morphological anomaly of one or both ears, which results from a confluence of genetic and external environmental factors. Up to now, extensive research has explored the potential utilization of computational methodologies in microtia and has obtained promising results. Thus, the authors reviewed the achievements and shortcomings of the research mentioned previously, from the aspects of artificial intelligence, computer-aided design and surgery, computed tomography, medical and biological data mining, and reality-related technology, including virtual reality and augmented reality. Hoping to offer novel concepts and inspire further studies within this field.

Legal framework for AI applications

Artificial intelligence (AI), the most widespread technological term, has become an integral part of human daily life. People are becoming increasingly dependent on AI-powered devices; thus, it is now essential to have a legal framework to oversee artificial intelligence's various uses and legal peculiarities. As artificial intelligence has entered all areas of life and into various sectors, which requires examining in detail the legal nature of artificial intelligence, determining the laws that must be applied to it, and identifying the people or entities responsible for it to determine the scope of their responsibilities for the resulting damages that may be caused to others as a result of the use of intelligence. Artificial, this research aimed to examine the adequacy of the legal rules in Jordanian legislation regulating the provisions of artificial intelligence in light of the diversity of its applications and its different legal nature. The research is divided into two chapters. The first chapter presents the concept of artificial intelligence, and the second chapter discusses the legal liability of artificial intelligence. The results of the research revealed that the Jordanian legislator did not specify the legal nature of the artificial intelligence and contented himself with stipulating it in separate texts, Legal liability resulting from utilizing artificial intelligence systems can be challenged under regulations of the defect in manufacturing, responsibility for guarding things, and the distinction between responsibilities due to the degree of independence and intelligence of artificial intelligence, In determining the liability of artificial intelligence, the legislator should consider the types of artificial intelligence systems, their different capabilities, and their independence from humans, The process of enacting special laws regulating all aspects of artificial intelligence must be expedited. This law should be characterized by flexibility that enables it to keep pace with and rapid development witnessed in this field.

Analysis the improvements of YOLOv5 algorithms: NRT-YOLO, MR-YOLO and YPH-YOLOv5

Computer Vision (CV) is a fundamental aspect of artificial intelligence, with applications spanning multiple domains. The YOLO (You Only Look Once) algorithm has significantly contributed to real-time object recognition in CV. This paper explores the evolution of the YOLO algorithm, focusing on the improvements brought by three specialized variants: NRT-YOLO, MR-YOLO, and TPH-YOLOv5. NRT-YOLO addresses the challenge by introducing the C3NRT module, enhancing precision while maintaining low complexity. MR-YOLO optimizes YOLOv5 for industrial quality control, improving speed and accuracy. TPH-YOLOv5 enhances object detection in drone-captured images by introducing additional prediction heads and transformer modules. Despite these advancements, YOLO algorithms have limitations, including difficulty in detecting small objects and issues in complex scenes. Nevertheless, the research sheds light on the continuous evolution of YOLO algorithms, offering insights into real-time object detection, with applications in manufacturing, healthcare, transportation, and more. The significance of this research lies in showcasing the adaptability and potential of the YOLO framework. As YOLO continues to evolve, it promises to revolutionize various industries and applications, providing robust, real-time object detection solutions.

Study of Artificial Intelligence Aspects in Policy Formulation and Decision-Making Paradigms and Theories of Administrative Science


 
 
 The development and use of Artificial Intelligence (AI) has become a widely discussed topic, not only in Indonesia but also globally. The emergence of ChatGPT in 2022 has led to the rapid development and use of AI in various fields, such as medicine, creative industries, academics, and social entrepreneurship. The history of AI development began with the creation of the Enigma code-breaking machine during World War II by Alan Turing. Since then, AI research has continued to evolve, with the Turing Test serving as the basis for identifying the intelligence of an artificial system. The COVID-19 pandemic has also accelerated the development of AI, particularly in the use of big data for diagnosis. The introduction of ChatGPT, a generative AI program, has further increased public interest in AI. The potential of generative AI to simplify workflows in various industries and individuals is vast, and it has been used in social entrepreneurship, such as the Sign-Speak application for real-time sign language recognition and translation. The government can also use AI to formulate policies and address issues in society. However, the use of AI must be ethical and not reduce the essence of research.
 
 

Comprehensive systematic review of information fusion methods in smart cities and urban environments

Smart cities result from integrating advanced technologies and intelligent sensors into modern urban infrastructure. The Internet of Things (IoT) and data integration are pivotal in creating interconnected and intelligent urban spaces. In this literature review, we explore the different methods of information fusion used in smart cities, along with their advantages and challenges. However, there are notable challenges in managing diverse data sources, handling large data volumes, and meeting the near-real-time demands of various smart city applications.The review aims to examine smart city applications in detail, incorporating quality evaluation and information fusion techniques and identifying critical issues while outlining promising research directions. In order to accomplish our goal, we conducted a comprehensive search of literature and applied selective criteria. We identified 59 recent studies addressing machine learning (ML) and deep learning (DL) techniques in smart city applications. These studies were obtained from various databases such as ScienceDirect (SD), Scopus, Web of Science (WoS), and IEEE Xplore. The main objective of this study is to provide more detailed insights into smart cities by supplementing existing research. The word cloud visualisation of machine learning/deep learning and information fusion in smart cities papers shows a diverse landscape, covering both technical aspects of artificial intelligence and practical applications in urban settings. Apart from technical exploration, the study also delves into the ethical and privacy implications arising in smart cities. Moreover, it thoroughly examines the challenges that must be addressed to realise this urban revolution's potential fully.

Conference Results on “National Experience in Implementing the Unesco Recommendation on the Ethical Aspects of Artificial Intelligence”

This article examines activities aimed at implementation and promotion of UNESCO’s fundamental documents in the field of regulation of artificial intelligence and, in particular, the “Recommendation on the Ethical Considerations of Artificial Intelligence” and other tools developed by this specialized agency of the United Nations. The article provides a detailed review of the conference “National experience in implementation of the UNESCO Recommendation on the Ethics of Artificial Intelligence”, which was organized on October 27, 2023 by the MGIMO Centre for Artificial intelligence with the support of the Commission of the Russian Federation for UNESCO and the Russian Committee of the UNESCO Information for All Program (IFAP).

Computational Methods and Artificial Intelligence in The Architectural Pre-Design Process (Case Study: House Design)

The current development of information technology infrastructure has positively impacted the ease with which people can carry out work activities physically and creatively. Artificial intelligence, which is currently starting to penetrate the world of visual design and architecture, is starting to develop from integrating design methods to methods of presenting or communicating architecture. In this study, aspects of artificial intelligence are used as a pre-design method, which is considered to help speed up decisions in design communication. The problem raised in this study is how optimal the involvement of computing and artificial intelligence is in providing pre-design considerations in the case of simple residential houses, especially in the analysis, space, and visual aspects. This study aims to obtain the methods and influence of computing and artificial intelligence in formulating pre-designs and generating understanding regarding the methods of their use. Several analysis tools are used for the spatial approach: the space syntax using DepthmapX software, solar analysis using the Shadedat plugin, and the visual shape of the building using Stable Diffusion. This research uses an experimental approach to obtain the desired design results. This study's findings explain that applying appropriate computational and artificial intelligence methods will produce an effective and efficient design process. With the correct sequence, it will have a measurable design process that can be assessed well.

Challenges of the Halal Food Industry in Era 5.0 Perspective of Science and Islamic Law

The halal industry continues to grow in various parts of the world, including Indonesia. It is currently one of the most potential economic sectors. However, despite having very good prospects, the halal industry also faces several challenges in the 5.0 era, especially in the fields of science and Islamic laws. For this reason, this research was conducted to reveal the challenges of the halal industry in Indonesia. The research method used is library research whose sources are from the Quran, hadiths, books, laws and regulations, and scientific articles. The research reveals that in terms of science, the challenges include the supply chain, and raw materials used in the production process. In addition, raw materials that were originally halal but due to a lack of public understanding, the final product becomes haram, either due to the slaughtering process or other processes. The next challenge is the use of food and beverage names, equipment, storage tools, and digital business processes. Meanwhile, from the Islamic law perspective, all processes in the halal industry must be by Islamic values found in the Quran, hadith, and the opinions of scholars. In addition, the next challenge is to develop modern halal fiqh that reaches aspects of artificial intelligence 5.0.
 Keywords: halal food industry, science, Islamic law, Era 5.0

The Exploration of Emotional Aspects of Artificial Intelligence (AI) in Artistic Design

The article explores the emotional aspect of artificial intelligence in art and design. With technological advancements, AI has shown tremendous potential in the realm of artistic creation. Firstly, the article reviews the development of AI in art and design, introducing applications of technologies such as generative art, deep learning, and generative adversarial networks. Secondly, it delves into the emotional dimension of AI in artistic design. Despite significant progress in learning and imitating artistic styles, AI's expression of emotions remains limited to simulating programs and data, creating a gap with human emotional experiences. However, by learning from human aesthetic experiences, AI utilizes universally recognized emotional symbols in artistic works, evoking aesthetic resonance among audiences. Furthermore, the article emphasizes the importance of human designers in the creative process and the potential for collaboration between AI and humans. Lastly, it discusses the future possibilities wherein AI, as technology advances, may enter an era of strong artificial intelligence, potentially disrupting the ecosystem of art and design. Although AI might acquire emotional and creative capabilities in the future, the emotional experiences and unique creativity of human creators remain irreplaceable. Therefore, the future of art and design might be a product of collaboration between humans and AI, opening new spaces for exploration and contemplation in the art world.

Discussion on the Current Application of Artificial Intelligence in the Digital Economy

In the era of the digital economy, data, algorithms, and computing capabilities constitute vital elements that drive economic development. The three elements of artificial intelligence are -computing power, algorithm, and data. As for the difference and progress, machines imitate and enhance human physical strength, but artificial intelligence imitates and improves human intelligence. This work first mentions the status quo of how artificial intelligence boosts the digital economy. Then, it comes to several aspects of artificial intelligence’s development, prospect, and application. Eventually, this paper mentioned how to apply artificial intelligence technology to various industries to form new industries, thus promoting the development of the digital economy.In conclusion, digital technology promotes the comprehensive efficiency upgrade of various national economy departments. Its formation is that the digital economy improves the efficiency of various departments through digital technology. Efficiency upgrade means cost reduction, relative competitive advantage in the industry, adjustment and transformation of the original industrial structure and product structure, and the use of digital technology for existing products and technologies to reduce the production costs of manufacturing enterprises and achieve product upgrades. Improvements in quality, structural changes, and management efficiency have improved the core competitiveness of enterprises and achieved a comparative advantage in competition.

Artificial Intelligence and Ethics

A more covert aspect of Artificial Intelligence (AI) pertains to the ethical quandaries surrounding the actions of machines. In the case of Large Language Models (LLMs), hidden beneath their seemingly impeccable automated outputs lies a colossal amalgamation of trillions of compiled data points, comprising copied blogs, articles, essays, books, and artworks. This raises profound questions about copyright ownership and retribution for the original authors. But beyond intellectual property, another insidious facet of LLMs emerges – their propensity to cause harm to individuals through what can only be described as hallucinatory outputs. Victims of these AI- -generated delusions suffer defamation, and their plight remains largely unnoticed. Amidst the marvels of AI, the plight of the underpaid laborers who form the backbone of AI development is seldom acknowledged, a subject that warrants more profound discussion. Furthermore, as AI algorithms continue to permeate various aspects of society, they bring to the fore issues of bias. For instance, facial recognition technologies frequently exhibit skewed outcomes, leading to false accusations and grave consequences due to over-reliance on these technologies.
 The algorithmic schemes employed in CV selection for job applications or university admissions also raise concerns about fairness.
 The question of machines replacing the human workforce looms ever larger on the horizon. The potential socio-economic ramifications demand careful evaluation.
 Lastly, the extensive reliance of artificial intelligence on vast datasets, including copyrighted works, results in the creation of gargantuan data servers with an unimaginable environmental impact.
 The hidden aspects of artificial intelligence encompass a multitude of ethical dilemmas, spanning intellectual property rights, biases, labour conditions, societal impacts, and environmental considerations. A thorough and elaborate examination of these issues is essential to navigate the ever-evolving landscape of AI responsibly and ethically.

Legal aspects of artificial intelligence in the employment process

The introduction of artificial intelligence in all domains of life is the most transformative process in recent history. It is also a highly dynamic process, and due to the pace of technological development, a very limited legal framework is available to address issues of human rights, ethics, transparency, privacy, safety and accountability. During the last few years, artificial intelligence started to reshape employment processes. Positive aspects of the introduction of AI in the employment process are efficiency and quality in job matching, digitalisation and acceleration of the process, ability to process large data and match job seekers to available vacancy announcements, the alleviation of administrative burdens of employees of employment agencies and giving them strategic and innovative roles. All these are indispensable in present times when demographic challenges in European countries are leading to increased labour migrations and require changes in the recruitment process. The paper explores the current challenges of AI, i.e. how to achieve human-centred values and fairness of AI use during the employment process, preventing algorithmic bias and discriminatory application of AI tools. In order to harness the maximum benefits of AI, we need to develop a regulatory framework that would be enforceable, inclusive and adaptive (OECD), particularly knowing that most AI solutions are privately owned and developed for commercial purposes.

Legal aspects of artificial intelligence in relation to intellectual property

Legal aspects of artificial intelligence in relation to intellectual property

Using LSTM to Identify Help Needs in Primary School Scratch Students

In the last few years, there has been increasing interest in the use of block-based programming languages as well as in the ethical aspects of Artificial Intelligence (AI) in primary school education. In this article, we present our research on the automatic identification of the need for assistance among primary school children performing Scratch exercises. For data collection, user experiences have been designed to take into account ethical aspects, including gender bias. Finally, a first-in-class distance calculation method for block-based programming languages has been used in a Long Short-Term Memory (LSTM) model, with the aim of identifying when a primary school student needs help while he/she carries out Scratch exercises. This model has been trained twice: the first time taking into account the gender of the students, and the second time excluding it. The accuracy of the model that includes gender is 99.2%, while that of the model that excludes gender is 91.1%. We conclude that taking into account gender in training this model can lead to overfitting, due to the under-representation of girls among the students participating in the experiences, making the model less able to identify when a student needs help. We also conclude that avoiding gender bias is a major challenge in research on educational systems for learning computational thinking skills, and that it necessarily involves effective and motivating gender-sensitive instructional design.

The Role of Artificial Intelligence in Education Informatisation: Prospects and Challenges

The purpose of the article is to conduct a comprehensive study of the role of artificial intelligence in the process of education informatisation and to identify the prospects and challenges associated with the introduction of these technologies into the educational process. Research methods. In order to effectively achieve the purpose of the study, the methods of analysis and synthesis, generalisation of theoretical data, observation, and a systematic approach were used. All of this made it possible to analyze and identify the features of the digitalization of education using artificial intelligence. The scientific novelty lies in a detailed analysis of the role of artificial intelligence in the process of education informatisation with a focus on the prospects and challenges associated with the introduction of these technologies into the educational process. The current state of education informatization is analyzed, key aspects of artificial intelligence are considered, the possibilities and limitations of its use in education are highlighted, and specific recommendations are given to educational institutions for the successful implementation of these technologies. Conclusions. Thus, the current state of education informatization reflects the great need for new approaches to learning and adaptation to the requirements of the digital society. Information technologies are changing the educational process, making it more accessible and efficient. The analysis shows that artificial intelligence can play an important role in achieving these goals. It provides opportunities for adaptive and personalised learning, automated assessment and reporting, as well as the development of recommendation systems and the use of virtual assistants in the educational process. However, along with the benefits of using artificial intelligence in education come challenges. Ethical issues, data privacy, training, and technical limitations are serious issues that need to be addressed and resolved. Despite these challenges, we believe that artificial intelligence has great potential to transform education. It can help create more innovative and accessible learning for all. That is why we recommend that educational institutions carefully develop strategies for implementing artificial intelligence, taking into account ethical and legal issues, and focusing on training qualified specialists in this field. Further research in this area can help develop best practices for using AI in the educational process and ensure access to quality education for all.

ARTIFICIAL NEURAL NETWORKS WITH DYNAMIC SYNAPSES: A REVIEW

Artificial neural networks (ANNs) are widely applied to solve real-world problems. Most of the actions we take and the processes around us are time-varying. ANNs with dynamic properties allow processing time-dependent data and solving tasks such as speech and text processing, prediction models, face and emotion recognition, game strategy development. Dynamics in neural networks can appear in the input data, the architecture of the neural network, and the individual elements of the neural network – synapses and neurons. Unlike static synapses, dynamic synapses can change their connection strength based on incoming information. This is a fundamental principle allows neural networks to perform complex tasks like word processing or face recognition more efficiently. Dynamic synapses play a key role in the ability of artificial neural networks to learn from experience and change over time, which is one of the key aspects of artificial intelligence. The scientific works examined in this article show that there are no literature sources that review and compare dynamic DNTs according to their synapses. To fill this gap, the article reviews and groups DNTs with dynamic synapses. Dynamic neural networks are defined by providing a general mathematical expression. A dynamic synapse is described by specifying its main properties and presenting a general mathematical expression. Also an explanation, how these synapses can be modelled and integrated into 11 different dynamic ANNs is shown. Moreover, structures of dynamic ANNs are compared according to the properties of dynamic synapses.

UNLOCKING THE SKY

Satellite imagery plays a crucial role in research and development, facilitating advancements in fields such as agriculture monitoring and disaster management. These images, captured through sophisticated systems, are processed using computers to extract valuable information. Machine Learning (ML), a fundamental aspect of artificial intelligence, involves constructing rules based on data. It revolves around creating software applications that access information and use it for self-guided learning. In the context of satellite imagery, Machine Learning algorithms have proven indispensable for analyzing images from various sources, yielding deeper insights. This article explores the utilization of Machine Learning- based image classification techniques to enhance the interpretation of Satellite Imagery. By employing these techniques, the process of classifying objects within satellite images can be improved, leading to more refined and detailed out comes window will be opened for the kids with specialized tools and description.