Search results for: AI (Artificial Intelligence)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2505

Search results for: AI (Artificial Intelligence)

1875 Challenges beyond the Singapore Future-Ready School ‘LEADER’ Qualities

Authors: Zoe Boon Suan Loy

Abstract:

An exploratory research undertaken in 2000 at the beginning of the COVID-19 pandemic examined the changing roles of Singapore school leaders as they lead teachers in developing future-ready learners. While it is evident that ‘LEADER’ qualities epitomize the knowledge, competencies, and skills required, recent events in an increasing VUCA and BANI world characterized by massively disruptive Ukraine -Russian war, unabating tense US-Sino relations, issues related to sustainability, and rapid ageing will have an impact on school leadership. As an increasingly complex endeavour, this requires a relook as they lead teachers in nurturing holistically-developed future-ready students. Digitalisation, new technology, and the push for a green economy will be the key driving forces that will have an impact on job availability. Similarly, the rapid growth of artificial intelligence (AI) capabilities, including ChatGPT, will aggravate and add tremendous stress to the work of school leaders. This paper seeks to explore the key school leadership shifts required beyond the ‘LEADER’ qualities as school leaders respond to the changes, challenges, and opportunities in the 21st C new normal. The research findings for this paper are based on an exploratory qualitative study on the perceptions of 26 school leaders (vice-principals) who were attending a milestone educational leadership course at the National Institute of Education, Nanyang Technological University, Singapore. A structured questionnaire is designed to collect the data, which is then analysed using coding methodology. Broad themes on key competencies and skills of future-ready leaders in the Singapore education system are then identified. Key Findings: In undertaking their leadership roles as leaders of future-ready learners, school leaders need to demonstrate the ‘LEADER’ qualities. They need to have a long-term view, understand the educational imperatives, have a good awareness of self and the dispositions of a leader, be effective in optimizing external leverages and are clear about their role expectations. These ‘LEADER’ qualities are necessary and relevant in the post-Covid era. Beyond this, school leaders with ‘LEADER’ qualities are well supported by the Ministry of Education, which takes cognizance of emerging trends and continually review education policies to address related issues. Concluding Statement: Discussions within the education ecosystem and among other stakeholders on the implications of the use of artificial intelligence and ChatGPT on the school curriculum, including content knowledge, pedagogy, and assessment, are ongoing. This augurs well for school leaders as they undertake their responsibilities as leaders of future-ready learners.

Keywords: Singapore education system, ‘LEADER’ qualities, school leadership, future-ready leaders, future-ready learners

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1874 Role of Artificial Intelligence in Nano Proteomics

Authors: Mehrnaz Mostafavi

Abstract:

Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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1873 Gamification of a Business Intelligence Tool

Authors: Stephen Miller

Abstract:

The act of applying game mechanics and dynamics (which have been traditionally used in video games) into business applications is being widely trialed in an effort to make conventional business software a bit more participative, fun and engaging. This new trend, named ‘gamification’ has its believers and of course, its critics who still need convincing that the concept is an effective and beneficial business tool worthy of investment. The literature reveals that user engagement of business intelligence (BI) tools is much lower than expected and investors are failing to get a good return on their investment (ROI). So, a software prototype will be designed and developed to add gamification to a BI tool to determine its effect upon the user engagement levels of test participants. The experimental study will be evaluated using the comprehensive User Engagement Scale (UES) to see if there are improvements in areas such as; aesthetics, perceived usability, endurability, novelty, felt involvement and focused attention. The results of this unique study should demonstrate whether or not ‘gamifying’ a BI tool has the potential to increase an individual’s motivation to use BI software more often.

Keywords: business intelligence, gamification, human computer interaction, user engagement

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1872 Cryptographic Protocol for Secure Cloud Storage

Authors: Luvisa Kusuma, Panji Yudha Prakasa

Abstract:

Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

Procedia PDF Downloads 341
1871 Artificial Intelligence Based Meme Generation Technology for Engaging Audience in Social Media

Authors: Andrew Kurochkin, Kostiantyn Bokhan

Abstract:

In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

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1870 Enhancing AI for Global Impact: Conversations on Improvement and Societal Benefits

Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

Abstract:

This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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1869 Improvement Image Summarization using Image Processing and Particle swarm optimization Algorithm

Authors: Hooman Torabifard

Abstract:

In the last few years, with the progress of technology and computers and artificial intelligence entry into all kinds of scientific and industrial fields, the lifestyles of human life have changed and in general, the way of humans live on earth has many changes and development. Until now, some of the changes has occurred in the context of digital images and image processing and still continues. However, besides all the benefits, there have been disadvantages. One of these disadvantages is the multiplicity of images with high volume and data; the focus of this paper is on improving and developing a method for summarizing and enhancing the productivity of these images. The general method used for this purpose in this paper consists of a set of methods based on data obtained from image processing and using the PSO (Particle swarm optimization) algorithm. In the remainder of this paper, the method used is elaborated in detail.

Keywords: image summarization, particle swarm optimization, image threshold, image processing

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1868 Extension of Moral Agency to Artificial Agents

Authors: Sofia Quaglia, Carmine Di Martino, Brendan Tierney

Abstract:

Artificial Intelligence (A.I.) constitutes various aspects of modern life, from the Machine Learning algorithms predicting the stocks on Wall streets to the killing of belligerents and innocents alike on the battlefield. Moreover, the end goal is to create autonomous A.I.; this means that the presence of humans in the decision-making process will be absent. The question comes naturally: when an A.I. does something wrong when its behavior is harmful to the community and its actions go against the law, which is to be held responsible? This research’s subject matter in A.I. and Robot Ethics focuses mainly on Robot Rights and its ultimate objective is to answer the questions: (i) What is the function of rights? (ii) Who is a right holder, what is personhood and the requirements needed to be a moral agent (therefore, accountable for responsibility)? (iii) Can an A.I. be a moral agent? (ontological requirements) and finally (iv) if it ought to be one (ethical implications). With the direction to answer this question, this research project was done via a collaboration between the School of Computer Science in the Technical University of Dublin that oversaw the technical aspects of this work, as well as the Department of Philosophy in the University of Milan, who supervised the philosophical framework and argumentation of the project. Firstly, it was found that all rights are positive and based on consensus; they change with time based on circumstances. Their function is to protect the social fabric and avoid dangerous situations. The same goes for the requirements considered necessary to be a moral agent: those are not absolute; in fact, they are constantly redesigned. Hence, the next logical step was to identify what requirements are regarded as fundamental in real-world judicial systems, comparing them to that of ones used in philosophy. Autonomy, free will, intentionality, consciousness and responsibility were identified as the requirements to be considered a moral agent. The work went on to build a symmetrical system between personhood and A.I. to enable the emergence of the ontological differences between the two. Each requirement is introduced, explained in the most relevant theories of contemporary philosophy, and observed in its manifestation in A.I. Finally, after completing the philosophical and technical analysis, conclusions were drawn. As underlined in the research questions, there are two issues regarding the assignment of moral agency to artificial agent: the first being that all the ontological requirements must be present and secondly being present or not, whether an A.I. ought to be considered as an artificial moral agent. From an ontological point of view, it is very hard to prove that an A.I. could be autonomous, free, intentional, conscious, and responsible. The philosophical accounts are often very theoretical and inconclusive, making it difficult to fully detect these requirements on an experimental level of demonstration. However, from an ethical point of view it makes sense to consider some A.I. as artificial moral agents, hence responsible for their own actions. When considering artificial agents as responsible, there can be applied already existing norms in our judicial system such as removing them from society, and re-educating them, in order to re-introduced them to society. This is in line with how the highest profile correctional facilities ought to work. Noticeably, this is a provisional conclusion and research must continue further. Nevertheless, the strength of the presented argument lies in its immediate applicability to real world scenarios. To refer to the aforementioned incidents, involving the murderer of innocents, when this thesis is applied it is possible to hold an A.I. accountable and responsible for its actions. This infers removing it from society by virtue of its un-usability, re-programming it and, only when properly functioning, re-introducing it successfully

Keywords: artificial agency, correctional system, ethics, natural agency, responsibility

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1867 Influence of Emotional Intelligence on Educational Supervision and Leadership Style in Saudi Arabia

Authors: Jawaher Bakheet Almudarra

Abstract:

An Educational Supervisor assists teachers to develop their competence and skills in teaching, solving educational problems, and to improve the teaching methods to suit the educational process. They evaluate their teachers and write reports based on their assessments. In 1957, the Saudi Ministry of Education instituted Educational Supervision to facilitate effective management of schools, however, there have been concerns that the Educational Supervision has not been effective in executing its mandate. Studies depicted that Educational supervision has not been effective because it has been marred by poor and autocratic leadership practices such as stringent inspection, commanding and judging. Therefore, there is need to consider some of the ways in which school outcomes can be enhanced through the improvement of Educational supervision practices. Emotional intelligence is a relatively new concept that can be integrated into the Saudi education system that is yet to be examined in-depth and embraced particularly in the realm of educational leadership. Its recognition and adoption may improve leadership practices among Educational supervisors. This study employed a qualitative interpretive approach that will focus on decoding, describing and interpreting the connection between emotional intelligence and leadership. The study also took into account the social constructions that include consciousness, language and shared meanings. The data collection took place in the Office of Educational Supervisors in Riyadh and involved 4 Educational supervisors and 20 teachers from both genders- male and female. The data collection process encompasses three methods namely; qualitative emotional intelligence self-assessment questionnaires, reflective semi-structured interviews, and open workshops. The questionnaires would explore whether the Educational supervisors understand the meaning of emotional intelligence and its significance in enhancing the quality of education system in Saudi Arabia. Subsequently, reflective semi-structured interviews were carried out with the Educational supervisors to explore the connection between their leadership styles and the way they conceptualise their emotionality. The open workshops will include discussions on emotional aspects of Educational supervisors’ practices and how Educational supervisors make use of the emotional intelligence discourse in their leadership and supervisory relationships.

Keywords: directors of educational supervision, emotional intelligence, educational leadership, education management

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1866 Optimal Injected Current Control for Shunt Active Power Filter Using Artificial Intelligence

Authors: Brahim Berbaoui

Abstract:

In this paper, a new particle swarm optimization (PSO) based method is proposed for the implantation of optimal harmonic power flow in power systems. In this algorithm approach, proportional integral controller for reference compensating currents of active power filter is performed in order to minimize the total harmonic distortion (THD). The simulation results show that the new control method using PSO approach is not only easy to be implanted, but also very effective in reducing the unwanted harmonics and compensating reactive power. The studies carried out have been accomplished using the MATLAB Simulink Power System Toolbox.

Keywords: shunt active power filter, power quality, current control, proportional integral controller, particle swarm optimization

Procedia PDF Downloads 597
1865 The Impact of Artificial Intelligence on Human Rights Development

Authors: Romany Wagih Farag Zaky

Abstract:

The relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the overlap between these two views and the idea that efforts should be made in the field of human rights have increased in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. The article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which is a good answer to the question posed above. This book therefore cites regional and international human rights agreements such as , as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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1864 Innovations in the Lithium Chain Value

Authors: Fiúza A., Góis J. Leite M., Braga H., Lima A., Jorge P., Moutela P., Martins L., Futuro A.

Abstract:

Lepidolite is an important lithium mineral that, to the author’s best knowledge, has not been used to produce lithium hydroxide, necessary for energy conversion to electric vehicles. Alkaline leaching of lithium concentrates allows the establishment of a production diagram avoiding most of the environmental drawbacks that are associated with the usage of acid reagents. The tested processes involve a pretreatment by digestion at high temperatures with additives, followed by leaching at hot atmospheric pressure. The solutions obtained must be compatible with solutions from the leaching of spodumene concentrates, allowing the development of a common treatment diagram, an important accomplishment for the feasible exploitation of Portuguese resources. Statistical programming and interpretation techniques are used to minimize the laboratory effort required by conventional approaches and also allow phenomenological comprehension.

Keywords: artificial intelligence, tailings free process, ferroelectric electrolyte battery, life cycle assessment

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1863 Comparative Study between Classical P-Q Method and Modern Fuzzy Controller Method to Improve the Power Quality of an Electrical Network

Authors: A. Morsli, A. Tlemçani, N. Ould Cherchali, M. S. Boucherit

Abstract:

This article presents two methods for the compensation of harmonics generated by a nonlinear load. The first is the classic method P-Q. The second is the controller by modern method of artificial intelligence specifically fuzzy logic. Both methods are applied to an Active Power Filter shunt (APFs) based on a three-phase voltage converter at five levels NPC topology. In calculating the harmonic currents of reference, we use the algorithm P-Q and pulse generation, we use the intersective PWM. For flexibility and dynamics, we use fuzzy logic. The results give us clear that the rate of Harmonic Distortion issued by fuzzy logic is better than P-Q.

Keywords: fuzzy logic controller, P-Q method, pulse width modulation (PWM), shunt active power filter (sAPF), total harmonic distortion (THD)

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1862 The Importance of Information in Psychological Operations for Counterterrorism

Authors: Abbas Fazelinia

Abstract:

Terrorism is not a new phenomenon to the world, yet it remains difficult to define and to counter. Countering terrorism requires several measures that must be taken at the same time. Counterterrorism strategies of most countries depend on military measures. However, those strategies should also focus on nonlethal measures, such as economic, political, and social measures. The psychological dimensions of terrorism must be understood, evaluated, and used in countering terrorism. This study suggests that psychological operations, as nonlethal military operations, can be used to influence individuals not to join terrorist organizations and to facilitate defections from terrorist organizations. However, in order to implement effective psychological operations, one has to have appropriate intelligence about terrorist organizations. Examining terrorist organizations help us to identify their vulnerabilities and obtain this intelligence. This article concludes that terrorists’ motivations, terrorist organizations’ radicalization, recruitment, and conversion processes, ideology, goals, strategies, and general structure form the intelligence requirement for psychological operations in counterterrorism. The methodology used in this article is a mixed method.

Keywords: psychological operations, terrorist, counterterrorism, terrorism

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1861 Flushing Model for Artificial Islands in the Persian Gulf

Authors: Sawsan Eissa, Momen Gharib, Omnia Kabbany

Abstract:

A flushing numerical study has been performed for intended artificial islands on the Persian Gulf coast in Abu Dhabi, UAE. The island masterplan was tested for flushing using the DELFT 3D hydrodynamic model, and it was found that its residence time exceeds the acceptable PIANC flushing Criteria. Therefore, a number of mitigation measures were applied and tested one by one using the flushing model. Namely, changing the location of the entrance opening, dredging, removing part of the mangrove existing in the near vicinity to create a channel, removing the mangrove altogether, using culverts of different numbers and locations, and pumping at selected points. The pumping option gave the best solution, but it was disregarded due to high capital and running costs. Therefore, it opted for a combination of other solutions, including removing mangroves, introducing culverts, and adjusting island boundaries and types of protection.

Keywords: hydrodynamics, flushing, delft 3d, Persian Gulf, artificial islands.

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1860 Input Data Balancing in a Neural Network PM-10 Forecasting System

Authors: Suk-Hyun Yu, Heeyong Kwon

Abstract:

Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: artificial intelligence, air quality prediction, neural networks, pattern recognition, PM-10

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1859 Effects on Spiritual Intelligence on Young Adult Muslim Female: Integration of Planned Behaviour Theory in Predicting Consumer Attitude towards Halal Cosmetic

Authors: Azreen Jihan Che Mohd Hashim, Rosidah Musa

Abstract:

Although 'Spiritual Intelligence' (SI) is hard to measure, it is impossible without a noble value that may affect the attitude in purchasing behavior process, so this paper aims to report on a pilot study analysis results in order to evaluate the degree of SI towards consumers’ attitude in purchasing halal cosmetics and, in turn, to reaffirm intention to purchase by using Theory Planned Behaviour (TPB). It is a descriptive cross-sectional study among the Muslim women as the subjects, working and staying in Klang valley area in Malaysia. The purpose of the study is to develop a new measurement scale to unravel and decompose the underlying dimensions of SI from the perspective of the Muslim deemed imperative. About 200 respondents of users and non-users of halal cosmetics are selected. The structure equation modeling (SEM) was conducted to examine the relationships among god, society and self, which are the dimensions of SI. A finding indicates that, in influencing attitude, those who obligate high spiritual intelligence have a good relationship with god, society and self which may influence them to purchase halal cosmetic product. This study offers important findings and implications for future research as it presents a framework on the importance of SI.

Keywords: spiritual intelligence, god, society, self, young adult Muslim female

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1858 Probabilistic-Based Design of Bridges under Multiple Hazards: Floods and Earthquakes

Authors: Kuo-Wei Liao, Jessica Gitomarsono

Abstract:

Bridge reliability against natural hazards such as floods or earthquakes is an interdisciplinary problem that involves a wide range of knowledge. Moreover, due to the global climate change, engineers have to design a structure against the multi-hazard threats. Currently, few of the practical design guideline has included such concept. The bridge foundation in Taiwan often does not have a uniform width. However, few of the researches have focused on safety evaluation of a bridge with a complex pier. Investigation of the scouring depth under such situation is very important. Thus, this study first focuses on investigating and improving the scour prediction formula for a bridge with complicated foundation via experiments and artificial intelligence. Secondly, a probabilistic design procedure is proposed using the established prediction formula for practical engineers under the multi-hazard attacks.

Keywords: bridge, reliability, multi-hazards, scour

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1857 A Real-time Classification of Lying Bodies for Care Application of Elderly Patients

Authors: E. Vazquez-Santacruz, M. Gamboa-Zuniga

Abstract:

In this paper, we show a methodology for bodies classification in lying state using HOG descriptors and pressures sensors positioned in a matrix form (14 x 32 sensors) on the surface where bodies lie down. it will be done in real time. Our system is embedded in a care robot that can assist the elderly patient and medical staff around to get a better quality of life in and out of hospitals. Due to current technology a limited number of sensors is used, wich results in low-resolution data array, that will be used as image of 14 x 32 pixels. Our work considers the problem of human posture classification with few information (sensors), applying digital process to expand the original data of the sensors and so get more significant data for the classification, however, this is done with low-cost algorithms to ensure the real-time execution.

Keywords: real-time classification, sensors, robots, health care, elderly patients, artificial intelligence

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1856 Artificial Neural Networks Controller for Active Power Filter Connected to a Photovoltaic Array

Authors: Rachid Dehini, Brahim Berbaoui

Abstract:

The main objectives of shunt active power filter (SAPF) is to preserve the power system from unwanted harmonic currents produced by nonlinear loads, as well as to compensate the reactive power. The aim of this paper is to present a (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: SAPF, harmonics current, photovoltaic cells, MPPT, artificial neural networks (ANN)

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1855 Particle Filter State Estimation Algorithm Based on Improved Artificial Bee Colony Algorithm

Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

Abstract:

In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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1854 Artificial Intelligence and Governance in Relevance to Satellites in Space

Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

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1853 Solving Directional Overcurrent Relay Coordination Problem Using Artificial Bees Colony

Authors: M. H. Hussain, I. Musirin, A. F. Abidin, S. R. A. Rahim

Abstract:

This paper presents the implementation of Artificial Bees Colony (ABC) algorithm in solving Directional OverCurrent Relays (DOCRs) coordination problem for near-end faults occurring in fixed network topology. The coordination optimization of DOCRs is formulated as linear programming (LP) problem. The objective function is introduced to minimize the operating time of the associated relay which depends on the time multiplier setting. The proposed technique is to taken as a technique for comparison purpose in order to highlight its superiority. The proposed algorithms have been tested successfully on 8 bus test system. The simulation results demonstrated that the ABC algorithm which has been proved to have good search ability is capable in dealing with constraint optimization problems.

Keywords: artificial bees colony, directional overcurrent relay coordination problem, relay settings, time multiplier setting

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1852 Axial Flux Permanent Magnet Motor Design and Optimization by Using Artificial Neural Networks

Authors: Tugce Talay, Kadir Erkan

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In this study, the necessary steps for the design of axial flow permanent magnet motors are shown. The design and analysis of the engine were carried out based on ANSYS Maxwell program. The design parameters of the ANSYS Maxwell program and the artificial neural network system were established in MATLAB and the most efficient design parameters were found with the trained neural network. The results of the Maxwell program and the results of the artificial neural networks are compared and optimal working design parameters are found. The most efficient design parameters were submitted to the ANSYS Maxwell 3D design and the cogging torque was examined and design studies were carried out to reduce the cogging torque.

Keywords: AFPM, ANSYS Maxwell, cogging torque, design optimisation, efficiency, NNTOOL

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1851 On the Framework of Contemporary Intelligent Mathematics Underpinning Intelligent Science, Autonomous AI, and Cognitive Computers

Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

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The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

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1850 Generative AI in Higher Education: Pedagogical and Ethical Guidelines for Implementation

Authors: Judit Vilarmau

Abstract:

Generative AI is emerging rapidly and transforming higher education in many ways, occasioning new challenges and disrupting traditional models and methods. The studies and authors explored remark on the impact on the ethics, curriculum, and pedagogical methods. Students are increasingly using generative AI for study, as a virtual tutor, and as a resource for generating works and doing assignments. This point is crucial for educators to make sure that students are using generative AI with ethical considerations. Generative AI also has relevant benefits for educators and can help them personalize learning experiences and promote self-regulation. Educators must seek and explore tools like ChatGPT to innovate without forgetting an ethical and pedagogical perspective. Eighteen studies were systematically reviewed, and the findings provide implementation guidelines with pedagogical and ethical considerations.

Keywords: ethics, generative artificial intelligence, guidelines, higher education, pedagogy

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1849 Improved Artificial Bee Colony Algorithm for Non-Convex Economic Power Dispatch Problem

Authors: Badr M. Alshammari, T. Guesmi

Abstract:

This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

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1848 The Impact of Artificial Intelligence on Human Developments Obligations and Theories

Authors: Seham Elia Moussa Shenouda

Abstract:

The relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the overlap between these two views and the idea that efforts should be made in the field of human rights have increased in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. The article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which is a good answer to the question posed above. This book therefore cites regional and international human rights agreements such as , as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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1847 Technology, Organizational and Environmental Determinants of Business Intelligence Systems Adoption in Croatian SME: A Case Study of Medium-Sized Enterprise

Authors: Ana-Marija Stjepić, Luka Sušac, Dalia Suša Vugec

Abstract:

In the last few years, examples from scientific literature and business practices show that the adoption of technological innovations increases enterprises' performance. Recently, when it comes to the field of information technology innovation, business intelligence systems (BISs) have drawn a significant amount of attention of the scientific circles. BISs can be understood as a form of technological innovation which can bring certain benefits to the organizations that are adopting it. Therefore, the aim of this paper is twofold: (1) to define determinants of successful BISs adoption in small and medium enterprises and thus contribute to this neglected research area and (2) to present the current state of BISs adoption in small and medium-sized companies. In order to do so, determinants are defined and classified into three dimensions, according to the Technology – Organization – Environment (TOE) theoretical framework that describes the impact of each dimension on technological innovations adoption. Moreover, paper brings a case study presenting the adoption of BISs in practice within an organization from tertiary (service) industry sector. Based on the results of the study, guidelines for more efficient, faster and easier BISs adoption are presented.

Keywords: adoption, business intelligence, business intelligence systems, case study, TOE framework

Procedia PDF Downloads 131
1846 Churn Prediction for Telecommunication Industry Using Artificial Neural Networks

Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

Abstract:

Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

Procedia PDF Downloads 131