Search results for: moral intelligence

Authors: Tajudeen Yusuf

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Arabic Literature of Nigerian Authorship, like others, has contributed widely to the spread of morality and values in human Society. There is no doubt that the relationship between literature and society has been widely conceived, for it reflects society and serves as a means of social control. Indeed, the influence of literature on attitude and human behaviors cannot be underestimated. Focused on some selected themes and verses in a literary work of Isa Abubakar Alabi known as (Ar-Ryaadh), the paper aims to reveal the contributions of the Arabic literary icon of Nigerian origin in spreading values and morality in society through his literary works. The study employs a descriptive method. Isa Abubakar Alabi, a Nigerian Arabic scholar, is known as a wise and famous poet not only in Nigeria but throughout West Africa and Arab countries at large. He has produced a sort of poetry that is distinguished with superiority in spreading peace, harmony, societal values and morality. Indeed, his literary works address humanism, kindness, honesty, law, justice, truthfulness, and patriotism, which may positively influence humans.

Keywords: Arabic, literature, moral, Nigeria, values

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Authors: Alaa Yehia, Ayatollah Yehia, Sherif Yehia

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There is a recurring issue of low enrollments across many civil engineering departments in postsecondary institutions. While there have been moments where enrollments begin to increase, civil engineering departments find themselves facing low enrollments at around 60% over the last five years across the Middle East. There are many reasons that could be attributed to this decline, such as low entry-level salaries, over-saturation of civil engineering graduates in the job market, and a lack of construction projects due to the impending or current recession. However, this recurring problem alludes to an intrinsic issue of the curriculum. The societal shift to the usage of high technology such as machine learning (ML) and artificial intelligence (AI) demands individuals who are proficient at utilizing it. Therefore, existing curriculums must adapt to this change in order to provide an education that is suitable for potential and current students. In this paper, In order to provide potential solutions for this issue, the analysis considers two possible implementations of high technology into the civil engineering curriculum. The first approach is to implement a course that introduces applications of high technology in Civil Engineering contexts. While the other approach is to intertwine applications of high technology throughout the degree. Both approaches, however, should meet requirements of accreditation agencies. In addition to the proposed improvement in civil engineering curriculum, a different pedagogical practice must be adapted as well. The passive learning approach might not be appropriate for Gen Z students; current students, now more than ever, need to be introduced to engineering topics and practice following different learning methods to ensure they will have the necessary skills for the job market. Different learning methods that incorporate high technology applications, like AI, must be integrated throughout the curriculum to make the civil engineering degree more attractive to prospective students. Moreover, the paper provides insight on the importance and approach of adapting the Civil Engineering curriculum to address the current low enrollment crisis that civil engineering departments globally, but specifically in the Middle East, are facing.

Keywords: artificial intelligence (AI), civil engineering curriculum, high technology, low enrollment, pedagogy

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Authors: Shaibu Ali, Sherif Heiman Shaban, Musah Ismaila, Imoro Alhassan, Yusif Ali

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Purpose: Islamic banking and finance is one of the most rapidly growing segments of the global finance industry. Starting with the Dubai Islamic Bank in 1975, the number of Islamic financial institutions worldwide has shot up astronomically, to over three hundred, with operations in seventy-five countries and assets in excess of US$400 billion. The purpose of this study is to explore the prospects and challenges of Islamic banking introduction in a non-Islamic country like Ghana. Design/Methodology: Data for the study was collected via an expert opinion of three Islamic scholars on Islamic banking from Ghana. Findings: Findings from this study indicates some of the benefits of Islamic banking includes connecting financial markets and economic activity, promoting the principle of financial justice, greater stability, avoiding economic bubbles (and bursts) and reducing the impact of harmful products and practices. The study also identified lack of experts in various fields of Islamic banking, product innovation, moral hazard, and need for experienced staff in Islamic banking as some of the challenges to Islamic banking system’s introduction. Contribution: The study contributes to literature on Islamic banking from a non-Islamic country like Ghana.

Keywords: Islamic banking, Shari’ah, Riba, conventional banking

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Authors: Mohammad E. Nikoofal, Mehmet Gumus

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Besides the many benefits of outsourcing, firms are still concerned about the lack of critical information regarding both the risk levels and actions of their suppliers that are just a few links away. In this paper, we study the effectiveness of audit for the manufacturer in managing her supplier’s process improvement effort when the supplier is privately informed about his disruption risk and actions. By comparing the agency costs associated with the optimal menu of contracts with and without audit, we completely characterize the value of audit for all the cases from the perspectives of both manufacturer, and supplier as well as total supply chain. First, the analysis of value of audit from the manufacturer’s perspective shows that she can strictly benefit from auditing her supplier’s actions. To the best of our knowledge, this result has not been documented before in the principal-agent literature under a standard setting where the agent is assumed to be risk-neutral and not protected by limited liability constraints. Second, we find that not only the manufacturer but also the supplier can strictly benefit from audit. Third, the audit enables the manufacturer to customize her contract offerings based on the reliability of the supplier. Finally, by analyzing the impact of problem parameters on the value of audit, we identify the conditions under which an audit would be beneficial for individual supply chain parties as well as total supply chain.

Keywords: supply disruption, adverse selection, moral hazard incentives, audit

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Authors: Y. R. Lai, J. C. Jehng, T. T. Chang

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Team is a popular job design in the management settings. Because people on a team need to work together to complete a lot of tasks, the interaction between team members strongly influences team effectiveness. The study examines the effect of social capital and empowering leadership on team cohesion. There are three facets of social capital: structural facet, relational facet, and cognitive facet. Empowering leadership includes enhancing the meaningfulness of work, fostering participation in decision making, expressing confidence in high performance, and providing autonomy from bureaucratic constraints. Data were collected from 181 team members of 47 teams in the real estate agency industry. The results show that the relational social capital, enhancing the meaningfulness of work, and providing autonomy from bureaucratic constraints are positively related to two dimensions of team cohesion: sense of belonging and feelings of moral. Additionally, expressing confidence in high performance is negatively related to sense of belonging.

Keywords: social capital, empowering leadership, team cohesion, team effectiveness

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Authors: Ram Dayal

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Since inception of the modern Olympic Games in 1896 in Athens, Greece, it has undergone a paradigm shift over a period of more than a century. It originated with the purpose of inculcating physical and moral qualities, sense of aesthetics, ethical and spiritual value and educating young people, through the spread of the philosophy of amateurism, which is free from the vices of racial discrimination, any country’s domination, corruption, doping menace and political interference. Now, it has metamorphosed into the arena where only professionalism matters and has been reduced to the show of strength for countries analogous to the cold war. Rather than spirit of sports, the economics of sports is the more relevant underpinning. Changes in medal tally over a period of time and its correlation with the changing geo-political structure have been evaluated quantitatively using regression analyses, which have yielded statistically significant relationship among variables. The present study also tries to explore this shift in Olympic spirit through historical approach, using books, thesis, dissertations, articles, related documents. The present study will help evaluate the Olympic ideals with modern perspective and the need to replace or reinstall the same in order to nurture and rejuvenate the modern Olympic movement.

Keywords: challenges, games, olympic, sports

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Authors: Mafawez Alharbi, Mahdi Jemmali

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E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: artificial intelligence, architecture, e-learning, software engineering, processing

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Authors: Abdul Wohab

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Context: The role of religion in the transformation of Bangladesh society has been significant since 1975. There has been a rise in religious presence, particularly Islam, in both private and public spheres supported by the state apparatuses. In 2009, a 'secular' political party came into power for the second time since independence and initiated the modernization of religious education systems. This research focuses on the transformation observed among the educated middle class who now prefer their children to attend modern, English medium madrasas that offer both religion-based and secular education. Research Aim: This research aims to investigate two main questions: a) what motivates the educated middle class to send their children to madrasa education? b) To what extent can it be argued that Bangladeshi society is transforming from its secular nature to being more religious?Methodology: The research applies a combination of primary and secondary methods. Case studies serve as the primary method, allowing for an in-depth exploration of the motivations of the educated middle class. The secondary method involves analyzing published news articles, op-eds, and websites related to madrasa education, as well as studying the reading syllabus of Aliya and Qwami madrasas in Bangladesh. Findings: Preliminary findings indicate that the educated middle class chooses madrasa education for reasons such as remembering and praying for their departed relatives, keeping their children away from substance abuse, fostering moral and ethical values, and instilling respect for seniors and relatives. The research also reveals that religious education is believed to help children remain morally correct according to the Quran and Hadith. Additionally, the establishment of madrasas in Bangladesh is attributed to economic factors, with demand and supply mechanisms playing a significant role. Furthermore, the findings suggest that government-run primary education institutions in rural areas face more challenges in enrollment compared to religious educational institutions like madrasas. Theoretical Importance: This research contributes to the understanding of societal transformation and the role of religion in this process. By examining the case of Bangladesh, it provides insights into how religion influences education choices and societal values. Data Collection and Analysis Procedures: Data for this research is collected through case studies, including interviews and observations of educated middle-class families who send their children to madrasas. In addition, analysis is conducted on relevant published materials such as news articles, op-eds, and websites. The reading syllabus of Aliya and Qwami madrasas is also analyzed to gain a comprehensive understanding of the education system. Questions Addressed: The research addresses two questions: a) what motivates the educated middle class to choose madrasa education for their children? b) To what extent can it be argued that Bangladeshi society is transforming from its secular nature to being more religious?Conclusion: The preliminary findings of this research highlight the motivations of the educated middle class in opting for madrasa education, including the desire to maintain religious traditions, promote moral values, and provide a strong foundation for their children. It also suggests that Bangladeshi society is experiencing a transformation towards a more religious orientation. This research contributes to the understanding of societal changes and the role of religion within Bangladesh, shedding light on the complex dynamics between religion and education.

Keywords: madrasa education, transformation, Bangladesh, religion and society, education

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Authors: Meshandren Naidoo, Amy Gooden

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Implantable brain-computer interface (BCI) technologies have developed to the point where brain-computer communication is possible. This has great potential in the medical field, as it allows persons who have lost capacities. However, ethicists and regulators call for a strict approach to these technologies due to the impact on personhood. This research demonstrates that the personhood debate is more nuanced and that where an African approach to personhood is used, it may produce results more favorable to the development and use of this technology.

Keywords: artificial intelligence, law, neuroscience, ethics

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

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Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

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Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

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The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

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Authors: B. Karabuluter, O. Karaduman

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Traffic management and traffic planning are important issues, especially in big cities. Due to the increase of personal vehicles and the physical constraints of urban roads, the problem of transportation especially in crowded cities over time is revealed. This situation reduces the living standards, and it can put human life at risk because the vehicles such as ambulance, fire department are prevented from reaching their targets. Even if the city planners take these problems into account, emergency planning and traffic management are needed to avoid cases such as traffic congestion, intersections, traffic jams caused by traffic accidents or roadworks. In this study, in smart traffic management issues, proposed solutions using intelligent vehicles acting in cooperation with urban roads are examined. Traffic management is becoming more difficult due to factors such as fatigue, carelessness, sleeplessness, social behavior patterns, and lack of education. However, autonomous vehicles, which remove the problems caused by human weaknesses by providing driving control, are increasing the success of practicing the algorithms developed in city traffic management. Such intelligent vehicles have become an important solution in urban life by using 'swarm intelligence' algorithms and cooperative driving methods to provide traffic flow, prevent traffic accidents, and increase living standards. In this study, studies conducted in this area have been dealt with in terms of traffic jam, intersections, regulation of traffic flow, signaling, prevention of traffic accidents, cooperation and communication techniques of vehicles, fleet management, transportation of emergency vehicles. From these concepts, some taxonomies were made out of the way. This work helps to develop new solutions and algorithms for cities where intelligent vehicles that can perform cooperative driving can take place, and at the same time emphasize the trend in this area.

Keywords: intelligent traffic management, cooperative driving, smart driving, urban road, swarm intelligence, connected vehicles

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Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

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Arrival of artificial intelligence or smart robots in the modern world put them in charge on pericise and at risk. So acting human activities with robots makes criminal or civil responsibilities for their acts or behavior. The practical usage of smart robots has entered them in to a unique situation when naturalization happens and smart robots are identifies as members of society. There would be some legal situation by adopting these new smart citizens. The first situation is about legal responsibility of robots. Recognizing the naturalization of robot involves some basic right , so humans have the rights of employment, property, housing, using energy and other human rights may be employed for robots. So how would be the practice of these rights in the society and if some problems happens with these rights, how would the civil responsibility and punishment? May we consider them as population and count on the social programs? The second episode is about the criminal responsibility of robots in important activity instead of human that is the aim of inventing robots with handling works in AI technology , but the problem arises when some accidents are happened by robots who are in charge of important activities like army, surgery, transporting, judgement and so on. Moreover, recognizing independent identification for robots in the legal world by register ID cards, naturalization and civilian rights makes and prepare the same rights and obligations of human. So, the civil responsibility is not avoidable and if the robot commit a crime it would have criminal responsibility and have to be punished. The basic component of criminal responsibility may changes in so situation. For example, if designation for criminal responsibility bounds to human by sane, maturity, voluntariness, it would be for robots by being intelligent, good programming, not being hacked and so on. So it is irrational to punish robots by prisoning , execution and other human punishments for body. We may determine to make digital punishments like changing or repairing programs, exchanging some parts of its body or wreck it down completely. Finally the responsibility of the smart robot creators, programmers, the boss in chief, the organization who employed robot, the government which permitted to use robot in important bases and activities , will be analyzing and investigating in their article.

Keywords: robot, artificial intelligence, personality, responsibility

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Mirjana Đ. Laban, Dragan N. Đurica, Nemanja M. Erceg

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Volunteer fire departments (VFD) in Serbia were established as civic associations in XIX Century. The founders and members of the first VFDs were prominent members of local communities. Today, those are volunteer organizations for preventing and extinguishing fires and rescuing people and property in various accidents. The paper presents the results of research about the number and resources of active VFDs done in Autonomous Province of Vojvodina, Serbia and about activities they perform today. The survey was done based on data provided by all registered VFDs in Vojvodina. Firefighters Association of Vojvodina includes 35 municipal firefighting associations, 230 volunteer fire departments with 5,300 active members in qualified fire units and more than 15,000 supporting members. Volunteer involvement is primarily an expression of high moral values and as such it has to be respected and stimulated. Better position of the volunteers would have a major impact on the formation of safety culture concept and general public awareness of fire safety and risk reduction, and therefore the security of the society as a whole. Volunteer fire departments make a significant contribution to educate young people and prevent catastrophic consequences of fires and natural disasters.

Keywords: education, prevention, rescue, volunteer fire departments

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Authors: Shahzada Gulfam

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Islamism was considered as a new phenomenon in Muslim World to revolt against static Religious Traditionalists and the Imperialists. Islamist political parties viewed the establishment of an Islamic state within the limits of Sharia’h as their destination. The Islamists movements like Ikhwan-ul Muslimun, Jamaat-i-Islami etc. did appear with revolutionary agenda but were contained by military forces and the secular modernists of Muslim World. The Muslim rulers, historically could not respect the democratic and moral norms and equally emerged as dictators in democracies, military rule as well as in monarchies. The Arab Spring did not follow the Islamists agenda but gathered the common masses against the corrupt rulers to have a just democratic political system. The Islamic State and Sharia’h were not their immediate targets but the achievement of moral norms in Muslim societies and eradication of dictatorial rule were the basic aims. This phenomenon is named as post-Islamism. The political struggle of PAT (Pakistan Awami Tehreek) and the PTI (Pakistan Tehreek-i-Insaf) has been following the footsteps of Arab Spring and can be noted as the extension of Arab Spring in Muslim World. The results of this struggle would define the fate of Post-Islamism in Pakistan. Has Jamaat-i-Islami got the potential to reform its agenda accordingly? This paper intends to study the Jamaat’s struggle and tries to predict Jamaat’s role in post-Islamism scenario. There is a clear distinction between the people of religion and the people following the popular materialistic westernized value system. This division is also evident in political parties. Pakistan has been ruled mostly by the secular parties and rulers. The inability to establish Islamic system by replacing the imperial system has created militancy and revolt which requires the establishment of a sound model Islamic based system in the country. The political parties of Pakistan could not device a modernize agenda, equally acceptable in modernized world and addressing the prevailing issues and also having the indigenous religious and cultural roots. The inability of Jamaat-i-Islami Pakistan to transform its agenda accordingly to serve the post-Islamism has made it irrelevant in Pakistan’s politics. Once Jamaat leaves behind its hard position as an Islamist party and accepts the post-Islamism as beginning to create its idealized state and society, it can pursue its agenda gradually. The phenomenon of post-Islamism does not make Islamists irrelevant but invites them to listen to the priorities of masses rather than insisting on the agenda of their respective ideologues to be followed for all times. The ruling Muslim democrats and military dictators of Pakistan have been following unfair means to sustain their political power which gave rise to space for the new political parties to emerge and organize agitation successfully in Pakistani Politics. Jamaat-i-Islami could not fill that space to be an agent of Post-Islamism and could not break their chains which had been tying them to the prevailing failed democracy of Pakistan. Post-Islamists are the addressers of the rulers corruption and are struggling for reforms in system. Jamaat due to its ideological compulsions could not transform its agenda accordingly. The new scenario indicates that the Post-Islamism which emerged in Arab World can be taken as first step to establish democracy and justice in state and society and then the establishment of Islamic law and the establishment of an Islamic state should have been the next targets. This gradual agenda would have delivered public support to the Jamaat which deserved that but PTI & PAT have cashed this opportunity in Pakistani politics by strengthening their respective vote banks.

Keywords: arab spring, islamic state, islamic political parties, muslim world, post-islamism

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Authors: Biniam Bahiru Tufa, Hana Delil Tesfaye, Seife Demisse Legesse, Manaye Tamire

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The healthcare industry is witnessing a digital transformation, with artificial intelligence (AI) offering potential solutions for challenges in health supply chain management (HSCM). However, the adoption of AI in this field remains limited. This research aimed to assess the knowledge, attitude, and practice of AI among students and employees in the health supply chain sector in Ethiopia. Using an explanatory case study research design with a concurrent mixed approach, quantitative and qualitative data were collected simultaneously. The study included 153 participants comprising students and employed health supply chain professionals working in various sectors. The majority had a pharmacy background, and one-third of the participants were male. Most respondents were under 35 years old, and around 68.6% had less than 10 years of experience. The findings revealed that 94.1% of participants had prior knowledge of AI, but only 35.3% were aware of its application in the supply chain. Moreover, the majority indicated that their training curriculum did not cover AI in health supply chain management. Participants generally held positive attitudes toward the necessity of AI for improving efficiency, effectiveness, and cost savings in the supply chain. However, many expressed concerns about its impact on job security and satisfaction, considering it as a burden Graduate students demonstrated higher knowledge of AI compared to employed staff, while graduate students also exhibited a more positive attitude toward AI. The study indicated low previous utilization and potential future utilization of AI in the health supply chain, suggesting untapped opportunities for improvement. Overall, while supply chain experts and graduate students lacked sufficient understanding of AI and its significance, they expressed favorable views regarding its implementation in the sector. The study recommends that the Ethiopian government and international organizations consider introducing AI in the undergraduate pharmacy curriculum and promote its integration into the health supply chain field.

Keywords: knowledge, attitude, practice, supply chain, articifial intellegence

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Authors: Mikko Salminen, Niklas Ravaja

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Emotional intelligence (EI) consists of skills for monitoring own emotions and emotions of others, skills for discriminating different emotions, and skills for using this information in thinking and actions. EI enhances, for example, work outcomes and organizational climate. We suggest that the role and manifestations of EI should also be studied in real leadership situations, especially during the emotional, social interaction. Leadership is essentially a process to influence others for reaching a certain goal. This influencing happens by managerial processes and computer-mediated communication (e.g. e-mail) but also by face-to-face, where facial expressions have a significant role in conveying emotional information. Persons with high EI are typically perceived more positively, and they have better social skills. We hypothesize, that during social interaction high EI enhances the ability to detect other’s emotional state and controlling own emotional expressions. We suggest, that emotionally intelligent leader’s experience less stress during social leadership situations, since they have better skills in dealing with the related emotional work. Thus the high-EI leaders would be more able to enjoy these situations, but also be more efficient in choosing appropriate expressions for building constructive dialogue. We suggest, that emotionally intelligent leaders show more positive emotional expressions than low-EI leaders. To study these hypotheses we observed performance review discussions of 40 leaders (24 female) with 78 (45 female) of their followers. Each leader held a discussion with two followers. Psychophysiological methods were chosen because they provide objective and continuous data from the whole duration of the discussions. We recorded sweating of the hands (electrodermal activation) by electrodes placed to the fingers of the non-dominant hand to assess the stress-related physiological arousal of the leaders. In addition, facial electromyography was recorded from cheek (zygomaticus major, activated during e.g. smiling) and periocular (orbicularis oculi, activated during smiling) muscles using electrode pairs placed on the left side of the face. Leader’s trait EI was measured with a 360 questionnaire, filled by each leader’s followers, peers, managers and by themselves. High-EI leaders had less sweating of the hands (p = .007) than the low-EI leaders. It is thus suggested that the high-EI leaders experienced less physiological stress during the discussions. Also, high scores in the factor “Using of emotions” were related to more facial muscle activation indicating positive emotional expressions (cheek muscle: p = .048; periocular muscle: p = .076, almost statistically significant). The results imply that emotionally intelligent managers are positively relaxed during s social leadership situations such as a performance review discussion. The current study also highlights the importance of EI in face-to-face social interaction, given the central role facial expressions have in interaction situations. The study also offers new insight to the biological basis of trait EI. It is suggested that the identification, forming, and intelligently using of facial expressions are skills that could be trained during leadership development courses.

Keywords: emotional intelligence, leadership, performance review discussion, psychophysiology, social interaction

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Authors: Fung Sze Wai Veera, Peter W. Ferretto

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Gender functions as a principle in organizing society based on the cultural meanings given to males and females. It is an essential component in constructing the spatial reality, one that is in most cases in favor of men’s needs and disregards that of women’s. Similar to other minorities in China, men of the Dong community hold the primary position in policymaking, moral standards, social values, and, furthermore, the building of the physical environment. This study, therefore, aims to investigate the residential architecture of Dong through the lens of gender. Specifically, it examines how the patriarchal practice of Dong is manifested in terms of the spatial organization, the architectural feature, and the construction process of Dong houses in the southern dialect areas. While the residential architecture of Dong has been extensively researched, the role of gender culture in designing and constructing it deserves more research attention. Ultimately, the objective of this study is to challenge the notion of gender-inclusive design in the rural China context while opening up a cross-disciplinary discussion concerning Chinese minority architecture and gender studies.

Keywords: Dong minority residential architecture, gender study, built environment, male-dominated society, gender-inclusive design

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Ilyes Athimni, Mouna Bouzazi, Mongi Boulehmi, Ahmed Ferchichi

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The principles of good governance, universal values, and digitization are among the tools to fight corruption and improve the quality of service delivery. In recent years, these tools have become one of the most controversial topics in the field of education and a concern of many international organizations and institutions against the problem of corruption. Corruption in the education sector, particularly in higher education, has negative impacts on the quality of education systems and on the quality of administrative or educational services. Currently, the health crisis due to the spread of the COVID-19 pandemic reveals the difficulties encountered by education systems in most countries of the world. Due to the poor governance of these systems, many educational institutions were unable to continue working remotely. To respond to these problems encountered by most education systems in many countries of the world, our initiative is to propose a methodology to reinvent education systems based on global values and digital technologies. This methodology includes a work strategy for educational institutions, whether in the provision of administrative services or in the teaching method, based on information and communication technologies (ICTs), intelligence artificial, and intelligent agents. In addition, we will propose a supervisory law that will be implemented and monitored by intelligent agents to improve accountability, transparency, and accountability in educational institutions. On the other hand, we will implement and evaluate a field experience by applying the proposed methodology in the operation of an educational institution and comparing it to the traditional methodology through the results of teaching an educational program. With these specifications, we can reinvent quality education systems. We also expect the results of our proposal to play an important role at local, regional, and international levels in motivating governments of countries around the world to change their university governance policies.

Keywords: artificial intelligence, corruption in education, distance learning, education systems, ICTs, intelligent agents, good governance

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Authors: Gianni Izzo

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The relation of Islam to its legal precepts, reflected in the various jurisprudential 'schools of thought' (madhahib), is one expressed in a version of 'positivism' (fiqh) providing the primary theory for deducing Qurʾan rulings and those from the narrations (hadith) of the Prophet Muhammad. Scholars of Islam, including Patricia Crone (2004) and others chronicled by Anver Emon (2005), deny the influence of natural law theories as extra-scriptural indices of revelation’s content. This paper seeks to dispute these claims by reference to historical and canonical examples within Shiʿa legal thought that emphasize the salient roles of ‘aql (reason), fitrah (primordial human nature), and lutf (divine grace). These three holistic features, congenital to every human, and theophanically reflected in nature make up a mode of moral intelligibility antecedent to prophetic revelation. The debate between the 'traditionalist' Akhbaris and 'rationalist' Usulis over the nature of deriving legal edicts in Islam is well-covered academic ground. Instead, an attempt is made to define and detail the built-in assumptions of natural law revealed in the jurisprudential summa of Imami Shiʿism, whether of either dominant school, that undergird its legal prescriptions and methods of deduction.

Keywords: Islam, fiqh, natural law, legal positivism, aql

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Authors: Carlos Joel Tchawouo Mbiada

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This paper intends to refrain from debating the different meanings of justice, such as its social or moral meaning, nor to discuss the different theories of justice. This paper focuses on the legal understanding of access to justice to mean access to the court. Using the Labour and Labour Appeal Courts as a case study, this paper investigates whether the composition of the bench, the personnel and state mechanisms to promote access to court offer ideal conditions to access to court. The investigation is benchmarked against the South African new constitutional order underpinned by the concept of social justice to eradicate past injustices. To provide justice to all, the Constitution of the Republic of South Africa 1996 guarantees the right to access to the court. The question that takes centre stage in this paper is whether litigants are denied the right to access the Labour and Labour Appeal Courts. The paper argues that factors such as the status of the Labour and Labour Appeal Courts, the number of judges, and the building structure prevent litigants from accessing these courts. The paper advocates for a legislative overhaul of the Labour and Labour Appeal Courts structure so that litigants may access the courts. Until such time, the paper argues that the right to access the Labour and Labour Appeal Courts would remain far from the reach of many litigants.

Keywords: access to justice, access to court, labour court, labour appeal court

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Authors: Adelaja O. Oriade

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The Nigerian hip-hop music genre, like the African American scene where it was adopted from, is riddled with musical lyrics that amplify and normalize hypermasculinity, homophobia, sexism, and objectification of women. Several factors are responsible for this anomaly; however, the greatest factor is the urge of hip-hop musicians to achieve the commercial success that is dependent on selling records and appealing to the established societal accepted norm for hip-hop music. Consequently, this paper presents a counter-narrative of this gender representation within the Nigerian hip-hop industry. This study analyzed the musical lyrics of the ‘Hypocrisy’ track on the 2019 album of famous Nigerian rapper, Falz the Bahd Guy; and argued that Falz in this album challenged the predominant ideas of hegemonic masculinity by singing in favor of LGBT people and women. Also, based on the success of this album, this paper argues that a hip-hop album can achieve commercial success without aligning with predominant hip-hop parameters of gender representation. The study recommends that future studies should evaluate the reactions of Nigerians to these gender presentations by Falz the Bahd guy.

Keywords: hegemonic masculinity, hypermasculinity, LGBT, misogyny, sexism

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Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

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Authors: A. Badran, M. Hollocks, H. Markus

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Background: Common risk factors for cardiovascular disease are associated with age-related cognitive decline. There has been much interest in treating modifiable cardiovascular risk factors in the hope of reducing cognitive decline. However, there is currently no validated neuropsychological test to assess the subclinical cognitive effects of vascular risk. The Brief Memory and Executive Test (BMET) is a clinical screening tool, which was originally designed to be sensitive and specific to Vascular Cognitive Impairment (VCI), an impairment characterised by decline in frontally-mediated cognitive functions (e.g. Executive Function and Processing Speed). Objective: To cross-sectionally assess the validity of the BMET as a measure of the subclinical effects of vascular risk on cognition, in an otherwise healthy elderly cohort. Methods: Data from 346 participants (57 ± 10 years) without major neurological or psychiatric disorders were included in this study, gathered as part of a previous multicentre validation study for the BMET. Framingham Vascular Age was used as a surrogate measure of vascular risk, incorporating several established risk factors. Principal Components Analysis of the subtests was used to produce common constructs: an index for Memory and another for Executive Function/Processing Speed. Univariate General Linear models were used to relate Vascular Age to performance on Executive Function/Processing Speed and Memory subtests of the BMET, adjusting for Age, Premorbid Intelligence and Ethnicity. Results: Adverse vascular risk was associated with poorer performance on both the Memory and Executive Function/Processing Speed indices, adjusted for Age, Premorbid Intelligence and Ethnicity (p=0.011 and p<0.001, respectively). Conclusions: Performance on the BMET reflects the subclinical effects of vascular risk on cognition, in age-related cognitive decline. Vascular risk is associated with decline in both Executive Function/Processing Speed and Memory groups of subtests. Future studies are needed to explore whether treating vascular risk factors can effectively reduce age-related cognitive decline.

Keywords: age-related cognitive decline, vascular cognitive impairment, subclinical cerebrovascular disease, cognitive aging

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Authors: Arnaud Deshais

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The supply chain industry has integrated the need for supplier Diversity and Inclusion (D&I), mostly from an ethical and moral argument. In addition, in some countries, it is also a legal requirement for companies reaching a certain size. As a matter of fact, a lot of successful companies have developed a Corporate Social Responsibility Program that encourages diversity and inclusion in the supply chain, such as building strong relationships with minority owned businesses (women, LGBT, veterans, etc.). Outside ethical and legal perspectives, it is also worth researching the economic and financial benefits of pursuing such efforts. Through surveys of purchasing and supply chain managers in their current roles as well as review of some case studies on supplier based D&I programs, it becomes apparent that a financial return on investment is to be expected as well for companies who make a concerted effort to grow their D&I programs. The study explores the levers to increase shareholder value and business efficiencies. Finally, the research highlights the competitive advantage related to a broad minority based supplier network. The benefits manifest themselves in the areas of competitiveness, innovation, and collaboration. The economic reward ends up being at the forefront of those programs while being an opportunity for organizations to become 'a good citizen'.

Keywords: diversity, inclusion, purchasing, supplier

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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