Search results for: artificial intelligence in finance

Authors: Zongping Wang, Chengjun Cui, Jiacun Wang

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The concept of intelligence has been widely used to access an individual's cognitive abilities to learn, form concepts, understand, apply logic, and reason. According to the multiple intelligence theory, there are eight distinguished types of intelligence. One of them is the bodily-kinaesthetic intelligence that links to the capacity of an individual controlling his body and working with objects. Motor intelligence, on the other hand, reflects the capacity to understand, perceive and solve functional problems by motor behavior. Both bodily-kinaesthetic intelligence and motor intelligence refer directly or indirectly to bodily capacity. Inspired by these two intelligence concepts, this paper introduces motional intelligence (MI). MI is two-fold. (1) Body strength, which is the capacity of various organ functions manifested by muscle activity under the control of the central nervous system during physical exercises. It can be measured by the magnitude of muscle contraction force, the frequency of repeating a movement, the time to finish a movement of body position, the duration to maintain muscles in a working status, etc. Body strength reflects the objective of MI. (2) Level of psychiatric willingness to physical events. It is a subjective thing and determined by an individual’s self-consciousness to physical events and resistance to fatigue. As such, we call it subjective MI. Subjective MI can be improved through education and proper social events. The improvement of subjective MI can lead to that of objective MI. A quantitative score of an individual’s MI is motional quotient (MQ). MQ is affected by several factors, including genetics, physical training, diet and lifestyle, family and social environment, and personal awareness of the importance of physical exercise. Genes determine one’s body strength potential. Physical training, in general, makes people stronger, faster and swifter. Diet and lifestyle have a direct impact on health. Family and social environment largely affect one’s passion for physical activities, so does personal awareness of the importance of physical exercise. The key to the success of the MQ study is developing an acceptable and efficient system that can be used to assess MQ objectively and quantitatively. We should apply different accessing systems to different groups of people according to their ages and genders. Field test, laboratory test and questionnaire are among essential components of MQ assessment. A scientific interpretation of MQ score is part of an MQ assessment system as it will help an individual to improve his MQ. IQ (intelligence quotient) and EQ (emotional quotient) and their test have been studied intensively. We argue that IQ and EQ study alone is not sufficient for an individual’s all round development. The significance of MQ study is that it offsets IQ and EQ study. MQ reflects an individual’s mental level as well as bodily level of intelligence in physical activities. It is well-known that the American Springfield College seal includes the Luther Gulick triangle with the words “spirit,” “mind,” and “body” written within it. MQ, together with IQ and EQ, echoes this education philosophy. Since its inception in 2012, the MQ research has spread rapidly in China. By now, six prestigious universities in China have established research centers on MQ and its assessment.

Keywords: motional Intelligence, motional quotient, multiple intelligence, motor intelligence, all round development

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Authors: Peter Shi

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Algorithmic trading is a rapidly expanding domain within quantitative finance, constituting a substantial portion of trading volumes in the US financial market. The demand for rigorous and robust mathematical theories underpinning these trading algorithms is ever-growing. In this study, the author establishes a new stock market model that integrates the Efficient Market Hypothesis and the statistical arbitrage. The model, for the first time, finds probabilistic relations between the rational price and the market price in terms of the conditional expectation. The theory consequently leads to a mathematical justification of the old market adage: buy-low and sell-high. The thresholds for “low” and “high” are precisely derived using a max-min operation on Bayes’s error. This explicit connection harmonizes the Efficient Market Hypothesis and Statistical Arbitrage, demonstrating their compatibility in explaining market dynamics. The amalgamation represents a pioneering contribution to quantitative finance. The study culminates in comprehensive numerical tests using historical market data, affirming that the “buy-low” and “sell-high” algorithm derived from this theory significantly outperforms the general market over the long term in four out of six distinct market environments.

Keywords: efficient market hypothesis, behavioral finance, Bayes' decision, algorithmic trading, risk control, stock market

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Authors: Raja Omman Zafar, Yves Rybarczyk, Johan Borg

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This article proposes a conceptual framework for the application of digital twin technology in home care. The main goal is to bridge the gap between advanced digital twin concepts and their practical implementation in home care. This study uses a literature review and thematic analysis approach to synthesize existing knowledge and proposes a structured framework suitable for homecare applications. The proposed framework integrates key components such as IoT sensors, data-driven models, cloud computing, and user interface design, highlighting the importance of personalized and predictive homecare solutions. This framework can significantly improve the efficiency, accuracy, and reliability of homecare services. It paves the way for the implementation of digital twins in home care, promoting real-time monitoring, early intervention, and better outcomes.

Keywords: digital twin, homecare, older adults, healthcare, IoT, artificial intelligence

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Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

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This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

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Authors: Laidi Maamar, Hanini Salah

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The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: Sabir Messalti, Bilal Boudjellal, Azouz Said

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In this paper, power system Voltage improvement using wind turbine is presented. Two controllers are used: a PI controller and Artificial Neural Networks (ANN) controllers are studied to control of the power flow exchanged between the wind turbine and the power system in order to improve the bus voltage. The wind turbine is based on a doubly-fed induction generator (DFIG) controlled by field-oriented control. Indirect control is used to control of the reactive power flow exchanged between the DFIG and the power system. The proposed controllers are tested on power system for large voltage disturbances.

Keywords: artificial neural networks controller, DFIG, field-oriented control, PI controller, power system voltage improvement

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Authors: Mustafa Tosun, Kevser Dincer

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In this study, analysis on whether the lightweight concrete walled structures used in four climatic regions of Turkey are also capable of insulating sound was conducted. As a new approach, first the wall’s thermal insulation sufficiency’s were calculated and then, artificial neural network (ANN) modeling was used on their cross sections to check if they are sound transmitters too. The ANN was trained and tested by using MATLAB toolbox on a personal computer. ANN input parameters that used were thickness of lightweight concrete wall, frequency and density of lightweight concrete wall, while the transmitted sound was the output parameter. When the results of the TS analysis and those of ANN modeling are evaluated together, it is found from this study, that sound transmit loss increases at higher frequencies, higher wall densities and with larger wall cross sections.

Keywords: artificial neuron network, lightweight concrete, sound insulation, sound transmit loss

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Authors: Shola Abidemi Olabode

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The technological revolution over the years has impacted journalistic practice. As a matter of fact, journalistic practice has evolved alongside technologies of every generation transforming news and reporting, entertainment, and politics. Alongside these developments, the emergence of new kinds of risks and harms associated with generative AI has become rife with implications for media and journalism. Despite their numerous benefits for research and development, generative AI technologies like ChatGPT introduce new practical, ethical, and regulatory complexities in the practice of media and journalism. This paper presents a preliminary overview of the new kinds of challenges and issues for journalism and media practice in the era of generative AI, the implications for Nigeria, and invites a consideration of methods to mitigate the evolving complexity. It draws mainly on desk-based research underscoring the literature in both developed and developing non-western contexts as a contribution to knowledge.

Keywords: AI, journalism, media, online harms

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Authors: M. Azugama, P. Okoro Ugo Chigozie, A. O. Nnamocha

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Emotional Intelligence constitutes powerful psychological forces that can strongly influence performance in behaviour, interaction and relationship management. Surprisingly how emotions are interpreted and employed in marketing of hospitality experience have had limited comprehension. Marketing of hospitality experiences have important emotional dimensions which the traditional marketing techniques tend to underplay. Guest and host relationship are challenged by mutual hospitableness obligations; suggesting that the commercial practice of delivering satisfactory guest experience has much to gain from traditional understanding of hospitality. By understanding the emotion-based hospitality transaction between guests and hosts, customers’ experiences can be delivered over and against competitor pressure. In this paper, marketing strategies and tactics in hospitality and tourism are principally concerned with adjusting each of the 6P & T elements (i.e. product, place, price and promotion; and adding people, processes and Time in service contexts), to provide a competitive offer (experience) to customers.

Keywords: Emotional intelligence, hospitality and tourism, relationship management, marketing

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Authors: Andri Ottesen, Sam Toglaw, Mirna Safa

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Entrepreneurial companies on their developing path from an idea to a corporation go through a similar six-step process. Each of these six development steps is supported by a distinctive financing path. This paper explores the Kuwait model for Entrepreneurial Finance and Development through in-depth interviews with ten successful Kuwaiti entrepreneurs. This paper offers insight into the development and financing of entrepreneurial companies in this oil-rich, predominantly Islamic country that are in many ways different from the steps. Western entrepreneurial companies go through. This model could be used to understand the commonalities and the difference between entrepreneurial development and financing and could be used to bridge the gap.

Keywords: entrepreneurial-financing, entrepreneurial-developing, Kuwait, Vancouver school

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Authors: Diane Ghanem, Oscar Covarrubias, Michael Raad, Dawn LaPorte, Babar Shafiq

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Introduction: Standardized exams have long been considered a cornerstone in measuring cognitive competency and academic achievement. Their fixed nature and predetermined scoring methods offer a consistent yardstick for gauging intellectual acumen across diverse demographics. Consequently, the performance of artificial intelligence (AI) in this context presents a rich, yet unexplored terrain for quantifying AI's understanding of complex cognitive tasks and simulating human-like problem-solving skills. Publicly available AI language models such as ChatGPT have demonstrated utility in text generation and even problem-solving when provided with clear instructions. Amidst this transformative shift, the aim of this study is to assess ChatGPT’s performance on the orthopaedic surgery in-training examination (OITE). Methods: All 213 OITE 2021 web-based questions were retrieved from the AAOS-ResStudy website. Two independent reviewers copied and pasted the questions and response options into ChatGPT Plus (version 4.0) and recorded the generated answers. All media-containing questions were flagged and carefully examined. Twelve OITE media-containing questions that relied purely on images (clinical pictures, radiographs, MRIs, CT scans) and could not be rationalized from the clinical presentation were excluded. Cohen’s Kappa coefficient was used to examine the agreement of ChatGPT-generated responses between reviewers. Descriptive statistics were used to summarize the performance (% correct) of ChatGPT Plus. The 2021 norm table was used to compare ChatGPT Plus’ performance on the OITE to national orthopaedic surgery residents in that same year. Results: A total of 201 were evaluated by ChatGPT Plus. Excellent agreement was observed between raters for the 201 ChatGPT-generated responses, with a Cohen’s Kappa coefficient of 0.947. 45.8% (92/201) were media-containing questions. ChatGPT had an average overall score of 61.2% (123/201). Its score was 64.2% (70/109) on non-media questions. When compared to the performance of all national orthopaedic surgery residents in 2021, ChatGPT Plus performed at the level of an average PGY3. Discussion: ChatGPT Plus is able to pass the OITE with a satisfactory overall score of 61.2%, ranking at the level of third-year orthopaedic surgery residents. More importantly, it provided logical reasoning and justifications that may help residents grasp evidence-based information and improve their understanding of OITE cases and general orthopaedic principles. With further improvements, AI language models, such as ChatGPT, may become valuable interactive learning tools in resident education, although further studies are still needed to examine their efficacy and impact on long-term learning and OITE/ABOS performance.

Keywords: artificial intelligence, ChatGPT, orthopaedic in-training examination, OITE, orthopedic surgery, standardized testing

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Authors: L. Ramirez, E. Guillén, J. Sánchez

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Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: analytics, telemedicine, internet of things, cloud computing

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Authors: Monika Paleczna, Małgorzata Holda

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Choosing an avatar's gender in a computer game is one of the key elements in the process of creating an online identity. The selection of a male or female avatar can define the entirety of subsequent decisions regarding both appearance and behavior. However, when the most popular games available for the Nintendo console in 1998 were analyzed, it turned out that 41% of computer games did not have female characters. Nowadays, players create their avatars based mainly on binary gender classification, with male and female characters to choose from. The main aim of the poster is to explore gender differences in adolescent avatars. 130 adolescents aged 15-17 participated in the study. They created their avatars and then played a computer game. The creation of the avatar was based on the choice of gender, then physical and mental characteristics. Data on gender consistency (consistency between participant’s sex and gender selected for the avatar) and masculinity-femininity of avatar nicknames and appearance will be presented. The masculinity-femininity of avatar nicknames and appearance was assessed by expert raters on a very masculine to very feminine scale. Additionally, data on the relationships of the perceived levels of masculinity-femininity with hostility-friendliness and the intelligence of avatars will be shown. The dimensions of hostility-friendliness and intelligence were also assessed by expert raters on scales ranging from very hostile to very friendly and from very low intelligence to very high intelligence.

Keywords: gender, avatar, adolescence, computer games

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Authors: Najla Althuniyan

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Online discussions take place across different platforms. These discussions have the potential to extract crowd wisdom and capture the collective intelligence from a different perspective. However, certain phenomena, such as controversy, often appear in online argumentation that makes the discussion between participants heated. Heated discussions can be used to extract new knowledge. Therefore, detecting the presence of controversy is an essential task to determine if collective intelligence can be extracted from online discussions. This paper uses existing measures for estimating controversy quantitatively in cyber-argumentation. First, it defines controversy in different fields, and then it identifies the attributes of controversy in online discussions. The distributions of user opinions and the distance between opinions are used to calculate the controversial degree of a discussion. Finally, the results from each controversy measure are discussed and analyzed using an empirical study generated by a cyber-argumentation tool. This is an improvement over the existing measurements because it does not require ground-truth data or specific settings and can be adapted to distribution-based or distance-based opinions.

Keywords: online argumentation, controversy, collective intelligence, agreement analysis, collaborative decision-making, fuzzy logic

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Authors: Babak Salekmahdy

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Microfinance is often seen as a means of repairing credit markets and unleashing the potential contribution of impoverished people who rely on self-employment. Since the 1990s, the microfinance industry has expanded rapidly, opening the path for additional kinds of social entrepreneurship and social investment. However, current data indicate relatively few average consumer effects, opposing pushback against microfinance. This research reconsiders microfinance statements, stressing the variety of data on impacts and the essential (but limited) role of reimbursements. The report finishes by explaining a shift in thinking: from microfinance as a strictly defined enterprise finance to microfinance as a more widely defined home finance. Microfinance, under this perspective, provides advantages by providing liquidity for various requirements rather than just by increasing income.

Keywords: microfinance, small business, economic development, credit markets

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Authors: Meruyert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova, Madina Ermaganbetova

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This research paper explores the process of creating a proctoring system by evaluating the implementation of practical face recognition algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As an outcome, a proctoring system will be created, enabling the conduction of tests and ensuring academic integrity checks within the system. Due to the correct operation of the system, test works are carried out. The result of the creation of the proctoring system will be the basis for the automation of the informational, educational portal developed by machine learning.

Keywords: artificial intelligence, education portal, face recognition, machine learning, proctoring

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Authors: Mahfoud Djebbar

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Stock dilution is a financial phenomenon resulting from the issue of additional shares by a company, or when holders convert their convertibles into new shares (capital increase). This issue and/or conversion enlarge the company’s share base that will result in marginal dilution (loss) for existing shareholders, and a benefit to new ones. Dilution issues have already been addressed in mainstream finance, particularly as far as information disclosure is concerned. However, in Islamic finance, stock dilution problems have not been deeply studied and the subject has not received sufficient attention from shariah-compatible firms, investors, and scholars. In this regard, this paper emphasises the forms, the effects of capital dilution on current shareholders as well as the ways and techniques of compensating them. And since the research in this field, in its Islamic perspective, is still in its infancy, the paper tries to analyse the phenomenon theoretically in detail using numerical examples, and expose some case studies of Shariah-compliant issuers of convertible Sukuk and how they compensate their existing shareholders. Finally, this study shows that the Sukuk issuers compensate old shareholders using the right of shuf’ah as a well known and practiced pre-emptive right in Islamic transactions centuries ago, as well as the ways conventional bond issuers use.

Keywords: compensating shareholders, convertible Sukuk, Islamic financial innovation, Shuf’ah

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Authors: Abdullah Bajelan, Adel Akbarimajd

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Object manipulation techniques in robotics can be categorized in two major groups including manipulation with grasp and manipulation without grasp. The original aim of this paper is to develop an object manipulation method where in addition to being grasp-less, the manipulation task is done in a passive approach. In this method, linear and angular positions of the object are changed and its manipulation path is controlled. The manipulation path is a helix track with constant radius and incline. The method presented in this paper proposes a system which has not the actuator and the active controller. So this system requires a passive mechanical intelligence to convey the object from the status of the source along the specified path to the goal state. This intelligent is created based on utilizing the geometry of the system components. A general set up for the components of the system is considered to satisfy the required conditions. Then after kinematical analysis, detailed dimensions and geometry of the mechanism is obtained. The kinematical results are verified by simulation in ADAMS.

Keywords: mechanical intelligence, object manipulation, passive mechanism, passive non-prehensile manipulation

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Authors: Fusun Akdag

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Today, as business becomes increasingly global, managers/leaders of multinational companies or local companies work with employees or customers from a variety of cultural backgrounds. To do this effectively, they need to develop cultural competence. Therefore, cultural intelligence (CQ) becomes a vitally important aptitude and skill, especially for leaders. The organizational success or failure depends upon the way, the kind of leadership which has been provided to its members. The culture we are born into deeply effects our values, beliefs, and behavior. Cultural intelligence (CQ) focuses on how well individuals can relate and work across cultures. CQ helps minimize conflict and maximize performance of a diverse workforce. The term 'decision,' refers to a commitment to a course of action that is intended to serve the interests and values of particular people. One dimension of culture that has received attention is individualism-collectivism or, independence-interdependence. These dimensions are associated with different conceptualizations of the 'self.' Individualistic cultures tend to value personal goal pursuit as opposed to pursuit of others’ goals. Collectivistic cultures, by contrast, view the 'self' as part of a whole. Each person is expected to work with his or her in-group toward goals, generally pursue group harmony. These differences underlie cross-cultural variation in decision-making, such as the decision modes people use, their preferences, negotiation styles, creativity, and more. The aim of this study is determining the effect of CQ on decision making styles of male and female managers in Turkey, an emergent economy framework. The survey is distributed to gather data from managers at various companies. The questionnaire consists of three parts: demographics, The Cultural Intelligence Scale (CQS) to measure the four dimensions of cultural intelligence and General Decision Making Style (GMDS) Inventory to measure the five subscales of decision making. The results will indicate the Turkish managers’ score at metacognitive, cognitive, motivational and behavioral aspects of cultural intelligence and to what extent these scores affect their rational, avoidant, dependent, intuitive and spontaneous decision making styles since business leaders make dozens of decisions every day that influence the success of the company and also having an impact on employees, customers, shareholders and the market.

Keywords: cultural intelligence, decision making, gender differences, management styles,

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Authors: Mohammad Abdullah-Al-Wadud

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In the current era of automation and artificial intelligence, different systems have been increasingly keeping on depending on decision-making capabilities of machines. Such systems/applications may range from simple classifiers to sophisticated surveillance systems based on traditional sensors and related equipment which are becoming more common in the internet of things (IoT) paradigm. However, the available data for such problems are usually imprecise and incomplete, which leads to uncertainty in decisions made based on traditional probability-based classifiers. This requires a robust fusion framework to combine the available information sources with some degree of certainty. The theory of evidence can provide with such a method for combining evidence from different (may be unreliable) sources/observers. This talk will address the employment of the Dempster-Shafer Theory of evidence in some practical applications.

Keywords: decision making, dempster-shafer theory, evidence fusion, incomplete data, uncertainty

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Zareen Khan

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Islamic Banking has experienced high growth in Pakistan in recent years and has successfully survived the economic downturn of 2009-2011. Despite the increase in branch network and expansion of services, it is unclear if Islamic banks are truly following the theory and practical application of Shariah Law. This paper explores the theological basis of Islamic finance and examines the discrepancies between the theory and practice of Islamic banking using Pakistan as a case study. It discusses areas where Islamic banks lack proper Shariah compliance and analyzes the financial weaknesses of Islamic banks in terms of the services offered. Furthermore, the paper offers plausible explanations for the clientele of Islamic banks. The case study has three major findings. Firstly, most of the employees of Islamic banks come from conventional banking backgrounds and the banks have to invest in additional trainings to specialize employees in Islamic Banking. Secondly despite the efforts of State Bank of Pakistan, there is a lack of accounting and auditing standards tailored for Islamic Banking. Thirdly, majority of the clients of Islamic banks in Pakistan are accustomed to conventional banking causing the bankers to “speak the conventional banking language.” Combined, these three factors can create gaps in the practical application of Islamic finance in Islamic banks in Pakistan.

Keywords: islamic finance, comparing theory with practice, islamic banking, Pakistan

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Lei Wang, Jiahao Zhou

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The development of heterogeneous computing clusters provides a strong computility guarantee for large-scale workflows (e.g., scientific computing, artificial intelligence (AI), etc.). However, the tasks within large-scale workflows have also gradually become heterogeneous due to different demands on computing resources, which leads to the addition of a task resource-restricted constraint to the workflow scheduling problem on heterogeneous computing platforms. In this paper, we propose a heterogeneous constrained minimum makespan scheduling algorithm based on the idea of greedy strategy, which provides an efficient solution to the heterogeneous workflow scheduling problem in a heterogeneous platform. In this paper, we test the effectiveness of our proposed scheduling algorithm by randomly generating heterogeneous workflows with heterogeneous computing platform, and the experiments show that our method improves 15.2% over the state-of-the-art methods.

Keywords: heterogeneous computing, workflow scheduling, constrained resources, minimal makespan

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Authors: Ayanda P. Deliwe, Storm B. Watson

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The COVID-19 pandemic has disrupted the established practices of higher education institutions (HEIs). Most higher education institutions worldwide had to shift from traditional face-to-face to online learning. The online environment and new online tools are disrupting the way in which higher education is presented. Furthermore, the structures of higher education institutions have been impacted by rapid advancements in information and communication technologies. Emerging technologies should not be viewed in a negative light because, as opposed to the traditional curriculum that worked to create productive and efficient researchers, emerging technologies encourage creativity and innovation. Therefore, using technology together with traditional means will enhance teaching and learning. Emerging technologies in higher education not only change the experience of students, lecturers, and the content, but it is also influencing the attraction and retention of students. Higher education institutions are under immense pressure because not only are they competing locally and nationally, but emerging technologies also expand the competition internationally. Emerging technologies have eliminated border barriers, allowing students to study in the country of their choice regardless of where they are in the world. Higher education institutions are becoming indifferent as technology is finding its way into the lecture room day by day. Academics need to utilise technology at their disposal if they want to get through to their students. Academics are now competing for students' attention with social media platforms such as WhatsApp, Snapchat, Instagram, Facebook, TikTok, and others. This is posing a significant challenge to higher education institutions. It is, therefore, critical to pay attention to emerging technologies in order to see how they can be incorporated into the classroom in order to improve educational quality while remaining relevant in the work industry. This study aims to understand how emerging technologies have been utilised at Nelson Mandela University in presenting teaching and learning activities since April 2020. The primary objective of this study is to analyse how academics are incorporating emerging technologies in their teaching and learning activities. This primary objective was achieved by conducting a literature review on clarifying and conceptualising the emerging technologies being utilised by higher education institutions, reviewing and analysing the use of emerging technologies, and will further be investigated through an empirical analysis of the use of emerging technologies at Nelson Mandela University. Findings from the literature review revealed that emerging technology is impacting several key areas in higher education institutions, such as the attraction and retention of students, enhancement of teaching and learning, increase in global competition, elimination of border barriers, and highlighting the digital divide. The literature review further identified that learning management systems, open educational resources, learning analytics, and artificial intelligence are the most prevalent emerging technologies being used in higher education institutions. The identified emerging technologies will be further analysed through an empirical analysis to identify how they are being utilised at Nelson Mandela University.

Keywords: artificial intelligence, emerging technologies, learning analytics, learner management systems, open educational resources

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Authors: Abdelazziz Aouiche, El Moundher Aouiche, Mouhamed Salah Soudani

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Renewable energy sources now significantly contribute to the replacement of traditional fossil fuel energy sources. One of the most potent types of renewable energy that has developed quickly in recent years is photovoltaic energy. We all know that solar energy, which is sustainable and non-depleting, is the best knowledge form of energy that we have at our disposal. Due to changing weather conditions, the primary drawback of conventional solar PV cells is their inability to track their maximum power point. In this study, we apply artificial neural networks (ANN) to automatically track and measure the maximum power point (MPP) of solar panels. In MATLAB, the complete system is simulated, and the results are adjusted for the external environment. The results are better performance than traditional MPPT methods and the results demonstrate the advantages of using neural networks in solar PV systems.

Keywords: modeling, photovoltaic panel, artificial neural networks, maximum power point tracking

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Authors: Noura Al-Ajmi, Mohammed A. Almulla

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With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

Keywords: headache diagnosis system, prescription recommender system, expert system, backward rule-based system

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Authors: Ismene Ithai Bras-Ruiz

Abstract:

Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

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Authors: Sara Fayez Fawzy Mikhael

Abstract:

Inclusive education services for students with autism are still developing in Thailand. Although many more children with intellectual disabilities have been attending school since the Thai government enacted the Education for Persons with Disabilities Act in 2008, facilities for students with disabilities and their families are generally inadequate. This comprehensive study used the Attitudes and Preparedness for Teaching Students with Autism Scale (APTSAS) to examine the attitudes and preparedness of 110, elementary teachers in teaching students with autism in the general education setting. Descriptive statistical analyzes showed that the most important factor in the formation of a negative image of teachers with autism is student attitudes. Most teachers also stated that their pre-service training did not prepare them to meet the needs of children with special needs who cannot speak. The study is important and provides directions for improving non-formal teacher education in Thailand.

Keywords: attitude, autism, teachers, thailandsports activates, movement skills, motor skills

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