Search results for: medical artificial intelligence

Authors: P. Jayashree, S. Rajkumar

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With the trend of virtual and augmented reality environments booming to provide a life like experience, gaming is a major tool in supporting such learning environments. In this work, a variant of Voronoi heuristics, employing supervised learning for the TRON game is proposed. The paper discusses the features that would be really useful when a machine learning bot is to be used as an opponent against a human player. Various game scenarios, nature of the bot and the experimental results are provided for the proposed variant to prove that the approach is better than those that are currently followed.

Keywords: artificial Intelligence, automation, machine learning, TRON game, Voronoi heuristics

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: Sonia Arradaza-Pajaron

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English as a second language is widely spoken in the Philippines. In fact, it is used as a medium of instruction in school. However, Filipino students, in general, are still not proficient in the use of the language. Since it plays a very crucial role in the learning and comprehension of some subjects in the school where important key concepts and in English, it is imperative to look into other factors that may affect such concern. This study may post an answer to the said concern because it aimed to investigate the association between a psychological construct, known as emotional intelligence, and the English language performance of the 55 senior high school students. The study utilized a descriptive correlational method to determine the significant relationship of variables with preliminary data, like GPA in English subject as baseline information of their performance. Results revealed that the respondents had an average GPA in the English subject; however, improving from their first-year high school level to the fourth year. Their English performance resulted to an above average level with a notable higher performance in the speaking test than in the written. Further, a strong correlation between English performance and emotional intelligence was manifested. Based on the findings, it can be concluded that students with higher emotional intelligence their English language performance is expected to be the same. It can be said further that when students’ emotional intelligence (EI components) is facilitated well through various classroom activities, a better English performance would just be spontaneous among them.

Keywords: English language performance, emotional intelligence, EI components, emotional literacy, emotional quotient competence, emotional quotient outcomes, values and beliefs

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Authors: Mahmoudi Marwa, Bahim Nadhem, Aydi Abdelwaheb, Issaoui Wissal, S. Najet

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This work represents a coupling between the geographic information system (GIS) and the multicriteria analysis aiming at the selection of an artificial recharge site by the treated wastewater for the Ariana governorate. On regional characteristics, bibliography and available data on artificial recharge, 13 constraints and 5 factors were hierarchically structured for the adequacy of an artificial recharge. The factors are subdivided into two main groups: environmental factors and economic factors. The adopted methodology allows a preliminary assessment of a recharge site, the weighted linear combination (WLC) and the analytical hierarchy process (AHP) in a GIS. The standardization of the criteria is carried out by the application of the different membership functions. The form and control points of the latter are defined by the consultation of the experts. The weighting of the selected criteria is allocated according to relative importance using the AHP methodology. The weighted linear combination (WLC) integrates the different criteria and factors to delineate the most suitable areas for artificial recharge site selection by treated wastewater. The results of this study showed three potential candidate sites that appear when environmental factors are more important than economic factors. These sites are ranked in descending order using the ELECTRE III method. Nevertheless, decision making for the selection of an artificial recharge site will depend on the decision makers in force.

Keywords: artificial recharge site, treated wastewater, analytical hierarchy process, ELECTRE III

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Authors: Amir Ahmadi, Hossein Ahmadi, Alireza Ahmadi

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Emotional Intelligence (EI) has been defined as the ability to empathize, persevere, control impulses, communicate clearly, make thoughtful decisions, solve problems, and work with others in a way that earns friends and success. These abilities allow an individual to recognize and regulate emotion, develop self-control, set goals, develop empathy, resolve conflicts, and develop skills needed for leadership and effective group participation. Due to the increasing complexity of organizations and different ways of thinking, attitudes and beliefs of individuals, conflict as an important part of organizational life has been examined frequently. The main point is that the conflict is not necessarily in organization, unnecessary; but it can be more creative (increase creativity), to promote innovation. The purpose of this study was to investigate the relation between principals emotional intelligence as one of the factors affecting conflict management among teachers. This relation was analyzed through cluster sampling with a sample size consisting of 120 individuals. The results of the study showed that at the 95% level of confidence, the two secondary hypotheses (i.e. relation between emotional intelligence of principals and use of competition and cooperation strategies of conflict management among teachers) were confirmed, but the other three secondary hypotheses (i.e. the relation between emotional intelligence of managers and use of avoidance, adaptation and adaptability strategies of conflict management among teachers) were rejected. The primary hypothesis (i.e. relation between emotional intelligence of principals with conflict management among teachers) is supported.

Keywords: emotional intelligence, conflict, conflict management, strategies of conflict management

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Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

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With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

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Authors: Louis Placido F. Lachica

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Freshman year in college, being a transition from high school to college, requires students to adjust by equipping themselves with competencies that will make them survive in college. This study conducted at in a state university in the Philippines aimed to determine the quality of school life and linguistic intelligence of 214 randomly selected college freshmen. Frequency counts and percentages were used to analyze quality of school life and linguistic intelligence. The chi-square test was utilized to determine significant relationship between quality of school life and linguistic intelligence and selected demographic variables. Results on quality of school life revealed that availability of religious books and paperbacks at home were significantly related to relationship with teachers. None of the selected demographic characteristics were significantly related to sense of achievement. Parents’ highest educational attainment was significantly related with opportunity at school. The availability of general references and song hits were significantly and highly significantly related to sense of identity which means that these promoted their sense of identity since their peers also preferred its availability. Type of high school graduated from was significantly related with students’ self-esteem. Graduates of public high schools have higher boosted self-esteem than those from private high schools. Both type of high school graduated from and reading materials available at home (religious books) had a highly significant relationship with linguistic intelligence. In addition, there was a significant relationship between time spent in reading per day and linguistic intelligence. There was a highly significant relationship between quality of school life in terms of relationship with teachers and sense of achievement with linguistic intelligence. Further, sense of identity and linguistic intelligence were significantly related.

Keywords: quality of school life, linguistic intelligence, college freshmen, state university

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Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

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Authors: Anna Dabrowska

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Taking Daniel Goleman’s (1994) belief that success in life depends on IQ in 20% and in 80% on emotional intelligence, and that it is worth considering emotional intelligence as an important factor in human performance and development potential, the aim of the paper is to explore the range of emotions experienced by university students who represent Society 5.0. This quantitative and qualitative study is meant to explore not only the list of the most and least experienced emotions by the students, but also the main reasons behind these feelings. The database of the study consists of 115 respondents out of 129 students of the 1st and 5th year of Applied Linguistics at Maria Curie-Skłodowska University, which constitutes 89% of those being surveyed. The data is extracted from the anonymous questionnaire, which comprises young people’s answers and discourse concerning the causes of their most experienced emotions. Following Robert Plutchik’s theory of eight primary emotions, i.e. anger, fear, sadness, disgust, surprise, anticipation, trust, and joy, we adopt his argument for the primacy of these emotions by showing each to be the trigger of behaviour with high survival value. In fact, all other emotions are mixed or derivative states; that is, they occur as combinations, mixtures, or compounds of the primary emotions. Accordingly, the eight primary emotions, and their mixed states, are checked in the study on the students.

Keywords: emotions, intelligence, students, discourse study, emotional intelligence

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Authors: Jalal Haghighat Monfared, Zahra Akbari

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Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: business intelligence, business intelligence capability, decision making, decision quality

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Authors: Pei-Chann Chang, Jhen-Fu Liao, Chin-Hung Teng, Meng-Hui Chen

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This research combines artificial immune system with user and item based collaborative filtering to create an efficient and accurate recommendation system. By applying the characteristic of antibodies and antigens in the artificial immune system and using Pearson correlation coefficient as the affinity threshold to cluster the data, our collaborative filtering can effectively find useful users and items for rating prediction. This research uses MovieLens dataset as our testing target to evaluate the effectiveness of the algorithm developed in this study. The experimental results show that the algorithm can effectively and accurately predict the movie ratings. Compared to some state of the art collaborative filtering systems, our system outperforms them in terms of the mean absolute error on the MovieLens dataset.

Keywords: artificial immune system, collaborative filtering, recommendation system, similarity

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Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: Arslan Ellahi, Syed Amjad Hussain, Fawaz Saleem Bokhari

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Optimization of software architecture can be done with respect to a quality attributes (QA). In this paper, there is an analysis of multiple research papers from different dimensions that have been used to classify those attributes. We have proposed a technique of swarm intelligence Meta heuristic ant colony optimization algorithm as a contribution to solve this critical optimization problem of software architecture. We have ranked quality attributes and run our algorithm on every QA, and then we will rank those on the basis of accuracy. At the end, we have selected the most accurate quality attributes. Ant colony algorithm is an effective algorithm and will perform best in optimizing the QA’s and ranking them.

Keywords: complexity, rapid evolution, swarm intelligence, dimensions

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Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

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The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

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Authors: Amir Ahmadi, Hossein Ahmadi, Alireza Ahmadi

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Emotional Intelligence (EI) has been defined as the ability to empathize, persevere, control impulses, communicate clearly, make thoughtful decisions, solve problems, and work with others in a way that earns friends and success. These abilities allow an individual to recognize and regulate emotion, develop self-control, set goals, develop empathy, resolve conflicts, and develop skills needed for leadership and effective group participation. Due to the increasing complexity of organizations and different ways of thinking, attitudes and beliefs of individuals, Conflict as an important part of organizational life has been examined frequently. The main point is that the conflict is not necessarily in organization, unnecessary; But it can be more creative (increase creativity), to promote innovation, or may avoid wasting energy and resources of the organization. The purpose of this study was to investigate the relation between principals emotional intelligence as one of the factors affecting conflict management among teachers. This relation was analyzed through cluster sampling with a sample size consisting of 120 individuals. The results of the study showed that, at the 95% level of confidence, the two secondary hypotheses (i.e. relation between emotional intelligence of principals and use of competition and cooperation strategies of conflict management among teachers)were confirmed, but the other three secondary hypotheses (i.e. the relation between emotional intelligence of managers and use of avoidance, adaptation and adaptability strategies of conflict management among teachers) were rejected. The primary hypothesis (i.e. relation between emotional intelligence of principals with conflict management among teachers) is supported.

Keywords: emotional intelligence, conflict, conflict management, strategies of conflict management

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Authors: Daniel Gebreslassie Mekonnen

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Effective leadership has a crucial role in excelling in the overall success of a school. Today there is much attention given to school leadership, without which schools can never be successful. Therefore, the study was aimed at investigating the role of principals’ leadership styles and their emotional intelligence on the work motivation and job performance of teachers in Addis Ababa, Ethiopia. The study, thus, first examined the relationship between work motivation and job performance of the teachers in relation to the perceived leadership styles and emotional intelligence of principals. Second, it assessed the mean differences and the interaction effects of the principals’ leadership styles and emotional intelligence on the work motivation and job performance of the teachers. Finally, the study investigated whether principals’ leadership styles and emotional intelligence variables had significantly predicted the work motivation and job performance of teachers. As a means, a quantitative approach and descriptive research design were employed to conduct the study. Three hundred sixteen teachers were selected using multistage sampling techniques as participants of the study from the eight sub-cities in Addis Ababa. The main data-gathering instruments used in this study were the path-goal leadership questionnaire, emotional competence inventory, multidimensional work motivation scale, and job performance appraisal scale. The quantitative data were analyzed by using the statistical techniques of Pearson–product-moment correlation analysis, two-way analysis of variance, and stepwise multiple regression analysis. Major findings of the study have revealed that the work motivation and job performance of the teachers were significantly correlated with the perceived participative leadership style, achievement-oriented leadership style, and emotional intelligence of principals. Moreover, the emotional intelligence of the principals was found to be the best predictor of the teachers’ work motivation, whereas the achievement-oriented leadership style of the principals was identified as the best predictor of the job performance of the teachers. Furthermore, the interaction effects of all four path-goal leadership styles vis-a-vis the emotional intelligence of the principals have shown differential effects on the work motivation and job performance of teachers. Thus, it is reasonable to conclude that emotional intelligence is the sine qua non of effective school leadership. Hence, this study would be useful for policymakers and educational leaders to come up with policies that would enhance the role of emotional intelligence on school leadership effectiveness. Finally, pertinent recommendations were drawn from the findings and the conclusions of the study.

Keywords: emotional intelligence, leadership style, job performance, work motivation

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Authors: Mehrzad Abdi Khalife, Iraj Mahdavi

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This paper presents the agile model for project management process. For project management process, the Project Management Body of Knowledge (PMBOK) guideline has been selected as platform. Combination of computational science and artificial intelligent methodology has been added to the guideline to transfer the standard to agile project management process. The model is the combination of practical standard, computational science and artificial intelligent. In this model, we present communication model and protocols to keep process agile. Here, we illustrate the collaboration man and machine in project management area with artificial intelligent approach.

Keywords: artificial intelligent, conceptual model, man-machine collaboration, project management, standard

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Authors: Qi Liu, Jiqin Yao, Xiaohu Zhou, Bo Zheng

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The first artificial cell was produced by Thomas Chang in the 1950s when he was trying to make a mimic of red blood cells. Since then, many different types of artificial cells have been constructed from one of the two approaches: a so-called bottom-up approach, which aims to create a cell from scratch, and a top-down approach, in which genes are sequentially knocked out from organisms until only the minimal genome required for sustaining life remains. In this project, bottom-up approach was used to build a new cell-free expression system which mimics artificial cell that capable of protein expression and communicate with each other. The artificial cells constructed from the bottom-up approach are usually lipid vesicles, polymersomes, hydrogels or aqueous droplets containing the nucleic acids and transcription-translation machinery. However, lipid vesicles based artificial cells capable of communication present several issues in the cell communication research: (1) The lipid vesicles normally lose the important functions such as protein expression within a few hours. (2) The lipid membrane allows the permeation of only small molecules and limits the types of molecules that can be sensed and released to the surrounding environment for chemical communication; (3) The lipid vesicles are prone to rupture due to the imbalance of the osmotic pressure. To address these issues, the hydrogel-based artificial cells were constructed in this work. To construct the artificial cell, polyacrylamide hydrogel was functionalized with Acrylate PEG Succinimidyl Carboxymethyl Ester (ACLT-PEG2000-SCM) moiety on the polymer backbone. The proteinaceous factors can then be immobilized on the polymer backbone by the reaction between primary amines of proteins and N-hydroxysuccinimide esters (NHS esters) of ACLT-PEG2000-SCM, the plasmid template and ribosome were encapsulated inside the hydrogel particles. Because the artificial cell could continuously express protein with the supply of nutrients and energy, the artificial cell-artificial cell communication and artificial cell-natural cell communication could be achieved by combining the artificial cell vector with designed plasmids. The plasmids were designed referring to the quorum sensing (QS) system of bacteria, which largely relied on cognate acyl-homoserine lactone (AHL) / transcription pairs. In one communication pair, “sender” is the artificial cell or natural cell that can produce AHL signal molecule by synthesizing the corresponding signal synthase that catalyzed the conversion of S-adenosyl-L-methionine (SAM) into AHL, while the “receiver” is the artificial cell or natural cell that can sense the quorum sensing signaling molecule form “sender” and in turn express the gene of interest. In the experiment, GFP was first immobilized inside the hydrogel particle to prove that the functionalized hydrogel particles could be used for protein binding. After that, the successful communication between artificial cell-artificial cell and artificial cell-natural cell was demonstrated, the successful signal between artificial cell-artificial cell or artificial cell-natural cell could be observed by recording the fluorescence signal increase. The hydrogel-based artificial cell designed in this work can help to study the complex communication system in bacteria, it can also be further developed for therapeutic applications.

Keywords: artificial cell, cell-free system, gene circuit, synthetic biology

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Authors: Sean Goltz, Michael Mayo

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The purpose of this research is to use Global-Regulation.com database of the world laws, focusing on tax treaties between countries, in order to create an AI-driven tax simulator that will run an AI agent through potential tax scenarios across countries. The AI agent goal is to identify the scenario that will result in minimum tax liability based on tax treaties between countries. The results will be visualized by a three dimensional matrix. This will be an online web application. Multinational corporations are running their business through multiple countries. These countries, in turn, have a tax treaty with many other countries to regulate the payment of taxes on income that is transferred between these countries. As a result, planning the best tax scenario across multiple countries and numerous tax treaties is almost impossible. This research propose to use Global-Regulation.com database of word laws in English (machine translated by Google and Microsoft API’s) in order to create a simulator that will include the information in the tax treaties. Once ready, an AI agent will be sent through the simulator to identify the scenario that will result in minimum tax liability. Identifying the best tax scenario across countries may save multinational corporations, like Google, billions of dollars annually. Given the nature of the raw data and the domain of taxes (i.e., numbers), this is a promising ground to employ artificial intelligence towards a practical and beneficial purpose.

Keywords: taxation, law, multinational, corporation

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Authors: Ahmadreza Jabalameli, Mohammad Ebrahimpour Borujeni

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This study aims to evaluate the effectiveness of intensive short-term dynamic psychotherapy (ISTDP) on ambiguity tolerance, emotional intelligence and stress coping strategies in financial market traders. The methodology of this study was quasi-experimental, pre-test and post-test with control group. The statistical population of this study includes all students at Jabalameli Information Technology Academy in 2022. Among them, 30 people were selected by voluntary sampling through interviews, and were randomly divided into two experimental and control groups of 51 people. And the components were measured according to McLain Ambiguity Tolerance Questionnaire, Bar-On Emotional Intelligence and Lazarus Stress Coping Strategies. The data were obtained by SPSS software and were analyzed by using multivariate analysis of covariance. The results indicate that intensive short-term dynamic psychotherapy influences the emotional intelligence as well as the ambiguity tolerance of traders.

Keywords: ISTDP, ambiguity tolerance, trading, emotional intelligence, stress

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Authors: Ladda Leungratanamart, Seree Chadcham

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Fluid intelligence declines along with age, but it can be developed. For this reason, increasing fluid intelligence in young adults can be possible. This study examined the effects of a two-month treadmill exercise program on fluid intelligence. The researcher designed a treadmill exercise program to promote cardiorespiratory fitness. Thirty-eight healthy voluntary students from the Boromarajonani College of Nursing, Chon Buri were assigned randomly to an exercise group (n=18) and a control group (n=20). The experiment consisted of three sessions: The baseline session consisted of measuring the VO₂max, electroencephalogram and behavioral response during performed the Raven Progressive Matrices (RPM) test, a measure of fluid intelligence. For the exercise session, an experimental group exercises using treadmill training at 60 % to 80 % maximum heart rate for 30 mins, three times per week, whereas the control group did not exercise. For the following two sessions, each participant was measured the same as baseline testing. The data were analyzed using the t-test to examine whether there is significant difference between the means of the two groups. The results showed that the mean VO₂ max in the experimental group were significantly more than the control group (p<.05), suggesting a two-month treadmill exercise program can improve fluid intelligence. When comparing the behavioral data, it was found that experimental group performed RPM test more accurately and faster than the control group. Neuroelectric data indicated a significant increase in percentages of alpha band ERD (%ERD) at P3 and Pz compared to the pre-exercise condition and the control group. These data suggest that a two-month treadmill exercise program can contribute to the development of cardiorespiratory fitness which influences an increase fluid intelligence. Exercise involved in cortical activation in difference brain areas.

Keywords: treadmill exercise, fluid intelligence, raven progressive matrices test, alpha band

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Authors: Marwa Ahmed Abd El Hamied

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In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

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Authors: László Schmidt

Abstract:

Technological and digital innovation is constantly and dynamically evolving, which poses an enormous challenge to both lawmaking and law enforcement. To legislation because artificial intelligence permeates many areas of people’s daily lives that the legislator must regulate. it can see how challenging it is to regulate e.g. self-driving cars/taxis/camions etc. Not to mention cryptocurrencies and Chat GPT, the use of which also requires legislative intervention. Artificial intelligence also poses an extraordinary challenge to law enforcement. In criminal cases, police and prosecutors can make great use of AI in investigations, e.g. in forensics, DNA samples, reconstruction, identification, etc. But it can also be of great help in the detection of crimes committed in cyberspace. In the case of cybercrime, on the one hand, it can be viewed as a new type of crime that can only be committed with the help of information systems, and that has a specific protected legal object, such as an information system or data. On the other hand, it also includes traditional crimes that are much easier to commit with the help of new tools. According to Hungarian Criminal Code section 375 (1), any person who, for unlawful financial gain, introduces data into an information system, or alters or deletes data processed therein, or renders data inaccessible, or otherwise interferes with the functioning of the information system, and thereby causes damage, is guilty of a felony punishable by imprisonment not exceeding three years. The Covid-19 coronavirus epidemic has had a significant impact on our lives and our daily lives. It was no different in the world of crime. With people staying at home for months, schools, restaurants, theatres, cinemas closed, and no travel, criminals have had to change their ways. Criminals were committing crimes online in even greater numbers than before. These crimes were very diverse, ranging from false fundraising, the collection and misuse of personal data, extortion to fraud on various online marketplaces. The most vulnerable age groups (minors and elderly) could be made more aware and prevented from becoming victims of this type of crime through targeted programmes. The aim of the study is to show the Hungarian judicial practice in relation to cybercrime and possible preventive solutions.

Keywords: cybercrime, COVID-19, Hungary, criminal law

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Authors: Onur Özdemir, M.Erhan ORHAN

Abstract:

Knowledge Development (KD) is just one of the important phases of Knowledge Management (KM). KD is the phase in which intelligence is used to see the big picture. In order to understand whether information is important or not, we have to use the intelligence cycle that includes four main steps: aiming, collecting data, processing and utilizing. KD also needs these steps. To make a precise decision, the decision maker has to be aware of his subordinates’ ideas. If the decision maker ignores the ideas of his subordinates or participants of the organization, it is not possible for him to get the target. KD is a way of using wisdom to accumulate the puzzle. If the decision maker does not bring together the puzzle pieces, he cannot get the big picture, and this shows its effects on the battlefield. In order to understand the battlefield, the decision maker has to use the intelligence cycle. To convert information to knowledge, KD is the main means for the intelligence cycle. On the other hand, the “Z Generation” born after the millennium are really the game changers. They have different attitudes from their elders. Their understanding of life is different - the definition of freedom and independence have different meanings to them than others. Decision makers have to consider these factors and rethink their decisions accordingly. This article tries to explain the relation between KD and Generation Z. KD is the main method of target managing. But if leaders neglect their people, the world will be seeing much more movements like the Arab Spring and other insurgencies.

Keywords: knowledge development, knowledge management, generation Z, intelligence cycle

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Authors: Adheesh Budree, Olaf Jacob, Louis CH Fourie, James Njenga, Gabriel D Hoffman

Abstract:

Business Intelligence (BI) is implemented by organisations for many reasons and chief among these is improved data support, decision support and savings. The main purpose of this study is to determine BI requirements and availability within South African organisations. The study addresses the following areas as identified as part of a literature review; assessing BI practices in businesses over a range of industries, sectors and managerial functions, determining the functionality of BI (technologies, architecture and methods). It was found that the overall satisfaction with BI in larger organisations is low due to lack of ability to meet user requirements.

Keywords: business intelligence, business value, data management, South Africa

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Authors: Suraj Mehrotra

Abstract:

The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Mohammad Shameel, Peter K. K. Loh, James H. Ng

Abstract:

Cybercrime is a new category of crime which poses a different challenge for crime investigators and incident responders. Attackers can mask their identities using a suite of tools and with the help of the deep web, which makes them difficult to track down. Scouring the deep web manually takes time and is inefficient. There is a growing need for a tool to scour the deep web to obtain useful evidence or intel automatically. In this paper, we will explain the background and motivation behind the research, present a survey of existing research on related tools, describe the design of our own crime/threat intelligence hunting tool prototype, demonstrate its capability with some test cases and lastly, conclude with proposals for future enhancements.

Keywords: cybercrime, deep web, threat intelligence, web crawler

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Authors: Cristina Costa-Lobo, Carla B. Vestena, Filomena E. Ponte

Abstract:

Creativity and intelligence are concepts that have aroused very expressive interest in the field of educational sciences and the field of psychological science since the middle of the last century since they have a great impact on the potential and well-being of individuals. However, due to progress in cognitive and positive psychology, there has been a growing interest in the psychoeducational domain of intelligence and creativity in the last decade. In this theoretical work, are analyzed comparatively the theoretical models that relate the intelligence and the creativity, are analyzed several psychoeducational intervention programs that have been implemented with a view to the promotion of creativity and signal possibilities, realities and ironies around the psychological evaluation of intelligence and creativity. In order to reach a broad perspective on creativity, the evidence is presented that points the need to evaluate different psychological domains. The psychoeducational intervention programs addressed have, with a common characteristic, the full stimulation of the creative potential of the participants, assumed as a highly valued capacity at the present time. The results point to the systematize that all interventions in the ambit of creativity have two guiding principles: all individuals can be creative, and creativity is a capacity that can be stimulated. This work refers to the importance of stimulus creativity in educational contexts, to the usefulness and pertinence of the creation, the implementation, and monitoring of flexible curricula, adapted to the educational needs of students, promoting a collaborative work among teachers, parents, students, psychologists, managers and educational administrators.

Keywords: creativity, intelligence, psychoeducational intervention programs, psychological evaluation, educational contexts

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Authors: Peter Mc Coll, Alberto Caro, Chiara Gandolfo, Montserrat Labbe, Francisca Schnaidt, Michela Palazzi

Abstract:

Self-esteem and emotional intelligence are variables that are related to people's nutritional status. Self-esteem may be at low levels in people living with obesity, while emotional intelligence can play an important role in the way people living with obesity cope. The objective of the study was to measure the association between self-esteem and emotional intelligence to nutritional status in adolescent population. Methodology: A cross-sectional study was carried out with 179 adolescent schoolchildren between 13 and 19 years old from a public school. The objective was to evaluate nutritional status; weight and height were measured by calculating the body mass index and Z score. Self-esteem was evaluated using the Coopersmith Self-esteem Inventory adapted by Brinkmann and Segure. Emotional intelligence was measured using the Emotional Quotient Inventory: short, by Bar On, adapted questionnaire, translated into Spanish by López Zafra. For statistical analysis: Pearson's Chi-square test, Pearson's correlation, and odd ratio calculation were used, with a p value at a significance level < 5%. Results: The study group was composed of 71% female and 29% male. The nutritional status was distributed as eutrophic 41.9%, overweight 20.1%, and obesity 21.1%. In relation to self-esteem, 44.1% presented low and very low levels, without differences by gender. Emotional intelligence was distributed: low 3.4%, medium 81%, and high 13.4% -no differences according to gender. The association between nutritional status (overweight and obesity) with low and very low self-esteem, an odds ratio of 2.5 (95% CI 1.12 – 5.59) was obtained with a p-value = 0.02. The correlation analysis between the intrapersonal sub-dimension emotional intelligence scores and the Z score of nutritional status presented a negative correlation of r = - 0.209 with a p-value < 0.005. The correlation between emotional intelligence subdimension stress management with Z score presented a positive correlation of r = 0.0161 with a p-value < 0.05. In conclusion, the group of adolescents studied had a high prevalence of overweight and obesity, a high prevalence of low self-esteem, and a high prevalence of average emotional intelligence. Overweight and obese adolescents were 2.5 times more likely to have low self-esteem. As overweight and obesity increase, self-esteem decreases, and the ability to manage stress increases.

Keywords: self-esteem, emotional intelligence, obesity, adolescent, nutritional status

Procedia PDF Downloads 37