Search results for: intercultural intelligence

Authors: Naser Zourikalatehsamad, Seyed Abdorreza Payambarpour, Ibrahim Alwashali, Zahra Abdolkarimi

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The paper aims to evaluate the effect of online advertising on consumer purchase behavior in Malaysian organizations. The paper has potential to extend and refine theory. A survey was distributed among Students of UTM university during the winter 2014 and 160 responses were collected. Regression analysis was used to test the hypothesized relationships of the model. Result shows that the predictors (cost saving factor, convenience factor and customized product or services) have positive impact on intention to continue seeking online advertising.

Keywords: consumer purchase, convenience, customized product, cost saving, customization, flow theory, mass communication, online advertising ads, online advertising measurement, online advertising mechanism, online intelligence system, self-confidence, willingness to purchase

Procedia PDF Downloads 480

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: 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: Dawn Tsang

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This paper aims at synthesizing the difficulties in cognitive processes faced by translation majors in mainland China. The purpose is to develop possible solutions and innovation in terms of translation pedagogy, curriculum reform, and syllabus design. This research will base its analysis on students’ instant feedback and interview after training in translation and interpreting courses, and translation faculty’s teaching experiences. This research will take our translation majors as the starting point, who will be one of the focus groups. At present, our Applied Translation Studies Programme is offering translation courses in the following areas: practical translation and interpreting, translation theories, culture and translation, and internship. It is a four-year translation programme, and our students would start their introductory courses since Semester 1 of Year 1. The medium of instruction of our College is solely in English. In general, our students’ competency in English is strong. Yet in translation and especially interpreting classes, no matter it is students’ first attempt or students who have taken university English courses, students find class practices very challenging, if not mission impossible. Their biggest learning problem seems to be weakening cognitive processes in terms of lack of intercultural competence, incomprehension of English language and foreign cultures, inadequate aptitude and slow reaction, and inapt to utilize one’s vocabulary bank etc. This being so, the research questions include: (1) What specific and common cognitive difficulties are students facing while learning translation and interpreting? (2) How to deal with such difficulties, and what implications can be drawn on curriculum reform and syllabus design in translation? (3) How significant should cognitive study be placed on translation curriculum, i.e., the proportion of cognitive study in translation/interpreting courses and in translation major curriculum? and (4) What can we as translation educators do to maximize teaching and learning effectiveness by incorporating the latest development of cognitive study?. We have collected translation students’ instant feedback and conduct interviews with both students and teaching staff, in order to draw parallels as well as distinguishing from our own current teaching practices at United International College (UIC). We have collected 500 questionnaires for now. The main learning difficulties include: poor vocabulary bank, lack of listening and reading comprehension skills in terms of not fully understanding the subtext, aptitude in translation and interpreting etc. This being so, we propose to reform and revitalize translation curriculum and syllabi to address to these difficulties. The aim is to maximize teaching effectiveness in translation by addressing the above-mentioned questions with a special focus on cognitive difficulties faced by translation majors.

Keywords: cognitive difficulties, teaching and learning effectiveness, translation curriculum reform, translation pedagogy

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Authors: Patrycja Pichnicka

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Anime is the Japanese art of animation and a kind of Japanese animated movie, different from the Western ones by its specific features. In the world dominated by live action movies, mostly the ones produced in the United States, Japanese animated movies, which constitute a large part of the Japanese movie industry, play the role of the Other. They adapt elements of Western culture and technology to create something that resists global Western domination. This phenomenon is particularly interesting to observe in the case of narration borrowed from the Western culture, yet transformed in a specific manner: such as Vampire Narration. The phenomenon should be examined using the theory of cultural adaptation of Siergiei Arutiunow, as well as theory of cultural hegemony and postcolonial theories, including the theory of the discourse of resistance. Relations of cultural hegemony and resistance have been mentioned in works of Susan Napier, however they are worth to be fully developed. Anime relations to globally dominating culture reveal tension between submission and resistance in which non-Western identity is constructed and performed. Nonetheless, the tension between the Global/Western and the Japanese is not the only one existing in contemporaneous Japanese society and culture. Sexual, gender, class, and ethnic issues are also expressed in and through pop culture narrations. Using the basic division of the types of cultural adaptation we can trace the line of the evolution of the Japanese cultural attitude towards the West, expressed in the Vampire Narration from the time of American occupation till now. These attitudes changed from the submissive assimilation or reproduction of cultural models, through the simple opposition, to the more nuanced attitude of nowadays. However, according to Kimberlé Crenshaw’s intersectional theory, there is no one category of discrimination or submission. There are individuals or groups existing on the cross of two or more categories of emancipation. If the Japanese were culturally subdued to the Westerner, the Japanese woman was doubly subdued: as a woman and as a Japanese. The emancipation of one group can deepen the submission of another one, of internal Other, of the group in which two or more categories of domination/submission intersect. That is why some Japanese female authors enthusiastically reproduce the Western cultural models, even if this means a cultural hegemony of the West over the Japanese. They see, as women, more liberal attitudes towards their gender in the Western culture than in the Japanese culture, as it is constructed and produced by Japanese men. The Japanese anime is the realm in which sophisticated art meets social tendencies and cultural attitudes. Anime examination permits to study of the composed contemporaneous Japanese identity, as well as general rules of cultural relations.

Keywords: anime, cultural hegemony, intercultural relations, resistance, vampire narration

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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: 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: Veronika Pivkina, Alla Kim, Khon Nataliya

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Actuality of the present study is defined first of all the role of subjective well-being problem in modern psychology and the comprehending of subjective well-being by current students. Purpose of this research is to educe peculiarities of comprehending of subjective well-being by students with various levels of emotional intelligent. Methods of research are adapted Russian-Language questionnaire of K. Riff 'The scales of psychological well-being'; emotional intelligent questionnaire of D. V. Lusin. The research involved 72 student from different universities and disciplines aged between 18 and 24. Analyzing the results of the studies, it can be concluded that the understanding of happiness in different groups of students with high and low levels of overall emotional intelligence is different, as well as differentiated by gender. Students with higher level of happiness possess more capacity and higher need to control their emotions, to cause and maintain the desired emotions and control something undesirable.

Keywords: subjective well-being, emotional intelligent, psychology of comprehending, students

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Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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Authors: Yuliia Skrynnik

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This research focuses on the interaction of verbal, non-verbal, and super-verbal communicative components used by the speaker changing social roles in the marketing discourse. The changing/performing of social roles is implemented through communicative strategies and tactics, the structural, semantic, and linguo-pragmatic means of which are characterized by specific features and differ for the performance of either a role of a supplier or a customer. Communication within the marketing discourse is characterized by symmetrical roles’ relation between communicative opponents. The strategy of a supplier’s social role realization and the strategy of a customer’s role realization influence the discursive personality's linguistic repertoire in the marketing discourse. This study takes into account that one person can be both a supplier and a customer under different circumstances, thus, exploring the one individual who can be both a supplier and a customer. Cooperative and non-cooperative tactics are the instruments for the implementation of these strategies. In the marketing discourse, verbal and non-verbal behaviour of the speaker performing a customer’s social role is highly informative for speakers who perform the role of a supplier. The research methods include discourse, context-situational, pragmalinguistic, pragmasemantic analyses, the method of non-verbal components analysis. The methodology of the study includes 5 steps: 1) defining the configurations of speakers’ social roles on the selected material; 2) establishing the type of the discourse (marketing discourse); 3) describing the specific features of a discursive personality as a subject of the communication in the process of social roles realization; 4) selecting the strategies and tactics which direct the interaction in different roles configurations; 5) characterizing the structural, semantic and pragmatic features of the strategies and tactics realization, including the analysis of interaction between verbal and non-verbal components of communication. In the marketing discourse, non-verbal behaviour is usually spontaneous but not purposeful. Thus, the adequate decoding of a partner’s non-verbal behavior provides more opportunities both for the supplier and the customer. Super-verbal characteristics in the marketing discourse are crucial in defining the opponent's social status and social role at the initial stage of interaction. The research provides the scenario of stereotypical situations of the play of a supplier and a customer. The performed analysis has perspectives for further research connected with the study of discursive variativity of speakers' verbal and non-verbal behaviour considering the intercultural factor influencing the process of performing the social roles in the marketing discourse; and the formation of the methods for the scenario construction of non-stereotypical situations of social roles realization/change in the marketing discourse.

Keywords: discursive personality, marketing discourse, non-verbal component of communication, social role, strategy, super-verbal component of communication, tactic, verbal component of communication

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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: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: David Sudre

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Today, the National Basketball Association (NBA) is the cultural model of reference for most of the French basketball community stakeholders (players, coaches, team and league managers). In addition to the strong impact it has on how this sport is played and perceived, the NBA also influences the ways professional basketball shows are organized in France (within the Jeep Elite league). The objective of this research is to see how and to what extent the NBA show, as a globalized cultural product, disrupts Jeep Elite's professional basketball cultural codes in the organization of its shows. The article will aim at questioning the intercultural phenomenon at stake in sports cultures in France through the prism of the basketball match. This angle will shed some light on the underlying relationships between local and global elements. The results of this research come from a one-year survey conducted in a small town in northern France, Le Portel, where the Etoile Sportive Saint Michel (ESSM), a Jeep Elite's club, operates. An ethnographic approach was favored. It entailed many participating observations and semi-directive interviews with supporters of the ESSM Le Portel. Through this ethnographic work with the team's fan groups (before the games, during the games and after the games), it was possible for the researchers to understand better all the cultural and identity issues that play out in the "Cauldron," the basketball arena of the ESSM Le Portel. The results demonstrate, at first glance, that many basketball events organized in France are copied from the American model. It seems difficult not to try to imitate the American reference that the NBA represents, whether it be at the French All-Star Game or a Jeep Elite Game at Le Portel. In this case, an acculturation process seems to occur, not only in the way people play but also in the creation of the show (cheerleaders, animations, etc.). However, this American culture of globalized basketball, although re-appropriated, is also being modified by the members of ESSM Le Portel within their locality. Indeed, they juggle between their culture of origin and their culture of reference to build their basketball show within their sociocultural environment. In this way, Le Portel managers and supporters introduce elements that are characteristic of their local culture into the show, such as carnival customs and celebrations, two ingredients that fully contribute to the creation of their identity. Ultimately, in this context of "glocalization," this research will ascertain, on the one hand, that the identity of French basketball becomes harder to outline, and, on the other hand, that the "Cauldron" turns out to be a place to preserve (fantasized) local identities, or even a place of (unconscious) resistance to the dominant model of American basketball culture.

Keywords: basketball, carnival, culture, globalization, identity, show, sport, supporters.

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Authors: Lana Dalawr Jalal

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This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: obstacle avoidance, particle swarm optimization, three-dimensional path planning unmanned aerial vehicles

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Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

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This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

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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: Navdeep Singh Randhawa, Shally Sharma

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Wireless Sensor Network is an autonomous technology emanating in the current scenario at a fast pace. This technology faces a number of defiance’s and energy management is one of them, which has a huge impact on the network lifetime. To sustain energy the different types of routing protocols have been flourished. The classical routing protocols are no more compatible to perform in complicated environments. Hence, in the field of routing the intelligent algorithms based on nature systems is a turning point in Wireless Sensor Network. These nature-based algorithms are quite efficient to handle the challenges of the WSN as they are capable of achieving local and global best optimization solutions for the complex environments. So, the main attention of this paper is to develop a routing algorithm based on some swarm intelligent technique to enhance the performance of Wireless Sensor Network.

Keywords: wireless sensor network, routing, swarm intelligence, MPRSO

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Authors: Ismene Ithai Bras-Ruiz

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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: Kolade Olawande Owoeye, George R. S. Weir

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The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

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Authors: Sara Fayez Fawzy Mikhael

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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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Authors: Zülfiye Bıkmaz, Aytolan Yıldırım

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This study was planned as a descriptive regressive study in order to determine the relationship between the competency levels of working nurses, the levels of competency expected by nursing students, the critical thinking disposition of nurses, their perceived autonomy levels, and certain socio demographic characteristics. It is also a methodological study with regard to the intercultural adaptation of the Nursing Competence Scale (NCS) in both working and student samples. The sample of the study group of nurses at a university hospital for at least 6 months working properly and consists of 443 people filled out questionnaires. The student group, consisting of 543 individuals from the 4 public university nursing 3rd and 4th grade students. Data collection tools consisted of a questionnaire prepared in order to define the socio demographic, economic, and personal characteristics of the participants, the ‘Nursing Competency Scale’, the ‘Autonomy Subscale of the Sociotropy – Autonomy Scale’, and the ‘California Critical Thinking Disposition Inventory’. In data evaluation, descriptive statistics, nonparametric tests, Rasch analysis and correlation and regression tests were used. The language validity of the ‘NCS’ was performed by translation and back translation, and the context validity of the scale was performed with expert views. The scale, which was formed into its final structure, was applied in a pilot application from a group consisting of graduate and student nurses. The time constancy of the test was obtained by analysis testing retesting method. In order to reduce the time problems with the two half reliability method was used. The Cronbach Alfa coefficient of the scale was found to be 0.980 for the nurse group and 0.986 for the student group. Statistically meaningful relationships between competence and critical thinking and variables such as age, gender, marital status, family structure, having had critical thinking training, education level, class of the students, service worked in, employment style and position, and employment duration were found. Statistically meaningful relationships between autonomy and certain variables of the student group such as year, employment status, decision making style regarding self, total duration of employment, employment style, and education status were found. As a result, it was determined that the NCS which was adapted interculturally was a valid and reliable measurement tool and was found to be associated with autonomy and critical thinking.

Keywords: nurse, nursing student, competence, autonomy, critical thinking, Rasch analysis

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Jana Ismail, Layla Fallatah, Maha Alshmaisi

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ChatGPT, a cutting-edge language model built on the GPT-3.5 architecture, has garnered attention for its profound natural language processing capabilities, holding promise for transformative applications in customer service and content creation. This study delves into ChatGPT's architecture, aiming to comprehensively understand its strengths and potential limitations. Through systematic experiments across diverse domains, such as general knowledge and creative writing, we evaluated the model's coherence, context retention, and task-specific accuracy. While ChatGPT excels in generating human-like responses and demonstrates adaptability, occasional inaccuracies and sensitivity to input phrasing were observed. The study emphasizes the impact of prompt design on output quality, providing valuable insights for the nuanced deployment of ChatGPT in conversational AI and contributing to the ongoing discourse on the evolving landscape of natural language processing in artificial intelligence.

Keywords: artificial Inelegance, chatGPT, open AI, NLP

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Authors: Saeid Jalilzadeh

Abstract:

PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. Honey Bee algorithm (HBA) and genetic algorithm (GA) are extensively used for real parameter optimization in diverse fields of study. This paper describes an application of HBA and GA to the problem of designing a PID controller whose parameters comprise proportionality constant, integral constant and derivative constant. Presence of three parameters to optimize makes the task of designing a PID controller more challenging than conventional P, PI, and PD controllers design. The suitability of the proposed approach has been demonstrated through computer simulation using MATLAB/SIMULINK.

Keywords: controller, GA, optimization, PID, PSO

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Authors: Tarek Aboueldahab, Hanan Farag

Abstract:

Cost minimization of Multiple Vehicle Routing Problem becomes a critical issue in the field of transportation because it is NP-hard optimization problem and the search space is complex. Many researches use the hybridization of artificial intelligence (AI) models to solve this problem; however, it can not guarantee to reach the best solution due to the difficulty of searching the whole search space. To overcome this problem, we introduce the hybrid model of Discrete Particle Swarm Optimization (DPSO) with a passive congregation which enable searching the whole search space to compromise between both local and global search. The practical experiment shows that our model obviously outperforms other hybrid models in cost minimization.

Keywords: cost minimization, multi-vehicle routing problem, passive congregation, discrete swarm, passive congregation

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Authors: Xu Zhang

Abstract:

This article unveils an indicator of language contact between English and Cantonese in one of the Outer Circle Englishes, Hong Kong (HK) English, through an empirical investigation into 1000 tokens from the Global Web-based English (GloWbE) corpus, employing frequency analysis and logistic regression analysis. It is perceived that Cantonese and general Chinese are contextually marked by an integral underlying thinking pattern. Chinese speakers exhibit a reliance on semantic context over syntactic rules and lexical forms. This linguistic trait carries over to their use of English, affording greater flexibility to formal elements in constructing English sentences. The study focuses on the syntactic positioning of the focusing subjunct ‘also’, a linguistic element used to add new or contrasting prominence to specific sentence constituents. The English language generally allows flexibility in the relative position of 'also’, while there is a preference for close marking relationships. This article shifts attention to Hong Kong, where Cantonese and English converge, and 'also' finds counterparts in Cantonese ‘jaa’ and Mandarin ‘ye’. Employing a corpus-based data-driven method, we investigate the syntactic position of 'also' in both HK and GB English. The study aims to ascertain whether HK English exhibits a greater 'syntactic freedom,' allowing for a more distant marking relationship with 'also' compared to GB English. The analysis involves a random extraction of 500 samples from both HK and GB English from the GloWbE corpus, forming a dataset (N=1000). Exclusions are made for cases where 'also' functions as an additive conjunct or serves as a copulative adverb, as well as sentences lacking sufficient indication that 'also' functions as a focusing particle. The final dataset comprises 820 tokens, with 416 for GB and 404 for HK, annotated according to the focused constituent and the relative position of ‘also’. Frequency analysis reveals significant differences in the relative position of 'also' and marking relationships between HK and GB English. Regression analysis indicates a preference in HK English for a distant marking relationship between 'also' and its focused constituent. Notably, the subject and other constituents emerge as significant predictors of a distant position for 'also.' Together, these findings underscore the nuanced linguistic dynamics in HK English and contribute to our understanding of language contact. It suggests that future pedagogical practice should consider incorporating the syntactic variation within English varieties, facilitating leaners’ effective communication in diverse English-speaking environments and enhancing their intercultural communication competence.

Keywords: also, Cantonese, English, focus marker, frequency analysis, language contact, logistic regression analysis

Procedia PDF Downloads 55