Search results for: artifical intelligence
156 Two-Stage Estimation of Tropical Cyclone Intensity Based on Fusion of Coarse and Fine-Grained Features from Satellite Microwave Data
Authors: Huinan Zhang, Wenjie Jiang
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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.Keywords: Artificial intelligence, deep learning, data mining, remote sensing
Procedia PDF Downloads 63155 Transformation of Periodic Fuzzy Membership Function to Discrete Polygon on Circular Polar Coordinates
Authors: Takashi Mitsuishi
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Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure).Keywords: defuzzification, fuzzy membership function, periodic function, polar coordinates transformation
Procedia PDF Downloads 363154 The Quantum Theory of Music and Human Languages
Authors: Mballa Abanda Luc Aurelien Serge, Henda Gnakate Biba, Kuate Guemo Romaric, Akono Rufine Nicole, Zabotom Yaya Fadel Biba, Petfiang Sidonie, Bella Suzane Jenifer
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The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original, and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological, and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation, and the question of modeling in the human sciences: mathematics, computer science, translation automation, and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal, and random music. The experimentation confirming the theorization, I designed a semi-digital, semi-analog application that translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music, and deterministic and random music). To test this application, I use music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). The translation is done (from writing to writing, from writing to speech, and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz, and world music or variety, etc. The software runs, giving you the option to choose harmonies, and then you select your melody.Keywords: language, music, sciences, quantum entenglement
Procedia PDF Downloads 77153 Foundations for Global Interactions: The Theoretical Underpinnings of Understanding Others
Authors: Randall E. Osborne
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In a course on International Psychology, 8 theoretical perspectives (Critical Psychology, Liberation Psychology, Post-Modernism, Social Constructivism, Social Identity Theory, Social Reduction Theory, Symbolic Interactionism, and Vygotsky’s Sociocultural Theory) are used as a framework for getting students to understand the concept of and need for Globalization. One of critical psychology's main criticisms of conventional psychology is that it fails to consider or deliberately ignores the way power differences between social classes and groups can impact the mental and physical well-being of individuals or groups of people. Liberation psychology, also known as liberation social psychology or psicología social de la liberación, is an approach to psychological science that aims to understand the psychology of oppressed and impoverished communities by addressing the oppressive sociopolitical structure in which they exist. Postmodernism is largely a reaction to the assumed certainty of scientific, or objective, efforts to explain reality. It stems from a recognition that reality is not simply mirrored in human understanding of it, but rather, is constructed as the mind tries to understand its own particular and personal reality. Lev Vygotsky argued that all cognitive functions originate in, and must therefore be explained as products of social interactions and that learning was not simply the assimilation and accommodation of new knowledge by learners. Social Identity Theory discusses the implications of social identity for human interactions with and assumptions about other people. Social Identification Theory suggests people: (1) categorize—people find it helpful (humans might be perceived as having a need) to place people and objects into categories, (2) identify—people align themselves with groups and gain identity and self-esteem from it, and (3) compare—people compare self to others. Social reductionism argues that all behavior and experiences can be explained simply by the affect of groups on the individual. Symbolic interaction theory focuses attention on the way that people interact through symbols: words, gestures, rules, and roles. Meaning evolves from human their interactions in their environment and with people. Vygotsky’s sociocultural theory of human learning describes learning as a social process and the origination of human intelligence in society or culture. The major theme of Vygotsky’s theoretical framework is that social interaction plays a fundamental role in the development of cognition. This presentation will discuss how these theoretical perspectives are incorporated into a course on International Psychology, a course on the Politics of Hate, and a course on the Psychology of Prejudice, Discrimination and Hate to promote student thinking in a more ‘global’ manner.Keywords: globalization, international psychology, society and culture, teaching interculturally
Procedia PDF Downloads 252152 The Impact of Artificial Intelligence on Children with Autism
Authors: Rania Melad Kamel Hakim
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. These have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these ‘syndrome’ forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or ‘non-syndrome’ autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way to improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co-morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties (‘sticky attention’), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 54151 The Outcome of Using Machine Learning in Medical Imaging
Authors: Adel Edwar Waheeb Louka
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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery
Procedia PDF Downloads 73150 The Impact of Artificial Intelligence on Autism Attitudes
Authors: Sara Asham Mahrous Kamel
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 54149 The Impact of Technology and Artificial Intelligence on Children in Autism
Authors: Dina Moheb Rashid Michael
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 55148 Common Health Problems of Filipino Overseas Household Service Workers: Implications for Wellness
Authors: Veronica Ramirez
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For over 40 years now, the Philippines has been supplying Household Service Workers (HSWs) globally. As a requirement of the Philippine Overseas Employment Agency (POEA), all Filipinos applying for overseas work undergo medical examination and a certificate of good health is submitted to the foreign employer before hiring. However, there are workplace-related health problems that develop during employment such as musculoskeletal strain or injury, back pain, hypertension and other illnesses. Some workers are in good working conditions but are on call more than 12 hours per day. There are also those who experience heavy physical work with short rest periods or time off. They can also be easily exposed to disease outbreaks and epidemics. It was the objective of this study to determine the common health problems of Filipino Overseas Service Workers and analyze their implications to wellness in the workplace. Specifically, it sought to describe the work conditions of HSWs and determine the work-related factors affecting their health. It also identified the medical care they avail of and how they perceive their health and wellness as determinants of well-being. Finally, it proposes ways to promote wellness among HSWs. This study focused on physical illnesses and does not include mental problems experienced by HSWs. Using a questionnaire, primary data were gathered online and through survey of HSW rehires who were retaking Pre-Departure Orientation Seminar at recruitment agencies. The 2010 Health Benefit Availment data from the Overseas Workers Welfare Administration (OWWA) was also utilized. Descriptive analysis was employed on the data gathered. Key stakeholders in the migration industry were also interviewed. Previous research studies, reports and literature on migration and wellness were used as secondary data. The study found that Filipino overseas HSWs are vulnerable to physical injury and experience body pains such as back, hip and shoulder pain. Long hours of work, work hazards and lack of rest due to poor accommodations can aggravate their physical condition. Although health insurance and health care are available, HSWs are not aware how to avail them. On the basis of the findings, a Wellness Program can be designed that include health awareness, health care availment, occupational ergonomics, safety and health, work and leisure balance, developing emotional intelligence, anger management and spirituality.Keywords: health, household service worker, overseas, wellness
Procedia PDF Downloads 258147 Low Cost Webcam Camera and GNSS Integration for Updating Home Data Using AI Principles
Authors: Mohkammad Nur Cahyadi, Hepi Hapsari Handayani, Agus Budi Raharjo, Ronny Mardianto, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan
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PDAM (local water company) determines customer charges by considering the customer's building or house. Charges determination significantly affects PDAM income and customer costs because the PDAM applies a subsidy policy for customers classified as small households. Periodic updates are needed so that pricing is in line with the target. A thorough customer survey in Surabaya is needed to update customer building data. However, the survey that has been carried out so far has been by deploying officers to conduct one-by-one surveys for each PDAM customer. Surveys with this method require a lot of effort and cost. For this reason, this research offers a technology called moblie mapping, a mapping method that is more efficient in terms of time and cost. The use of this tool is also quite simple, where the device will be installed in the car so that it can record the surrounding buildings while the car is running. Mobile mapping technology generally uses lidar sensors equipped with GNSS, but this technology requires high costs. In overcoming this problem, this research develops low-cost mobile mapping technology using a webcam camera sensor added to the GNSS and IMU sensors. The camera used has specifications of 3MP with a resolution of 720 and a diagonal field of view of 78⁰. The principle of this invention is to integrate four camera sensors, a GNSS webcam, and GPS to acquire photo data, which is equipped with location data (latitude, longitude) and IMU (roll, pitch, yaw). This device is also equipped with a tripod and a vacuum cleaner to attach to the car's roof so it doesn't fall off while running. The output data from this technology will be analyzed with artificial intelligence to reduce similar data (Cosine Similarity) and then classify building types. Data reduction is used to eliminate similar data and maintain the image that displays the complete house so that it can be processed for later classification of buildings. The AI method used is transfer learning by utilizing a trained model named VGG-16. From the analysis of similarity data, it was found that the data reduction reached 50%. Then georeferencing is done using the Google Maps API to get address information according to the coordinates in the data. After that, geographic join is done to link survey data with customer data already owned by PDAM Surya Sembada Surabaya.Keywords: mobile mapping, GNSS, IMU, similarity, classification
Procedia PDF Downloads 84146 The Impact of Artificial Intelligence on Autism Attitudes and Laws
Authors: Randa Reda Luke Waheeb
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 55145 The Impact of Artificial Intelligence on Autism Attitudes and Laws
Authors: Amany Nosshy Fawzy George
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 49144 The Impact of Artificial Intelligence on Autism Attitudes and Laws
Authors: Abanoub Youssry Anwar Sadek
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 42143 The Impact of Artificial Intelligence on Autism Attitudes and Laws
Authors: Wassim Azmy Abdalla Ishak
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populationsKeywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 36142 The Impact of Artificial Intelligence on Autism Attitudes and Laws
Authors: Narges Arsanious Kamel Arsanious
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 57141 The Impact of Artificial Intelligence on Autism Attitudes and Laws
Authors: Narges Arsanious Kamel Arsanious
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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. It have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these ‘syndrome’ forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or ‘non-syndrome’ autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties (sticky attention), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism). In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills
Procedia PDF Downloads 42140 The Effect of Artificial Intelligence on Banking Development and Progress
Authors: Mina Malak Hanna Saad
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New strategies for supplying banking services to the customer have been brought, which include online banking. Banks have begun to recall electronic banking (e-banking) as a manner to replace some conventional department features by means of the usage of the internet as a brand-new distribution channel. A few clients have at least one account at multiple banks and get admission to those debts through online banking. To test their present-day internet worth, customers need to log into each of their debts, get particular statistics, and paint closer to consolidation. Not only is it time-ingesting; however, but it is also a repeatable activity with a certain frequency. To solve this problem, the idea of account aggregation was delivered as a solution. Account consolidation in e-banking as a form of digital banking appears to build stronger dating with clients. An account linking service is usually known as a service that permits customers to manipulate their bank accounts held at exceptional institutions through a common online banking platform that places a high priority on safety and statistics protection. The object affords an outline of the account aggregation approach in e-banking as a distinct carrier in the area of e-banking. The advanced facts generation is becoming a vital thing in the improvement of financial services enterprise, specifically the banking enterprise. It has brought different ways of delivering banking to the purchaser, which includes net Banking. Banks began to study electronic banking (e-banking) as a means to update some of their traditional branch functions and the use of the net as a distribution channel. Some clients have at least multiple accounts throughout banks and get the right of entry to that money owed through the usage of e-banking offerings. To examine the contemporary internet's well-worth position, customers have to log in to each of their money owed, get the information and work on consolidation. This no longer takes sufficient time; however, it is a repetitive interest at a specified frequency. To address this point, an account aggregation idea is brought as an answer. E-banking account aggregation, as one of the e-banking kinds, appeared to construct a more potent dating with clients. Account Aggregation carrier usually refers to a service that allows clients to control their bank bills maintained in one-of-a-kind institutions via a common Internet banking working platform, with an excessive subject to protection and privateness. This paper offers an overview of an e-banking account aggregation technique as a new provider in the e-banking field.Keywords: compatibility, complexity, mobile banking, observation, risk banking technology, Internet banks, modernization of banks, banks, account aggregation, security, enterprise developmente-banking, enterprise development
Procedia PDF Downloads 35139 Real Estate Trend Prediction with Artificial Intelligence Techniques
Authors: Sophia Liang Zhou
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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.Keywords: linear regression, random forest, artificial neural network, real estate price prediction
Procedia PDF Downloads 103138 The Effects of Computer Game-Based Pedagogy on Graduate Students Statistics Performance
Authors: Clement Yeboah, Eva Laryea
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A pretest-posttest within subjects experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant, indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant, indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop an interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers and will continue to be a dynamic and rapidly evolving field for years to come.Keywords: pretest-posttest within subjects, computer game-based learning, statistics achievement, statistics anxiety
Procedia PDF Downloads 77137 Evolution of Web Development Progress in Modern Information Technology
Authors: Abdul Basit Kiani
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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design
Procedia PDF Downloads 54136 Multidisciplinary Approach to Mio-Plio-Quaternary Aquifer Study in the Zarzis Region (Southeastern Tunisia)
Authors: Ghada Ben Brahim, Aicha El Rabia, Mohamed Hedi Inoubli
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Climate change has exacerbated disparities in the distribution of water resources in Tunisia, resulting in significant degradation in quantity and quality over the past five decades. The Mio-Plio-Quaternary aquifer, the primary water source in the Zarzis region, is subject to climatic, geographical, and geological challenges, as well as human stress. The region is experiencing uneven distribution and growing threats from groundwater salinity and saltwater intrusion. Addressing this challenge is critical for the arid region’s socioeconomic development, and effective water resource management is required to combat climate change and reduce water deficits. This study uses a multidisciplinary approach to determine the groundwater potential of this aquifer, involving geophysics and hydrogeology data analysis. We used advanced techniques such as 3D Euler deconvolution and power spectrum analysis to generate detailed anomaly maps and estimate the depths of density sources, identifying significant Bouguer anomalies trending E-W, NW-SE, and NE-SW. Various techniques, such as wavelength filtering, upward continuation, and horizontal and vertical derivatives, were used to improve the gravity data, resulting in consistent results for anomaly shapes and amplitudes. The Euler deconvolution method revealed two prominent surface faults, trending NE-SW and NW-SE, that have a significant impact on the distribution of sedimentary facies and water quality within the Mio-Plio-Quaternary aquifer. Additionally, depth maxima greater than 1400 m to the North indicate the presence of a Cretaceous paleo-fault. Geoelectrical models and resistivity pseudo-sections were used to interpret the distribution of electrical facies in the Mio-Plio-Quaternary aquifer, highlighting lateral variation and depositional environment type. AI optimises the analysis and interpretation of exploration data, which is important to long-term management and water security. Machine learning algorithms and deep learning models analyse large datasets to provide precise interpretations of subsurface conditions, such as aquifer salinisation. However, AI has limitations, such as the requirement for large datasets, the risk of overfitting, and integration issues with traditional geological methods.Keywords: mio-plio-quaternary aquifer, Southeastern Tunisia, geophysical methods, hydrogeological analysis, artificial intelligence
Procedia PDF Downloads 14135 The Principle of a Thought Formation: The Biological Base for a Thought
Authors: Ludmila Vucolova
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The thought is a process that underlies consciousness and cognition and understanding its origin and processes is a longstanding goal of many academic disciplines. By integrating over twenty novel ideas and hypotheses of this theoretical proposal, we can speculate that thought is an emergent property of coded neural events, translating the electro-chemical interactions of the body with its environment—the objects of sensory stimulation, X, and Y. The latter is a self- generated feedback entity, resulting from the arbitrary pattern of the motion of a body’s motor repertory (M). A culmination of these neural events gives rise to a thought: a state of identity between an observed object X and a symbol Y. It manifests as a “state of awareness” or “state of knowing” and forms our perception of the physical world. The values of the variables of a construct—X (object), S1 (sense for the perception of X), Y (object), S2 (sense for perception of Y), and M (motor repertory that produces Y)—will specify the particular conscious percept at any given time. The proposed principle of interaction between the elements of a construct (X, Y, S1, S2, M) is universal and applies for all modes of communication (normal, deaf, blind, deaf and blind people) and for various language systems (Chinese, Italian, English, etc.). The particular arrangement of modalities of each of the three modules S1 (5 of 5), S2 (1 of 3), and M (3 of 3) defines a specific mode of communication. This multifaceted paradigm demonstrates a predetermined pattern of relationships between X, Y, and M that passes from generation to generation. The presented analysis of a cognitive experience encompasses the key elements of embodied cognition theories and unequivocally accords with the scientific interpretation of cognition as the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses, and cognition means thinking and awareness. By assembling the novel ideas presented in twelve sections, we can reveal that in the invisible “chaos”, there is an order, a structure with landmarks and principles of operations and mental processes (thoughts) are physical and have a biological basis. This innovative proposal explains the phenomenon of mental imagery; give the first insight into the relationship between mental states and brain states, and support the notion that mind and body are inseparably connected. The findings of this theoretical proposal are supported by the current scientific data and are substantiated by the records of the evolution of language and human intelligence.Keywords: agent, awareness, cognitive, element, experience, feedback, first person, imagery, language, mental, motor, object, sensory, symbol, thought
Procedia PDF Downloads 384134 Developing a Model to Objectively Assess the Culture of Individuals and Teams in Order to Effectively and Efficiently Achieve Sustainability in the Manpower
Authors: Ahmed Mohamed Elnady Mohamed Elsafty
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This paper explains a developed applied objective model to measure the culture qualitatively and quantitatively, whether in individuals or in teams, in order to be able to use culture correctly or modify it efficiently. This model provides precise measurements and consistent interpretations by being comprehensive, updateable, and protected from being misled by imitations. Methodically, the provided model divides the culture into seven dimensions (total 43 cultural factors): First dimension is outcome-orientation which consists of five factors and should be highest in leaders. Second dimension is details-orientation which consists of eight factors and should be in highest intelligence members. Third dimension is team-orientation which consists of five factors and should be highest in instructors or coaches. Fourth dimension is change-orientation which consists of five factors and should be highest in soldiers. Fifth dimension is people-orientation which consists of eight factors and should be highest in media members. Sixth dimension is masculinity which consists of seven factors and should be highest in hard workers. Last dimension is stability which consists of seven factors and should be highest in soft workers. In this paper, the details of all cultural factors are explained. Practically, information collection about each cultural factor in the targeted person or team is essential in order to calculate the degrees of all cultural factors using the suggested equation of multiplying 'the score of factor presence' by 'the score of factor strength'. In this paper, the details of how to build each score are explained. Based on the highest degrees - to identify which cultural dimension is the prominent - choosing the tested individual or team in the supposedly right position at the right time will provide a chance to use minimal efforts to make everyone aligned to the organization’s objectives. In other words, making everyone self-motivated by setting him/her at the right source of motivation is the most effective and efficient method to achieve high levels of competency, commitment, and sustainability. Modifying a team culture can be achieved by excluding or including new members with relatively high or low degrees in specific cultural factors. For conclusion, culture is considered as the software of the human beings and it is one of the major compression factors on the managerial discretion. It represents the behaviors, attitudes, and motivations of the human resources which are vital to enhance quality and safety, expanding the market share, and defending against attacks from external environments. Thus, it is tremendously essential and useful to use such a comprehensive model to measure, use, and modify culture.Keywords: culture dimensions, culture factors, culture measurement, cultural analysis, cultural modification, self-motivation, alignment to objectives, competency, sustainability
Procedia PDF Downloads 164133 Using Chatbots to Create Situational Content for Coursework
Authors: B. Bricklin Zeff
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This research explores the development and application of a specialized chatbot tailored for a nursing English course, with a primary objective of augmenting student engagement through situational content and responsiveness to key expressions and vocabulary. Introducing the chatbot, elucidating its purpose, and outlining its functionality are crucial initial steps in the research study, as they provide a comprehensive foundation for understanding the design and objectives of the specialized chatbot developed for the nursing English course. These elements establish the context for subsequent evaluations and analyses, enabling a nuanced exploration of the chatbot's impact on student engagement and language learning within the nursing education domain. The subsequent exploration of the intricate language model development process underscores the fusion of scientific methodologies and artistic considerations in this application of artificial intelligence (AI). Tailored for educators and curriculum developers in nursing, practical principles extending beyond AI and education are considered. Some insights into leveraging technology for enhanced language learning in specialized fields are addressed, with potential applications of similar chatbots in other professional English courses. The overarching vision is to illuminate how AI can transform language learning, rendering it more interactive and contextually relevant. The presented chatbot is a tangible example, equipping educators with a practical tool to enhance their teaching practices. Methodologies employed in this research encompass surveys and discussions to gather feedback on the chatbot's usability, effectiveness, and potential improvements. The chatbot system was integrated into a nursing English course, facilitating the collection of valuable feedback from participants. Significant findings from the study underscore the chatbot's effectiveness in encouraging more verbal practice of target expressions and vocabulary necessary for performance in role-play assessment strategies. This outcome emphasizes the practical implications of integrating AI into language education in specialized fields. This research holds significance for educators and curriculum developers in the nursing field, offering insights into integrating technology for enhanced English language learning. The study's major findings contribute valuable perspectives on the practical impact of the chatbot on student interaction and verbal practice. Ultimately, the research sheds light on the transformative potential of AI in making language learning more interactive and contextually relevant, particularly within specialized domains like nursing.Keywords: chatbot, nursing, pragmatics, role-play, AI
Procedia PDF Downloads 65132 AI-Enabled Smart Contracts for Reliable Traceability in the Industry 4.0
Authors: Harris Niavis, Dimitra Politaki
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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.Keywords: blockchain, data quality, industry4.0, product quality
Procedia PDF Downloads 189131 The Effects of Computer Game-Based Pedagogy on Graduate Students Statistics Performance
Authors: Eva Laryea, Clement Yeboah Authors
Abstract:
A pretest-posttest within subjects, experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising, as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers, and will continue to be a dynamic and rapidly evolving field for years to come.Keywords: pretest-posttest within subjects, experimental design, achievement, statistics-related anxiety
Procedia PDF Downloads 58130 A Hybrid Artificial Intelligence and Two Dimensional Depth Averaged Numerical Model for Solving Shallow Water and Exner Equations Simultaneously
Authors: S. Mehrab Amiri, Nasser Talebbeydokhti
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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme. In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations
Procedia PDF Downloads 187129 Enhancing Large Language Models' Data Analysis Capability with Planning-and-Execution and Code Generation Agents: A Use Case for Southeast Asia Real Estate Market Analytics
Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee
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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru
Procedia PDF Downloads 87128 Servitization in Machine and Plant Engineering: Leveraging Generative AI for Effective Product Portfolio Management Amidst Disruptive Innovations
Authors: Till Gramberg
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In the dynamic world of machine and plant engineering, stagnation in the growth of new product sales compels companies to reconsider their business models. The increasing shift toward service orientation, known as "servitization," along with challenges posed by digitalization and sustainability, necessitates an adaptation of product portfolio management (PPM). Against this backdrop, this study investigates the current challenges and requirements of PPM in this industrial context and develops a framework for the application of generative artificial intelligence (AI) to enhance agility and efficiency in PPM processes. The research approach of this study is based on a mixed-method design. Initially, qualitative interviews with industry experts were conducted to gain a deep understanding of the specific challenges and requirements in PPM. These interviews were analyzed using the Gioia method, painting a detailed picture of the existing issues and needs within the sector. This was complemented by a quantitative online survey. The combination of qualitative and quantitative research enabled a comprehensive understanding of the current challenges in the practical application of machine and plant engineering PPM. Based on these insights, a specific framework for the application of generative AI in PPM was developed. This framework aims to assist companies in implementing faster and more agile processes, systematically integrating dynamic requirements from trends such as digitalization and sustainability into their PPM process. Utilizing generative AI technologies, companies can more quickly identify and respond to trends and market changes, allowing for a more efficient and targeted adaptation of the product portfolio. The study emphasizes the importance of an agile and reactive approach to PPM in a rapidly changing environment. It demonstrates how generative AI can serve as a powerful tool to manage the complexity of a diversified and continually evolving product portfolio. The developed framework offers practical guidelines and strategies for companies to improve their PPM processes by leveraging the latest technological advancements while maintaining ecological and social responsibility. This paper significantly contributes to deepening the understanding of the application of generative AI in PPM and provides a framework for companies to manage their product portfolios more effectively and adapt to changing market conditions. The findings underscore the relevance of continuous adaptation and innovation in PPM strategies and demonstrate the potential of generative AI for proactive and future-oriented business management.Keywords: servitization, product portfolio management, generative AI, disruptive innovation, machine and plant engineering
Procedia PDF Downloads 82127 Investigations of Effective Marketing Metric Strategies: The Case of St. George Brewery Factory, Ethiopia
Authors: Mekdes Getu Chekol, Biniam Tedros Kahsay, Rahwa Berihu Haile
Abstract:
The main objective of this study is to investigate the marketing strategy practice in the Case of St. George Brewery Factory in Addis Ababa. One of the core activities in a Business Company to stay in business is having a well-developed marketing strategy. It assessed how the marketing strategies were practiced in the company to achieve its goals aligned with segmentation, target market, positioning, and the marketing mix elements to satisfy customer requirements. Using primary and secondary data, the study is conducted by using both qualitative and quantitative approaches. The primary data was collected through open and closed-ended questionnaires. Considering the size of the population is small, the selection of the respondents was carried out by using a census. The finding shows that the company used all the 4 Ps of the marketing mix elements in its marketing strategies and provided quality products at affordable prices by promoting its products by using high and effective advertising mechanisms. The product availability and accessibility are admirable with the practices of both direct and indirect distribution channels. On the other hand, the company has identified its target customers, and the company’s market segmentation practice is geographical location. Communication effectiveness between the marketing department and other departments is very good. The adjusted R2 model explains 61.6% of the marketing strategy practice variance by product, price, promotion, and place. The remaining 38.4% of variation in the dependent variable was explained by other factors not included in this study. The result reveals that all four independent variables, product, price, promotion, and place, have a positive beta sign, proving that predictor variables have a positive effect on that of the predicting dependent variable marketing strategy practice. Even though the marketing strategies of the company are effectively practiced, there are some problems that the company faces while implementing them. These are infrastructure problems, economic problems, intensive competition in the market, shortage of raw materials, seasonality of consumption, socio-cultural problems, and the time and cost of awareness creation for the customers. Finally, the authors suggest that the company better develop a long-range view and try to implement a more structured approach to attain information about potential customers, competitor’s actions, and market intelligence within the industry. In addition, we recommend conducting the study by increasing the sample size and including different marketing factors.Keywords: marketing strategy, market segmentation, target marketing, market positioning, marketing mix
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