Search results for: Deep learning based segmentation
30115 A Machine Learning Framework Based on Biometric Measurements for Automatic Fetal Head Anomalies Diagnosis in Ultrasound Images
Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi
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Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.Keywords: biometric measurements, fetal head malformations, machine learning methods, US images
Procedia PDF Downloads 29230114 Development of an EEG-Based Real-Time Emotion Recognition System on Edge AI
Authors: James Rigor Camacho, Wansu Lim
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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors
Procedia PDF Downloads 10930113 Idea, Creativity, Design, and Ultimately, Playing with Mathematics
Authors: Yasaman Azarmjoo
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Since ancient times, it has been said that mathematics is the mother of all sciences and the foundation of basic concepts in every field and profession. It would be great if, after learning this subject, we could enable students to create games and activities based on the same mathematical concepts. This article explores the design of various mathematical activities in the form of games, utilizing different mathematical topics such as algebra, equations, binary systems, and one-to-one correspondence. The theoretical significance of this article lies in uncovering alternative approaches to teaching and learning mathematics. By employing creative and interactive methods such as game design, it challenges the traditional perception of mathematics as a difficult and laborious subject. The theoretical significance of this article lies in demonstrating that mathematics can be made more accessible and enjoyable, which can result in heightened interest and engagement in the subject. In general, this article reveals another aspect of mathematics.Keywords: playing with mathematics, algebra and equations, binary systems, one-to-one correspondence
Procedia PDF Downloads 9730112 Depth of Penetration and Nature of Interferential Current in Cutaneous, Subcutaneous and Muscle Tissues
Authors: A. Beatti, L. Chipchase, A. Rayner, T. Souvlis
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The aims of this study were to investigate the depth of interferential current (IFC) penetration through soft tissue and to investigate the area over which IFC spreads during clinical application. Premodulated IFC and ‘true’ IFC at beat frequencies of 4, 40 and 90Hz were applied via four electrodes to the distal medial thigh of 15 healthy subjects. The current was measured via three Teflon coated fine needle electrodes that were inserted into the superficial layer of skin, then into the subcutaneous tissue (≈1 cm deep) and then into muscle tissue (≈2 cm deep). The needle electrodes were placed in the middle of the four IFC electrodes, between two channels and outside the four electrodes. Readings were taken at each tissue depth from each electrode during each treatment frequency then digitized and stored for analysis. All voltages were greater at all depths and locations than baseline (p < 0.01) and voltages decreased with depth (P=0.039). Lower voltages of all currents were recorded in the middle of the four electrodes with the highest voltage being recorded outside the four electrodes in all depths (P=0.000).For each frequency of ‘true’ IFC, the voltage was higher in the superficial layer outside the electrodes (P ≤ 0.01).Premodulated had higher voltages along the line of one circuit (P ≤ 0.01). Clinically, IFC appears to pass through skin layers to depth and is more efficient than premodulated IFC when targeting muscle tissue.Keywords: electrotherapy, interferential current, interferential therapy, medium frequency current
Procedia PDF Downloads 34830111 Audio-Visual Co-Data Processing Pipeline
Authors: Rita Chattopadhyay, Vivek Anand Thoutam
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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech
Procedia PDF Downloads 8330110 ChatGPT as a “Foreign Language Teacher”: Attitudes of Tunisian English Language Learners
Authors: Leila Najeh Bel'Kiry
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Artificial intelligence (AI) brought about many language robots, with ChatGPT being the most sophisticated thanks to its human-like linguistic capabilities. This aspect raises the idea of using ChatGPT in learning foreign languages. Starting from the premise that positions ChatGPT as a mediator between the language and the leaner, functioning as a “ghost teacher" offering a peaceful and secure learning space, this study aims to explore the attitudes of Tunisian students of English towards ChatGPT as a “Foreign Language Teacher” . Forty-five students, in their third year of fundamental English at Tunisian universities and high institutes, completed a Likert scale questionnaire consisting of thirty-two items and covering various aspects of language (phonology, morphology, syntax, semantics, and pragmatics). A scale ranging from 'Strongly Disagree,' 'Disagree,' 'Undecided,' 'Agree,' to 'Strongly Agree.' is used to assess the attitudes of the participants towards the integration of ChaGPTin learning a foreign language. Results indicate generally positive attitudes towards the reliance on ChatGPT in learning foreign languages, particularly some compounds of language like syntax, phonology, and morphology. However, learners show insecurity towards ChatGPT when it comes to pragmatics and semantics, where the artificial model may fail when dealing with deeper contextual and nuanced language levels.Keywords: artificial language model, attitudes, foreign language learning, ChatGPT, linguistic capabilities, Tunisian English language learners
Procedia PDF Downloads 6830109 E-Learning Network Support Services: A Comparative Case Study of Australian and United States Universities
Authors: Sayed Hadi Sadeghi
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This research study examines the current state of support services for e-network practice in an Australian and an American university. It identifies information that will be of assistance to Australian and American universities to improve their existing online programs. The study investigated the two universities using a quantitative methodological approach. Participants were students, lecturers and admins of universities engaged with online courses and learning management systems. The support services for e-network practice variables, namely academic support services, administrative support and technical support, were investigated for e-practice. Evaluations of e-network support service and its sub factors were above average and excellent in both countries, although the American admins and lecturers tended to evaluate this factor higher than others did. Support practice was evaluated higher by all participants of an American university than by Australians. One explanation for the results may be that most suppliers of the Australian university e-learning system were from eastern Asian cultural backgrounds with a western networking support perspective about e-learning.Keywords: support services, e-Network practice, Australian universities, United States universities
Procedia PDF Downloads 17030108 Investigating Iraqi EFL University Students' Productive Knowledge of Grammatical Collocations in English
Authors: Adnan Z. Mkhelif
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Grammatical collocations (GCs) are word combinations containing a preposition or a grammatical structure, such as an infinitive (e.g. smile at, interested in, easy to learn, etc.). Such collocations tend to be difficult for Iraqi EFL university students (IUS) to master. To help address this problem, it is important to identify the factors causing it. This study aims at investigating the effects of L2 proficiency, frequency of GCs and their transparency on IUSs’ productive knowledge of GCs. The study involves 112 undergraduate participants with different proficiency levels, learning English in formal contexts in Iraq. The data collection instruments include (but not limited to) a productive knowledge test (designed by the researcher using the British National Corpus (BNC)), as well as the grammar part of the Oxford Placement Test (OPT). The study findings have shown that all the above-mentioned factors have significant effects on IUSs’ productive knowledge of GCs. In addition to establishing evidence of which factors of L2 learning might be relevant to learning GCs, it is hoped that the findings of the present study will contribute to more effective methods of teaching that can better address and help overcome the problems IUSs encounter in learning GCs. The study is thus hoped to have significant theoretical and pedagogical implications for researchers, syllabus designers as well as teachers of English as a foreign/second language.Keywords: corpus linguistics, frequency, grammatical collocations, L2 vocabulary learning, productive knowledge, proficiency, transparency
Procedia PDF Downloads 25630107 Signed Language Phonological Awareness: Building Deaf Children's Vocabulary in Signed and Written Language
Authors: Lynn Mcquarrie, Charlotte Enns
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The goal of this project was to develop a visually-based, signed language phonological awareness training program and to pilot the intervention with signing deaf children (ages 6 -10 years/ grades 1 - 4) who were beginning readers to assess the effects of systematic explicit American Sign Language (ASL) phonological instruction on both ASL vocabulary and English print vocabulary learning. Growing evidence that signing learners utilize visually-based signed language phonological knowledge (homologous to the sound-based phonological level of spoken language processing) when reading underscore the critical need for further research on the innovation of reading instructional practices for visual language learners. Multiple single-case studies using a multiple probe design across content (i.e., sign and print targets incorporating specific ASL phonological parameters – handshapes) was implemented to examine if a functional relationship existed between instruction and acquisition of these skills. The results indicated that for all cases, representing a variety of language abilities, the visually-based phonological teaching approach was exceptionally powerful in helping children to build their sign and print vocabularies. Although intervention/teaching studies have been essential in testing hypotheses about spoken language phonological processes supporting non-deaf children’s reading development, there are no parallel intervention/teaching studies exploring hypotheses about signed language phonological processes in supporting deaf children’s reading development. This study begins to provide the needed evidence to pursue innovative teaching strategies that incorporate the strengths of visual learners.Keywords: American sign language phonological awareness, dual language strategies, vocabulary learning, word reading
Procedia PDF Downloads 33730106 An Ecological Grandeur: Environmental Ethics in Buddhist Perspective
Authors: Merina Islam
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There are many environmental problems. Various counter measures have been taken for environmental problems. Philosophy is an important contributor to environmental studies as it takes deep interest in meaning analysis of the concept environment and other related concepts. The Buddhist frame, which is virtue ethical, remains a better alternative to the traditional environmental outlook. Granting the unique role of man in immoral deliberations, the Buddhist approach, however, maintains a holistic concept of ecological harmony. Buddhist environmental ethics is more concerned about the complete moral community, the total ecosystem, than any particular species within the community. The moral reorientation proposed here has resemblance to the concept of 'deep ecology. Given the present day prominence of virtue ethics, we need to explore further into the Buddhist virtue theory, so that a better framework to treat the natural world would be ensured. Environment has turned out to be one of the most widely discussed issues in the recent times. Buddhist concepts such as Pratityasamutpadavada, Samvrit Satya, Paramartha Satya, Shunyata, Sanghatvada, Bodhisattva, Santanvada and others deal with interdependence in terms of both internal as well external ecology. The internal ecology aims at mental well-being whereas external ecology deals with physical well-being. The fundamental Buddhist concepts for dealing with environmental Problems are where the environment has the same value as humans as from the two Buddhist doctrines of the Non-duality of Life and its Environment and the Origination in Dependence; and the inevitability of overcoming environmental problems through the practice of the way of the Bodhisattva, because environmental problems are evil for people and nature. Buddhism establishes that there is a relationship among all the constituents of the world. There is nothing in the world which is independent from any other thing. Everything is dependent on others. The realization that everything in the universe is mutually interdependent also shows that the man cannot keep itself unaffected from ecology. This paper would like to focus how the Buddhist’s identification of nature and the Dhamma can contribute toward transforming our understanding, attitudes, and actions regarding the care of the earth. Environmental Ethics in Buddhism presents a logical and thorough examination of the metaphysical and ethical dimensions of early Buddhist literature. From the Buddhist viewpoint, humans are not in a category that is distinct and separate from other sentient beings, nor are they intrinsically superior. All sentient beings are considered to have the Buddha-nature, that is, the potential to become fully enlightened. Buddhists do not believe in treating of non-human sentient beings as objects for human consumption. The significance of Buddhist theory of interdependence can be understood from the fact that it shows that one’s happiness or suffering originates from ones realization or non-realization respectively of the dependent nature of everything. It is obvious, even without emphasis, which in the context of deep ecological crisis of today there is a need to infuse the consciousness of interdependence.Keywords: Buddhism, deep ecology, environmental problems, Pratityasamutpadavada
Procedia PDF Downloads 31730105 Concept-Based Assessment in Curriculum
Authors: Nandu C. Nair, Kamal Bijlani
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This paper proposes a concept-based assessment to track the performance of the students. The idea behind this approach is to map the exam questions with the concepts learned in the course. So at the end of the course, each student will know how well he learned each concept. This system will give a self assessment for the students as well as instructor. By analyzing the score of all students, instructor can decide some concepts need to be teaching again or not. The system’s efficiency is proved using three courses from M-tech program in E-Learning technologies and results show that the concept-wise assessment improved the score in final exam of majority students on various courses.Keywords: assessment, concept, examination, question, score
Procedia PDF Downloads 47430104 Injury Prediction for Soccer Players Using Machine Learning
Authors: Amiel Satvedi, Richard Pyne
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Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer
Procedia PDF Downloads 18730103 Eradicating Rural Poverty in Nigeria through Entrepreneurship Education
Authors: Nwachukwu Ihiejeto Celestine
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Rural poverty in Nigeria has been the bake of the society. It has been a canker worm which has eaten deep into the fabric of Nigerian society. Different models and principles have been applied to eradicate it, such as operation feed the nation, green revolution, NAPEP etc. Little or nothing has been done in the area of entrepreneurship education to tame this monster. It is based on this that the author wants to x-ray the role entrepreneurship education which studies “the process of identifying, bringing a vision to life” could play in the eradication of rural poverty in Nigeria. This will go along in providing appropriate principles for poverty alleviation and eradication in Nigeria. Some selected states in the eastern Geo-political region could be x-rayed in this circumstance. It is hoped that policy makers etc will find the work cogent in formulating and implementing policy decisions.Keywords: poverty, entrepreneurship, education, Nigeria
Procedia PDF Downloads 47030102 Reinforcement Learning Optimization: Unraveling Trends and Advancements in Metaheuristic Algorithms
Authors: Rahul Paul, Kedar Nath Das
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The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.Keywords: machine learning, reinforcement learning, loss function, evolutionary optimization techniques
Procedia PDF Downloads 8230101 Improving Fingerprinting-Based Localization System Using Generative AI
Authors: Getaneh Berie Tarekegn, Li-Chia Tai
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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine
Procedia PDF Downloads 4830100 Monitoring of Wound Healing Through Structural and Functional Mechanisms Using Photoacoustic Imaging Modality
Authors: Souradip Paul, Arijit Paramanick, M. Suheshkumar Singh
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Traumatic injury is the leading worldwide health problem. Annually, millions of surgical wounds are created for the sake of routine medical care. The healing of these unintended injuries is always monitored based on visual inspection. The maximal restoration of tissue functionality remains a significant concern of clinical care. Although minor injuries heal well with proper care and medical treatment, large injuries negatively influence various factors (vasculature insufficiency, tissue coagulation) and cause poor healing. Demographically, the number of people suffering from severe wounds and impaired healing conditions is burdensome for both human health and the economy. An incomplete understanding of the functional and molecular mechanism of tissue healing often leads to a lack of proper therapies and treatment. Hence, strong and promising medical guidance is necessary for monitoring the tissue regeneration processes. Photoacoustic imaging (PAI), is a non-invasive, hybrid imaging modality that can provide a suitable solution in this regard. Light combined with sound offers structural, functional and molecular information from the higher penetration depth. Therefore, molecular and structural mechanisms of tissue repair will be readily observable in PAI from the superficial layer and in the deep tissue region. Blood vessel formation and its growth is an essential tissue-repairing components. These vessels supply nutrition and oxygen to the cell in the wound region. Angiogenesis (formation of new capillaries from existing blood vessels) contributes to new blood vessel formation during tissue repair. The betterment of tissue healing directly depends on angiogenesis. Other optical microscopy techniques can visualize angiogenesis in micron-scale penetration depth but are unable to provide deep tissue information. PAI overcomes this barrier due to its unique capability. It is ideally suited for deep tissue imaging and provides the rich optical contrast generated by hemoglobin in blood vessels. Hence, an early angiogenesis detection method provided by PAI leads to monitoring the medical treatment of the wound. Along with functional property, mechanical property also plays a key role in tissue regeneration. The wound heals through a dynamic series of physiological events like coagulation, granulation tissue formation, and extracellular matrix (ECM) remodeling. Therefore tissue elasticity changes, can be identified using non-contact photoacoustic elastography (PAE). In a nutshell, angiogenesis and biomechanical properties are both critical parameters for tissue healing and these can be characterized in a single imaging modality (PAI).Keywords: PAT, wound healing, tissue coagulation, angiogenesis
Procedia PDF Downloads 10930099 First Occurrence of Histopathological Assessment in Gadoid Deep-Fish Phycis blennoides from the Southwestern Mediterranean Sea
Authors: Zakia Alioua, Amira Soumia, Zerouali-Khodja Fatiha
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In spite of a wide variety of contaminants such as heavy metals and organic compounds in addition to the importance of extended pollution, the deep-sea and its species are not in haven and being affected through contaminants exposure. This investigation is performed in order to provide data on the presence of pathological changes in the liver and gonads of the greater forkbeard. A total of 998 specimens of the teleost fish Phycis blennoides Brünnich, 1768 ranged from 5,7 to 62,7 cm in total length, were obtained from the commercial fisheries of Algerian ports. The sampling has been carried out monthly from December 2013 to June 2015 and from January to June 2016 caught by trawlers and longlines between 75 and 600 fathoms in the coast of Algeria. Individuals were sexed their gonads, and their livers were removed and processed for light microscopy and one case of atresia was identified. In whole, overall 0,002% of the specimens presented some degree of liver steatosis. For the gastric section, 442 selected stomachs contents were observed looking for parasitic infestation and enumerate 212 nematodes. A prospecting survey for metal contaminant was performed on the liver by atomic absorption spectrophotometry analysis.Keywords: atresia, coast of Algeria, histopathology, nematode, Phycis blennoides, steatosis
Procedia PDF Downloads 23630098 The Impact of Neuroscience Knowledge on the Field of Education
Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena
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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors
Procedia PDF Downloads 6630097 Research Related to the Academic Learning Stress, Reflected into PubMed Website Publications
Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau, Dong Hun Kwak, Nicolae-Alexandru Colceriu
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Background: Academic environment led, in time, to the birth of some research subjects concluded with many publications. One of these issues is related to the learning stress. Thus far, the PubMed website displays an impressive number of papers related to the academic stress. Aims: Through this study, we aimed to evaluate the research concerning academic learning stress (ALS), by a retrospective analysis of PubMed publications. Methods: We evaluated the ALS, considering: a) different keywords as - ‘academic stress’ (AS), ‘academic stressors’ (ASs), ‘academic learning stress’ (ALS), ‘academic student stress’ (ASS), ‘academic stress college’ (ASC), ‘medical academic stress’ (MAS), ‘non-medical academic stress’ (NMAS), ‘student stress’ (SS), ‘nursing student stress’ (NS), ‘college student stress’ (CSS), ‘university student stress’ (USS), ‘medical student stress’ (MSS), ‘dental student stress’ (DSS), ‘non-medical student stress’ (NMSS), ‘learning students stress’ (LSS), ‘medical learning student stress’ (MLSS), ‘non-medical learning student stress’ (NMLSS); b) the year average for decades; c) some selection filters provided by PubMed website: Article types - Journal Article (JA), Clinical Trial (CT), Review (R); Species - Humans (H); Sex - Male (M) and Female (F); Ages - 13-18, 19-24, 19-44. Statistical evaluation was made on the basis of the Student test. Results: There were differences between keywords, referring to all filters. Nevertheless, for all keywords were noted the following: the majority of studies have indicated that subjects were humans; there were no important differences between the number of subjects M and F; the age of participants was mentioned only in some studies, predominating those with teenagers and subjects between 19-24 years. Conclusions: 1) PubMed publications document that concern for the research field of academic stress, lasts for 56 years and was materialized in more than 5.010 papers. 2) Number of publications in the field of academic stress varies depending on the selected keywords: those with a general framing (AS, ASs, ALS, ASS, SS, USS, LSS) are more numerous than those with a specific framing (ASC, MAS, NMAS, NS, CSS, MSS, DSS, NMSS, MLSS, NMLSS); those concerning the academic medical environment (MAS, NS, MSS, DSS, MLSS) prevailed compared to the non-medical environment (NMAS, NMSS, NMLSS). 3) Most of the publications are included at JA, of which a small percentage are CT and R. 4) Most of the academic stress studies were conducted with subjects both M and F, most aged under 19 years and between 19-24 years.Keywords: academic stress, student stress, academic learning stress, medical student stress
Procedia PDF Downloads 56830096 Evaluating the Teaching and Learning Value of Tablets
Authors: Willem J. A. Louw
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The wave of new advanced computing technology that has been developed during the recent past has significantly changed the way we communicate, collaborate and collect information. It has created a new technology environment and paradigm in which our children and students grow-up and this impacts on their learning. Research confirmed that Generation Y students have a preference for learning in the new technology environment. The challenge or question is: How do we adjust our teaching and learning to make the most of these changes. The complexity of effective and efficient teaching and learning must not be underestimated and changes must be preceded by proper objective research to prevent any haphazard developments that could do more harm than benefit. A blended learning approach has been used in the Forestry department for a few numbers of years including the use of electronic-peer assisted learning (e-pal) in a fixed-computer set-up within a learning management system environment. It was decided to extend the investigation and do some exploratory research by using a range of different Tablet devices. For this purpose, learning activities or assignments were designed to cover aspects of communication, collaboration and collection of information. The Moodle learning management system was used to present normal module information, to communicate with students and for feedback and data collection. Student feedback was collected by using an online questionnaire and informal discussions. The research project was implemented in 2013, 2014 and 2015 amongst first and third-year students doing a forestry three-year technical tertiary qualification in commercial plantation management. In general, more than 80% of the students alluded to that the device was very useful in their learning environment while the rest indicated that the devices were not very useful. More than ninety percent of the students acknowledged that they would like to continue using the devices for all of their modules whilst the rest alluded to functioning efficiently without the devices. Results indicated that information collection (access to resources) was rated the highest advantageous factor followed by communication and collaboration. The main general advantages of using Tablets were listed by the students as being mobility (portability), 24/7 access to learning material and information of any kind on a user friendly device in a Wi-Fi environment, fast computing process speeds, saving time, effort and airtime through skyping and e-mail, and use of various applications. Ownership of the device is a critical factor while the risk was identified as a major potential constraint. Significant differences were reported between the different types and quality of Tablets. The preferred types are those with a bigger screen and the ones with overall better functionality and quality features. Tablets significantly increase the collaboration, communication and information collection needs of the students. It does, however, not replace the need of a computer/laptop because of limited storage and computation capacity, small screen size and inefficient typing.Keywords: tablets, teaching, blended learning, tablet quality
Procedia PDF Downloads 25030095 Brain Connectome of Glia, Axons, and Neurons: Cognitive Model of Analogy
Authors: Ozgu Hafizoglu
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An analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with physical, behavioral, principal relations that are essential to learning, discovery, and innovation. The Cognitive Model of Analogy (CMA) leads and creates patterns of pathways to transfer information within and between domains in science, just as happens in the brain. The connectome of the brain shows how the brain operates with mental leaps between domains and mental hops within domains and the way how analogical reasoning mechanism operates. This paper demonstrates the CMA as an evolutionary approach to science, technology, and life. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions in the new era, especially post-pandemic. In this paper, we will reveal how to draw an analogy to scientific research to discover new systems that reveal the fractal schema of analogical reasoning within and between the systems like within and between the brain regions. Distinct phases of the problem-solving processes are divided thusly: stimulus, encoding, mapping, inference, and response. Based on the brain research so far, the system is revealed to be relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain’s mechanism in macro context; brain and spinal cord, and micro context: glia and neurons, relative to matching conditions of analogical reasoning and relational information, encoding, mapping, inference and response processes, and verification of perceptual responses in four-term analogical reasoning. Finally, we will relate all these terminologies with these mental leaps, mental maps, mental hops, and mental loops to make the mental model of CMA clear.Keywords: analogy, analogical reasoning, brain connectome, cognitive model, neurons and glia, mental leaps, mental hops, mental loops
Procedia PDF Downloads 16730094 Neuronal Mechanisms of Observational Motor Learning in Mice
Authors: Yi Li, Yinan Zheng, Ya Ke, Yungwing Ho
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Motor learning is a process that frequently happens among humans and rodents, which is defined as the changes in the capability to perform a skill that is conformed to have a relatively permanent improvement through practice or experience. There are many ways to learn a behavior, among which is observational learning. Observational learning is the process of learning by watching the behaviors of others, for example, a child imitating parents, learning a new sport by watching the training videos or solving puzzles by watching the solutions. Many research explores observational learning in humans and primates. However, the neuronal mechanism of which, especially observational motor learning, was uncertain. It’s well accepted that mirror neurons are essential in the observational learning process. These neurons fire when the primate performs a goal-directed action and sees someone else demonstrating the same action, which suggests they have high firing activity both completing and watching the behavior. The mirror neurons are assumed to mediate imitation or play a critical and fundamental role in action understanding. They are distributed in many brain areas of primates, i.e., posterior parietal cortex (PPC), premotor cortex (M2), and primary motor cortex (M1) of the macaque brain. However, few researchers report the existence of mirror neurons in rodents. To verify the existence of mirror neurons and the possible role in motor learning in rodents, we performed customised string-pulling behavior combined with multiple behavior analysis methods, photometry, electrophysiology recording, c-fos staining and optogenetics in healthy mice. After five days of training, the demonstrator (demo) mice showed a significantly quicker response and shorter time to reach the string; fast, steady and accurate performance to pull down the string; and more precisely grasping the beads. During three days of observation, the mice showed more facial motions when the demo mice performed behaviors. On the first training day, the observer reduced the number of trials to find and pull the string. However, the time to find beads and pull down string were unchanged in the successful attempts on the first day and other training days, which indicated successful action understanding but failed motor learning through observation in mice. After observation, the post-hoc staining revealed that the c-fos expression was increased in the cognitive-related brain areas (medial prefrontal cortex) and motor cortices (M1, M2). In conclusion, this project indicated that the observation led to a better understanding of behaviors and activated the cognitive and motor-related brain areas, which suggested the possible existence of mirror neurons in these brain areas.Keywords: observation, motor learning, string-pulling behavior, prefrontal cortex, motor cortex, cognitive
Procedia PDF Downloads 9030093 Educational Sustainability: Teaching the Next Generation of Educators in Medical Simulation
Authors: Thomas Trouton, Sebastian Tanner, Manvir Sandher
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The use of simulation in undergraduate and postgraduate medical curricula is ever-growing, is a useful addition to the traditional apprenticeship model of learning within medical education, and better prepares graduates for the team-based approach to healthcare seen in real-life clinical practice. As a learning tool, however, undergraduate medical students often have little understanding of the theory behind the use of medical simulation and have little experience in planning and delivering their own simulated teaching sessions. We designed and implemented a student-selected component (SSC) as part of the undergraduate medical curriculum at the University of Buckingham Medical School to introduce students to the concepts behind the use of medical simulation in education and allow them to plan and deliver their own simulated medical scenario to their peers. The SSC took place over a 2-week period in the 3rd year of the undergraduate course. There was a mix of lectures, seminars and interactive group work sessions, as well as hands-on experience in the simulation suite, to introduce key concepts related to medical simulation, including technical considerations in simulation, human factors, debriefing and troubleshooting scenarios. We evaluated the success of our SSC using “Net Promotor Scores” (NPS) to assess students’ confidence in planning and facilitating a simulation-based teaching session, as well as leading a debrief session. In all three domains, we showed an increase in the confidence of the students. We also showed an increase in confidence in the management of common medical emergencies as a result of the SSC. Overall, the students who chose our SSC had the opportunity to learn new skills in medical education, with a particular focus on the use of simulation-based teaching, and feedback highlighted that a number of students would take these skills forward in their own practice. We demonstrated an increase in confidence in several domains related to the use of medical simulation in education and have hopefully inspired a new generation of medical educators.Keywords: simulation, SSC, teaching, medical students
Procedia PDF Downloads 13130092 The Use of Authentic Videos to Change Learners’ Negative Attitudes and Perceptions toward Grammar Learning
Authors: Khaldi Youcef
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This investigation seeks to inquire into the effectiveness of using authentic videos for grammar teaching purposes. In this investigation, an English animated situation, Hercules, was used as a type of authentic multimedia to teach a particular grammatical structure, namely conditional sentences. This study also aims at investigating the EFL learners’ attitudes toward grammar learning after being exposed to such an authentic video. To reach that purpose, 56 EFL learners were required ultimately to respond to a questionnaire with an aim to reveal their attitudes towards grammar as a language entity and as a subject for being learned. Then, as a second stage of the investigation, the EFL learners were divided into a control group and an experimental group with 28 learners in each. The first group was taught grammar -conditional sentences- using a deductive-inductive approach, while the second group was exposed to an authentic video to learn conditional sentences. There was a post-lesson stage that included a questionnaire to be answered by learners of each group. The aim of this stage is to capture any change in learners' attitudes shown in the pre-lesson questionnaire. The findings of the first stage revealed learners' negative attitudes towards grammar learning. And the third stage results showed the effectiveness of authentic videos in entirely turning learners' attitudes toward grammar learning to be significantly positive. Also, the utility of authentic videos in highly motivating EFL learners can be deduced. The findings of this survey asserted the need for incorporation and integration of authentic videos in EFL classrooms as they resulted in rising effectively learners’ awareness of grammar and looking at it from a communicative perspective.Keywords: multimedia, authentic videos, negative attitudes, grammar learning, EFL learners
Procedia PDF Downloads 10330091 Attitude of Beef Cattle Farmers toward Biosecurity Practices
Authors: Veronica Sri Lestari, Sitti Nurani Sirajuddin, Kasmiyati Kasim
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The purpose of this research was to know the attitude of beef cattle farmers toward bio security practices. This research was conducted in Barru regency, South Sulawesi province, Indonesia, in 2014. Thirty beef cattle farmers were selected through random sampling. Primary and secondary data were collected through report, observation and deep interview by using questionnaire. Bio security practices consisted of 35 questions. Every answer of the question was scored based on three categories: score 1 (not important), score 2 (important) and 3 (very important). The results of this research showed that the attitude of beef cattle farmers toward bio security practices was categorized as important.Keywords: attitude, beef cattle, biosecurity, farmers
Procedia PDF Downloads 29930090 A Metallography Study of Secondary A226 Aluminium Alloy Used in Automotive Industries
Authors: Lenka Hurtalová, Eva Tillová, Mária Chalupová, Juraj Belan, Milan Uhríčik
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The secondary alloy A226 is used for many automotive casting produced by mould casting and high pressure die-casting. This alloy has excellent castability, good mechanical properties and cost-effectiveness. Production of primary aluminium alloys belong to heavy source fouling of life environs. The European Union calls for the emission reduction and reduction in energy consumption, therefore, increase production of recycled (secondary) aluminium cast alloys. The contribution is deal with influence of recycling on the quality of the casting made from A226 in automotive industry. The properties of the casting made from secondary aluminium alloys were compared with the required properties of primary aluminium alloys. The effect of recycling on microstructure was observed using combination different analytical techniques (light microscopy upon black-white etching, scanning electron microscopy-SEM upon deep etching and energy dispersive X-ray analysis-EDX). These techniques were used for the identification of the various structure parameters, which was used to compare secondary alloy microstructure with primary alloy microstructure.Keywords: A226 secondary aluminium alloy, deep etching, mechanical properties, recycling foundry aluminium alloy
Procedia PDF Downloads 54630089 Dots to Dialogue: Enhancing Accessibility through Braille Image-to-Speech Conversion
Authors: Shwetha B. S., Sirisha M., Vachana U., Aditya Kadlimatti, Manjushree N. S.
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Braille script holds significant importance in bridging the communication gap for visually impaired individuals. However, the challenge of interpreting Braille for non-experts creates barriers in education and day-to-day interactions. This paper aims to develop a system that translates Braille text into multilingual speech using advanced Convolutional Neural Networks (CNNs) and Google Text-to-Speech (GTTS) technology. The proposed system employs image recognition techniques powered by CNNs to accurately identify and decode Braille characters from captured images. The deep learning model undergoes training on a diverse dataset of Braille symbols to ensure high accuracy and robustness. Among the models evaluated, AlexNet demonstrated the highest accuracy in decoding Braille characters. Once recognized, the decoded text is converted into speech in the user’s preferred language using the GTTS API. This system possesses the ability to greatly improve inclusivity by enabling real-time Braille interpretation for visually impaired individuals, educators, and caregivers.Keywords: convolutional neural networks, Braille image, image-to-speech, GTTS, AlexNet, VGG16, DenseNet121, ResNet50
Procedia PDF Downloads 530088 The Effect of Observational Practice on the Volleyball Service Learning with Emphasis on the Role of Self–Efficacy
Authors: Majed Zobairy, Payam Mohammadpanahi
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Introduction: Skill movement education is one of extremely important duty for sport coaches and sport teachers. Researchers have done lots of studies in this filed to gain the best methodology in movement learning. One of the essential aspects in skill movement education is observational learning. Observational learning, or learning by watching demonstrations, has been characterized as one of the most important methods by which people learn variety of skill and behaviours.The purpose of this study was determined the effect of observational practice on the volleyball service learning with emphasis on the Role of Self–Efficacy. Methods: The Sample consisted of100 male students was assigned accessible sampling technique and homogeneous manner with emphasis on the Role of Self–Efficacy level to 4 groups. The first group performed physical training, the second group performed observational practice task, the third practiced physically and observationally and the fourth group served as the control group. The experimental groups practiced in a one day acquisition and performed the retention task, after 72 hours. Kolmogorov-Smirnov test and independent t-test were used for Statistical analyses. Results and Discussion: Results shows that observation practice task group can significantly improve volleyball services skills acquisition (T=7.73). Also mixed group (physically and observationally) is significantly better than control group regarding to volleyball services skills acquisition (T=7.04). Conclusion: Results have shown observation practice task group and mixed group are significantly better than control group in acquisition test. The present results are in line with previous studies, suggesting that observation learning can improve performance. On the other hand, results shows that self-efficacy level significantly effect on acquisition movement skill. In other words, high self-efficacy is important factor in skill learning level in volleyball service.Keywords: observational practice, volleyball service, self–efficacy, sport science
Procedia PDF Downloads 39730087 Evaluation: Developing An Appropriate Survey Instrument For E-Learning
Authors: Brenda Ravenscroft, Ulemu Luhanga, Bev King
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A comprehensive evaluation of online learning needs to include a blend of educational design, technology use, and online instructional practices that integrate technology appropriately for developing and delivering quality online courses. Research shows that classroom-based evaluation tools do not adequately capture the dynamic relationships between content, pedagogy, and technology in online courses. Furthermore, studies suggest that using classroom evaluations for online courses yields lower than normal scores for instructors, and may affect faculty negatively in terms of administrative decisions. In 2014, the Faculty of Arts and Science at Queen’s University responded to this evidence by seeking an alternative to the university-mandated evaluation tool, which is designed for classroom learning. The Faculty is deeply engaged in e-learning, offering large variety of online courses and programs in the sciences, social sciences, humanities and arts. This paper describes the process by which a new student survey instrument for online courses was developed and piloted, the methods used to analyze the data, and the ways in which the instrument was subsequently adapted based on the results. It concludes with a critical reflection on the challenges of evaluating e-learning. The Student Evaluation of Online Teaching Effectiveness (SEOTE), developed by Arthur W. Bangert in 2004 to assess constructivist-compatible online teaching practices, provided the starting point. Modifications were made in order to allow the instrument to serve the two functions required by the university: student survey results provide the instructor with feedback to enhance their teaching, and also provide the institution with evidence of teaching quality in personnel processes. Changes were therefore made to the SEOTE to distinguish more clearly between evaluation of the instructor’s teaching and evaluation of the course design, since, in the online environment, the instructor is not necessarily the course designer. After the first pilot phase, involving 35 courses, the results were analyzed using Stobart's validity framework as a guide. This process included statistical analyses of the data to test for reliability and validity, student and instructor focus groups to ascertain the tool’s usefulness in terms of the feedback it provided, and an assessment of the utility of the results by the Faculty’s e-learning unit responsible for supporting online course design. A set of recommendations led to further modifications to the survey instrument prior to a second pilot phase involving 19 courses. Following the second pilot, statistical analyses were repeated, and more focus groups were used, this time involving deans and other decision makers to determine the usefulness of the survey results in personnel processes. As a result of this inclusive process and robust analysis, the modified SEOTE instrument is currently being considered for adoption as the standard evaluation tool for all online courses at the university. Audience members at this presentation will be stimulated to consider factors that differentiate effective evaluation of online courses from classroom-based teaching. They will gain insight into strategies for introducing a new evaluation tool in a unionized institutional environment, and methodologies for evaluating the tool itself.Keywords: evaluation, online courses, student survey, teaching effectiveness
Procedia PDF Downloads 26830086 Evaluation of Site Laboratory Conditions Effect on Seismic Design Characteristics in Ramhormoz
Authors: Sayyed Yaghoub Zolfegharifar, Khairul Anuar Kassim, Hossein Khoramrooz, Khodayar Farhadiasl, Sadegh Jahan
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Iran is one of the world's seismically active countries so that it experiences many small to medium earthquakes annually and a large earthquake every ten years. Due to seism tectonic conditions and special geographical and climatic position, Iran has the potential to create numerous severe earthquakes. Therefore, seismicity studies and seismic zonation of seismic zones of the country are necessary. In this article, the effect of local site conditions on the characteristics of seismic design in Rahmormoz will be examined. After analyzing the seismic hazard for Rahmormoz through deterministic and statistical methods and preparing the necessary geotechnical models based on available data, the ground response will be analyzed for different parts of the city based on four inputs and acceleration level estimated for bedrock through the equivalent linear method and by means of Deep Soil program. Finally, through the analysis of the obtained results, the seismic profiles of the ground surface for different parts of the city will be presented.Keywords: seismic microzonation, ground response, resonance spectrum, period, site conditions
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