Search results for: brain emotional learning based intelligent controller

Authors: P. Sawatnatee, S. Udomsuk, K-N. Areerak, K-L. Areerak, A. Srikaew

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The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional method. The controller design using the proposed technique can be used to create the software package for engineers to achieve the optimal controller design of the induction motor speed control based on the indirect vector concept.

Keywords: indirect vector control, induction motor, adaptive tabu search, control design, artificial intelligence

Procedia PDF Downloads 383

Authors: Lara Ann Türeli, Özlem Bozkurt

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There is a biochemical component to listening to music. The type of music listened to can lead to different levels of neurotransmitter and biochemical activity within the brain, resulting in brain stimulation and different moods. Therefore, music plays an important role in neuromarketing and consumer behavior. The quality of a commercial can be measured by the effect the music has on its audience. Thus, understanding how music can affect the brain can provide better marketing strategies for all businesses. The type of music used plays an important role in how a person responds to certain experiences. In the context of marketing and consumer behavior, music can determine whether a person will be intrigued to buy something. Depending on the type of music listened to by an individual; the music may trigger the release of pleasurable neurotransmitters such as dopamine. Dopamine is a neurotransmitter that plays an important role in reward pathways in the brain. When an individual experiences a pleasurable activity, increased levels of dopamine are produced, eventually leading to the formation of new reward pathways. Consequently, the increased dopamine activity within the brain triggered by music can result in new reward pathways along the dopamine pathways in the brain. Selecting pleasurable music for commercials can result in long-term brain stimulation, increasing consumerism. The effect of music on consumerism should be considered not only in commercials but also in the atmosphere it creates within stores. The type of music played in a store can affect consumer behavior and intention. Specifically, the rhythm, pitch, and pace of music can contribute to the mood of the song. The background music in a store can determine the consumer’s emotional presence and consequently affect their intentions. In conclusion, understanding the physiological, psychological, and neurochemical basis of the effect of music on brain stimulation is essential to understand consumer behavior. The role of dopamine in the formation of reward pathways as a result of music directly contributes to consumer behavior and the tendency of a commercial or store to leave a long-term effect on the consumer. The careful consideration of the pitch, pace, and rhythm of a song in the selection of music can not only help companies predict the behavior of a consumer but also determine the behavior of a consumer.

Keywords: sensory processing, neuropsychology, dopamine, neuromarketing

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Authors: V. Sankaranarayanan, V. Amrita Sundari, Sunit P. Gopal

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This paper presents the design and implementation of a nonlinear controller for the point to point control of a mobile inverted pendulum (MIP). The controller is designed based on the kinematic model of the MIP to stabilize all the four coordinates. The stability of the closed-loop system is proved using Lyapunov stability theory. The proposed controller is validated through numerical simulations and also implemented in a laboratory prototype. The results are presented to evaluate the performance of the proposed closed loop system.

Keywords: mobile inverted pendulum, switched control, nonlinear systems, lyapunov stability

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Authors: A. Elnady

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This paper presents an improved Direct Power Control (DPC) scheme applied to the multilevel inverter that forms a Distributed Generation Unit (DGU). This paper demonstrates the performance of active and reactive power injected by the DGU to the smart grid. The DPC is traditionally operated by the hysteresis controller with the Space Vector Modulation (SVM) which is applied on the 2-level inverters or 3-level inverters. In this paper, the DPC is operated by the PI controller with the Phase-Disposition Pulse Width Modulation (PD-PWM) applied to the 5-level diode clamped inverter. The new combination of the DPC, PI controller, PD-PWM and multilevel inverter proves that its performance is much better than the conventional hysteresis-SVM based DPC. Simulations results have been presented to validate the performance of the suggested control scheme in the grid-connected mode.

Keywords: direct power control, PI controller, PD-PWM, and power control

Procedia PDF Downloads 222

Authors: Martins Olatunbosun Babatunde, Muhammed Bashir Muazu, Emmanuel Adewale Adedokun

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This paper presents the development of a double-loop trajectory-tracking controller for the ball and plate system (BPS) using the Normalized Right Coprime Factorization (NRCF) scheme.The Linear Algebraic (LA) method is used to design the inner loop required to stabilize the ball, while H-infinity NRCF method, that involved the lead-lag compensator design approach, is used to develop the outer loop that controls the plate. Simulation results show that the plate was stabilized at 0.2989 seconds and the ball was able to settle after 0.9646 seconds, with a trajectory tracking error of 0.0036. This shows that the controller has good adaptability and robustness.

Keywords: ball and plate system, normalized right coprime factorization, linear algebraic method, compensator, controller, tracking.

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Authors: Ahmad Fahad Alotaibi, Khalid Hamed Hajri, Humoud Hudiban Rashidi

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Intelligent information technology infrastructure is considered one of the enablers to enhance digital transformation in the gas and oil fields to optimize IT infrastructure reliability by supporting operations and maintenance in a safe and secure method to optimize resources. Smart IT buildings, communication rooms and shelters with intelligent technologies can strengthen the performance and profitability of gas and oil companies by ensuring business continuity. This paper describes the advantages of deploying intelligent IT infrastructure in the oil and gas industry by illustrating its positive impacts on some development aspects, for instance, operations, maintenance, safety, security and resource optimization. Moreover, it highlights the challenges and difficulties of providing smart IT services in a remote area and proposes solutions to overcome such difficulties.

Keywords: intelligent IT infrastructure, remote areas, oil and gas field, digitalization

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Authors: Omar Al Ali

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The current study was aimed to explore the relationships between emotional intelligence, cognitive ability, and leader's performance. Data were collected from 260 senior managers from UAE. The results showed that there are significant relationships between emotional intelligence and leadership performance as measured by the annual internal evaluations of each participant (r = .42, p < .01). Data from regression analysis revealed that both variables namely emotional intelligence (beta = .31, p < .01), and cognitive ability (beta = .29, p < .01), predicted leadership competencies, and together explained 26% of its variance. Data suggests that EI and cognitive ability are significantly correlated with leadership performance. In depth implications of the present findings for human resource development theory and practice are discussed.

Keywords: emotional intelligence, cognitive ability, leadership, performance

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Authors: Shafaq Rubab

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The inclusion of special needs students in a classroom is prevailing gradually in developing countries. Digital game-based learning is one the most effective instructional methodology for special needs students. Digital game-based learning facilitates special needs students who actually face challenges and obstacles in their learning processes. This study aimed to evaluate the effectiveness of digital game-based learning on the educational progress of special needs students in developing countries. The quasi-experimental research was conducted by using purposively selected sample size of eight special needs students. Results of both experimental and control group showed that performance of the experimental group students was better than the control group students and there was a significant difference between both groups’ results. This research strongly recommended that digital game-based learning can help special needs students in an inclusive classroom. It also revealed that special needs students can learn efficiently by using pedagogically sound learning games and game-based learning helps a lot for the self-paced fast-track learning system.

Keywords: inclusive education, special needs, digital game-based learning, fast-track learning

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

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Authors: Simeon Mayala, Ida Herdlevær, Jonas Bull Haugsøen, Shamundeeswari Anandan, Sonia Gavasso, Morten Brun

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In this paper, we propose a minimum spanning tree-based method for segmenting brain tumors. The proposed method performs interactive segmentation based on the minimum spanning tree without tuning parameters. The steps involve preprocessing, making a graph, constructing a minimum spanning tree, and a newly implemented way of interactively segmenting the region of interest. In the preprocessing step, a Gaussian filter is applied to 2D images to remove the noise. Then, the pixel neighbor graph is weighted by intensity differences and the corresponding minimum spanning tree is constructed. The image is loaded in an interactive window for segmenting the tumor. The region of interest and the background are selected by clicking to split the minimum spanning tree into two trees. One of these trees represents the region of interest and the other represents the background. Finally, the segmentation given by the two trees is visualized. The proposed method was tested by segmenting two different 2D brain T1-weighted magnetic resonance image data sets. The comparison between our results and the standard gold segmentation confirmed the validity of the minimum spanning tree approach. The proposed method is simple to implement and the results indicate that it is accurate and efficient.

Keywords: brain tumor, brain tumor segmentation, minimum spanning tree, segmentation, image processing

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Authors: Behnoush Sabayan, Ali Alidadi, Saeid Ebarhimi, N. M. Bakhshani

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Hemodialysis (HD) patients are at a high risk of atherosclerotic and vascular disease; also little information is available for the HD impact on brain structure of these patients. We studied the brain abnormalities in HD patients. The aim of this study was to investigate the effect of long term HD on brain structure of HD patients. Non-contrast MRI was used to evaluate imaging findings. Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% were female. According to study, HD patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had small vessel ischemia than the HD patients who underwent HD for a shorter term, which the median time was 3 to 5 months. Most of the small vessel ischemia was located in pre-ventricular, subcortical and white matter (1.33± .471, 1.23± .420 and 1.39±.490). However, the other brain damages like: central pons abnormality, global brain atrophy, thinning of corpus callosum and frontal lobe atrophy were found (P<0.01). The present study demonstrated that HD patients who were under HD for a longer time had small vessel ischemia and we conclude that this small vessel ischemia might be a causative mechanism of brain atrophy in chronic hemodialysis patients. However, additional researches are needed in this area.

Keywords: Hemodialysis Patients, Duration of Hemodialysis, MRI, Zahedan

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Authors: Mahdi Farajzadeh Ajirlou

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Ordinary fetal brain development can be considered by in vivo attractive reverberation imaging (MRI) from the 18th gestational week (GW) to term and depends fundamentally on T2-weighted and diffusion-weighted (DW) arrangements. The foremost commonly suspected brain pathologies alluded to fetal MRI for assist assessment are ventriculomegaly, lost corpus callosum, and anomalies of the posterior fossa. Brain division could be a crucial to begin with step in neuroimage examination. Within the case of fetal MRI it is especially challenging and critical due to the subjective introduction of the hatchling, organs that encompass the fetal head, and irregular fetal movement. A few promising strategies have been proposed but are constrained in their execution in challenging cases and in realtime division. Fetal MRI is routinely performed on a 1.5-Tesla scanner without maternal or fetal sedation. The mother lies recumbent amid the course of the examination, the length of which is ordinarily 45 to 60 minutes. The accessibility and continuous approval of standardizing fetal brain development directions will give critical devices for early discovery of impeded fetal brain development upon which to oversee high-risk pregnancies.

Keywords: brain, fetal, MRI, imaging

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Authors: Ogunremi Beatrice, Oluwole David Adebayo

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Public secondary school students are face with some challenges from the parents, government and teachers in school. Some of the challenges that arises from the parents are lack of attention and adequate communication. From the government are unavailability of useful instructional materials, competent and professionally trained teachers for each subject the students do in school. The challenges that arise from the teachers most often are mismanagement of time, inability to understand the capacity of the student and lack class management and follow up. This study investigated self-regulation, emotional intelligence, self-efficacy and goal orientation as predictors of school engagement among public secondary school students in Ibadan. A structured questionnaire was administered on 258 students from six mixed secondary schools in Ibadan. Pearson Product Moment Correlation method was used for data analysis. Four hypothesis were raised and answered, the results showed there is positive and significant relationships between school engagement among public secondary school students and each of the independent variable: Self-regulation, Emotional intelligence, Self-efficacy, Goal orientation. On the basis of these findings, it was recommended that the parents have to encourage their children on how to be goal oriented ,build their self-efficacy skill, to be self-regulated and emotionally intelligent in order to be effective in school and be able to increase their intellectual ability.

Keywords: emotional intelligence, self-efficacy, goal orientation, school engagement, self-regulation

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Authors: J. Mano Ranjini

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Each and every child is special, born with a unique talent to explore this world. The word Dyslexia is derived from the Greek language in which “dys” meaning poor or inadequate and “lexis” meaning words or language. Dyslexia describes about a different kind of mind, which is often gifted and productive, that learns the concept differently. The main aim of the study is to bring the positive outcome of the reading level by examining the effectiveness of Visual Auditory Kinesthetic Tactile technique on Reading Level among Dyslexic Children at Helikx Open School and Learning Centre. A Quasi experimental one group pretest post test design was adopted for this study. The Reading Level was assessed by using the Schonell Graded Word Reading Test. Thirty subjects were drawn by using purposive sampling technique and the intervention Visual Auditory Kinesthetic Tactile technique was implemented to the Dyslexic Children for 30 consecutive days followed by the post Reading Level assessment revealed the improvement in the mean score value of reading level by 12%. Multi-sensory (VAKT) teaching uses all learning pathways in the brain (visual, auditory, kinesthetic-tactile) in order to enhance memory and learning and the ability in uplifting emotional, physical and societal dimensions. VAKT is an effective method to improve the reading skill of the Dyslexic Children that ensures the enormous significance of learning thereby influencing the wholesome of the child’s life.

Keywords: visual auditory kinesthetic tactile technique, reading level, dyslexic children, Helikx Open School

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Authors: Adi Gielgun-Katz, Alina S. Rusu

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In the last two decades, education systems worldwide have integrated new pedagogical methods and strategies in lesson plans, such as innovative technologies, social-emotional learning (SEL), gamification, mixed learning, multiple literacies, and many others. Visual language, such as photographs, is known to transcend cultures and languages, and it is commonly used by youth to express positions and affective states in social networks. Therefore, visual language needs more educational attention as a linguistic and communicative component that can create connectedness among the students and their teachers. Nowadays, when SEL is gaining more and more space and meaning in the area of academic improvement in relation to social well-being, and taking and sharing pictures is part of the everyday life of the majority of people, it becomes natural to add the visual language to SEL approach as a reinforcement strategy for connecting education to the contemporary culture and language of the youth. This article presents a program conducted in a high school class in Israel, which combines the five SEL with photography techniques, i.e., Social-Emotional Learning Visual Empowerments (SELVEs) program (experimental group). Another class of students from the same institution represents the control group, which is participating in the SEL program without the photography component. The SEL component of the programs addresses skills such as: troubleshooting, uncertainty, personal strengths and collaboration, accepting others, control of impulses, communication, self-perception, and conflict resolution. The aim of the study is to examine the effects of programs on the level of the five SEL aspects in the two groups of high school students: Self-Awareness, Social Awareness, Self-Management, Responsible Decision Making, and Relationship Skills. The study presents a quantitative assessment of the SEL programs’ impact on the students. The main hypothesis is that the students’ questionnaires' analysis will reveal a better understanding and improvement of the five aspects of the SEL in the group of students involved in the photography-enhanced SEL program.

Keywords: social-emotional learning, photography, education program, adolescents

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Authors: Jin Xu

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5G network developers need to satisfy the necessary requirements of additional capacity from massive users and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in network is motivating operators to combine long-term evolution (LTE) with intelligent spectrum management technology. This new LTE intelligent spectrum management in unlicensed band (LTE-U) has the physical layer topology to access spectrum, specifically the 5-GHz band. We proposed a new intelligent cloud RAN for 5G.

Keywords: cloud radio access network, wireless network, cloud computing, multi-agent

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Authors: Sathapath Kilaso

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Attendance checking in the classroom for student is object to record the student’s attendance in order to support the learning activities in the classroom. Despite the teaching trend in the 21st century is the student-center learning and the lecturer duty is to mentor and give an advice, the classroom learning is still important in order to let the student interact with the classmate and the lecturer or for a specific subject which the in-class learning is needed. The development of the system prototype by applied the microcontroller technology and embedded system with the “internet of thing” trend and the web socket technique will allow the lecturer to be alerted immediately whenever the data is updated.

Keywords: arduino, embedded system, classroom, raspberry PI

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Olusegun Omoluwa, Kolawole Israel Anthony

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Pupils with learning disabilities are found in every classroom, but because learning disabilities cannot be seen, the condition is often too neglected. Unless these pupils are recognised and treated, they are likely to become educational discards. This study consequently attempted to determine effects of self-monitoring strategy on homework completion among pupils with learning disabilities. Ninety (90) participants were engaged in the study. Pre-test, post-test, control group quasi experimental design was adopted. Purposive sampling technique was used to select pupils with evidence of learning disabilities from three primary schools in Ondo State. Findings showed that self-monitoring strategy was significant in enhancing homework completion among pupils with learning disabilities. However, gender and self-esteem did not significantly contribute to homework completion. The study therefore recommended that measures such that would uncover unsettling academic, psychological and emotional deficiencies of these pupils through appropriate diagnosis should be undertaken by the parents and teachers, in order for them to have a sense of belonging in the society.

Keywords: self monitoring, home work completion, learning dissabilities, learning

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Authors: Kian Jon Chua, Islam Md Raisul

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Findings on a research study conducted for a group of year-2 engineering students participating in a flipped classroom (FC) experience that is judiciously incorporated into project-based learning (PBL) module are presented. The chief purpose of the research is to identify whether if the incorporation of flipped classroom approach to project-based learning indeed yields a positive learning experience for engineering students. Results are presented and compared from the two classes of students – one is subjected to a traditional PBL learning mode while the other undergoes a hybrid PBL-FC learning format. Some themes related to active learning, problem-solving ability, teacher as facilitator, and degree of self-efficacy are also discussed. This paper hopes to provide new knowledge and insights relating to the introduction of flipped classroom learning to a project-based engineering module. Some potential study limitations and future directions to address them are also presented.

Keywords: hybrid project-based learning, flipped classroom, problem-solving, active learning

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Authors: Sherine Shafik Aly, Farida Ahmed El Mallah

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Technology is a quoted keyword nowadays in all fields; it has been recently thought of and integrated into urban development. This research explains the role of technology in establishing intelligent urbanism to create a convivial and sustainable environment for people to live in. Cities are downgrading socially, economically and environmentally. A framework is to be developed where these three pillars are involved in the planning, design, and spreading of technology to create convivial environments. The aim of this research is achieved by highlighting the importance and approaches of intelligent urbanism, it’s characteristics and principles, then analyzing some relevant examples to achieve a set of guidelines.

Keywords: convivial, intelligent, technology, urban development

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Authors: Menelaos N. Katsantonis, Athanasios Manikas, Alexandros Chatzis, Stavros Doropoulos, Anastasios Avramis, Ioannis Mavridis

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Museums enhance their potential by adopting new technologies and techniques to appeal to more visitors and engage them in creative and joyful activities. In this study, the Haptic Cycle is presented, a cycle of museum activities proposed for the development of museum learning approaches with optimized effectiveness and engagement. Haptic Cycle envisages the improvement of the museum’s services by offering a wide range of activities. Haptic Cycle activities make the museum’s exhibitions more approachable by bringing them closer to the visitors. Visitors can interact with the museum’s artifacts and explore them haptically and sonically. Haptic Cycle proposes constructivist learning activities in which visitors actively construct their knowledge by exploring the artifacts, experimenting with them and realizing their importance. Based on the Haptic Cycle, we developed the HapticSOUND system, an innovative virtual reality system that includes an advanced user interface that employs gesture-based technology. HapticSOUND’s interface utilizes the leap motion gesture recognition controller and a 3D-printed traditional Cretan lute, utilized by visitors to perform various activities such as exploring the lute and playing notes and songs.

Keywords: haptic cycle, HapticSOUND, museum learning, gesture-based, leap motion

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Authors: Malak Alqaydhi

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A problem in the Saudi Arabia education system is that there is a lack of curriculum- based Social, emotional learning (SEL) teaching practices with the pedagogical concept of SEL yet to be practiced in the Kingdom of Saudi Arabia (KSA). Furthermore, voices of teachers and parents have not been captured regarding the use of SEL, particularly in preschools. The importance of this research is to help determine, with the input of teachers and mothers of preschoolers, the efficacy of a culturally adapted SEL program. The purpose of this research is to determine the most appropriate SEL intervention method to appropriately apply in the cultural context of the Saudi preschool classroom setting. The study will use a mixed method exploratory sequential research design, applying qualitative and quantitative approaches including semi-structured interviews with teachers and parents of preschoolers and an experimental research approach. The research will proceed in four phases beginning with a series of interviews with Saudi preschool teachers and mothers, whose voices and perceptions will help guide the second phase of selection and adaptation of a suitable SEL preschool program. The third phase will be the implementation of the intervention by the researcher in the preschool classroom environment, which will be facilitated by the researcher’s cultural proficiency and practical experience in Saudi Arabia. The fourth and final phase will be an evaluation to assess the effectiveness of the trialled SEL among the preschool student participants. The significance of this research stems from its contribution to knowledge about SEL in culturally appropriate Saudi preschools and the opportunity to support initiatives for Saudi early childhood educators to consider implementing SEL programs. The findings from the study may be useful to inform the Saudi Ministry of Education and its curriculum designers about SEL programs, which could be beneficial to trial more widely in the Saudi preschool curriculum.

Keywords: social emotional learning, preschool children, saudi Arabia, child behavior

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: Endri Rama, Genci Capi, Shigenori Kawahara

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The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: brain-machine interface, decision-making, mobile robot, neural network

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Authors: Aisha Khalid, Talha Aftab, Fareeha Zafar

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This paper investigates the impact of emotional intelligence on job satisfaction and organizational commitment at workplace in the doctors; age ranging from 25 to 32 years. Job satisfaction and organizational commitment have been considered as important issue in terms of high quality services and superior performance. This paper presents a field survey conducted in 9 different public sector hospitals which operate in Punjab, Pakistan. 250 questionnaires were distributed out of which 180 returned back were showing 72% response rate, confirming the significant positive relationship between emotional intelligence and job satisfaction and emotional intelligence and organizational commitment.

Keywords: emotional intelligence, job satisfaction, organizational commitment, young doctors

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Authors: Halkiopoulos Constantinos, Gkintoni Evgenia, Koutsopoulou Ioanna, Antonopoulou Hera

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E-sports and e-gaming have emerged in recent years since the increase in internet use have become universal and e-gamers are the new reality in our homes. The excessive involvement of young adults with e-sports has already been revealed and the adverse consequences have been reported in researches in the past few years, but the issue has not been fully studied yet. The present research is conducted in Greece and studies the psychological profile of video game players and provides information on personality traits, habits and emotional status that affect online gamers’ behaviors in order to help professionals and policy makers address the problem. Three standardized self-report questionnaires were administered to participants who were young male and female adults aged from 19-26 years old. The Profile of Mood States (POMS) scale was used to evaluate people’s perceptions of their everyday life mood; the personality features that can trace back to people’s habits and anticipated reactions were measured by Eysenck Personality Questionnaire (EPQ), and the Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure which cognitive (gamers’ beliefs) and emotional parameters (gamers’ emotional abilities) mainly affected/ predicted gamers’ behaviors and leisure time activities?/ gaming behaviors. Data mining techniques were used to analyze the data, which resulted in machine learning algorithms that were included in the software package R. The research findings attempt to designate the effect of personality traits, emotional status and emotional intelligence influence and correlation with e-sports, gamers’ behaviors and help policy makers and stakeholders take action, shape social policy and prevent the adverse consequences on young adults. The need for further research, prevention and treatment strategies is also addressed.

Keywords: e-sports, e-gamers, personality traits, POMS, emotional intelligence, data mining, R

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Authors: M. Saard, A. Kolk, K. Sepp, L. Pertens, L. Reinart, C. Kööp

Abstract:

Introduction: Social competence is often impaired in children with acquired brain injury (ABI), but evidence-based rehabilitation for social skills has remained undeveloped. Modern technology-based methods create effective and safe learning environments for pediatric social skills remediation. The aim of the study was to implement our structured model of neuro rehab for socio-cognitive deficit using multitouch-multiuser tabletop (MMT) computer-based platforms and virtual reality (VR) technology. Methods: 40 children aged 8-13 years (yrs) have participated in the pilot study: 30 with ABI -epilepsy, traumatic brain injury and/or tic disorder- and 10 healthy age-matched controls. From the patients, 12 have completed the training (M = 11.10 yrs, SD = 1.543) and 20 are still in training or in the waiting-list group (M = 10.69 yrs, SD = 1.704). All children performed the first individual and paired assessments. For patients, second evaluations were performed after the intervention period. Two interactive applications were implemented into rehabilitation design: Snowflake software on MMT tabletop and NoProblem on DiamondTouch Table (DTT), which allowed paired training (2 children at once). Also, in individual training sessions, HTC Vive VR device was used with VR metaphors of difficult social situations to treat social anxiety and train social skills. Results: At baseline (B) evaluations, patients had higher deficits in executive functions on the BRIEF parents’ questionnaire (M = 117, SD = 23.594) compared to healthy controls (M = 22, SD = 18.385). The most impaired components of social competence were emotion recognition, Theory of Mind skills (ToM), cooperation, verbal/non-verbal communication, and pragmatics (Friendship Observation Scale scores only 25-50% out of 100% for patients). In Sentence Completion Task and Spence Anxiety Scale, the patients reported a lack of friends, behavioral problems, bullying in school, and social anxiety. Outcome evaluations: Snowflake on MMT improved executive and cooperation skills and DTT developed communication skills, metacognitive skills, and coping. VR, video modelling and role-plays improved social attention, emotional attitude, gestural behaviors, and decreased social anxiety. NEPSY-II showed improvement in Affect Recognition [B = 7, SD = 5.01 vs outcome (O) = 10, SD = 5.85], Verbal ToM (B = 8, SD = 3.06 vs O = 10, SD = 4.08), Contextual ToM (B = 8, SD = 3.15 vs O = 11, SD = 2.87). ToM Stories test showed an improved understanding of Intentional Lying (B = 7, SD = 2.20 vs O = 10, SD = 0.50), and Sarcasm (B=6, SD = 2.20 vs O = 7, SD = 2.50). Conclusion: Neurorehabilitation based on the Structured Model of Neurorehab for Socio-Cognitive Deficit in children with ABI were effective in social skills remediation. The model helps to understand theoretical connections between components of social competence and modern interactive computerized platforms. We encourage therapists to implement these next-generation devices into the rehabilitation process as MMT and VR interfaces are motivating for children, thus ensuring good compliance. Improving children’s social skills is important for their and their families’ quality of life and social capital.

Keywords: acquired brain injury, children, social skills deficit, technology-based neurorehabilitation

Procedia PDF Downloads 104

Authors: Amir Salamatzade, Marhamet HematPour

Abstract:

Due to the increasing importance of psychological factors in the incidence and exacerbation of chronic diseases such as multiple sclerosis, the aim of this study was to determine the difference between emotional regulation strategies and psychological symptoms in patients with multiple sclerosis and normal people. The research method was causal-comparative (post-event). The statistical population of this research included all patients with multiple sclerosis referred to the MS Association of Rasht in the first quarter of 2021, approximately 350 people. The study sample also included 120 people (60 patients with multiple sclerosis and 60 normal people) who were selected by the available sampling method and completed the emotional regulation and anxiety, depression, and stress Lavibund and Lavibund (1995) questionnaires. Data were analyzed using an independent t-test and multivariate variance analysis. The results showed that there was a significant difference between the mean of emotional regulation strategies and the components of emotional reassessment and emotional inhibition between the two groups of patients with multiple sclerosis and normal individuals (p < 0.01). There is a significant difference between the mean of psychological symptoms and the components of depression, anxiety, and stress in the two groups of patients with multiple sclerosis and normal individuals. (p < 0.01). Based on this, it can be concluded that patients with multiple sclerosis have lower levels of emotional regulation strategies and higher levels of psychological symptoms than normal individuals.

Keywords: emotional regulation strategies, psychological symptoms, multiple sclerosis, normal Individuals

Procedia PDF Downloads 195