Search results for: virtual hands-on learning

Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

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

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

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Authors: Badiy Elmabrouk, Abdelhamid Boujarif, Zhiguo Zeng, Stephane Borrel, Robert Heidsieck

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In an era where sustainability is paramount, this paper introduces a machine learning-driven testing protocol to accurately predict diode failures, merging reliability engineering with failure physics to enhance repair operations efficiency. Our approach refines the burn-in process, significantly curtailing its duration, which not only conserves energy but also elevates productivity and mitigates component wear. A case study from GE HealthCare’s repair center vividly demonstrates the method’s effectiveness, recording a high prediction of diode failures and a substantial decrease in energy consumption that translates to an annual reduction of 6.5 Tons of CO2 emissions. This advancement sets a benchmark for environmentally conscious practices in the electronics repair sector.

Keywords: maintenance, burn-in, failure physics, reliability testing

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Authors: Margarita Zavala, Julio Rolón, Gabriel Chavira, José González, Jorge Orozco, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally at this stage is when the middle school level is studied. In 2006 in Mexico incorporated “mentoring" space to assist students in their integration and participation in life. In public middle schools, is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. Whit this they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Tshepang Tshube

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The primary purpose of this study was to examine student-athletes’ experiences, particularly an in-depth account of balancing school and sport. The secondary objective was to assess student-athletes’ susceptibility to the effects of the “dumb-jock” stereotype threat and also determine the strength of athletic and academic identity as predicated by the extent to which stereotype is perceived by student-athletes. Sub-objectives are (a) examine support structures available for student-athletes in their respective academic institutions, (b) to establish the most effective ways to address student-athletes’ learning needs, (c) to establish crucial entourage members who play a pivotal role in student-athletes’ academic pursuits, (d) and unique and effective ways lecturers and coaches can contribute to student-athletes’ learning experiences. To achieve the above stated objectives, the study used a mixed methods approach. A total of 110 student-athletes from colleges and universities in Botswana completed an online survey that was followed by semi-structured interviews with eight student-athletes, and four coaches. The online survey assessed student-athletes’ demographic variables, measured athletic (AIMS), academic (modified from AIMS) identities, and perceived stereotype threat. Student-athletes reported a slightly higher academic identity (M=5.9, SD= .85) compared to athletic identity (M=5.4, SD=1.0). Student-athletes reported a moderate mean (M=3.6, SD=.82) just above the midpoint of the 7-point scale for stereotype threat. A univariate ANOVA was conducted to determine if there was any significant difference between university and college brackets in Botswana with regard to three variables: athletic identity, student identity and stereotype threat. The only significant difference was in the academic identity (Post Hoc-Tukey Student Identity: Bracket A < Bracket B, Bracket C) with Bracket A schools being the least athletically competitive. Bracket C and B are the most athletically competitive brackets in Botswana. Follow-up interviews with student-athletes and coaches were conducted. All interviews lasted an average of 55 minutes. Following all the interviews, all recordings were transcribed which is an obvious first step in qualitative data analysis process. The researcher and an independent academic with experience in qualitative research independently listened to all recordings of the interviews and read the transcripts several times. Qualitative data results indicate that even though student-athletes reported a slightly higher student identity, there are parallels between sports and academic structures on college campuses. Results also provide evidence of lack of academic support for student-athletes. It is therefore crucial for student-athletes to have access to academic support services (e.g., tutoring, flexible study times, and reduced academic loads) to meet their academic needs. Coaches and lecturers play a fundamental role in sporting student-athletes. Coaches and professors’ academic efficacy on student-athletes enhances student-athletes’ academic confidence. Results are discussed within the stereotype threat theory.

Keywords: athletic identity, colligiate sport, sterotype threat, student athletes

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the newly developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: demand forecasting, machine learning, risk management, supply chain design

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Authors: Fatin Mansour Daas

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Language education responds to and is reflective of emerging social and political trends. Language policies and practices are shaped by political, economic, social and cultural considerations. Following this, Israeli language education policy as implemented in Arab schools in Israel is influenced by the particular political and social situation of Arab-Palestinian citizens of Israel. This national group remained in their homeland following the war in 1948 between Israel and its Arab neighbors and became Israeli citizens following the establishment of the State of Israel. This study examines language policy in Arab schools in Israel from 1948 until the present time in light of the unique experience of the Palestinian Arab homeland minority in Israel with a particular focus on questions of politics and identity. The establishment of the State of Israel triggered far-reaching political, social and educational transformations within Arab Palestinian society in Israel, including in the area of language and language studies. Since 1948, the linguistic repertoire of Palestinian Arabs in Israel has become more complex and diverse, while the place and status of different languages have changed. Following the establishment of the State of Israel, only Hebrew and Arabic were retained as the official languages, and Israeli policy reflected this in schools as well: with the advent of the Jewish state, Hebrew language education among Palestinians in Israel has increased. Similarly, in Arab Palestinian schools in Israel, English is taught as a third language, Hebrew as a second language, and Arabic as a first language – even though it has become less important to native Arabic speakers. This research focuses on language studies and language policy in the Arab school system in Israel from 1948 onwards. It will analyze the relative focus of language education between the different languages, the rationale of various language education policies, and the pedagogic approach used to teach each language and student achievements vis-à-vis language skills. This study seeks to understand the extent to which Arab schools in Israel are multi-lingual by examining successes, challenges and difficulties in acquiring the respective languages. This qualitative study will analyze five different components of language education policy: (1) curriculum, (2) learning materials; (3) assessment; (4) interviews and (5) archives. Firstly, it consists of an analysis examining language education curricula, learning materials and assessments used in Arab schools in Israel from 1948-2018 including a selection of language textbooks for the compulsory years of study and the final matriculation (Bagrut) examinations. The findings will also be based on archival material which traces the evolution of language education policy in Arabic schools in Israel from the years 1948-2018. This archival research, furthermore, will reveal power relations and general decision-making in the field of the Arabic education system in Israel. The research will also include interviews with Ministry of Education staff who provide instructional oversight in the instruction of the three languages in the Arabic education system in Israel. These interviews will shed light on the goals of language education as understood by those who are in charge of implementing policy.

Keywords: language education policy, languages, multilingualism, language education, educational policy, identity, Palestinian-Arabs, Arabs in Israel, educational school system

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Authors: Ebenezer Joseph

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Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

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Authors: Atara Shriki, Ilana Lavy

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In a rapidly changing technological society, creativity is considered as an engine of economic and social progress. No doubt the education system has a central role in nurturing all students’ creativity, however, it is normally not encouraged at school. The causes of this reality are related to a variety of circumstances, among them: external pressures to cover the curriculum and succeed in standardized tests that mostly require algorithmic thinking and implementation of rules; teachers’ tendency to teach similarly to the way they themselves were taught as school students; relating creativity to giftedness, and therefore avoid nurturing all students' creativity; lack of adequate learning materials and accessible tools for following and evaluating the development of students’ creativity; and more. Since success in academic studies requires, among other things, creativity, lecturers in higher education institutions should consider appropriate ways to nurture students’ creative thinking and assess its development. Obviously, creativity has a multifaceted nature, numerous definitions, various perspectives for studying its essence (e.g., process, personality, environment, and product), and several approaches aimed at evaluating and assessing creative expressions (e.g., cognitive, social-personal, and psychometric). In this framework, we suggest nurturing students’ creativity through engaging them in problem posing activities that are part of inquiry assignments. In order to assess the development of their creativity, we propose to employ a model that was designed for this purpose, based on the psychometric approach, viewing the posed problems as the “creative product”. The model considers four measurable aspects- fluency, flexibility, originality, and organization, as well as a total score of creativity that reflects the relative weights of each aspect. The scores given to learners are of two types: (1) Total scores- the absolute number of posed problems with respect to each of the four aspects, and a final score of creativity; (2) Relative scores- each absolute number is transformed into a number that relates to the relative infrequency of the posed problems in student’s reference group. Through converting the scores received over time into a graphical display, students can assess their progress both with respect to themselves and relative to their reference group. Course lecturers can get a picture of the strengths and weaknesses of each student as well as the class as a whole, and to track changes that occur over time in response to the learning environment they had generated. Such tracking may assist lecturers in making pedagogical decisions about emphases that should be put on one or more aspects of creativity, and about the students that should be given a special attention. Our experience indicates that schoolteachers and lecturers in higher education institutes find the combination of engaging learners in problem posing along with self-assessment of their progress through utilizing the graphical display of accumulating total and relative scores has the potential to realize most learners’ creative potential.

Keywords: creativity, problem posing, psychometric model, self-assessment

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Authors: Lindelwa Pepu

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Visual Arts and Visual Literacy are defined with distinction from one another. Visual Arts are known for art forms such as drawing, painting, and photography, just to name a few. At the same time, Visual Literacy is known for learning through images. The Visual Literacy phenomenon may be attributed to the use of images was first established for creating memories and enjoyment. As time evolved, images became the center and essential means of making contact between people. Gradually, images became a means for interpreting and understanding words through visuals, that being Visual Arts. The purpose of this study is to present the analogy of the two terms Visual Arts and Visual Literacy, which are defined and compared through early practicing visual artists as well as relevant researchers to reveal how they interrelate with one another. This is a qualitative study that uses an interpretive approach as it seeks to understand and explain the interest of the study. The results reveal correspondence of the analogy between the two terms through various writers of early and recent years. This study recommends the significance of the two terms and the role they play in relation to other fields of study.

Keywords: visual arts, visual literacy, pictures, images

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Authors: J. C. Moctezuma, V. Breña-Medina, Jose Luis Nunez-Yanez, Joseph P. McGeehan

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In this work we make a bifurcation analysis for a single compartment representation of Traub model, one of the most important conductance-based models. The analysis focus in two principal parameters: current and leakage conductance. Study of stable and unstable solutions are explored; also Hop-bifurcation and frequency interpretation when current varies is examined. This study allows having control of neuron dynamics and neuron response when these parameters change. Analysis like this is particularly important for several applications such as: tuning parameters in learning process, neuron excitability tests, measure bursting properties of the neuron, etc. Finally, a hardware implementation results were developed to corroborate these results.

Keywords: Traub model, Pinsky-Rinzel model, Hopf bifurcation, single-compartment models, bifurcation analysis, neuron modeling

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: M. Pellerone, S. G. Razza, L. Miano, A. Miccichè, M. Adamo

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The teacher’s attitude plays a decisive role in promoting the development of the non-native or disabled student and counteracting hypothetical negative attitudes and prejudice towards those who are “different”.The objective of the present research is to measure the relationship between teachers’ prejudices towards disabled and/or immigrant students as predictors of teaching-learning strategies. A cross-sectional study involved 200 Italian female teachers who completed an anamnestic questionnaire, the Assessment Teaching Scale, the Italian Modern and Classical Prejudices Scale towards people with ID, and the Pettigrew and Meertens’ Blatant Subtle Prejudice Scale. Confirming research hypotheses, data underlines the predictive role of prejudice on teaching strategies, and in particular on the socio-emotional and communicative-relational dimensions. Results underline that general training appears necessary, especially for younger generations of teachers.

Keywords: disabled students, immigrant students, instructional competence, prejudice, teachers

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Authors: Mairo Musa Galadima, Phoebe Mshelia

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In Nigeria, the national policy of education stipulates that the kindergarten primary schools and the legislature are to use the three popular Nigerian Languages namely: Hausa, Igbo and Yoruba. However, the English language seems to be preferred and this calls for this paper. Attempts were made to draw out the challenges faced by learners in understanding English speech sounds and using them to communicate effectively in English; using 5(five) selected secondary school in Bauchi. It was discover that challenges abound in the wrong use of stress and intonation, transfer of phonetic features from their first language. Others are inadequate qualified teachers and relevant materials including text-books. It is recommended that teachers of English should lay more emphasis on the teaching of supra-segmental features and should be encouraged to go for further studies, seminars and refresher courses.

Keywords: kindergarten, stress, phonetic and intonation, Nigeria

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Lulu Wang, Yongjun Xu, Xiaoyang Qiao

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The Forbidden City is well known for being full of Chinese cultural and historical relics. However, the Masters in the Forbidden City, a documentary film, doesn’t just dwell on the stories of the past. Instead, it focuses on ordinary people—the restorers of the relics and antiquities, which has caught the sight of Chinese audiences. From this popular documentary film, a new way can be considered, that is to show the relics, antiquities and painting with a character of modern humanities by films and TV programs. Of course, it can’t just like a simple explanation from tour guides in museums. It should be a perfect combination of scenes, heritages, stories, storytellers and background music. All we want to do is trying to dig up the humanity behind the heritages and then create a virtual scene for the audience to have emotional resonance from the humanity. It is believed that there are two problems. One is that compared with the entertainment shows, why people prefer to see the boring restoration work. The other is that what the interaction is between those history documentary films, the heritages, the audiences and collective memory. This paper mainly used the methods of text analysis and data analysis. The audiences’ comment texts were collected from all kinds of popular video sites. Through analyzing those texts, there was a word cloud chart about people preferring to use what kind of words to comment the film. Then the usage rate of all comments words was calculated. After that, there was a Radar Chart to show the rank results. Eventually, each of them was given an emotional value classification according their comment tone and content. Based on the above analysis results, an interaction model among the audience, history films/TV programs and the collective memory can be summarized. According to the word cloud chart, people prefer to use such words to comment, including moving, history, love, family, celebrity, tone... From those emotional words, we can see Chinese audience felt so proud and shared the sense of Collective Identity, so they leave such comments: To our great motherland! Chinese traditional culture is really profound! It is found that in the construction of collective memory symbology, the films formed an imaginary system by organizing a ‘personalized audience’. The audience is not just a recipient of information, but a participant of the documentary films and a cooperator of collective memory. At the same time, it is believed that the traditional background music, the spectacular present scenes and the tone of the storytellers/hosts are also important, so it is suggested that the museums could try to cooperate with the producers of movie and TV program to create a vivid scene for the people. Maybe it’s a more artistic way for heritages to be open to all the world.

Keywords: audience, heritages, history movies, TV programs

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Authors: Haider Javed Uppal, Javed Yunas Uppal

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In today's globalized world, it is necessary to develop a form of music that is able to evoke equal emotional responses among people from diverse cultural backgrounds. Indigenous cultures throughout history have developed their own music cognition, specifically in terms of the connections between music and mood. With the advancements in artificial intelligence technologies, it has become possible to analyze and categorize music features such as timbre, harmony, melody, and rhythm and relate them to the resulting mood effects experienced by listeners. This paper presents a model that utilizes a screenshot translator to convert music from different origins into waveforms, which are then analyzed using machine learning and information retrieval techniques. By connecting these waveforms with Thayer's matrix of moods, a mood classifier has been developed using fuzzy logic algorithms to determine the emotional impact of different types of music on listeners from various cultures.

Keywords: cognition, world music, artificial intelligence, Thayer’s matrix

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Authors: Girish Prayag, Wantanee Suntikul, Elizabeth Agyeiwaah

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Current research on dark tourism largely follows residents’ perspectives with limited evaluations of tourists’ experiences. Unravelling the case of a dark heritage site in Elmina, Ghana, this paper develops a theoretical model to understand the relationships among four constructs namely, motivation, tourism impacts, place attachment, and satisfaction. Based on a sample of 414 domestic tourists, PLS-SEM confirmed several relationships and inter-relationships among the four constructs. For example, motivation had a positive relationship with perceptions of positive and negative tourism impacts suggesting that the more tourists were motivated to visit the site for cultural/learning experiences, the more positive and negative tourism impacts they perceived. Implications for dark tourism and heritage site management are offered.

Keywords: dark tourism, motivation, place attachment, tourism impacts

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Authors: Mubashra Khalid, Saadia Amir

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This study initiated to explore the empirical relationship between psychological effects of economic recession on the educated youth in Pakistan. The diminishing economic resources during recession can create certain psychological consequences on the physical and cognitive aspects of the individuals. It may generate symptoms like aggression, depression, anxiety, frustration, stress and physical health related problems among the young generation. The sample of the study was consisted of 300 students belonging to six public sector universities of the Punjab province of Pakistan. Two hypotheses were advanced in this study regarding the relationship between recession and its effects on educated youth. The findings of the research represent that a significant relationship exists between decrease in employment opportunities and growing rate of aggression among educated youth and a significant association was found between economic instability and its influence on the learning abilities of the students during recession.

Keywords: psychological effects, recession, educated youth

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Authors: Ahmed Amin Mousa, Gehan Azam

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The current study presents an electronic test to measure teaching skills. This test is a part of the admission system of the Faculty of Education for Early Childhood, Cairo University. The test has been prepared to evaluate university students who apply for admission the Faculty. It measures some social and physiological skills which are important for successful teachers, such as emotional adjustment and problem solving; moreover, the extent of their love for children and their capability to interact with them. The test has been approved by 13 experts. Finally, it has been introduced to 1,100 students during the admission system of the academic year 2016/2017. The results showed that most of the applicants have an auditory learning style. In addition, 97% of them have the minimum requirement skills for teaching children.

Keywords: electronic test, performance, early childhood, skills, teacher student

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Authors: Kawinphat Lertpongmanee

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The purposes of this study were (1) investigate the English language learning motivation and the attainment of their English proficiency, (2) to find out how motivation and motivational variables of the high and low proficiency subjects are related to their English proficiency. The respondents were 80 fourth-year from Faculty of Management Sciences students in Rajabhat Suansunadha University. The instruments used for data collection were questionnaires. The statistically analyzed by using the SPSS program for frequency, percentage, arithmetic mean, standard deviation (SD), t-test, one-way analysis of variance (ANOVA), and Pearson correlation coefficient. The findings of this study are summarized as there was a significant difference in overall motivation between high and low proficiency groups of subjects at .05 (p < .05), but not in overall motivational variables. Additionally, the high proficiency group had a significantly higher level of intrinsic motivation than did the low proficiency group at .05 (p < .05).

Keywords: English language proficiency, faculty of management sciences, motivation factors, proficiency subjects

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: approach instance-based, area under the ROC curve, patient-specific decision path, clinical predictions

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Authors: Krzysztof Pomorski

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In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: D. S. Denchuk, O. M. Zamyatina, M. G. Minin, M. A. Soloviev, K. V. Bogrova

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The article considers invention activity in Russia and worldwide, its modern state, and the impact of innovative engineering activity on the national economy of the considered countries. It also analyses the historical premises of modern engineer-ing invention. The authors explore the development of engineering invention at an engineer-ing university, the creation of particular environment for scientific and technical creativity of students on the example of Elite engineering education program at Tomsk Polytechnic University, Russia. It is revealed that for the successful de-velopment of engineering invention in a higher education institution it is neces-sary to apply a learning model that develops the creative potential of a student, which is, in its turn, inseparably connected with the ability to generate new ideas in engineering. Such academic environment can become a basis for revealing stu-dents' creativity.

Keywords: engineering invention, scientific and technical creativity, students, project-based approach

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Authors: Jovanca Smith, Derek Gay

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All universities possess a standard by which students are assessed and administered into their programs. This paper considers the effect of the educational history of students, as measured by specific subject grades in Caribbean examinations, on overall performance in introductory engineering math and mechanics courses. Results reflect a correlation between the highest grade in the Caribbean examinations with a higher probability of successful advancement in the university courses. Alternatively, lower entrance grades are commensurate with underperformance in the university courses. Results also demonstrate that students matriculating with the Caribbean examinations will not necessarily possess a significant advantage over students entering through an alternative route, and while previous educational background of students is a significant indicator of tentative performance in the University level math and mechanics courses, it is not the sole factor.

Keywords: bimodal distribution, differential learning, engineering education, entrance qualification

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: Jayme R. T. Silva, Paulo G. P. Toro, Angelo Passaro, Giannino P. Camillo, Antonio C. Oliveira

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An in-house C++ code has been developed, at the Prof. Henry T. Nagamatsu Laboratory of Aerothermodynamics and Hypersonics from the Institute of Advanced Studies (Brazil), to estimate the aerothermodynamic properties around the Hypersonic Vehicle Integrated to the Scramjet. In the future, this code will be applied to the design of the Brazilian Scramjet Technological Demonstrator 14-X B. The first step towards accomplishing this objective, is to apply the in-house C++ code at the leading edge of a flat plate, simulating the leading edge of the 14-X Hypersonic Vehicle, making possible the wave phenomena of oblique shock and boundary layer to be analyzed. The development of modern hypersonic space vehicles requires knowledge regarding the characteristics of hypersonic flows in the vicinity of a leading edge of lifting surfaces. The strong interaction between a shock wave and a boundary layer, in a high supersonic Mach number 4 viscous flow, close to the leading edge of the plate, considering no slip condition, is numerically investigated. The small slip region is neglecting. The study consists of solving the fluid flow equations for unstructured meshes applying the SIMPLE algorithm for Finite Volume Method. Unstructured meshes are generated by the in-house software ‘Modeler’ that was developed at Virtual’s Engineering Laboratory from the Institute of Advanced Studies, initially developed for Finite Element problems and, in this work, adapted to the resolution of the Navier-Stokes equations based on the SIMPLE pressure-correction scheme for all-speed flows, Finite Volume Method based. The in-house C++ code is based on the two-dimensional Navier-Stokes equations considering non-steady flow, with nobody forces, no volumetric heating, and no mass diffusion. Air is considered as calorically perfect gas, with constant Prandtl number and Sutherland's law for the viscosity. Solutions of the flat plate problem for Mach number 4 include pressure, temperature, density and velocity profiles as well as 2-D contours. Also, the boundary layer thickness, boundary conditions, and mesh configurations are presented. The same problem has been solved by the academic license of the software Ansys Fluent and for another C++ in-house code, which solves the fluid flow equations in structured meshes, applying the MacCormack method for Finite Difference Method, and the results will be compared.

Keywords: boundary-layer, scramjet, simple algorithm, shock wave

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Authors: David Hough

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Indigenous peoples can generally be described as the original or first peoples of a land prior to colonization. While there is no single definition of indigenous peoples, the United Nations has developed a general understanding based on self-identification and historical continuity with pre-colonial societies. Indigenous peoples are often traditional holders of unique languages, knowledge systems and beliefs who possess valuable knowledge and practices which support sustainable management of natural resources. They often have social, economic, political systems, languages and cultures, which are distinct from dominant groups in the society or state where they live. They generally resist attempts by the dominant culture at assimilation and endeavour to maintain and reproduce their ancestral environments and systems as distinctive peoples and communities. In 2007, the United Nations General Assembly passed a declaration on the rights of indigenous peoples, known as UNDRIP. It (in addition to other international instruments such as ILO 169), sets out far-reaching guidelines, which – among other things – attempt to protect and promote indigenous languages and cultures. Paragraphs 13 and 14 of the declaration state the following regarding language, culture and education: Article 13, Paragraph 1: Indigenous peoples have the right to revitalize, use, develop and transmit for future generations their histories, languages, oral traditions, philosophies, writing systems, and literatures, and to designate and retain their own names for communities, places and persons. Article 14, Paragraph I: Indigenous peoples have the right to establish and control their educational systems and institutions providing education in their own languages, in a manner appropriate to their cultural methods of teaching and learning. These two paragraphs call for the right of self-determination in education. Paragraph 13 gives indigenous peoples the right to control the content of their teaching, while Paragraph 14 states that the teaching of this content should be based on methods of teaching and learning which are appropriate to indigenous peoples. This paper reviews an approach to furthering linguistic and cultural human rights for indigenous peoples in education, which supports UNDRIP. It has been employed in countries in Asia and the Pacific, including the Republic of the Marshall Islands, the Federated States of Micronesia, Far East Russia and Nepal. It is based on bottom-up community-based initiatives where students, teachers and local knowledge holders come together to produce classroom materials in their own languages that reflect their traditional beliefs and value systems. They may include such things as knowledge about herbal medicines and traditional healing practices, local history, numerical systems, weights and measures, astronomy and navigation, canoe building, weaving and mat making, life rituals, feasts, festivals, songs, poems, etc. Many of these materials can then be mainstreamed into math, science language arts and social studies classes.

Keywords: Indigenous peoples, linguistic and cultural human rights, materials development, teacher training, traditional knowledge

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Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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