Search results for: Cognitive learning

Authors: Ashiquer Rahman

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The cutting edge knowledge mediation system called ‘ePLANETe’ provides a framework for building knowledge, tools, and methods for education, research, and sustainable practices, as well as the deliberative assessment support for Higher Education, Research Institutions, and elsewhere e.g., the collaborative learning and research on sustainability and biodiversity issues of territorial development sectors. The paper is to present the analytical perspective of the ‘ePLANETe’ concept and functionalities as an experimental platform for contributing to sustainability assessment. Now the ‘ePLANETe’ can be seen as experimentation of the challenges of “ICT for Green”. The digital technologies of ‘ePLANETe’ are exploited (i) to facilitate collaborative research, learning tools, and knowledge for sustainability challenges, and (ii) as deliberation support tools in pursuing of sustainability performance and practices in territorial governance, public policy, and business strategy, as well as in the higher education sectors itself. The paper investigates the dealing capacity of qualitative and quantitative assessment of agriculture sustainability through the stakeholder-based integrated assessment. Specifically, this paper focuses on integrating system methodologies with Deliberation Support Tools (DST) and INTEGRAAL method for collective assessment and decision-making in implementing regional plans. The report aims to identify the effective knowledge and tools to enable deliberations methodologies regarding practices on the sustainability of agriculture and biodiversity issues, societal responsibilities, and regional planning, concentrating on the question: “How to effectively mobilize resources (knowledge, tools, and methods) from different sources and at different scales regarding on agriculture and biodiversity issues to address sustainability challenges” that will create the scope for qualitative and quantitative assessments of sustainability as a new landmark of the agriculture sector.

Keywords: Biodiversity, Deliberation Support Tools, INTEGRAAL, stakeholder.

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Authors: M. Guillard, M. Philippe, F. Laurent, J. Martinerie, J. P. Lachaux, G. Florence

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One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.

Keywords: Classification, EEG Synchrony, alpha, resting situation.

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Authors: D. Reich, R. Stark

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To provide reliable and valid findings when evaluating innovative in-car devices in the automotive context highly realistic driving environments are recommended. Nowadays, in-car devices are mostly evaluated due to driving simulator studies followed by real car driving experiments. Driving simulators are characterized by high internal validity, but weak regarding ecological validity. Real car driving experiments are ecologically valid, but difficult to standardize, more time-robbing and costly. One economizing suggestion is to implement more immersive driving environments when applying driving simulator studies. This paper presents research comparing non-immersive standard PC conditions with mobile and highly immersive Oculus Rift conditions while performing the Lane Change Task (LCT). Subjective data with twenty participants show advantages regarding presence and immersion experience when performing the LCT with the Oculus Rift, but affect adversely cognitive workload and simulator sickness, compared to non-immersive PC condition.

Keywords: LCT, immersion, oculus rift, presence, situation awareness.

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Authors: Mustafa Qaseem Hielat, Ahmad Mohammad Al-Shabatat

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Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared to public schools. This study investigated the environments of gifted students compared with other non-gifted, using a survey instrument that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total number of 109 were selected from excellence schools for academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and 32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%, “Seldom" support with 15.4%, “Often" support with 26.6%, “Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly, statistical differences were found between the two groups favoring non-gifted students in perception of their surrounding environments in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions of the survey, namely, family, peers, and resources. As the differences were found in teachers, school- support, and society, the nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful identification models. Thus, families, schools, and society should increase their cooperation, communication, and awareness of the gifted supportive environments. However, more studies to investigate other aspects of promoting academic giftedness and excellence are recommended.

Keywords: Academic giftedness, Supportive environment, Excellence schools, Gifted grouping, Gifted nurturing.

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Authors: Sotiria Tzivinikou, Dimitra Kagkara

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Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: Inclusive education, pre-service, self-efficacy, training program.

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Authors: David G. Maxínez, Francisco Javier Sánchez Rangel, Guillermo Castillo Tapia, Petra Baldovinos Noyola, M. Antonieta García Galván, Moisés G Sierra

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Describes the current situation of educational Robotics "the State of the art" its concept, its evolution their niches of opportunity, academic and business and the importance of education and academic outreach. It shows that the development of high-tech automated educational materials influence the teaching-learning process and that communication between machines and humans is a reality.

Keywords: Education, robotics, robots, technology, innovation, educational constructivism

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Authors: Mohammad Hassanzadeh

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As far as incidental vocabulary learning is concerned, the basic contention of the Involvement Load Hypothesis (ILH) is that retention of unfamiliar words is, generally, conditional upon the degree of involvement in processing them. This study examined input modality and incidental vocabulary uptake in a task-induced setting whereby three variously loaded task types (marginal glosses, fill-in-task, and sentence-writing) were alternately assigned to one group of students at Allameh Tabataba’i University (n=2l) during six classroom sessions. While one round of exposure was comprised of the audiovisual medium (TV talk shows), the second round consisted of textual materials with approximately similar subject matter (reading texts). In both conditions, however, the tasks were equivalent to one another. Taken together, the study pursued the dual objectives of establishing a litmus test for the ILH and its proposed values of ‘need’, ‘search’ and ‘evaluation’ in the first place. Secondly, it sought to bring to light the superiority issue of exposure to audiovisual input versus the written input as far as the incorporation of tasks is concerned. At the end of each treatment session, a vocabulary active recall test was administered to measure their incidental gains. Running a one-way analysis of variance revealed that the audiovisual intervention yielded higher gains than the written version even when differing tasks were included. Meanwhile, task 'three' (sentence-writing) turned out the most efficient in tapping learners' active recall of the target vocabulary items. In addition to shedding light on the superiority of audiovisual input over the written input when circumstances are relatively held constant, this study for the most part, did support the underlying tenets of ILH.

Keywords: Evaluation, incidental vocabulary learning, input mode, involvement load hypothesis, need, search.

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Authors: Hsiu-Hua Cheng

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This study analyzed the creativity of student teams participating in an exploratory information system development project (ISDP) and examined antecedents of their creativity. By using partial least squares (PLS) to analyze a sample of thirty-six teams enrolled in an information system department project training course that required three semesters of project-based lessons, the results found social capitals (structural, relational and cognitive social capital) positively influence knowledge integration. However, relational social capital does not significantly influence knowledge integration. Knowledge integration positively affects team creativity. This study also demonstrated that social capitals significantly influence team creativity through knowledge integration. The implications of our findings for future research are discussed.

Keywords: Information system development project (ISDP), Social capital, Knowledge integration, Team creativity.

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Authors: Sitalakshmi Venkataraman

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Recent scientific investigations indicate that multimodal biometrics overcome the technical limitations of unimodal biometrics, making them ideally suited for everyday life applications that require a reliable authentication system. However, for a successful adoption of multimodal biometrics, such systems would require large heterogeneous datasets with complex multimodal fusion and privacy schemes spanning various distributed environments. From experimental investigations of current multimodal systems, this paper reports the various issues related to speed, error-recovery and privacy that impede the diffusion of such systems in real-life. This calls for a robust mechanism that caters to the desired real-time performance, robust fusion schemes, interoperability and adaptable privacy policies. The main objective of this paper is to present a framework that addresses the abovementioned issues by leveraging on the heterogeneous resource sharing capacities of Grid services and the efficient machine learning capabilities of artificial neural networks (ANN). Hence, this paper proposes a Grid-based neural network framework for adopting multimodal biometrics with the view of overcoming the barriers of performance, privacy and risk issues that are associated with shared heterogeneous multimodal data centres. The framework combines the concept of Grid services for reliable brokering and privacy policy management of shared biometric resources along with a momentum back propagation ANN (MBPANN) model of machine learning for efficient multimodal fusion and authentication schemes. Real-life applications would be able to adopt the proposed framework to cater to the varying business requirements and user privacies for a successful diffusion of multimodal biometrics in various day-to-day transactions.

Keywords: Back Propagation, Grid Services, MultimodalBiometrics, Neural Networks.

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets, especially in the motorist sector, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of Python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. 60 vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes that the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: Convolutional Neural Network, CNN, location identification, tracking, GPS, GSM.

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Authors: Ayse Okvuran

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Creative drama which interconnects with the concepts of play, theatre, animation and role playing is a field which can only be learnt and expressed through experiencing. This study about assessment of the drama teaching in preschools by children was conducted in 3 preschools in Ankara with participation of 12 children of 6 ages who had taken drama learning courses. Qualitative research approach and semi-structured interviewing technique were employed. The results of the study indicated that all of 12 children defined drama as a game and entertainment.

Keywords: Creative drama, preschoolers, drama courses

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Authors: Mariam Abdulaziz Y.Esmaeel

Abstract:

The study aimed to identify the nature of autistic talent, the manifestations of their weak central coherence, and their sensory characteristics. The case study consisted of four talented autistic males. Two of them in drawing, one in clay formation and one in jigsaw puzzle. Tools of data collection were Group Embedded Figures Test, Block Design Test, Sensory Profile Checklist Revised, Interview forms and direct observation. Results indicated that talent among autistics emerges in limited domain and being extraordinary for each case. Also overlapping construction properties. Indeed, they show three perceptual aspects of weak central coherence: The weak in visual spatial-constructional coherence, the weak in perceptual coherence and the weak in verbal – semantic coherence. Moreover, the majority of the study cases used the three strategies of weak central coherence (segmentation, obliqueness and rotation). As for the sensory characteristics, all study cases have numbers of that characteristics that especially emerges in the visual system.

Keywords: Autism, Central Coherence, Savant, Sensory characteristics, Talent.

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Authors: Eugene Allevato

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Developing a responsible personal worldview is central to sustainable development, but achieving quality education to promote transformative learning for sustainability is thus far, poorly understood. Most programs involving education for sustainable development rely on changing behavior, rather than attitudes. The emphasis is on the scientific and utilitarian aspect of sustainability with negligible importance on the intrinsic value of nature. Campus sustainability projects include building sustainable gardens and implementing energy-efficient upgrades, instead of focusing on educating for sustainable development through exploration of students’ values and beliefs. Even though green technology adoption maybe the right thing to do, most schools are not targeting the root cause of the environmental crisis; they are just providing palliative measures. This study explores the under-examined factors that lead to pro-environmental behavior by investigating the environmental perceptions of both college business students and personnel of green organizations. A mixed research approach of qualitative, based on structured interviews, and quantitative instruments was developed including 30 college-level students’ interviews and 40 green organization staff members involved in sustainable activities. The interviews were tape-recorded and transcribed for analysis. Categorization of the responses to the open‐ended questions was conducted with the purpose of identifying the main types of factors influencing attitudes and correlating with behaviors. Overall the findings of this study indicated a lack of appreciation for nature, and inability to understand interconnectedness and apply critical thinking. The results of the survey conducted on undergraduate students indicated that the responses of business and liberal arts students by independent t-test were significantly different, with a p‐value of 0.03. While liberal arts students showed an understanding of human interdependence with nature and its delicate balance, business students seemed to believe that humans were meant to rule over the rest of nature. This result was quite intriguing from the perspective that business students will be defining markets, influencing society, controlling and managing businesses that supposedly, in the face of climate change, shall implement sustainable activities. These alarming results led to the focus on green businesses in order to better understand their motivation to engage in sustainable activities. Additionally, a probit model revealed that childhood exposure to nature has a significantly positive impact in pro-environmental attitudes to most of the New Ecological Paradigm scales. Based on these findings, this paper discusses educators including Socrates, John Dewey and Paulo Freire in the implementation of eco-pedagogy and transformative learning following a curriculum with emphasis on critical and systems thinking, which are deemed to be key ingredients in quality education for sustainable development.

Keywords: Eco-pedagogy, environmental behavior, quality education for sustainable development, transformative learning.

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Authors: Rinaldo Christian Tanumara, Ming Xie

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Color categorization is shared among members in a society. This allows communication of color, especially when using natural language such as English. Hence sociable robot, to live coexist with human in human society, must also have the shared color categorization. To achieve this, many works have been done relying on modeling of human color perception and mathematical complexities. In contrast, in this work, the computer as brain of the robot learns color categorization through interaction with humans without much mathematical complexities.

Keywords: Color categorization, color learning, machinelearning.

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Authors: Ioannis Pratikakis, Anna Karahaliou, Katerina Vassiou, Vassilis Virvilis, Dimitrios Kosmopoulos, Stavros Perantonis

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In this paper, a Web-based e-Training platform that is dedicated to multimodal breast imaging is presented. The assets of this platform are summarised in (i) the efficient representation of the curriculum flow that will permit efficient training; (ii) efficient tagging of multimodal content appropriate for the completion of realistic cases and (iii) ubiquitous accessibility and platform independence via a web-based approach.

Keywords: Breast imaging, e-Training, web-based learning.

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Authors: B. Thanasansomboon, S. Choemprayong, N. Parinyanitikul, U. Tanlamai

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Being diagnosed with metastatic breast cancer, the patients as well as their caretakers are affected physically and mentally. Although the medical systems in Thailand have been attempting to improve the quality and effectiveness of the treatment of the disease in terms of physical illness, the success of the treatment also depends on the quality of mental health. Metastatic breast cancer patients have found that social support is a key factor that helps them through this difficult time. It is recognized that social support in different dimensions, including emotional support, social network support, informational support, instrumental support and appraisal support, are contributing factors that positively affect the quality of life of patients in general, and it is undeniable that social support in various forms is important in promoting the quality of life of metastatic breast patients. However, previous studies have not been dedicated to investigating their quality of life concerning affective, cognitive, and behavioral outcomes. Therefore, this study aims to develop integrated social support through social networks to improve the quality of life of metastatic breast cancer patients in Thailand.

Keywords: Social support, metastatic breast cancer, quality of life, social network.

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Authors: A. Karaali

Abstract:

This paper will seek to clarify important key terms such as home schooling and home education as well as the legalities attached to such terms. It will reflect on the recent proposed changes to terminology in NSW, Australia. The various pedagogical approaches to home education will be explored including their prominence in the Australian context. There is a strong focus on literature from Australia. The historical background of home education in Australia will be explained as well as the difference between distance education and home education. The future of home education in Australia will be discussed.

Keywords: Alternative education, e-learning, home education, home schooling, online resources, technology.

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Authors: T. Dubayova

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Slovak, as well as foreign authors, believe that the influence of non-cognitive factors on a student's academic success or failure is unquestionable. The aim of this paper is to establish a link between the mental vulnerability and coping strategies used by 4^th grade elementary school students in dealing with stressful situations and their academic performance, which was used as a simple quantitative indicator of academic success. The research sample consists of 320 students representing the standard population and 60 students with special education needs (SEN), who were assessed by the Strengths and Difficulties Questionnaire (SDQ) by their teachers and the Children’s Coping Strategies Checklist (CCSC-R1) filled in by themselves. Students with SEN recorded an extraordinarily high frequency of mental vulnerability (34.5 %) than students representing the standard population (7 %). The poorest academic performance of students with SEN was associated with the avoidance behavior displayed during stressful situations. Students of the standard population did not demonstrate this association. Students with SEN are more likely to display mental health problems than students of the standard population. This may be caused by the accumulation of and frequent exposure to situations that they perceive as stressful.

Keywords: Coping, mental vulnerability, students with special education needs, academic performance, academic success.

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Authors: Yasar Guneri Sahin, Mehmet Cudi Okur

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In this presentation, we discuss the use of information technologies in the area of special education for teaching individuals with learning disabilities. Application software which was developed for this purpose is used to demonstrate the applicability of a database integrated information processing system to alleviate the burden of educators. The software allows the preparation of individualized education programs based on the predefined objectives, goals and behaviors.

Keywords: Special education, disabled individual, informationtechnology, individual education programs.

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: Subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing.

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Authors: Mousavian, M. Moghimi Mofrad, M. H. Vakili, D. Ashouri, R. Alizadeh

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The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.

Keywords: Neural Network, Net Heating Value, Crude Oil, Experimental, Modeling.

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Authors: Scott Dyer, Nicoletta Adamo-Villani

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In this paper we report a study aimed at determining the effects of animation on usability and appeal of educational software user interfaces. Specifically, the study compares 3 interfaces developed for the Mathsigner™ program: a static interface, an interface with highlighting/sound feedback, and an interface that incorporates five Disney animation principles. The main objectives of the comparative study were to: (1) determine which interface is the most effective for the target users of Mathsigner™ (e.g., children ages 5-11), and (2) identify any Gender and Age differences in using the three interfaces. To accomplish these goals we have designed an experiment consisting of a cognitive walkthrough and a survey with rating questions. Sixteen children ages 7-11 participated in the study, ten males and six females. Results showed no significant interface effect on user task performance (e.g., task completion time and number of errors); however, interface differences were seen in rating of appeal, with the animated interface rated more 'likeable' than the other two. Task performance and rating of appeal were not affected significantly by Gender or Age of the subjects.

Keywords: Animation, Animated interfaces, EducationalSoftware, Human Computer Interaction, Multimedia.

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Authors: Itgel Bayarsaikhan, Jimin Lee, Sejong Oh

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Classification is one of the primary themes in computational biology. The accuracy of classification strongly depends on quality of a dataset, and we need some method to evaluate this quality. In this paper, we propose a new graphical analysis method using 'Membership-Deviation Graph (MDG)' for analyzing quality of a dataset. MDG represents degree of membership and deviations for instances of a class in the dataset. The result of MDG analysis is used for understanding specific feature and for selecting best feature for classification.

Keywords: feature, classification, machine learning algorithm.

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Authors: Mikael Soini, Kari Björn

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Metropolia University of Applied Sciences (MUAS) Information and Communication Technology (ICT) Degree Programme provides full-time Bachelor-level undergraduate studies. ICT Degree Programme has seven different major options; this paper focuses on Health Technology. In Health Technology, a significant curriculum change in 2014 enabled transition from fragmented curriculum including dozens of courses to a new integrated curriculum built around three 30 ECTS themes. This paper focuses especially on the second theme called Customer Oriented Software Applications. From students’ point of view, the goal of this theme is to get familiar with existing health related ICT solutions and systems, understand business around health technology, recognize social and healthcare operating principles and services, and identify customers and users and their special needs and perspectives. This also acts as a background for health related web application development. Built web application is tested, developed and evaluated with real users utilizing versatile user centred development methods. This paper presents experiences obtained from the first implementation of Customer Oriented Software Applications theme. Student feedback was gathered with two questionnaires, one in the middle of the theme and other at the end of the theme. Questionnaires had qualitative and quantitative parts. Similar questionnaire was implemented in the first theme; this paper evaluates how the theme-based integrated curriculum has progressed in Health Technology major by comparing results between theme 1 and 2. In general, students were satisfied for the implementation, timing and synchronization of the courses, and the amount of work. However there is still room for development. Student feedback and teachers’ observations have been and will be used to develop the content and operating principles of the themes and whole curriculum.

Keywords: Engineering education, integrated and theme-based curriculum, learning experience, student centred learning.

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Authors: Monjed Ezzeddinne, Nicolas Lefebvre, Régis Lengellé

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This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.

Keywords: Identification, Learning systems, Mixture ofExperts, Support Vector Machines.

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Authors: Mohamed Aymen Slim, Afef Abdelkrim, Mohamed Benrejeb

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The handwriting is a physical demonstration of a complex cognitive process learnt by man since his childhood. People with disabilities or suffering from various neurological diseases are facing so many difficulties resulting from problems located at the muscle stimuli (EMG) or signals from the brain (EEG) and which arise at the stage of writing. The handwriting velocity of the same writer or different writers varies according to different criteria: age, attitude, mood, writing surface, etc. Therefore, it is interesting to reconstruct an experimental basis records taking, as primary reference, the writing speed for different writers which would allow studying the global system during handwriting process. This paper deals with a new approach of the handwriting system modeling based on the velocity criterion through the concepts of artificial neural networks, precisely the Radial Basis Functions (RBF) neural networks. The obtained simulation results show a satisfactory agreement between responses of the developed neural model and the experimental data for various letters and forms then the efficiency of the proposed approaches.

Keywords: ElectroMyoGraphic (EMG) signals, Experimental approach, Handwriting process, Radial Basis Functions (RBF) neural networks, Velocity Modeling.

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Authors: Lee Bih Ni, Nurul Asyikin Binti Hassan

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This paper discusses the use of mnemonic and mathematical methods in enhancing the understanding of history. Mnemonics can help students from all levels including high school and in various disciplines including language, math and history. At the secondary level, students are exposed to various courses that require them to remember many facts that can be mastered through the application of mnemonic techniques. Researchers use narrative literature studies to illustrate the current state of art and science in the field of research focused. Researchers used narrative literature reviews to build a scientific base of knowledge. Researchers gather all the key points in the discussion, and put it here by referring to the specific field where the paper is essentially based. The findings suggest that the use of mnemonic techniques can improve the individual's memory by adding little effort. In implementing mnemonic techniques, it is important to integrate mathematics and history in the course as both are interconnected as mathematics has shaped our history and vice versa. This study shows that memory skills can actually be improved; the human mind can remember something more than expected.

Keywords: Cognitive strategy, mnemonic technique, secondary school level study, mathematical mnemonic.

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

Abstract:

Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.

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Authors: Roland Lang, Dietmar Bruckner, Rosemarie Velik, Tobias Deutsch

Abstract:

Modern building automation needs to deal with very different types of demands, depending on the use of a building and the persons acting in it. To meet the requirements of situation awareness in modern building automation, scenario recognition becomes more and more important in order to detect sequences of events and to react to them properly. We present two concepts of scenario recognition and their implementation, one based on predefined templates and the other applying an unsupervised learning algorithm using statistical methods. Implemented applications will be described and their advantages and disadvantages will be outlined.

Keywords: Building automation, ubiquitous computing, scenariorecognition, surveillance system.

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Authors: Antonio Espingardeiro

Abstract:

It is likely that robots will cross the boundaries of industry into households over the next decades. With demographic challenges worldwide, the future ageing populations will require the introduction of assistive technologies capable of providing, care, human dignity and quality of life through the aging process. Robotics technology has a high potential for being used in the areas of social and healthcare by promoting a wide range of activities such as entertainment, companionship, supervision or cognitive and physical assistance. However such close Human Robotics Interaction (HRI) encompass a rich set of ethical scenarios that need to be addressed before Socially Assistive Robots (SARs) reach the global markets. Such interactions with robots may seem a worthy goal for many technical/financial reasons but inevitably require close attention to the ethical dimensions of such interactions. This article investigates the current HRI benchmark of social success. It revises it according to the ethical principles of beneficence, non-maleficence and justice aligned with social care ethos. An extension of such benchmark is proposed based on an empirical study of HRIs conducted with elderly groups.

Keywords: HRI, SARs, Social Success, Benchmark, Elderly care.

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