Search results for: interpreting deep learning

Authors: Danute Karcauskiene, Dalia Ambrazaitiene, Regina Skuodiene, Monika Vilkiene, Regina Repsiene, Ieva Jokubauskaite

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The main ambition for nowadays agriculture is to get the economically effective yield and to secure the soil ecological sustainability. According to the effect on the main soil quality indexes, tillage systems may be separated into two types, conventional and conservation tillage. The goal of this study was to determine the impact of conservation and conventional primary soil tillage methods and soil fertility improvement measures on soil properties and crop productivity. Methods: The soil of the experimental site is Dystric Glossic Retisol (WRB 2014) with texture of sandy loam. The trial was established in 2003 in the experimental field of crop rotation of Vėžaičiai Branch of Lithuanian Research Centre for Agriculture and Forestry. Trial factors and treatments: factor A- primary soil tillage in (autumn): deep ploughing (20-25cm), shallow ploughing (10-12cm), shallow ploughless tillage (8-10cm); factor B – soil fertility improvement measures: plant residues, plant residues + straw, green manure 1st cut + straw, farmyard manure 40tha-1 + straw. The four - course crop rotation consisted of red clover, winter wheat, spring rape and spring barley with undersown. Results: The tillage had no statistically significant effect on topsoil (0-10 cm) pHKCl level, it was 5.5 - 5.7. During all experiment period, the highest soil pHKCl level (5.65) was in the shallow ploughless tillage. The organic fertilizers particularly the biomass of grass and farmyard manure had tendency to increase the soil pHKCl. The content of plant - available phosphorus and potassium significantly increase in the shallow ploughing compared with others tillage systems. The farmyard manure increases those elements in whole arable layer. The dissolved organic carbon concentration was significantly higher in the 0 - 10 cm soil layer in the shallow ploughless tillage compared with deep ploughing. After the incorporation of clover biomass and farmyard manure the concentration of dissolved organic carbon increased in the top soil layer. During all experiment period the largest amount of water stable aggregates was determined in the soil where the shallow ploughless tillage was applied. It was by 12% higher compared with deep ploughing. During all experiment time, the soil moisture was higher in the shallow ploughing and shallow ploughless tillage (9-27%) compared to deep ploughing. The lowest emission of CO2 was determined in the deep ploughing soil. The highest rate of CO2 emission was in shallow ploughless tillage. The addition of organic fertilisers had a tendency to increase the CO2 emission, but there was no statistically significant effect between the different types of organic fertilisers. The crop yield was larger in the deep ploughing soil compared to the shallow and shallow ploughless tillage.

Keywords: reduced tillage, soil structure, soil pH, biological activity, crop productivity

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Authors: Gunniga Anugkakul, Suwaree Yordchim

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The objectives were to study language learning strategies (LLSs) employed by Chinese students, and the frequency of LLSs they used, and examine the relationship between the use of LLSs and gender. The Strategy Inventory for Language Learning (SILL) by Oxford was administered to thirty-six Chinese students at Suan Sunandha Rajabhat University in Thailand. The data obtained was analyzed using descriptive statistics and chi-square tests. Three useful findings were found on the use of LLSs reported by Chinese students. First, Chinese students used overall LLSs at a high level. Second, among the six strategy groups, Chinese students employed compensation strategy most frequently and memory strategy least frequently. Third, the research results also revealed that gender had significant effect on Chinese Student’s use of overall LLSs.

Keywords: English language, language learning strategy, Chinese students, compensation strategy

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Authors: Nigar Hussain

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It is a subset of big data. Dark data means those data in which we fail to use for future decisions. There are many issues in existing work, but some need powerful tools for utilizing dark data. It needs sufficient techniques to deal with dark data. That enables users to exploit their excellence, adaptability, speed, less time utilization, execution, and accessibility. Another issue is the way to utilize dark data to extract helpful information to settle on better choices. In this paper, we proposed upgrade strategies to remove the dark side from dark data. Using a supervised model and machine learning techniques, we utilized dark data and achieved an F1 score of 89.48%.

Keywords: big data, dark data, machine learning, heatmap, random forest

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Authors: Didiosky Benítez-Erice, Frederik Questier, Dalgys Pérez-Luján

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This paper aims to present two models around the production of students’ experiential knowledge in the teaching-learning process of higher education: the teacher-centered production model and the student-centered production model. From a range of knowledge management and experiential learning theories, the paper elaborates into the nature of students’ experiential knowledge and proposes further adjustments of existing second-generation knowledge management theories taking into account the particularities of higher education. Despite its theoretical nature the paper can be relevant for future studies that stress student-driven improvement and innovation at higher education institutions.

Keywords: experiential knowledge, higher education, knowledge management, teaching-learning process

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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Authors: Amal A. Abdel-Sattar

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The curriculum of architecture department in Prince Sultan University includes ‘Building Surveying’ course which is usually a part of civil engineering courses. As a fundamental requirement of the course, it requires a strong background in mathematics and physics, which are not usually preferred subjects to the architecture students and many of them are not giving the required and necessary attention to these courses during their preparation year before commencing their architectural study. This paper introduces the concept and the methodology of the student-centered learning approach in the course of building surveying for architects. One of the major outcomes is the improvement in the students’ involvement in the course and how this will cover and strength their analytical weak points and improve their mathematical skills. The study is conducted through three semesters with a total number of 99 students. The effectiveness of the student-centered learning approach is studied using the student survey at the end of each semester and teacher observations. This survey showed great acceptance of the students for these methods. Also, the teachers observed a great improvement in the students’ mathematical abilities and how keener they became in attending the classes which were clearly reflected on the low absence record.

Keywords: architecture, building surveying, student-centered learning, teaching and learning

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Authors: Kanlaya Ratanasuphakarn, Suttipong Boonphadung

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The research on the development of ability in reading comprehension based on metacognitive strategies aimed to (1) improve the students’development of ability in reading comprehension based on metacognitive strategies, (2) evaluate the students’ satisfaction on using metacognitive strategies in learning as a tool developing the ability in reading comprehension. Forty-eight of Mattayom 3 students who have enrolled in the subject of research for learning development of semester 2 in 2013 were purposively selected as the research cohort. The research tools were lesson plans for reading comprehension, pre-posttest and satisfaction questionnaire that were approved as content validity and reliability (IOC=.66-1.00,0.967). The research found that the development of ability in reading comprehension of the research samples before using metacognitive strategies in learning activities was in the normal high level. Additionally, the research discovered that the students’ satisfaction of the research cohort after applying model in learning activities appeared to be high level of satisfaction on using metacognitive strategies in learning as a tool for the development of ability in reading comprehension.

Keywords: development of ability, metacognitive strategies, satisfaction, reading comprehension

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Authors: C. W. Kan

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This study examines the results of optical whitening process of different textiles such as cotton, wool and polyester. The optical whitening agents used are commercially available products, and the optical whitening agents were applied to the textiles with manufacturers’ suggested methods. The aim of this study is to illustrate the proper application methods of optical whitening agent to different textiles and hence to provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, optical whitening agent, wool, cotton, polyester

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Authors: R. Abdulrahman, A. Eardley, A. Soliman

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The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: mobile learning, nursing institute students’ acceptance of m-learning activity in Saudi Arabia, unified theory of acceptance and use of technology model (UTAUT), structural equation modelling (SEM)

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Authors: Naser Alajmi, Ali Alobaidly, Mubarak Alhajri, Salem Salamah, Muhammad Alsubaie

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Iterative Learning Control (ILC) known to be a controlling tool to overcome periodic disturbances for repetitive systems. This technique is required to let the error signal tends to zero as the number of operation increases. The learning process that lies within this context is strongly dependent on the initial input which if selected properly tends to let the learning process be more effective compared to the case where a system starts from blind. ILC uses previous recorded execution data to update the following execution/trial input such that a reference trajectory is followed to a high accuracy. Error convergence in ILC is generally highly dependent on the input applied to a plant for trial $1$, thus a good choice of initial starting input signal would make learning faster and as a consequence the error tends to zero faster as well. In the work presented within, an upper limit based on the Singular Values Principle (SV) is derived for the initial input signal applied at trial $1$ such that the system follow the reference in less number of trials without responding aggressively or exceeding the working envelope where a system is required to move within in a robot arm, for example. Simulation results presented illustrate the theory introduced within this paper.

Keywords: initial input, iterative learning control, maximum input, singular values

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Authors: Payal Maheshwari, Maheaswari Brindavan

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The present study aimed at studying the level of perceived self-efficacy of children with learning disability and their mother’s perception about the efficacy of the child and the relationship between the two. The study further aimed at finding out the relationship between the level of perceived self-efficacy of children with learning disability and their academic achievement and their mother’s perception about the Efficacy of the child and child’s Academic Achievement. The sample comprised of 80 respondents (40 children with learning disability and their mothers). Children with learning disability as their primary condition, belonging to middle or upper middle class, living with both the parents, residing in Mumbai and their mothers were selected. Purposive or judgmental and snowball sampling technique was used to select the sample for the present study. Proformas in the form of questionnaires were used to obtain the background information of the children with learning disability and their mother’s. A self-constructed Mother’s Perceived Efficacy of their Child Assessment Scale was used to measure mothers perceived level of efficacy of their child with learning disability. Self-constructed Child’s Perceived Self-Efficacy Assessment Scale was used to measure the level of child’s perceived self-efficacy. Academic scores of the child were collected from the child’s parents or teachers and were converted into percentage. The data were analyzed quantitatively using frequencies, mean and standard deviation. Correlations were computed to ascertain the relationships between the different variables. The findings revealed that majority of the mother’s perceived efficacy about their child with learning disability was above average as well as majority of the children with learning disability also perceived themselves as having above average level of self-efficacy. Further in the domains of self-regulated learning and emotional self-efficacy majority of the mothers perceived their child as having average or below average efficacy, 50% of the children also perceived their self-efficacy in the two domains at average or below average level. A significant (r=.322, p < .05) weak correlation (Spearman’s rho) was found between mother’s perceived efficacy about their child, and child’s perceived self-efficacy and a significant (r=.377, p < .01) weak correlation (Pearson Correlation) was also found between mother’s perceived efficacy about their child and child’s academic achievement. Significant weak positive correlation was found between child’s perceived self-efficacy and academic achievement (r=.332, p < .05). Based on the findings, the study discussed the need for intervention program for children in non-academic skills like self-regulation and emotional competence.

Keywords: learning disability, perceived self efficacy, academic achievement, mothers, children

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Authors: Khan Zeenat, S. B. Dandegaonkar

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Dyslexia is a neurological disorder which affects the reading and writing ability of children. A sample of 72 dyslexic children (36 from English medium and 36 from Marathi medium schools) of class V from English and Marathi medium schools were selected. The Experimental method was used to study the effect of Remedial Teaching Programme on the Learning outcome of Dyslexic students. The findings showed that there is a Positive effect of remedial teaching programme on the Learning outcome of English and Marathi medium students.

Keywords: remedial teaching, Dyslexic students, learning outcome, neurological

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Authors: Asra Yousuf, Ajaykumar Tannirkulum

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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.

Keywords: development, migration, internal migration, machine learning, prediction

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Authors: Prakash Kumar Nayak, Avinash Kumar, Uma Dash, Kalpana Rayaguru

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Soybean oil is one of the most widely consumed cooking oils, worldwide. Deep-fat frying of foods at higher temperatures adds unique flavour, golden brown colour and crispy texture to foods. But it brings in various changes like hydrolysis, oxidation, hydrogenation and thermal alteration to oil. The presence of Peroxide value (PV) is one of the most important factors affecting the quality of the deep-fat fried oil. Using bentonite as an adsorbent, the PV can be reduced, thereby improving the quality of the soybean oil. In this study, operating parameters like heating time of oil (10, 15, 20, 25 & 30 h), contact time ( 5, 10, 15, 20, 25 h) and concentration of adsorbent (0.25, 0.5, 0.75, 1.0 and 1.25 g/ 100 ml of oil) have been optimized by response surface methodology (RSM) considering percentage reduction of PV as a response. Adsorption data were analysed by fitting with Langmuir and Freundlich isotherm model. The results show that the Langmuir model shows the best fit compared to the Freundlich model. The adsorption process was also found to follow a pseudo-second-order kinetic model.

Keywords: bentonite, Langmuir isotherm, peroxide value, RSM, soybean oil

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Authors: G. S. Androulakis, G. Deli, M. Kaisari, N. Mihos

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Teaching practices at the university level have changed and developed during the last decade. Implementation of inverted classroom method in secondary education consists of a well-formed basis for academic teachers. On the other hand, distance learning is a well-known field in education research and widespread as a method of teaching. Nonetheless, the new pandemic found many Universities all over the world unprepared, which made adaptations to new methods of teaching a necessity. In this paper, we analyze a model of an inverted university classroom in a distance learning context. Thus, the main purpose of our research is to investigate students’ difficulties as they transit to a new style of teaching and explore their learning development during a semester totally different from others. Our teaching experiment took place at the Business Administration department of the University of Patras, in the context of two courses: Calculus, a course aimed at first-year students, and Statistics, a course aimed at second-year students. Second-year students had the opportunity to attend courses in the university classroom. First-year students started their semester with distance learning. Using a comparative study of these two groups, we explored significant differences in students’ learning procedures. Focused group interviews, written tests, analyses of students’ dialogues were used in a mixed quantity and quality research. Our analysis reveals students’ skills, capabilities but also a difficulty in following, non-traditional style of teaching. The inverted classroom model, according to our findings, offers benefits in the educational procedure, even in a distance learning environment.

Keywords: distance learning, higher education, inverted classroom, mathematics teaching

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Authors: Olukemi E. Adetuyi-Olu-Francis

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Learning is natural for living. One stops learning when life ends. Hence, there is no negotiating life-long learning. An individual has the innate ability to learn as many languages as he/she desires as long as life exists. French language education to every Nigerian teacher-trainee is a necessity. Nigeria’s geographical location requires that the French language should be upheld for economic and cultural co-operations between Nigeria and the francophone countries sharing borders with her. The French language will enhance the leadership roles of the teacher-trainees and their ability to function across borders. The 21st century learning tools are basically digital, and many apps are complementing the actual classroom interactions. This study examined the communicative competence in the French language to equip Nigerian teacher-trainees in the new-normal society using mobile apps as a lifelong learning tool. Three research questions and hypotheses guided the study, and the researcher adopted a pre-test, a post-test experimental design, using a sample size of 87 teacher-trainees in South-south geopolitical zone of Nigeria. Results showed that the use of mobile apps is effective for learning the French language. One of the recommendations is that the use of mobile apps should be encouraged for all Nigerian youths to learn the French language for enhancing leadership roles in the world of work and for international interactions for socio-economic co-operations with Nigerian neighboring countries.

Keywords: communicative competence, french language, life long learning, mobile apps, new normal society, teacher trainees

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Authors: Agah Tugrul Korucu

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Significant changes have taken place for the better in the bulk of information and in the use of technology available in the field of education induced by technological changes in the 21st century. It is mainly the job of the teachers and pre-service teachers to integrate information and communication technologies into education by means of conveying the use of technology to individuals. While the pre-service teachers are conducting lessons by using technology, the methods they have developed are important factors for the requirements of the lesson and for the satisfaction levels of the students. The study of this study is to examine the satisfaction levels of pre-service teachers as regards e-learning in a technological environment in which there are lesson activities conducted through an online learning environment in terms of various variables. The study group of the research is composed of 156 pre-service teachers that were students in the departments of Computer and Teaching Technologies, Art Teaching and Pre-school Teaching in the academic year of 2014 - 2015. The qualitative research method was adopted for this study; the scanning model was employed in collecting the data. “The Satisfaction Scale regarding the E-learning Process”, developed by Gülbahar, and the personal information form, which was developed by the researcher, were used as means of collecting the data. Cronbach α reliability coefficient, which is the internal consistency coefficient of the scale, is 0.91. SPSS computerized statistical package program and the techniques of medium, standard deviation, percentage, correlation, t-test and variance analysis were used in the analysis of the data.

Keywords: online learning environment, integration of information technologies, e-learning, e-learning satisfaction, pre-service teachers

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Authors: Manthekeleng Linake, Fesi Liziwe

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The ongoing argument over the use of English as a learning and teaching language in schools was examined in this study. The nature of the language proficiency gap is particularly relevant in light of the present emphasis on learning and educational quality in contemporary debates, as well as the education sustainable development goal. As a result, an interpretivist paradigm, a qualitative technique, and a case study-based research design were used in the work. Two school principals, two teachers, two members of the School Governing Body (SGB), and four learners were chosen using purposive sampling from two schools in the Amathole West Education District. The researchers were able to acquire in-depth information on the disputes surrounding the use of English as a language of learning and teaching by using semi-structured interview questions and focus groups. Despite knowing that they do not have the potential to do well in English, teachers found that despite appreciating the value of mother tongue and cultural identity, they prefer to use English as the language of teaching in schools. The findings, on the other hand, revealed that proponents of mother-language-based education argue that learning one's mother tongue is a human right.

Keywords: English first additional language learners, social justice, human capabilities, language proficiency

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Authors: Asha Dukkipati

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Cognitive neuroscience explores neural functioning and aberrant brain activity during cognitive and perceptual tasks. Neurocinematics is a subfield of cognitive neuroscience that observes neural responses of individuals watching a film to see similarities and differences between individuals. This method is typically used for commercial use, allowing directors and filmmakers to produce better visuals and increasing their results in the box office. However, neurocinematics is increasingly becoming a common tool for neuroscientists interested in studying similar patterns of brain activity across viewers outside of the film industry. In this review, it argue that neurocinematics provides an easy, naturalistic approach for studying and diagnosing learning disorders. While the neural underpinnings of developmental learning disorders are traditionally assessed with well-established methods like EEG and fMRI that target particular cognitive domains, such as simple visual and attention tasks, there is initial evidence and theoretical background in support of neurocinematics as a biomarker for learning differences. By using ADHD, dyslexia, and autism as case studies, this literature review discusses the potential advantages of neurocinematics as a new tool for learning disorders research.

Keywords: behavioral and social sciences, neuroscience, neurocinematics, biomarkers, neurobehavioral disorders

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Authors: Khaled M. Alhawiti

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Natural Language Processing (NLP) is an effective approach for bringing improvement in educational setting. This involves initiating the process of learning through the natural acquisition in the educational systems. It is based on following effective approaches for providing the solution for various problems and issues in education. Natural Language Processing provides solution in a variety of different fields associated with the social and cultural context of language learning. It is based on involving various tools and techniques such as grammar, syntax, and structure of text. It is effective approach for teachers, students, authors, and educators for providing assistance for writing, analysis, and assessment procedure. Natural Language Processing is widely integrated in the large number of educational contexts such as research, science, linguistics, e-learning, evaluations system, and various other educational settings such as schools, higher education system, and universities. Natural Language Processing is based on applying scientific approach in the educational settings. In the educational settings, NLP is an effective approach to ensure that students can learn easily in the same way as they acquired language in the natural settings.

Keywords: natural language processing, education, application, e-learning, scientific studies, educational system

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Chuluundorj Begz

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This paper presents the dynamic, psycho-cognitive approach to study of human verbal thinking on the basis of typologically different languages /as a Mongolian, English and Russian/. Topological equivalence in verbal communication serves as a basis of Universality of mental structures and therefore deep structures. Mechanism of verbal thinking consisted at the deep level of basic concepts, rules for integration and classification, neural networks of vocabulary. In neuro cognitive study of language, neural architecture and neuro psychological mechanism of verbal cognition are basis of a vector-based modeling. Verbal perception and interpretation of the infinite set of meanings and propositions in mental continuum can be modeled by applying tensor methods. Euclidean and non-Euclidean spaces are applied for a description of human semantic vocabulary and high order structures.

Keywords: Euclidean spaces, isomorphism and homomorphism, mental lexicon, mental mapping, semantic memory, verbal cognition, vector space

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Authors: Kyle Saltmarsh

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Acoustic testing possesses many benefits due to its non-destructive nature and practicality. There hence exists many scenarios in which using acoustic testing for condition testing shows powerful feasibility. A wealth of information is contained within the acoustic and vibration characteristics of structures, allowing the development meaningful features for the classification of their respective condition. In this paper, methods, results, and discussions are presented on the use of non-destructive acoustic testing coupled with acoustic feature extraction and machine learning techniques for the condition testing of manufactured circular steel plates subjected to varied levels of damage.

Keywords: plates, deformation, acoustic features, machine learning

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Authors: Namubiru Zula, Aganyira Kelle, Van der Linden Josje, Openjuru George Laadah

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Learning to know is a key principle to lifelong learning, with self-direction as the cornerstone. This study sought to initiate self-direction for lifelong learning through social constructivism among fishers; with the major goal of creating a community of fishers who continuously learn from each other for sustainable fishing. Government of Uganda has instituted several mechanisms like co-management with Beach Management Unit (BMU) System against illegal fishing. However, illegal fishing persists, there is reduced fish stocks with several outcry on how fishers are handled. Some studies have indicated that it’s the poor orientation of BMU leaders and fishers which are top down. This initial engagement of fishers was conducted through a meeting and use of stake holder’s analysis tool to discuss the relevance of the study; harnessing fishers’ knowledge for sustainable fisheries on Lake Victoria, its objectives, the key stake holders to enable them fish sustainably. It revealed initial attempt to learn from each other and learning to know among fishers, with some elements of self-direction. However, fishers attempt to learning and self-direction are affected by prior brutal enforcement experiences. This meeting led to fishers gain some sense of hope towards enforcement brutality. The key stakeholders highlighted include MAAIF, FAO, UNBS, NaFIRRI, LVFO, BMU, UFPEA, Fishers m employers, Fisheries Protection Unit, GIZ, and any Non-Government organization but declined the Association of Fisheries and Lake Users in Uganda.

Keywords: self direction, lifelong learning, social constructivism, sustainable fishing

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Authors: Fadoua Ouamani, Narjès Bellamine Ben Saoud, Henda Hajjami Ben Ghézala

Abstract:

In the last few years and over the last decades, there was a growing interest in the development of Computer Supported Collaborative Learning (CSCL) environments. However, the existing systems ignore the variety of learners and their socio-cultural differences, especially in the case of distant and networked learning. In fact, within such collaborative learning environments, learners from different socio-cultural backgrounds may interact together. These learners evolve within various cultures and social contexts and acquire different socio-cultural values and behaviors. Thus, they should be assisted while communicating and collaborating especially in an intercultural group. Besides, the communication and collaboration tools provided to each learner must depend on and be adapted to her/his socio-cultural profile. The main goal of this paper is to present the proposed socio-cultural adaptation approach based on and guided by ontologies to adapt CSCL environments to the socio-cultural profiles of its users (learners or others).

Keywords: CSCL, socio-cultural profile, adaptation, ontology

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Authors: C. W. Kan

Abstract:

Heat setting is a commonly used technique in textile industry for treating synthetic fibers. In this study, we examined the effect of heat-setting process on the dyeing properties of polyester fabric. The heat setting conditions were varied, and these conditions would affect the dyeing results. The aim of this study is to illustrate the proper application method of heat setting process to polyester fabric, and the results could provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, heat setting, polyester, dyeing

Procedia PDF Downloads 247

Authors: Early Sol A. Gadong, Lourdes C. Zamora, Jonny B. Pornel, Aurora Fe C. Bautista

Abstract:

Various research has shown that writing allows students to engage in metacognition and provides them with a venue to communicate their disposition towards what they are learning. However, few studies have explored students’ feelings about the incorporation of such writing activities in their mathematics classes. Through reflection sheets, group discussions, and interviews, this mixed-methods study explored students’ perceptions and insights on supplementary writing activities in their Elementary Algebra class. Findings revealed that while students generally have a positive regard for writing activities, they have conflicting views about how writing activities can help them in their learning. A big majority contend that writing activities can enhance the learning of mathematical content and attitudes towards mathematics if they allow students to explore and synthesize what they have learned and reflected on their emotional disposition towards mathematics. Also, gender does not appear to play a significant role in students’ reactions to writing activities.

Keywords: writing in math, metacognition, affective factors in learning, elementary algebra classroom

Procedia PDF Downloads 443

Authors: Wera Supa, Panita Wannapiroon

Abstract:

This paper is a report on the designing of the social collaborative learning model based on proactive involvement to Promote the global merit principle in cultivating youths’ morality. The research procedures into two phases, the first phase is to design the social collaborative learning model based on proactive involvement to promote the global merit principle in cultivating youths’ morality, and the second is to evaluate the social collaborative learning model based on proactive involvement. The sample group in this study consists of 15 experts who are dominant in proactive participation, moral merit principle and youths’ morality cultivation from executive level, lecturers and the professionals in information and communication technology expertise selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. This study has explored that there are four significant factors in promoting the hands-on collaboration of global merit scheme in order to implant virtues to adolescences which are: 1) information and communication Technology Usage; 2) proactive involvement; 3) morality cultivation policy, and 4) global merit principle. The experts agree that the social collaborative learning model based on proactive involvement is highly appropriate.

Keywords: social collaborative learning, proactive involvement, global merit principle, morality

Procedia PDF Downloads 388

Authors: Craig Mertens

Abstract:

Teaching art history or any other academic subject to EFL students can be done successfully. A course called Western Images was created to teach Japanese students art history while only using English in the classroom. An approach known as Content and Language Integrated Learning (CLIL) was used as a basis for this course. This paper’s purpose is to state the reasons why learning about art history is important, go through the process of creating content for the course, and suggest multiple tasks to help students practice the critical thinking skills used in analyzing and drawing conclusions of works of art from western culture. As a guide for this paper, Brown’s (1995) six elements of a language curriculum will be used. These stages include needs analysis, goals and objectives, assessment, materials, teaching method and tasks, and evaluation of the course. The goal here is to inspire debate and discussion regarding CLIL and its pros and cons, and to question current curriculum in university language courses.

Keywords: art history, EFL, content and language integration learning, critical thinking

Procedia PDF Downloads 597