Search results for: blended and integrated learning

Authors: Canan Duzan

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For most language learners, mastery of the speaking skill is the proof of the mastery of the foreign language. On the other hand, the speaking skill is considered as the most difficult aspect of language learning to develop for both learners and teachers. Especially in countries like Turkey where exposure to the target language is minimum and resources and opportunities provided for language practice are scarce, teaching and learning to speak the language become a real struggle for teachers and learners alike. Data collected from students, instructors, faculty members and the business sector in needs analysis studies conducted previously at Middle East Technical University (METU) consistently revealed the need for addressing the problem of lack of confidence in speaking English. Action was taken during the design of the only EAP speaking course offered in Modern Languages Department since lack of confidence is considered to be a serious barrier for effective communication and causes learners to suffer from insecurity, uncertainty and fear. “Confidence building” served as the guiding principle in the syllabus design, nature of the tasks created for the course and the assessment procedures to help learners become more confident speakers of English. In order to see the effectiveness of the decisions made during the design phase of the course and whether students become more confident speakers upon completion of the course, a case study was carried out with 100 students at METU. A questionnaire including both Likert-Scale and open-ended items were administered to students to collect data and this data were analyzed using the SPSS program. Group interviews were also carried out to gain more insight into the effectiveness of the course in terms of building speaking confidence. This presentation will explore the specific actions taken to develop students’ confidence based on the findings of program evaluation studies and to what extent the students believe these actions to be effective in improving their confidence. The unique design of this course and strategies adopted for confidence building are highly applicable in other EAP contexts and may yield similar positive results.

Keywords: confidence, EAP, speaking, strategy

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Malephole Philomena Sefotho

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Nowadays, it is a fact that the majority of people, worldwide, are bilingual rather than monolingual due to the surge of globalisation and mobility. Consequently, bilingual education is a topical issue of discussion among researchers. Several studies that have focussed on it have highlighted the importance and need for incorporating learners’ linguistic repertoires in multilingual classrooms and move away from the colonial approach which is a monolingual bias – one language at a time. Researchers pointed out that a systematic approach that involves the concurrent use of languages and not a separation of languages must be implemented in bilingual classroom settings. Translanguaging emerged as a systematic approach that assists learners to make meaning of their world and it involves allowing learners to utilize all their linguistic resources in their classrooms. The South African language policy also room for diverse languages use in bi/multilingual classrooms. This study, therefore, sought to explore how teachers apply translanguaging in bilingual classrooms in incorporating learners’ linguistic repertoires. It further establishes teachers’ perspectives in the use of more than one language in teaching and learning. The participants for this study were language teachers who teach at bilingual primary schools in Johannesburg in South Africa. Semi-structured interviews were conducted to establish their perceptions on the concurrent use of languages. Qualitative research design was followed in analysing data. The findings showed that teachers were reluctant to allow translanguaging to take place in their classrooms even though they realise the importance thereof. Not allowing bilingual learners to use their linguistic repertoires has resulted in learners’ negative attitude towards their languages and contributed in learners’ loss of their identity. This article, thus recommends a drastic change to decolonised approaches in teaching and learning in multilingual settings and translanguaging as a decolonial move where learners are allowed to translanguage freely in their classroom settings for better comprehension and making meaning of concepts and/or related ideas. It further proposes continuous conversations be encouraged to bring eminent cultural and linguistic genocide to a halt.

Keywords: bilingualism, decolonisation, linguistic repertoires, translanguaging

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Authors: Clince Rodrigues

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Due to high dense areas, there is a continuous increase in the global warming and urban pollution, thus integrating green with the built environment is vital. The paper deals with the understanding of vegetation in architecture and how a proper design strategy can aim at improving not only the performances of buildings but also the outdoor climate. In the present scenario of cities, one cannot inhale pure air. Vegetations combat global warming by absorbing the carbon emitted by vehicles, lowering carbon emissions from fossil fuel-burning plants, and reducing the energy used for climate control in buildings by the use of plants which can reduce the carbon emission and thus, making the environment less polluted. A comparative study of areas, neighborhood and dwelling unit has been used as a scope for understanding different scenarios and scale. By comparing a system (area; building) with and without vegetation, and then finding out the difference. Understanding the Vijayawada city by taking its past and present conditions, and how these changes have affected the environment and people at a macro and micro level. Built environment and climactic performance at the building level and surrounding spaces are the areas that are covered in the study.

Keywords: climate, environment, neighborhood, pollution, vegetation, Vijayawada, urban

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Authors: Fawzi Srairi, Abderrahmane Dib

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Recently, the desire for a self-powered micro and nanodevices has attracted a great interest of using sustainable energy sources. Further, the ultimate goal of nanogenerator is to harvest energy from the ambient environment in which a self-powered device based on these generators is needed. With the development of nanogenerator-based circuits design and optimization, the building of new device simulator is necessary for the study and the synthesis of electromechanical parameters of this type of models. In the present article, both numerical modeling and optimization of piezoelectric nanogenerator based on zinc oxide have been carried out. They aim to improve the electromechanical performances, robustness, and synthesis process for nanogenerator. The proposed model has been developed for a systematic study of the nanowire morphology parameters in stretching mode. In addition, heuristic optimization technique, namely, particle swarm optimization has been implemented for an analytic modeling and an optimization of nanogenerator-based process in stretching mode. Moreover, the obtained results have been tested and compared with conventional model where a good agreement has been obtained for excitation mode. The developed nanogenerator model can be generalized, extended and integrated into simulators devices to study nanogenerator-based circuits.

Keywords: electrical potential, heuristic algorithms, numerical modeling, nanogenerator

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Authors: Ugo Galvanetto, Pirto G. Pavan, Mirco Zaccariotto

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The discipline of Computer-integrated surgery (CIS) will provide equipment able to improve the efficiency of healthcare systems and, which is more important, clinical results. Surgeons and machines will cooperate in new ways that will extend surgeons’ ability to train, plan and carry out surgery. Patient specific CIS of the brain requires several steps: 1 - Fast generation of brain models. Based on image recognition of MR images and equipped with artificial intelligence, image recognition techniques should differentiate among all brain tissues and segment them. After that, automatic mesh generation should create the mathematical model of the brain in which the various tissues (white matter, grey matter, cerebrospinal fluid …) are clearly located in the correct positions. 2 – Reliable and fast simulation of the surgical process. Computational mechanics will be the crucial aspect of the entire procedure. New algorithms will be used to simulate the mechanical behaviour of cutting through cerebral tissues. 3 – Real time provision of visual and haptic feedback A sophisticated human-machine interface based on ergonomics and psychology will provide the feedback to the surgeon. The present work will address in particular point 2. Modelling the cutting of soft tissue in a structure as complex as the human brain is an extremely challenging problem in computational mechanics. The finite element method (FEM), that accurately represents complex geometries and accounts for material and geometrical nonlinearities, is the most used computational tool to simulate the mechanical response of soft tissues. However, the main drawback of FEM lies in the mechanics theory on which it is based, classical continuum Mechanics, which assumes matter is a continuum with no discontinuity. FEM must resort to complex tools such as pre-defined cohesive zones, external phase-field variables, and demanding remeshing techniques to include discontinuities. However, all approaches to equip FEM computational methods with the capability to describe material separation, such as interface elements with cohesive zone models, X-FEM, element erosion, phase-field, have some drawbacks that make them unsuitable for surgery simulation. Interface elements require a-priori knowledge of crack paths. The use of XFEM in 3D is cumbersome. Element erosion does not conserve mass. The Phase Field approach adopts a diffusive crack model instead of describing true tissue separation typical of surgical procedures. Modelling discontinuities, so difficult when using computational approaches based on classical continuum Mechanics, is instead easy for novel computational methods based on Peridynamics (PD). PD is a non-local theory of mechanics formulated with no use of spatial derivatives. Its governing equations are valid at points or surfaces of discontinuity, and it is, therefore especially suited to describe crack propagation and fragmentation problems. Moreover, PD does not require any criterium to decide the direction of crack propagation or the conditions for crack branching or coalescence; in the PD-based computational methods, cracks develop spontaneously in the way which is the most convenient from an energy point of view. Therefore, in PD computational methods, crack propagation in 3D is as easy as it is in 2D, with a remarkable advantage with respect to all other computational techniques.

Keywords: computational mechanics, peridynamics, finite element, biomechanics

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Authors: Tamas Hartvanyi, Zoltan Andras Nagy, Miklos Szabo

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The dynamic and static capacity are two opposing aspect of warehouse design. Static capacity optimization aims to maximize the space-usage for goods storing, while dynamic capacity needs more free place to handling them. They are opposing by the building structure and the area utilization. According to Pareto principle: the 80% of the goods are the 20% of the variety. From the origin of this statement, it worth to store the big amount of same products by fulfill the space with minimal corridors, meanwhile the rest 20% of goods have the 80% variety of the whole range, so there is more important to be fast-reachable instead of the space utilizing, what makes the space fulfillment numbers worse. The warehouse design decisions made in present practice by intuitive and empiric impressions, the planning method is formed to one selected technology, making this way the structure of the warehouse homogeny. Of course the result can’t be optimal for the inhomogeneous demands. A new innovative model based on our research will be introduced in this paper to describe the technic capacities, what makes possible to define optimal cluster of technology. It is able to optimize the space fulfillment and the dynamic operation together with this cluster application.

Keywords: warehouse, warehouse capacity, warehouse design method, warehouse optimization

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Authors: Han-Wei Shih, Yao-Nan Wang, Ko-Tung Chang, Lung-Ming Fu

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A multi-channel cell growth real-time monitor and evaluation system using charge-coupled device (CCD) sensors with 40X lens integrating a NI LabVIEW image processing program is proposed and demonstrated. The LED light source control of monitor system is utilizing 8051 microprocessor integrated with NI LabVIEW software. In this study, the same concentration RAW264.7 cells growth rate and morphology in four different culture conditions (DMEM, LPS, G1, G2) were demonstrated. The real-time cells growth image was captured and analyzed by NI Vision Assistant every 10 minutes in the incubator. The image binarization technique was applied for calculating cell doubling time and cell division index. The cells doubling time and cells division index of four group with DMEM, LPS, LPS+G1, LPS+G2 are 12.3 hr,10.8 hr,14.0 hr,15.2 hr and 74.20%, 78.63%, 69.53%, 66.49%. The image magnification of multi-channel CCDs cell real-time monitoring system is about 100X~200X which compares with the traditional microscope.

Keywords: charge-coupled device (CCD), RAW264.7, doubling time, division index

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Authors: Nizar Ahmad, Mushtaq Ahmad Jadoon, Farhat Ullah

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This study investigates the peace efforts made by Pakhtun’s traditional institution Jirga in conflict-affected communities of Khyber Pakhtunkhwa. Data were collected through a structured interview schedule from a sample of 278 household members in four selected villages of Dir Upper and Dir Lower Districts. A Chi square test was applied to ascertain relationships between Jirga related factors with the state of peace in the study area. It was found that factors such as Jirga regularly conducted meetings (P=. 000), it inflicted punishment upon local militants (P=. 001), ex-combatants were re-integrated through Jirga (P= .000) and Jirga ordered the local the defiant to leave the community had a significant association with state of peace in the area. It is concluded that Jirga system had played a vital role in the peacebuilding process of the area through provision of support to government in peace operation and mobilizing local people for peace in the area. It is suggested that Jirga shall to be the part of peace process and government needs to provide its possible support to members of the Jirga in order to enhance their capacity of peace work.

Keywords: Jirga, peacebuilding, terrorism, traditional mechanism, conflict affect areas

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Authors: Yi-Hsiang Pan, Chen-Hui Huang, Wei-Ting Hsu

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The purposes of the study were to understand these topics as follows: 1. To explore the effect of merging teaching personal and social responsibility (TPSR) with sports education model on students' game performance and responsibility. 2. To explore the effect of sports education model on students' game performance and responsibility. 3. To compare the difference between "merging TPSR with sports education model" and "sports education model" on students' game performance and responsibility. The participants include three high school physical education teachers and six physical education classes. Every teacher teaches an experimental group and a control group. The participants had 121 students, including 65 students in the experimental group and 56 students in the control group. The research methods had game performance assessment, questionnaire investigation, interview, focus group meeting. The research instruments include personal and social responsibility questionnaire and game performance assessment instrument. Paired t-test test and MANCOVA were used to test the difference between "merging TPSR with sports education model" and "sports education model" on students' learning performance. 1) "Merging TPSR with sports education model" showed significant improvements in students' game performance, and responsibilities with self-direction, helping others, cooperation. 2) "Sports education model" also had significant improvements in students' game performance, and responsibilities with effort, self-direction, helping others. 3.) There was no significant difference in game performance and responsibilities between "merging TPSR with sports education model" and "sports education model". 4)."Merging TPSR with sports education model" significantly improve learning atmosphere and peer relationships, it may be developed in the physical education curriculum. The conclusions were as follows: Both "Merging TPSR with sports education model" and "sports education model" can help improve students' responsibility and game performance. However, "Merging TPSR with sports education model" can reduce the competitive atmosphere in highly intensive games between students. The curricular projects of hybrid TPSR-Sport Education model is a good approach for moral character education.

Keywords: curriculum and teaching model, sports self-efficacy, sport enthusiastic, character education

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Ali Kheyroddin, Niloufar Mashhadiali, Frazaneh Kheyroddin

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In last decades, tubular systems employed for tall buildings were efficient structural systems. However, increasing the height of a building leads to an increase in structural material corresponding to the loads imposed by lateral loads. Based on this approach, new structural systems are emerging to provide strength and stiffness with the minimum premium for height. In this research, selected tube-type structural systems such as framed tubes, braced tubes, diagrids and hexagrid systems were applied as a single tube, tubular structures combined with braced core and outrigger trusses on a set of 48, 72, and 96-story, respectively, to improve integrated structural systems. This paper investigated structural material consumption by model structures focusing on the premium for height. Compared analytical results indicated that as the height of the building increased, combination of the structural systems caused the framed tube, hexagrid and braced tube system to pay fewer premiums to material tonnage while in diagrid system, combining the structural system reduced insignificantly the steel material consumption.

Keywords: braced tube, diagrid, framed tube, hexagrid

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Authors: Zahra Okba, Hassan El Ouizgani

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Anticipating an individual’s behavior to the environmental factors allows for having relevant ecological forecasts. The Dynamic Energy Budget model facilitates prediction, and it is mechanically dependent on biology to abiotic factors but is generally field verified under relatively stable physical conditions. Dynamic Energy Budget Theory (DEB) is a robust framework that can link the individual state to environmental factors, and in our work, we have tested its ability to account for variability by looking at model predictions in the Agadir Bay, which is characterized by a semi-arid climate and temperature is strongly influenced by the trade winds front and nutritional availability. From previous works in our laboratory, we have collected different biological DEB model parameters of Mytilus galloprovincialis mussel in Agadir Bay. We mathematically formulated the equations that make up the DEB model and then adjusted our analytical functions with the observed biological data of our local species. We also assumed the condition of constant immersion, and then we integrated the details of the tidal cycles to calculate the metabolic depression at low tide. Our results are quite satisfactory concerning the length and shape of the shell in one part and the gonadosomatic index in another part.

Keywords: dynamic energy budget, mussels, mytilus galloprovincialis, agadir bay, DEB model

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Authors: Tomasz Zarebski

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A very important element of the education system is its evaluation procedure. Each education system should be systematically evaluated and improved. Among the criteria subject to evaluation, attention should be paid to the following: structure of the study programme, implementation of the study programme, admission to studies, verification of learning outcomes achievement by students, giving credit for individual semesters and years, and awarding diplomas, competence, experience, qualifications and the number of staff providing education, staff development, and in-service training, education infrastructure, cooperation with social and economic stakeholders on the development, conditions for and methods of improving the internationalisation of education provided as part of the degree programme, supporting learning, social, academic or professional development of students and their entry on the labour market, public access to information about the study programme and quality assurance policy. Concerning the assessment process and the individual assessment indicators, the participation of students in these processes is essential. The purpose of this paper is to analyse the rules of student participation in accreditation processes on the example of individual countries in Europe. The rules of students' participation in the work of accreditation committees and their influence on the final grade of the committee were analysed. Most of the higher education institutions follow similar rules for accreditation. The general model gives the individual institution freedom to organize its own quality assurance, as long as the system lives up to the criteria for quality and relevance laid down in the particular provisions. This point also applies to students. The regulations of the following countries were examined in the legal-comparative aspect: Poland (Polish Accreditation Committee), Denmark (The Danish Accreditation Institution), France (High Council for the Evaluation of Research and Higher Education), Germany (Agency for Quality Assurance through Accreditation of Study Programmes) and Italy (National Agency for the Evaluation of Universities and Research Institutes).

Keywords: accreditation, student, study programme, quality assurance in higher education

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Authors: Mohammad Ali Al-Deeb, Hamda Ateeq Al Dhaheri

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Insects cause major damage to crops and fruit trees worldwide. In the United Arab Emirates, the date palm tree is the most economically important tree which is used for date production as well as an ornamental tree. In 2002, the number of date palm trees in UAE was 40,700,000 and it is increasing over time. The longhorn stem borer (Jebusaea hammerschmidtii) and the lesser date month (Batrachedra amydraula) are important insect pests causing damage to date palm trees in UAE. Population dynamics of the Jebusaea hammerschmidtii and Batrachedra amydraula were studied by using light and pheromons traps, respectively in Al-Ain, UAE. The first trap catch of B. amydraula adults occurred on 19 April and the insect population peaked up on 26 April 2014. The first trap catch of J. hammerschmidtii occurred in April 2014. The numbers increased over time and the population peak occurred in June. The trapping was also done in 2015. The changes in insect numbers in relation to weather parameters are discussed. Also, the importance of the results on the management of these two pests is highlighted.

Keywords: date palm, integrated pest management, UAE, light trap, pheromone trap

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

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Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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Authors: Muhammad Afzal, Muhammad Sajjad

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Climate change has become a global environmental challenge and it has affected the world’s economy. Its impact is widespread across all major sectors of the economy i.e. agriculture, industry, and services sectors. This study attempts to measure the long run as well as the short-run dynamic between energy; environment and economic growth by using Autoregressive Distributed Lag (ARDL) bound testing approach at aggregate as well as sectoral level. We measured the causal relationship between electricity consumption, fuel consumption, CO₂ emission, and real Gross Domestic Product (GDP) for the period of 1980 to 2016 for Pakistan. Our co-integration results reveal that all the variables are co-integrated at aggregate as well as at sectoral level. Electricity consumption shows two-way casual relation at for industry, services and aggregate level. The inverted U-Curve hypothesis tested the relationship between greenhouse gas emissions and per capita GDP and results supported the Environment Kuznet Curve (EKC) hypothesis. This study cannot ignore the importance of energy for economic growth but prefers to focus on renewable and green energy to pave on the trajectory of development.

Keywords: climate change, economic growth, energy, environment

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Authors: A. Kahil, A. Nekmouche, N. Khelil, I. Hamadou, M. Hamizi, Ne. Hannachi

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The objective of this work is to study the influence of the nonlinear behavior models of the concrete (concrete_BAEL and concrete_UNI) as well as the confinement brought by the transverse reinforcement on the seismic response of reinforced concrete frame (RC/frame). These models as well as the confinement are integrated in the Cast3m finite element calculation code. The consideration of confinement (TAC, taking into account the confinement) provided by the transverse reinforcement and the non-consideration of confinement (without consideration of containment, WCC) in the presence and absence of a vertical load is studied. The application was made on a reinforced concrete frame (RC/frame) with 3 levels and 2 spans. The results show that on the one hand, the concrete_BAEL model slightly underestimates the resistance of the RC/frame in the plastic field, whereas the concrete_uni model presents the best results compared to the simplified model "concrete_BAEL", on the other hand, for the concrete-uni model, taking into account the confinement has no influence on the behavior of the RC/frame under imposed displacement up to a vertical load of 500 KN.

Keywords: reinforced concrete, nonlinear calculation, behavior laws, fiber model confinement, numerical simulation

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Rajesh Kondareddy, Prakash Kumar Nayak, Maunash Das, Vrinatri Velentina Boro

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Today, there is a huge global concern for sustainable development which would include minimizing the consumption of non-renewable energies without affecting the basic global economy. Solar drying is one of the important processes used for extending the shelf life of agricultural products. The performance of a low cost automated solar dryer fitted with cascade control scheme and modified PI controller for drying chilli was investigated. The dryer was composed of designed solar collector (air heater) fitted with cylindrical pipes to improve the air velocity and a solar drying chamber containing rack of two cheese cloth (net) trays both being integrated together. The air allowed in through air inlet is heated up in the solar collector and channelled through the drying chamber where it is utilized in drying (removing the moisture content from the food substance or agricultural produce loaded). Here, to maintain the temperature in the heating chambers and to improve performance, a modified PI (Proportional–Integral) controller was used due its simplicity and robustness. Drying time for drying chilli from the initial moisture content of 88.5% (wb) to 7.3% (wb) was estimated to be 14 hours in solar dryer whereas 32 h was observed in the open sun drying.

Keywords: cascade control, chilli, PI controller, solar dryer

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 64

Authors: Odai Ibrahim Mohammed Al Balasmeh, Tapas Karmaker, Richa Babbar

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In this study, the reservoir capacity and sediment deposition were estimated using remote sensing data. The satellite images were synchronized with water level and storage capacity to find out the change in sediment deposition due to soil erosion and transport by streamflow. The water bodies spread area was estimated using vegetation indices, e.g., normalize differences vegetation index (NDVI) and normalize differences water index (NDWI). The 3D reservoir bathymetry was modeled by integrated water level, storage capacity, and area. From the models of different time span, the change in reservoir storage capacity was estimated. Another reservoir with known water level, storage capacity, area, and sediment deposition was used to validate the estimation technique. The t-test was used to assess the results between observed and estimated reservoir capacity and sediment deposition.

Keywords: satellite data, normalize differences vegetation index, NDVI, normalize differences water index, NDWI, reservoir capacity, sedimentation, t-test hypothesis

Procedia PDF Downloads 151

Authors: Jiri Barta

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At the present time, awareness, education, computer simulation and information systems protection are very serious and relevant topics. The article deals with perspectives and possibilities of implementation of emergence or natural hazard threats into the system which is developed for communication among members of crisis management staffs. The Czech Hydro-Meteorological Institute with its System of Integrated Warning Service resents the largest usable base of information. National information systems are connected to foreign systems, especially to flooding emergency systems of neighboring countries, systems of European Union and international organizations where the Czech Republic is a member. Use of outputs of particular information systems and computer simulations on a single communication interface of information system for communication among members of crisis management staff and setting the site interoperability in the net will lead to time savings in decision-making processes in solving extraordinary events and crisis situations. Faster managing of an extraordinary event or a crisis situation will bring positive effects and minimize the impact of negative effects on the environment.

Keywords: computer simulation, communication, continuity, critical infrastructure, information systems, safety

Procedia PDF Downloads 322

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

Procedia PDF Downloads 69

Authors: Mohammad H. Yarmohammadian, Fatemeh Rezaei

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Introduction: Improving patient safety in health systems is one of the main priorities in healthcare systems, so clinical risk management in organizations has become increasingly significant. Although several tools have been developed for clinical risk management, each has its own limitations. Aims: This study aims to develop a comprehensive tool that can complete the limitations of each risk assessment and management tools with the advantage of other tools. Methods: Procedure was determined in two main stages included development of an initial model during meetings with the professors and literature review, then implementation and verification of final model. Subjects and Methods: This study is a quantitative − qualitative research. In terms of qualitative dimension, method of focus groups with inductive approach is used. To evaluate the results of the qualitative study, quantitative assessment of the two parts of the fourth phase and seven phases of the research was conducted. Purposive and stratification sampling of various responsible teams for the selected process was conducted in the operating room. Final model verified in eight phases through application of activity breakdown structure, failure mode and effects analysis (FMEA), healthcare risk priority number (RPN), root cause analysis (RCA), FT, and Eindhoven Classification model (ECM) tools. This model has been conducted typically on patients admitted in a day-clinic ward of a public hospital for surgery in October 2012 to June. Statistical Analysis Used: Qualitative data analysis was done through content analysis and quantitative analysis done through checklist and edited RPN tables. Results: After verification the final model in eight-step, patient's admission process for surgery was developed by focus discussion group (FDG) members in five main phases. Then with adopted methodology of FMEA, 85 failure modes along with its causes, effects, and preventive capabilities was set in the tables. Developed tables to calculate RPN index contain three criteria for severity, two criteria for probability, and two criteria for preventability. Tree failure modes were above determined significant risk limitation (RPN > 250). After a 3-month period, patient's misidentification incidents were the most frequent reported events. Each RPN criterion of misidentification events compared and found that various RPN number for tree misidentification reported events could be determine against predicted score in previous phase. Identified root causes through fault tree categorized with ECM. Wrong side surgery event was selected by focus discussion group to purpose improvement action. The most important causes were lack of planning for number and priority of surgical procedures. After prioritization of the suggested interventions, computerized registration system in health information system (HIS) was adopted to prepare the action plan in the final phase. Conclusion: Complexity of health care industry requires risk managers to have a multifaceted vision. Therefore, applying only one of retrospective or prospective tools for risk management does not work and each organization must provide conditions for potential application of these methods in its organization. The results of this study showed that the integrated clinical risk management model can be used in hospitals as an efficient tool in order to improve clinical governance.

Keywords: failure modes and effective analysis, risk management, root cause analysis, model

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Authors: Seung Yoon Hyun, Hyeong Seung An, Myeong Ho Choi, Sung Hwan Bae, Yu Jong Sim

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In 2015, the southern part of the Korean Peninsula has 8.6 million poles, 1.25 million km power lines, and 2 million transformers, etc. It is the massive amount of distribution equipments which could cover a round-trip distance from the earth to the moon and 11 turns around the earth. These distribution equipments are spread out like capillaries and supplying power to every corner of the Korean Peninsula. In order to manage these huge power facility efficiently, KEPCO use DAS (Distribution Automation System) to operate distribution power system since 1997. DAS is integrated system that enables to remotely supervise and control breakers and switches on distribution network. Using DAS, we can reduce outage time and power loss. KEPCO has about 160,000 switches, 50%(about 80,000) of switches are automated, and 41 distribution center monitoring&control these switches 24-hour 365 days to get the best efficiency of distribution networks. However, the rapid increasing renewable energy sources become the problem in the efficient operation of distributed power system. (currently 2,400 MW, 75,000 generators operate in distribution power system). In this paper, it suggests the way to interconnect between renewable energy source and distribution power system.

Keywords: distribution, renewable, connect, DAS (Distribution Automation System)

Procedia PDF Downloads 602

Authors: Y. Fekir, K. Mederbal, M. A. Hamadouche, D. Anteur

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The soil erosion by water has become one of the biggest problems of the environment in the world, threatening the majority of countries. There are several models to evaluate erosion. These models are still a simplified representation of reality. They permit the analysis of complex systems, measurements are complementary to allow an extrapolation in time and space and may combine different factors. The empirical model of soil loss proposed by Wischmeier and Smith (Universal Soil Loss Equation), is widely used in many countries. He considers that erosion is a multiplicative function of five factors: rainfall erosivity (the R factor) the soil erodibility factor (K), topography (LS), the erosion control practices (P) and vegetation cover and agricultural practices (C). In this work, we tried to develop a tool based on Web GIS functionality to evaluate soil losses caused by erosion taking into account five factors. This tool allows the user to integrate all the data needed for the evaluation (DEM, Land use, rainfall ...) in the form of digital layers to calculate the five factors taken into account in the USLE equation (R, K, C, P, LS). Accordingly, and after treatment of the integrated data set, a map of the soil losses will be achieved as a result. We tested the proposed tool on a watershed basin located in the weste of Algeria where a dataset was collected and prepared.

Keywords: USLE, erosion, web gis, Algeria

Procedia PDF Downloads 318

Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

Procedia PDF Downloads 191

Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

Procedia PDF Downloads 158