Search results for: conventional learning method

Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

Procedia PDF Downloads 216

Authors: Nhung T. Bui

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Part of the dilemma facing educational reforms in Vietnam as in other Asian contexts is how to encourage more independence in students’ learning approaches. Since 2005, the Ministry of Education and Training of Vietnam has included the students’ ability to learn independently in its national education objectives. While learner autonomy has been viewed as a goal in the teaching and learning English as a foreign language (EFL) and there has been a considerable literature on strategies to stimulate autonomy in learners, teachers’ voices have rarely been heard. Given that teachers play a central role in helping their students to be more autonomous, especially in an inherent Confucian heritage culture like Vietnam, their attitudes towards learner autonomy should be investigated before any practical implementations could be undertaken. This paper reports significant findings of a survey questionnaire with 262 lecturers of English from 5 universities in Hanoi, Vietnam giving opinions regarding the practices and prospects of learner autonomy in their classrooms. The study reveals that lecturers perceive they should be more responsible than their students in all class-related activities; they most appreciate their students’ ability to learn cooperatively and that they consider stimulating students’ interest as the most important teaching strategy to promote learner autonomy. Lecturers, then, are strongly suggested to gradually ‘empower’ their students through the application of out-of-classroom activities; of learning activities which requires collaboration and team spirit; and of activities which could boost students’ interest in learning English.

Keywords: English as a foreign language, higher education, learner autonomy, Vietnam

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Authors: Ameen Alshugaa, Farrukh Habib

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Shariah (the Islamic law) sanctions a plethora of profit-sharing arrangements for financial transactions. However, when it comes to the practice of Islamic banking, it is felt by the scholars and practitioners that many of these arrangements often fail to compensate different parties of a financial transaction compared to conventional banking, due to the Riba (interest / usury) element. This issue is caused by the parties inability to codify these compensations in any contract so as to avoid Riba. Here, hibah (gift) may be regarded as one of the solutions. In essence, hibah is a unilateral charity contract where a party voluntarily gives away something to another party without any counter value. This paper attempts to analyse theoretical and practical aspects of hibah from the perspective of Islamic law, enunciating its legality and detailing its allowance in Islamic banking. It also discusses several practices evaluating the role of hibah in resolving issues related to Riba. In particular, these practices demonstrate the validity of hibah as a way to distribute revenues and compensate parties in Islamic financial transactions, while achieving competitive advantage over conventional banking, and avoiding the element of Riba.

Keywords: hibah (gift), Islamic Finance, Islamic Law of Contract, profit distribution, Shariah

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Authors: Prakash Singh

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The focus of this exploratory study is on whether teachers demonstrate emphatic concern for their learners in planning, implementing and assessing learning outcomes in their regular classrooms. Empathy must be shown to all learners equally and not only for high-risk learners at the expense of other ability learners. Empathy demonstrated by teachers allows them to build a stronger bond with all their learners. This bond based on trust leads to positive outcomes for learners to be able to excel in their work. Empathic teachers must make every effort to simplify the subject matter for high risk learners so that these learners not only enjoy their learning activities but are also successful like their more able peers. A total of 87.5% of the participants agreed that empathy allows teachers to demonstrate humanistic values in their choice of learning materials for learners of different abilities. It is therefore important for teachers to select content and instructional materials that will contribute to the learners’ success in the mainstream of education. It is also imperative for teachers to demonstrate empathic skills and consequently, to be attuned to the emotions and emotional needs of their learners. Schools need to be reformed, not by simply lengthening the school day or by simply adding more content in the curriculum, but by making school more satisfying to learners. This must be consistent with their diverse learning needs and interests so that they gain a sense of power, fulfillment, and importance in their regular classrooms. Hence, teacher - pupil relationships based on empathic concern for the latter’s educational needs lays the foundation for quality education to be offered.

Keywords: emotional intelligence, empathy, learners’ emotional needs, teachers’ empathic skills

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Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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Authors: Lidija Jevrić, Denis Kučević, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Milica Karadžić

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In the present study, the Hierarchical Cluster Analysis (HCA) was applied in order to determine the differences between the milk samples originating from a conventional dairy farm (CF) and an organic dairy farm (OF) in AP Vojvodina, Republic of Serbia. The clustering was based on the basis of the average values of saturated fatty acids (SFA) content and unsaturated fatty acids (UFA) content obtained for every season. Therefore, the HCA included the annual SFA and UFA content values. The clustering procedure was carried out on the basis of Euclidean distances and Single linkage algorithm. The obtained dendrograms indicated that the clustering of UFA in OF was much more uniform compared to clustering of UFA in CF. In OF, spring stands out from the other months of the year. The same case can be noticed for CF, where winter is separated from the other months. The results could be expected because the composition of fatty acids content is greatly influenced by the season and nutrition of dairy cows during the year.

Keywords: chemometrics, clustering, food engineering, milk quality

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Authors: H. Majour, L. Djabri

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Many methods in the groundwater vulnerability have been developed in the world (methods like PRAST, DRIST, APRON/ARAA, PRASTCHIM, GOD). In this study, our choice dealt with two recent complementary methods using category mapping of index with weighting criteria (Point County Systems Model MSCP) namely the standard DRASTIC method and SI (Susceptibility Index). At present, these two methods are the most used for the mapping of the intrinsic vulnerability of groundwater. Two classes of groundwater vulnerability in the Biskra sandy aquifer were identified by the DRASTIC method (average and high) and the SI method (very high and high). Integrated analysis has revealed that the high class is predominant for the DRASTIC method whereas for that of SI the preponderance is for the very high class. Furthermore, we notice that the method SI estimates better the vulnerability for the pollution in nitrates, with a rate of 85 % between the concentrations in nitrates of groundwater and the various established classes of vulnerability, against 75 % for the DRASTIC method. By including the land use parameter, the SI method produced more realistic results.

Keywords: DRASTIC, SI, GIS, Biskra sandy aquifer, Algeria

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Authors: R. N. Pateriya, T. K. Bhattacharya

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In India, rice-wheat cropping system occupies the major area and contributes about 40% of the country’s total food grain production. It is necessary that production of rice and wheat must keep pace with growing population. However, various factors such as degradation in natural resources, shift in cropping pattern, energy constraints etc. are causing reduction in the productivity of these crops. Seedbed for rice after wheat is difficult to prepare due to presence of straw and stubbles, and require excessive tillage operations to bring optimum tilth. In addition, delayed sowing and transplanting of rice is mainly due to poor crop residue management, multiplicity of tillage operations and non-availability of the power source. With increasing concern for fuel conservation and energy management, farmers might wish to estimate the best cultivation system for more productivity. The widest spread method of tilling land is ploughing with mould board plough. However, with the mould board plough upper layer of soil is neither always loosened at the desired extent nor proper mixing of different layers are achieved. Therefore, additional operations carried out to improve tilth. The farmers are becoming increasingly aware of the need for minimum tillage by minimizing the use of machines. Soil management can be achieved by using the combined active-passive tillage machines. A study was therefore, undertaken in wheat-harvested field to study the impact of conventional and modified tillage practices on paddy crop cultivation. Tillage treatments with tractor as a power source were selected during the experiment. The selected level of tillage treatments of tractor machinery management were (T1:- Direct Sowing of Rice), (T2:- 2 to 3 harrowing and no Puddling with manual transplanting), (T3:- 2 to 3 harrowing and Puddling with paddy harrow with manual transplanting), (T4:- 2 to 3 harrowing and Puddling with Rotavator with manual transplanting). The maximum output was obtained with treatment T1 (7.85 t/ha)) followed by T4 (6.4 t/ha), T3 (6.25 t/ha) and T2 (6.0 t/ha)) respectively.

Keywords: crop residues, cropping system, minimum tillage, yield

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Authors: Duangkamol Thitivesa

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This paper explores the use of project work in a content-based instruction in a Rajabhat University, Thailand. The use of project is to promote kinds of learning expected of student teachers as stated by Thailand Quality Framework: TQF. The kinds of learning are grouped into five domains: Ethical and moral development, knowledge, cognitive skill, interpersonal skills and responsibility, and analytical and communication skills. The content taught in class is used to lead the student teachers to relate their previously-acquired linguistic knowledge to meaningful realizations of the language system in passages of immediate relevance to their professional interests, teaching methods in particular. Two research questions are formulate to guide this study: 1) To what degree are the five domains of learning expected of student teachers after the use of project in a content class?, and 2) What is the academic achievement of the students’ writing skills, as part of the learning domains stated by TQF, against the 70% attainment target after the use of project to enhance the skill? The sample of the study comprised of 38 fourth-year English major students. The data was collected by means of a summative achievement test, student writing works, an observation checklist, and project diary. The scores in the summative achievement test were analyzed by mean score, standard deviation, and t-test. Project diary serves as students’ record of the language acquired during the project. List of structures and vocabulary noted in the diary has shown students’ ability to attend to, recognize, and focus on meaningful patterns of language forms.

Keywords: Thailand quality framework, project Work, writing skill, summative

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Authors: Björn de Kruijf, Arjen Edzes, Sietske Waslander

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In an ever-quickly changing society, lifelong development is seen as a solution to labor market problems by politicians and policymakers. In this paper, we investigate how policy instruments are used to increase participation in lifelong development and on which behavioral principles policy is based. Digitization, automation, and an aging population change society and the labor market accordingly. Skills that were once most sought after in the workforce can become abundantly present. For people to remain relevant in the working population, they need to continue adapting new skills useful in the current labor market. Many reports have been written that focus on the role of lifelong development in this changing society and how lifelong development can help keep people adapt and stay relevant. Inspired by these reports, governments have implemented a broad range of policies to support participation in lifelong development. The question we ask ourselves is how government policies promote participation in lifelong development. This stems from a complex interplay of policy instruments and learning. Regulation, economic and soft instruments can be combined to promote lifelong development, and different types of education further complex policies on lifelong development. Literature suggests that different stages in people’s lives might warrant different methods of learning. Governments could anticipate this in their policies. In order to influence people’s behavior, the government can tap into a broad range of sociological, psychological, and (behavioral) economic principles. The traditional economic assumption that behavior is rational is known to be only partially true, and the government can use many biases in human behavior to stimulate participation in lifelong development. In this paper, we also try to find which biases the government taps into to promote participation if they tap into any of these biases. The goal of this paper is to analyze government policies intended to promote participation in lifelong development. To do this, we develop a framework to analyze the policies on lifelong development. We specifically incorporate the role of learning and the behavioral principles underlying policy instruments in the framework. We apply this framework to the case of the Netherlands, where we examine a set of policy documents. We single out the policies the government has put in place and how they are vertically and horizontally related. Afterward, we apply the framework and classify the individual policies by policy instrument and by type of learning. We find that the Dutch government focuses on formal and non-formal learning in their policy instruments. However, the literature suggests that learning at a later age is mainly done in an informal manner through experiences.

Keywords: learning, lifelong development, policy analysis, policy instruments

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Hong Zhang

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The main purpose of this study is to show that machine translation (MT) post-editing (PE) training can help our Chinese students learn Spanish as a second language. Our hypothesis is that they might make better use of it by learning PE skills specific for foreign language learning. We have developed PE training materials based on the data collected in a previous study. Training material included the special error types of the output of MT and the error types that our Chinese students studying Spanish could not detect in the experiment last year. This year we performed a pilot study in order to evaluate the PE training materials effectiveness and to what extent PE training helps Chinese students who study the Spanish language. We used screen recording to record these moments and made note of every action done by the students. Participants were speakers of Chinese with intermediate knowledge of Spanish. They were divided into two groups: Group A performed PE training and Group B did not. We prepared a Chinese text for both groups, and participants translated it by themselves (human translation), and then used Google Translate to translate the text and asked them to post-edit the raw MT output. Comparing the results of PE test, Group A could identify and correct the errors faster than Group B students, Group A did especially better in omission, word order, part of speech, terminology, mistranslation, official names, and formal register. From the results of this study, we can see that PE training can help Chinese students learn Spanish as a second language. In the future, we could focus on the students’ struggles during their Spanish studies and complete the PE training materials to teach Chinese students learning Spanish with machine translation.

Keywords: machine translation, post-editing, post-editing training, Chinese, Spanish, foreign language learning

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Authors: Amal Machtalay

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In this survey, we aim to review the rapidly growing literature on numerical methods to solve different forms of mean field problems, namely mean field games (MFG), mean field controls (MFC), potential MFGs, and master equations, as well as their corresponding recent applications. Here, we distinguish two families of numerical methods: iterative methods based on mesh generation and those called mesh-free, normally related to neural networking and learning frameworks.

Keywords: mean-field games, numerical schemes, partial differential equations, complex systems, machine learning

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Authors: Zainuddin Abuhamid Muhammad Ghozali, Andrew Whitworth

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Islamic boarding school or pesantren is a distinctive education institution in Indonesia focusing on religious teachings. Its stance in restricting access to the internet raises a question about its students’ development of digital literacy. Inspired by Luckin’s ecology of resource model, this study aims to map out the digital literacy situation of the institution based on the availability of learning resources, such as digital facilities, digital accessibility, and digital competence. This study was carried out through a survey method involving 50 teachers from pesantrens across the nation. The result shows that pesantrens have provided students with digital facilities at a moderate level, yet the accessibility to using them is still limited. They also incorporated digital competencies into their curriculum, with an emphasis on digital ethics. The study also identifies different patterns of pesantrens’ behavior based on types and educational levels, where certain school types and educational levels tend to give a stricter policy compared to others or vice versa. The restriction of digital resources in pesantren indicated that they had done a filtration process to design their learning environment. The filtration was mainly motivated by sociocultural factors, where they drew concern for the negative impact of the internet. Notably, this restriction also contributes to students’ poor development of digital literacy.

Keywords: digital literacy, ecology of resources, Indonesia, Islamic boarding school

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Authors: David Sinfield, Thomas Cochrane, Marcos Steagall

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While there is much hype around the potential and development of mobile virtual reality (VR), the two key critical success factors are the ease of user experience and the development of a simple user-generated content ecosystem. Educational technology history is littered with the debris of over-hyped revolutionary new technologies that failed to gain mainstream adoption or were quickly superseded. Examples include 3D television, interactive CDROMs, Second Life, and Google Glasses. However, we argue that this is the result of curriculum design that substitutes new technologies into pre-existing pedagogical strategies that are focused upon teacher-delivered content rather than exploring new pedagogical strategies that enable student-determined learning or heutagogy. Visual Communication design based learning such as Graphic Design, Illustration, Photography and Design process is heavily based on the traditional forms of the classroom environment whereby student interaction takes place both at peer level and indeed teacher based feedback. In doing so, this makes for a healthy creative learning environment, but does raise other issue in terms of student to teacher learning ratios and reduced contact time. Such issues arise when students are away from the classroom and cannot interact with their peers and teachers and thus we see a decline in creative work from the student. Using AR and VR as a means of stimulating the students and to think beyond the limitation of the studio based classroom this paper will discuss the outcomes of a student project considering the virtual classroom and the techniques involved. The Atelier learning environment is especially suited to the Visual Communication model as it deals with the creative processing of ideas that needs to be shared in a collaborative manner. This has proven to have been a successful model over the years, in the traditional form of design education, but has more recently seen a shift in thinking as we move into a more digital model of learning and indeed away from the classical classroom structure. This study focuses on the outcomes of a student design project that employed Augmented Reality and Virtual Reality technologies in order to expand the dimensions of the classroom beyond its physical limits. Augmented Reality when integrated into the learning experience can improve the learning motivation and engagement of students. This paper will outline some of the processes used and the findings from the semester-long project that took place.

Keywords: augmented reality, blogging, design in community, enhanced learning and teaching, graphic design, new technologies, virtual reality, visual communications

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Authors: N. Naz, A. D. Domenico, M. N. Huda

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Soft Robotics is a rapidly growing multidisciplinary field where robots are fabricated using highly deformable materials motivated by bioinspired designs. The high dexterity and adaptability to the external environments during contact make soft robots ideal for applications such as gripping delicate objects, locomotion, and biomedical devices. The actuation system of soft robots mainly includes fluidic, tendon-driven, and smart material actuation. Among them, Soft Pneumatic Actuator, also known as SPA, remains the most popular choice due to its flexibility, safety, easy implementation, and cost-effectiveness. However, at present, most of the fabrication of SPA is still based on traditional molding and casting techniques where the mold is 3d printed into which silicone rubber is cast and consolidated. This conventional method is time-consuming and involves intensive manual labour with the limitation of repeatability and accuracy in design. Recent advancements in direct 3d printing of different soft materials can significantly reduce the repetitive manual task with an ability to fabricate complex geometries and multicomponent designs in a single manufacturing step. The aim of this research work is to design and analyse the Soft Pneumatic Actuator (SPA) utilizing both conventional casting and modern direct 3d printing technologies. The mold of the SPA for traditional casting is 3d printed using fused deposition modeling (FDM) with the polylactic acid (PLA) thermoplastic wire. Hyperelastic soft materials such as Ecoflex-0030/0050 are cast into the mold and consolidated using a lab oven. The bending behaviour is observed experimentally with different pressures of air compressor to ensure uniform bending without any failure. For direct 3D-printing of SPA fused deposition modeling (FDM) with thermoplastic polyurethane (TPU) and stereolithography (SLA) with an elastic resin are used. The actuator is modeled using the finite element method (FEM) to analyse the nonlinear bending behaviour, stress concentration and strain distribution of different hyperelastic materials after pressurization. FEM analysis is carried out using Ansys Workbench software with a Yeon-2nd order hyperelastic material model. FEM includes long-shape deformation, contact between surfaces, and gravity influences. For mesh generation, quadratic tetrahedron, hybrid, and constant pressure mesh are used. SPA is connected to a baseplate that is in connection with the air compressor. A fixed boundary is applied on the baseplate, and static pressure is applied orthogonally to all surfaces of the internal chambers and channels with a closed continuum model. The simulated results from FEM are compared with the experimental results. The experiments are performed in a laboratory set-up where the developed SPA is connected to a compressed air source with a pressure gauge. A comparison study based on performance analysis is done between FDM and SLA printed SPA with the molded counterparts. Furthermore, the molded and 3d printed SPA has been used to develop a three-finger soft pneumatic gripper and has been tested for handling delicate objects.

Keywords: finite element method, fused deposition modeling, hyperelastic, soft pneumatic actuator

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Authors: Hoa Pham

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The literature on language teaching and second language acquisition has been largely driven by monolingual ideology with a common assumption that a second language (L2) is best taught and learned in the L2 only. The current study challenges this assumption by reporting learners' positive perceptions of tertiary level teachers' code switching practices in Vietnam. The findings of this study contribute to our understanding of code switching practices in language classrooms from a learners' perspective. Data were collected from student participants who were working towards a Bachelor degree in English within the English for Business Communication stream through the use of focus group interviews. The literature has documented that this method of interviewing has a number of distinct advantages over individual student interviews. For instance, group interactions generated by focus groups create a more natural environment than that of an individual interview because they include a range of communicative processes in which each individual may influence or be influenced by others - as they are in their real life. The process of interaction provides the opportunity to obtain the meanings and answers to a problem that are "socially constructed rather than individually created" leading to the capture of real-life data. The distinct feature of group interaction offered by this technique makes it a powerful means of obtaining deeper and richer data than those from individual interviews. The data generated through this study were analysed using a constant comparative approach. Overall, the students expressed positive views of this practice indicating that it is a useful teaching strategy. Teacher code switching was seen as a learning resource and a source supporting language output. This practice was perceived to promote student comprehension and to aid the learning of content and target language knowledge. This practice was also believed to scaffold the students' language production in different contexts. However, the students indicated their preference for teacher code switching to be constrained, as extensive use was believed to negatively impact on their L2 learning and trigger cognitive reliance on the L1 for L2 learning. The students also perceived that when the L1 was used to a great extent, their ability to develop as autonomous learners was negatively impacted. This study found that teacher code switching was supported in certain contexts by learners, thus suggesting that there is a need for the widespread assumption about the monolingual teaching approach to be re-considered.

Keywords: codeswitching, L1 use, L2 teaching, learners’ perception

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: Enny Suswati, Supangat Supangat

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Background. Ready-to-eat food products are becoming increasingly popular because consumers are increasingly busy, competitive, and changing lifestyles. Examples of ready-to-eat foods include crispy fried chicken. Escherichia coli is one of the most important causes of food-borne diseases and the most frequent antibiotic-resistant pathogen globally. This study assessed the prevalence and antibiotic resistance profile of E. coli from ready-to-eat crispy fried chicken in Jember city, Indonesia. Methodology. This cross-sectional study was conducted from November 2020 to April 2021 by collecting 81crispy fried chicken samples from 27 food stalls in campus area using a simple random sampling method. Isolation and determination of E. coli use were performed by conventional culture method. An antibiotic susceptibility test was conducted using Kirby Bauer disk diffusion method on the Mueller–Hinton agar. Result. Out of 81crispy fried chicken samples, 77 (95.06%) were positive for E. coli. High E. coli drug resistance was observed on ampicillin, amoxicillin (100%) followed by cefixime (98.72%), erythromycin (97.59%), sulfamethoxazole (93.59%), azithromicin (83.33%), cefotaxime (78.28%), choramphenicol (75.64%), and cefixime (74.36%). On the other hand, there was the highest susceptibility for ciprofloxacin (64.10%). The multiple antibiotic resistance indexes of E. coli isolates varied from 0.4 to 1. The predominant antimicrobial resistance profiles of E. coli were CfmCroAmlAmpAzmCtxSxtCE (n=17), CfmCroAmlCipAmpAzmCtxSxtCE (n=16), and CfmAmlAmpAzmCtxSxtCE (n=5), respectively. Multidrug resistance was also found in the isolates' 76/77 (98.70%). Conclusion. The resistance pattern CfmCroAmlAmpAzmCtxSxtCE was the most common among the E. coli isolates, with 17 showing it. The multiple antibiotic index (MAR index) ranged from 0.4 to 1. Hygienic measures should be rigorously implemented and monitoring resistance of E. coli is required to reduce the risks related to the emergence of multi-resistant bacteria

Keywords: antibacterial drug, ready to eat, crispy fried chicken, escherichia coli

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Authors: Majid Vafaeipour, Mohamed El Baghdadi, Florian Verbelen, Peter Sergeant, Joeri Van Mierlo, Kurt Stockman, Omar Hegazy

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The Electrical Variable Transmission (EVT), an electromechanical device, can be considered as an alternative solution to the conventional transmission system utilized in Hybrid Electric Vehicles (HEVs). This study present comparisons in terms of fuel consumption, power split, and state of charge (SoC) of an HEV containing an EVT to a conventional parallel topology and a series topology. To this end, corresponding simulations of these topologies are all performed in presence of control strategies enabling battery charge-sustaining and efficient power split. The power flow through the components of the vehicle are attained, and fuel consumption results of the considered cases are compared. The investigation of the results indicates utilizing EVT can provide significant added values in HEV configurations. The outcome of the current research paves its path for implementation of design optimization approaches on such systems in further research directions.

Keywords: Electrical Variable Transmission (EVT), Hybrid Electric Vehicle (HEV), parallel, series, modeling

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Authors: Dua Hişam, Serhat İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: Ngong Eugene Ekia

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Education is the foundation for the success of any society as its impact transcends across all sectors, including economics, politics, and social welfare. It is through education that individuals acquire the necessary knowledge and skills to succeed in life and contribute meaningfully to society. However, the world is changing rapidly, and it is vital for education systems to adapt to these changes to remain relevant. In this paper, we will discuss the current trends and challenges in education and management and propose solutions that can enable individuals to thrive in an ever-evolving world.

Keywords: access to education, effective teaching and learning, strong management practices, and empowering and personal development

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Authors: Atul K. Desai, Hemal J. Shah

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The tall windmill towers are designed as monopole tower or lattice tower. In the present research, a 125-meter high hybrid tower which is a combination of lattice and monopole type is proposed. The response of hybrid tower is compared with conventional monopole tower. The towers were analyzed in finite element method software considering nonlinear seismic time history load. The synthetic seismic time history for different soil is derived using the SeismoARTIF software. From the present research, it is concluded that, in the hybrid tower, we are not getting resonance condition. The base shear is less in hybrid tower compared to monopole tower for different soil conditions.

Keywords: dynamic analysis, hybrid wind mill tower, resonance condition, synthetic time history

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Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: Deepa Kapoor, Rajshree Singh

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This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

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Authors: Jožef Ritonja, Bojan Grčar, Boštjan Polajžer

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In recent years, electricity trade between neighboring countries has become increasingly intense. Increasing power transmission over long distances has resulted in an increase in the oscillations of the transmitted power. The damping of the oscillations can be carried out with the reconfiguration of the network or the replacement of generators, but such solution is not economically reasonable. The only cost-effective solution to improve the damping of power oscillations is to use power system stabilizers. Power system stabilizer represents a part of synchronous generator control system. It utilizes semiconductor’s excitation system connected to the rotor field excitation winding to increase the damping of the power system. The majority of the synchronous generators are equipped with the conventional power system stabilizers with fixed parameters. The control structure of the conventional power system stabilizers and the tuning procedure are based on the linear control theory. Conventional power system stabilizers are simple to realize, but they show non-sufficient damping improvement in the entire operating conditions. This is the reason that advanced control theories are used for development of better power system stabilizers. In this paper, the adaptive control theory for power system stabilizers design and synthesis is studied. The presented work is focused on the use of model reference adaptive control approach. Control signal, which assures that the controlled plant output will follow the reference model output, is generated by the adaptive algorithm. Adaptive gains are obtained as a combination of the "proportional" term and with the σ-term extended "integral" term. The σ-term is introduced to avoid divergence of the integral gains. The necessary condition for asymptotic tracking is derived by means of hyperstability theory. The benefits of the proposed model reference adaptive power system stabilizer were evaluated as objectively as possible by means of a theoretical analysis, numerical simulations and laboratory realizations. Damping of the synchronous generator oscillations in the entire operating range was investigated. Obtained results show the improved damping in the entire operating area and the increase of the power system stability. The results of the presented work will help by the development of the model reference power system stabilizer which should be able to replace the conventional stabilizers in power systems.

Keywords: power system, stability, oscillations, power system stabilizer, model reference adaptive control

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Authors: Latif Karimi, Yasuhide Mochida

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The purpose of this paper is to study Modern Methods of Construction (MMC); specifically, the prefabrication technology and check the applicability, suitability, and benefits of this construction technique over conventional methods for building new houses in Afghanistan. Construction industry and house building sector are a key contributor to Afghanistan’s economy. However, this sector is challenged with lack of innovation and severe impacts that it has on the environment due to huge amount of construction waste from building, demolition and or renovation activities. This paper studies the prefabrication technology, a popular MMC that is becoming more common, improving in quality and being available in a variety of budgets. Several feasibility studies worldwide have revealed that this method is the way forward in improving construction industry performance as it has been proven to reduce construction time, construction wastes and improve the environmental performance of the construction processes. In addition, this study emphasizes on 'sustainability' in-house building, since it is a common challenge in housing construction projects on a global scale. This challenge becomes more severe in the case of under-developed countries, like Afghanistan. Because, most of the houses are being built in the absence of a serious quality control mechanism and dismissive to basic requirements of sustainable houses; well-being, cost-effectiveness, minimization - prevention of wastes production during construction and use, and severe environmental impacts in view of a life cycle assessment. Methodology: A literature review and study of the conventional practices of building houses in urban areas of Afghanistan. A survey is also being completed to study the potentials and challenges of using prefabrication technology for building modern houses in the cities across the country. A residential housing project is selected for case study to determine the drawbacks of current construction methods vs. prefabrication technique for building a new house. Originality: There are little previous research available about MMC considering its specific impacts on sustainability related to house building practices. This study will be specifically of interest to a broad range of people, including planners, construction managers, builders, and house owners.

Keywords: modern methods of construction (MMC), prefabrication, prefab houses, sustainable construction, modern houses

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Authors: Maha Wiss, Wael Khreich

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Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

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Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

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Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors by Latour. The learning conditions are found to be distinguished by broad complexity characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation

Procedia PDF Downloads 356