Search results for: computation and language

Authors: Tien Nguyen

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The relationship between mentors and mentees in teaching practicum has received the attention of researchers and been widely investigated. Mentors’ authority and power have captured a large and growing body of the literature in the field of teaching practicum. This article revisits mentor-mentee relationship and shifts the focus to mentees’ agency in planning and delivering lessons, an area which has been under-researched. Drawing on Vygotsky’s Zone of Proximal Development and Harré’s Positioning Theory, this qualitative study examines how mentees responded to mentors’ instructions in practicum. Interviews and classroom observations were conducted with 20 participants including both mentors and mentees across two English language teacher education programs in two different geographical locations in Vietnam. The result indicates that regardless of the similarities and/or differences of the programs, mentees’ agency varied in accordance with their identities in specific contexts. Specifically, mentees follow or resist to mentors’ feedback and instruction in revising their lesson plans and delivery these lessons, depending on their professional identities and institutional conditions. This study contributes to the importance of supporting the agency of mentees in teacher education.

Keywords: mentors, mentees, relationship, agency, professional identity, teacher education

Procedia PDF Downloads 129

Authors: B. Umaru Mohammed, Faris A. Al-Maziad, Mohammad Y. Numan

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One of the most important factors affecting the energy performance within a building is a carefully and efficiently designed facade. The primary aim of this research was to identify and present the potentiality of utilising Double-Skin Facade (DSF) construction and critically examine its effect on the energy consumption of an office building located within a maritime desert climate as to the conventional single-skin curtain wall system. A comparative analysis of the effect on the overall energy consumption within an office building was investigated in which a combination of various Double-Skin Facade configurations, systems, and cavity depths, glazing types and orientations were utilised. A computer dynamic modelling was utilised in order to ensure accurate calculations and efficient simulations of the various DSF systems due to the complex nature of the various functions within the Facade cavity. Through the use of the dynamic thermal modelling simulations, the best cavity size glazed type and orientation were determined to lead to a detailed analysis of the efficiency of each respective combination of Double-Skin Facade construction. As such the optimal facade combination for use within an office building located in a maritime desert climate was identified. Results demonstrated that a multi-story Facade, depending on its configuration, save up to 5% on annual cooling loads respect to a Corridor Facade and while vented can save unto 12% when compared to the single skin façade, on annual cooling load in the maritime desert climate. The selected configuration of the DSF from SSF saves an overall annual cooling load of 32%.A comparative analysis of the effect on the overall energy consumption within an office building was investigated in which a combination of various Double-Skin Facade configurations, systems, and cavity depths, glazing types and orientations were utilized. A computer dynamic modelling was utilized in order to ensure accurate calculations and efficient simulations of the various DSF systems due to the complex nature of the various functions within the Facade cavity. Through the use of the dynamic thermal modelling simulations, the best cavity size glazed type and orientation were determined to lead to a detailed analysis of the efficiency of each respective combination of Double-Skin Facade construction. As such the optimal facade combination for use within an office building located in a maritime desert climate was identified. Results demonstrated that a multi-story Facade, depending on its configuration, save up to 5% on annual cooling loads respect to a Corridor Facade and while vented can save unto 12% when compared to the single skin facade, on annual cooling load in the maritime desert climate. The selected configuration of the DSF from SSF saves an overall annual cooling load of 32%.

Keywords: computer dynamics modelling, comparative analysis, energy computation, double skin facade, single skin curtain wall, maritime desert climate

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Authors: Kaoutar Ben Azzou, Hanaa Talei

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Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

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Authors: Archana Vadeyar, Smita Phatak

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Nurturing flora and fauna is the crux of Environment Education yet one tends to forget to nurture the human minds. Youth education presently is too academic, exam oriented and lacks all-round development. A project is whole-hearted purposeful activity proceeding in a social environment. Projects at +2 stages have become, just an easier way of securing marks. The purpose of this study was to explore the concept of an experiential environment education (EE) project for youth involving community interaction. Youth were encouraged to plan activities for children-based on EE through General knowledge (GK), language, math, science, fun games, quiz, sports, art and craft, stories. A purposive sample of 73 students was administered a self-prepared and validated questionnaire; supported by content analysis of reports from EE Journals of 21 students and some photos. Responses of students revealed that project was a joyful and motivating experience, with learnings and realizations, developed concern for others, made them feel responsible, happy and contented. Community interaction programs need to be included in the regular schedule to add more meaning to EE projects and cater to the needs of adolescents for diverting youth energy towards positive action.

Keywords: experiential, project, environment education, youth, community interaction

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Authors: Meruert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova

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The article highlights and describes the characteristic features of real-time face detection in images and videos using machine learning algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As a result, the advantages and disadvantages of Haar Cascade (Haar Cascade OpenCV), HoG SVM (Histogram of Oriented Gradients, Support Vector Machine), and MMOD CNN Dlib (Max-Margin Object Detection, convolutional neural network) detectors used for face detection were determined. Dlib is a general-purpose cross-platform software library written in the programming language C++. It includes detectors used for determining face detection. The Cascade OpenCV algorithm is efficient for fast face detection. The considered work forms the basis for the development of machine learning methods by future computer science teachers.

Keywords: algorithm, artificial intelligence, education, machine learning

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Authors: Martina Kanciruk, Jac J. W. Andrews, Tyrone Donnon

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The purpose of this study was to determine the significance of maternal smoking for the development of childhood overweight and/or obesity. Accordingly, a systematic literature review of English-language studies published from 1980 to 2012 using the following data bases: MEDLINE, PsychINFO, Cochrane Database of Systematic Reviews, and Dissertation Abstracts International was conducted. The following terms were used in the search: pregnancy, overweight, obesity, smoking, parents, childhood, risk factors. Eighteen studies of maternal smoking during pregnancy and obesity conducted in Europe, Asia, North America, and South America met the inclusion criteria. A meta-analysis of these studies indicated that maternal smoking during pregnancy is a significant risk factor for overweight and obesity; mothers who smoke during pregnancy are at a greater risk for developing obesity or overweight; the quantity of cigarettes consumed by the mother during pregnancy influenced the odds of offspring overweight and/or obesity. In addition, the results from moderator analyses suggest that part of the heterogeneity discovered between the studies can be explained by the region of world that the study occurred in and the age of the child at the time of weight assessment.

Keywords: childhood obesity, overweight, smoking, parents, risk factors

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Authors: Maxime Vignon

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This study delves into the discourse surrounding Africatown ancestors’ will, through a rigorous discourse analysis, to reveal the intricate narratives shaping heritage and identity within this unique community. Situated near Mobile, Alabama, Africatown traces its origins to the Clotilda, the last known slave ship to bring captives from Africa to the United States. Through a meticulous examination of Africatown ancestors posthumous will, this analysis aims to uncover the spiritual linguistic nuances which will contribute to the preservation of Africatown's ancestral heritage and the construction of individual self and collective empowerment. This research will be grounded in Michel Foucault discourse. In its attempt to analyze the four core elements of discourse, this study explores the role of rituals and spiritual discourses within the will of Africatown ancestors. Additionally, it delves into the descendants’ public appearance scrutinizing the use of ancestral names and identities. Ultimately, this discourse analysis contributes to a nuanced understanding of how language and narrative from the ancestors would shape unity, a valuable insight into the complexities of identity formation and the enduring impact of the transatlantic slave trade on this resilient community.

Keywords: applied linguistics, culture, discourse analysis, identity, spirituality, transatlantic slave trade

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Y. Perera, M. Pathiraja

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Within the paradigm of 'Resilient Built-environments,' in order for architecture to be resilient, 'Resilience' should be identified as an essential component of the architect’s notion of creativity. In much simpler terms, 'Resilient Built-Environment' should necessarily be a by-product of the 'Resilient Architect.' The inherent influence of individualistic notions of creativity upon the practice had intensified the dichotomy between theory and practice unless the notion of 'Resilience' is identified as an integral component of the architect’s notion of creativity. Analysing the architectural position is an ideal way of understanding the architect’s notion of creativity, therefore, in exploring the notion of 'Resilience' and the 'Resilient Architect' within the Sri Lankan platform, the architectural positions of two renowned architects; Geoffrey Bawa and Valentine Gunasekara were explored and analysed. The architectural positions of both the architects asserted specific rules and methodologies adopted within the process of problem solving that had subsequently led to a traceable language / pattern within their architecture. The dominance of such rules within the practice could be detrimental to adaptation of theories / notions, such as 'Resilience' and the formation of the 'Resilient Architect', unless methodologies itself are flexible, robust, despite rigidity, or else the notion of 'Resilience' exist in the form of a methodological rule.

Keywords: architectural position, creativity, education, practice, resilience, theory

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

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

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

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Authors: Chie Urawa

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Cautionary statements or disclaimers in corporate annual reports need to be carefully designed because clear cautionary statements may protect a company in the case of legal disputes and may undermine positive impressions. This study compares the language of cautionary statements using two corpora, Sony’s cautionary statement corpus (S-corpus) and Panasonic’s cautionary statement corpus (P-corpus), illustrating the differences and similarities in relation to the use of meaningful cautionary statements and critically analyzing why practitioners use the way. The findings describe the distinct differences between the two companies in the presentation of the risk factors and the way how they make the statements. The word ability is used more for legal protection in S-corpus whereas the word possibility is used more to convey a better impression in P-corpus. The main similarities are identified in the use of lexical words and pronouns, and almost the same wordings for eight years. The findings show how they make the statements unique to the company in the presentation of risk factors, and the characteristics of specific genre of professional communication. Important implications of this study are that more comprehensive approach can be applied in other contexts, and be used by companies to reflect upon their cautionary statements.

Keywords: cautionary statements, corporate annual reports, corpus, risk factors

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Authors: Mingshu Liu, Laura Santamaria, Xavier Carmaniu Mainadé

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As one of the sectors most affected by the COVID-19 pandemic, tourism is facing challenges in revitalizing the industry. But at the same time, it would be a good opportunity to take advantage of digital communication as an effective tool for tourism promotion. Our proposal aims to verify the linguistic operations on online platforms in China. The research is carried out based on the theory of Eco-traductology put forward by Gengshen Hu, whose contribution focuses on the translator's adaptation to the ecosystem environment and the three elaborated parameters (linguistic, cultural and communicative). We also relate it to Even-Zohar's and Toury's theoretical postulates on the Polysystem to elaborate on interdisciplinary methodology. Such a methodology allows us to analyze personal treatments and phraseology in the target text. As for the corpus, we adopt the official Spanish-language website of Turismo de España as the source text and the postings on the two major social networks in China, Weibo and Wechat, in 2019. Through qualitative analysis, we conclude that, in the tourism advertising campaign on Chinese social networks, chengyu (Chinese phraseology) and honorific titles are used very frequently.

Keywords: digital communication, eco-traductology, polysystem theory, tourism advertising

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Authors: Zafar Ali

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The aim of this research is to highlight problems that are faced by women at the hands of men. Males in Pakistani society have power and use this power for the exploitation of women. Further, the purpose of the study is to make societies like Pakistan and especially the young generation, aware and enable them to resist such issues, and the role of discourse in this regard is to minimize its political and social repercussions. The study finds out different discursive techniques and manipulative language used in the short story to construct gender identity. The study also investigates socio-economic roles in the construction of gender identity. This study has been completed with the help of Critical Discourse Analysis (CDA) principles. CDA principles have been applied to the text of the selected short story Saleema from Daniyal Mueenuddin’s collection In Other Rooms, Other Wonders. Related passages, structures, expressions, and text are analyzed from the point of view of CDA, especially Norman Fairclough’s CDA approach. It was found from the analysis that women have no identity of their own in patriarchal societies like Pakistan. Further, it was found women are mistreated, and they have a very limited and defined role in Pakistan. They cannot go beyond the limit defined to them by men.

Keywords: gender issues, resourceful groups, CDA, exploitation

Procedia PDF Downloads 118

Authors: Victoria Zenotz

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For Fairclough (1989) critical literacy is a tool to enable readers and writers to build up meaning in discourse. More recently other authors (Leu et al., 2004) have included the new technology context in their definition of literacy. In their view being literate nowadays means to “successfully use and adapt to the rapidly changing information and communication technologies and contexts that continuously emerge in our world and influence all areas of our personal and professional lives.” (Leu et al., 2004: 1570). In this presentation the concept of critical literacy will be related to the creation of digital stories. In the first part of the presentation concepts such as literacy and critical literacy are examined. We consider that real social practices will help learners may improve their literacy level. Accordingly, we show some research, which was conducted at a secondary school in the north of Spain (2013-2014), to illustrate how the “writing” of digital stories may contribute to the development of critical literacy. The use of several instruments allowed the collection of data at the different stages of their creative process including watching and commenting models for digital stories, planning a storyboard, creating and selecting images, adding voices and background sounds, editing and sharing the final product. The results offer some valuable insights into learners’ literacy progress.

Keywords: literacy, computer assisted language learning, esl

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Authors: Aqleem Fatimah

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The purpose of study was to find out the impact of teachers’ gender on students’ score achievement. Focusing on primary level’s teachers & students, a survey research was conducted by using convenient sampling technique. All the students of grade four (1500) and fifty-six teachers (equally divided by gender) from the 50 randomly selected coeducational schools from Lahore were taken as sample. The academic performance was operationalized using a t-test on standardized achievement tests of the students in language, science mathematics and social studies. In addition, all those gender based characteristics of teachers that count a lot in classroom interactions (taking Multi-grade classes, classroom strategies, feedback strategies and evaluation method) that influence students’ achievement were also analyzed by using a questionnaire and an observation schedule. The results of the study showed better academic achievement of students (girl &boy) of female teachers comparatively to the students of male teachers. Therefore, as the female teachers’ number lacks in Pakistan, the study suggests policy makers to seek guidelines to induct more specialized and professionally competent female teachers because their induction will prove highly beneficial for the betterment of students’ score achievement.

Keywords: gender, teacher, competency, score achievement

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Authors: Sita Yiemkuntitavorn

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The purposes of this research were to: (1) Develop a distance training package on the teaching principles foundation english language in order to gain the teaching ability for secondary school english teachers in Bangkok and its vicinity (2) study the satisfaction of English teachers towards the quality of a distance training package. The samples for the efficiency testing consisted of 30 english teachers in Bangkok and its vicinity, obtained by purposive sampling. Research tools comprised (1) a distance learning package on the foundation of English writing for teachers. (2) The questionnaires asking the teachers on the quality of the distance training package, and (3) two parallel forms of an achievement test for pre-testing and post-testing. Statistics used were the E1/E2 index, mean and standard deviation. Research findings showed that, (1) the distance training package were efficient at 80.2/80.6 according to the set efficiency criterion of 80/80; (2) and the satisfaction of the teachers on the distance training package of the teaching principles of foundation english for secondary school english teachers in Bangkok and its vicinity was at “Satisfied” level.

Keywords: a distance training package, teaching principles of foundation english, secondary school, Bangkok and its vicinity

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Authors: Yemi Mahmud

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Semiotics is the study of signs and symbols as significations in a communication process. Television advertisement combines verbal and nonverbal signs to apprise consumers of products’ deliverables. This makes the language of television advertisement an important area of semiotic research. This paper focuses on nonverbal signs in television advertisement in purposively selected advertisements of two Nivea beauty products television advertisements: New Nivea Natural Fairness and Nivea Natural Fairness Lotion in Nigeria to investigate signs in meaning construction. It studies the interpretative realities of the signification of the nonverbal signs in television advertisements in Nigeria; examining signs in relation to the embedded and contextual meanings they are capable of exhuming vis-a-vis, viewers’ social and cultural senses extrapolated to draw inferences. The paper anchors its research on visual rhetorics and concludes that signs, as nonverbal elements in television advertisements, form part of the entire linguistic system of meaning transmission, noting that interpretations do not rely, solely, on the intrinsic properties of signs as signifiers, but on the imbued sociocultural elements that suggest meaning to viewers.

Keywords: Nivea, nonverbal signs, semiotics, signification, signifiers, television advertisement

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Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

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Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

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Authors: Eman Tadros

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Solution Focused Therapy sheds a positive light on a client’s problem(s) by instilling hope, focusing on the connection with the client, and describing the problem in a way to display change being possible. Solution focused therapists highlight clients’ positive strengths, reframe what clients say, do, or believe in a positive statement, action, or belief. Narrative Therapy focuses on the stories individuals tell about their past in which shape their current and future lives. Changing the language used aids clients in reevaluating their values and views of themselves, this then constructs a more positive way of thinking about their story. Both therapies are based on treating each client as an individual with a problem rather than that the individual is a problem and being able to give power back to the client. The purpose of these ideologies is to open a client to alternative understandings. This paper displays how clinicians can empower and identify their clients’ positive strengths and resiliency factors. Narrative and Solution-Focused Techniques will be integrated to instill positivity and empowerment in clients. Techniques such as deconstruction, collaboration, complimenting, miracle/exception/scaling questioning will be analyzed and modeled. Furthermore, bridging Solution Focused Therapy and Narrative Therapy gives a voice to unheard client(s).

Keywords: solution focused therapy, narrative therapy, empowerment, resilience

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Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

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Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

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Authors: Dennis Infante

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This paper examined the reflections of teachers on curriculum reforms, the implementation of the K-12 Basic Education Program in the Philippines. The results revealed that problems and concerns raised by teachers could be classified into curriculum materials and design; competence, readiness and motivation of the teachers; the learning environment, and support systems; readiness, competence and motivation of students; and other relevant factors. The best features of the K-12 curriculum reforms included (1) the components, curriculum materials; (2) the design, structure and delivery of the lessons; (3) the framework and theoretical approach; (3) the qualities of the teaching-learning activities; (4) and other relevant features. With the demanding task of implementing the new curriculum, the teachers expressed their needs which included (1) making the curriculum materials available to achieve the goals of the curriculum reforms; (2) enrichment of the learning environments; (3) motivating and encouraging the teachers to embrace change; (4) providing appropriate support systems; (5) re-tooling, and empowering teachers to implement the curriculum reforms; and (6) other relevant factors. The research concluded with a synthesis that provided a paradigm for implementing curriculum reforms which recognizes the needs of the teachers and the features of the new curriculum.

Keywords: curriculum reforms, K-12, teachers' reflections, implementing curriculum change

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Authors: Pimpisa Rattanadilok Na Phuket

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This research study aims to examine: 1) teaching competency of the native English-speaking teacher (NEST) 2) the English language learning achievement of Thai students, and 3) students’ perceptions toward their NEST. The population considered in this research was a group of 39 undergraduate students of the academic year 2013. The tools consisted of a questionnaire employed to measure the level of competency of NEST, pre-test and post-test used to examine the students’ achievement on English pronunciation, and an interview used to discover how participants perceived their NEST. The data was statistically analysed as percentage, mean, standard deviation and One-sample-t-test. In addition, the data collected by interviews was qualitatively analyzed. The research study found that the level of teaching competency of native speaker teachers of English was mostly low, the English pronunciation achievement of students had increased significantly at the level of 0.5, and the students’ perception toward NEST is combined. The students perceived their NEST as an English expertise, but they felt that NEST had not recognized students' linguistic difficulty and cultural differences.

Keywords: competency, native English-speaking teacher (NET), English teaching, learning achievement

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Authors: Jude Opara, Esemokumo Perewarebo Akpos

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This paper is on non-parametric linear regression over its parametric counterparts with large sample size. Data set on anthropometric measurement of primary school pupils was taken for the analysis. The study used 50 randomly selected pupils for the study. The set of data was subjected to normality test, and it was discovered that the residuals are not normally distributed (i.e. they do not follow a Gaussian distribution) for the commonly used least squares regression method for fitting an equation into a set of (x,y)-data points using the Anderson-Darling technique. The algorithms for the nonparametric Theil’s regression are stated in this paper as well as its parametric OLS counterpart. The use of a programming language software known as “R Development” was used in this paper. From the analysis, the result showed that there exists a significant relationship between the response and the explanatory variable for both the parametric and non-parametric regression. To know the efficiency of one method over the other, the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) are used, and it is discovered that the nonparametric regression performs better than its parametric regression counterparts due to their lower values in both the AIC and BIC. The study however recommends that future researchers should study a similar work by examining the presence of outliers in the data set, and probably expunge it if detected and re-analyze to compare results.

Keywords: Theil’s regression, Bayesian information criterion, Akaike information criterion, OLS

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Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

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Authors: Martina Kanciruk, Jac J. W. Andrews, Tyrone Donnon

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The purpose of this study was to determine the significance of history of obesity for the development of childhood overweight and/or obesity. Accordingly, a systematic literature review of English-language studies published from 1980 to 2012 using the following data bases: MEDLINE, PsychINFO, Cochrane Database of Systematic Reviews, and Dissertation Abstracts International was conducted. The following terms were used in the search: pregnancy, overweight, obesity, family history, parents, childhood, risk factors. Eleven studies of family history and obesity conducted in Europe, Asia, North America, and South America met the inclusion criteria. A meta-analysis of these studies indicated that family history of obesity is a significant risk factor of overweight and /or obesity in offspring; risk for offspring overweight and/or obesity associated with family history varies depending of the family members included in the analysis; and when family history of obesity is present, the offspring are at greater risk for developing obesity or overweight. In addition, the results from moderator analyses suggest that part of the heterogeneity discovered between the studies can be explained by the region of world that the study occurred in and the age of the child at the time of weight assessment.

Keywords: childhood obesity, overweight, family history, risk factors, meta-analysis

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Authors: Teh Kean Kheng, Low Soon Yee, Burra Venkata Durga Kumar

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In 2022, as the future world becomes increasingly computer-related, more individuals are attempting to study coding for themselves or in school. This is because they have discovered the value of learning code and the benefits it will provide them. But learning coding is difficult for most people. Even senior programmers that have experience for a decade year still need help from the online source while coding. The reason causing this is that coding is not like talking to other people; it has the specific syntax to make the computer understand what we want it to do, so coding will be hard for normal people if they don’t have contact in this field before. Coding is hard. If a user wants to learn bash code with bash prompt, it will be harder because if we look at the bash prompt, we will find that it is just an empty box and waiting for a user to tell the computer what we want to do, if we don’t refer to the internet, we will not know what we can do with the prompt. From here, we can conclude that the bash prompt is not user-friendly for new users who are learning bash code. Our goal in writing this paper is to give an idea to implement a user-friendly Bash prompt in Ubuntu OS using Artificial Intelligent (AI) to lower the threshold of learning in Bash code, to make the user use their own words and concept to write and learn Bash code.

Keywords: user-friendly, bash code, artificial intelligence, threshold, semantic similarity, lexical similarity

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Authors: Imen Ben Abda

Abstract:

Languages have been classified into different rhythm classes. 'Stress-timed' languages are exemplified by English, 'syllable-timed' languages by French and 'mora-timed' languages by Japanese. However, to our best knowledge, acoustic studies have not been unanimous in strictly establishing which rhythm category a given language belongs to and failed to show empirical evidence for isochrony. Perception seems to be a good approach to categorize languages into different rhythm classes. This study, within the scope of experimental phonetics, includes an account of different perceptual experiments using cues from natural and inverted speech, as well as pitch extracted from speech data. It is an attempt to categorize speech rhythm over a large set of Arabic (Tunisian, Algerian, Lebanese and Moroccan) and English dialects (Welsh, Irish, Scottish and Texan) as well as other languages such as Chinese, Japanese, French, and German. Listeners managed to classify the different languages and dialects into different rhythm classes using suprasegmental cues mainly rhythm and pitch (F0). They also perceived rhythmic differences even among languages and dialects belonging to the same rhythm class. This may show that there are different subclasses within very broad rhythmic typologies.

Keywords: F0, inverted speech, mora-timing, rhythm variation, stress-timing, syllable-timing

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Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

Abstract:

Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

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Authors: Rafat Alwazna

Abstract:

Technical lexicon is witnessing a large upsurge in the use of new terminologies whose emergence is an inevitable result of the spread of high-quality technology, the existence of scientific paradigms and the fast growth of research in different disciplines. One important subfield of terminology is legal terminology, which forms a crucial part of legal studies, and whose translation from one legal system into another is deemed a formidable and arduous task that needs to be properly performed by legal translators. Indeed, the issue of untranslatability of legal terms, particularly between originally unrelated languages, like legal Arabic and legal English, has long been a real challenge in legal translation. It stems from the conceptual incongruency between legal terms of different legal languages, which are derived from different legal cultures and legal systems. Such conceptual asymmetry is owing to the fact that law has no universal reference and that legal language is what determines the degree of difference in conceptual correspondence. The present paper argues that although conceptual asymmetry, which is the main reason for the issue of untranslatability of legal terms, cannot be denied in legal translation, there exist certain translation techniques which, if properly adopted, would resolve the issue of untranslatability of legal terms and therefore achieve acceptable legal translation. Hence, the question of untranslatability of legal terms should no longer exist within the context of legal translation.

Keywords: conceptual incongruency, Legal terms, translation techniques, untranslatability

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Authors: George Zhou, Yunchan Chen, Candace Chien

Abstract:

Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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