Search results for: language learning strategies

Authors: N. G. Teik Hiang, Fathyah Hashim

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This is a case of how strategic management techniques can be used to help resolving problems faced by an ageing Small and Medium Enterprise (SME). Strategic way of resolving problems had been proven to be possible in this case despite general thought that strategic management is useful mostly for large corporations. Small and Medium Enterprises (SMEs) can also use strategic management in managing their business and determining their future cause of action and strategies in order to survive in this ever competent world. Strategic orientation is the key to survival and development of small and medium enterprises. In order to adapt to the fierce market competition, ageing SMEs should improve competitiveness and operational efficiency. They must therefore establish a sense of strategic management to improve the strategic management skills, combined with its own unique characteristics, and work out practical strategies to develop core competitiveness of enterprises in the fierce market competition in order to be sustainable. In this case, internal strengths and weaknesses of an SME had been identified. Strategic internal factors and external factors had been classified and further utilized to formulate potential strategies to encounter various problems faced by the SME. These strategies had been further match to take advantages of the opportunities and to overcome the weaknesses and minimize the threats it is facing. Tan, a consultant who was given the opportunity to formulate a plan for the business started with the environmental scanning (internal and external environmental analysis), assessing strengths and weaknesses for the company, strategies generation, analysis and evaluation. He had numerous discussions with the owner of the business and the senior management in order to match the key internal and external factors to formulate alternative strategies for solving the problems that the company facing. Some of the recommendations or solutions are generated from the inspiration of the owner of the business who is a very enterprising and experience businessman.

Keywords: strategic orientation, strategic management, SME, core competitiveness, sustainable

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Authors: Laura Zizka, Gaby Probst

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The Covid-19 pandemic has affected the way Higher Education Institutions (HEIs) have given their courses. From emergency remote where all students and faculty were immediately confined to home teaching and learning, the continuing evolving sanitary situation obliged HEIs to adopt other methods of teaching and learning from blended courses that included both synchronous and asynchronous courses and activities to hy-flex models where some students were on campus while others followed the course simultaneously online. Each semester brought new challenges for HEIs and, subsequently, additional emotional reactions. This paper investigates the affective side of teaching and learning in various online modalities and its toll on students and faculty members over the past three semesters. The findings confirm that students and faculty who have more self-efficacy, flexibility, and resilience reported positive emotions and embraced the opportunities that these past semesters have offered. While HEIs have begun a new semester in an attempt to return to ‘normal’ face-to-face courses, this paper posits that there are lessons to be learned from these past three semesters. The opportunities that arose from the challenge of the pandemic should be considered when moving forward by focusing on a greater emphasis on the affective aspect of teaching and learning in HEIs worldwide.

Keywords: effective teaching and learning, higher education, engagement, interaction, motivation

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Authors: Dries Dulsster

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This research we want to discuss the implications of the concept of ‘lalangue’ and illustrate its importance for lacanian psychoanalysis and its clinical practice. We will look at this concept through an in depth reading of Lacan’s later seminars, his lectures at the North-American universities and his study on James Joyce. We will illustrate the importance of this concept with a case study from a clinical practice. We will argue that the introduction of ‘lalangue’ has several theoretical and clinical implications that will radically change Lacans teachings. We will illustrate the distinction between language and lalangue. Language serves communication, but this is not the case with lalangue. We will claim that there is jouissance in language and will approach this by introducing the concept of ‘lalangue’. We will ask ourselves what the effect will be of this distinction and how we can use this in clinical practice. The concept of ‘lalangue’ will introduce a new way of thinking about the unconscious. It will force us to no longer view the unconscious as Symbolic, but as Imaginary or Real. Another implication will be the approach on the symptom, no longer approaching it as a formation of the unconscious. It will be renamed as ‘sinthome’, as function of the real. Last of all it will force us to rethink the lacanian interpretation and how we direct the treatment. The implications on a clinical level will be how we think about the lacanian interpretation and the direction of the treatment. We will no longer focus on language and meaning, but focus on jouissance and the ways in which the subject deals with this. We will illustrate this importance with a clinical case study. To summarize, the concept of lalangue forces us to radically rethink lacanian psychoanalysis, with major implications on a theoretical and clinical level. It introduces new concepts such as the real unconscious and the sinthome. It will also make us rethink the way we work as lacanian psychoanalysts.

Keywords: Lacan's later teaching, language, Lalangue, the unconscious

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Authors: Wen-Chao Tang, Tang-Yi Liu, Ming Gao, Gang Xu, Hua-Yuan Yang

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This study developed a method for teaching acupuncture manipulation in small groups optimized with the theory of motor learning. Sixty acupuncture students and their teacher participated in our research. Motion videos were recorded of their manipulations using the lifting-thrusting method. These videos were analyzed using Simi Motion software to acquire the movement parameters of the thumb tip. The parameter velocity curves along Y axis was used to generate small teaching groups clustered by a self-organized map (SOM) and K-means. Ten groups were generated. All the targeted instruction based on the comparative results groups as well as the videos of teacher and student was provided to the members of each group respectively. According to the theory and research of motor learning, the factors or technologies such as video instruction, observational learning, external focus and summary feedback were integrated into this teaching method. Such efforts were desired to improve and enhance the effectiveness of current acupuncture teaching methods in limited classroom teaching time and extracurricular training.

Keywords: acupuncture, group teaching, video instruction, observational learning, external focus, summary feedback

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Authors: Estevan B. Costa, Armando M. Toda, Marcell A. A. Mesquita, Jacques D. Brancher

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The advances in technology in the last five years allowed an improvement in the educational area, as the increasing in the development of educational software. One of the techniques that emerged in this lapse is called Gamification, which is the utilization of video game mechanics outside its bounds. Recent studies involving this technique provided positive results in the application of these concepts in many areas as marketing, health and education. In the last area there are studies that cover from elementary to higher education, with many variations to adequate to the educators methodologies. Among higher education, focusing on IT courses, data structures are an important subject taught in many of these courses, as they are base for many systems. Based on the exposed this paper exposes the development of an interactive web learning environment, called DSLEP (Data Structure Learning Platform), to aid students in higher education IT courses. The system includes basic concepts seen on this subject such as stacks, queues, lists, arrays, trees and was implemented to ease the insertion of new structures. It was also implemented with gamification concepts, such as points, levels, and leader boards, to engage students in the search for knowledge and stimulate self-learning.

Keywords: gamification, Interactive learning environment, data structures, e-learning

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Authors: Yali Liu

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The ethnographic research involved a multi-sited field trip study in China to compile in-depth data from Chinese multilingual academics of Korean, Japanese, and Russian. It aimed to create a culturally-informed portrait of their values and perceptions regarding their choice of language for academic publishing. Extended and lengthy fieldwork, or known as ‘deep hanging out’, enabled the author to gain a comprehensive understanding of the research context at the macro-level and the participants’ experiences at the micro-level. This research involved multiple fieldwork sites, which the author selected in acknowledgment of the diversity in China’s regions with respect to their geopolitical context, socio-economic development, cultural traditions, and administrative status. The 14 weeks of data collection took the author over-land to five regions in northern China: Hebei province, Tianjin, Jilin province, Gansu province, and Xinjiang. Responding to the fieldwork dynamics, the author positioned herself at different degrees of insiderness and outsiderness. This occurred at three levels: the regional level, the individual level, and the within-individual level. To enhance the ability to reflect on the authors’ researcher subjectivity, the author explored her understanding of the five ‘I’s, derived from the authors’ natural attributes. This helped the author to monitor her subjectivity, particularly during critical decision-making. The methodological challenges the author navigated were related to interviewing elites; this involved the initial approach, establishing a relationship, and negotiating the unequal power relationship during our contact. The author developed a number of strategies to strengthen her authority, and to gain the confidence of her envisaged participants and secure their collaboration, and the author negotiated a form of reciprocity that reflected their needs and expectations. The current ethnographic research has both theoretical and practical significance. It contributes to the methodological development regarding multi-sited ethnographic research. The messiness and strategies about positioning and interviewing elites will provide practical lessons for researchers who conduct ethnographic research, especially from power-‘less’ positions.

Keywords: multi-sited ethnographic research, elite interview, multilingual China, subjectivity, reciprocity

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Authors: Totok Suhardijanto, Ninie Susanti Tedjowasono

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This paper discusses the relationship between the distribution of Ancient Malay inscriptions and Spice Trade Route, especially in the relation with material cultures that accompany them, to understand how Malay could spread out around the archipelago beyond its original native-speakers’ region. The archipelago was known as the Spice Islands from the very beginning of the first century due to mace, cloves, and nutmeg that were originally exclusively found there. According to the Indian record, since the 2nd century, there has been a contact established between Indian and Indonesian people. A Chinese document from 3rd Century has mentioned Wangka (now widely known as Bangka) an island near Sumatra where some Chinese expeditions had visited. All of these records supported the existence of a maritime trade system and route between the archipelago and other countries during the first millennium. This paper will discuss first the Ancient Malay inscription spread around the archipelago from the perspectives of language variation and writing system style. Analyzing language variations of inscriptions certainly is not as easy as studying current spoken language variations in modern sociolinguistics. A huge amount of data is available for such kind of studies. On the contrary, in language variation research with inscription texts as an object, data is insufficient. Other resources will be needed to support the linguistic analysis. For this reason, this research made use of epigraphical evidence in the surrounding areas of the inscriptions to explain the variation of language and writing style. The research next expands the analysis to figure out the relationship between language variation and inscriptions distribution to the Spice Trade Route that spreads from the Molucca Sea to Mediterranian Sea. Data in this research consists of six different inscriptions: Kedukan Bukit, Koto Kapur, Dapunta Salendra, Sang Hyang Wintang, Ligor, and Laguna from the 7th-9th Century and found in Sumatra, Jawa, and the Philippines. In addition, as a comparative resource, this research also used Hikayat Tanjung Tanah, the first-founded Ancient Malay manuscript. In language analysis, we conduct a sociolinguistic method to explore the language variation and writing style of the inscriptions. For dealing with archaeological data, we conducted a hermeneutic method to analyze the possible meaning and social uses of the data. Language variations and writing system style in this research can be classified into two main groups. The language, epigraphical, and archaeological evidence explain that Ancient Malay had been widely used in the Eastern area of Spice Trade Route because it played an important role in the region as a lingua franca between people from different ethnic groups with different languages.

Keywords: Ancient Malay, Spice trade route, language variation, writing system variation

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Authors: Jenjira Chinnawong, Phusit Phukamchanoad

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The objective of this study is to explore the guidelines for the development of community classroom for research and academic services in Ranong province. By interviewing leaders involved in the development of learning resources, research, and community services, it was found that the leaders' perceptions in the development of learning resources, research, and community services in Ranong, was at the highest level. They perceived at every step on policies of community classroom implementation, research, and community services in Ranong. Leaders' perceptions were at the moderate level in terms of analysis of problems related to procedures of community classroom management, research and community services in Ranong especially in the planning and implementation of the examination, improvement, and development of learning sources to be in good condition and ready to serve the visitors. Their participation in the development of community classroom, research, and community services in Ranong was at a high level, particularly in the participation in monitoring and evaluation of the development of learning resources as well as in reporting on the result of the development of learning resources. The most important thing in the development of community classroom, research and community services in Ranong is the necessity to integrate the three principles of knowledge building in teaching, research and academic services in order to create the identity of the local and community classroom for those who are interested to visit to learn more about the useful knowledge. As a result, community classroom, research, and community services were well-known both inside and outside the university.

Keywords: community classroom, learning resources, development, participation

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Authors: Michael McMahon

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The use of media (video/animation/graphics) has long been used by athletes, coaches, and sports scientists to analyse and improve performance in technical skills and team tactics. Sports educators are increasingly open to the use of technology to support coach and learner development. However, an overreliance is a concern., This paper is part of a larger Ph.D. study looking into these new challenges for Sports Educators. Most notably, how to exploit the deep-learning potential of Digital Media among expert learners, how to instruct sports educators to create effective media content that fosters deep learning, and finally, how to make the process manageable and cost-effective. Central to the study is Richard Mayers Cognitive Theory of Multimedia Learning. Mayers Multimedia Learning Theory proposes twelve principles that shape the design and organization of multimedia presentations to improve learning and reduce cognitive load. For example, the Prior Knowledge principle suggests and highlights different learning outcomes for Novice and Non-Novice learners, respectively. Little research, however, is available to support this principle in modified domains (e.g., sports tactics and strategy). As a foundation for further research, this paper compares and contrasts a range of contemporary multimedia sports coaching content and assesses how they perform as learning tools for Strategic and Tactical Play Acquisition among elite sports practitioners. The stress tests applied are guided by Mayers's twelve Multimedia Learning Principles. The focus is on the elite athletes and whether current coaching digital media content does foster improved sports learning among this cohort. The sport of Gaelic Football was selected as it has high strategic and tactical play content, a wide range of Practitioner skill levels (Novice to Elite), and also a significant volume of Multimedia Coaching Content available for analysis. It is hoped the resulting data will help identify and inform the future instructional content design and delivery for Sports Practitioners and help promote best design practices optimal for different levels of expertise.

Keywords: multimedia learning, e-learning, design for learning, ICT

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Authors: Rania Kassir, Christophe Dos Santos, Halim Abboud, Olivier Godefroy

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The ability to communicate in at least two different languages is shared by a growing number of humans. Recently, many researchers have been studying the elderly bilingual population around the world in neuroscience, and yet, until today there’s no accurate nor universal measure or methodology used to examine bilingualism across these studies which constitute a real challenge for results generalization. This study contributes to the quest of a multidimensional bilingualism index and language proficiency literature by investigating a new bilingualism index from a reliable subjective questionnaire the Language Experience and Proficiency Questionnaire (LEAP-Q), multi-linguistic tests, and a diverse bilingual population all featured in one analysis and one index. One hundred Lebanese subjects aged between 55 and 92 years old divided into three different bilingualism subgroups (Arabic prominent, balanced, and French prominent) were recruited and underwent the LEAP-Q with a set of linguistic and cognitive tests. The analysis of the collected data led to the creation of a robust bilingualism index from speaking and oral understanding scores that underline specifically bilingualism subtype according to cutoffs scored. The practice implications of this index, particularly its use within bilingual populations, are addressed in the conclusion of this work.

Keywords: bilingualism, language dominance, bilingualism index, balanced bilingualism, Arabic first language, Lebanese, Arabic-French bilingualism

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Alex Arghya Adhikari

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Gaming and esports industry is one of the biggest and fastest growing industries in the world. Globally people have started investing more in this industry since now people believe just like traditional sports, esports can also sustain their future. Last year in the month of December, the Indian government also recognised esports as an official sport but there has not been any positive initiative by the government in encouraging people to enter esports. This is a problem which cannot be overlooked since we are already in the digital age and gaming and esports is the future industry. There is a need for multiple effective marketing strategies by the game publishers to stabilize the esports in the country. Purpose: To observe the marketing-communication strategies that are implemented by Riot Games’ Valorant and how those strategies influence the consumer behavior and the esports of the game. Methodology: Activities over the internet related to the game like livestreams, discord chats, Instagram posts and YouTube videos over a period of two months have been collected through the Digital Ethnography. To support and validate the observations of the data collected, in-depth online interviews have been conducted which includes streamers, journalists, LAN experienced players and casual players. Findings: The game publisher through its Dynamic Competitive Gaming Experience and Community-Engaged Ecosystem succeeded in making the game a Recreational activity and a Community which goes beyond the In-game experiences which helped in understanding the impact of audience engagement on esports and the loopholes and setbacks of Indian esports. Conclusion: The study provides a comprehensive analysis of how Valorant's successful marketing and community engagement strategies have contributed to its global popularity and competitive esports environment. It highlights the various strategies employed by Riot Games to keep players engaged and connected, and also the challenges in the Indian esports landscape which differentiates it from the global competition.

Keywords: esports, valorant, marketing, consumer behaviour

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Authors: Mamatha Hosapatna, Anne D. Souza, Antony Sylvan Dsouza, Vrinda Hari Ankolekar

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Our study intends to know the effect of the overall teaching program of Anatomy on a students learning. The advancement of various teaching methodologies in the present era has led to progressive changes in education. A student should be able to correlate well between the theory and practical knowledge attained even in the early years of their education in medicine and should be able to implement the same in patient care. The present study therefore aims to assess the impact the current anatomy teaching program has on a students learning and to what extent is it successful in making the learning program effective. Specific objectives of our study to assess the impact of overall teaching program of Anatomy in a students’ learning. Description of process proposed: A questionnaire will be constructed and the students will be asked to put forth their views regarding the Anatomy teaching program and its method of assessment. Suggestions, if any will also be encouraged to be put forth. Type of study is cross sectional observations. Target population is the first year MBBS students and sample size is 250. Assessment plan is to obtaining students responses using questionnaire. Calculating percentages of the responses obtained. Tabulation of the results will be done.

Keywords: anatomy, observational study questionnaire, observational study, M.B.B.S students

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Authors: Brittany Joi B. Kirsch

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Textbooks carry a crucial role in imparting ideologies that stimulate inclusivity and social diversity. In the Philippines, a law on inclusive education (IE) for differently-abled learners has recently been signed in order to ensure their rights to quality and IE are protected and upheld (Republic Act No. 11650, 2022). With the presence of ableism in textbooks, the promotion of IE may be challenged. A considerable amount of research has been done on disability representation and ableism in foreign countries; however, none, to the extent of the researcher’s knowledge, has been conducted on ableist ideologies in primary education English language textbooks in the Philippines. Hence, this paper aims to investigate the negotiation of ableist ideologies in primary education English language textbooks in the Philippines. Utilizing Fairclough’s (1995) three-dimensional model of critical discourse analysis (CDA) as the framework, six prescribed primary education English language textbooks from different grade levels were analyzed to examine instances of ableism in the texts. To further support the analysis of the study, supplemental data were gathered from the accounts of six public elementary school English language teachers. Findings reveal that the textbooks contain ableist ideologies with a limited representation of differently-abled people; by disclosing them as (1) invisible, (2) equipped with negative abilities, and (3) plagued with delicate health. By identifying ableist ideologies in textbooks, educational institutions and publishers may benefit in assessing and reforming instructional materials to resolve the presence of such ideologies, thereby abiding by the country’s law on IE and strengthening its overall implementation.

Keywords: textbooks, ideologies, inclusive education, critical discourse analysis, ableism

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Ching-Hsu Huang, Shang-Huan Wu

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In recent years, environmental awareness has increased, environmental issues caused by meat-eating have been extended to promote reducing food surplus and waste advocates. We lose more than 3 million tons of food on average on a daily basis. Private households represent the largest food-waste faction. The main purpose of this study is to design and develop household dishes by using edible food surplus. The questionnaires were conducted to find the majority of food surplus from households, including carrot peel, pumpkin, fish skin, and soy dregs—this study designed and developed the household dishes by using the leftovers. We briefly discuss the contributions of the dishes. Mapping the household dishes deepens the promotion of household food waste prevention strategies. This study also linked the results with a set of policy, education, and restaurant business options

Keywords: food waste, food surplus, household dishes design, food waste prevention strategies

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Authors: Ayşe Yurdakul, Eckehard Schnieder

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Because of the growing multidisciplinarity and multilinguality, communication problems in different technical fields grows more and more. Therefore, each technical field has its own specific language, terminology which is characterised by the different definition of terms. In addition to definition problems, there are also relation problems between terms. Among these problems of relation, there are the synonymy, antonymy, hypernymy/hyponymy, ambiguity, risk of confusion, and translation problems etc. Thus, the terminology management system iglos of the Institute for Traffic Safety and Automation Engineering of the Technische Universität Braunschweig has the target to solve these problems by a methodological standardisation of term definitions with the aid of the iglos sign model and iglos relation types. The focus of this paper should be on solving definition and relation problems between terms in English navigation terminology.

Keywords: iglos, iglos sign model, methodological resolutions, navigation terminology, common language, technical language, positioning, definition problems, relation problems

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Authors: Yingying Ding

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This study presents a methodology of specialized translation with the objective of helping teachers to improve the strategies in teaching translation. In order to allow students to acquire skills to translate specialized texts, they need to become familiar with the semantic and syntactic features of source texts and target texts. The aim of our study is to use a corpus-based approach in the teaching of specialized translation between Chinese and Italian. This study proposes to construct a specialized Chinese - Italian comparable corpus that consists of 50 economic contracts from the domain of food. With the help of AntConc, we propose to compile a comparable corpus in for translation teaching purposes. This paper attempts to provide insight into how teachers could benefit from comparable corpus in the teaching of specialized translation from Italian into Chinese and through some examples of passive sentences how students could learn to apply different strategies for translating appropriately the voice.

Keywords: contrastive studies, specialised translation, corpus-based approach, teaching

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Authors: Francisca Margarita Ocran

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Underwear, and more particularly bras and panties, are defined as intimate clothing. Strictly speaking, they enhance the place of women in the public or private satchel. Therefore, women's lingerie is a complex garment with a high involvement profile, motivating consumers to buy it not only by its functional utility but also by the multisensory experience it provides them. Customer behavior models are generally based on customer data mining, and each model is designed to answer questions at a specific time. Predicting the customer experience is uncertain and difficult. Thus, knowledge of consumers' tastes in lingerie deserves to be treated as an experiential product, where the dimensions of the experience motivating consumers to buy a lingerie product and to remain faithful to it must be analyzed in detail by the manufacturers and retailers to engage and retain consumers, which is why this research aims to identify the variables that push consumers to choose their lingerie product, based on an in-depth analysis of the types of fabrics used to make lingerie. The data used in this study comes from online purchases. Machine learning approach with the use of Python programming language and Pycaret gives us a precision of 86.34%, 85.98%, and 84.55% for the three algorithms to use concerning the preference of a buyer in front of a range of lingerie. Gradient Boosting, random forest, and K Neighbors were used in this study; they are very promising and rich in the classification of preference in the textile industry.

Keywords: consumer behavior, data mining, lingerie, machine learning, preference

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Authors: Nguyen Quynh Trang, Nguyễn Thị Hông Nhung

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The study aimed to identify the effectiveness of using the mind map technique to enhance students’ medical vocabulary retention among a group of students at a higher education institution - Thai Nguyen University of Medicine and Pharmacy during the first semester of the school year 2022-2023. The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. Almost teachers and students showed high preferences for the implementation of the mind map technique in language teaching and learning. Furthermore, results from the pre-and-post tests between the experimental group and control one pointed out that this technique brought back positive academic performance in teaching and learning English. The research findings revealed that there should be more supportive policies to evoke the use of the mind map technique in a pedagogical context. Aim of the Study: The purpose of this research was to investigate whether using mind mapping can help students to enhance nursing students’ medical vocabulary retention and to assess the students’ attitudes toward using mind mapping as a tool to improve their vocabulary. The methodology of the study: The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. The contribution of the study: The research contributed to the innovation of teaching vocabulary methods for English teachers at a higher education institution. Moreover, the research helped the English teachers and the administrators at a university evoke and maintain the motivation of students not only in English classes but also in other subjects. The findings of this research were beneficial to teachers, students, and researchers interested in using mind mapping to teach and learn English vocabulary. The research explored and proved the effectiveness of applying mind mapping in teaching and learning English vocabulary. Therefore, teaching and learning activities were conducted more and more effectively and helped students overcome challenges in remembering vocabulary and creating motivation to learn English vocabulary.

Keywords: medical vocabulary retention, mind map technique, nursing students, medical vocabulary

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Authors: Taghreed Alghamdi, Wendy Hall, David Millard

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Massive Open Online Courses (MOOCs) have recently gained widespread interest in the academic world, starting a wide range of discussion of a number of issues. One of these issues, using MOOCs in teaching and learning in the higher education by integrating MOOCs’ contents with traditional face-to-face activities in blended learning format, is called blended MOOCs (bMOOCs) and is intended not to replace traditional learning but to enhance students learning. Most research on MOOCs has focused on students’ perception and institutional threats whereas there is a lack of published research on academics’ experiences and practices. Thus, the first aim of the study is to develop a classification of blended MOOCs models by conducting a systematic literature review, classifying 19 different case studies, and identifying the broad types of bMOOCs models namely: Supplementary Model and Integrated Model. Thus, the analyses phase will emphasize on these different types of bMOOCs models in terms of adopting MOOCs by lecturers. The second aim of the study is to improve the understanding of lecturers’ acceptance of bMOOCs by investigate the factors that influence academics’ acceptance of using MOOCs in traditional learning by distributing an online survey to lecturers who participate in MOOCs platforms. These factors can help institutions to encourage their lecturers to integrate MOOCs with their traditional courses in universities.

Keywords: acceptance, blended learning, blended MOOCs, higher education, lecturers, MOOCs, professors

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Authors: S. Alfalah, J. Falah, T. Alfalah, M. Elfalah, O. Falah

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The field of education is an ever-evolving area constantly enriched by newly discovered techniques provided by active research in all areas of technologies. The recent years have witnessed the introduction of a number of promising technologies and applications to enhance the teaching and learning experience. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing education in many fields. VR creates an artificial environment, using computer hardware and software, which is similar to the real world. This simulation provides a solution to improve the delivery of materials, which facilitates the teaching process by providing a useful aid to instructors, and enhances the learning experience by providing a beneficial learning aid. In order to assure future utilization of such systems, students’ perceptions were examined toward utilizing VR as an educational tool in the Faculty of Information Technology (IT) in The University of Jordan. A questionnaire was administered to IT undergraduates investigating students’ opinions about the potential opportunities that VR technology could offer and its implications as learning and teaching aid. The results confirmed the end users’ willingness to adopt VR systems as a learning aid. The result of this research forms a solid base for investing in a VR system for IT education.

Keywords: information, technology, virtual reality, education

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: S. Aberkane, N. Djabali, S. Fafi, A. Baghezza

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Chronic illnesses affect many Algerians. It is possible to investigate the impact of illness representations and coping on quality of life and whether illness representations are indirectly associated with quality of life through their influence on coping. This study aims at investigating the relationship between illness perception, coping strategies and quality of life with chronic illness. Illness perceptions are indirectly associated with the quality of life through their influence on coping mediation. A sample of 316 participants with chronic illness living in the region of Batna, Algeria, has been adopted in this study. A correlation statistical analysis is used to determine the relationship between illness perception, coping strategies, and quality of life. Multiple regression analysis was employed to highlight the predictive ability of the dimensions of illness perception and coping strategies on the dependent variables of quality of life, where mediation analysis is considered in the exploration of the indirect effect significance of the mediator. This study provides insights about the relationship between illness perception, coping strategies and quality of life in the considered sample (r = 0.39, p < 0.01). Therefore, it proves that there is an effect of illness identity perception, external and medical attributions related to emotional role, physical functioning, and mental health perceived, and these were fully mediated by the asking for assistance (c’= 0.04, p < 0.05), the guarding (c’= 0.00, p < 0.05), and the task persistence strategy (c’= 0.05, p < 0.05). The findings imply partial support for the common-sense model of illness representations in a chronic illness population. Directions for future research are highlighted, as well as implications for psychotherapeutic interventions which target unhelpful beliefs and maladaptive coping strategies (e.g., cognitive behavioral therapy).

Keywords: chronic illness, coping, illness perception, quality of life, self- regulation model

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Authors: Oliwia Bator

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The subject of this description is phraseologisms with the component “spices and food additives component" in Polish and Russian. The purpose of the study is to analyze the phraseologisms from the point of view of lexis and semantics. The material for analysis was extracted from Phraseological Dictionaries of Polish and Russian. The phraseologisms were considered from the lexical point of view, taking into account the name of the " spices and food additives" component, which forms them. From the semantic point of view, 12 semantic groups of phraseologisms were separated in Polish, while 9 semantic groups were separated in Russian. In addition is shown their functioning in the contexts of contemporary Polish and Russian. The contexts were taken from the National Corpus of the Polish Language and the National Corpus of the Russian Language.

Keywords: phraseology, language, slavic studies, linguistics

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Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: Bryony Pound

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This study investigated how views of green or urban space affect learning performance. It provides evidence of the value of visual access to greenspace in work and learning environments, and builds on the extensive research into the cognitive and learning-related benefits of access to green and natural spaces, particularly in learning environments. It demonstrates that benefits of visual access to natural spaces whilst learning can produce statistically significant faster responses than those facing urban views after only 5 minutes. The primary hypothesis of this research was that a greenspace view would improve short-term learning. Participants were randomly assigned to either a view of parkland or of urban buildings from the same room. They completed a psychological test of two stages. The first stage consisted of a presentation of words from eight different categories (four manmade and four natural). Following this a 2.5 minute break was given; participants were not prompted to look out of the window, but all were observed doing so. The second stage of the test involved a word recognition/false memory test of three types. Type 1 was presented words from each category; Type 2 was non-presented words from those same categories; and Type 3 was non-presented words from different categories. Participants were asked to respond with whether they thought they had seen the words before or not. Accuracy of responses and reaction times were recorded. The key finding was that reaction times for Type 2 words (highest difficulty) were significantly different between urban and green view conditions. Those with an urban view had slower reaction times for these words, so a view of greenspace resulted in better information retrieval for word and false memory recognition. Importantly, this difference was found after only 5 minutes of exposure to either view, during winter, and with a sample size of only 26. Greenspace views improve performance in a learning task. This provides a case for better visual access to greenspace in work and learning environments.

Keywords: benefits, greenspace, learning, restoration

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Authors: Nahla Khatib

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This study investigated several learning difficulties that affected the classroom learning experience of preservice students who are studying general science and methods of teaching science students at Faculty of Educational Studies at the Arab Open University (AOU) in Amman, Jordan. The focus questions for this study were to find answers for the following: 1. What are the main areas of learning difficulty among preservice students towards science education? 2. What are the main aspects of reducing obstacles towards success in science education? To achieve this goal, the researcher prepared a questionnaire which included 30 items to point out the learning difficulties among preservice students towards science education. The questionnaire was distributed among students enrolled in the general science courses 1&2 and methods of teaching science courses at the beginning of the spring semester of year (2013-2014). After collecting the filled questionnaire a descriptive statistical analysis was carried out (means and standard deviation) for the items of the questionnaire. After analyzing the data statistically our findings showed that student control–factors as well as course controlled factor, factors related to the nature of science, and factors related to the role of instructor affected student success toward science education. The study was concluded with a number of recommendations.

Keywords: nature of science, preservice teachers, science education, learning difficulties

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