Search results for: academic learning integration

Authors: Jessica Da Silva

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This paper examines France as a microcosm of the rise of right-wing populism in the broader European context. The attack on the Charlie Hebdo newspaper is arguably, a reaction to the aggressive European secularism spreading throughout Europe that sees its true enemy in the growth of extremist and violent interpretations of Islam. With each terrorist attack, the popularity of anti-immigrant policies and ideologies increases. What ultimately drives movements like the French National Front are the concepts of monoculture and ethnic identity. This paper analyses the character of right-wing populist parties using the National Front as a case study. Such parties generate anxiety and resentment by fomenting an irrational fear of the ‘other’. In this way, populists promote their identity on the basis of xenophobia, Islamophobia, and practices of social exclusion against targeted out-groups. They position immigrants and foreigners as ‘others’, claiming they are a threat to native cultures and a source of social and economic strife. Ultimately, right-wing populism exerts a negative influence over the democratic framework in Europe and opposes the European Union’s integration project. Right-wing populism attacks this supranational model because of its alleged inefficiency and departure from what it considers to be 'authentic' European traditions and citizenship. In this context, understanding the rise of radical right-wing populist parties is extremely important for the future of Europe, democracy and multiculturalism.

Keywords: cultural identity, Europeanization, front national, immigration, integration, Islamophobia, multiculturalism, nationalism, right-wing populist parties, xenophobia

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Authors: Lynn Machin

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Using the lens of a theoretical framework relating to learning to learn the intention of the case study was to explore how transferable the teaching and learning skills of a newly qualified teacher (post-compulsory education) were when used in an overseas, unfamiliar and challenging post-compulsory educational environment. Particularly, the research sought to explore how this newly qualified teacher made use of the skills developed during their teacher training and to ascertain if, and what, other skills were necessary in order for them to have a positive influence on their learners and for them to be able to thrive within a different country and learning milieu. This case study looks at the experience of a trainee teacher who recently qualified in the UK to teach in post compulsory education (i.e. post 16 education). Rather than gaining employment in a UK based academy or college of further education this newly qualified teacher secured her first employment as a teacher in a province in China. Moreover, the newly qualified teacher had limited travel experience and had never travelled to Asia. She was one of the quieter and more reserved members on the one year teacher training course and was the least likely of the group to have made the decision to work abroad. How transferable the pedagogical skills that she had gained during her training would be when used in a culturally different and therefore (to her, challenging) environment was a key focus of the study. Another key focus was to explore the dispositions being used by the newly qualified teacher in order for her to teach and to thrive in an overseas educational environment. The methodological approach used for this study was both interpretative and qualitative. Associated methods were: Observation: observing the wider and operational practice of the newly qualified teacher over a five day period, and their need, ability and willingness to be reflective, resilient, reciprocal and resourceful. Interview: semi-structured interview with the newly qualified teacher following the observation of her practice. Findings from this case study illuminate the modifications made by the newly qualified teacher to her bank of teaching and learning strategies as well as the essentiality of dispositions used by her to know how to learn and also, crucially, to be ready and willing to do so. Such dispositions include being resilient, resourceful, reciprocal and reflective; necessary in order to adapt to the emerging challenges encountered by the teacher during their first months of employment in China. It is concluded that developing the skills to teach is essential for good teaching and learning practices. Having dispositions that enable teachers to work in ever changing conditions and surroundings is, this paper argues, essential for transferability and longevity of use of these skills.

Keywords: learning, post-compulsory, resilience, transferable

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Authors: Jonathan Glazzard

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National student satisfaction data in England demonstrate that undergraduate students are less satisfied overall with assessment and feedback than other aspects of their higher education courses. Given that research findings suggest that high-quality feedback is a critical factor associated with academic achievement, it is important that feedback enables students to demonstrate improved academic achievement in their subsequent assessments. Given the growing importance of staff-student partnerships in higher education, this research examined students’ perceptions of assessment and feedback in one UK university. Students’ perceptions were elicited through the use of a university-wide survey which was completed by undergraduate students. In addition, three focus groups were used to provide qualitative student perception data across the three university Facilities. The data indicate that whilst students valued detailed feedback on their work, less detailed feedback could be compensated for by the development of pre-assessment literacy skills which are front-loaded into courses. Assessment literacy skills valued by students included the use of clear assessment criteria and assignment briefings which enabled students to fully understand the assessment task. Additionally, students valued assessment literacy pre-assessment tasks which enabled them to understand the standards which they were expected to achieve. Students valued opportunities for self and peer assessment prior to the final assessment and formative assessment feedback which matched the summative assessment feedback. Students also valued dialogic face-to-face feedback after receiving written feedback Above all, students valued feedback which was particular to their work and which gave recognition for the effort they had put into completing specific assessments. The data indicate that there is a need for higher education lecturers to receive systematic training in assessment and feedback which provides a comprehensive grounding in pre-assessment literacy skills.

Keywords: formative assessment, summative assessment, feedback, marking

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Authors: Tokihiko Akita, Seiichi Mita

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A millimeter-wave radar is the most robust against adverse environments, making it an essential environment recognition sensor for automated driving. However, the reflection signal is sparse and unstable, so it is difficult to obtain the high recognition accuracy. Deep learning provides high accuracy even for them in recognition, but requires large scale datasets with ground truth. Specially, it takes a lot of cost to annotate for a millimeter-wave radar. For the solution, utilizing a simulator that can generate an annotated huge dataset is effective. Simulation of the radar is more difficult to match with real world data than camera image, and recognition by deep learning with higher-order features using the simulator causes further deviation. We have challenged to improve the accuracy of traffic participant classification by fusing simulator and real-world data with domain adaptation technique. Experimental results with the domain adaptation network created by us show that classification accuracy can be improved even with a few real-world data.

Keywords: millimeter-wave radar, object classification, deep learning, simulation, domain adaptation

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Authors: Teresa Kupczyk, Selçuk Mustafa Özcan, Joanna Kubicka

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The paper presents results of specialist literature analysis concerning learning outcomes and student satisfaction as a factor of the necessary change in the Polish higher education system. The objective of the empirical research was to determine students’ assessment of learning outcomes, satisfaction of their expectations, as well as their satisfaction with lectures and practical classes held in the traditional form, e-learning and video-conference. The assessment concerned effectiveness of time spent at classes, usefulness of the delivered knowledge, instructors’ preparation and teaching skills, application of tools, studies curriculum, its adaptation to students’ needs and labour market, as well as studying conditions. Self-assessment of learning outcomes was confronted with assessment by lecturers. The indirect objective of the research was also to identify how students assessed their activity and commitment in acquisition of knowledge and their discipline in achieving education goals. It was analysed how the studies held affected the students’ willingness to improve their skills and assessment of their perspectives at the labour market. To capture the changes underway, the research was held at the beginning, during and after completion of the studies. The study group included 86 students of two editions of full-time studies majoring in Management and specialising in “Mega-event organisation”. The studies were held within the EU-funded project entitled “Responding to challenges of new markets – innovative managerial education”. The results obtained were analysed statistically. Average results and standard deviations were calculated. In order to describe differences between the studied variables present during the process of studies, as well as considering the respondents’ gender, t-Student test for independent samples was performed with the IBM SPSS Statistics 21.0 software package. Correlations between variables were identified by calculation of Pearson and Spearman correlation coefficients. Research results suggest necessity to introduce some changes in the teaching system applied at Polish higher education institutions, not only considering the obtained outcomes, but also impact on students’ willingness to improve their qualifications constantly, improved self-assessment among students and their opportunities at the labour market.

Keywords: higher education, learning outcomes, students, change

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Authors: Troy A. Tyre

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Organizational behavior and organizational change are elements of the ever-changing global business environment. Leadership and organizational behavior are 21st century disciplines. Network marketing organizations need to understand the ever-changing nature of global business and be ready and willing to adapt to the environment. Network marketing organizations have a challenge keeping up with a rapid escalation in global growth. Network marketing growth has been steady and global. Network marketing organizations have been slow to develop a 21st century global strategy to manage the rapid escalation of growth degrading organizational behavior, job satisfaction, increasing attrition, and degrading customer service. Development of an organizational behavior and leadership theory for the 21st century to help network marketing develops a global business strategy to manage the rapid escalation in growth that affects organizational behavior. Managing growth means organizational leadership must develop and adapt to the organizational environment. Growth comes with an open mind and one’s departure from the comfort zone. Leadership growth operates in the tacit dimension. Systems thinking and adaptation of mental models can help shift organizational behavior. Shifting the organizational behavior requires organizational learning. Organizational learning occurs through single-loop, double-loop, and triple-loop learning. Triple-loop learning is the most difficult, but the most rewarding. Tools such as theory U can aid in developing a landscape for organizational behavioral development. Additionally, awareness to espoused and portrayed actions is imperatives. Theories of motivation, cross-cultural diversity, and communications are instrumental in founding an organizational behavior suited for the 21st century.

Keywords: global, leadership, network marketing, organizational behavior

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: Nezha Badi

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It has been shown in the literature that Algerian university students suffer from low levels of reading comprehension proficiency, which hinder their overall proficiency in English. This low level is mainly related to the methodology of teaching reading which is employed by the teacher in the classroom (a teacher-centered environment), as well as students’ poor sense of self-efficacy to undertake reading comprehension activities. Arguably, what is needed is an approach necessary for enhancing students’ self-beliefs about their abilities to deal with different reading comprehension activities. This can be done by providing them with opportunities to take responsibility for their own learning (learners’ autonomy). As a result of learning autonomy, learners’ beliefs about their abilities to deal with certain language tasks may increase, and hence, their language learning ability. Therefore, this experimental research study attempts to assess the extent to which an integrated approach combining one particular reading approach known as ‘collaborative strategic reading’ (CSR), and teacher’s attributional feedback (on students’ reading performance and strategy use) can improve the reading comprehension skill and the sense of self-efficacy of EFL Algerian university students. It also seeks to examine students’ main reasons for their successful or unsuccessful achievements in reading comprehension activities, and whether students’ attributions for their reading comprehension outcomes can be modified after exposure to the instruction. To obtain the data, different tools including a reading comprehension test, questionnaires, an observation, an interview, and learning logs were used with 105 second year Algerian EFL university students. The sample of the study was divided into three groups; one control group (with no treatment), one experimental group (CSR group) who received a CSR instruction, and a second intervention group (CSR Plus group) who received teacher’s attribution feedback in addition to the CSR intervention. Students in the CSR Plus group received the same experiment as the CSR group using the same tools, except that they were asked to keep learning logs, for which teacher’s feedback on reading performance and strategy use was provided. The results of this study indicate that the CSR and the attributional feedback intervention was effective in improving students’ reading comprehension proficiency and sense of self-efficacy. However, there was not a significant change in students’ adaptive and maladaptive attributions for their success and failure d from the pre-test to the post-test phase. Analysis of the perception questionnaire, the interview, and the learning logs shows that students have positive perceptions about the CSR and the attributional feedback instruction. Based on the findings, this study, therefore, seeks to provide EFL teachers in general and Algerian EFL university teachers in particular with pedagogical implications on how to teach reading comprehension to their students to help them achieve well and feel more self-efficacious in reading comprehension activities, and in English language learning more generally.

Keywords: attributions, attributional feedback, collaborative strategic reading, self-efficacy

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Authors: Helen Potkin

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This paper presents a practice-based case study of a project in which the student group designed and planned the curriculum content, classroom activities and assessment briefs in collaboration with the tutor. It focuses on the co-creation of the curriculum within a history and theory module, Researching the Contemporary, which runs for BA (Hons) Fine Art and Art History and for BA (Hons) Art Design History Practice at Kingston University, London. The paper analyses the potential of collaborative approaches to engender students’ investment in their own learning and to encourage reflective and self-conscious understandings of themselves as learners. It also addresses some of the challenges of working in this way, attending to the risks involved and feelings of uncertainty produced in experimental, fluid and open situations of learning. Alongside this, it acknowledges the tensions inherent in adopting such practices within the framework of the institution and within the wider of context of the commodification of higher education in the United Kingdom. The concept underpinning the initiative was to test out co-creation as a creative process and to explore the possibilities of altering the traditional hierarchical relationship between teacher and student in a more active, participatory environment. In other words, the project asked about: what kind of learning could be imagined if we were all in it together? It considered co-creation as producing different ways of being, or becoming, as learners, involving us reconfiguring multiple relationships: to learning, to each other, to research, to the institution and to our emotions. The project provided the opportunity for students to bring their own research and wider interests into the classroom, take ownership of sessions, collaborate with each other and to define the criteria against which they would be assessed. Drawing on students’ reflections on their experience of co-creation alongside theoretical considerations engaging with the processual nature of learning, concepts of equality and the generative qualities of the interrelationships in the classroom, the paper suggests that the dynamic nature of collaborative and participatory modes of engagement have the potential to foster relevant and significant learning experiences. The findings as a result of the project could be quantified in terms of the high level of student engagement in the project, specifically investment in the assessment, alongside the ambition and high quality of the student work produced. However, reflection on the outcomes of the experiment prompts a further set of questions about the nature of positionality in connection to learning, the ways our identities as learners are formed in and through our relationships in the classroom and the potential and productive nature of creative practice in education. Overall, the paper interrogates questions of what it means to work with students to invent and assemble the curriculum and it assesses the benefits and challenges of co-creation. Underpinning it is the argument that, particularly in the current climate of higher education, it is increasingly important to ask what it means to teach and to envisage what kinds of learning can be possible.

Keywords: co-creation, collaboration, learning, participation, risk

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Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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Authors: Mathuravech Thanaphon, Thephasit Nat

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The Electricity Generating Authority of Thailand (EGAT) is focusing on expanding its pumped storage hydropower (PSH) capacity to increase the reliability of the system during peak demand and allow for greater integration of renewables. To achieve this requirement, Thailand will have to double its current renewable electricity production. To address the challenges of balancing supply and demand in the grid with increasing levels of RE penetration, as well as rising peak demand, EGAT has already been studying the potential for additional PSH capacity for several years to enable an increased share of RE and replace existing fossil fuel-fired generation. In addition, the role that pumped-storage hydropower would play in fulfilling multiple grid functions and renewable integration. The proposed sites for new PSH would help increase the reliability of power generation in Thailand. However, most of the electricity generation will come from RE, chiefly wind and photovoltaic, and significant additional Energy Storage capacity will be needed. In this paper, the impact of integrating the PSH system on the adequacy of renewable rich power generating systems to reduce the thermal power generating units is investigated. The variations of system adequacy indices are analyzed for different PSH-renewables capacities and storage levels. Power Development Plan 2018 rev.1 (PDP2018 rev.1), which is modified by integrating a six-new PSH system and RE planning and development aftermath in 2030, is the very challenge. The system adequacy indices through power generation are obtained using Multi-Objective Genetic Algorithm (MOGA) Optimization. MOGA is a probabilistic heuristic and stochastic algorithm that is able to find the global minima, which have the advantage that the fitness function does not necessarily require the gradient. In this sense, the method is more flexible in solving reliability optimization problems for a composite power system. The optimization with hourly time step takes years of planning horizon much larger than the weekly horizon that usually sets the scheduling studies. The objective function is to be optimized to maximize RE energy generation, minimize energy imbalances, and minimize thermal power generation using MATLAB. The PDP2018 rev.1 was set to be simulated based on its planned capacity stepping into 2030 and 2050. Therefore, the four main scenario analyses are conducted as the target of renewables share: 1) Business-As-Usual (BAU), 2) National Targets (30% RE in 2030), 3) Carbon Neutrality Targets (50% RE in 2050), and 5) 100% RE or full-decarbonization. According to the results, the generating system adequacy is significantly affected by both PSH-RE and Thermal units. When a PSH is integrated, it can provide hourly capacity to the power system as well as better allocate renewable energy generation to reduce thermal generations and improve system reliability. These results show that a significant level of reliability improvement can be obtained by PSH, especially in renewable-rich power systems.

Keywords: pumped storage hydropower, renewable energy integration, system adequacy, power development planning, RE100, multi-objective genetic algorithm

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Yuanxiang Miao

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Couchsurfing is a free homestay and social networking service accessible via the website and mobile app. Couchsurfers can directly request free accommodations from others and receive offers from each other. However, it is typically difficult for people to make a decision that accepts or declines a request when they receive it from Couchsurfers because they do not know each other at all. People are expected to meet up with some Couchsurfers who are kind, generous, and interesting while it is unavoidable to meet up with someone unfriendly. This paper utilized classification algorithms of Machine Learning to help people to find out the Good Couchsurfers and Not Good Couchsurfers on the Couchsurfing website. By knowing the prior experience, like Couchsurfer’s profiles, the latest references, and other factors, it became possible to recognize what kind of the Couchsurfers, and furthermore, it helps people to make a decision that whether to host the Couchsurfers or not. The value of this research lies in a case study in Kyoto, Japan in where the author has hosted 54 Couchsurfers, and the author collected relevant data from the 54 Couchsurfers, finally build a model based on classification algorithms for people to predict Couchsurfers. Lastly, the author offered some feasible suggestions for future research.

Keywords: Couchsurfing, Couchsurfers prediction, classification algorithm, hospitality tourism platform, hospitality sciences, machine learning

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Authors: Oleg Shovkovyy

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This research conducted in response to one of the most pressing questions on the agenda of many public administration offices around the world: “What could be done for better integration and assimilation of immigrants into hosting communities?” In author’s view, the answer could be suggested by immigrants themselves. They, often ‘bogged down in the past,’ snared by own idols and demons, perceive things differently, which, in turn, may result in their inability to integrate smoothly into hosting communities. Brief literature review suggests that perceptions of immigrants are completely neglected or something unsought in the current research on migrants, which, often, based on opinion polls by members of hosting communities themselves or superficial research data by various research organizations. Even those specimens that include voices of immigrants, unlikely to shed any additional light onto the problem simply because certain things are not made to speak out loud, especially to those in whose hands immigrants’ fate is (authorities). In this regard, this qualitative study, conducted by an insider to a few Russian-speaking communities, represents a unique opportunity for all stakeholders to look at the question of integration through the eyes of immigrants, from a different perspective and thus, makes research findings especially valuable for better understanding of the problem. Case study research employed ethnographic methods of gathering data where, approximately 200 Russian-speaking immigrants of first and second generations were closely observed by the Russian-speaking researcher in their usual setting, for eight months, and at different venues. The number of informal interviews with 27 key informants, with whom the researcher managed to establish a good rapport and who were keen enough to share their experiences voluntarily, were conducted. The field notes were taken at 14 locations (study sites) within the Brisbane region of Queensland, Australia. Moreover, all this time, researcher lived in dwelling of one of the immigrants and was an active participant in the social life (worship, picnics, dinners, weekend schools, concerts, cultural events, social gathering, etc.) of observed communities, whose members, to a large extent, belong to various religious lines of the Russian and Protestant Church. It was found that the majority of immigrants had experienced some discrimination in matters of hiring, employment, recognition of educational qualifications from home countries, and simply felt a sort of dislike from society in various everyday situations. Many noted complete absences or very limited state assistance in terms of employment, training, education, and housing. For instance, the Australian Government Department of Human Services not only does not stimulate job search but, on the contrary, encourages to refuse short-term works and employment. On the other hand, offered free courses on adaptation, and the English language proved to be ineffective and unpopular amongst immigrants. Many interviewees have reported overstated requirements for English proficiency and local work experience, whereas it was not critical for the given task or job. Based on the result of long-term monitoring, the researcher also had the courage to assert the negative and decelerating roles of immigrants’ communities, particularly religious communities, on processes of integration and assimilation. The findings suggest that governments should either change current immigration policies in the direction of their toughening or to take more proactive and responsible role in dealing with immigrant-related issues; for instance, increasing assistance and support to all immigrants and probably, paying more attention to and taking stake in managing and organizing lives of immigrants’ communities rather, simply leaving it all to chance.

Keywords: Australia, immigration, integration, perceptions

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Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

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Authors: Derssie Mebratu

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As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

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Authors: Murat Arıbaş, Uğur Özcan

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Due to the increasing number of universities and academics, the fund of the universities for research activities and grants/supports given by government institutions have increased number and quality of academic research projects. Although every academic research project has a specific purpose and importance, limited resources (money, time, manpower etc.) require choosing the best ones from all (Amiri, 2010). It is a pretty hard process to compare and determine which project is better such that the projects serve different purposes. In addition, the evaluation process has become complicated since there are more than one evaluator and multiple criteria for the evaluation (Dodangeh, Mojahed and Yusuff, 2009). Mehrez and Sinuany-Stern (1983) determined project selection problem as a Multi Criteria Decision Making (MCDM) problem. If a decision problem involves multiple criteria and objectives, it is called as a Multi Attribute Decision Making problem (Ömürbek & Kınay, 2013). There are many MCDM methods in the literature for the solution of such problems. These methods are AHP (Analytic Hierarchy Process), ANP (Analytic Network Process), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), UTADIS (Utilities Additives Discriminantes), ELECTRE (Elimination et Choix Traduisant la Realite), MAUT (Multiattribute Utility Theory), GRA (Grey Relational Analysis) etc. Teach method has some advantages compared with others (Ömürbek, Blacksmith & Akalın, 2013). Hence, to decide which MCDM method will be used for solution of the problem, factors like the nature of the problem, types of choices, measurement scales, type of uncertainty, dependency among the attributes, expectations of decision maker, and quantity and quality of the data should be considered (Tavana & Hatami-Marbini, 2011). By this study, it is aimed to develop a systematic decision process for the grant support applications that are expected to be evaluated according to their scientific adequacy by multiple evaluators under certain criteria. In this context, project evaluation process applied by The Scientific and Technological Research Council of Turkey (TÜBİTAK) the leading institutions in our country, was investigated. Firstly in the study, criteria that will be used on the project evaluation were decided. The main criteria were selected among TÜBİTAK evaluation criteria. These criteria were originality of project, methodology, project management/team and research opportunities and extensive impact of project. Moreover, for each main criteria, 2-4 sub criteria were defined, hence it was decided to evaluate projects over 13 sub-criterion in total. Due to superiority of determination criteria weights AHP method and provided opportunity ranking great number of alternatives TOPSIS method, they are used together. AHP method, developed by Saaty (1977), is based on selection by pairwise comparisons. Because of its simple structure and being easy to understand, AHP is the very popular method in the literature for determining criteria weights in MCDM problems. Besides, the TOPSIS method developed by Hwang and Yoon (1981) as a MCDM technique is an alternative to ELECTRE method and it is used in many areas. In the method, distance from each decision point to ideal and to negative ideal solution point was calculated by using Euclidian Distance Approach. In the study, main criteria and sub-criteria were compared on their own merits by using questionnaires that were developed based on an importance scale by four relative groups of people (i.e. TUBITAK specialists, TUBITAK managers, academics and individuals from business world ) After these pairwise comparisons, weight of the each main criteria and sub-criteria were calculated by using AHP method. Then these calculated criteria’ weights used as an input in TOPSİS method, a sample consisting 200 projects were ranked on their own merits. This new system supported to opportunity to get views of the people that take part of project process including preparation, evaluation and implementation on the evaluation of academic research projects. Moreover, instead of using four main criteria in equal weight to evaluate projects, by using weighted 13 sub-criteria and decision point’s distance from the ideal solution, systematic decision making process was developed. By this evaluation process, new approach was created to determine importance of academic research projects.

Keywords: Academic projects, Ahp method, Research projects evaluation, Topsis method.

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

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Authors: Raveendranath Veeramani, Sunil Jonathan Holla, Parkash Chand, Sunil Chumber

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Gray’s Anatomy for Students has been a well-appreciated book among undergraduate students of anatomy in Asia. However, the current curricular requirements of anatomy require a more focused and organized approach. The editors of the first South Asia edition of Gray’s Anatomy for Students hereby highlight the modifications and importance of this edition. There is an emphasis on active learning by making the clinical relevance of anatomy explicit. Learning anatomy in context has been fostered by the association between anatomists and clinicians in keeping with the emerging integrated curriculum of the 21st century. The language has been simplified to aid students who have studied in the vernacular. The original illustrations have been retained, and few illustrations have been added. There are more figure numbers mentioned in the text to encourage students to refer to the illustrations while learning. The text has been made more student-friendly by adding generalizations, classifications and summaries. There are useful review materials at the beginning of the chapters which include digital resources for self-study. There are updates on imaging techniques to encourage students to appreciate the importance of essential knowledge of the relevant anatomy to interpret images, due emphasis has been laid on dissection. Additional importance has been given to the cranial nerves, by describing their relevant details with several additional illustrations and flowcharts. This new edition includes innovative features such as set inductions, outlines for subchapters and flowcharts to facilitate learning. Set inductions are mostly clinical scenarios to create interest in the need to study anatomy for healthcare professions. The outlines are a modern multimodal facilitating approach towards various topics to empower students to explore content and direct their learning and include learning objectives and material for review. The components of the outline encourage the student to be aware of the need to create solutions to clinical problems. The outlines help students direct their learning to recall facts, demonstrate and analyze relationships, use reason to explain concepts, appreciate the significance of structures and their relationships and apply anatomical knowledge. The 'structures to be identified in a dissection' are given as Level I, II and III which represent the 'must know, desirable to know and nice to know' content respectively. The flowcharts have been added to get an overview of the course of a structure, recapitulate important details about structures, and as an aid to recall. There has been a great effort to balance the need to have content that would enable students to understand concepts as well as get the basic material for the current condensed curriculum.

Keywords: Grays anatomy, South Asia, human anatomy, students anatomy

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Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches

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Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.

Keywords: groundwater monitoring, observation networks, machine learning, madrid

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Authors: Cynthia Adlerstein

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Physical learning environment (PLE) has been considered, after family and educators, as the third teacher. There have been conflicting and converging viewpoints on the role of the physical dimensions of places to learn, in facilitating educational innovation and quality. Despite the different approaches, PLE has been widely recognized as a key factor in the quality of the learning experience , and in the levels of learning achievement in ECE . The conceptual frameworks of the field assume that PLE consists of a complex web of factors that shape the overall conditions for learning, and that much more interdisciplinary and complementary methodologies of research and development are required. Although the relevance of PLE attracts a broad international consensus, in Chile it remains under-researched and weakly regulated by public policy. Gaining deeper contextual understanding and more thoughtfully-designed recommendations require the use of innovative assessment tools that cross cultural and disciplinary boundaries to produce new hybrid approaches and improvements. When considering a PLE-based change process for ECE improvement, a central question is what dimensions, variables and indicators could allow a comprehensive assessment of PLE in Chilean kindergartens? Based on a grounded theory social justice inquiry, we adopted a mixed method design, that enabled a multivocal and interdisciplinary construction of data. By using in-depth interviews, discussion groups, questionnaires, and documental analysis, we elicited the PLE discourses of politicians, early childhood practitioners, experts in architectural design and ergonomics, ECE stakeholders, and 3 to 5 year olds. A constant comparison method enabled the construction of the dimensions, variables and indicators through which PLE assessment is possible. Subsequently, the instrument was applied in a sample of 125 early childhood classrooms, to test reliability (internal consistency) and validity (content and construct). As a result, an interdisciplinary and multivocal tool for assessing physical learning environments was constructed and validated, for Chilean kindergartens. The tool is structured upon 7 dimensions (wellbeing, flexible, empowerment, inclusiveness, symbolically meaningful, pedagogically intentioned, institutional management) 19 variables and 105 indicators that are assessed through observation and registration on a mobile app. The overall reliability of the instrument is .938 while the consistency of each dimension varies between .773 (inclusive) and .946 (symbolically meaningful). The validation process through expert opinion and factorial analysis (chi-square test) has shown that the dimensions of the assessment tool reflect the factors of physical learning environments. The constructed assessment tool for kindergartens highlights the significance of the physical environment in early childhood educational settings. The relevance of the instrument relies in its interdisciplinary approach to PLE and in its capability to guide innovative learning environments, based on educational habitability. Though further analysis are required for concurrent validation and standardization, the tool has been considered by practitioners and ECE stakeholders as an intuitive, accessible and remarkable instrument to arise awareness on PLE and on equitable distribution of learning opportunities.

Keywords: Chilean kindergartens, early childhood education, physical learning environment, third teacher

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Authors: Jessica Wood, Serge Desmarais

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There has been recent resurgence in the popular and academic interest of consensual non-monogamous (CNM) relationships- an umbrella term that defines relationships in which each partner has openly agreed to engage in additional romantic and/or sexual relationships outside of their primary partnership. Despite an increase in the academic study of CNM, little psychological attention has been paid to the study of CNM, with the consideration of these relationships commonly occurring within related social science disciplines such as sociology or anthropology. As a discipline, psychology has a history of conducting research in the area of intimate relationships, and psychologists have amassed a wealth of theoretical knowledge in this field. However, historically individuals who engage in "alternative" sexual and romantic behaviours, such as non-heterosexual sex or sex with multiple partners have been pathologized within psychological research. Individuals in CNM relationships or individuals identifying as lesbian, gay, bisexual, trans or queer have often been excluded from research or “othered” in psychological interpretations of what healthy relationships entail. Thus, our current theoretical understandings of romantic relationships are limited to heterosexual, monogamous relationships. The goal of this presentation is to examine commonly cited components of relationship satisfaction (e.g., commitment, communication) and to critically assess how CNM experiences are presented in, or missing from, the psychological literature on romantic relationships. Additionally, the presentation will also consider how CNM relationships may add to our understanding or enhancement of traditional psychological theories and address issues related to heteronormativity and mononormativity within the discipline. Finally, we will close with a consideration of additional theoretical perspectives that may aid in our understanding of CNM relationships and suggest directions for future research.

Keywords: heteronormativity, mononormativity, psychological research, diverse relationships, gender, sexuality, feminism, queer theory

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

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Authors: Zhe Li, Aihua Cai

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Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Gezahegn Bekele Welldgiyorgise

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It is obvious that the economics, politics and social conditions of a country are determined by the quality and standard of its education. Indeed, education plays a vital role in changing the consciousness and awareness of society and transforming it on a large scale. Moreover, education contributes a lot to the advancement of science and technology, information and communication, and above all, it speeds up its progress in no time if it focuses mainly on the qualitative approach to education. Education brings about universal change and transformation and lightens mankind in all dimensions. It creates an educated, enlightened and brightened generation in society. The generation will be sharped, sharpened and well-oriented if it gets modern, sophisticated and standardized education in its field of study. The main goal of education is to produce well-qualified, well-trained and disciplined young offers in a given community. If the youth is well trained and well-mannered, he will certainly be enlightened, problem solvers and solution seekers, researchers, and innovators. In this respect, we have to provide the youth with modern education, a teaching-learning process led by active learning and a participatory approach with a new curriculum preparation for the age of children supported by modern facilities (ICT).In addition to that, the curriculum should have to give attention to mathematics and science lessons that include international experience in a comfortable school and classrooms. Therefore, the generation that will be created through such kinds of the guided education system will make the students active participants, self-confident, researchers and problem solvers, besides that result in changed life standards and a developed country. Similarly, our country, Ethiopia, has aimed to get such change in youth (generation) through modern education, designing a new educational policy and curriculum which was implemented for many years, although the goal of education has not reached the required level. To get the main idea of the article, I should have answered the question of why our country's educational goal had not reached the desired level because it is necessary to lay the foundation for research in finding out problems seen through students learning performance, the first task is selecting primary-school as a sample. Therefore, we selected “Dilla primary school (5-8)” which is a workplace for a teacher and gives me a chance to recognize students’ learning performance to recognize their learning grades (internal and external) and measure performance (achievement) of students easily’.

Keywords: curriculum, performance, innovation, learning

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Authors: Nune Ayvazyan

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Since the proclamation of monolingual foreign-language learning methods (the Berlitz Method in the early 20ᵗʰ century and the like), the dilemma has been to allow or not to allow learners’ mother tongue in the foreign-language learning process. The reason for not allowing learners’ mother tongue is reported to create a situation of immersion where students will only use the target language. It could be argued that this artificial monolingual situation is defective, mainly because there are very few real monolingual situations in the society. This is mainly due to the fact that societies are nowadays increasingly multilingual as plurilingual speakers are the norm rather than an exception. More recently, the use of learners’ mother tongue and translation has been put under the spotlight as valid foreign-language teaching tools. The logic dictates that if learners were permitted to use their mother tongue in the foreign-language learning process, that would not only be natural, but also would give them additional means of participation in class, which could eventually lead to learning. For example, when learners’ metalinguistic skills are poor in the target language, a question they might have could be asked in their mother tongue. Otherwise, that question might be left unasked. Attempts at empirically testing the role of translation as a didactic tool in foreign-language teaching are still very scant. In order to fill this void, this study looks into the interaction patterns between students in two kinds of English-learning classes: one with translation and the other in English only (immersion). The experiment was carried out with 61 students enrolled in a second-year university subject in English grammar in Spain. All the students underwent the two treatments, classes with translation and in English only, in order to see how they interacted under the different conditions. The analysis centered on four categories of interaction: teacher talk, teacher-initiated student interaction, student-initiated student-to-teacher interaction, and student-to-student interaction. Also, pre-experiment and post-experiment questionnaires and individual interviews gathered information about the students’ attitudes to translation. The findings show that translation elicited more student-initiated interaction than did the English-only classes, while the difference in teacher-initiated interactional turns was not statistically significant. Also, student-initiated participation was higher in comprehension-based activities (into L1) as opposed to production-based activities (into L2). As evidenced by the questionnaires, the students’ attitudes to translation were initially positive and mainly did not vary as a result of the experiment.

Keywords: foreign language, learning, mother tongue, translation

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Authors: Faranak Omidian

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This study has been carried out to examine the status of architecture department at bachelor's level of engineering architecture in Islamic Azad University of Dezful in 2012-13 academic year. The present research is a descriptive cross sectional study and in terms of measurement, it is descriptive and analytical, which was done based on 7 steps and in 7 areas with 32 criteria and 169 indicators. The sample includes 201 students, 14 faculty members, 72 graduates and 39 employers. Simple random sampling method, complete enumeration method, network sampling (snowball sampling) were used for students, faculty members and graduates respectively. All sample responded to the questions. After data collection, the findings were ranked on Likert scale from desirable to undesirable with the scores ranging from 1 to 3.The results showed that the department with a score of 1.88 in regard to objectives, organizational status, management and organizations, with a score of 2 in relation to students, with a score of 1.8 in regard to faculty members was in a relatively desirable status. Regarding training courses and curriculum, it gained a score of 2.33 which indicates the desirable status of the department in this regard. It gained scores of 1.75, 2, and 1.8 with respect to educational and research facilities and equipment, teaching and learning strategies, and graduates respectively, all of which shows the relatively desirable status of the department. The results showed that the department of architecture, with an average score of 2.14 in all evaluated areas, was in a desirable situation. Therefore, although the department generally has a desirable status, it needs to put in more effort to tackle its weaknesses and shortages and corrects its defects in order to promote educational quality, taking to the desirable level.

Keywords: internal evaluation, architecture department in Islamic, Azad University, Dezful

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Authors: Zhepeng Rui, Zhenyu Gu, Caitilin de Bérigny

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In the current study, we designed an interactive meditation and brain painting application to cultivate users’ creativity, promote meditation, reduce stress, and improve cognition while attempting to learn a foreign language. User tests and data analyses were conducted on 42 male and 42 female participants to better understand sex-associated psychological and aesthetic differences. Our method utilized brain-computer interfaces to import meditation and attention data to create artwork in meditation-based applications. Female participants showed statistically significantly different language learning outcomes following three meditation paradigms. The art style of brain painting helped females with language memory. Our results suggest that the most ideal methods for promoting memory attention were meditation methods and brain painting exercises contributing to language learning, memory concentration promotion, and foreign word memorization. We conclude that a short period of meditation practice can help in learning a foreign language. These findings provide new insights into meditation, creative language education, brain-computer interface, and human-computer interactions.

Keywords: brain-computer interface, creative thinking, meditation, mental health

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