Search results for: teaching and learning English

Authors: Yuet Wah Echo Yeung

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Working with people from minority ethnic groups, refugees and asylum seeking communities who have limited proficiency in the language of the host country often presents a major challenge for social workers. Because of language differences, social workers need to work with interpreters to ensure accurate information is collected for their assessment and intervention. Drawing from social learning theory, this paper discusses how role play was used as an experiential learning exercise in a training session to help social work students develop skills when working with interpreters. Social learning theory posits that learning is a cognitive process that takes place in a social context when people observe, imitate and model others’ behaviours. The roleplay also helped students understand the role of the interpreter and the challenges they may face when they rely on interpreters to communicate with service users and their family. The first part of the session involved role play. A tutor played the role of social worker and deliberately behaved in an unprofessional manner and used inappropriate body language when working alongside the interpreter during a home visit. The purpose of the roleplay is not to provide a positive role model for students to ‘imitate’ social worker’s behaviours. Rather it aims to active and provoke internal thinking process and encourages students to critically consider the impacts of poor practice on relationship building and the intervention process. Having critically reflected on the implications for poor practice, students were then asked to play the role of social worker and demonstrate what good practice should look like. At the end of the session, students remarked that they learnt a lot by observing the good and bad example; it showed them what not to do. The exercise served to remind students how practitioners can easily slip into bad habits and of the importance of respect for the cultural difference when working with people from different cultural backgrounds.

Keywords: role play, social learning theory, social work practice, working with interpreters

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Authors: Bowen Zhang

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Transnational higher education (TNHE) is one of the most prominent symbols of higher education’s internationalisation. The case university, Xi'an Jiaotong Liverpool University (XJTLU), represents an equal collaboration between its parent institutions as they are tied in academic strength. Therefore, compared to the more prescribed route of UNNC, which is working towards creating another UK university in China, XJTLU’s future is fraught with uncertainty. Such kind of uncertainty underpins the rationale of selecting XJTLU as a case university in researching internationalisation -it does not aim to build an international university based on a template; instead, internationalisation in XJTLU is established in a more participatory manner that also reflects an understanding of its staff and students. Therefore, this article focuses on Chinese students' expectations and experiences in XJTLU. While there are research discussing international students' experiences in TNHE institutions, the experiences of Chinese students who attend their domestic TNHE have been less explored. This might be due to the potential issues they confront are not as intuitive as those faced by international students, whose experiences are largely shaped by mobility and cross-cultural transition, a well-documented and conceptualised phenomenon. Research regarding Chinese students mainly focuses on their motivations, for example, enhancing English proficiency, improving competitive advantage in labour market, and gaining an international perspective. However, it should be noted that these motivations are based on the internationalised features of TNHE institutions. Internationalisation in XJTLU is symbolised through 100% English-medium instruction, internationalised curriculum, and the national diversity of its students and staff. However, in practice, these promises for internationalisation are hardly met; for example, in terms of EMI, lecturers may engage in their native language, either out of their hope to enhance students’ understanding or forcibly switch back to Chinese due to limited language capacity. Therefore, it could be seen that the non-application of internationalised policy may result in a negotiated internationalising experience for students. It is important to point out that, in this study, both the expected capital that students hope to access prior to their enrollment to XJTLU and the actual capital that students are accumulating during their attendance, are examined, as the difference between the actual and potential could be an important indicator of the discrepancy between how internationalisation is perceived and how it is enacted in practice. The potential resources implicate perceived compatibility between habitus and field, which is highly relevant to the way that a field makes itself known, whereas the actual resources represent the lived experience and the actual compatibility between habitus and field. This study explores the similarities and differences between the expected and lived capital from XJTLU, and the way that students form and navigate their expectations, in turn providing insights on how XJTLU, or HE internationalisation as a whole, is depicted, imagined, and enacted among Chinese students.

Keywords: transnational higher education, English-medium instruction, students' experience, Chinese higher education

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Authors: Suffian Hadi Ayub, Mohammad Rezal Hamzah, Nor Hafizah Abdullah, Sharipah Nur Mursalina Syed Azmy, Hishamuddin Salim

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The liberalisation of the education industry has exposed the institute of higher learning (IHL) in Malaysia to the financial challenges. Without good financial standing, public institution will rely on the government funding. Ostensibly, this contradicts with the government’s aspiration to make universities self-sufficient. With stiff competition from private institutes of higher learning, IHL need to be prepared at the forefront level. The corporate identity itself is the entrance to the world of higher learning and it is in this uniqueness, it will be able to distinguish itself from competitors. This paper examined the perception of the stakeholders at one of the public universities in the east coast region in Malaysia on the perceived reputation and how the university communicate its preparedness for self-sustainability through corporate identity. The findings indicated while the stakeholders embraced the challenges in facing the stiff competition and struggling market conditions, most of them felt the university should put more efforts in mobilising the corporate identity to its constituencies.

Keywords: communication, corporate identity, market conditions, universities

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Authors: Tanzeela Anbreen, Ammara Maqsood

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Reading into writing is one of university students' most required academic skills. The current study explored postgraduate university students’ writing quality using a corpus-based approach. Twelve postgraduate students’ literature review essays were chosen for the corpus-based analysis. These essays were chosen because students had to incorporate multiple reading sources in these essays, which was a new writing exercise for them. The students were provided feedback at least two times which comprised of the written comments by the tutor highlighting the areas of improvement and also by using the ‘track changes’ function. This exercise was repeated two times, and students submitted two drafts. This investigation included only the finally submitted work of the students. A corpus-based approach was adopted to analyse the essays because it promotes autonomous discovery and personalised learning. The aim of this analysis was to understand the existing level of students’ writing before the start of their postgraduate thesis. Text Inspector was used to analyse the quality of essays. With the help of the Text Inspector tool, the vocabulary used in the essays was compared to the English Vocabulary Profile (EVP), which describes what learners know and can do at each Common European Framework of Reference (CEFR) level. Writing quality was also measured for the Flesch reading ease score, which is a standard to describe the ease of understanding the writing content. The results reflected that students found writing essays using multiple sources challenging. In most essays, the vocabulary level achieved was between B1-B2 of the CEFL level. The study recommends that students need extensive training in developing academic writing skills, particularly in writing the literature review type assignment, which requires multiple sources citations.

Keywords: literature review essays, postgraduate students, corpus-based analysis, vocabulary proficiency

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Authors: Jonathan Heng, Yoong Cheah Huei

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A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

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Authors: Juha Kettunen

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The purpose of this study is to develop a framework for the assessment of research and development projects. The assessment map is developed in this study based on the strategy map of the balanced scorecard approach. The assessment map is applied in a project that aims to reduce the inequality and risk of exclusion of young people from disadvantaged social groups. The assessment map denotes that not only funding but also necessary skills and qualifications should be carefully assessed in the implementation of the project plans so as to achieve the objectives of projects and the desired impact. The results of this study are useful for those who want to develop the implementation of the Erasmus+ Programme and the project teams of research and development projects.

Keywords: non-formal learning, youth work, social inclusion, innovation

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Authors: A.Chayaporn Kaoropthai, B. Onjaree Natakuatoong, C. Nagul Cooharojananone

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The first year is usually the most critical year for university students. Generally, a considerable number of first-year students worldwide drop out of university every year. One of the major reasons for dropping out is failing. Although they are supposed to have mastered sufficient English proficiency upon completing their high school education, most first-year students are still novices in academic reading. Due to their lack of experience in academic reading, first-year students need significant support from teachers to help develop their academic reading skills. Reading strategies training is thus a necessity and plays a crucial role in classroom instruction. However, individual differences in both students, as well as teachers, are the main factors contributing to the failure in not responding to each individual student’s needs. For this reason, reading strategies training inevitably needs a diagnosis of students’ academic reading skills levels before, during, and after learning, in order to respond to their different needs. To further support reading strategies training, scaffolding is proposed to facilitate students in understanding and practicing using reading strategies under the teachers’ guidance. The use of the Intelligent Tutoring Systems (ITSs) as a tool for diagnosing students’ reading problems will be very beneficial to both students and their teachers. The ITSs consist of four major modules: the Expert module, the Student module, the Diagnostic module, and the User Interface module. The application of Artificial Intelligence (AI) enables the systems to perform diagnosis consistently and appropriately for each individual student. Thus, it is essential to develop the Intelligent Scaffolding Diagnostic Reading Strategies Tutoring Systems to enhance first-year students’ academic reading skills. The systems proposed will contribute to resolving classroom reading strategies training problems, developing students’ academic reading skills, and facilitating teachers.

Keywords: academic reading, intelligent tutoring systems, scaffolding, university students

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Authors: Amani Jaber-Awida

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This study examines two bilingual phenomena in the narratives of Arabic Hebrew and Hebrew-English bilingual adults in Israel: CO memories and code-switching (CS). The study examined these phenomena in the context of autobiographical memory, using a cue word technique. Student experimenters held two sessions in the homes of the participants. In separate language sessions, the participant was asked to look first at each of 16 cue words and then to state a concrete memory. After stating the memory, participants reported whether their memories were in the same language of the experiment session or different. Memories were classified as ‘Crossovers’ (CO) or ‘Same Language’ (SL) according to participants' self-reports. Participants were also required to elaborate about the setting, interlocutors and other languages involved in the specific memory. Beyond replicating the procedure of cuing technique, one memory from a specific lifespan period was chosen per participant, and the participant was required to provide further details about it. For the more detailed memories, CS count was conducted. Both bilingual groups confirmed the Reminiscence Bump phenomenon, retrieving more memories in the 10-30 age period. CO memories prevailed in second language sessions (L2). Same language memories were more abundant in first language sessions (L1). Higher CS frequency was found in L2 sessions. Finally, as predicted, 'individual' CS was prevalent in L2 sessions, but 'community-based' CS was not higher in L1 sessions. The two bilingual measures in this study, crossovers, and CS came from different research traditions, the former from an experimental paradigm in the psychology of autobiographical memory based on self-reported judgments, the latter a behavioral measure from linguistics. This merger of approaches offers new insight into the field of bilingual autobiographical memory. In addition, the study attempted to shed light on the investigation of motivations for CS, beginning with Walters’ SPPL Model and concluding with a distinction between ‘community-based’ and individual motivations.

Keywords: bilinguals, code-switching, crossover memories, narratives

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Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

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Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

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Authors: Vania Helena Tonussi Vidal, Ester Eliane Jeunon

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This article aims to analyze the change processes of management related bureaucracy and learning organization model. The theoretical framework was based on Beer and Nohria (2001) model, identified as E and O Theory. Based on this theory the empirical research was conducted in connection with six key dimensions: goal, leadership, focus, process, reward systems and consulting. We used a case study of an educational Institution located in Barbacena, Minas Gerais. This traditional center of technical knowledge for long time adopted the bureaucratic way of management. After many changes in a business model, as the creation of graduate and undergraduate courses they decided to make a deep change in management model that is our research focus. The data were collected through semi-structured interviews with director, managers and courses supervisors. The analysis were processed by the procedures of Collective Subject Discourse (CSD) method, develop by Lefèvre & Lefèvre (2000), Results showed the incremental growing of management model toward a learning organization. Many impacts could be seeing. As negative factors we have: people resistance; poor information about the planning and implementation process; old politics inside the new model and so on. Positive impacts are: new procedures in human resources, mainly related to manager skills and empowerment; structure downsizing, open discussions channel; integrated information system. The process is still under construction and now great stimulus is done to managers and employee commitment in the process.

Keywords: bureaucracy, organizational learning, organizational change, E and O theory

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Authors: Paulo Sérgio Ribeiro de Araújo Bogas

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Although several studies have assumed (at least implicitly) that learners' approaches to learning develop into deeper approaches to higher education, there appears to be no clear theoretical basis for this assumption and no empirical evidence. As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation, and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences result from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the student's responses can be described as students who reinforce the initial deep approach, students who maintain the initial deep approach level, and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to the possible adoption of deep approaches to learning since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself, and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: experiential learning, higher education, mixed methods, reflective learning, marketing

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Authors: Vineesh Amin, Ananya Agrawal

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In a prolonged period of uncertainty and disruptions in the pre-said normal order, non-cognitive skills, especially entrepreneurial mindsets, have become a pillar that can reform the educational models to inform the economy. Dreamverse Learning Lab’s IVR-based storytelling program -Call-a-Kahaani- is an evolving experiment with an aim to kindle entrepreneurial mindsets in the remotest locations of India in an accessible and engaging manner. At the heart of this experiment is the belief that at every phase in our life’s story, we have a choice which brings us closer to achieving our true potential. This interactive program is thus designed using real-time storytelling principles to empower learners, ages 24 and below, to make choices and take decisions as they become more self-aware, practice grit, try new things through stories, guided activities, and interactions, simply over a phone call. This research paper highlights the framework behind an ongoing scalable, data-oriented, low-tech program to kindle entrepreneurial mindsets in media dark zones supported by iterative design and prototyping to reach 13700+ unique learners who made 59000+ calls for 183900+min listening duration to listen to content pieces of around 3 to 4 min, with the last monitored (March 2022) record of 34% serious listenership, within one and a half years of its inception. The paper provides an in-depth account of the technical development, content creation, learning, and assessment frameworks, as well as mobilization models which have been leveraged to build this end-to-end system.

Keywords: non-cognitive skills, entrepreneurial mindsets, speech interface, remote learning, storytelling

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Fatin Mansour Daas

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Language education responds to and is reflective of emerging social and political trends. Language policies and practices are shaped by political, economic, social and cultural considerations. Following this, Israeli language education policy as implemented in Arab schools in Israel is influenced by the particular political and social situation of Arab-Palestinian citizens of Israel. This national group remained in their homeland following the war in 1948 between Israel and its Arab neighbors and became Israeli citizens following the establishment of the State of Israel. This study examines language policy in Arab schools in Israel from 1948 until the present time in light of the unique experience of the Palestinian Arab homeland minority in Israel with a particular focus on questions of politics and identity. The establishment of the State of Israel triggered far-reaching political, social and educational transformations within Arab Palestinian society in Israel, including in the area of language and language studies. Since 1948, the linguistic repertoire of Palestinian Arabs in Israel has become more complex and diverse, while the place and status of different languages have changed. Following the establishment of the State of Israel, only Hebrew and Arabic were retained as the official languages, and Israeli policy reflected this in schools as well: with the advent of the Jewish state, Hebrew language education among Palestinians in Israel has increased. Similarly, in Arab Palestinian schools in Israel, English is taught as a third language, Hebrew as a second language, and Arabic as a first language – even though it has become less important to native Arabic speakers. This research focuses on language studies and language policy in the Arab school system in Israel from 1948 onwards. It will analyze the relative focus of language education between the different languages, the rationale of various language education policies, and the pedagogic approach used to teach each language and student achievements vis-à-vis language skills. This study seeks to understand the extent to which Arab schools in Israel are multi-lingual by examining successes, challenges and difficulties in acquiring the respective languages. This qualitative study will analyze five different components of language education policy: (1) curriculum, (2) learning materials; (3) assessment; (4) interviews and (5) archives. Firstly, it consists of an analysis examining language education curricula, learning materials and assessments used in Arab schools in Israel from 1948-2018 including a selection of language textbooks for the compulsory years of study and the final matriculation (Bagrut) examinations. The findings will also be based on archival material which traces the evolution of language education policy in Arabic schools in Israel from the years 1948-2018. This archival research, furthermore, will reveal power relations and general decision-making in the field of the Arabic education system in Israel. The research will also include interviews with Ministry of Education staff who provide instructional oversight in the instruction of the three languages in the Arabic education system in Israel. These interviews will shed light on the goals of language education as understood by those who are in charge of implementing policy.

Keywords: language education policy, languages, multilingualism, language education, educational policy, identity, Palestinian-Arabs, Arabs in Israel, educational school system

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Uwaruile Austin Obuh

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This research work focuses on the use of computers in improving the academic performance of students in mathematics in Benin City, Edo State. To guide this study, two research questions were raised, and two corresponding hypotheses were formulated. A total of one hundred and twenty (120) respondents were randomly selected from four schools in the city (60 boys and 60 girls). The instrument employed for the collation of data for the study was the multiple-choice test items on geometry (MCTIOG), drawn from past senior school certificate examinations (SSCE) questions. The instrument was validated by an expert in mathematics and measurement and evaluation. The data obtained from the pre and post-test were analysed using the mean, standard deviation, and T-test. The study revealed a non-significant difference between the experimental and control group in the pre-test, and the two groups were found to be the same before treatment began. The study also revealed that the experimental group performed better than the control group. One can, therefore, conclude that the use of computers for mathematics instruction has improved the performance of students in Geometry. Therefore, the hypothesis was rejected. The study finally revealed that there was no significant difference between the boys and girls taught mathematics using a computer. Therefore, the hypothesis which states there will be no significant difference in the performance of boys and girls taught mathematics using the computer was not rejected. Consequent upon the findings of this study, a number of recommendations were postulated that would enhance the performance of teachers in the use of computer-aided instruction.

Keywords: computer, teaching, learning, mathematics

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: John D. Sanderson

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The popularity of American cinema worldwide has contributed to the development of sociolects related to specific film genres in other cultural contexts by means of screen translation, in many cases eluding norms of usage in the target language, a process whose result has come to be known as 'dubbese'. A consequence for the reception in countries where local audiovisual fiction consumption is far lower than American imported productions is that this linguistic construct is preferred, even though it differs from common everyday speech. The iconography of film genres such as science-fiction, western or sword-and-sandal films, for instance, generates linguistic expectations in international audiences who will accept more easily the sociolects assimilated by the continuous reception of American productions, even if the themes, locations, characters, etc., portrayed on screen may belong in origin to other cultures. And the non-normative language (e.g., calques, semantic loans) used in the preferred mode of linguistic transfer, whether it is translation for dubbing or subtitling, has diachronically evolved in many cases into a status of canonized sociolect, not only accepted but also required, by foreign audiences of American films. However, a remarkable step forward is taken when this typology of artificial linguistic constructs starts being used creatively by nationals of these target cultural contexts. In the case of Spain, the success of American sitcoms such as Friends in the 1990s led Spanish television scriptwriters to include in national productions lexical and syntactical indirect borrowings (Anglicisms not formally identifiable as such because they include elements from their own language) in order to target audiences of the former. However, this commercial strategy had already taken place decades earlier when Spain became a favored location for the shooting of foreign films in the early 1960s. The international popularity of the then newly developed sub-genre known as Spaghetti-Western encouraged Spanish investors to produce their own movies, and local scriptwriters made use of the dubbese developed nationally since the advent of sound in film instead of using normative language. As a result, direct Anglicisms, as well as lexical and syntactical borrowings made up the creative writing of these Spanish productions, which also became commercially successful. Interestingly enough, some of these films were even marketed in English-speaking countries as original westerns (some of the names of actors and directors were anglified to that purpose) dubbed into English. The analysis of these 'back translations' will also foreground some semantic distortions that arose in the process. In order to perform the research on these issues, a wide corpus of American films has been used, which chronologically range from Stagecoach (John Ford, 1939) to Django Unchained (Quentin Tarantino, 2012), together with a shorter corpus of Spanish films produced during the golden age of Spaghetti Westerns, from una tumba para el sheriff (Mario Caiano; in English lone and angry man, William Hawkins) to tu fosa será la exacta, amigo (Juan Bosch, 1972; in English my horse, my gun, your widow, John Wood). The methodology of analysis and the conclusions reached could be applied to other genres and other cultural contexts.

Keywords: dubbing, film genre, screen translation, sociolect

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Authors: Cristina Maria Mendoza Sanchez, Maria Angeles Navarro Perán

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Introduction: Nursing as a profession, from its initial formation and after its development in practice, has been built and identified mainly from its technical competence and professionalization within the positivist approach of the XIX century that provides a conception of the disease built on the basis of to the biomedical paradigm, where the care provided is more focused on the physiological processes and the disease than on the suffering person understood as a whole. The main issue that is in need of study here is a review of the nursing profession's history to get to know how the nursing profession was before the XIX century. It is unclear if there were organizations or people with knowledge about looking after others or if many people survived by chance. The holistic care, in which the appearance of the disease directly affects all its dimensions: physical, emotional, cognitive, social and spiritual. It is not a concept from the 21st century. It is common practice, most probably since established life in this world, with the final purpose of covering all these perspectives through quality care. Objective: In this paper, we describe and analyze the history of education in nursing learning in terms of reviewing and analysing theoretical foundations of clinical teaching and learning in nursing, with the final purpose of determining and describing the development of the nursing profession along the history. Method: We have done a descriptive systematic review study, doing a systematically searched of manuscripts and articles in the following health science databases: Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL. The selection of articles has been made according to PRISMA criteria, doing a critical reading of the full text using the CASPe method. A compliment to this, we have read a range of historical and contemporary sources to support the review, such as manuals of Florence Nightingale and John of God as primary manuscripts to establish the origin of modern nursing and her professionalization. We have considered and applied ethical considerations of data processing. Results: After applying inclusion and exclusion criteria in our search, in Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL, we have obtained 51 research articles. We have analyzed them in such a way that we have distinguished them by year of publication and the type of study. With the articles obtained, we can see the importance of our background as a profession before modern times in public health and as a review of our past to face challenges in the near future. Discussion: The important influence of key figures other than Nightingale has been overlooked and it emerges that nursing management and development of the professional body has a longer and more complex history than is generally accepted. Conclusions: There is a paucity of studies on the subject of the review to be able to extract very precise evidence and recommendations about nursing before modern times. But even so, as more representative data, an increase in research about nursing history has been observed. In light of the aspects analyzed, the need for new research in the history of nursing emerges from this perspective; in order to germinate studies of the historical construction of care before the XIX century and theories created then. We can assure that pieces of knowledge and ways of care were taught before the XIX century, but they were not called theories, as these concepts were created in modern times.

Keywords: nursing history, nursing theory, Saint John of God, Florence Nightingale, learning, nursing education

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Kevin R. Wilson, Roger Mantie

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Community arts-based learning and participatory education are pedagogical techniques that serve to be advantageous for students, curriculum development, and local communities. Using an interpretive approach to examine the significance of this arts-informed research in relation to the eight ‘design imperatives’ proposed as the new model for measuring quality in scholarship for Arizona State University as ‘A New American University’, the purpose of this study was to investigate personal, social, and cultural benefits resulting from student engagement in interdisciplinary community-based projects. Students from a graduate level music education class at the ASU Tempe campus (n=7) teamed with students from an undergraduate level community development class at the ASU Downtown Phoenix campus (n=14) to plan, facilitate, and evaluate seven community-based projects in several locations around the Phoenix-metro area. Data was collected using photo evidence, student reports, and evaluative measures designed by the students. The effectiveness of each project was measured in terms of their ability to meet the eight design imperatives to: 1) leverage place; 2) transform society; 3) value entrepreneurship; 4) conduct use-inspired research; 5) enable student success; 6) fuse intellectual disciplines; 7) be socially embedded; and 8) engage globally. Results indicated that this community arts-based project sufficiently captured the essence of each of these eight imperatives. Implications for how the nature of this interdisciplinary initiative allowed for the eight imperatives to manifest are provided, and project success is expounded upon in relation to utility of each imperative. Discussion is also given for how this type of service learning project formatted within the ‘New American University’ model for measuring quality in academia can be a beneficial pedagogical tool in higher education.

Keywords: community arts-based learning, participatory education, pedagogy, service learning

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Authors: Florence A. Undiyaundeye, Aniashie Akpanke

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Early identification of developmental disorders in infants and toddlers is critical for the well being of children. It is also an integral function of the primary care medical provider and the early care given in the home or crèche. This paper is focused at providing information on special need infants and toddlers and strategies to support them in developmental concern to cope with the challenges in and out of the classroom and to interact with their peers without stigmatization and inferiority complex. The target children are from birth through three years of age. There is a strong recommendation for developmental surveillance to be incorporated at every well child preventive care program in training and practical stage of formal school settings. The paper posits that any concerns raised during surveillance should be promptly addressed with standardized developmental screening by appropriate health service providers. In addition screening tests should be administered regularly at age 9+, 19+ and 30 months of these infants. The paper also establishes that the early identification of these developmental challenges of the infants and toddlers should lead to further developmental and medical evaluation, diagnosis and treatment, including early developmental school intervention, control and teaching and learning integration and inclusion for proper career build up. Children diagnosed with developmental disorders should be identified as children with special needs so that management is initiated and its underlying etiology may also drive a range of treatment of the child, to parents. Conselling and school integration as applicable to the child’s specific need and care for sustenance in societal functioning.

Keywords: care, special need, support, infants and toddlers, management and developmental disorders

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Authors: Zakir Hossain

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Nowadays reading e-books on laptops, smartphones, and tablets have become a new leisure activity for Vietnamese youth. Since 2011 the copyrighted e-book market began to develop in Vietnam with the participation of five local enterprises. Over the last five years, thousands of e-books were published including the first online early education book series for children from 0 to 6 years old. Research shows that 61% Vietnamese find reading e-books is comfortable, and 45% feel convenient buying books online. More than half of the Vietnamese consider reading online far better than buying printed books, and surprisingly people over age 30 desire reading online while those under 18 prefer reading printed books. Hence with a market of more than 40 million regular internet users including 22 million smartphone users, Vietnam has ample opportunities to develop the e-book market and contribute a great deal to the diversity of the local reading culture which is essential for Building a Lifelong Learning Society, a state ambition of Vietnam by 2020. However, the e-book market in Vietnam is still in its infancy and is growing far too slowly than e-book producers had expected. All five e-book enterprises are facing numerous challenges. While the big profit that e-book technology can bring has been clearly recognised in other countries, e-books in Vietnam only make up less than 1% share of the book market. The objective of the study is to identify the difficulties and barriers to the development of the e-book market in Vietnam through an extensive literature review available in English. The study revealed that illegal e-books due to copyright infringement and an inconvenient payment system to purchase e-books are the major obstacles. The great potential of e-books in Vietnam is a reality but requires government enforcement of copyright protection laws, a new area of focus for the e-book market. Furthermore, Vietnamese readers should change their habits from using free and illegal e-books to develop the e-publishing industry in Vietnam.

Keywords: copyright, e-book, e-book reading, e-publishing, Vietnam

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Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

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Authors: Ahmad Saleem

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Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

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Authors: Naor Cohen

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In recent years, business schools made teaching ethical leadership a higher priority. Greater attention to moral and ethical concepts and reasoning processes may prove beneficial to future business leaders. But with a shift in focus, there is a need for a shift in pedagogy. This paper explores an imaginative literature-based pedagogy in the teaching of ethical leadership. An imaginative literature-based pedagogy uses works of fiction to help students build moral analysis and moral judgment capabilities through a rigorous assessment of the moral soundness of actions, motivations, rationales, and consequences portrayed in works of fiction. Business students enrolled in 4 leadership senior-level courses were assigned the White Tiger: A Novel by Aravind Adiga as their main course reading. Students' engagement was measured as a three-factor construct exploring cognitive engagement, behavioural engagement and emotional engagement. In addition, students' final papers were analyzed using thematic content analysis. This paper will present the results of this analysis and argue that incorporating fiction into the leadership curriculum allows students to explore the dire consequences of avoiding countervailing interests, engaging in dishonesty and engaging in moral puffery-based leadership.

Keywords: ethical leadership, empathetic imagination, business education, pedagogy, fiction

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Authors: Rohan Roberts

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The purpose of this project was to collaborate with a group of high-functioning, more-able students (aged 15-18) to promote STEM Education and a love for science by bringing a cosmic perspective into the classroom and high school environment. This was done using 21st century science of learning, a focus on the latest research on Neuroeducation, and modern pedagogical methods based on Howard Gardner's theory of Multiple Intelligences, Bill Lucas’ theory of New Smarts, and Sir Ken Robinson’s recommendations on encouraging creativity. The result was an increased sense of passion, excitement, and wonder about science in general, and about the marvels of space and the universe in particular. In addition to numerous unique and innovative science-based initiatives, clubs, workshops, and science trips, this project also saw a marked rise in student-teacher collaboration in science learning and in student engagement with the general public through the press, social media, and community-based initiatives. This paper also outlines the practical impact that bringing a cosmic perspective into the classroom has had on the lives, interests, and future career prospects of the students involved in this endeavour.

Keywords: cosmic perspective, gifted and talented, neuro-education, STEM education

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Authors: Rabih Joseph Nabhan

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This case study explores the impact of two major computer software programs Learn to Speak English and Learn English Spelling and Pronunciation, and some Internet search engines such as Google on mending the decoding and spelling deficiency of Simon X, a dyslexic student. The improvement in decoding and spelling may result in better reading comprehension and composition writing. Some computer programs and Internet materials can help regain the missing awareness and consequently restore his self-confidence and self-esteem. In addition, this study provides a systematic plan comprising a set of activities (four computer programs and Internet materials) which address the problem from the lowest to the highest levels of phoneme and phonological awareness. Four methods of data collection (accounts, observations, published tests, and interviews) create the triangulation to validly and reliably collect data before the plan, during the plan, and after the plan. The data collected are analyzed quantitatively and qualitatively. Sometimes the analysis is either quantitative or qualitative, and some other times a combination of both. Tables and figures are utilized to provide a clear and uncomplicated illustration of some data. The improvement in the decoding, spelling, reading comprehension, and composition writing skills that occurred is proved through the use of authentic materials performed by the student under study. Such materials are a comparison between two sample passages written by the learner before and after the plan, a genuine computer chat conversation, and the scores of the academic year that followed the execution of the plan. Based on these results, the researcher recommends further studies on other Lebanese dyslexic learners using the computer to mend their language problem in order to design and make a most reliable software program that can address this disability more efficiently and successfully.

Keywords: analysis, awareness, dyslexic, software

Procedia PDF Downloads 207