Search results for: online teaching and learning

Authors: L. Freeborn

Abstract:

This paper discusses the application of complex dynamic system theory (DST) to the study of individual differences in second language development. This transdisciplinary framework allows researchers to view the trajectory of language development as a dynamic, non-linear process. A DST approach views language as multi-componential, consisting of multiple complex systems and nested layers. These multiple components and systems continuously interact and influence each other at both the macro- and micro-level. Dynamic systems theory aims to explain and describe the development of the language system, rather than make predictions about its trajectory. Such a holistic and ecological approach to second language development allows researchers to include various research methods from neurological, cognitive, and social perspectives. A DST perspective would involve in-depth analyses as well as mixed methods research. To illustrate, a neurobiological approach to second language development could include non-invasive neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate areas of brain activation during language-related tasks. A cognitive framework would further include behavioural research methods to assess the influence of intelligence and personality traits, as well as individual differences in foreign language aptitude, such as phonetic coding ability and working memory capacity. Exploring second language development from a DST approach would also benefit from including perspectives from the field of applied linguistics, regarding the teaching context, second language input, and the role of affective factors such as motivation. In this way, applying mixed research methods from neurobiological, cognitive, and social approaches would enable researchers to have a more holistic view of the dynamic and complex processes of second language development.

Keywords: dynamic systems theory, mixed methods, research design, second language development

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Houxiang Zhu, Chun Liang

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The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. The published CRISPR-Cpf1 gRNA data was reanalyzed. Many sequences and structural features of gRNAs (e.g., the position-specific nucleotide composition, position-nonspecific nucleotide composition, GC content, minimum free energy, and melting temperature) correlated with target efficiency were found. Using machine learning technology, a support vector machine (SVM) model was created to predict target efficiency for any given gRNAs. The first web service application, CRISPR-DT (CRISPR DNA Targeting), has been developed to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT will empower researchers in genome editing.

Keywords: CRISPR-Cpf1, genome editing, target efficiency, target specificity

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Authors: Nidhi Kaushal, Sanjit Mishra

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Narrative writings in literature are ample source of knowledge and easily understandable. In every old tradition, we found that people learn ethics from oral tales. They had their leaders and lessons of leadership in their stories. In India, we have sufficient amount of stories of leaders. Whether the story is of an ordinary person or a corporate leader of large firm, it always has a unique message of motivation. The objective of this paper is to elaborate the story lines in literature and get the leadership lessons from them, so that we can set up a new concept of leadership based on scholarship of literature. This is our hypothesis that leadership lessons can be learned from the study of literary writings and it can also act an innovative way of learning the management skills through literature. The role of the leader can be familiarly communicated in the form of the tales. Describing a positive psychological narrative from the text is the best way to manifesting an idea into the minds of people. We accomplished this paper that leadership as an attribute can be learned from the folk psychological literary writings.

Keywords: leadership, literature, management, psychology

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Authors: Chunfang Zhou

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The growing issues of sustainability have increased the discussions on how to foster “green engineers” from diverse perspectives in both contexts of education and organizations. As creativity has been considered as the first stage of innovation process that can also be regarded as a path to sustainability, this paper will particularly propose creativity as a scientific literacy meaning a collection of awareness, ability, and skills about sustainability. From this sense, creativity should be an element in IT engineering education and organizational learning programmes, since IT engineers are one group of key actors in designing, researching and developing social media products that are most important channels of improving public awareness of sustainability. This further leads this paper to discuss by which pedagogical strategies and by which training methods in organizations, creativity and sustainability can be integrated into IT engineering education and IT enterprise innovation process in order to meeting the needs of ‘creative engineers’ in the society changes towards sustainability. Accordingly, this paper contributes to future work on the links between creativity, innovation, sustainability, and IT engineering development both theoretically and practically.

Keywords: creativity, innovation, IT engineers, sustainability

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Authors: Chad Brown

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This paper establishes general conditions for the convergence rates of nonparametric sieve estimators with dependent data. We present two key results: one for nonstationary data and another for stationary mixing data. Previous theoretical results often lack practical applicability to deep neural networks (DNNs). Using these conditions, we derive convergence rates for DNN sieve estimators in nonparametric regression settings with both nonstationary and stationary mixing data. The DNN architectures considered adhere to current industry standards, featuring fully connected feedforward networks with rectified linear unit activation functions, unbounded weights, and a width and depth that grows with sample size.

Keywords: sieve extremum estimates, nonparametric estimation, deep learning, neural networks, rectified linear unit, nonstationary processes

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: Mikko Salminen, Simo Järvelä, Niklas Ravaja

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One of the central models of emotional intelligence (EI) is that of Mayer and Salovey’s, which includes ability to monitor own feelings and emotions and those of others, ability to discriminate different emotions, and to use this information to guide thinking and actions. There is vast amount of previous research where positive links between EI and, for example, leadership successfulness, work outcomes, work wellbeing and organizational climate have been reported. EI has also a role in the effectiveness of work teams, and the effects of EI are especially prominent in jobs requiring emotional labor. Thus, also the organizational context must be taken into account when considering the effects of EI on work outcomes. Based on previous research, it is suggested that EI can also protect managers from the negative consequences of stress. Stress may have many detrimental effects on the manager’s performance in essential work tasks. Previous studies have highlighted the effects of stress on, not only health, but also, for example, on cognitive tasks such as decision-making, which is important in managerial work. The motivation for the current study came from the notion that, unfortunately, many stressed individuals may not be aware of the circumstance; periods of stress-induced physiological arousal may be prolonged if there is not enough time for recovery. To tackle this problem, physiological stress levels of managers were collected using recording of heart rate variability (HRV). The goal was to use this data to provide the managers with feedback on their stress levels. The managers could access this feedback using a www-based learning environment. In the learning environment, in addition to the feedback on stress level and other collected data, also developmental tasks were provided. For example, those with high stress levels were sent instructions for mindfulness exercises. The current study focuses on the relation between the measured physiological stress levels and EI of the managers. In a pilot study, 33 managers from various fields wore the Firstbeat Bodyguard HRV measurement devices for three consecutive days and nights. From the collected HRV data periods (minutes) of stress and recovery were detected using dedicated software. The effects of EI on HRV-calculated stress indexes were studied using Linear Mixed Models procedure in SPSS. There was a statistically significant effect of total EI, defined as an average score of Schutte’s emotional intelligence test, on the percentage of stress minutes during the whole measurement period (p=.025). More stress minutes were detected on those managers who had lower emotional intelligence. It is suggested, that high EI provided managers with better tools to cope with stress. Managing of own emotions helps the manager in controlling possible negative emotions evoked by, e.g., critical feedback or increasing workload. High EI managers may also be more competent in detecting emotions of others, which would lead to smoother interactions and less conflicts. Given the recent trend to different quantified-self applications, it is suggested that monitoring of bio-signals would prove to be a fruitful direction to further develop new tools for managerial and leadership coaching.

Keywords: emotional intelligence, leadership, heart rate variability, personality, stress

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Authors: Thomas J. Bell III

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Pursuing a business degree is fraught with perplexing questions regarding the rising tuition cost and the immediate value of earning a degree. Any decision to pursue an undergraduate business degree is perceived to have value if it facilitates post-graduate job placement. Business programs have decreased value in the absence of innovation in business programs that close the skills gap between recent graduates and employment opportunities. Industry-based certifications are seemingly becoming a requirement differentiator among job applicants. Texas Wesleyan University offers a Computer Information System (CIS) program with an innovative curriculum that integrates industry-recognized certification training into its traditional curriculum with core subjects and electives. This paper explores a culture of innovation in the CIS business program curriculum that creates sustainable stakeholder value for students, employers, the community, and the university. A quantitative research methodology surveying over one-hundred students in the CIS program will be used to examine factors influencing the success or failure of students taking certification exams. Researchers will analyze control variables to identify specific correlations between practice exams, teaching pedagogy, study time, age, work experience, etc. This study compared various exam preparation techniques to corresponding exam results across several industry certification exams. The findings will aid in understanding control variables with correlations that positively and negatively impact exam results. Such discovery may provide useful insight into pedagogical impact indicators that positively contribute to certification exam success and curriculum enhancement.

Keywords: taking certification exams, exam training, testing skills, exam study aids, certification exam curriculum

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Authors: Elysee Guy Yohou

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Côte d'Ivoire established a National Commission for Sustainable Development with a view to implementing the ESD. This study aims to understand the knowledge, attitude and practice about education for sustainability of teachers, students, principals, and staff in secondary schools in Côte d’Ivoire while exploring the barriers, levers and examines the leadership skills needed to help carrying out ESD. The data collection took place in October and December 2015. Questionnaires were administered to 400 participants, which involved teachers, students, principals and staff in 25 public and private secondary schools in four regional offices of education. 297 questionnaires were collected producing a collection-rate of 74.25%. Descriptive statistics, independent t-test, dependent sample t-test, One way ANOVA, Pearson correlation were used to analyze the data. Thereupon, knowledge, attitudes about education for sustainability of teachers, principals and staff in secondary school are better than students. However, there is little practice of ESD. 68.3% of participants are not familiar with the Decade of Education for Sustainable Development. In addition, 92.8% of schools do not have a school Agenda 21. The major barriers that prevent the teaching of education for sustainability are lack of access to technical tools, insufficient funding and lack of information. The main levers are teacher and staff training, financing, awareness of students, and public engagement. Principals do possess good human and technical skills but limited conceptual skills. The study showed that conceptual and human skills are convenient assets which rhyme more with education for sustainability. Thereupon, if schools’ principal need to improve education for sustainability through practice, they need more conceptual skills.

Keywords: Côte d'Ivoire, education for sustainability, leadership skills, secondary school

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Authors: Mohamed Nabhan

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The research aims to build a measure of sensory preferences for (wrestling and boxing) players. The researchers used the descriptive approach and a sample of (8) consisting of (40) wrestling players, (40) boxing players with different scales, and they were chosen in a deliberate random way, and the most important results were that there were statistically significant differences between wrestlers and boxers in the sensory preferences of their senses. There is no indication in the sensory preferences for the senses of “sight and hearing” and that the significance is in favor of the wrestlers in the senses of “sight and touch,” and there is a convergence in the sense of hearing. Through the value of the averagesAfter collecting the data and statistical treatments and the results reached by the researcher, it was possible to reach: The following conclusions and recommendations: There are differences between wrestling and boxing players in their sensory preferences, the senses used in learning, due to several reasons, the most important of which may be as follows:- Scales for the player and for each sport separately. The nature of the game, the performance of skills, and dealing with the opponent or competitor.Tools used in performance and training.

Keywords: sensory preferences, sensory scale, wrestling players, boxing players

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: Bhavna Malik

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The study is build on a theoretical framework that links characteristics of job, key attitudes and intention to leave, why faculty may be disengaging from institutional service. The literature indicates that job characteristics, key attitudes and intention to leave are very important for effective organizational functioning. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attitudes predicted intention to leave negatively. The present study attempted to propose a new integrative model of the relationships among job characteristics, key attitudes, and intention to leave. The main purpose of the present study is to examine the effects of job characteristics on intention to leave. While examining the role of job characteristics, the mediating roles of key attitudes were taken into account in order to better understand how job characteristics affect the exhibition of intention to leave. The secondary purpose is to investigate the effects of job characteristics on key attitudes, and the effects of key attitudes on intention to leave. Job characteristics of remuneration, resource for professional activities, career opportunities were positively associated with the work attitude of job satisfaction. The aggregate job scope was positively associated with the work attitude of organizational commitment although no single job characteristic was significantly associated with organizational commitment. Commitment, however, did not significantly affect time spent on institutional service. Two job characteristics—time spent on research and time spent on teaching—were negatively associated with this behavior. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attiudes predicted intention to leave negatively. In turn, job satisfaction and organizational commitment were negatively associated with the intention to leave. In addition to these, organizational commitment was negatively associated with the intention to leave. However, no significant direct association was found between job characteristics and intention to leave.

Keywords: Job Characteristics Model, job satisfaction, organizational commitment, intention to leave

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Authors: Ya-Hui Lee, Ching-Yi Lu, Hui-Chuan Wei

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The purpose of this research was to explore the relation between proactive coping and well-being of middle-aged adults. We conducted survey research that with t-test, one way ANOVA, Pearson correlation and stepwise multiple regression to analyze. This research drew on a sample of 395 participants from the senior learning centers of Taiwan. The results provided the following findings: 1.The participants from different residence areas associated significant difference with proactive coping, but not with well-being. 2. The participants’ perceived of financial level associated significant difference with both proactive coping and well-being. 3. There was significant difference between participants’ income and well-being. 4. The proactive coping was positively correlated with well-being. 5. From stepwise multiple regression analysis showed that two dimensions of proactive coping had positive predictability. Finally, these results of this study can be provided as references for designing older adult educational programs in Taiwan.

Keywords: middle-age and older adults, learners, proactive coping, well-being

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Authors: Rahime Filiz Kiremit

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This study identifies six different articles to explain which strategies are most effective for kindergarten English Language Learners. The literature review project has information about six different research articles, purpose of the studies, and results of the studies. There are several strategies can be used for ELL students to help them to develop their English language skills. Some articles mention technology as a multimedia integrated into the curriculum, some of them mention writing as a method of learning English as a second language. However, they all have a common strategy that is shared reading. According to these six articles, shared reading has a big role of ELL students’ language developmental process. All in all, read-aloud with multimedia enhancement strategy is the best strategy to use in the classroom, because this strategy is based on shared reading and also integrated with technology.

Keywords: bilingual education, effective strategies, english language learners, kindergarten

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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Authors: Ammar Ayad Issa Al-Rifaie, Zuhreya Muazu, Maysam Ali Abdulwahid, Dermot Gleeson

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The aim of this audit was to examine the efficiency of alcohol history documentation and screening for hazardous drinkers at the Medical Admission Unit (MAU) of Northern General Hospital (NGH), Sheffield, to identify any potential for enhancing clinical practice. Data were collected from medical clerking sheets, ICE system and directly from 82 patients by three junior medical doctors using both CAGE questionnaire and AUDIT-C tool for newly admitted patients to MAU in NGH, in the period between January and March 2015. Alcohol consumption was documented in around two-third of the patient sample and this was documented fairly accurately by health care professionals. Some used subjective words such as 'social drinking' in the alcohol units’ section of the history. CAGE questionnaire was applied to only four patients and none of the patients had documented advice, education or referral to an alcohol liaison team. AUDIT-C tool had identified 30.4%, while CAGE 10.9%, of patients admitted to the NGH MAU as hazardous drinkers. The amount of alcohol the patient consumes positively correlated with the score of AUDIT-C (Pearson correlation 0.83). Re-audit is planned to be carried out after integrating AUDIT-C tool as labels in the notes and presenting a brief teaching session to junior doctors. Alcohol misuse screening is not adequately undertaken and no appropriate action is being offered to hazardous drinkers. CAGE questionnaire is poorly applied to patients and when satisfactory and adequately used has low sensitivity to detect hazardous drinkers in comparison with AUDIT-C tool. Re-audit of alcohol screening practice after introducing AUDIT-C tool in clerking sheets (as labels) is required to compare the findings and conclude the audit cycle.

Keywords: alcohol screening, AUDIT-C, CAGE, hazardous drinking

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Authors: Aisha Iddrsiu

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Public Relations (PR) has rapidly evolved around the world, just as companies have expanded to reach other parts of the world. With most multinational corporations conducting businesses in more than one country, only a few of these Multinational Corporations (MNC’s) are actual public relations firms, many have public relations departments or divisions that conduct public relations practices internationally. Hence international public relations is seen as a fast-growing specialty in the field of Public Relations. Multinational companies have devised strategies to effectively communicate and execute their roles within and between foreign publics and other cultures in which they operate through various means including the internet which is among the major inventions that have enabled corporations to establish their presents while targeting anonymous and diverse publics from varied cultures. International public relations practitioners rely on strategies coupled with internet use to communicate among and with foreign publics. Corporate websites and various social media handles have served as an important channel for public relations activities targeting both internal and international publics. In an incessant expansion of corporations and interactions with the publics from different cultures, it has become eminent to understand the public relation strategies used by MNCs in their international communication. This study therefore seeks to establish the international public relation strategies or models employed by Multinational Corporations specifically Arcelik Global in the management of its subsidiaries and communicating with international public. This study analyses both Arçelik global’s (one of the largest multinational companies in Turkey) website and social media accounts to understand the management strategy used with it subsidiary as well as strategies used to communicate with its global and local publics. Other underlying objective of this study are, 1. To examine the dominant international public relations models used by Multinational Corporations (Arcelik global). 2. To understand how Multinational Corporations manage (Arcelik global) its subsidiaries. 3. To understand how Multinational Corporations (Arcelik global) communicate with international or global publics. Research Questions 1. The main global PR strategies employed by multinational corporations (Arcelik global) 2. How subsidiaries of multinational corporations like Arcelik Global are managed. 3. How multinational corporations, like Arcelik worldwide, interact with international publics.

Keywords: multinational corporation, ethnocentric model, polycentric model, international public relations

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Authors: F. Arıkan, Z. Karakus

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Cancer is a widespread disease in the world and is the third reason of deaths among the chronic diseases. Educating patients and caregivers has a vital role for empowering them in managing disease and treatment's symptoms. Informing of the patients about their disease and treatment process decreases patient's distress and decisional conflicts, improves wellbeing of them, increase success of the treatment and survival. In this era, technological education methods are used for patients that have different chronic disease. Many studies indicated that especially web based patient education such as chronic obstructive lung disease; heart failure is more effective than printed materials. Web based education provide easiness to patients while they are reaching health services. It also has more advantages because of it decreases health cost and requirement of staff. It is thought that web based education may be beneficial method for cancer patient's empowerment in coping with the disease's symptoms. The aim of the study is evaluate the effectiveness of web based education for cancer patients' clinical outcomes.

Keywords: cancer patients, e-learning, nursing, web based education

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Authors: Alvaro Armenta-Ramade, Arturo Serrano-Santoyo, Veronica Rojas-Mendizabal, Roberto Conte-Galvan

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The availability and affordability of commercial off-the-shell products have brought a major impetus in the development of university projects related to the design, construction and launching of small satellites on a global scale. Universities in emerging economies as well as in least developed countries have been able to develop prototypes of small satellites (cubesats and cansats) with limited budgets. The experience gained in the development of small satellites gives rise to capacity building for designing more complex aerospace systems. This trend has significantly increased the pace and number of aerospace university projects around the world. In the case of Mexico, projects funded by different agencies have been very effective in accelerating the capacity building and technology transfer initiatives in the aerospace ecosystem. However, many of this initiatives have centered their efforts in technology development matters with minimum or no considerations of key regulatory issues related to frequency assignment, management and licensing, as well as launching requirements and measures of mitigation of space debris. These regulatory concerns are fundamental to accomplish successful missions that take into account the complete value chain of an aerospace project. The purpose of this paper is to develop a regulatory framework to support the efforts of educational institutions working on the development of small satellites in Mexico. We base our framework on recommendations from the International Telecommunications Union (ITU), the United Nations Office for Outer Space Affairs (UNOOSA) and other major actors of the Mexican regulatory ecosystem. In order to develop an integrated and cohesive framework, we draw on complexity science to identify the agents, their role and interactions. Our goal is to create a guiding instrument available both in print and online that can also be used in other regions of the world

Keywords: capacity building, complexity science, cubesats, space regulations, small satellites

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Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

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Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

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Authors: Khaled ElEbyary, Ramy Shabara

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L2 research has generally acknowledged the role of noticing in language learning. The role of teacher feedback is to trigger learners’ noticing of errors and direct the writing process. Recently L2 learners are seemingly using computerized applications which provide corrective feedback (CF) at different stages of writing (i.e., during and after writing). This study aimed principally to answer the question, “Is noticing likely to be maximized when feedback on erroneous output is electronically provided either during or after the composing stage, or does teacher annotated feedback have a stronger effect?”. Seventy-five participants were randomly distributed into four groups representing four conditions. These include receiving automated feedback at the composing stage, automated feedback after writing, teacher feedback, and no feedback. Findings demonstrate the impact of CF on writing and the intensity of noticing certain language areas at different writing stages and from different feedback sources.

Keywords: written corrective feedback, error correction, noticing, automated written corrective feedback, L2 acquisition

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Authors: V. Nikkhah Rashidabad, M. Manteghian, M. Masoumi, S. Mousavian, D. Ashouri

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In this research, the capability of neural networks in modeling and learning complicated and nonlinear relations has been used to develop a model for the prediction of changes in the diameter of bubbles in pool boiling distilled water. The input parameters used in the development of this network include element temperature, heat flux, and retention time of bubbles. The test data obtained from the experiment of the pool boiling of distilled water, and the measurement of the bubbles form on the cylindrical element. The model was developed based on training algorithm, which is typologically of back-propagation type. Considering the correlation coefficient obtained from this model is 0.9633. This shows that this model can be trusted for the simulation and modeling of the size of bubble and thermal transfer of boiling.

Keywords: bubble diameter, heat flux, neural network, training algorithm

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Authors: S. Thongchai

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Result of the study on knowledge management systems in businesses was shown that the most of these businesses provide internet accessibility for their employees in order to study new knowledge via internet, corporate website, electronic mail, and electronic learning system. These business organizations use information technology application for knowledge management because of convenience, time saving, ease of use, accuracy of information and knowledge usefulness. The result indicated prominent improvements for corporate knowledge management systems as the following; 1) administrations must support corporate knowledge management system 2) the goal of corporate knowledge management must be clear 3) corporate culture should facilitate the exchange and sharing of knowledge within the organization 4) cooperation of personnel of all levels must be obtained 5) information technology infrastructure must be provided 6) they must develop the system regularly and constantly.

Keywords: business organizations, information technology application, knowledge management systems, prominent improvements

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Authors: Razan Salem

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This study aims to investigate the investment behavior of Arab women (in regards to their herding behavior, risk tolerance, confidence and investment literacy levels). This study aims to investigate the relationship between three demographic factors (age, income, education) and the investment behavior of Arab women. On average, women in the Arab region face several obstacles that limit them from fully participating in stocks investments. In the context, this study focuses on extending the existing literature to include Arab women individuals and their investment behaviors. To achieve the study’s objective, the researcher distributed 600 close-ended online questionnaires to a sample of Arab male and female individual investors in both Saudi Arabia and Jordan. The researcher used quantitative statistical methods (frequency distribution along with the Kruskal-Wallis H Test and the Mann-Whitney U Test) to analyze the 550 questionnaire respondents. The findings indicated that only age, educational level, and annual income level are associated with the investment behavior of Arab women, where age is only negatively associated with their financial risk tolerance levels. Additionally, income level is positively associated with Arab women‘s confidence and investment literacy levels, while educational level is only associated positively with their investment confidence levels. According to annual income, Arab women with lower incomes have lower confidence and investment literacy levels. The limited income level might prevent the sample Arab women from investing in the financial information and advisors that may help in improving their investment literacy levels. Furthermore, Arab women with lower educational levels have lower investment literacy levels and thus, this may limit their stock investments. Overall, the study contributes to the existing literature by focusing directly on examining the investment behavior of Arab women and its association with age, annual income, and education. Generally, there are scarce existing studies that investigate the association of demographic factors with the investment behavior of women only in regards to their herding behavior, risk tolerance, investment confidence, and investment literacy levels (combined), especially Arab women investors.

Keywords: Arab region, demographic factors, investment behavior, women investors

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Authors: Julia Wong, Hua Beng Lim, Petrina Goh, Johanna Foo, Caleb Ng, Nurul ‘Aqilah Bte Mohd Taufek

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Animal-assisted therapy (AAT) utilizes human-animal interaction to achieve specific therapeutic goals, and its efficacy has been demonstrated across various settings overseas. The use of AAT in Singapore, however, is still limited. Ang Mo Kio-Thye Hua Kwan (AMKH) is one of the first community hospitals in Singapore to use AAT to complement its occupational therapy services with elderly patients. This study explored the perspectives of AMKH’s occupational therapists (OTs) in relation to AAT to understand barriers and enablers in implementing and practising AAT. We also examined how OTs at-large across practice settings perceive AAT. A mixed method design was used. 64 OTs at-large participated in on online survey, and 7 AMKH OTs were interviewed individually via Zoom. Survey results were analysed with descriptive and Mann-Whitney U tests. Interviews were thematically analysed. AMKH OTs perceived various benefits of AAT articulated in overseas studies in domains such as motivation and participation, emotional, social interaction, sensory tactile stimulation, and cognition. Interestingly, this perception was also supported by 67% of OTs who had responded to the survey, even though most of the OTs who had participated in the survey had no experience in AAT. Despite the perceived benefits of AAT, both OTs from AMKH and those at-large articulated concerns on risks pertaining to AAT (e.g., allergies, unexpected animal behaviour, infections, etc). However, AMKH OTs shared several ways to mitigate these risks, demonstrating their ability to develop a safe program. For e.g., volunteers and their dogs must meet specific recruitment criteria, stringent protocols are used to screen and match dogs with patients, and there are strict exclusion criteria for patients participating in AAT. AMKH OTs’ experience suggests that additional skills and knowledge are required to implement AAT, therefore, healthcare institutions should first consider improving their staff training and risk mitigation knowledge before implementing AAT. They can also refer to AMKH’s AAT protocols and those found in overseas studies, but institutions must adapt the protocols to fit their institutional settings and patients’ profiles.

Keywords: animal-assisted therapy, dog-assisted therapy, occupational therapy, complementary therapy

Procedia PDF Downloads 143

Authors: Denise Levy, Gian M. A. A. Sordi

Abstract:

This web based project focuses on continuing corporate education and improving workers' skills in Brazilian radioactive facilities throughout the country. The potential of Information and Communication Technologies (ICTs) shall contribute to improve the global communication in this very large country, where it is a strong challenge to ensure high quality professional information to as many people as possible. The main objective of this system is to provide Brazilian radioactive facilities a complete web-based repository - in Portuguese - for research, consultation and information, offering conditions for learning and improving professional and personal skills. UNIPRORAD is a web based system to offer unified programs and inter-related information about radiological protection programs. The content includes the best practices for radioactive facilities in order to meet both national standards and international recommendations published by different organizations over the past decades: International Commission on Radiological Protection (ICRP), International Atomic Energy Agency (IAEA) and National Nuclear Energy Commission (CNEN). The website counts on concepts, definitions and theory about optimization and ionizing radiation monitoring procedures. Moreover, the content presents further discussions related to some national and international recommendations, such as potential exposure, which is currently one of the most important research fields in radiological protection. Only two publications of ICRP develop expressively the issue and there is still a lack of knowledge of fail probabilities, for there are still uncertainties to find effective paths to quantify probabilistically the occurrence of potential exposures and the probabilities to reach a certain level of dose. To respond to this challenge, this project discusses and introduces potential exposures in a more quantitative way than national and international recommendations. Articulating ICRP and AIEA valid recommendations and official reports, in addition to scientific papers published in major international congresses, the website discusses and suggests a number of effective actions towards safety which can be incorporated into labor practice. The WEB platform was created according to corporate public needs, taking into account the development of a robust but flexible system, which can be easily adapted to future demands. ICTs provide a vast array of new communication capabilities and allow to spread information to as many people as possible at low costs and high quality communication. This initiative shall provide opportunities for employees to increase professional skills, stimulating development in this large country where it is an enormous challenge to ensure effective and updated information to geographically distant facilities, minimizing costs and optimizing results.

Keywords: distance learning, information and communication technology, nuclear science, radioactive facilities

Procedia PDF Downloads 195

Authors: K. Y. Chen, H. Chua, C. W. Kan

Abstract:

In this study, we will analyze Germany’s environmental situation such as water and air quality and review its environmental policy. In addition, we will collect the yearly environmental data as well as information concerning public environmental investment. Based on the data collect, we try to find out the relationship between public environmental investment and sustainable development in Germany. In addition, after comparing the trend of environmental quality and situation of environmental policy and investment, we may have some conclusions and learnable aspects to refer to. Based upon the data collected, it was revealed that Germany has established a well-developed institutionalization of environmental education. And the ecological culture at school is dynamic and continuous renewal. The booming of green markets in Germany is a very successful experience for learning. The green market not only creates a number of job opportunities, but also helps the government to improve and protect the environment. Acknowledgement: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: Germany, public environmental investment, environment quality, sustainable development

Procedia PDF Downloads 244

Authors: Mamunur Rashid, Jialin Yan

Abstract:

The current years have witnessed a rapid evolution and integration of artificial intelligence (AI) in various fields, prominently influencing the education industry. Acknowledging this transformative wave, AI tools like ChatGPT and Grammarly have undeniably introduced perspectives and skills, enriching the educational experiences of higher education students. The prevalence of AI utilization in higher education also drives an increasing number of researchers' attention in various dimensions. Departments, offices, and professors in universities also designed and released a set of policies and guidelines on using AI effectively. In regard to this, the study targets exploring and analyzing graduate students' perspectives regarding AI guidelines set by teachers. A mixed-methods study will be mainly conducted in this study, employing in-depth interviews and focus groups to investigate and collect students' perspectives. Relevant materials, such as syllabi and course instructions, will also be analyzed through the documentary analysis to facilitate understanding of the study. Surveys will also be used for data collection and students' background statistics. The integration of both interviews and surveys will provide a comprehensive array of student perspectives across various academic disciplines. The study is anchored in the theoretical framework of self-determination theory (SDT), which emphasizes and explains the students' perspective under the AI guidelines through three core needs: autonomy, competence, and relatedness. This framework is instrumental in understanding how AI guidelines influence students' intrinsic motivation and sense of empowerment in their learning environments. Through qualitative analysis, the study reveals a sense of confusion and uncertainty among students regarding the appropriate application and ethical considerations of AI tools, indicating potential challenges in meeting their needs for competence and autonomy. The quantitative data further elucidates these findings, highlighting a significant communication gap between students and educators in the formulation and implementation of AI guidelines. The critical findings of this study mainly come from two aspects: First, the majority of graduate students are uncertain and confused about relevant AI guidelines given by teachers. Second, this study also demonstrates that the design and effectiveness of course materials, such as the syllabi and instructions, also need to adapt in regard to AI policies. It indicates that certain of the existing guidelines provided by teachers lack consideration of students' perspectives, leading to a misalignment with students' needs for autonomy, competence, and relatedness. More emphasize and efforts need to be dedicated to both teacher and student training on AI policies and ethical considerations. To conclude, in this study, graduate students' perspectives on teacher-provided AI guidelines are explored and reflected upon, calling for additional training and strategies to improve how these guidelines can be better disseminated for their effective integration and adoption. Although AI guidelines provided by teachers may be helpful and provide new insights for students, educational institutions should take a more anchoring role to foster a motivating, empowering, and student-centered learning environment. The study also provides some relevant recommendations, including guidance for students on the ethical use of AI and AI policy training for teachers in higher education.

Keywords: higher education policy, graduate students’ perspectives, higher education teacher, AI guidelines, AI in education

Procedia PDF Downloads 65

Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

Abstract:

Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

Procedia PDF Downloads 315