Search results for: student-centered learning technologies

Authors: Sanam Mujahid, Aliza Ahmad

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Women education and empowerment has fundamental importance in the development of a civilized society however, in a developing country like Pakistan, there are serious challenges in this regard. Herein, we summarize the findings of 2012 study which revealed the key problems associated with women education and their proposed solutions. A survey tool was used to question female students and female faculty members in 20 different public sector universities of all four provinces of Pakistan. In this study, 1755 female students and 410 female faculty members responded. In addition to survey, semi-structured interview were also conducted with 25 female students and 10 female faculty members. Respondents of the survey emphasize the lack of adequate educational institutions in nearby vicinity, social exclusion including gender discrimination, shortage of female teachers, lack of resources and inefficient government policies are the major factors that influence female education. To solve these problems, the main recommendations by respondents include safe and secure learning environment for females in educational institutions, community and parental support, well qualified and sufficient number of female teachers. One of the most important proposals was the participation of females at policy level. Current study will provide a general layout to design the future educational strategies for promoting women education in all regions of Pakistan thus, developing towards modern educated society.

Keywords: women education, education strategies, developing countries, Pakistan

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Authors: Phusit Phukamchanoad

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This study aimed to analyse the application of sufficiency economy in students’ ways of life on campus at Suan Sunandha Rajabhat University. Data was gathered through 394 questionnaires. The study results found that the majority of students were confident that “where there’s a will, there’s a way.” Overall, the students applied the sufficiency economy at a great level, along with being people who do not exploit others, were satisfied with living their lives moderately, according to the sufficiency economy. Importance was also given to kindness and generosity. Importantly, students were happy with living according to their individual circumstances and status at the present. They saw the importance of joint life planning, self-development, and self-dependence, always learning to be satisfied with “adequate”. As for their practices and ways of life, socially relational activities rated highly, especially initiation activities for underclassmen at the university and the seniority system, which are suitable for activities on campus. Furthermore, the students knew how to build a career and find supplemental income, knew how to earnestly work according to convention to finish work, and preferred to study elective subjects which directly benefit career-wise. The students’ application of sufficiency economy philosophy principles depended on their lives in their hometowns. The students from the provinces regularly applied sufficiency economy philosophy to their lives, for example, by being frugal, steadfast, determined, avoiding negligence, and making economical spending plans; more so than the students from the capital.

Keywords: application of sufficiency economy philosophy, way of living, undergraduate students, spending plan

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Authors: Huiling Feng, Jihong Liang, Xiaodong Gong, Yongjun Xu

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Recording history is a tradition in ancient China. A record of a dynasty makes a dynastic history; a record of a locality makes a chorography, and a record of a clan makes a genealogy – the three combined together depicts a complete national history of China both macroscopically and microscopically, with genealogy serving as the foundation. Genealogy in ancient China traces back to a family tree or pedigrees in the early and medieval historical times. After Song Dynasty, the civilian society gradually emerged, and the Emperor had to allow people from the same clan to live together and hold the ancestor worship activities, thence compilation of genealogy became popular in the society. Since then, genealogies, regarded as important as ancestor and religious temples in a traditional villages even today, have played a primary role in identification of a clan and maintain local social order. Chinese genealogies are rich in their documentary materials. Take the Genealogy of Wu Clan in Gaoqian as an example. Gaoqian is a small village in Xianju County of Zhejiang Province. The Genealogy of Wu Clan in Gaoqian is composed of a whole set of materials from Foreword to Family Trees, Family Rules, Family Rituals, Family Graces and Glories, Ode to An ancestor’s Portrait, Manual for the Ancestor Temple, documents for great men in the clan, works written by learned men in the clan, the contracts concerning landed property, even notes on tombs and so on. Literally speaking, the genealogy, with detailed information from every aspect recorded in stylistic rules, is indeed the carrier of the entire culture of a clan. However, due to their scarcity in number and difficulties in reading, genealogies seldom fall into the horizons of common people. This paper, focusing on the case of the Genealogy of Wu Clan in the Village of Gaoqian, intends to reproduce a digital Genealogy by use of ICTs, through an in-depth interpretation of the literature and field investigation in Gaoqian Village. Based on this, the paper goes further to explore the general methods in transferring physical genealogies to digital ones and ways in visualizing the clanism culture embedded in the genealogies with a combination of digital technologies such as software in family trees, multimedia narratives, animation design, GIS application and e-book creators.

Keywords: clanism culture, multimedia narratives, genealogy of Wu Clan, GIS

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Authors: Thammanoon Charmjuree, Yuosre F. Badir, Umar Safdar

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There is a consensus among innovation scholars that knowledge is a vital antecedent for firm’s innovation; e.g., process innovation. Recently, there has been an increasing amount of attention to more open approaches to innovation. This open model emphasizes the use of purposive flows of knowledge across the organization boundaries. Firms adopt open innovation strategy to improve their innovation performance by bringing knowledge into the organization (inbound open innovation) to accelerate internal innovation or transferring knowledge outside (outbound open innovation) to expand the markets for external use of innovation. Reviewing open innovation research reveals the following. First, the majority of existing studies have focused on inbound open innovation and less on outbound open innovation. Second, limited research has considered the possible interaction between both and how this interaction may impact the firm’s innovation performance. Third, scholars have focused mainly on the impact of open innovation strategy on product innovation and less on process innovation. Therefore, our knowledge of the relationship between firms’ inbound and outbound open innovation and how these two impact process innovation is still limited. This study focuses on the firm’s external technology acquisition (ETA) and external technology exploitation (ETE) and the firm’s process innovation performance. The ETA represents inbound openness in which firms rely on the acquisition and absorption of external technologies to complement their technology portfolios. The ETE, on the other hand, refers to commercializing technology assets exclusively or in addition to their internal application. This study hypothesized that both ETA and ETE have a positive relationship with process innovation performance and that ETE fully mediates the relationship between ETA and process innovation performance, i.e., ETA has a positive impact on ETE, and turn, ETE has a positive impact on process innovation performance. This study empirically explored these hypotheses in software development firms in Thailand. These firms were randomly selected from a list of Software firms registered with the Department of Business Development, Ministry of Commerce of Thailand. The questionnaires were sent to 1689 firms. After follow-ups and periodic reminders, we obtained 329 (19.48%) completed usable questionnaires. The structure question modeling (SEM) has been used to analyze the data. An analysis of the outcome of 329 firms provides support for our three hypotheses: First, the firm’s ETA has a positive impact on its process innovation performance. Second, the firm’s ETA has a positive impact its ETE. Third, the firm’s ETE fully mediates the relationship between the firm’s ETA and its process innovation performance. This study fills up the gap in open innovation literature by examining the relationship between inbound (ETA) and outbound (ETE) open innovation and suggest that in order to benefits from the promises of openness, firms must engage in both. The study went one step further by explaining the mechanism through which ETA influence process innovation performance.

Keywords: process innovation performance, external technology acquisition, external technology exploitation, open innovation

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Authors: P. Byrnes, F. A. DiazDelaO

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The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.

Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines

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Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

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Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

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Authors: Mairo Musa Galadima

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This paper examines the impact of Mother tongue interference on students’ performance in English Language in Bauchi State. It is observed that the students of Bauchi district share the same problem with Hausa native speakers of Kano dialect which is the standard form. It is observed that there are some phonemes which are present in English but absent in Hausa so the Hausa speakers of Bauchi district also replace these sounds with similar ones present in Hausa. Students in Bauchi district fail English language because they transfer features of their mother tongue (MT) into English. The data is obtained through unobtrusive observation of the English speech of about fifty Hausa native speakers of Bauchi district which is similar to Kano dialect from Abubakar Tatari Ali Polytechnic, Bauchi since only those who have had some good background of secondary education are used because uneducated Nigeria English of whatever geographical location is more likely to be unintelligible as cockney or uneducated African-American English. For instance /Ə:/ is absent in Hausa so the speakers find it difficult to distinguish between such pairs of words as /bƏ:d / and /bΛst/, /fa:st/ and /fƏ:st / hence /a:/ is generally used wherever /Ə:/ is present regardless of the spelling, that is why words like ‘work’, ‘first’ and ‘person’ all have / a:/. In Hausa most speakers use /P/ in place of, or in alternation with /f/, e.g. ‘few’ is pronounced as ‘pew’, or ‘pen’, as ‘fen’, /b/ for /v/, /s/ for /z/ and /z/ for /ᵹ/. Also the word vision/visn/ is pronounced as /vidzn/. Therefore, there is confusion in spellings and pronunciation of words. One solution out of the problem is having constant practice with a qualified consistent staff and making use of standard textbooks in the learning process.

Keywords: English, failure, mother tongue, interference, students

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Authors: Kelvin Tang

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As the world is approaching global warming of 1.5°C above pre-industrial levels, more atrocious consequences of climate change are projected to occur in the future. Consequently, it is today’s adolescents who will encounter the grand consequences of climate change. Therefore, nurturing adolescents that are well-informed, emotionally engaged, and motivated to take actions for combating climate change may be pivotal. Climate change education has a role in not only raising awareness, but also promoting behaviour change for climate change mitigation and adaptation. However, what kind of climate change education is suitable for whom? Requiring a learner-centred approach, tailoring climate change education requires a comprehensive understanding of the audience and their preconditions. In Japan, where climate change education has yet to be recognised as a field of environmental education, understanding climate change conceptions possessed by early adolescents is critical for a better design and more impactful implementation of climate change education. This exploratory study aims to investigate climate change conceptions among Japanese early adolescents from the perspective of cognition, affective, and conative dimensions. Questionnaire surveys were conducted targeting 423 students aged 12–14 in three public junior high schools located in Kashiwa City and Oita City. Findings suggest that the majority of Japanese early adolescents belong to groups that exhibit lower levels of cognition, affect, and conation in relation to climate change. The relationships among those dimensions were found to be positive and bidirectional. Moreover, several misconceptions about climate change and the effectiveness of its solutions were identified among the sample.

Keywords: climate change conceptions, climate change education, environmental education, adolescents, three learning dimensions, Japan

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Authors: Eru Ihie Joel

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This study was carried out to investigate the influence of information technology on financial management practice in secondary schools for transformation. In Zone C Senatorial District of Benue state. The study answered four research questions and tested four hypotheses. Related literature was reviewed to show the gap to be filled in the study. The population was 196 respondents made up of principals and finance clerks of secondary schools. The descriptive survey was adopted for the study. A structured 20 item questionnaire (IITFMPSQ) was constructed and used to collect date for the study. Data obtained were analyzed using descriptive and inferential statistic. Mean and standard deviation were used to analyze the research question while the chi- square (x2) test of goodness of fit was used to test the hypothesis. The major findings revealed that the use of computer system significantly influences budgeting in secondary schools in zone senatorial district of Benue State for transformation. It was also established that the use of internet facilities influences the funding of secondary schools for transformation in the zone. Based on the findings of the study, it was recommended among other things that administrators and teachers in schools should be trained to make effective use of the computer in budgeting so as to facilitate delegations, control, evaluation, accountability for transformation. It was further suggested that the study be replicated on the effective use of information communication teaching (ITC) in teaching and learning in secondary school for transformation.

Keywords: influence, finance, management, technology

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Authors: Waleed Jarjoura

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In various cases of visual impairments, the individuals are referred to expert Ophthalmologists in order to establish a correct diagnosis. Children with visual-impairments confront various challenging experiences in life since early childhood throughout lifespan. In some cases, blind infants, especially due to congenital hydrocephalus, suffer from high intra-cranial pressure and, consequently, go through a ventriculo-peritoneal shunt surgery in order to limit the neurological symptoms or decrease the cognitive impairments. In this article, a detailed description of numerous crucial implications of the V/P shunt surgery, through the right posterior-inferior parieto-temporal cortex, on the observed preliminary capabilities that are pre-requisites for the acquisition of literacy skills in braille, basic Math competencies, braille printing which suggest Gerstmann syndrome in the blind. In addition, significant difficultiesorientation and mobility skills using the Cane, in general, organizational skills, and social interactions were observed. The primary conclusion of this report focuses on raising awareness among neuro-surgeons towards the need for alternative intracranial routes for V/P shunt implantation in blind infants that preserve the right posterior-inferior parieto-temporal cortex that is hypothesized to modulate the tactual-spatial cues in braille discrimination. A second conclusion targets educators and therapists that address the acquired dysfunctionsin blind individuals due to V/P shunt surgeries.

Keywords: congenital blindness, hydrocephalus, shunt surgery, spatial orientation

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Authors: Kshama Sharma

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Education is one of the most powerful tools to transform the world into a just, sustainable, and more peaceful place for existing lives across the globe. However, its recent objective approach focused on materialistic, factual, and existing knowledge, has a constraint of human experiences that is limited to certain dimensions only. And leads to a materialistic world which is deprived of spiritual approaches and makes it less compassionate, and more grades oriented. To make it more comprehensive, education should explore the subjective approaches towards spiritualism to connect lives with the greater self and consciousness of cosmic intelligence. This approach will bring a major shift in the orientation of pedagogical processes, assessment strategies, and administrative management of the present education system. Spirituality often related to the religious aspect of human civilization and development, however, when universal consciousness /cosmic intelligence (which is often claimed as dark energy) and the human mind competencies works in coherence and coordination then the efficiency of human mind reaches to a different dimension and achieve extraordinary level of human understanding. Quantitative analysis of the existing secondary data from the different agencies working in the field of meditation had been analyzed to conclude its implications on human mind and further how it can effectively use in education to bring the desired and expected results. Any kind of meditation practice affects the cognitive, mental, physical, emotional, and conscious state of mind. If aligned with the teaching and learning methodology will lead to conscious learner and peaceful world.

Keywords: spirituality, cosmic intelligence, consciousness, mind competencies

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Authors: L. Cruz-Lopes, M. Sell, P. Escudeiro, B. Esteves

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It might be difficult for deaf people to communicate since spoken and written languages are different from sign language. When it comes to getting information, going to places of cultural heritage, or using services and infrastructure, there is a clear lack of inclusiveness. By creating assistive technology that enables deaf individuals to get around communication hurdles and encourage inclusive tourism, the ICHT- Inclusive Cultural Heritage Tourism initiative hopes to increase knowledge of sign language. The purpose of the Inclusive Cultural Heritage Tourism (ICHT) project is to develop online and on-site sign language tools and material for usage at popular tourist destinations in the northern region of Portugal, including Torre dos Clérigos, the Lello bookstore, Maia Zoo, Porto wine cellars, and São Pedro do Sul (Viseu) thermae. The ICHT system consists of an application using holography, a mobile game, an online platform for collaboration with deaf and hearing users, and a collection of International Sign training courses. The project also offers a prospect for a more inclusive society by introducing a method of teaching sign languages to tourism industry professionals. As a result, the teaching and learning of sign language along with the assistive technology tools created by the project sets up an inclusive environment for the deaf community, producing results in the area of automatic sign language translation and aiding in the global recognition of the Portuguese tourism industry.

Keywords: inclusive tourism, games, international sign training, deaf community

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Authors: Wahhaj Ahmed Farooqi, Bilal Ahmad, Sandra Maritza Zambrano Bernal

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In view of structural engineering, monitoring of structural responses over time is of great importance with respect to recent developments of construction technologies. Recently, developments of advanced computing tools have enabled researcher’s better execution of structural health monitoring (SHM) and control systems. In the last decade, building information modeling (BIM) has substantially enhanced the workflow of planning and operating engineering structures. Typically, building information can be stored and exchanged via model files that are based on the Industry Foundation Classes (IFC) standard. In this study a modeling approach for semantic modeling of SHM and control systems is integrated into the BIM methodology using the IFC standard. For validation of the modeling approach, a laboratory test structure, a four-story shear frame structure, is modeled using a conventional BIM software tool. An IFC schema extension is applied to describe information related to monitoring and control of a prototype SHM and control system installed on the laboratory test structure. The SHM and control system is described by a semantic model applying Unified Modeling Language (UML). Subsequently, the semantic model is mapped into the IFC schema. The test structure is composed of four aluminum slabs and plate-to-column connections are fully fixed. In the center of the top story, semi-active tuned liquid column damper (TLCD) is installed. The TLCD is used to reduce effects of structural responses in context of dynamic vibration and displacement. The wireless prototype SHM and control system is composed of wireless sensor nodes. For testing the SHM and control system, acceleration response is automatically recorded by the sensor nodes equipped with accelerometers and analyzed using embedded computing. As a result, SHM and control systems can be described within open BIM, dynamic responses and information of damages can be stored, documented, and exchanged on the formal basis of the IFC standard.

Keywords: structural health monitoring, open building information modeling, industry foundation classes, unified modeling language, semi-active tuned liquid column damper, nondestructive testing

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Authors: S. Jigna, K. Nanda Kumar, T. Anna

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Being a major contributor to the Indian economy and a critical facilitator for the country’s digital India vision, the Indian telecommunications industry is also a major source of employment for the country. Since the last few years, the Indian telecommunication service providers (TSPs), however, are facing business challenges related to increasing competition, losses, debts, and decreasing revenue. The strategic use of digital technologies for a successful digital transformation has the potential to equip organizations to meet these business challenges. Despite an increased focus on digital transformation, the telecom service providers globally, including Indian TSPs, have seen limited success so far. The purpose of this research was thus to identify the factors that are critical for the digital transformation and to what extent they influence the successful digital transformation of the Indian TSPs. The literature review of more than 300 digital transformation-related articles, mostly from 2013-2019, demonstrated a lack of an empirical model consisting of factors for the successful digital transformation of the TSPs. This study theorizes a research framework grounded in multiple theories, and a research model consisting of 7 constructs that may be influencing business success during the digital transformation of the organization was proposed. The questionnaire survey of senior managers in the Indian telecommunications industry was seeking to validate the research model. Based on 294 survey responses, the validation of the Structural equation model using the statistical tool ADANCO 2.1.1 was found to be robust. Results indicate that Digital Capabilities, Digital Strategy, and Corporate Level Data Strategy in that order has a strong influence on the successful Business Performance, followed by IT Function Transformation, Digital Innovation, and Transformation Management respectively. Even though Digital Organization did not have a direct significance on Business Performance outcomes, it had a strong influence on IT Function Transformation, thus affecting the Business Performance outcomes indirectly. Amongst numerous practical and theoretical contributions of the study, the main contribution for the Indian TSPs is a validated reference for prioritizing the transformation initiatives in their strategic roadmap. Also, the main contribution to the theory is the possibility to use the research framework artifact of the present research for quantitative validation in different industries and geographies.

Keywords: corporate level data strategy, digital capabilities, digital innovation, digital strategy

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Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Anne Crescini

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The number of loanwords borrowed into the Japanese language is increasing rapidly in recent years, and many linguists argue that loanwords make up more than 10% of the Japanese lexicon. While these loanwords come from various Western languages, 80%-90% are borrowed from English. Also, there is a separate group of words and phrases categorized as ‘Japanese English’. These made-in-Japan linguistic creations may look and sound like English, but in fact are not used by native speakers and are often incomprehensible to them. Linguistically, the important thing to remember is that these terms are not English ones, but in fact, 100% Japanese words. A problem arises in language teaching, however, when Japanese English learners are unable to distinguish authentic loans from Japanese English terms. This confusion could greatly impede language acquisition and communication. The goal of this paper is to determine to what degree this potential misunderstanding may interfere with communication. Native English speakers living in the United States were interviewed and shown a list of romanized Japanese English terms, which are both commonly used and often mistaken for authentic loans. Then, the words were put into the context of a sentence in order to ascertain if context in any way aided comprehension. The results showed that while some terms are understood on their own, and others are understood better in context, a large number of the terms are entirely incomprehensible to native English speakers. If that is the case, and a Japanese learner mistakes a Japanese English term for an authentic loan, a communication breakdown may occur during interaction in English. With the ever-increasing presence of both groups of terms in the Japanese language, it is more important than ever that teaching professionals address this topic in the language classroom.

Keywords: Japanese, Japanese English, language acquisition, loanwords

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Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

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Authors: Araceli Martínez Ortiz

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An educational research effort is analyzed using systems theory to document the power of collective impact when addressing multiple factors contributing towards the retention of students majoring in science, technology, engineering and mathematics (STEM) academic programs. This research promotes understanding on how networked communities may work effectively toward a shared vision and mutually aligned activities that result in sustained, large scale change. The actions of a team of researchers in their third year of collaboration are presented to describe a model that positively aligns work efforts resulting in greater total gains. The goals of the multiple programs managed by the funded program team are to: 1) expand the number of students who choose to study a STEM field of study; 2) promote student collaborative learning; 3) support faculty understanding of the funds of knowledge of diverse students and 4) establish innovative and robust STEM education research that will lead to the development of nationally replicable, scalable models for broadening participation in STEM. The impacts of this research effort are measured through quantitative statistical analysis of the changes in second-year STEM undergraduate student retention rates and representation rates of women, Hispanics and African American STEM majors.

Keywords: collaborative impact, diversity, student retention, systems theory, STEM education

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Authors: Vu H. N. Khue, Marian Pavelka, Georg Jocher, Jiří Dušek, Le T. Son, Bui T. An, Ho Q. Bang, Pham Q. Huong

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Agriculture is an important economic sector of Vietnam, the most popular of which is wet rice cultivation. These activities are also known as the main contributor to the national greenhouse gas. In order to understand more about greenhouse gas exchange in these activities and to investigate the factors influencing carbon cycling and sequestration in these types of ecosystems, since 2019, the first eddy covariance station has been installed in a paddy field in Long An province, Mekong Delta. The station was equipped with state-of-the-art equipment for CO₂ and CH₄ gas exchange and micrometeorology measurements. In this study, data from the station was processed following the ICOS recommendations (Integrated Carbon Observation System) standards for CO₂, while CH₄ was manually processed and gap-filled using a random forest model from methane-gapfill-ml, a machine learning package, as there is no standard method for CH₄ flux gap-filling yet. Finally, the carbon equivalent (Ce) balance based on CO₂ and CH₄ fluxes was estimated. The results show that in 2020, even though a new water management practice - alternate wetting and drying - was applied to reduce methane emissions, the paddy field released 928 g Cₑ.m⁻².yr⁻¹, and in 2021, it was reduced to 707 g Cₑ.m⁻².yr⁻¹. On a provincial level, rice cultivation activities in Long An, with a total area of 498,293 ha, released 4.6 million tons of Cₑ in 2020 and 3.5 million tons of Cₑ in 2021.

Keywords: eddy covariance, greenhouse gas, methane, rice cultivation, Mekong Delta

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

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Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

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Authors: S. Ben Fredj, H. Ghali, M. Ben Rejeb, S. Layouni, S. Khefacha, L. Dhidah, H. Said

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Background: The Intensive Care Unit (ICU) provides continuous care and uses a high level of treatment technologies. Although developed country hospitals allocate only 5–10% of beds in critical care areas, approximately 20% of nosocomial infections (NI) occur among patients treated in ICUs. Whereas in the developing countries the situation is still less accurate. The aim of our study is to assess mortality rates in ICUs and to determine its predictive factors. Methods: We carried out a nested case-control study in a 630-beds public tertiary care hospital in Eastern Tunisia. We included in the study all patients hospitalized for more than two days in the surgical or medical ICU during the entire period of the surveillance. Cases were patients who died before ICU discharge, whereas controls were patients who survived to discharge. NIs were diagnosed according to the definitions of ‘Comité Technique des Infections Nosocomiales et les Infections Liées aux Soins’ (CTINLIS, France). Data collection was based on the protocol of Rea-RAISIN 2009 of the National Institute for Health Watch (InVS, France). Results: Overall, 301 patients were enrolled from medical and surgical ICUs. The mean age was 44.8 ± 21.3 years. The crude ICU mortality rate was 20.6% (62/301). It was 35.8% for patients who acquired at least one NI during their stay in ICU and 16.2% for those without any NI, yielding an overall crude excess mortality rate of 19.6% (OR= 2.9, 95% CI, 1.6 to 5.3). The population-attributable fraction due to ICU-NI in patients who died before ICU discharge was 23.46% (95% CI, 13.43%–29.04%). Overall, 62 case-patients were compared to 239 control patients for the final analysis. Case patients and control patients differed by age (p=0,003), simplified acute physiology score II (p < 10-3), NI (p < 10-3), nosocomial pneumonia (p=0.008), infection upon admission (p=0.002), immunosuppression (p=0.006), days of intubation (p < 10-3), tracheostomy (p=0.004), days with urinary catheterization (p < 10-3), days with CVC ( p=0.03), and length of stay in ICU (p=0.003). Multivariate analysis demonstrated 3 factors: age older than 65 years (OR, 5.78 [95% CI, 2.03-16.05] p=0.001), duration of intubation 1-10 days (OR, 6.82 [95% CI, [1.90-24.45] p=0.003), duration of intubation > 10 days (OR, 11.11 [95% CI, [2.85-43.28] p=0.001), duration of CVC 1-7 days (OR, 6.85[95% CI, [1.71-27.45] p=0.007) and duration of CVC > 7 days (OR, 5.55[95% CI, [1.70-18.04] p=0.004). Conclusion: While surveillance provides important baseline data, successful trials with more active intervention protocols, adopting multimodal approach for the prevention of nosocomial infection incited us to think about the feasibility of similar trial in our context. Therefore, the implementation of an efficient infection control strategy is a crucial step to improve the quality of care.

Keywords: intensive care unit, mortality, nosocomial infection, risk factors

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Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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Authors: Ahmad Tijani Surajudeen, Muhammad Zahiri Awang Mat, Aliy Abdulwahid Adebisi

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With arrival of Islam in the South-Western Nigeria in the late fifteenth and early sixteenth centuries, various masājid established in different parts of the area played vital roles towards the betterment and unity of the Muslims. However, despite the fact that the masājid in the South-Western part of Nigeria contributed immensely to the spiritual and educational enhancement of the Muslims, it has not fully captured the holistic educational roles as a unique model used by the Prophet (S.A.W). Therefore, the primary objective of this paper is to investigate and broaden the roles of masjid towards its compartmentalized and holistic contributions among the Muslims in the south-western Nigeria. The findings from the paper have identified five holistic roles of masjid, namely, spiritual, intellectual, physical, social and emotional contributions which have been exemplified in the prophetic model of masjid. The paper has argued that the five factors must be unreservedly unified towards the betterment of the Muslims and enhancement of Islamic education and Arabic Language in the South-Western Nigeria. However, the challenges of masjid management in the South-Western Nigeria are the main hindrance in achieving the holistic roles of masjid. It is thereby suggested that, the management of masjid should take the identified prophetic model of masjid into account in order to positively improve the affairs of Muslims as well as promoting the teaching and learning of Islamic education and Arabic language among the Muslims in the South-Western Nigeria.

Keywords: worship, Islamic education, Arabic language, prophetic holistic model

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Authors: Fatemeh Torabi, Jamal El-Den, Narumon Sriratanviriyakul

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Perpetual changes in the workplace and daily business activities bring a need for imbedding organizational knowledge sharing within the organizations’ culture, routines and processes. Organizations should adapt to the changing in the environment in order to survive. Accordingly, the management should promote a knowledge sharing culture which might result in knowledge accumulation, hence better response to these changing environmental conditions. Researchers in the field of strategy and marketing stressed that employees’, as well as the overall performance of the organization, would improve as a result of implementing a knowledge-oriented culture. The research investigated the significant impact of knowledge sharing on market response and the competitiveness of organizations. A knowledge sharing framework was developed based on current literary frameworks with additional constructs such as employees’ learning commitments, experiences and prior knowledge. Linear regression was used to analyze the relationships among dependent and independent variables. The research’s results indicated strong positive correlation between the dependent and independent variables, especially in organizational market sharing. We anticipate that this correlation would improve organizational knowledge sharing related practices and the associated knowledge entities. The research posits the introduced framework could be a solid ground for further investigations on how some organizational factors would influence the organization’s response to the market as well as on competitiveness. Final results support all hypotheses. Finding of this research show that knowledge sharing intention had the significant and positive effect on market response and competitiveness of organizations.

Keywords: knowledge management, knowledge sharing, market response, organizational competitiveness

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Authors: Alexander Zotov, Ilkin Osmanov, Emil Sakharov, Oleg Shelest, Aleksander Troitskiy, Robert Khabazov

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Objective: Thoracoscopic surgical ablation of atrial fibrillation (AF) includes two technologies in performing of operation. 1st strategy used is the AtriCure device (bipolar, nonirrigated, non clamping), 2nd strategy is- the Medtronic device (bipolar, irrigated, clamping). The study presents a comparative analysis of clinical outcomes of two strategies in thoracoscopic ablation of AF using AtriCure vs. Medtronic devices. Methods: In 2 center study, 123 patients underwent thoracoscopic ablation of AF for the period from 2016 to 2020. Patients were divided into two groups. The first group is represented by patients who applied the AtriCure device (N=63), and the second group is - the Medtronic device (N=60), respectively. Patients were comparable in age, gender, and initial severity of the condition. Among the patients, in group 1 were 65% males with a median age of 57 years, while in group 2 – 75% and 60 years, respectively. Group 1 included patients with paroxysmal form -14,3%, persistent form - 68,3%, long-standing persistent form – 17,5%, group 2 – 13,3%, 13,3% and 73,3% respectively. Median ejection fraction and indexed left atrial volume amounted in group 1 – 63% and 40,6 ml/m2, in group 2 - 56% and 40,5 ml/m2. In addition, group 1 consisted of 39,7% patients with chronic heart failure (NYHA Class II) and 4,8% with chronic heart failure (NYHA Class III), when in group 2 – 45% and 6,7%, respectively. Follow-up consisted of laboratory tests, chest Х-ray, ECG, 24-hour Holter monitor, and cardiopulmonary exercise test. Duration of freedom from AF, distant mortality rate, and prevalence of cerebrovascular events were compared between the two groups. Results: Exit block was achieved in all patients. According to the Clavien-Dindo classification of surgical complications fraction of adverse events was 14,3% and 16,7% (1st group and 2nd group, respectively). Mean follow-up period in the 1st group was 50,4 (31,8; 64,8) months, in 2nd group - 30,5 (14,1; 37,5) months (P=0,0001). In group 1 - total freedom of AF was in 73,3% of patients, among which 25% had additional antiarrhythmic drugs (AADs) therapy or catheter ablation (CA), in group 2 – 90% and 18,3%, respectively (for total freedom of AF P<0,02). At follow-up, the distant mortality rate in the 1st group was – 4,8%, and in the 2nd – no fatal events. Prevalence of cerebrovascular events was higher in the 1st group than in the 2nd (6,7% vs. 1,7% respectively). Conclusions: Despite the relatively shorter follow-up of the 2nd group in the study, applying the strategy using the Medtronic device showed quite encouraging results. Further research is needed to evaluate the effectiveness of this strategy in the long-term period.

Keywords: atrial fibrillation, clamping, ablation, thoracoscopic surgery

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Authors: Karen V. Lee

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The background and significance of this study involve communication in education by a faculty advisor exploring story and music that informs others about a disabled teacher. Social issues draw deep reflection about the emotional turmoil. As a musician becoming a teacher is a passionate yet complex endeavor, the faculty advisor shares a poetic but painful story about a disabled teacher being inducted into the teaching profession. The qualitative research method as theoretical framework draws on autoethnography of music and story where the faculty advisor approaches a professor for advice. His musicianship shifts her forward, backward, and sideways through feelings that evoke and provoke curriculum to remove communication barriers in education. They discover they do not transfer knowledge from educational method classes. Instead, the autoethnography embeds musical language as a metaphorical conduit for removing communication barriers in teacher education. Sub-themes involve communication barriers and educational technologies to ensure teachers receive social, emotional, physical, spiritual, and intervention disability resources that evoke visceral, emotional responses from the audience. Major findings of the study discover how autoethnography of music and story bring the authors to understand wider political issues of the practicum internship for teachers with disabilities. An epiphany reveals the irony of living in a culture of both uniformity and diversity. They explore the constructs of secrecy, ideology, abnormality, and marginalization by evoking visceral and emotional responses from the audience. As the voices harmonize plot, climax, characterization, and denouement, they dramatize meaning that is episodic yet incomplete to highlight the circumstances surrounding the disabled protagonist’s life. In conclusion, the qualitative research method argues for embracing storied experiences that depict communication in education. Scholarly significance embraces personal thoughts and feelings as a way of understanding social phenomena while highlighting the importance of removing communication barriers in education. The circumstance about a teacher with a disability is not uncommon in society. Thus, the authors resolve to removing barriers in education by using stories to transform the personal and cultural influences that provoke new ways of thinking about the curriculum for a disabled teacher.

Keywords: communication in education, communication barriers, autoethnography, teaching

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Authors: Aisha Adam

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This study critically examines the transformative impact of automated decision-making (ADM) and artificial intelligence (AI) systems on South African labour law. As AI technologies increasingly infiltrate workplaces, existing liability frameworks face challenges in addressing the unique complexities presented by these innovations. This article explores the necessity of redefining liability to accommodate the nuanced landscape of ADM and AI within South African labour law. It emphasises the importance of ensuring responsible deployment and safeguarding the rights of workers amid evolving technological dynamics. This research investigates the central concern of fairness, bias, and discrimination in ADM and AI decision-making. Focusing on algorithmic bias and discriminatory outcomes, the paper advocates for the integration of mechanisms within the South African legal framework, particularly under the Promotion of Equality and Prevention of Unfair Discrimination Act (PEPUDA) and the Employment Equity Act (EEA). The study scrutinises the shifting dynamics of the employment relationship, calling for clear guidelines on the responsibilities and liabilities of employers, employees, and technology providers. Furthermore, the article analyses legal and policy responses to ADM and AI within South African labour law, exploring potential amendments to legislation, guidelines, and codes of practice. It assesses the role of regulatory bodies, specifically the Commission for Conciliation, Mediation, and Arbitration (CCMA), in overseeing and enforcing responsible practices in the workplace. Lastly, the research evaluates the impact of ADM and AI on human and social rights in the South African context. Emphasising the protection of constitutional rights, including fair labour practices, privacy, and equality, the study proposes remedies and safeguards. It advocates for a multidisciplinary approach involving legal, technological, and ethical considerations to redefine liability in South African labour law effectively. The article contends that a shift from accountability to responsibility is crucial for promoting fairness, antidiscrimination, and the protection of human and social rights in the age of automated decision-making. It calls for collaborative efforts among stakeholders to shape responsible practices and redefine liability in this evolving technological landscape.

Keywords: automated decision-making, artificial intelligence, labour law, vicarious liability

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Authors: Jonas Colin

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Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

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Authors: Chih-Chieh Yang, Chung-Neng Huang

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In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

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