Search results for: learning society
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9968

Search results for: learning society

6188 Alignment and Antagonism in Flux: A Diachronic Sentiment Analysis of Attitudes towards the Chinese Mainland in the Hong Kong Press

Authors: William Feng, Qingyu Gao

Abstract:

Despite the extensive discussions about Hong Kong’s sentiments towards the Chinese Mainland since the sovereignty transfer in 1997, there has been no large-scale empirical analysis of the changing attitudes in the mainstream media, which both reflect and shape sentiments in the society. To address this gap, the present study uses an optimised semantic-based automatic sentiment analysis method to examine a corpus of news about China from 1997 to 2020 in three main Chinese-language newspapers in Hong Kong, namely Apple Daily, Ming Pao, and Oriental Daily News. The analysis shows that although the Hong Kong press had a positive emotional tone toward China in general, the overall trend of sentiment was becoming increasingly negative. Meanwhile, the alignment and antagonism toward China have both increased, providing empirical evidence of attitudinal polarisation in the Hong Kong society. Specifically, Apple Daily’s depictions of China have become increasingly negative, though with some positive turns before 2008, whilst Oriental Daily News has consistently expressed more favourable sentiments. Ming Pao maintained an impartial stance toward China through an increased but balanced representation of positive and negative sentiments, with its subjectivity and sentiment intensity growing to an industry-standard level. The results provide new insights into the complexity of sentiments towards China in the Hong Kong press and media attitudes in general in terms of the “us” and “them” positioning by explicating the cross-newspaper and cross-period variations using an enhanced sentiment analysis method which incorporates sentiment-oriented and semantic role analysis techniques.

Keywords: media attitude, sentiment analysis, Hong Kong press, one country two systems

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6187 Voting Representation in Social Networks Using Rough Set Techniques

Authors: Yasser F. Hassan

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Social networking involves use of an online platform or website that enables people to communicate, usually for a social purpose, through a variety of services, most of which are web-based and offer opportunities for people to interact over the internet, e.g. via e-mail and ‘instant messaging’, by analyzing the voting behavior and ratings of judges in a popular comments in social networks. While most of the party literature omits the electorate, this paper presents a model where elites and parties are emergent consequences of the behavior and preferences of voters. The research in artificial intelligence and psychology has provided powerful illustrations of the way in which the emergence of intelligent behavior depends on the development of representational structure. As opposed to the classical voting system (one person – one decision – one vote) a new voting system is designed where agents with opposed preferences are endowed with a given number of votes to freely distribute them among some issues. The paper uses ideas from machine learning, artificial intelligence and soft computing to provide a model of the development of voting system response in a simulated agent. The modeled development process involves (simulated) processes of evolution, learning and representation development. The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of structure. We employ agent-based computer simulation to demonstrate the formation and interaction of coalitions that arise from individual voter preferences. We are interested in coordinating the local behavior of individual agents to provide an appropriate system-level behavior.

Keywords: voting system, rough sets, multi-agent, social networks, emergence, power indices

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6186 Web 2.0 in Higher Education: The Instructors’ Acceptance in Higher Educational Institutes in Kingdom of Bahrain

Authors: Amal M. Alrayes, Hayat M. Ali

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Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.

Keywords: Web 2.0, higher education, acceptance, students' perception

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6185 Conviviality as a Principle in Natural and Social Realms

Authors: Xiao Wen Xu

Abstract:

There exists a challenge of accommodating/integrating people at risk and those from various backgrounds in urban areas. The success of interdependence as a tool for survival largely rests on the mutually beneficial relationships amongst individuals within a given society. One approach to meeting this challenge has been written by Ivan Illich in his book, Tools for Conviviality, where he defines 'conviviality' as interactions that help individuals. With the goal of helping the community and applying conviviality as a principle to actors in both natural and social realms of Moss Park in Toronto, the proposal involves redesigning the park and buildings as a series of different health care, extended learning, employment support, armoury, and recreation facilities that integrate the exterior landscape as treatment, teaching, military, and recreation areas; in other words, the proposal links services with access to park space. While buildings are traditionally known to physically provide shelter, parks embody shelter and act as service, as people often find comfort and relief from being in nature, and Moss Park, in particular, is home to many people at risk. This landscape is not only an important space for the homeless community but also the rest of the neighborhood. The thesis proposes that the federal government rebuilds the current armoury, as it is an obsolete building while acknowledging the extensive future developments proposed by developers and its impact on public space. The neighbourhood is an underserved area, and the new design develops not just a new armoury, but also a complex of interrelated services, which are completely integrated into the park. The armoury is redesigned as an integral component of the community that not only serves as training facilities for reservists but also serves as an emergency shelter in sub-zero temperatures for the homeless community. This paper proposes a new design for Moss Park through examining how 'park buildings', interconnected buildings and parks, can foster empowering relationships that create a supportive public realm.

Keywords: conviviality, natural, social, Ivan Illich

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6184 An Energy Efficient Clustering Approach for Underwater ‎Wireless Sensor Networks

Authors: Mohammad Reza Taherkhani‎

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make a connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: underwater sensor networks, clustering, learning automata, energy consumption

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6183 Inversely Designed Chipless Radio Frequency Identification (RFID) Tags Using Deep Learning

Authors: Madhawa Basnayaka, Jouni Paltakari

Abstract:

Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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6182 FMR1 Gene Carrier Screening for Premature Ovarian Insufficiency in Females: An Indian Scenario

Authors: Sarita Agarwal, Deepika Delsa Dean

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Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.

Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation

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6181 Process Driven Architecture For The ‘Lessons Learnt’ Knowledge Sharing Framework: The Case Of A ‘Lessons Learnt’ Framework For KOC

Authors: Rima Al-Awadhi, Abdul Jaleel Tharayil

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On a regular basis, KOC engages into various types of Projects. However, due to very nature and complexity involved, each project experience generates a lot of ‘learnings’ that need to be factored into while drafting a new contract and thus avoid repeating the same mistakes. But, many a time these learnings are localized and remain as tacit leading to scope re-work, larger cycle time, schedule overrun, adjustment orders and claims. Also, these experiences are not readily available to new employees leading to steep learning curve and longer time to competency. This is to share our experience in designing and implementing a process driven architecture for the ‘lessons learnt’ knowledge sharing framework in KOC. It high-lights the ‘lessons learnt’ sharing process adopted, integration with the organizational processes, governance framework, the challenges faced and learning from our experience in implementing a ‘lessons learnt’ framework.

Keywords: lessons learnt, knowledge transfer, knowledge sharing, successful practices, Lessons Learnt Workshop, governance framework

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6180 Language Teachers Exercising Agency Amid Educational Constraints: An Overview of the Literature

Authors: Anna Sanczyk

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Teacher agency plays a crucial role in effective teaching, supporting diverse students, and providing an enriching learning environment; therefore, it is significant to gain a deeper understanding of language teachers’ sense of agency in teaching linguistically and culturally diverse students. This paper presents an overview of qualitative research on how language teachers exercise their agency in diverse classrooms. The analysis of the literature reveals that language teachers strive for addressing students’ needs and challenging educational inequalities, but experience educational constraints in enacting their agency. The examination of the research on language teacher agency identifies four major areas where language teachers experience challenges in enacting their agency: (1) implementing curriculum; (2) adopting school reforms and policies; (3) engaging in professional learning; (4) and negotiating various identities as professionals. The practical contribution of this literature review is that it provides a much-needed compilation of the studies on how language teachers exercise agency amid educational constraints. The discussion of the overview points to the importance of teacher identity, learner advocacy, and continuous professional learning and the critical need of promoting empowerment, activism, and transformation in language teacher education. The findings of the overview indicate that language teacher education programs should prepare teachers to be active advocates for English language learners and guide teachers to become more conscious of complexities of teaching in constrained educational settings so that they can become agentic professionals. This literature overview illustrates agency work in English language teaching contexts and contributes to understanding of the important link between experiencing educational constraints and development of teacher agency.

Keywords: advocacy, educational constraints, language teacher agency, language teacher education

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6179 Advancing Inclusive Curriculum Development for Special Needs Education in Africa

Authors: Onosedeba Mary Ayayia

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Inclusive education has emerged as a critical global imperative, aiming to provide equitable educational opportunities for all, regardless of their abilities or disabilities. In Africa, the pursuit of inclusive education faces significant challenges, particularly concerning the development and implementation of inclusive curricula tailored to the diverse needs of students with disabilities. This study delves into the heart of this issue, seeking to address the pressing problem of exclusion and marginalization of students with disabilities in mainstream educational systems across the continent. The problem is complex, entailing issues of limited access to tailored curricula, shortages of qualified teachers in special needs education, stigmatization, limited research and data, policy gaps, inadequate resources, and limited community awareness. These challenges perpetuate a system where students with disabilities are systematically excluded from quality education, limiting their future opportunities and societal contributions. This research proposes a comprehensive examination of the current state of inclusive curriculum development and implementation in Africa. Through an innovative and explicit exploration of the problem, the study aims to identify effective strategies, guidelines, and best practices that can inform the development of inclusive curricula. These curricula will be designed to address the diverse learning needs of students with disabilities, promote teacher capacity building, combat stigmatization, generate essential data, enhance policy coherence, allocate adequate resources, and raise community awareness. The goal of this research is to contribute to the advancement of inclusive education in Africa by fostering an educational environment where every student, regardless of ability or disability, has equitable access to quality education. Through this endeavor, the study aligns with the broader global pursuit of social inclusion and educational equity, emphasizing the importance of inclusive curricula as a foundational step towards a more inclusive and just society.

Keywords: inclusive education, special education, curriculum development, Africa

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6178 Heart Ailment Prediction Using Machine Learning Methods

Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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6177 Turkish Graduate Students' Perceptions of Drop Out Issues in Massive Open Online Courses

Authors: Harun Bozna

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MOOC (massive open online course) is a groundbreaking education platform and a current buzzword in higher education. Although MOOCs offer many appreciated learning experiences to learners from various universities and institutions, they have considerably higher dropout rates than traditional education. Only about 10% of the learners who enroll in MOOCs actually complete the course. In this case, perceptions of participants and a comprehensive analysis of MOOCs have become an essential part of the research in this area. This study aims to explore the MOOCs in detail for better understanding its content, purpose and primarily drop out issues. The researcher conducted an online questionnaire to get perceptions of graduate students on their learning experiences in MOOCs and arranged a semi- structured oral interview with some participants. The participants are Turkish graduate level students doing their MA and Ph.D. in various programs. The findings show that participants are more likely to drop out courses due to lack of time and lack of pressure.

Keywords: distance education, MOOCs, drop out, perception of graduate students

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6176 StockTwits Sentiment Analysis on Stock Price Prediction

Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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6175 Preserving Egypt's Cultural Heritage Amidst Urban Development: A Case Study of the Historic Cairo Cemetery

Authors: Ali Mahfouz

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Egypt's cultural heritage and artistic riches find themselves at a complex intersection of preservation and urban development, where they face intricate challenges exacerbated by climate change, pollution, urbanization, and construction activities. In this research, it delves into the multifaceted dynamics involved in conserving Egypt's heritage within urban contexts, spotlighting the historic Cairo cemetery as a poignant and timely case study. The historic Cairo cemetery serves as a repository of priceless cultural assets, housing the final resting places of public figures, artists, historians, politicians, and other luminaries. These graves are adorned with magnificent artworks and rare tombstones, collectively representing an irreplaceable slice of Egypt's history and culture. Yet, the looming threat of demolition to make way for new infrastructure projects underscores the delicate equilibrium that preservation efforts must maintain in the face of urban development pressures. This paper illuminates the collaborative efforts of historians, intellectuals, and civil society organizations who are determined to forestall the destruction of this invaluable cultural heritage. Their initiatives, driven by a shared commitment to documenting and safeguarding the cemetery's treasures, underscore the urgent imperative of protecting Egypt's cultural legacy. Through this case study, It gain insights into how Egypt navigates the challenges of preserving its rich heritage amidst urban expansion and a changing climate, emphasizing the broader importance of heritage conservation in an evolving world.

Keywords: Egypt’s cultural heritage, urban development, historic Cairo cemetery, tombstone artworks, demolition threat, heritage conservation, civil society initiatives

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6174 The Relationship between the Feeling of Distributive Justice and National Identity of the Youth

Authors: Leila Batmany

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This research studies the relationship between the feeling of distributive justice and national identity of the youth. The present analysis intends to experimentally investigate the various dimensions of the justice feeling and its effect on the national identity components. The study has taken justice into consideration from four different points of view on the basis of availability of valuable social sources such as power, wealth, knowledge and status in the political, economic, and cultural and status justice respectively. Furthermore, the national identity has been considered as the feeling of honour, attachment and commitment towards national society and its seven components i.e. history, language, culture, political system, religion, geographical territory and society. The 'field study' has been used as the method for the research with the individual as unit, taking 368 young between the age of 18 and 29 living in Tehran, chosen randomly according to Cochran formula. The individual samples have been randomly chosen among five districts in north, south, west, east, and centre of Tehran, based on the multistage cluster sampling. The data collection has been performed with the use of questionnaire and interview. The most important results are as follows: i) The feeling of economic justice is the weakest one among the youth. ii) The strongest and the weakest dimensions of the national identity are, respectively, the historical and the social dimension. iii) There is a positive and meaningful relationship between the feeling political and statues justice and then national identity, whereas no meaningful relationship exists between the economic and cultural justice and the national identity. iv) There is a positive and meaningful relationship between the feeling of justice in all dimensions and legitimacy of the political system. There is also such a relationship between the legitimacy of the political system and national identity. v) Generally, there is a positive and meaningful relationship between the feeling of distributive justice and national identity among the youth. vi) It is through the legitimacy of the political system that justice feeling can have an influence on the national identity.

Keywords: distributive justice, national identity, legitimacy of political system, Cochran formula, multistage cluster sampling

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6173 A Comprehensive Survey of Artificial Intelligence and Machine Learning Approaches across Distinct Phases of Wildland Fire Management

Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

Abstract:

Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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6172 Initial Observations of the Utilization of Zoom Software for Synchronous English as a Foreign Language Oral Communication Classes at a Japanese University

Authors: Paul Nadasdy

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In 2020, oral communication classes at many universities in Japan switched to online and hybrid lessons because of the coronavirus pandemic. Teachers had to adapt their practices immediately and deal with the challenges of the online environment. Even for experienced teachers, this still presented a problem as many had not conducted online classes before. Simultaneously, for many students, this type of learning was completely alien to them, and they had to adapt to the challenges faced by communicating in English online. This study collected data from 418 first grade students in the first semester of English communication classes at a technical university in Tokyo, Japan. Zoom software was used throughout the learning period. Though there were many challenges in the setting up and implementation of Zoom classes at the university, the results indicated that the students enjoyed the format and made the most of the circumstances. This proved the robustness of the course that was taught in regular lessons and the adaptability of teachers and students to challenges in a very short timeframe.

Keywords: zoom, hybrid lessons, communicative english, online teaching

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6171 Implementation of International Standards in the Field of Higher Secondary Education in Kerala

Authors: Bernard Morais Joosa

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Kerala, the southern state of India, is known for its accomplishments in universal education and enrollments. Through this mission, the Government proposes comprehensive educational reforms including 1000 Government schools into international standards during the first phase. The idea is not only to improve the infrastructural facilities but also to reform the teaching and learning process to the present day needs by introducing ICT enabled learning and providing smart classrooms. There will be focus on creating educational programmes which are useful for differently abled students. It is also meant to reinforce the teaching–learning process by providing ample opportunities to each student to construct their own knowledge using modern technology tools. The mission will redefine the existing classroom learning process, coordinate resource mobilization efforts and develop ‘Janakeeya Vidyabhyasa Mathruka.' Special packages to support schools which are in existence for over 100 years will also be attempted. The implementation will enlist full involvement and partnership of the Parent Teacher Association. Kerala was the first state in the country to attain 100 percent literacy more than two and a half decades ago. Since then the State has not rested on its laurels. It has moved forward in leaps and bounds conquering targets that no other State could achieve. Now the government of Kerala is taking off towards new goal of comprehensive educational reforms. And it focuses on Betterment of educational surroundings, use of technology in education, renewal of learning method and 1000 schools will be uplifted as Smart Schools. Need to upgrade 1000 schools into international standards and turning classrooms from standard 9 to 12 in high schools and higher secondary into high-tech classrooms and a special unique package for the renovation of schools, which have completed 50 and 100 years. The government intends to focus on developing standards first to eighth standards in tune with the times by engaging the teachers, parents, and alumni to recapture the relevance of public schools. English learning will be encouraged in schools. The idea is not only to improve the infrastructure facilities but also reform the curriculum to the present day needs. Keeping in view the differently-abled friendly approach of the government, there will be focus on creating educational program which is useful for differently abled students. The idea is to address the infrastructural deficiencies being faced by such schools. There will be special emphasis on ensuring internet connectivity to promote IT-friendly existence. A task-force and a full-time chief executive will be in charge of managing the day to day affairs of the mission. Secretary of the Public Education Department will serve as the Mission Secretary and the Chairperson of Task Force. As the Task Force will stress on teacher training and the use of information technology, experts in the field, as well as Directors of SCERT, IT School, SSA, and RMSA, will also be a part of it.

Keywords: educational standards, methodology, pedagogy, technology

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6170 An Alternative to Problem-Based Learning in a Post-Graduate Healthcare Professional Programme

Authors: Brogan Guest, Amy Donaldson-Perrott

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The Master’s of Physician Associate Studies (MPAS) programme at St George’s, University of London (SGUL), is an intensive two-year course that trains students to become physician associates (PAs). PAs are generalized healthcare providers who work in primary and secondary care across the UK. PA programmes face the difficult task of preparing students to become safe medical providers in two short years. Our goal is to teach students to develop clinical reasoning early on in their studies and historically, this has been done predominantly though problem-based learning (PBL). We have had an increase concern about student engagement in PBL and difficulty recruiting facilitators to maintain the low student to facilitator ratio required in PBL. To address this issue, we created ‘Clinical Application of Anatomy and Physiology (CAAP)’. These peer-led, interactive, problem-based, small group sessions were designed to facilitate students’ clinical reasoning skills. The sessions were designed using the concept of Team-Based Learning (TBL). Students were divided into small groups and each completed a pre-session quiz consisting of difficult questions devised to assess students’ application of medical knowledge. The quiz was completed in small groups and they were not permitted access of external resources. After the quiz, students worked through a series of openended, clinical tasks using all available resources. They worked at their own pace and the session was peer-led, rather than facilitator-driven. For a group of 35 students, there were two facilitators who observed the sessions. The sessions utilised an infinite space whiteboard software. Each group member was encouraged to actively participate and work together to complete the 15-20 tasks. The session ran for 2 hours and concluded with a post-session quiz, identical to the pre-session quiz. We obtained subjective feedback from students on their experience with CAAP and evaluated the objective benefit of the sessions through the quiz results. Qualitative feedback from students was generally positive with students feeling the sessions increased engagement, clinical understanding, and confidence. They found the small group aspect beneficial and the technology easy to use and intuitive. They also liked the benefit of building a resource for their future revision, something unique to CAAP compared to PBL, which out students participate in weekly. Preliminary quiz results showed improvement from pre- and post- session; however, further statistical analysis will occur once all sessions are complete (final session to run December 2022) to determine significance. As a post-graduate healthcare professional programme, we have a strong focus on self-directed learning. Whilst PBL has been a mainstay in our curriculum since its inception, there are limitations and concerns about its future in view of student engagement and facilitator availability. Whilst CAAP is not TBL, it draws on the benefits of peer-led, small group work with pre- and post- team-based quizzes. The pilot of these sessions has shown that students are engaged by CAAP, and they can make significant progress in clinical reasoning in a short amount of time. This can be achieved with a high student to facilitator ratio.

Keywords: problem based learning, team based learning, active learning, peer-to-peer teaching, engagement

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6169 Energy Atlas: Geographic Information Systems-Based Energy Analysis and Planning Tool

Authors: Katarina Pogacnik, Ursa Zakrajsek, Nejc Sirk, Ziga Lampret

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Due to an increase in living standards along with global population growth and a trend of urbanization, municipalities and regions are faced with an ever rising energy demand. A challenge has arisen for cities around the world to modify the energy supply chain in order to reduce its consumption and CO₂ emissions. The aim of our work is the development of a computational-analytical platform for dynamic support in decision-making and the determination of economic and technical indicators of energy efficiency in a smart city, named Energy Atlas. Similar products in this field focuse on a narrower approach, whereas in order to achieve its aim, this platform encompasses a wider spectrum of beneficial and important information for energy planning on a local or regional scale. GIS based interactive maps provide an extensive database on the potential, use and supply of energy and renewable energy sources along with climate, transport and spatial data of the selected municipality. Beneficiaries of Energy atlas are local communities, companies, investors, contractors as well as residents. The Energy Atlas platform consists of three modules named E-Planning, E-Indicators and E-Cooperation. The E-Planning module is a comprehensive data service, which represents a support towards optimal decision-making and offers a sum of solutions and feasibility of measures and their effects in the area of efficient use of energy and renewable energy sources. The E-Indicators module identifies, collects and develops optimal data and key performance indicators and develops an analytical application service for dynamic support in managing a smart city in regards to energy use and sustainable environment. In order to support cooperation and direct involvement of citizens of the smart city, the E-cooperation is developed with the purpose of integrating the interdisciplinary and sociological aspects of energy end-users. Interaction of all the above-described modules contributes to regional development because it enables for a precise assessment of the current situation, strategic planning, detection of potential future difficulties and also the possibility of public involvement in decision-making. From the implementation of the technology in Slovenian municipalities of Ljubljana, Piran, and Novo mesto, there is evidence to suggest that the set goals are to be achieved to a great extent. Such thorough urban energy planning tool is viewed as an important piece of the puzzle towards achieving a low-carbon society, circular economy and therefore, sustainable society.

Keywords: circular economy, energy atlas, energy management, energy planning, low-carbon society

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6168 An Investigation of the Influence of Education Backgrounds on Mathematics Achievements: An Example of Chinese High School

Authors: Wang Jiankun

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This paper analyses how different educational backgrounds affect the mathematics performance of middle and high school students in terms of three dimensions: parental involvement, school teaching ability, and demographic variables and personal attributes of the student. Based on the analysis of Beijing High School Mathematics Competition in 2022, it was found that students from high level schools won significantly more awards than those from low level schools. In addition, a significant positive correlation (p<0.05) was identified between school level and students' mathematics performance. This study also confirms that parents' education level and family environment show a significant impact on the next generation’s mathematics learning performance. The findings suggest that interest and student’s habits, the family environment and the quality of teaching and learning at school are the main factors affecting the mathematics performance of middle and high school students.

Keywords: educational background, academic performance, middle and high school education, teenager

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6167 Adaption Model for Building Agile Pronunciation Dictionaries Using Phonemic Distance Measurements

Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

Abstract:

Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: pronunciation variations, dynamic programming, machine learning, natural language processing

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6166 Beyond Baudrillard: A Critical Intersection between Semiotics and Materialism

Authors: Francesco Piluso

Abstract:

Nowadays, to restore the deconstructive power of semiotics implies a critical analysis of neoliberal ideology, and, even more critically, a confrontation with materialist perspective. The theoretical path of Jean Baudrillard is crucial to understand the ambivalence of this intersection. A semiotic critique of Baudrillard’s work, through tools of both structuralism and interpretative semiotics, has the aim to give materialism a new consistent semiotic approach and vice-versa. According to Baudrillard, the commodity form is characterized by the same abstract and systemic logic of the sign-form, in which the production of the signified (use-value) is a mere ideological mean for the reproduction of the signifiers-chain (exchange-value). Nevertheless, this parallelism is broken by the author himself: if the use-value is deconstructed in its relative logic, the signified and the referent, both as discrete and positive elements, are collapsed on the same plane at the shadows of the signified forms. These divergent considerations lead Baudrillard to the same crucial point: the dismissal of the material world, replaced by the hyperreality as reproduction of a semiotic (genetic) Code. The stress on the concept of form, as an epistemological and semiotic tool to analyse the construction of values in the consumer society, has led to the Code as its ontological drift. In other words, Baudrillard seems to enclose consumer society (and reality) in this immanent and self-fetishized world of signs–an ideological perspective that mystifies the gravity of the material relationships between Northern-Western World and Third World. The notion of Encyclopaedia by Umberto Eco is the key to overturn the relationship of immanence/transcendence between the Code and the economic political of the sign, by understanding the former as an ideological plane within the encyclopedia itself. Therefore, rather than building semiotic (hyper)realities, semiotics has to deal with materialism in terms of material relationships of power which are mystified and reproduced through such ideological ontologies of signs.

Keywords: Baudrillard, Code, Eco, Encyclopaedia, epistemology vs. ontology, semiotics vs. materialism

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6165 A Teaching Learning Based Optimization for Optimal Design of a Hybrid Energy System

Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

Abstract:

This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

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6164 Forensic Analysis of Thumbnail Images in Windows 10

Authors: George Kurian, Hongmei Chi

Abstract:

Digital evidence plays a critical role in most legal investigations. In many cases, thumbnail databases show important information in that investigation. The probability of having digital evidence retrieved from a computer or smart device has increased, even though the previous user removed data and deleted apps on those devices. Due to the increase in digital forensics, the ability to store residual information from various thumbnail applications has improved. This paper will focus on investigating thumbnail information from Windows 10. Thumbnail images of interest in forensic investigations may be intact even when the original pictures have been deleted. It is our research goal to recover useful information from thumbnails. In this research project, we use various forensics tools to collect left thumbnail information from deleted videos or pictures. We examine and describe the various thumbnail sources in Windows and propose a methodology for thumbnail collection and analysis from laptops or desktops. A machine learning algorithm is adopted to help speed up content from thumbnail pictures.

Keywords: digital forensic, forensic tools, soundness, thumbnail, machine learning, OCR

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6163 Design and Implementation of an AI-Enabled Task Assistance and Management System

Authors: Arun Prasad Jaganathan

Abstract:

In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

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6162 The Impact of a Cognitive Acceleration Program on Prospective Teachers' Reasoning Skills

Authors: Bernardita Tornero

Abstract:

Cognitive Acceleration in Mathematics Education (CAME) programmes have been used successfully for promoting the development of thinking skills in school students for the last 30 years. Given that the approach has had a tremendous impact on the thinking capabilities of participating students, this study explored the experience of using the programme with prospective primary teachers in Chile. Therefore, this study not only looked at the experience of prospective primary teachers during the CAME course as learners, but also examined how they perceived the approach from their perspective as future teachers, as well as how they could transfer the teaching strategies they observed to their future classrooms. Given the complexity of the phenomenon under study, this research used a mixed methods approach. For this reason, the impact that the CAME course had on prospective teachers’ thinking skills was not only approached by using a test that assessed the participants’ improvements in these skills, but their learning and teaching experiences were also recorded through qualitative research tools (learning journals, interviews and field notes). The main findings indicate that, at the end of the CAME course, prospective teachers not only demonstrated higher thinking levels, but also showed positive attitudinal changes towards teaching and learning in general, and towards mathematics in particular. The participants also had increased confidence in their ability to teach mathematics and to promote thinking skills in their students. In terms of the CAME methodology, prospective teachers not only found it novel and motivating, but also commented that dealing with the thinking skills topic during a university course was both unusual and very important for their professional development. This study also showed that, at the end of the CAME course, prospective teachers felt they had developed strategies that could be used in their classrooms in the future. In this context, the relevance of the study is not only that it described the impact and the positive results of the first experience of using a CAME approach with prospective teachers, but also that some of the conclusions have significant implications for the teaching of thinking skills and the training of primary school teachers.

Keywords: cognitive acceleration, formal reasoning, prospective teachers, initial teacher training

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6161 The Structuring of Economic of Brazilian Innovation and the Institutional Proposal to the Legal Management for Global Conformity to Treat the Technological Risks

Authors: Daniela Pellin, Wilson Engelmann

Abstract:

Brazil has sought to accelerate your development through technology and innovation as a response to the global influences, which has received in internal management practices. For this, it had edited the Brazilian Law of Innovation 13.243/2016. However observing the Law overestimated economic aspects the respective application will not consider the stakeholders and the technological risks because there is no legal treatment. The economic exploitation and the technological risks must be controlled by limits of democratic system to find better social development to contribute with the economics agents for making decision to conform with global directions. The research understands this is a problem to face given the social particularities of the country because there has been the literal import of the North American Triple Helix Theory consolidated in developed countries and the negative consequences when applied in developing countries. Because of this symptomatic scenario, it is necessary to create adjustment to conduct the management of the law besides social democratic interests to increase the country development. For this, therefore, the Government will have to adopt some conducts promoting side by side with universities, civil society and companies, informational transparency, catch of partnerships, create a Confort Letter document for preparation to ensure the operation, joint elaboration of a Manual of Good Practices, make accountability and data dissemination. Also the Universities must promote informational transparency, drawing up partnership contracts and generating revenue, development of information. In addition, the civil society must do data analysis about proposals received for discussing to give opinion related. At the end, companies have to give public and transparent information about investments and economic benefits, risks and innovation manufactured. The research intends as a general objective to demonstrate that the efficiency of the propeller deployment will be possible if the innovative decision-making process goes through the institutional logic. As specific objectives, the American influence must undergo some modifications to better suit the economic-legal incentives to potentiate the development of the social system. The hypothesis points to institutional model for application to the legal system can be elaborated based on emerging characteristics of the country, in such a way that technological risks can be foreseen and there will be global conformity with attention to the full development of society as proposed by the researchers.The method of approach will be the systemic-constructivist with bibliographical review, data collection and analysis with the construction of the institutional and democratic model for the management of the Law.

Keywords: development, governance of law, institutionalization, triple helix

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6160 Private Universities and Socio-Economic Development of Host Communities: The Case of Fountain University, Nigeria

Authors: Ganiyu Rasaq Omokeji

Abstract:

The growing recognition of the pivotal role of universities in promoting socio-economic development has led to a focus upon the expansion of the sector around the world. As the economy and society become more ‘knowledge intensive’, the role of universities in development is more onerous than just teaching, research, and service. It is to help create the open society upon which the progress of ideas depends on. Driven to fulfill this role, universities are likely to become even more important in building regional networks of their host communities. Currently, there are about 129 universities in Nigeria, with a total number of 37 federal, 36 state, and 56 privately owned universities. Fountain University is among the private universities in Nigeria located in Osogbo, Osun State. The university is committed to the total development of men and women in an enabling environment, through appropriate teaching, research, and service to humanity, influenced by Islamic ethics and culture. The university focuses on educational development and growth that are relevant to the nation’s manpower needs and global competitiveness through a gradual but steady process. This paper examines the role of Private University in the socio-economic development of host community using Fountain University as a case study. The research methodology design for this paper has a total of 200 respondents. The research instrument of data collection was a questionnaire and in-depth interview (IDI). The finding reveals that Fountain University plays an important role in socio-economic and cultural development through their Islamic culture. The paper recommend that universities must bridge the gaps between creative individual with innovative ideas and the application of technology for economic progress and social betterment of their host communities. University also must serve as a bridge that carries the traffic of social and economic development.

Keywords: private university, socio-economic development, host communities, role of universities and community development

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6159 Utilization of Secure Wireless Networks as Environment for Learning and Teaching in Higher Education

Authors: Mohammed A. M. Ibrahim

Abstract:

This paper investigate the utilization of wire and wireless networks to be platform for distributed educational monitoring system. Universities in developing countries suffer from a lot of shortages(staff, equipment, and finical budget) and optimal utilization of the wire and wireless network, so universities can mitigate some of the mentioned problems and avoid the problems that maybe humble the education processes in many universities by using our implementation of the examinations system as a test-bed to utilize the network as a solution to the shortages for academic staff in Taiz University. This paper selects a two areas first one quizzes activities is only a test bed application for wireless network learning environment system to be distributed among students. Second area is the features and the security of wireless, our tested application implemented in a promising area which is the use of WLAN in higher education for leering environment.

Keywords: networking wire and wireless technology, wireless network security, distributed computing, algorithm, encryption and decryption

Procedia PDF Downloads 326