Search results for: data-driven insights

Authors: Tracy Ho, Huann-Shyang Lin, Mina Lin

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This study investigated the different learning path of students with different learning attitude and learning styles in Arts Creation. Based on direct instruction, guided-discovery learning, and discovery learning theories, a tablet app including the following three learning areas were developed for students: (1) replication and remix practice area, (2) guided creation area, and (3) free creation area. Thirty. students with different learning attitude and learning styles were invited to use this app. Students’ learning behaviors were categorized and defined. The results will provide both educators and researchers with insights that can form a useful foundation for designing different content and strategy with the application of new technologies in school teaching. It also sheds light on how an educational App can be designed to enhance Arts Creation.

Keywords: App, arts creation, learning attitude, learning style, tablet

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Authors: Abdul Haq

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The goal of this research is to better understand how wind loads affect bridges and develop strategies for designing bridges that are more stable and resistant to wind. The effect of wind on bridges is essential to their safety and functionality, especially in areas that are prone to high wind speeds or violent wind conditions. The study looks at the aerodynamic forces and vibrations caused by wind and how they affect bridge construction. Part of the research method involves first understanding the underlying ideas influencing wind flow near bridges. Computational fluid dynamics (CFD) simulations are used to model and forecast the aerodynamic behaviour of bridges under different wind conditions. These models incorporate several factors, such as wind directionality, wind speed, turbulence intensity, and the influence of nearby structures or topography. The results provide significant new insights into the loads and pressures that wind places on different bridge elements, such as decks, pylons, and connections. Following the determination of the wind loads, the structural response of bridges is assessed. By simulating their dynamic behavior under wind-induced forces, Finite Element Analysis (FEA) is used to model the bridge's component parts. This work contributes to the understanding of which areas are at risk of experiencing excessive stresses, vibrations, or oscillations due to wind excitations. Because the bridge has inherent modes and frequencies, the study considers both static and dynamic responses. Various strategies are examined to maximize the design of bridges to withstand wind. It is possible to alter the bridge's geometry, add aerodynamic components, add dampers or tuned mass dampers to lessen vibrations, and boost structural rigidity. Through an analysis of several design modifications and their effectiveness, the study aims to offer guidelines and recommendations for wind-resistant bridge design. In addition to the numerical simulations and analyses, there are experimental studies. In order to assess the computational models and validate the practicality of proposed design strategies, scaled bridge models are tested in a wind tunnel. These investigations help to improve numerical models and prediction precision by providing valuable information on wind-induced forces, pressures, and flow patterns. Using a combination of numerical models, actual testing, and long-term performance evaluation, the project aims to offer practical insights and recommendations for building wind-resistant bridges that are secure, long-lasting, and comfortable for users.

Keywords: wind effects, aerodynamic forces, computational fluid dynamics, finite element analysis

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Authors: Yechan Kim, Bonhyuk Ku, Minkyung Jung, Hyoungku Kang

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This study presents the remanufacturing of a 25kV gas insulated switchgear (GIS) that operated indoors for 27 years before being decommissioned due to aging. The research involved a detailed process of dismantling, visual inspection, component-wise examination, and various testing methodologies to assess the equipment's condition. The focus was on evaluating the GIS's integrity and feasibility for remanufacturing. The results highlight the potential of remanufacturing in extending the life of electrical power equipment, offering insights into the best practices, challenges, and technical considerations of such an undertaking. This contributes to a sustainable approach in the power industry, emphasizing the reuse and restoration of aging equipment.

Keywords: remanufacturing, dismantling, gas insulated switchgear, sustainability, life extension

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Masud Ibrahim

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in Ghana. The sample of the study comprised 450 bank customers from universal banks operating in Ghana. A conceptual framework was framed from a revised TAM model. A total of nine hypotheses were developed and tested using Structural Equation Modeling Technique. Findings from this study revealed that perceived ease of use and perceived usefulness are influenced positively by design and perceived security. Also, perceived ease of use, social influence and perceived security risk were found to have a strong influence on mobile banking app adoption intention. This study provides significant insights and implications for banking organizations on how to ensure the adoption and usage of their mobile banking apps.

Keywords: mobile banking app, perceived ease of use, perceived usefulness, technology acceptance model

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Authors: Muhammad Wahb

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Physical activity is increasingly recognized as a significant factor in maintaining optimal health and preventing chronic diseases. This research scrutinizes the long-term health benefits of sustained physical activity, employing a systematic review of epidemiological studies and randomized control trials conducted over the past decade. The study illuminates the protective effects of regular physical activity against cardiovascular disease, obesity, diabetes, and mental health disorders, with a special focus on the mechanisms involved. Furthermore, the paper provides insights into how public health initiatives can effectively promote physical activity among diverse populations, contributing to improved community health outcomes.

Keywords: physical activity, long-term health benefits, chronic disease prevention, public health

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Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: Iyad Alazzam, Kenneth Magel, Izzat Alsmadi

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The different activities and approaches in software testing try to find the most possible number of errors or failures with the least amount of possible effort. Mutation is a testing approach that is used to discover possible errors in tested applications. This is accomplished through changing one aspect of the software from its original and writes test cases to detect such change or mutation. In this paper, we present a mutation approach for testing software components integration aspects. Several mutation operations related to components integration are described and evaluated. A test case study of several open source code projects is collected. Proposed mutation operators are applied and evaluated. Results showed some insights and information that can help testing activities in detecting errors and improving coverage.

Keywords: software testing, integration testing, mutation, coverage, software design

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Authors: Pappas Theodoros, Mihail Diakomihalis

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Measuring the economic impact of tourism in a benchmark economy is a global concern, with previous measurements being partial and not fully integrated. Tourism is a phenomenon that requires individual consumption of visitors and which should be observed and measured to reveal, thus, the overall contribution of tourism to an economy. The Tourism Satellite Account (TSA) is a critical tool for assessing the annual growth of tourism, providing reliable measurements. This article introduces a system of TSA information that encompasses all the works of the TSA, including input, storage, management, and analysis of data, as well as additional future functions and enhances the efficiency of tourism data management and TSA collection utility. The methodology and results presented offer insights into the development and implementation of TSA.

Keywords: tourism satellite account, information system, data-based tourist account, relation database

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Authors: Gholam Reza Parvizi, Ali Reza Kargar, Amir Arani

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In the present days, learning and teaching researchers have emphasized the role which teachers, tutors, and trainers’ constraint knowledge treat in resizing and trimming what they perform in educational atmosphere. Regarding English language as subject to teaching, although the prominence of instructor’s knowledge about grammar has also been stressed, but the lack of empirical insights into the relationship between teacher’ self-monitoring and self-response of grammar knowledge have been observed. With particular attention to the grammar this article indicates and discusses information obtained self- feedback and conversing teachers of a kind who backwash the issue. The result of the study indicates that enabling teachers to progress and maintain a logical and realistic awareness of their knowledge about grammar have to be prominent goal for teachers’ education and development programs.

Keywords: grammar knowledge, self-monitoring, self-response, teaching grammar, language teaching program

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Authors: Suraini Mohd Rhouse, Noor Lela Ahmad, Nek Kamal Yeop Yunus, Rosfizah Md Taib

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This article aims to explore the importance of trust to women entrepreneurs. In particular, the research uses a social constructionist lens to examine ways in which women entrepreneurs construct trust in relation to their various stakeholders. A semi-structured interview was used to gather the data. The findings suggest women highlight the importance of trust in order to establish customer satisfaction that can further develop customer loyalty. In addition, aspect of trust with the employees is seen as vital for building organizational commitment to the business organization. Women also see the trust dimension in terms of their relationships with financial providers in order to gain approval for financial resources. This article contributes to the literature on the value of trust to women’s business environments.

Keywords: qualitative, social constructionist, trust, women entrepreneurship

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Authors: Mona Mohamed Shawkt Ragab, Heba Mohamed Darwish

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Context: Comfort properties of garments are crucial for the wearer, and with the increasing demand for cotton fabric, there is a need to explore alternative fabrics that can offer similar or superior comfort properties. This study focuses on comparing the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the aim of identifying fabrics that are more suitable for summer clothes. Research Aim: The aim of this study is to evaluate the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the goal of identifying fabrics that can serve as alternatives to cotton, considering their comfort properties for summer clothing. Methodology: An experimental, analytical approach was employed in this study. Two circular knitting machines were used to produce the fabrics, one with a 24 inches gauge and the other with a 28 inches gauge. Both fabrics were knitted with three different loop lengths (3.05 mm, 2.9 mm, and 2.6 mm) to obtain loose, medium, and tight fabrics for evaluation. Various comfort properties, including air permeability, water vapor permeability, wickability, and thermal resistance, were measured for both fabric types. Findings: The study found a significant difference in comfort properties between tencel/cotton single jersey fabric and cotton single jersey fabric. Tencel/cotton fabric exhibited higher air permeability, water vapor permeability, and wickability compared to cotton fabric. These findings suggest that tencel fabric is more suitable for summer clothes due to its superior ventilation and absorption properties. Theoretical Importance: This study contributes to the exploration of alternative fabrics to cotton by evaluating their comfort properties. By identifying fabrics that offer better comfort properties than cotton, particularly in terms of water usage, the study provides valuable insights into sustainable fabric choices for the fashion industry. Data Collection and Analysis Procedures: The comfort properties of the fabrics were measured using appropriate testing methods. Paired comparison t-tests were conducted to determine the significant differences between tencel/cotton fabric and cotton fabric in the measured properties. Correlation coefficients were also calculated to examine the relationships between the factors under study. Question Addressed: The study addresses the question of whether tencel/cotton single jersey fabric can serve as an alternative to cotton fabric for summer clothes, considering their comfort properties. Conclusion: The study concludes that tencel/cotton single jersey fabric offers superior comfort properties compared to cotton single jersey fabric, making it a suitable alternative for summer clothes. The findings also highlight the importance of considering fabric properties, such as air permeability, water vapor permeability, and wickability, when selecting materials for garments to enhance wearer comfort. This research contributes to the search for sustainable alternatives to cotton and provides valuable insights for the fashion industry in making informed fabric choices.

Keywords: comfort properties, cotton fabric, tencel fabric, single jersey

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Authors: Mohammad Asadpour, Maryam Sadeghi, Mahmoud Jafari

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The transformation of carbon dioxide into fuels and commodity chemicals is considered one of the most attractive methods to meet energy demands and reduce atmospheric CO₂ levels. Cobalt complexes have previously shown high faradaic efficiency in the reduction of CO₂ to CO. In this study, a nanostructure, referred to as a porphyrin-like buckyball, is simulated and analyzed for its electrical properties. The investigation aims to understand the unique characteristics of this material and its potential applications in electronic devices. Through computational simulations and analysis, the electrocatalytic reduction of CO₂ to CO by Cobalt-porphyrin-like buckyball is explored. The findings of this study offer valuable insights into the electrocatalytic properties of this predicted structure, paving the way for further research and development in the field of nanotechnology.

Keywords: porphyrin-like buckyball, DFT, nanomaterials, CO₂ to CO

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Authors: Kriuk Boris, Kriuk Fedor

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This paper presents a comparative study of fundamental similarity functions for Siamese networks in semantic textual similarity (STS) tasks. We evaluate various similarity functions using the STS Benchmark dataset, analyzing their performance and stability. Additionally, we introduce a multi-objective approach for optimal threshold selection. Our findings provide insights into the effectiveness of different similarity functions and offer a straightforward method for threshold selection optimization, contributing to the advancement of Siamese network architectures in STS applications.

Keywords: siamese networks, semantic textual similarity, similarity functions, STS benchmark dataset, threshold selection

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Authors: Johnstone Walubengo Wangusi

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Climate change is undeniably altering the frequency, intensity, and geographic distribution of extreme weather events worldwide. In this paper, we explore the complex interconnections between climate change and extreme weather phenomena, drawing upon research from atmospheric science, geology, and climatology. We examine the underlying mechanisms driving these changes, the impacts on natural ecosystems and human societies, and strategies for adaptation and mitigation. By synthesizing insights from interdisciplinary research, this paper aims to provide a comprehensive understanding of the multifaceted relationship between climate change and extreme weather, informing efforts to address the challenges posed by a changing climate.

Keywords: climate change, extreme weather, atmospheric science, geology, climatology, impacts, adaptation, mitigation

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Authors: Balarabe Nkom, Adam P. R. Taylor, Craig Baguley

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Power Line Communications (PLC) is being employed in existing power systems, despite the infrastructure not being designed with PLC considerations in mind. Given that power transformers can last for decades, the distribution transformer in particular exists as a relic of un-optimized technology. To determine issues that may need to be addressed in subsequent designs of such transformers, it is essential to have a highly accurate transformer model for simulations and subsequent optimization for the PLC environment, with a view to increase data speed, throughput, and efficiency, while improving overall system stability and reliability. This paper reviews various methods currently available for creating transformer models and provides insights into the requirements of each for obtaining high accuracy. The review indicates that a combination of traditional analytical methods using a hybrid approach gives good accuracy at reasonable costs.

Keywords: distribution transformer, modelling, optimization, power line communications

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Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

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This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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Authors: Jerome D. Donovan

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The pandemic has resulted in a dramatic re-consideration of the reliance on international student fees to support university models in Australia. A key resulting initiative for the Australian Federal Government has been shifting the way universities consider their research model, emphasising the importance of commercialising research. This study specifically examines this shift from the perspective of a university spin-off, examining how university support structures and incubation models have assisted in the translation of fundamental research into a high-growth university spin-off. A focused case study approach is adopted in this study, using an auto-ethnographic research method to document the experiences and insights drawn from being a co-founder in a university spin-off in a time where research commercialisation has emerged as a central focus in Australian universities.

Keywords: research commercialisation, spin-offs, university incubation, entrepreneurship

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Authors: Vehbi Gorgulu

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The primary objective of the current study is to explore how brand managers can employ Internet memes as a marketing tool. Internet memes are marked for their sarcastic and entertaining content and their amateur/DIY natures. The current study focuses on #TFWGucci, a collaborative marketing project enacted by Gucci, which is marked for being one of the first structured collaborative memetic marketing campaigns in the world. By embracing a qualitative approach, the study will explore production and meaning making processes of #TFWGucci campaign via analysis of sample campaign contents. The study will provide hints and insights for digital marketers on how to employ memetic marketing strategies in successful ways.

Keywords: meme, internet meme, online marketing, memetic marketing, #TFWGucci

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Authors: Milad Abolfazli, Milad Bazli

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In this critical review, the topic of how composites maintain their tensile strength when exposed to elevated temperatures will be studied. A comprehensive database of 761 tests have been analyzed and closely examined to study the various factors that affect the strength retention. Conclusions are drawn from the collective research efforts of numerous scholars who have investigated this subject. Through the analysis of these tests, the relationships between the tensile strength retention and various effective factors are investigated. This review is meant to be a practical resource for researchers and engineers. It provides valuable information that can guide the development of composites tailored for high-temperature applications. By offering a deeper understanding of how composites behave in extreme heat, the paper contributes to the advancement of materials science and engineering.

Keywords: tesnile tests, high temperatures, FRP composites, mechanical perfomance

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Authors: Hsien-Tsen Wang

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Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: Tran Thi Thuy Oanh, Nguyen Ngoc Bao Tran

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In the view of Cognitive Linguistics (CL), knowledge and experience of things and events are used by human beings in expressing concepts, especially in their daily life. The human conceptual system is considered to be fundamentally metaphorical in nature. It is also said that the way we think, what we experience, and what we do everyday is very much a matter of language. In fact, language is an integral factor of cognition in that CL is a family of broadly compatible theoretical approaches sharing the fundamental assumption. The relationship between language and thought, of course, has been addressed by many scholars. CL, however, strongly emphasizes specific features of this relation. By experiencing, we receive knowledge of lives. The partial things are ideal domains, we make use of all aspects of this domain in metaphorically understanding abstract targets. The paper refered to applying this theory on pragmatics lessons for major English students at University of Foreign Language Studies - The University of Da Nang, Viet Nam. We conducted the study with two third – year students groups studying English pragmatics lessons. To clarify this study, the data from these two classes were collected for analyzing linguistic perspectives in the view of CL and traditional concepts. Descriptive, analytic, synthetic, comparative, and contrastive methods were employed to analyze data from 50 students undergoing English pragmatics lessons. The two groups were taught how to transfer the meanings of expressions in daily life with the view of CL and one group used the traditional view for that. The research indicated that both ways had a significant influence on students' English translating and interpreting abilities. However, the traditional way had little effect on students' understanding, but the CL view had a considerable impact. The study compared CL and traditional teaching approaches to identify benefits and challenges associated with incorporating CL into the curriculum. It seeks to extend CL concepts by analyzing metaphorical expressions in daily conversations, offering insights into how CL can enhance language learning. The findings shed light on the effectiveness of applying CL in teaching and learning English pragmatics. They highlight the advantages of using metaphorical expressions from daily life to facilitate understanding and explore how CL can enhance cognitive processes in language learning in general and teaching English pragmatics to third-year students at the UFLS - UDN, Vietnam in personal. The study contributes to the theoretical understanding of the relationship between language, cognition, and learning. By emphasizing the metaphorical nature of human conceptual systems, it offers insights into how CL can enrich language teaching practices and enhance students' comprehension of abstract concepts.

Keywords: cognitive linguisitcs, lakoff and johnson, pragmatics, UFLS

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Authors: Gerhard D. Muller, Nadine C. Sonnenberg, Suné Donoghue

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This study delves into the intricacies of male and female consumers’ perceptions of Corporate Social Responsibility (CSR) in the South African clothing retail sector, a sector experiencing increasing consumption, yet facing significant environmental and social challenges. The aim is to discern between male and female consumers’ perceptions of clothing retailers’ CSR initiatives based on the Triple Bottom Line (TBL) framework, which evaluates organizational sustainability across social, environmental, and economic domains. Methodologically, the study is embedded in a quantitative research paradigm adopting a cross-sectional survey design. A purposive sampling strategy was used to recruit male and female respondents from a diverse South African demographic background. A structured questionnaire was developed and included established consumer CSR perception scales that were adapted for the purposes of this study. The questionnaire was distributed via online platforms. The data collected from the online survey, were split by gender to allow for comparison between male and female consumers’ perceptions of clothing retailers’ CSR initiatives. Exploratory Factor Analysis (EFA) was conducted on each of the datasets. The EFA for females revealed a five-factor solution, whereas the male EFA presented a six-factor solution, with the notable addition of an Economic Performance dimension. Results indicate subtle differences in the gender groups’ CSR perceptions. While both genders seem to value clothing retailers’ focus on quality services, females seem to have more pronounced perceptions surrounding clothing retailers’ contributions to social and environmental causes. Males, on the other hand, seem to be more discerning in their perceptions surrounding clothing retailers’ support of social and environmental causes. Ethical stakeholder relationships emerged as a shared concern across genders. Still, males presented a distinct factor, Economic Performance, highlighting a gendered divergence in the weighting of economic success and financial performance in CSR evaluation. The implications of these results are multifaceted. Theoretically, the study enriches the discourse on CSR by integrating gender insights into the TBL framework, offering a greater understanding of consumers’ CSR perceptions in the South African clothing retail context. Practically, it provides actionable insights for clothing retailers, suggesting that CSR initiatives should be gender-sensitive and communicate the TBL's elements effectively to resonate with the pertinent concerns of each segment. Additionally, the findings advocate for a contextualized approach to CSR in emerging markets that aligns with local cultural and social differences.

Keywords: consumer perceptions, corporate Social responsibility, gender differentiation, triple bottom line

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Authors: Almontas Vilutis, Vytenis Jankauskas

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The paper presents the results of the investigation of the dry sliding friction of wood-plastic composites (WPCs) against WC-Co cemented carbide. The dependence of the dynamic coefficient of friction on the main influencing factors (vertical load, temperature, and sliding distance) was investigated by evaluating their mutual interaction. Multiple regression analysis showed a high polynomial dependence (adjusted R2 > 0.98). The resistance of the composite to thermo-mechanical effects determines how temperature and force factors affect the magnitude of the coefficient of friction. WPC-B composite has the lowest friction and highest resistance compared to WPC-A, while composite and cemented carbide materials wear the least. Energy dispersive spectroscopy (EDS), based on elemental composition, provided important insights into the friction process.

Keywords: friction, composite, carbide, factors

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Authors: Bharti Singh, Shri K. Singh

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Child malnutrition is a multifaceted issue that transcends geographical boundaries. Malnutrition not only stunts physical growth but also leads to a spectrum of morbidities and child mortality. It is one of the leading causes of death (~50 %) among children under age five. Despite economic progress and advancements in healthcare, child malnutrition remains a formidable challenge for India. The objective is to investigate the impact of women's empowerment on child nutrition outcomes in India from 2006 to 2021. A composite index of women's empowerment was constructed using Confirmatory Factor Analysis (CFA), a rigorous technique that validates the measurement model by assessing how well-observed variables represent latent constructs. This approach ensures the reliability and validity of the empowerment index. Secondly, kernel density plots were utilised to visualise the distribution of key nutritional indicators, such as stunting, wasting, and overweight. These plots offer insights into the shape and spread of data distributions, aiding in understanding the prevalence and severity of malnutrition. Thirdly, linear polynomial graphs were employed to analyse how nutritional parameters evolved with the child's age. This technique enables the visualisation of trends and patterns over time, allowing for a deeper understanding of nutritional dynamics during different stages of childhood. Lastly, multilevel analysis was conducted to identify vulnerable levels, including State-level, PSU-level, and household-level factors impacting undernutrition. This approach accounts for hierarchical data structures and allows for the examination of factors at multiple levels, providing a comprehensive understanding of the determinants of child malnutrition. Overall, the utilisation of these statistical methodologies enhances the transparency and replicability of the study by providing clear and robust analytical frameworks for data analysis and interpretation. Our study reveals that NFHS-4 and NFHS-5 exhibit an equal density of severely stunted cases. NFHS-5 indicates a limited decline in wasting among children aged five, while the density of severely wasted children remains consistent across NFHS-3, 4, and 5. In 2019-21, women with higher empowerment had a lower risk of their children being undernourished (Regression coefficient= -0.10***; Confidence Interval [-0.18, -0.04]). Gender dynamics also play a significant role, with male children exhibiting a higher susceptibility to undernourishment. Multilevel analysis suggests household-level vulnerability (intra-class correlation=0.21), highlighting the need to address child undernutrition at the household level.

Keywords: child nutrition, India, NFHS, women’s empowerment

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Authors: Chandan Jha, Amit Sachan, Arnab Adhikari, Sayantan Kundu

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The purpose of this study is to evaluate the performance of Higher Education Institutions (HEIs) of India and examine the impact of urbanization on the performance of HEIs. In this study, the Data Envelopment Analysis (DEA) has been used, and the authors have collected the required data related to performance measures from the National Institutional Ranking Framework web portal. In this study, the authors have evaluated the performance of HEIs by using two different DEA models. In the first model, geographic locations of the institutes have been categorized into two categories, i.e., Urban Vs. Non-Urban. However, in the second model, these geographic locations have been classified into three categories, i.e., Urban, Semi-Urban, Non-Urban. The findings of this study provide several insights related to the degree of urbanization and the performance of HEIs.

Keywords: DEA, higher education, performance evaluation, urbanization

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Authors: Marcel Randermann, Roland Jochem

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Research activities are mostly conducted in form of projects. In fact, research projects take the highest share of all project forms combined. However, project management is very rarely applied purposefully by researchers and scientists. More specifically no project management frameworks, methods or tools are not being used to plan, execute or control research project to ensure research success or improve project quality. In this qualitative study, several interviews were conducted with scientists and research managers from German institutions to gain insights into project management activities, to determine challenges and barriers, and to evaluate premises for successful project management. The analyses show that conventional project management is not easily applicable in scientific environments and researchers’ mindsets prevent a reasonable application.

Keywords: academics, project management methods, research and science projects, scientist's mindset

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Authors: M. Holle, M. Roth, M. R. Gürtler, U. Lindemann

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This paper gives insights into the research project "InnoCyFer" (in the form of an outlook) which is funded by the German Federal Ministry of Economics and Technology. Enabling the integrated customer individual product design as well as flexible manufacturing of these products are the main objectives of the project. To achieve this, a web-based open innovation-platform containing an integrated Toolkit will be developed. This toolkit enables the active integration of the customer’s creativity and potentials of innovation in the product development process. Furthermore, the project will show the chances and possibilities of customer individualized products by building and examining the continuous process from innovation through the customers to the flexible manufacturing of individual products.

Keywords: customer individual product design, innovation networks, open innovation, open innovation platform, toolkit

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Authors: Georgia Pozoukidou

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TELUM software is a land use model designed specifically to help metropolitan planning organizations (MPOs) prepare their transportation improvement programs and fulfill their numerous planning responsibilities. In this context obtaining, preparing, and validating socioeconomic forecasts are becoming fundamental tasks for an MPO in order to ensure that consistent population and employment data are provided to travel demand models. Chittenden County Metropolitan Planning Organization of Vermont State was used as a case study to test the applicability of TELUM land use model. The technical insights and lessons learned from the land use model application have transferable value for all MPOs faced with land use forecasting development and transportation modelling.

Keywords: calibration data requirements, land use models, land use planning, metropolitan planning organizations

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