Search results for: learning integration

Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

Procedia PDF Downloads 44

Authors: Ioannis Andrianakis, Panagiotis Panagiotopoulos, Kyriakos Chatzidimitriou, Dimitrios Tampakis, Manolis Falelakis

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Live music, whether performed in organized venues, restaurants, hotels or any other spots, creates value chains that support and develop local economies and tourism development. In this paper, we describe PerformAnts, a platform that increases the mobility of musicians and their accessibility to remotely located venues by rationalizing the cost of live acts. By analyzing the event history and taking into account their potential availability, the platform provides bespoke recommendations to both bands and venues while also facilitating the organization of tours and helping rationalize transportation expenses by realizing an innovative mechanism called “chain booking”. Moreover, the platform provides an environment where complicated tasks such as technical and financial negotiations, concert promotion or copyrights are easily manipulated by users using best practices. The proposed solution provides important benefits to the whole spectrum of small/medium size concert organizers, as the complexity and the cost of the production are rationalized. The environment is also very beneficial for local talent, musicians that are very mobile, venues located away from large urban areas or in touristic destinations, and managers who will be in a position to coordinate a larger number of musicians without extra effort.

Keywords: machine learning, music industry, creative industries, web applications

Procedia PDF Downloads 97

Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal

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Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.

Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test

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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, SamutSongkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: (1) The identity of Amphur (District) Mueang, SamutSongkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. (2) The communication of the identity of AmphurMueang, SamutSongkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of AmphurMueang, SamutSongkram province 2) WatPhetSamutWorrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep AmphurMueang, SamutSongkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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Authors: Chiu-Wen Chang, I-Yun Chang, Wei-Ting Chen, Hui-Ping Ho, Ruei-Hun Chang, Joh-Jong Huang

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Kaohsiung City is located in the tropical region where has Aedes aegypti and Aedes albopictus distributed; once the virus invades, it’s can easily trigger local epidemic. Besides, Kaohsiung City has a world-class airport and harbor, trade and tourism are close and frequently with every country, especially with the Southeast Asian countries which also suffer from dengue. Therefore, Kaohsiung City faces the difficult challenge of dengue every year. The objectives of this study was to enhance dengue clinical care, border management and vector surveillance in Kaohsiung City by establishing an larger scale, innovatively and more coordinated dengue prevention and control strategies in 2016, including (1) Integrated medical programs: facilitated 657 contract medical institutions, widely set up NS1 rapid test in clinics, enhanced triage and referrals system, dengue case daily-monitoring management (2) Border quarantine: comprehensive NS1 screening for foreign workers and fisheries when immigration, hospitalization and isolation for suspected cases, health education for high risk groups (foreign students, other tourists) (3) Mosquito control: Widely use Gravitrap to monitor mosquito density in environment, use NS1 rapid screening test to detect community dengue virus (4) Health education: create a dengue app for people to immediately inquire the risk map and nearby medical resources, routine health education to all districts to strengthen public’s dengue knowledge, neighborhood cleaning awards program. The results showed that after new integration of dengue prevention and control strategies fully implemented in Kaohsiung City, the number of confirmed cases in 2016 declined to 342 cases, the majority of these cases are the continuation epidemic in 2015; in fact, only two cases confirmed after the 2016 summer. Besides, the dengue mortality rate successfully decreased to 0% in 2016. Moreover, according to the reporting rate from medical institutions in 2014 and 2016, it dropped from 27.07% to 19.45% from medical center, and it decreased from 36.55% to 29.79% from regional hospital; however, the reporting rate of district hospital increased from 11.88% to 15.87% and also increased from 24.51% to 34.89% in general practice clinics. Obviously, it showed that under the action of strengthening medical management, it reduced the medical center’s notification ratio and improved the notification ratio of general clinics which achieved the great effect of dengue clinical management and dengue control.

Keywords: dengue control, integrated control strategies, clinical management, NS1

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Authors: Oloyede Akinniyi Ojo

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This study investigated the relationship between truancy and academic performance of Colleges of Education students in southwestern, Nigeria. It also examined the relationship between College Physical environment and truancy behavior among students. Furthermore, it examined the relationship between male and female students involvement in truancy behavior. Purposive sampling was used to select four colleges of education in south-western Nigeria and 120 students per college were selected from year 3 while stratified sampling was used to select schools and courses. A total of 480 students participated in the study. Three research instruments were used for this study namely: Lecturers Attendance Record, Students Statement of Result and ‘College Environment Questionnaires’ (CEQ). Four research questions guided the study. Data was analyzed using descriptive, Chi-square and T-Test. CEQ was validated by a team of experts in the field of educational evaluation. Test reliability was established at an r=0-74. The study concluded that truancy exist in colleges of education and that there was a significant relationship between truancy and academic performance of male and female truants, the study also revealed that physical environment has so much effect on the truancy behavior of the students, hence the study recommended that effort should be made to provide attractive college environment for effective learning.

Keywords: academic performance, colleges of education, students, truancy

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

Procedia PDF Downloads 125

Authors: K. Shaloom Mbambu, M. Pascal Tshimbalanga, K. Ruth Mutala, K. Roger Kabuya, N. Dieudonné Kabeya, Y. L. Kabeya Mukeba

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In this article, the authors examine the even more worrying situation of girls in sub-Saharan Africa. Two-girls on five are private of Global Education, which represents a real loss to the development of communities and countries. Cultural traditions, poverty, violence, early and forced marriages, early pregnancies, and many other gender inequalities were the causes of this cancer development. Namely, "it is no more efficient development tool that is educating girls." The non-schooling of girls and their lack of supervision by liberal professions have serious consequences for the life of each of them. To improve the conditions of their inferior status, girls to men introduce poverty and health risks. Raising awareness among parents and communities on the importance of girls' education, improving children's access to school, girl-boy equality with their rights, creating income, and generating activities for girls, girls, and girls learning of liberal trades to make them self-sufficient. Organizations such as the United Nations Organization can save the children. ASEAD and the AEDA group are predicting the impact of this cancer on the development of a nation's future generation must be preserved.

Keywords: young girl, Sub-Saharan Africa, higher and vocational education, development, society, environment

Procedia PDF Downloads 254

Authors: Nzereogu Stella Kosi, Igwe Ogbonnaya, Emeh Chukwuebuka Odinaka

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A comparative analysis of the expansion rate and soil erodibility of some gullies in Nnewi and Nnobi both of Nanka Formation were studied. The study involved an integration of field observations, geotechnical analysis, slope stability analysis, multivariate statistical analysis, gully expansion rate analysis, and determination of the soil erodibility factor (K) from Revised Universal Soil Loss Equation (RUSLE). Fifteen representative gullies were studied extensively, and results reveal that the geotechnical properties of the soil, topography, vegetation cover, rainfall intensity, and the anthropogenic activities in the study area were major factors propagating and influencing the erodibility of the soils. The specific gravity of the soils ranged from 2.45-2.66 and 2.54-2.78 for Nnewi and Nnobi, respectively. Grain size distribution analysis revealed that the soils are composed of gravel (5.77-17.67%), sand (79.90-91.01%), and fines (2.36-4.05%) for Nnewi and gravel (7.01-13.65%), sand (82.47-88.67%), and fines (3.78-5.02%) for Nnobi. The soils are moderately permeable with values ranging from 2.92 x 10-5 - 6.80 x 10-4 m/sec and 2.35 x 10-6 - 3.84 x 10⁻⁴m/sec for Nnewi and Nnobi respectively. All have low cohesion values ranging from 1–5kPa and 2-5kPa and internal friction angle ranging from 29-38° and 30-34° for Nnewi and Nnobi, respectively, which suggests that the soils have low shear strength and are susceptible to shear failure. Furthermore, the compaction test revealed that the soils were loose and easily erodible with values of maximum dry density (MDD) and optimum moisture content (OMC) ranging from 1.82-2.11g/cm³ and 8.20-17.81% for Nnewi and 1.98-2.13g/cm³ and 6.00-17.80% respectively. The plasticity index (PI) of the fines showed that they are nonplastic to low plastic soils and highly liquefiable with values ranging from 0-10% and 0-9% for Nnewi and Nnobi, respectively. Multivariate statistical analyses were used to establish relationship among the determined parameters. Slope stability analysis gave factor of safety (FoS) values in the range of 0.50-0.76 and 0.82-0.95 for saturated condition and 0.73-0.98 and 0.87-1.04 for unsaturated condition for both Nnewi and Nnobi, respectively indicating that the slopes are generally unstable to critically stable. The erosion expansion rate analysis for a fifteen-year period (2005-2020) revealed an average longitudinal expansion rate of 36.05m/yr, 10.76m/yr, and 183m/yr for Nnewi, Nnobi, and Nanka type gullies, respectively. The soil erodibility factor (K) are 8.57x10⁻² and 1.62x10-4 for Nnewi and Nnobi, respectively, indicating that the soils in Nnewi have higher erodibility potentials than those of Nnobi. From the study, both the Nnewi and Nnobi areas are highly prone to erosion. However, based on the relatively lower fine content of the soil, relatively lower topography, steeper slope angle, and sparsely vegetated terrain in Nnewi, soil erodibility and gully intensity are more profound in Nnewi than Nnobi.

Keywords: soil erodibility, gully expansion, nnewi-nnobi, slope stability, factor of safety

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Authors: Beverly Komen

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Online crimes have been on the rise in the recent days, especially with the hit of the covid-19 pandemic. The coronavirus pandemic has led to an unprecedented rise in screen time, this means more families are relying on technology and digital solutions to keep children learning, spending more time on the virtual platforms can leave children vulnerable to online abuse and exploitation. With ease access of affordable phones, internet, and increased online activities, all children are at risk of being abused online hence making the digital space unsafe for children. With these increased use of technology and its accessibility, children are at risk of facing challenges such as access to inappropriate content, online grooming, identity theft, cyber bullying, among other risks. The big question is; as we enjoy the benefits brought in by technology, how do we ensure that our children are save in this digital space? With the analysis of the current trends, there is a gap in knowledge on people’s understanding on child online protection and safety measures when using the digital space. A survey conducted among 50 parents in Nairobi in Kenya indicated that there is a gap in knowledge on online protection of children and over 50 % of the participants shared that for sure they have no idea on how to protect children online. This paper seeks to address the concept of child protection in the digital space and come up with viable solutions in protecting children from online vices.

Keywords: child protection, digital space, online risks, online grooming, cyber bulying, online child sexual exploitation, and abuse

Procedia PDF Downloads 186

Authors: Wedad Albalawi

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The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques, and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then, dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is an arbitrary nonempty closed subset of the real numbers. Then, the dynamic inequalities on time scales have received a lot of attention in the literature and has become a major field in pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on Hardy and Coposon inequalities, using Steklov operator on time scale in double integrals to obtain special cases of time-scale inequalities of Hardy and Copson on high dimensions. The advantage of this study is that it uses the one-dimensional classical Hardy inequality to obtain higher dimensional on time scale versions that will be applied in the solution of the Cauchy problem for the wave equation. In addition, the obtained inequalities have various applications involving discontinuous domains such as bug populations, phytoremediation of metals, wound healing, maximization problems. The proof can be done by introducing restriction on the operator in several cases. The concepts in time scale version such as time scales calculus will be used that allows to unify and extend many problems from the theories of differential and of difference equations. In addition, using chain rule, and some properties of multiple integrals on time scales, some theorems of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of hardy, inequality of coposon, steklov operator

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Authors: Bâlc Denisa-Maria

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This paper aims to present some ways of preserving a language heritage in the global era. Teaching a second language to foreign students does not imply only teaching the grammar and the vocabulary in order to reach the 4 skills, but it means constant work on developing strategies to make the students aware of the heritage that the language they learn has. Teachers and professors need to be aware of the fact that language is in constant change, they need to adjust their techniques to the digital era, but they also have to be aware of the changes, the good and the bad parts of globalizations. How is it possible to preserve the patrimony of a certain language in a globalized era? What transformations does a language face in time? What does it mean to preserve the heritage of a language through L2 teaching? What makes a language special? What impact does it have on the foreign students? How can we, as teachers, preserve the heritage of our language? Would it be everything about books, films, music, cultural events or what else? How is it possible to include digital programs in your teaching and preserving the patrimony of a language at the same time? How does computational linguistics help us in teaching a certain language? All these questions will be tackled during the essay, with special accent on the definition of a language heritage, the new perspectives for teachers/ professors, everything in a multimodal and complex way of presenting the context. The objectives of this research are: - to present some ways of preserving the heritage of a certain language against globalization - to illustrate what preservation means for L2 teaching - to encourage teachers to be aware of their language patrimony The main contributions of my research are on moving the discussion of preserving a certain language patrimony in the context of L2 teaching.

Keywords: preservation, globalization, language heritage, L2 teaching

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Authors: Hasan Husain Ali Abdulnabi

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Formative assessment feedback is increasingly practiced in higher education. Instructors allocate great time and effort to provide assessment feedback. However, educators are not sure about students’ perceptions, understanding and respond to the feedback given, as very limited research have been done about what students do with feedback and whether if they understand it. This study aims to explore students’ conceptions and perceptions of formative assessment feedback through questionnaire and focus group interviews. One hundred eighty undergraduate students doing different courses filled the questionnaire, and ten focus group discussions were conducted. Basic descriptive and content analyses were used to analyze students’ responses to the questionnaire, while grounded theory with open coding was used to analyze the focus group interviews. The study revealed that most students believe assessment feedback is helpful to improve their academic performance, and they take time to read, think and discuss their feedback. Also, the study shows most students understand the feedback given. However, students expressed that most of the written feedback given are too general, and they prefer individual oral feedback as it can lead to better understanding on how what and where to improve. The study concluded that students believe formative assessment feedback is valuable, students have reasonable understanding and respond to the feedback provided. However, this practice could be improved by requesting lecturers to make more specific feedback and communicate with students on the way of interpreting and using assessment feedback as a part of the learning and teaching process.

Keywords: assessment, feedback, formative, undergraduate, higher education

Procedia PDF Downloads 86

Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

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Authors: Nola Nahla Bacha

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Research has indicated that ESL/EFL (nonnative students of English) students have difficulty in reading at the university as often times the requirements are long texts in which both cultural and linguistic factors impede their understanding and thus their motivation. This is especially the case in literature courses. It is the author’s view that if readings are selected according to the students’ interests and linguistic level, related to life situations and coupled with film study they will not only be motivated to read, but they will find reading interesting and exciting. They will view novels, and thus literature, as a picture of life. Students will also widen their vocabulary repertoire and overcome many of their linguistic problems. This study describes the procedure used in in a 20th Century American Novel class at one English medium university in Lebanon and explores students’ views on the novels assigned and their recommendations. Findings indicate that students significantly like to read novels, contrary to what some faculty claim and view the inclusion of novels as helping them with expanding their vocabulary repertoire and learning about real life which helps them linguistically, pedagogically, and above all personally during their life in and out of the university. Annotated texts, pictures and film will be used through technological aids to show how the class was conducted and how the students’ interacted with the novels assigned. Implications for teaching reading in the classroom are made.

Keywords: language, literature, novels, reading, university teaching

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Authors: Samal Abzhanova, Saule Mussabekova

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Today, a new system of education is being created in Kazakhstan in order to develop the system of education and to satisfy the world class standards. For this purpose, there have been established new requirements and responsibilities to the instructors. Students should not be limited with providing only theoretical knowledge. Also, they should be encouraged to be competitive, to think creatively and critically. Moreover, students should be able to implement these skills into practice. These issues could be resolved through the permanent improvement of teaching methods. Therefore, a specialist who teaches the languages should use up-to-date methods and introduce new technologies. The result of the investigation suggests that an interactive teaching method is one of the new technologies in this field. This paper aims to provide information about implementing new technologies in the process of teaching language. The paper will discuss about necessity of introducing innovative technologies and the techniques of organizing interactive lessons. At the same time, the structure of the interactive lesson, conditions, principles, discussions, small group works and role-playing games will be considered. Interactive methods are carried out with the help of several types of activities, such as working in a team (with two or more group of people), playing situational or role-playing games, working with different sources of information, discussions, presentations, creative works and learning through solving situational tasks and etc.

Keywords: interactive education, interactive methods, system of education, teaching a language

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Authors: Nkosingiphile Mbusozayo Zungu

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The purpose of the current study is to adopt informetrics methods to analyse the research on phishing from 2012 to 2021 in three selected databases in order to contribute to global cybersecurity through impactful research. The study follows a quantitative research methodology. We opted for the positivist epistemology and objectivist ontology. The analysis focuses on: (i) the productivity of individual authors, institutions, and countries; (ii) the research contributions, using co-authorship as a measure of collaboration; (iii) the altmetrics of selected research contributions; (iv) the citation patterns and research impact of research on phishing; and (v) research contributions by keywords, to discover the concepts that are related to phishing. The preliminary findings favour developed countries in terms of quantity and quality of research in the domain. There are unique research trends and patterns in the developing countries, including those in Africa, that provide opportunities for research development in the domain in the region. This study explores an important research domain by using unexplored method in the region. The study supports the SDG Agenda 2030, such as ending abuse, exploitation, trafficking, and all other forms of violence and torture of children through the use of cyberspace (SDG 16). Further, the results from this study can inform research, teaching, and learning largely in Africa. Invariably, the study contributes to cybersecurity awareness that will mitigate cybersecurity threats against vulnerable communities.

Keywords: phishing, cybersecurity, informetrics, information security

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Authors: Sree Sanyal

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Research in ageing often highlights the age-related health dimension more than the psycho-social characteristics of the elderly, which also influences and challenges the health outcomes. Multimorbidity is defined as the person having more than one chronic non-communicable diseases and their prevalence increases with ageing. The study aims to evaluate the influence of social ties on self-reported prevalence of multimorbidity (selected chronic non-communicable diseases) among the selected states of elderly population in India. The data is accessed from Building Knowledge Base on Population Ageing in India (BKPAI), collected in 2011 covering the self-reported chronic non-communicable diseases like arthritis, heart disease, diabetes, lung disease with asthma, hypertension, cataract, depression, dementia, Alzheimer’s disease, and cancer. The data of the above diseases were taken together and categorized as: ‘no disease’, ‘one disease’ and ‘multimorbidity’. The predicted variables were demographic, socio-economic, residential types, and the variable of social ties includes social support, social engagement, perceived support, connectedness, and importance of the elderly. Predicted probability for multiple logistic regression was used to determine the background characteristics of the old in association with chronic morbidities showing multimorbidity. The finding suggests that 24.35% of the elderly are suffering from multimorbidity. Research shows that with reference to ‘no disease’, according to the socio-economic characteristics of the old, the female oldest old (80+) from others in caste and religion, widowed, never had any formal education, ever worked in their life, coming from the second wealth quintile standard, from rural Maharashtra are more prone with ‘one disease’. From the social ties background, the elderly who perceives they are important to the family, after getting older their decision-making status has been changed, prefer to stay with son and spouse only, satisfied with the communication from their children are more likely to have less single morbidity and the results are significant. Again, with respect to ‘no disease’, the female oldest old (80+), who are others in caste, Christian in religion, widowed, having less than 5 years of education completed, ever worked, from highest wealth quintile, residing in urban Kerala are more associated with multimorbidity. The elderly population who are more socially connected through family visits, public gatherings, gets support in decision making, who prefers to spend their later years with son and spouse only but stays alone shows lesser prevalence of multimorbidity. In conclusion, received and perceived social integration and support from associated neighborhood in the older days, knowing about their own needs in life facilitates better health and wellbeing of the elderly population in selected states of India.

Keywords: morbidity, multi-morbidity, prevalence, social ties

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Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

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Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

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Authors: Sarah Rietze, Hannes Zacher

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Daily stand-up meetings are the most commonly used method in agile teams. In daily stand-ups, team members gather to coordinate and align their efforts, typically for a predefined period of no more than 15 minutes. The primary purpose is to ask and answer the following three questions: What was accomplished yesterday? What will be done today? What obstacles are impeding my progress? Daily stand-ups aim to enhance communication, mutual understanding, and support within the team, as well as promote collective learning from mistakes through daily synchronization and transparency. The use of daily stand-ups is intended to positively influence psychological safety within teams, which is the belief that it is safe to show oneself and take personal risks. Two studies will be presented, which explore the relationships between daily stand-ups, psychological safety, and psychological well-being. In a first study, based on survey results (n = 318), we demonstrated that daily stand-ups have a positive indirect effect on job satisfaction and a negative indirect effect on turnover intention through their impact on psychological safety. In a second study, we investigate, using an experimental design, how the use of daily stand-ups in teams enhances psychological safety and well-being compared to a control group that does not use daily stand-ups. Psychological safety is considered one of the most crucial cultural factors for a sustainable, agile organization. Agile approaches, such as daily stand-ups, are a critical part of the evolving work environment and offer a proactive means to shape and foster psychological safety within teams.

Keywords: occupational wellbeing, agile work practices, psychological safety, daily stand-ups

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Patcharaporn Sakulpong, Wiriya Phokhwang

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Background: Banpunrug (Love Sharing House) established in 2013 provides a community-based palliative care for patients with cancer from 7 provinces in southern Thailand. These patients come to receive outpatient chemotherapy and radiotherapy at Suratthani Cancer Hospital. They are poor and uneducated; they need an accommodation during their 30-45 day course of therapy. Methods: A community-participatory action research (PAR) was employed to establish a model of palliative care for patients with cancer. The participants included health care providers, community, and patients and families. The PAR process includes problem identification and need assessment, community and team establishment, field survey, organization founding, model of care planning, action and inquiry (PDCA), outcome evaluation, and model distribution. Results: The model of care at Banpunrug involves the concepts of HHHS model, in that Banpunrug is a Home for patients; patients live in a house comfortable like in a Hotel resource; the patients are given care and living facilities similarly to those in a Hospital; the house is a School for patients to learn how to take care themselves, how to live well with cancer, and most importantly how to prepare themselves for a good death. The house is also a humanized care school for health care providers. Banpunrug’s philosophy of care is based on friendship therapy, social and spiritual support, community partnership, patient-family centeredness, Live & Love sharing house, and holistic and humanized care. With this philosophy, the house is managed as a home of the patients and everyone involved; everything is costless for all eligible patients and their family members; all facilities and living expense are donated from benevolent people, friends, and community. Everyone, including patients and family, has a sense of belonging to the house and there is no authority between health care providers and the patients in the house. The house is situated in a temple and a community and supported by many local nonprofit organizations and healthcare facilities such as a health promotion hospital at sub-disctrict level and Suratthani Cancer Hospital. Village health volunteers and multi-professional health care volunteers have contributed not only appropriate care, but also knowledge and experience to develop a distinguishing HHHS community-based palliative care model for patients with cancer. Since its opening the house has been a home for more than 400 patients and 300 family members. It is also a model for many national and international healthcare organizations and providers, who come to visit and learn about palliative care in and by community. Conclusions: The success of this palliative care model comes from community involvement, multi-professional volunteers and distributions, and concepts of HHHS model. Banpunrug promotes a consistent care across the cancer trajectory independent of prognosis in order to strengthen a full integration of palliative

Keywords: community-based palliative care, model, participatory action research, patients with cancer

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Authors: Aude Gounelle, Gloria Senfaute, Ludivine Saint-Mard, Thomas Chartier

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The long-term deformation rates of faults are not fully captured by Probabilistic Seismic Hazard Assessment (PSHA). PSHA that use catalogues to develop area or smoothed-seismicity sources is limited by the data available to constraint future earthquakes activity rates. The integration of faults in PSHA can at least partially address the long-term deformation. However, careful treatment of fault sources is required, particularly, in low strain rate regions, where estimated seismic hazard levels are highly sensitive to assumptions concerning fault geometry, segmentation and slip rate. When integrating faults in PSHA various constraints on earthquake rates from geologic and seismologic data have to be satisfied. For low strain rate regions where such data is scarce it would be especially challenging. Faults in PSHA requires conversion of the geologic and seismologic data into fault geometries, slip rates and then into earthquake activity rates. Several approaches exist for translating slip rates into earthquake activity rates. In the most frequently used approach, the background earthquakes are handled using a truncated approach, in which earthquakes with a magnitude lower or equal to a threshold magnitude (Mw) occur in the background zone, with a rate defined by the rate in the earthquake catalogue. Although magnitudes higher than the threshold are located on the fault with a rate defined using the average slip rate of the fault. As high-lighted by several research, seismic events with magnitudes stronger than the selected magnitude threshold may potentially occur in the background and not only at the fault, especially in regions of slow tectonic deformation. It also has been known that several sections of a fault or several faults could rupture during a single fault-to-fault rupture. It is then essential to apply a consistent modelling procedure to allow for a large set of possible fault-to-fault ruptures to occur aleatory in the hazard model while reflecting the individual slip rate of each section of the fault. In 2019, a tool named SHERIFS (Seismic Hazard and Earthquake Rates in Fault Systems) was published. The tool is using a methodology to calculate the earthquake rates in a fault system where the slip-rate budget of each fault is conversed into rupture rates for all possible single faults and faultto-fault ruptures. The objective of this paper is to compare the SHERIFS method with one other frequently used model to analyse the impact on the seismic hazard and through sensibility studies better understand the influence of key parameters and assumptions. For this application, a simplified but realistic case study was selected, which is in an area of moderate to hight seismicity (South Est of France) and where the fault is supposed to have a low strain.

Keywords: deformation rates, faults, probabilistic seismic hazard, PSHA

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Authors: Kwame Amoah

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Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

Procedia PDF Downloads 316

Authors: Heribert R. Kaijage, Samuel N. A. Codjoe, Simon H. D. Mamuya, Mangi J. Ezekiel

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There is strong evidence that climate has changed significantly affecting various sectors including public health. The recommended feasible solution is adopting development trajectories which combine both mitigation and adaptation measures for improving resilience pathways. This approach demands a consideration for complex interactions between climate and social-ecological systems. While other sectors such as agriculture and water have developed climate resilience indices, the public health sector in Tanzania is still lagging behind. The aim of this study was to find out how can we use Demographic and Health Surveys (DHS) linked with Remote Sensing (RS) technology and metrological information as tools to inform climate change resilient development and evaluation for the health sector. Methodological review was conducted whereby a number of studies were content analyzed to find appropriate indicators and indices for climate resilience household and their integration approach. These indicators were critically reviewed, listed, filtered and their sources determined. Preliminary identification and ranking of indicators were conducted using participatory approach of pairwise weighting by selected national stakeholders from meeting/conferences on human health and climate change sciences in Tanzania. DHS datasets were retrieved from Measure Evaluation project, processed and critically analyzed for possible climate change indicators. Other sources for indicators of climate change exposure were also identified. For the purpose of preliminary reporting, operationalization of selected indicators was discussed to produce methodological approach to be used in resilience comparative analysis study. It was found that household climate resilient index depends on the combination of three indices namely Household Adaptive and Mitigation Capacity (HC), Household Health Sensitivity (HHS) and Household Exposure Status (HES). It was also found that, DHS alone cannot complement resilient evaluation unless integrated with other data sources notably flooding data as a measure of vulnerability, remote sensing image of Normalized Vegetation Index (NDVI) and Metrological data (deviation from rainfall pattern). It can be concluded that if these indices retrieved from DHS data sets are computed and scientifically integrated can produce single climate resilience index and resilience maps could be generated at different spatial and time scales to enhance targeted interventions for climate resilient development and evaluations. However, further studies are need to test for the sensitivity of index in resilience comparative analysis among selected regions.

Keywords: climate change, resilience, remote sensing, demographic and health surveys

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Authors: Gilda Santos, Rita Marques, Francisca Marques, João Ribeiro, André Fonseca, João M. Miranda, João B. L. M. Campos, Soraia F. Neves

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Every year, an unacceptable number of firefighters are seriously burned during firefighting operations, with some of them eventually losing their life. Although thermal protective clothing research and development has been searching solutions to minimize firefighters heat load and skin burns, currently commercially available solutions focus in solving isolated problems, for example, radiant heat or water-vapor resistance. Therefore, episodes of severe burns and heat strokes are still frequent. Taking this into account, a consortium composed by Portuguese entities has joined synergies to develop an innovative protective clothing system by following a procedure based on the application of numerical models to optimize the design and using a combinationof protective clothing components disposed in different layers. Recently, it has been shown that Phase Change Materials (PCMs) can contribute to the reduction of potential heat hazards in fire extinguish operations, and consequently, their incorporation into firefighting protective clothing has advantages. The greatest challenge is to integrate these materials without compromising garments ergonomics and, at the same time, accomplishing the International Standard of protective clothing for firefighters – laboratory test methods and performance requirements for wildland firefighting clothing. The incorporation of PCMs into the firefighter's protective jacket will result in the absorption of heat from the fire and consequently increase the time that the firefighter can be exposed to it. According to the project studies and developments, to favor a higher use of the PCM storage capacityand to take advantage of its high thermal inertia more efficiently, the PCM layer should be closer to the external heat source. Therefore, in this stage, to integrate PCMs in firefighting clothing, a mock-up of a vest specially designed to protect the torso (back, chest and abdomen) and to be worn over a fire-resistant jacketwas envisaged. Different configurations of PCMs, as well as multilayer approaches, were studied using suitable joining technologies such as bonding, ultrasound, and radiofrequency. Concerning firefighter’s protective clothing, it is important to balance heat protection and flame resistance with comfort parameters, namely, thermaland water-vapor resistances. The impact of the most promising solutions regarding thermal comfort was evaluated to refine the performance of the global solutions. Results obtained with experimental bench scale model and numerical simulation regarding the integration of PCMs in a vest designed as protective clothing for firefighters will be presented.

Keywords: firefighters, multilayer system, phase change material, thermal protective clothing

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Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

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Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

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