Search results for: deep Learning

Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

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Authors: K. C. Wong

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This paper demonstrates a number of examples in the hope to shed some light on the possibility of designing future operating systems in a more adaptation-based manner. A modern operating system, we conceive, should possess the capability of 'learning' in such a way that it can dynamically adjust its services and behavior according to the current status of the environment in which it operates. In other words, a modern operating system should play a more proactive role during the session of providing system services to users. As such, a modern operating system is expected to create a computing environment, in which its users are provided with system services more matching their dynamically changing needs. The examples demonstrated in this paper show that user's resource access patterns 'learned' and determined during a session can be utilized to improve system performance and hence to provide users with a better and more effective computing environment. The paper also discusses how to use the frequency, the continuity, and the duration of resource accesses in a session to quantitatively measure and determine user's resource access patterns for the examples shown in the paper.

Keywords: adaptation-based systems, operating systems, resource access patterns, system performance

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Authors: Rhommel Grutas, Ishmael Narag, Harley Lacbawan

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Construction of high-rise buildings is a means to address the increasing population in Metro Manila, Philippines. The existence of the Valley Fault System within the metropolis and other nearby active faults poses threats to a densely populated city. The distant, shallow and large magnitude earthquakes have the potential to generate slow and long-period vibrations that would affect medium-to-high rise buildings. Heavy damage and building collapse are consequences of prolonged shaking of the structure. If the ground and the building have almost the same period, there would be a resonance effect which would cause the prolonged shaking of the building. Microzoning the long-period ground response would aid in the seismic design of medium to high-rise structures. The shear-wave velocity structure of the subsurface is an important parameter in order to evaluate ground response. Borehole drilling is one of the conventional methods of determining shear-wave velocity structure however, it is an expensive approach. As an alternative geophysical exploration, microtremor array measurements can be used to infer the structure of the subsurface. Microtremor array measurement system was used to survey fifty sites around Metro Manila including some municipalities of Rizal and Cavite. Measurements were carried out during the day under good weather conditions. The team was composed of six persons for the deployment and simultaneous recording of the microtremor array sensors. The instruments were laid down on the ground away from sewage systems and leveled using the adjustment legs and bubble level. A total of four sensors were deployed for each site, three at the vertices of an equilateral triangle with one sensor at the centre. The circular arrays were set up with a maximum side length of approximately four kilometers and the shortest side length for the smallest array is approximately at 700 meters. Each recording lasted twenty to sixty minutes. From the recorded data, f-k analysis was applied to obtain phase velocity curves. Inversion technique is applied to construct the shear-wave velocity structure. This project provided a microzonation map of the metropolis and a profile showing the long-period response of the deep sedimentary basin underlying Metro Manila which would be suitable for local administrators in their land use planning and earthquake resistant design of medium to high-rise buildings.

Keywords: earthquake, ground motion, microtremor, seismic microzonation

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Joann Douziech

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Individuals with intellectual and developmental disabilities (IDD) possess characteristics that present both challenges and gifts. Individuals with IDD require and are worthy of intentional, strategic, and specialized support throughout their lifespan to ensure optimum quality-of-life outcomes. The current global advocacy movement advancing the rights of individuals with IDD emphasizes a high degree of choice over life decisions. For some individuals, this degree of choice results in a variety of negative health and well-being outcomes. Improving the quality of life outcomes requires the combination of a commitment to the rights of the individual with a responsibility to provide support and choice commensurate with individual capacity. A belief that individuals with IDD are capable of learning and they are worthy of being taught provides the foundation for a holistic model of support throughout their lifespan. This model is based on three pillars of engineering the environment, promoting skill development and maintenance, and staff support. In an ever-changing world, supporting quality of life requires attention to moments, phases, and changes in stages throughout the lifespan. Balancing these complexities with strategic, responsive, and dynamic interventions enhances the quality of life of individuals with ID throughout their lifespan.

Keywords: achieving optimum quality of life, comprehensive support, lifespan approach, philosophy and pedagogy

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Authors: Nady Farag Faragalla Hanna

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In the car dealership industry in Japan, the sales specialist is a key factor in the success of the company. I hypothesize that when a company understands the characteristics of sales professionals in its industry, it is easier to recruit and train salespeople effectively. Lean human resources management ensures the economic success and performance of companies, especially small and medium-sized companies.The purpose of the article is to determine the characteristics of sales specialists for small and medium-sized car dealerships using the chi-square test and the proximate variable model. Accordingly, the results show that career change experience, learning ability and product knowledge are important, while university education, career building through internal transfer, leadership experience and people development are not important for becoming a sales professional. I also show that the characteristics of sales specialists are perseverance, humility, improvisation and passion for business.

Keywords: electronics engineering, marketing, sales, E-commerce digitalization, interactive systems, sales process ARIMA models, sales demand forecasting, time series, R codetraits of sales professionals, variable precision rough sets theory, sales professional, sales professionals

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Authors: Liu Dan

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It was considered either unnecessary or impossible for primary school students to implement online teaching until last year. A large number of E-learning or E-teaching researches have been focused on adult-learners, andragogy and technology, however, primary school education, it is facing many problems that need to be solved. Therefore, this research is aimed at exploring barriers and influential factors on online teaching for K-12 students from teachers’ perspectives and discussing the E-pedagogy that is suitable for primary school students and teachers. Eight hundred and ninety-six teachers from 10 primary schools in Shanghai were invited to participate in a questionnaire survey. Data were analysed by hierarchical regression, and the results stress the significant three barriers by teachers with online teaching: the existing system is deficient in emotional interaction, teachers’ attitude towards the technology is negative and the present teacher training is lack of systematic E-pedagogy guidance. The barriers discovered by this study will help the software designers (E-lab) develop tools that allow for flexible and evolving pedagogical approaches whilst providing an easy entry point for cautious newcomers, so that help the teachers free to engage in E-teaching at pedagogical and disciplinary levels, to enhance their repertoire of teaching practices.

Keywords: online teaching barriers (OTB), e-teaching, primary school, teachers, technology

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Ovidiu Domşa, Nicolae Bold

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Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Lee Bih Ni, Kiu Su Na

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This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: a second language, Chinese language teaching, immersion teaching, instructional strategies

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Authors: Leah Plocharczyk, Matthew Conner

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This paper analyzes the relatively new trend of PSE programs which seek to provide education, vocational training, and a college experience to individuals with an intellectual and developmental disability (IDD). Specifically, the paper examines the degree of interaction between PSE programs and the libraries of their college campuses. Using ThinkCollege, a clearinghouse and advocate for PSE programs, the researchers identified 293 programs throughout the country. These were all contacted with an email survey asking them about the nature of their involvement, if any, with the academic libraries on their campus. Where indicated by the responses, the libraries of PSE programs were contacted for additional information about their programming. Responses to the survey questions were tabulated and analyzed quantitatively. Written comments were analyzed for themes which were then tabulated. This paper presents the results of this study. They show obvious preferences for library programming, such as group formal instruction, individual liaisons, embedded reference, and various instructional designs. These are discussed in terms of special education principles of mainstreaming, level of restriction, training demands and cost effectiveness. The work serves as a foundation for best practices that can advance the field.

Keywords: disability studies, instructional design, universal design for learning, assessment methodology

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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Authors: Douglas Shabe

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The world of the performing musician is one of high pressure that comes from the expected high standards they have to live up to and that they expect from themselves. The pressure that musicians put themselves under can manifest itself in physical problems such as focal dystonia. Knowledge of the contributing factors and potential rehabilitation strategies cannot only give players hope for recovery but also the information to prevent it from happening in the first place. This dissertation presents a multiple case study of two performing brass musicians who developed focal dystonia of the embouchure, also known as embouchure dystonia, combined with an autoethnography of the author’s experience of battling embouchure dystonia and our attempts at recovery. Extensive research into the current state of focal dystonia research was done to establish a base of knowledge. That knowledge was used to develop interview questions for the two participants and interpret the findings of the qualitative data collected. The research knowledge, as well as the qualitative data from the case studies, was also used to interpret the author’s experience. The author determined that behavioral, environmental, and psychological factors were of prime importance in the subjects’ development of focal dystonia and that modifications of those factors are essential for the best chance at recovery.

Keywords: focal dystonia, embouchure dystonia, music teaching and learning, music education

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Authors: Cazadira Fediva Tamzil, Agung Sulthonaulia Utama

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The rise in popularity of Indonesian Islamic fashion displayed and sold through social networking sites, especially Instagram, might seem at first glance like a commonplace and localized phenomenon. However, when analyzed critically, it actually reveals the relations between the global and local Indonesian economy, as well as a deep socio-anthropological dimension relating to religion, culture, class, work, identity. Conducted using a qualitative methodology, data collection technique of literature review, and observation of various social networking sites, this research finds four things that lead to the aforementioned conclusion. First, the rise of online Islamic fashion retailers was triggered by the shift in the structure of global and national Indonesian economy as well as the free access of information made possible by democratization in Indonesia and worldwide advances in terms of technology. All of those factors combined together gave birth to a large amount of middle-class Indonesians with high consumer culture and entrepreneurial flair. Second, online Islamic fashion retailers are the new cultural trendsetters in society. All these show how Indonesians are becoming increasingly pious, no longer only adhere to Western conception of luxury and that many are increasingly exploiting Islam commercial and status-acquiring purposes. Third, the online Islamic fashion retailers actually reveal a shift in the conception of ‘work’ – social media has made work no longer only confined to the toiling activities inside factories, but instead something that can be done from any location only through posting online words or pictures that can increase a fashion product’s capital value. Without realizing it, many celebrities and online retailers who promote Islamic fashion through social media on a daily basis are now also ‘semi-free immaterial labors’ – a slight reconceptualization to Tiziana Terranova’s concept of ‘free labor’ and Maurizio Lazzarato’s ‘immaterial labor’, which basically refer to people who create economic value and thus help out capitals from producing immaterial things with only little compensation in return. Fourth, this research also shows that the diversity of Islamic fashion styles being sold on Instagram reflects the polarized identity of Islam in Indonesia. In stark contrast with the theory which states that globalization always leads to the strengthening and unification of identity, this research shows how polarized the Islamic identity in Indonesia really is – even in the face of globalization.

Keywords: global economy, Indonesian online Islamic fashion, political relations, socio-anthropology

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Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

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The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

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Authors: Sakapas Saengchai, Vilasinee Jintalikhitdee, Mathinee Khongsatid, Nattapol Pourprasert

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This paper studied the participation of people of the five villages of Bang Nang Li Community in Ampawa District, Samut Songkram Province, in designing community planning. The population was 2,755 villagers from the 5 villages with 349 people sampled. The level of involvement was measured by using Likert Five Scale for: preparing readiness of local people in the community, providing information for community and self analysis and learning, designing goals and directions for community development, designing strategic plans for community projects, and operating according to the plans. All process items reported a medium level of involvement except the item of preparing readiness for local people that presented the highest mean score. A test of a correlation between personal factors and level of involvement in designing the community planning unveiled no correlation between gender, age and career. Contrarily, the findings revealed that the villagers’ educational level and community membership status had a correlation with their level of involvement in designing the community planning.

Keywords: community development, community planning, people participation, educational level

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Authors: Camille Rich, Nadine Ferris France, Ann Nolan, Webster Mavhu, Vongai Munatsi

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Background and Aim: Zimbabwe has one of the highest HIV rates in the world, with a 12.7% adult prevalence rate. Young adults are a key group affected by HIV, and one-third of all new infections in Zimbabwe are amongst people ages 18-24 years. Stigma remains one of the main barriers to managing and reducing the HIV crisis, especially for young adults. There are several types of stigma, including enacted stigma, the outward discrimination towards someone and self-stigma, the negative self-judgments one has towards themselves. Self-stigma can have severe consequences, including feelings of worthlessness, shame, suicidal thoughts, and avoidance of medical help. This can have detrimental effects on those living with HIV. However, the unique beliefs and impacts of self-stigma amongst key groups living with HIV have not yet been explored. Therefore, the focus of this study is on the beliefs and experiences of HIV-related self-stigma, as experienced by young adults living in Harare, Zimbabwe. Research Methods: A qualitative approach was taken for this study, using sixteen semi-structured interviews with young adults (18-24 years) who are living with HIV in Harare. Participants were conveniently and purposefully sampled as members of Africa, an organization dedicated to young people living with HIV. Interviews were conducted over Zoom due to the COVID-19 pandemic, recorded and then coded using the software NVivo. The data was analyzed using both inductive and deductive Thematic Analysis to find common themes. Results: All of the participants experienced HIV-related self-stigma, and both beliefs and experiences were explored. These negative self-perceptions included beliefs of worthlessness, hopelessness, and negative body image. The young adults described believing they were not good enough to be around HIV negative people or that they could never be loved due to their HIV status. Developing self-stigmatizing thoughts came from internalizing negative cultural values, stereotypes about people living with HIV, and adverse experiences. Three main themes of self-stigmatizing experiences emerged: disclosure difficulties, relationship complications, and being isolated. Fear of telling someone their status, rejection in a relationship, and being excluded by others due to their HIV status contributed to their self-stigma. These experiences caused feelings of loneliness, sadness, shame, fear, and low self-worth. Conclusions: This study explored the beliefs and experiences of HIV-related self-stigma of these young adults. The emergence of negative self-perceptions demonstrated deep-rooted beliefs of HIV-related self-stigma that adversely impact the participants. The negative self-perceptions and self-stigmatizing experiences caused the participants to feel worthless, hopeless, shameful, and alone-negatively impacting their physical and mental health, personal relationships, and sense of self-identity. These results can now be used to pursue interventions to target the specific beliefs and experiences of young adults living with HIV and reduce the adverse consequences of self-stigma.

Keywords: beliefs, HIV, self-stigma, stigma, Zimbabwe

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, A. Lamadrid Álvarez, A. Pastrana Palma, H. F. Valencia Pérez, M. Vivanco Vargas

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This work proposes a Cooperation-Competitive (Coopetitive) approach that allows coordinated work among the Secretary of Public Education (SEP), the Autonomous University of Querétaro (UAQ) and government funds from National Council for Science and Technology (CONACYT) or some other international organizations. To work on an overall knowledge transfer strategy with e-learning over the Cloud, where experts in junior high and high school education, working in multidisciplinary teams, perform analysis, evaluation, design, production, validation and knowledge transfer at large scale using a Cloud Computing platform. Allowing teachers and students to have all the information required to ensure a homologated nationally knowledge of topics such as mathematics, statistics, chemistry, history, ethics, civism, etc. This work will start with a pilot test in Spanish and initially in two regional dialects Otomí and Náhuatl. Otomí has more than 285,000 speaking indigenes in Queretaro and Mexico´s central region. Náhuatl is number one indigenous dialect spoken in Mexico with more than 1,550,000 indigenes. The phase one of the project takes into account negotiations with indigenous tribes from different regions, and the Information and Communication technologies to deliver the knowledge to the indigenous schools in their native dialect. The methodology includes the following main milestones: Identification of the indigenous areas where Otomí and Náhuatl are the spoken dialects, research with the SEP the location of actual indigenous schools, analysis and inventory or current schools conditions, negotiation with tribe chiefs, analysis of the technological communication requirements to reach the indigenous communities, identification and inventory of local teachers technology knowledge, selection of a pilot topic, analysis of actual student competence with traditional education system, identification of local translators, design of the e-learning platform, design of the multimedia resources and storage strategy for “Cloud Computing”, translation of the topic to both dialects, Indigenous teachers training, pilot test, course release, project follow up, analysis of student requirements for the new technological platform, definition of a new and improved proposal with greater reach in topics and regions. Importance of phase one of the project is multiple, it includes the proposal of a working technological scheme, focusing in the cultural impact in Mexico so that indigenous tribes can improve their knowledge about new forms of crop improvement, home storage technologies, proven home remedies for common diseases, ways of preparing foods containing major nutrients, disclose strengths and weaknesses of each region, communicating through cloud computing platforms offering regional products and opening communication spaces for inter-indigenous cultural exchange.

Keywords: Mexicans indigenous tribes, education, knowledge transfer, cloud computing, otomi, Náhuatl, language

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Authors: Verónica Díaz Quezada

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The importance given to the development of the problem solving skill and the requirement to solve problems framed in mathematical or real life contexts, in practice, they are not evidence in relation to the teaching of proportional variations. This qualitative and descriptive study aims to (1) to improve problem solving ability of high school students in Chile, (ii) to elaborate and describe a didactic intervention strategy based on learning situations in proportional variations, focused on solving types of routine problems of various contexts and non-routine problems. For this purpose, participant observation was conducted, test of mathematics problems and an opinion questionnaire to thirty-six high school students. Through the results, the highest academic performance is evidenced in the routine problems of purely mathematical context, realistic, fantasy context, and non-routine problems, except in the routine problems of real context and compound proportionality problems. The results highlight the need to consider in the curriculum different types of problems in the teaching of mathematics that relate the discipline to everyday life situations

Keywords: algebra, high school, proportion variations, nonroutine problem solving, routine problem solving

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Authors: B. Alajmi, L. Marouf, A. S. Chaudhry

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In recent years, increasing emphasis has been placed upon issues concerning the evaluation of health care. In this regard, knowledge management has also been considered an important component of the evaluation process. KM facilitates the transfer of existing knowledge or the development of new knowledge among healthcare staff and patients. This research aimed to examine how hospitals in Kuwait employ knowledge management practices, including capturing, sharing, and generating, and the perceived impact of KM practices on performance of hospitals in Kuwait. Through adopting a quantitative survey method with 277 sample of doctors, the study found that in terms of the three major knowledge management practices – knowledge capturing, sharing, and generating – the adoption of KM practices were rated very low in the sampled hospitals in Kuwait. Hospitals paid little attention to the main activities that support the transfer of expertise among doctors in hospitals. However, as predicted by previous studies, knowledge management practices were perceived to have an impact on hospitals’ performance. Through knowledge capturing, sharing, and generating, hospitals could improve the services they provide through documenting best practices, transforming their hospitals into learning organizations in which lessons learned are captured, stored, and made available for others to learn from.

Keywords: knowledge management, hospitals, knowledge management practices, knowledge management tools, performance

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Authors: Hamad Aldosari

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The purpose of this study is to investigate the status of sexism, or gender discrepancies, in current pedagogical and curricular practices in EFL learning higher education settings. Qualitative and quantitative analyses of both course contents and pedagogies in Saudi higher education institutions are to be discussed with reference to female/male topic presentation in dialogs and reading passages, sex-based activity types, stereotyped sex roles and the masculine generic conceptions of male superiority subliminally related in EFL curriculum and pedagogical practices, as well as the causes and effects of segregated language education practices in Saudi Arabia from a holistic vantage point of analysis. Analysis findings show that language educational practices including educational settings and segregation are gender-biased in attitude, but with regard to curriculum, sexism has not been traced. Findings also show that sexism is rampant due to socio-cultural aspects of language education rather than to religious reasons: a finding that seems to mirror the institutionalized unfair sex discrimination to the disadvantage of women in the Arabian societies at large.

Keywords: genderism, sex segregation, Saudi Arabia, EFL

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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: Poom Thiparapkul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that doesn't translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: user experience design, user experience, electric vehicle, dashboard design, Thailand driver.

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Authors: Khaled M. Alhawiti

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Reading capability is a major segment of language competency. On the other hand, discovering topical writings at a fitting level for outside and second language learners is a test for educators. We address this issue utilizing natural language preparing innovation to survey reading level and streamline content. In the connection of outside and second-language learning, existing measures of reading level are not appropriate to this errand. Related work has demonstrated the profit of utilizing measurable language preparing procedures; we expand these thoughts and incorporate other potential peculiarities to measure intelligibility. In the first piece of this examination, we join characteristics from measurable language models, customary reading level measures and other language preparing apparatuses to deliver a finer technique for recognizing reading level. We examine the execution of human annotators and assess results for our finders concerning human appraisals. A key commitment is that our identifiers are trainable; with preparing and test information from the same space, our finders beat more general reading level instruments (Flesch-Kincaid and Lexile). Trainability will permit execution to be tuned to address the needs of specific gatherings or understudies.

Keywords: natural language processing, trainability, syntactic simplification tools, education

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Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

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Authors: Gebreselassie Sebhatleab

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According to the Global Peace Index report (GPI, 2023), global peacefulness has deteriorated by more than 0.42%. Old and new conflicts, COVID-19, and political and cultural polarization are the main drivers of conflicts in the world. The 2022 was the deadliest year for armed conflict in the history of the GPI. In Ethiopia, over half a million people died in the Tigray war, which was the largest conflict death event since the 1994 Rwandan genocide. In total, 84 countries recorded an improvement, while 79 countries recorded a deterioration in peacefulness across the globe. The Russia-Ukraine war and its consequences were the main drivers of the deterioration in peacefulness globally. Both Russia and Ukraine are now ranked amongst the ten least peaceful countries, and Ukraine had the largest deterioration of any country in the 2023 GPI. In the same year, the global impact of violence on the economy was 17 percent, which was equivalent to 10.9% of global GDP. Besides, the brutal conflict in Tigray started in November. 2020 claimed more than half a million lives lost and displaced nearly 3 million people, along with widespread human rights violations and sexual violence has left deep damage on the population. The displaced people are still unable to return home because the western, southern and Eastern parts of Tigray are occupied by Eritrean and Amhara forces, despite the Pretoria Agreement. Currently, armed conflicts in Amhara in the Oromya regions are intensified, and human rights violations are being reported in both regions. Meanwhile, protests have been held by war-injured TDF members, IDPs and teachers in the Tigray region. Hence, the general objective of this project is to explore the challenges of peace-building processes in the border woredas of the Eastern Zone of the Tigray Region. Methodologically, the project will employ exploratory qualitative research designs to gather and analyze qualitative data. A purposive sampling technique will be applied to gather pertinent information from the key stakeholders. Open-ended interview questions will be prepared to gather relevant information about the challenges and perceptions of peacebuilding in the study area. Data will be analyzed using qualitative methods such as content analysis, narrative analysis and phenomenological analysis to deeply investigate the challenges of peace-building in the study woredas. Findings of this research project will be employed for program intervention to promote sustainable peace in the study area.

Keywords: peace building, conflcit and violence, political instability, insecurity

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Authors: Engku Haliza Engku Ibrahim, Isarji Sarudin, Ainon Jariah Muhamad

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It is generally agreed that many factors contribute to one’s reading comprehension and there is consensus that vocabulary size one of the main factors. This study explores the relationship between second language learners’ vocabulary size and their reading comprehension scores. 130 Malay pre-university students of a public university participated in this study. They were students of an intensive English language programme doing preparatory English courses to pursue bachelors degree in English. A quantitative research method was employed based on the Vocabulary Levels Test by Nation (1990) and the reading comprehension score of the in-house English Proficiency Test. A review of the literature indicates that a somewhat positive correlation is to be expected though findings of this study can only be explicated once the final analysis has been carried out. This is an ongoing study and it is anticipated that results of this research will be finalized in the near future. The findings will help provide beneficial implications for the prediction of reading comprehension performance. It also has implications for the teaching of vocabulary in the ESL context. A better understanding of the relationship between vocabulary size and reading comprehension scores will enhance teachers’ and students’ awareness of the importance of vocabulary acquisition in the L2 classroom.

Keywords: vocabulary size, vocabulary learning, reading comprehension, ESL

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Authors: Muhammad Akram, Qamar Naseem, Imtiaz Ahmad

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The purpose of this study was to correlate students’ perceptions of teacher effectiveness with their academic achievement in English and Mathematics at the secondary level (grade 9th) based on five national professional standards for teacher evaluation in Pakistan (subject matter knowledge, instructional planning and strategies, assessment, learning environment, effective communication. A Students’ Perceptions of Teacher Effectiveness Questionnaire (SPTEQ) was developed by the researchers to collect data from 2009 students from forty public girls and boys high/ higher secondary schools in district Khanewal, Pakistan. The overall reliability of the SPTEQ was α=.86. The study found a significant positive relationship among all the five factors of teacher effectiveness construct. The study also showed significant, positive relationship between teacher effectiveness factors and students’ achievement in English and mathematics. No significant differences were found between male and female students’ perceptions about their English teacher effectiveness. The implications include students’ personal attachments with their teachers that might convince them to overrate their teachers.

Keywords: communication, students’ achievement, teacher effectiveness, teaching strategies, teaching strategies

Procedia PDF Downloads 298