Search results for: distributed training

Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: Bronwyn S. Mthimunye, Athena S. Pedro, Nicolette V. Roman

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Inclusive education is a global concern, in the context of Brazil, Russia, India, China, and South Africa. These countries are all striving for inclusive education, as there are many children excluded from formal schooling. The need for inclusive education is imperative, given the increase in special needs diagnoses. Many children confronted with special needs are still not able to exercise their basic right to education. The aim of conducting this scoping review was to explore the policies and procedures addressing the implementation of inclusive education in Brazil, Russia, India, China, and South Africa. The studies included were published between 2006-2016 and located in Academic Search Complete, ERIC, Medline, PsycARTICLES, JSTOR, and SAGE Journals. Seven articles were included in which all of the articles reported on inclusive education and the status of implementation. The findings identified many challenges faced by Brazil, Russia, India, China, and South Africa that affect the implementation of policies and programmes. Challenges such as poor planning, resource-constrained communities, lack of professionals in schools, and the need for adequate teacher training were identified. Brazil, Russia, India, China, and South Africa are faced with many social and economic challenges, which serves as a barrier to the implementation of inclusive education.

Keywords: special needs, inclusion, education, scoping review

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Authors: Xinyi Le

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In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side.

Keywords: 3d printing, perceptual model, fuzzy evaluation, data-driven approach

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Bayu Rizky Pratama, Hardiansyah Nur Sahaya

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Riau Province is the worst emitter for forest burning which causes the huge scale of externality such as declining of forest habitat, health disease, and climate change impact. Indonesia forum of budget transparency for Riau Province (FITRA) reported the length of forest burning reached about 186.069 hectares which is 7,13% of total national forest burning disaster, consisted of 107.000 hectares of peatland and the rest 79.069 hectares of mineral land. Anti-fire group, a voluntary group next to the forest, to help in protecting the forest burning and heavily smoke residual has been established but unfortunately the implementation still far from expectation. This research will emphasize on (1) how the anti-fire group contribute to fire hazard tackling; (2) the identification of SWOT analysis to enhance the group benefit; and (3) government policy implication to maximize the role of Anti-fire group and reduce the case of forest burning as well as heavily smoke which can raise climate change impact. As the observation found some weakness from SWOT identification such as (1) lack of education and training; (2) facility in extinguishing the fire damage; (3) law for economic incentive; (4) communication and field experience; (5) also the reporting the fire case.

Keywords: anti-fire group, forest burning impact, SWOT, climate change mitigation

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Authors: Nivedita Ghosh

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In his critique of Lefebvre’s view that ‘technological capacities’ are class-dependent, Francois Hetman argues that technology today is participatory, allowing the entry of individuals from different levels of social stratification. As a result, we are entering into an era of technology operators or ‘clerks’ who become the new decision-makers because of the knowledge they possess of the use of technologies. In response to Hetman’s thesis, this paper argues that knowledge of technology, while indeed providing a momentary space for decision-making, does not necessarily restructure social hierarchies. Through case studies presented from the world of Indian documentary filmmaking, this paper puts forth the view that Hetman’s clerks, despite being technologically advanced, do not break into the filmmaking hierarchical order. This remains true even for a situation where technical knowledge rests most with those in the lowest rungs of the filmmaking ladder. Instead, technological knowledge provides the space for other kinds of relationships to evolve, such as those of ‘trusting the technician’ or ‘admiration for the technician’s work’. Furthermore, what continues to define documentary filmmaking hierarchy is conceptualization capacities of the practitioners, which are influenced by a similarity in socio-cultural backgrounds and film school training accessible primarily to the filmmakers instead of the technicians. Accordingly, the paper concludes with the argument that more than ‘technological-capacities’, it is ‘conceptualization capacities’ which are class-dependent, especially when we study the field of documentary filmmaking.

Keywords: documentary filmmaking, India, technology, knowledge, hierarchy

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Authors: Sozan H. Omar, Lina L. Al-Rewaili

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The current study aimed to measure the fifth Grade student skills of reading illustrates in physical and chemical chapter included in science textbook, as well as identity the tasks the dispersants related to designing these illustrates which obstruct the students to read them properly. The researcher applied the test instrument of open discuss questions to measure the skill of: recognizing, description, interpretation and assessment for a sample of this research consisted of (269) students who read three illustrates, and conduct an interview with sample of them (27) students to recognize the dispersants related to designing of these illustrates. The study results showed that there are poor levels in illustrated drawing reading skills: description, interpretation, and assessment. The most important dispersants which obstruct the students to read theses illustrates properly representing: Art impacts of these illustrates, there are some elements which don’t serve these illustrates. In the light of the above results, the researcher provided some recommendations such as training the students on using the images and illustrates properly in science textbooks, as well as create simple designs of illustrates and they should be free of crowded elements and impacts which don’t serve the illustrates.

Keywords: reading illustrated drawings skills, fifth grade science, physical and chemical changes

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Authors: Mengyu Lu, Yongsheng Guo

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This study investigates how employee incentives affect employee performance in financing from customers. This study followed a grounded theory approach where data were collected through 29 interviews. Main themes and categories were identified through the coding processes. This study found that casual conditions, including financial barriers, informal finance, business location, customer base and customer relationship, influenced the adoption of customer finance in the case of SMEs. The SMEs build and maintain long-term relationships with customers through personal communications. The SMEs engage and motivate employees in customer communications and business financing strategy through financial incentives programs, including bonuses, salary rises, rewards and non-financial incentives, including training opportunities, extra holiday leave, and flexible working hours. Employee performance was measured through financing contribution and job contribution. As a consequence, customers will be well served by employees and get a better customer experience. SMEs can get benefits such as employee engagement, employee satisfaction and sustainable financing sources. This study gets in sight of employee incentives in improving employee performance in customer finance and makes implications to human capital theories. Suggestions are provided to the decision-makers in businesses as incentive programs improve employee performance that, eventually contributes to overall business performance.

Keywords: SMEs, financing from customers, employee incentives, performance-based measurement

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Authors: Mahdi Fakheri, Mohammad Mohsen Mahdizadeh Naeini

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This paper addresses an understudied aspect of U.S. foreign aids between the years 2000 and 2020. Despite a growing body of literature on the impacts of U.S. aids, the question about how the United States uses its foreign aids to change developing countries has remained unanswered. As foreign aid is a tool of the United States' foreign policy, answering this very question can reveal the future that the U.S. prefers for developing countries and that secures its national interest. This paper will explore USAID's official dataset, which includes the data of foreign aids to the Middle East, Africa, Latin America, and Southeast Asia from 2000 to 2020. Through an empirical analysis, this paper argues that the focus of U.S. foreign aid is evenly divided between institutional and non-institutional (i.e., slight enhancement of status quo) changes. The former is induced by training and education, funding the initiatives and projects, making capacity and increasing the efficiency of human, operational, and management sectors, and enhancing the living condition of the people. Moreover, it will be demonstrated that the political, military, cultural, economic, and judicial are some of the institutions that the U.S. has planned to change in the aforementioned period and regions.

Keywords: USAID, foreign aid, development, developing countries, Middle East, Africa, Southeast Asia, Latin America

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Authors: Jose Manuel Rodriguez-Dominguez, Rodrigo Barba-Gonzalez, Ernesto Tapia-Campos

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Sprekelia formosissima (L.) Herbert is a bulbous ornamental species of the monocotyledonous Amaryllidaceae family, and it is a perennial, herbaceous monotypic plant commonly known as ‘Aztec Lily’ or ‘Jacobean Lily’; it is distributed through Mexico and Guatemala. Its scarlet flowers with curved petals have made it an exceptional ornamental pot plant. Cytogenetic studies in this species have shown differences in chromosome number (2n=60, 120, 150, 180) with a basic number x=30. Different reports have shown a variable ploidy level (diploid, tetraploid, pentaploid and hexaploid); however, triploid plants have not been reported. In this work, triploid plants of S. formosissima were obtained by crossing tetraploid (2n=4x=120) with diploid (2n=2x=60) genotypes of this species; the seeds obtained from the crosses were placed in pots with a moist substrate made of Peat Moss: Vermiculite (7:3) for germination. Root tips were collected, and metaphasic chromosome preparations were performed. For chromosome counting, the best five metaphases obtained were photographed with a Leica DMRA2 microscope (Leica Microsystems, Germany) microscopy coupled to an Evolution QEI camera under phase contrast (Media-Cybernetics). Chromosomes counting in root-tip cells showed that 100% of the plants were triploid (2n=3x=90). Although tetraploid or pentaploid plants of S. formosissima are highly appreciated, they usually have lower growth rates than related diploid ones. For this reason, it is important to obtain triploid plants, which have advantages such as higher growth rates than tetraploid and pentaploid, larger flowers than those of the diploid plants and they are expected to not be able to produce seeds because their gametes are aneuploids. Furthermore, triploids may become very important for genomic research in the future, creating opportunities for discovering and monitoring genomic and transcriptomic changes in unbalanced genomes, hence the importance of this work.

Keywords: Amaryllidaceae, cytogenetics, ornamental, ploidy level

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Authors: Felermino D. M. A. Ali, S. C. Ng

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E-learning is an evolutionary form of distance learning and has become better over time as new technologies emerged. Today, efforts are still being made to embrace E-learning systems with emerging technologies in order to make them better. Among these advancements, Educational Data Mining (EDM) is one that is gaining a huge and increasing popularity due to its wide application for improving the teaching-learning process in online practices. However, even though EDM promises to bring many benefits to educational industry in general and E-learning environments in particular, its principal drawback is the lack of easy to use tools. The current EDM tools usually require users to have some additional technical expertise to effectively perform EDM tasks. Thus, in response to these limitations, this study intends to design and implement an EDM application framework which aims at automating and simplify the development of EDM in E-learning environment. The application framework introduces a Service-Oriented Architecture (SOA) that hides the complexity of technical details and enables users to perform EDM in an automated fashion. The framework was designed based on abstraction, extensibility, and interoperability principles. The framework implementation was made up of three major modules. The first module provides an abstraction for data gathering, which was done by extending Moodle LMS (Learning Management System) source code. The second module provides data mining methods and techniques as services; it was done by converting Weka API into a set of Web services. The third module acts as an intermediary between the first two modules, it contains a user-friendly interface that allows dynamically locating data provider services, and running knowledge discovery tasks on data mining services. An experiment was conducted to evaluate the overhead of the proposed framework through a combination of simulation and implementation. The experiments have shown that the overhead introduced by the SOA mechanism is relatively small, therefore, it has been concluded that a service-oriented architecture can be effectively used to facilitate educational data mining in E-learning environments.

Keywords: educational data mining, e-learning, distributed data mining, moodle, service-oriented architecture, Weka

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Authors: Mitra Savabi-Esfahani, Fariba Taleghani, Mahnaz Noroozi, Maryam Tabatabaeian, Elsebeth Lynge

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Breast cancer is a health concern in worldwide. All women have not adequate information about breast cancer, resulting in undetected some tumors until advanced stages. Therefore awareness of people was recommended as a strategy to control that. The aim of this study was to assess the effect of an educational intervention on women's knowledge and attitude about breast cancer and screening. This study was conducted in 2016 on 191 women. All women living in one of big cities were invited to enroll in training classes. Inclusion criteria consisted women who were 20 - 69 years and not participated in any educational intervention. The lecture with group discussion was used as educational methods. Data collection tool was a structured questionnaire which filled out before and after intervention. The reliability of the questionnaire was determined by Cronbach's alpha. The data were analyzed using SPSS software. The average age was 44/4 ± 11.5 and 42.6% of the women had obtained high school. Of the 191 women, 70(36.6%) and 76(39.8%) had low and medium level of knowledge respectively and half of them, 95(50%) had medium level of attitude in before intervention. There was significant difference between mean scores of knowledge and attitude before and after the intervention by Paired T test (p < 0/001). It seems applying effective educational interventions can increase knowledge and attitude women about breast cancer particularly in community that they have insufficient levels. Moreover, the lecture method along with group discussion can be proposed as effective and conventional methods for this purpose.

Keywords: attitude, breast cancer, educational intervention, knowledge

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Authors: Nhung T. Bui

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Part of the dilemma facing educational reforms in Vietnam as in other Asian contexts is how to encourage more independence in students’ learning approaches. Since 2005, the Ministry of Education and Training of Vietnam has included the students’ ability to learn independently in its national education objectives. While learner autonomy has been viewed as a goal in the teaching and learning English as a foreign language (EFL) and there has been a considerable literature on strategies to stimulate autonomy in learners, teachers’ voices have rarely been heard. Given that teachers play a central role in helping their students to be more autonomous, especially in an inherent Confucian heritage culture like Vietnam, their attitudes towards learner autonomy should be investigated before any practical implementations could be undertaken. This paper reports significant findings of a survey questionnaire with 262 lecturers of English from 5 universities in Hanoi, Vietnam giving opinions regarding the practices and prospects of learner autonomy in their classrooms. The study reveals that lecturers perceive they should be more responsible than their students in all class-related activities; they most appreciate their students’ ability to learn cooperatively and that they consider stimulating students’ interest as the most important teaching strategy to promote learner autonomy. Lecturers, then, are strongly suggested to gradually ‘empower’ their students through the application of out-of-classroom activities; of learning activities which requires collaboration and team spirit; and of activities which could boost students’ interest in learning English.

Keywords: English as a foreign language, higher education, learner autonomy, Vietnam

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Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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Authors: N. C. Ghosh, Niladri Das, Prolay Mondal, Ranajit Ghosh

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Groundwater quality deterioration due to human activities has become a prime factor of modern life. The major concern of the study is to access spatial variation of groundwater quality and to identify the sources of groundwater chemicals and its impact on human health of the concerned area. Multivariate statistical techniques, cluster, principal component analysis, and hydrochemical fancies are been applied to measure groundwater quality data on 14 parameters from 107 sites distributed randomly throughout the Birbhum district. Five factors have been extracted using Varimax rotation with Kaiser Normalization. The first factor explains 27.61% of the total variance where high positive loading have been concentrated in TH, Ca, Mg, Cl and F (Fluoride). In the studied region, due to the presence of basaltic Rajmahal trap fluoride contamination is highly concentrated and that has an adverse impact on human health such as fluorosis. The second factor explains 24.41% of the total variance which includes Na, HCO₃, EC, and SO₄. The last factor or the fifth factor explains 8.85% of the total variance, and it includes pH which maintains the acidic and alkaline character of the groundwater. Hierarchical cluster analysis (HCA) grouped the 107 sampling station into two clusters. One cluster having high pollution and another cluster having less pollution. Moreover hydromorphological facies viz. Wilcox diagram, Doneen’s chart, and USSL diagram reveal the quality of the groundwater like the suitability of the groundwater for irrigation or water used for drinking purpose like permeability index of the groundwater, quality assessment of groundwater for irrigation. Gibb’s diagram depicts that the major portion of the groundwater of this region is rock dominated origin, as the western part of the region characterized by the Jharkhand plateau fringe comprises basalt, gneiss, granite rocks.

Keywords: correlation, factor analysis, hydrological facies, hydrochemistry

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Authors: Haruka Ando

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Undernutrition of children is a critical issue, especially for people in the remote areas of the Republic of Djibouti, since household food insecurity, inadequate child caring and feeding, unhealthy environment and lack of clean water, as well as insufficient maternal and child healthcare, are underlying causes which affect. Nomadic pastoralists living in the Dikhil region (Dikhil) are socio-economically and geographically more vulnerable due to displacement, which in turn worsens the situation of child stunting. A high prevalence of inappropriate complementary feeding among pastoral mothers might be a significant barrier to child growth. This study aims to identify health promotion intervention strategies that would support an increase in optimal complementary feeding among pastoral mothers of children aged 6-23 months in Dikhil. There are four objectives; to explore and to understand the existing practice of complementary feeding among pastoral mothers in Dikhil; to identify the barriers in appropriate complementary feeding among the mothers; to critically explore and analyse the strategies for an increase in complementary feeding among the mothers; to make pragmatic recommendations to address the barriers in Djibouti. This is an in-depth study utilizing a conceptual framework, the behaviour change wheel, to analyse the determinants of complementary feeding and categorize health promotion interventions for increasing optimal complementary feeding among pastoral mothers living in Dikhil. The analytical tool was utilized to appraise the strategies to mitigate the selected barriers against optimal complementary feeding. The data sources were secondary literature from both published and unpublished sources. The literature was systematically collected. The findings of the determinants including the barriers of optimal complementary feeding were identified: heavy household workload, caring for multiple children under five, lack of education, cultural norms and traditional eating habits, lack of husbands' support, poverty and food insecurity, lack of clean water, low media coverage, insufficient health services on complementary feeding, fear, poor personal hygiene, and mothers' low decision-making ability and lack of motivation for food choice. To mitigate selected barriers of optimal complementary feeding, four intervention strategies based on interpersonal communication at the community-level were chosen: scaling up mothers' support groups, nutrition education, grandmother-inclusive approach, and training for complementary feeding counseling. The strategies were appraised through the criteria of effectiveness and feasibility. Scaling up mothers' support groups could be the best approach. Mid-term and long-term recommendations are suggested based on the situation analysis and appraisal of intervention strategies. Mid-term recommendations include complementary feeding promotion interventions are integrated into the healthcare service providing system in Dikhil, and donor agencies advocate and lobby the Ministry of Health Djibouti (MoHD) to increase budgetary allocation on complementary feeding promotion to implement interventions at a community level. Moreover, the recommendations include a community health management team in Dikhil training healthcare workers and mother support groups by using complementary feeding communication guidelines and monitors behaviour change of pastoral mothers and health outcome of their children. Long-term recommendations are the MoHD develops complementary feeding guidelines to cover sector-wide collaboration for multi-sectoral related barriers.

Keywords: Afar, child food, child nutrition, complementary feeding, complementary food, developing countries, Djibouti, East Africa, hard-to-reach areas, Horn of Africa, nomad, pastoral, rural area, Somali, Sub-Saharan Africa

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Authors: Azzeddine Atibi, Sara Atibi, Salim Ahmed, Khadija El Kabab

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In an educational context where innovation holds a predominant position, political discourses and pedagogical practices are increasingly oriented toward this concept. Innovation has become a benchmark value, gradually replacing the notion of progress. This term is omnipresent in discussions among policymakers, administrators, and academic researchers. The pressure to innovate impacts all levels of education, influencing institutional and educational policies, training objectives, and teachers' pedagogical practices. Higher education and continuing education sectors are not exempt from this trend. These sectors are compelled to transform to attract and retain an audience whose behaviors and expectations have significantly evolved. Indeed, the employability of young graduates has become a crucial issue, prompting us to question the effectiveness of various pedagogical methods in meeting this criterion. In this article, we propose to thoroughly examine the relationship between pedagogical methods employed in different fields of higher education and the acquisition of interpersonal skills, or "soft skills". Our aim is to determine to what extent these methods contribute to better-preparing students for the professional world. We will analyze how innovative pedagogical approaches can enhance the acquisition of soft skills, which are essential for the professional success of young graduates.

Keywords: educational context, innovation, higher education, soft skills, pedagogical practices, pedagogical approaches

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Henry Wilde, Thiravat Hemachudha

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Human rabies deaths are underreported worldwide at 55,000 annual cases; more than of dengue and Japanese encephalitis. Almost half are children. A recent study from the Philippines of nearly 2,000 rabies deaths revealed that none of had received incomplete or no post exposure prophylaxis. Coming from a canine rabies endemic country, this is not unique. There are two major barriers to reducing human rabies deaths: 1) the large number of unvaccinated dogs and 2) post-exposure prophylaxis (PEP) that is not available, incomplete, not affordable, or not within reach for bite victims travel means. Only the first barrier, inadequate vaccination of dogs, is now being seriously addressed. It is also often not done effectively or sustainably. Rabies PEP has evolved as a complex, prolonged process, usually delegated to centers in larger cities. It is virtually unavailable in villages or small communities where most dog bites occur, victims are poor and usually unable to travel a long distance multiple times to receive PEP. Reseacrh that led to better understanding of the pathophysiology of rabies and immune responses to potent vaccines and immunoglobulin have allowed shortening and making PEP more evidence based. This knowledge needs to be adopted and applied so that PEP can be rendered safely and affordably where needed the most: by village health care workers who have long performed more complex services after appropriate training. Recent research makes this an important and long neglected goal that is now within our means to implement.

Keywords: rabies, post-exposure prophylaxis, availability, immunoglobulin

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Authors: Ntokozo Dennis Ndwandwe

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The aim of the study was to explore the barriers facing the implementation of peace education as a strategy to combat violence in selected secondary schools in the Western Cape Province of South Africa. The problem that motivated this enquiry was the absence of stable peace and the increase of incidents of violence in schools. A qualitative approach was followed when conducting the study, and small samples of three case studies of secondary schools were used. Method used in collecting data consisted of semi-structured interviews; focus group interviews and observation. The participants consisted of the program manager for Quaker for Peace Centre (QPC), three principals, nine teachers, and fifteen learners. Data were analysed by transcribing, organising, marking by hand and coding that produced labels that allowed key points to be highlighted. Findings revealed that the effective implementation of peace education was being constrained by factors such as financial constraints, inadequate time allocated, lack of parental involvement, over work-loaded teachers, negative attitude and other societal influences. It is recommended that teachers should receive an ongoing training for peace education. Therefore, the government should prioritise and provide funds for peace education. In addition, parental involvement should be improved in order to enhance the implementation of peace education in selected secondary schools.

Keywords: barriers, implementation, conflict, peace, peace education, conflict resolution, violence

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Authors: M. A. Rashed, A. S. Mansour, H. Faris, W. Afify

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The calcarenites carbonate rocks of the Quaternary ridges, which extend along the northwestern Mediterranean coastal plain of Egypt, represent an excellent model for the transformation of loose sediments to real sedimentary rocks by the different stages of meteoric diagenesis. The depositional and diagenetic fabrics of the rocks, in addition to the strata orientation, highly affect their ultimate compressive strength and other geotechnical properties. There is a marked increase in the compressive strength (UCS) from the first to the fourth ridge rock samples. The lowest values are related to the loose packing, weakly cemented aragonitic ooid sediments with high porosity, besides the irregularly distributed of cement, which result in decreasing the ability of these rocks to withstand crushing under direct pressure. The high (UCS) values are attributed to the low porosity, the presence of micritic cement, the reduction in grain size and the occurrence of micritization and calcretization processes. The strata orientation has a notable effect on the measured (UCS). The lowest values have been recorded for the samples cored in the inclined direction; whereas the highest values have been noticed in most samples cored in the vertical and parallel directions to bedding plane. In case of the inclined direction, the bedding planes were oriented close to the plane of maximum shear stress. The lowest and highest anisotropy values have been recorded for the first and the third ridges rock samples, respectively, which may attributed to the relatively homogeneity and well sorted grain-stone of the first ridge rock samples, and relatively heterogeneity in grain and pore size distribution and degree of cementation of the third ridge rock samples, besides, the abundance of shell fragments with intra-particle pore spaces, which may produce lines of weakness within the rock.

Keywords: compressive strength, anisotropy, calcarenites, Egypt

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Authors: Budi Purnomo, Karen M. Fernandez

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The creation of an ASEAN Community in 2015 is definitely one thing to look forward to. Integration may have birth pains in the beginning but at the end of the day, there are many opportunities that each member-state can take advantage that will benefit the people of ASEAN. Once fully integrated in 2015, ASEAN-certified tourism professionals who pass the common competency standards may find employment in various divisions of labor that are common across various sectors of tourism in member countries. At present, there are six labor divisions where tourism professionals may find employment in ASEAN member countries: namely Front Office; Housekeeping; Food Production; Food and Beverage Services (for Hotel Services); Travel Agency; and Tour Operations (for Travel Services Division). The study attempts to assess the readiness of Indonesian and Filipino students prospective skilled and educated tourism labors to work in ASEAN member countries by 2015. The data sources are obtained from a researcher-designed questionnaire and in-depth interview to reveal the interest of Indonesian and Filipino students to work in other ASEAN member states. The questionnaires were distributed to 240 third and fourth year students who are currently enrolled at the leading tourism institutes/universities in Indonesia and Philippines. The findings of the study will reveal the fulfillment of the requirements to work in ASEAN member-states, the comparison of existing tourism management curricula of Indonesia and Philippines to the Common ASEAN Curriculum (CATC) and Regional Qualifications Framework and Skills Recognition System (RQFSRS) which supports the policies of the Ministry of Tourism and Creative Economy of the Republic of Indonesia and the Department of Tourism and Department of Labor and Employment of the Republic of the Philippines.

Keywords: ASEAN economic community, prospective skilled and educated tourism labors, tourism labor movement, ASEAN certified-tourism professionals

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Authors: Mehdi Montakhabrazlighi, Ercan Balikci

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The neural network (NN) method is applied to alloy development of single crystal Ni-base Superalloys with low density and improved mechanical strength. A set of 1200 dataset which includes chemical composition of the alloys, applied stress and temperature as inputs and density and time to rupture as outputs is used for training and testing the network. Thermodynamic phase diagram modeling of the screened alloys is performed with Thermocalc software to model the equilibrium phases and also microsegregation in solidification processing. The model is first trained by 80% of the data and the 20% rest is used to test it. Comparing the predicted values and the experimental ones showed that a well-trained network is capable of accurately predicting the density and time to rupture strength of the Ni-base superalloys. Modeling results is used to determine the effect of alloying elements, stress, temperature and gamma-prime phase volume fraction on rupture strength of the Ni-base superalloys. This approach is in line with the materials genome initiative and integrated computed materials engineering approaches promoted recently with the aim of reducing the cost and time for development of new alloys for critical aerospace components. This work has been funded by TUBITAK under grant number 112M783.

Keywords: neural network, rupture strength, superalloy, thermocalc

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Authors: Shalini Tripathi, Pardeep Kumar

Abstract:

The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Robin Molinier

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Industrial symbiosis (I.S) rely on two basic modes of cooperation between organizations that are infrastructure/service sharing and resource substitution (the use of waste materials, fatal energy and recirculated utilities for production). The former consists in the intensification of use of an asset and thus requires to compare the incremental investment cost to be incurred and the stand-alone cost faced by each potential participant to satisfy its own requirements. In order to investigate the way such a cooperation mode can be implemented we formulate a game theoretic model integrating the grassroot investment decision and the ex-post access pricing problem. In the first period two actors set cooperatively (resp. non-cooperatively) a level of common (resp. individual) infrastructure capacity oversizing to attract ex-post a potential entrant with a plug-and-play offer (available capacity, tariff). The entrant’s requirement is randomly distributed and known only after investments took place. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period under some conditions that we derive. The entrant willingness-to-pay for the access to the infrastructure is driven by both her standalone cost and the complement cost to be incurred in case she chooses to access an infrastructure whose the available capacity is lower than her requirement level. The expected complement cost function is thus derived, and we show that it is decreasing, convex and shaped by the entrant’s requirements distribution function. For both uniform and triangular distributions optimal capacity level is obtained in the cooperative setting and equilibrium levels are determined in the non-cooperative case. Regarding the latter, we show that competition is deterred by the first period investor with the highest requirement level. Using the non-cooperative game outcomes which gives lower bounds for the profit sharing problem in the cooperative one we solve the whole game and describe situations supporting sharing agreements.

Keywords: capacity, cooperation, industrial symbiosis, pricing

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Authors: Dina Ahmed Alkhodary

Abstract:

Human Resources are the individual skills, knowledge, attitude, capabilities and experience collected to produce wealth to the company. Human Resource disclosure is the process of involving, reporting, and sharing the Investments made in the Human Resources of an Organization that such as organizations short goals and objectives, employees creation value, training and development plan are presently not accounted for in the conventional accounting practices which is importance nowadays to reduce the employee`s turnover. For the purpose of the study 3 telecommunications companies in Jordan have been selected. Telecommunication industry has been chosen for this study since it is a successful sector in Jordan and Human resource disclosure practices were adopted in all the selected companies and companies was aware to the HR practices. The objective of the study is to find out the HR disclosures practices of the telecommunication Companies in Jordan and to find the relationship between the HR Disclosures practices and employees’ turnover which has been measured by leaver proficiencies, remaining member proficiencies and the new comers proficiencies. The researcher has used the questioner to collect data for the research purpose. Results reveal that There are human resource disclosure practices in telecommunication companies in Jordan but in some areas only and has found There that there is a significant relationship between the human resource disclosure practices of the telecommunication companies in Jordan and Employees turnover. It is important to the companies to disclose more information and it’s important to the researchers to study the HR disclosure in the other industries in Jordan to increase the awareness about it.

Keywords: HR, disclosure, employee, turnover

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

Abstract:

Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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Authors: H. Booke, R. Nordmeier

Abstract:

Sudden cardiac arrest is sometimes eye-witnessed by kids. Mostly, their (grand-)parents are affected by sudden cardiac arrest, putting these kids under enormous psychological pressure: Although they are more than desperate to help, they feel insecure and helpless and are afraid of causing harm rather than realizing their chance to help. Even years later, they may blame themselves for not having helped their beloved ones. However, the absolute majority of school children - at least in Germany - is not educated to provide first aid. Teaching young kids (5th grade) in basic life support thus may help to save lives while washing away the kids' fear from causing harm during cardio-pulmonary resuscitation. A teaching of circulatory and respiratory (patho-)physiology, followed by hands-on training of basic life support for every single child, was offered to each school in our district. The teaching was performed by anesthesiologists, and the program was called 'kids can save lives'. However, before enrollment in this program, the entire class must have had lessons in biology with a special focus on heart and circulation as well as lung and gas exchange. More than 1.000 kids were taught and trained in basic life support, giving them the knowledge and skills to provide basic life support. This may help to reduce the rate of failure to provide first aid. Therefore, educating young kids in basic life support may not only help to save lives, but it also may help to prevent any feelings of guilt because of not having helped in cases of eye-witnessed sudden cardiac arrest.

Keywords: teaching, children, basic life support, cardiac arrest, CPR

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 52