Search results for: ubiquitous learning environment scaffolding

Authors: Cate MacMillan, Nicholas J. Stevens, Johanna Rosier, Steven Boyd

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Choosing where to live is an important decision for anybody, however, this decision is more complex if you are an adult with intellectual disability. Our research asked adults with intellectual disability, parents and carers and disability, housing and built environment decision makers what they considered important in deciding where to live. If medical advances continue to improve the longevity of adults with intellectual disability, many of these adults will outlive their parents. With appropriate community support, and in appropriately designed neighbourhoods, many will be able to live independently. Our research suggests that the key to achieving independent living as an adult with intellectual disability is not so much about the house but the type of neighbourhood and its design. This paper presents the results of interviews and details a practical approach which will better inform urban development decision-makers in establishing safe, inclusive and accessible neighbourhood design.

Keywords: inclusion, independent living, intellectual disability, neighbourhoods, systems thinking, urban design and planning

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Authors: Kavish Kejriwal, Richa Grover

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Consumer awareness and pending legislation have pushed environmental issues into the spotlight, making it imperative for organizations to have a plan of action for “going green.” This is the reason why Green Supply Chain Management has become the integral part of many organization with a goal to reduce cost, increase efficiency and be environmental friendly. Implementation of GSCM involves many factors which act as barriers, making it a tedious task. These barriers have different relationship among themselves creating different impact on implementation Green Supply Chain Management. This work focuses on determining those barriers which have essentially to be removed in the initial stages of GSCM adoption. In this work, the author has taken the case of a petroleum industry in order to come up with a solution. A DEMATEL approach is used to reach the solution.

Keywords: barriers, environment, green supply chain management, impact, interpretive structural modeling

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Authors: Shohei Nakai, Yasuhiro Yamada

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Weed suppression and weeding are necessary measures for rice cultivation. Weed suppression precedes the process of weeding. It means suppressing the growth of young weeds and creating a weed-less environment. If we suppress the growth of weeds, we can reduce the number of weeds in a paddy field. This would result in a reduction of the weeding work load. In this paper, we will show how we developed a weed suppression robot for the purpose of reducing the weeding work load. The robot has a laser range finder for autonomous mobility and a robot arm for weed suppression. It travels along the rice rows without stepping on and injuring the rice plants in a paddy field. The robot arm applies force to the weed seedlings and thereby suppresses the growth of weeds. This paper will explain the methodology of the autonomous mobile, the experiment in weed suppression, and the method of controlling the robot’s posture on uneven ground.

Keywords: mobile robot, paddy field, robot arm, weed

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Authors: Yeganeh Jabbari, Sepideh Khalatabad

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This study explores the development of virtual reality (VR) technology for training applications, specifically its the potential benefits of VR technology for employee training and its ability to simulate real-world scenarios in a safe and controlled environment are highlighted, along with the associated cost and time savings. The adoption of VR technology in high-risk industrial organizations such as the oil and gas industry is discussed, with a focus on its ability to improve worker performance. Additionally, the use of VR technology in activities such as simulation and data visualization in the oil and gas industry is explored, leading to enhanced safety measures and collaboration between teams. The integration of advanced technologies such as robotics is mentioned as a way to further promote efficiency and sustainability. Also, the study mentions that the digital transformation of the oil and gas industry is revolutionizing operations and promoting safety, efficiency, and sustainability through the use of VR technology.

Keywords: virtual reality training, virtual reality benefits, high-risk industries, digital transformation

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Authors: Greeshma Sharma, Sushil Chandra, Vijander Singh, Alok Prakash Mittal

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Navigational ability requires spatial representation, planning, and memory. It covers three interdependent domains, i.e. cognitive and perceptual factors, neural information processing, and variability in brain microstructure. Many attempts have been made to see the role of spatial representation in the navigational ability, and the individual differences have been identified in the neural substrate. But, there is also a need to address the influence of planning, memory on navigational ability. The present study aims to evaluate relations of aforementioned factors in the navigational ability. Total 30 participants volunteered in the study of a virtual shopping complex and subsequently were classified into good and bad navigators based on their performances. The result showed that planning ability was the most correlated factor for the navigational ability and also the discriminating factor between the good and bad navigators. There was also found the correlations between spatial memory recall and navigational ability. However, non-verbal episodic memory and spatial memory recall were also found to be correlated with the learning variable. This study attempts to identify differences between people with more and less navigational ability on the basis of planning and memory.

Keywords: memory, planning navigational ability, virtual reality

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Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

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This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

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Authors: Yao-Hong Tsai

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This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: authentication, iris recognition, adaboost, local binary pattern

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Authors: Wongwarit Nipitwittaya

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The objectives of this research is bringing folk song with the teaching of Western music were to examine to investigate, to compare, develop the skill, technique, knowledge of Thai folk song and to preserve folk song of Thailand to be known more widely also learn Thai culture from Thai folk song. Study by bringing Thailand folk song is widely known for learning with Western music in course brass performance. Bringing the melody of Thai folk music and changing patterns to western music notes for appropriate on brass performance. A sample was selected from brass students, using research by assessment of knowledge from test after used Thai folk song lesson. The lesson focus for scales and key signature in western music by divided into two groups, the one study by used research tools and another one used simple lesson and a collection of research until testing. The results of the study were as follows: 1. There are good development skill form research method 2. Sound recognition can be even better. The study was a qualitative research and data collection by observation.

Keywords: Thai folk song, brass instrument, key signature, western music

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Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike

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Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.

Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes

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Authors: Ugur Karakaya, Hasan Bulent Kantarcı

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In this study, firstly democratic thoughts which directly or indirectly affect economic development and/or the interaction between authoritarian regimes and the economic development and the direction and channels of this interaction were studied and then the study tried to determine how democracy affects economic development. It was concluded that the positive contributions of democracy to economic development were more determinant than the effects that were either negative or restrictive in terms of development. When compared to autocracy, since democracy is more successful in managing social conflicts, ensuring political stability and preventing social disasters such as famine, it contributes more to economic development. Democracy also facilitates delegation of authority, provides a stable investment environment and accelerates mobilization of resources in accordance with economic growth/development. Democracy leads to an increase in human capital accumulation and increases the growth rate through reducing income inequality. It can be said that democratic regimes are the most appropriate ones in terms of increasing economic performance and supporting economic development through their strong institutional structures and the assurance they will ensure in property rights.

Keywords: democracy, economic growth, economic freedom, autocratic regime

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Phontip Kanlahasuth

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This paper presents the environmental safety and occupational health risk assessment of rocket static test by assessing risk level from probability and severity and then appropriately applying the risk control measures. Before the environmental safety and occupational health measures are applied, the serious hazards level is 31%, medium level is 24% and low level is 45%. Once risk control measures are practically implemented, the serious hazard level can be diminished, medium level is 38%, low level is 45% and eliminated level is 17%. It is clearly shown that the environmental safety and occupational health measures can significantly reduce the risk level.

Keywords: rocket static test, hazard, risk, risk assessment, risk analysis, environment, safety, occupational health, acceptable risk, probability, severity, risk level

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Authors: Jason M. Hegenauer, Nicholas Fucci

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In the late 1990s, a major deinstitutionalization movement of elderly patients took place, since which, the design of long-term care facilities has not been adequately analyzed in the United States. Over the course of the last 25 years, major innovations in construction methods, technology, and medicine have been developed, drastically changing the landscape of healthcare architecture. In light of recent events, and the expected increase in elderly populations with the aging of the baby-boomer generation, it is evident that reconsideration of these facilities is essential for the proper care of aging populations. The global response has been effective in stifling this pandemic; however, widespread disease still poses an imminent threat to the human race. Having witnessed the devastation Covid-19 has reaped throughout nursing homes and long-term care facilities, it is evident that the current strategies for protecting our most vulnerable populations are not enough. Light renovation of existing facilities and previously overlooked considerations for new construction projects can drastically lower the risk at nursing homes and long-term care facilities. A reconfigured entry sequence supplements several of the features which have been long-standing essentials of the design of these facilities. This research focuses on several aspects identified as needing improvement, including indoor environment quality, security measures incorporated into healthcare architecture and design, and architectural mitigation strategies for sick building syndrome. The results of this study have been compiled as 'best practices' for the design of future healthcare construction projects focused on the health, safety, and quality of life of the residents of these facilities. These design strategies, which can easily be implemented through renovation of existing facilities and new construction projects, minimize risk of infection and spread of disease while allowing routine functions to continue with minimal impact, should the need for future lockdowns arise. Through the current lockdown procedures, which were implemented during the Covid-19 pandemic, isolation of residents has caused great unrest and worry for family members and friends as they are cut off from their loved ones. At this time, data is still being reported, leaving infection and death rates inconclusive; however, recent projections in some states list long-term care facility deaths as high as 60% of all deaths in the state. The population of these facilities consists of residents who are elderly, immunocompromised, and have underlying chronic medical conditions. According to the Centers for Disease Control, these populations are particularly susceptible to infection and serious illness. The obligation to protect our most vulnerable population cannot be overlooked, and the harsh measures recently taken as a response to the Covid-19 pandemic prove that the design strategies currently utilized for doing so are inadequate.

Keywords: building security, healthcare architecture and design, indoor environment quality, new construction, sick building syndrome, renovation

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Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

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Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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Authors: Aimad Oulebsir, Toufik Chaabane, Venkataraman Sivasankar, André Darchen, Titus A. M. Msagati

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Currently, the presence of pharmaceutical substances in the environment is an emerging pollution leading to the disruption of ecosystems. Indeed, water loaded with pharmaceutical residues is an issue that has raised the attention of researchers. The aim of this study was to monitor the effectiveness of the alumina electro-generated by the adsorption process the iron of well water for the production of drugs. The Fe2+ was removed from wastewater by adsorption in a batch cell. Performance results of iron removal by alumina electro-generated revealed that the efficiency of the carrier in the method of electro-generated adsorption. The overall Fe2+ of the synthetically solutions and simulated effluent removal efficiencies reached 75% and 65%, respectively. The application of models and isothermal adsorption kinetics complement the results obtained experimentally. Desorption of iron was investigated using a solution of 0.1M NaOH. Regeneration of the tests shows that the adsorbent maintains its capacity after five adsorption/desorption cycles.

Keywords: electrocoagulation, aluminum electrode, electrogenerated alumina, iron, adsorption/desorption

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Authors: Hyunjoo Park, Taehyun Kim, Taehyun Kim

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Human life, activity, and culture depend on the wider environment. Cities offer economic opportunities for goods and services, but cannot exist in environments without food, energy, and water supply. Technological innovation in energy supply and transport speeds up the expansion of urban areas and the physical separation from agricultural land. As a result, division of urban agricultural areas causes more energy demand for food and goods transport between the regions. As the energy resources are leaking all over the world, the impact on the environment crossing the boundaries of cities is also growing. While advances in energy and other technologies can reduce the environmental impact of consumption, there is still a gap between energy supply and demand by current technology, even in technically advanced countries. Therefore, reducing energy demand is more realistic than relying solely on the development of technology for sustainable development. The purpose of this study is to introduce the application of carbon footprint assessment in fields of urban planning and geography. In urban studies, carbon footprint has been assessed at different geographical scales, such as nation, city, region, household, and individual. Carbon footprint assessment for a nation and a city is available by using national or city level statistics of energy consumption categories. By means of carbon footprint calculation, it is possible to compare the ecological capacity and deficit among nations and cities. Carbon footprint also offers great insight on the geographical distribution of carbon intensity at a regional level in the agricultural field. The study shows the background of carbon footprint applications in urban planning and geography by case studies such as figuring out sustainable land-use measures in urban planning and geography. For micro level, footprint quiz or survey can be adapted to measure household and individual carbon footprint. For example, first case study collected carbon footprint data from the survey measuring home energy use and travel behavior of 2,064 households in eight cities in Gyeonggi-do, Korea. Second case study analyzed the effects of the net and gross population densities on carbon footprint of residents at an intra-urban scale in the capital city of Seoul, Korea. In this study, the individual carbon footprint of residents was calculated by converting the carbon intensities of home and travel fossil fuel use of respondents to the unit of metric ton of carbon dioxide (tCO₂) by multiplying the conversion factors equivalent to the carbon intensities of each energy source, such as electricity, natural gas, and gasoline. Carbon footprint is an important concept not only for reducing climate change but also for sustainable development. As seen in case studies carbon footprint may be measured and applied in various spatial units, including but not limited to countries and regions. These examples may provide new perspectives on carbon footprint application in planning and geography. In addition, additional concerns for consumption of food, goods, and services can be included in carbon footprint calculation in the area of urban planning and geography.

Keywords: carbon footprint, case study, geography, urban planning

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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Authors: Sum Lau, Wing Chung Cleo Lau, Wing Yan Chu, Long Ching Ip, Wan Yin Lo, Jo Long Sam Yau, Ka Ho Hui, Sze Yi Mak

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Biomedical engineering (BME) is an interdisciplinary subject where knowledge about biology and medicine is applied to novel applications, solving clinical problems. This subject is crucial for cities such as Hong Kong, where the burden on the medical system is rising due to reasons like the ageing population. Hong Kong, who is actively boosting technological advancements in recent years, sets BME, or biotechnology, as a major category, as reflected in the 2018-19 Budget, where biotechnology was one of the four pillars for development. Over the years, while resources in terms of money and space have been provided, there has been a lack of talents expressed by both the academia and industry. While exogenous factors, such as COVID, may have hindered talents from outside Hong Kong to come, endogenous factors should also be considered. In particular, since there are already a few local universities offering BME programmes, their curriculum or style of education requires to be reviewed to intensify the network of the BME community and support post-academic career development. It was observed that while undergraduate (UG) studies focus on knowledge teaching with some technical training and postgraduate (PG) programmes concentrate on upstream research, the programmes are generally confined to the academic sector and lack connections to the industry. In light of that, a “Biomedical Innovation and Outreach Programme 2022” (“B.I.O.2022”) was held to connect students and professors from academia with clinicians and engineers from the industry, serving as a comparative approach to conventional education methods (UG and PG programmes from tertiary institutions). Over 100 participants, including undergraduates, postgraduates, secondary school students, researchers, engineers, and clinicians, took part in various outreach events such as conference and site visits, all held from June to July 2022. As a case study, this programme aimed to tackle the aforementioned problems with the theme of “4Cs” (connection, communication, collaboration, and commercialisation). The effectiveness of the programme is investigated by its ability to serve as an adult and continuing education and the effectiveness of causing social change to tackle current societal challenges, with the focus on tackling the lack of talents engaging in biomedical engineering. In this study, B.I.O.2022 is found to be able to complement the traditional educational methods, particularly in terms of knowledge exchange between the academia and the industry. With enhanced communications between participants from different career stages, there were students who followed up to visit or even work with the professionals after the programme. Furthermore, connections between the academia and industry could foster the generation of new knowledge, which ultimately pointed to commercialisation, adding value to the BME industry while filling the gap in terms of human resources. With the continuation of events like B.I.O.2022, it provides a promising starting point for the development and relationship strengthening of a BME community in Hong Kong, and shows potential as an alternative way of adult education or learning with societal benefits.

Keywords: biomedical engineering, adult education for social change, comparative methods and principles, lifelong learning, faced problems, promises, challenges and pitfalls

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However,these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: optimization technique, quality assurance, software certification model, software assessment

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Authors: Sandra Figueiredo

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To guarantee the well-being and the academic achievement it is crucial into the global society to develop techniques to assess language competence and control psychological aspects on the second language learning context. The current scenario of the war conflicts that are emerging mostly in Europe and Middle East have been resulting in forced immigration and refugees’ maladjustment. The inclusion is the priority for United Nations concerning the sustainability of societies. For inclusion, psychological screening tests and educational tools are urgent. Method: Approximately 100 refugees from Ukraine were assessed, in Portugal, under the administration of the PCL-5. This 20-item instrument evaluates the Post-Traumatic Disorder. Expected results: The statistical analysis will be performed with the International Database Analyzer and SPSS (v. 28). The results expected are the relationship between traumatic events caused by war and post-traumatic symptomatology (anxiety, hypervigilance, stress). Implications: The data will be discussed concerning the problems of belonging, the psychological constraints and educational attainment (language needs included) experienced by the individuals more recently arrived to the hosting societies. The refugees’ acculturation process and the emotional regulation will be addressed.

Keywords: refugees, immigration, educational needs, trauma, inclusion, second language.

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Authors: Juneseok You, Chanho Park, Kuehwan Jang, Sungsoo Na

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Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nanotoxic material, qcm, frequency, in situ sensing

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Authors: Wanghongshu Zhou

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This study aims to explore the relationship between the L2MSS and WTC among Chinese non-English major students in order to provide pedagogical implications for English as a Foreign Language (EFL) classrooms in Chinese universities. By employing a mixed methods approach, we involved 103 Chinese non-English major students from a typical university in China, conducted questionnaire survey to measure their levels of L2WTC and L2MSS level, and then analyzed the correlation between the two above mentioned variables. Semi-structured interviews were conducted with eight participants to provide a deeper understanding and explanation of the questionnaire data. Findings show that 1) Chinese non-English major students’ ideal L2 self and L2 learning experience could positively predict their L2 WTC in EFL class; 2) Chinese non-English major students’ ought-to L2 self might have no significant impact on their L2 WTC in EFL class; and 3) self-confidence might be another main factor that will influence Chinese non-English major students’ L2 WTC in EFL class. These findings might shed light on the second language acquisition field and provide pedagogical recommendations for pre-service as well as in-service EFL teachers.

Keywords: L2 willingness to communicate, L2 motivation, self-confidence, Chinese non-English major students

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Authors: Selaphares Jatico Tajale

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This research aims to understand the notions of quality education by conducting case studies among internationally-accredited Christian schools in Southeast Asia. Five internationally-accredited Christian schools from Cambodia, Indonesia, Malaysia, The Philippines, and Singapore will be chosen as cases for this study. This study will utilize the processes of interviews, filling up of questionnaires, and writing of reflections in order to obtain data and relevant information. These processes will be conducted through multi-sectoral respondents such as administrators, academic heads, and faculty. This study employs five aspects within the realm of education as guides in the formulation of questionnaire and guide questions in the interview, namely: a) school context, b) classroom, c) quality assurance, d) stakeholders, e) faculty and staff. Guide interview questions and questions in the questionnaires are formulated to uncover information on how those five aspects were managed to achieve desired student learning outcomes and uncover other information useful for the study.

Keywords: internationally-accredited, notions of quality education, quality education, quality education in Southeast Asia

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Authors: Bilal Liaqat, Muhammad Umar, Zara Bashir, Hassan Rafique, Mohsin Abbasi, Zarak Khan

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Transformational leadership is one of the most studied topics in the organization sciences. However, the impact of transformational leadership on employee’s individual attributes have not yet been studied. Purpose: This research aims to discover the relationship between transformational leadership and employee motivation, performance and creativity. Moreover, the study will also investigate the influence of transformational leadership on employee performance through employee motivation and employee creativity. Design-Methodology-Approach: The data was collected from employees in different organization. This cross-sectional study collected data from employees and the methodology used includes survey data that were collected from employees in organizations. Structured interviews were also conducted to explain the outcomes from the survey. Findings: The results of this study reveal that transformational leadership has a positive impact on employee’s individual attributes. Research Implications: Although this study expands our knowledge about the role of learning orientation between transformational leadership and employee motivation, performance and creativity, the prospects for further research are still present.

Keywords: employee creativity, employee motivation, employee performance, transformational leadership

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Authors: James A. Adeyanju, John O. Olajide, Akinbode A. Adedeji

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A predictive mathematical model based on the fundamental principles of mass transfer was developed to simulate the moisture content and oil content during Deep-Fat Frying (DFF) process of dodo. The resulting governing equation, that is, partial differential equation that describes rate of moisture loss and oil uptake was solved numerically using explicit Finite Difference Technique (FDT). Computer codes were written in MATLAB environment for the implementation of FDT at different frying conditions and moisture loss as well as oil uptake simulation during DFF of dodo. Plantain samples were sliced into 5 mm thickness and fried at different frying oil temperatures (150, 160 and 170 ⁰C) for periods varying from 2 to 4 min. The comparison between the predicted results and experimental data for the validation of the model showed reasonable agreement. The correlation coefficients between the predicted and experimental values of moisture and oil transfer models ranging from 0.912 to 0.947 and 0.895 to 0.957, respectively. The predicted results could be further used for the design, control and optimization of deep-fat frying process.

Keywords: frying, moisture loss, modelling, oil uptake

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Authors: Zahra Mohagheghian, Fatema Agharebparast

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Professional ethic is a subject that has been an issue today, so most of the businesses, including the teaching profession, understand the need and importance of it. So they need to develop a code of professional ethics for their own. In this regard, this study seeks to answer the question, with respect to the integrity of the Qur'an (Nahl / 89), is it possible to contemplate the divine teachers conduct to extract the divine pattern for teaching and training? In the code of conduct for divine teachers what are the most important moral obligations and duties of the teaching professionals? The results of this study show that the teaching of Khidr, according to the Quran’s verses, Abundant and subtle hints emphasized that it can be as comprehensive and divine pattern used in teaching and in the drafting of the charter of professional ethics of teachers used it. Also, the results show that in there have been many ethical principles in prophet Khidr’s teaching pattern.The most important ethical principles include: Student assessment, using objective and not subjective examples, assessment during teaching, flexibility, and others. According to each of these principles can help teachers achieve their educational goals and lead human being in their path toward spiritual evaluation.

Keywords: professional ethics, teaching-learning process, teacher, student, Quran

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Authors: Isiya Salihu Shinkafi

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The focus of this paper is to elaborate on employment opportunities within the tourism sector and the solutions to youth unemployment in Africa and Nigeria in particular. Youth unemployment creates a monumental social problem to African continent, the world over and Nigeria in particular. The intelligence of this paper was collected from secondary sources using previews researches and analysis of scholars to gather empirical data. The findings revealed that unemployment in Africa and specifically Nigeria among youths were caused by certain factors which constitute a greater challenge to the economy and the existence of the continent. The tourism sector provides the enabling environment to address the different categories of unemployment among the youths. One of the unique characteristics of the tourism industry that makes it a prime sector from which employment can be engineered; especially in the case of the African countries, are its labour intensive characteristics of both experts, skilled, semi-skilled and unskilled labour.

Keywords: tourism industry, employment opportunities, youth employment

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Authors: Kingfahd Adewale Adedapo, Adekunle Ajisebiyawo

Abstract:

The focus of this paper is to explore the different theoretical perspectives that underline academic attempts at understanding and explaining the nature of conflicts in Africa. The African environment is riddled with the past history of conflicts among groups either for an economic outlet or imperial space, and most often, such past negative interactions have made it difficult even now for some of these groups to live harmoniously together within the present state system and to trust each other. The paper observed that no one theory or explanatory schema could offer a holistic explanation of conflict in Africa. At best, each of the possible theories can only offer a partial explanation of the causes and nature of conflict in a particular African society or state. This paper, therefore, attempted to synthesize the many sources of theories of conflicts and provided the intellectual background from which these different theories emanated. Therefore, if this paper has done anything at all, it is to offer the basis for assessing different theoretical strands aimed at offering cogent and reliable explanations for most of the conflicts in Africa and especially in the West African sub-region.

Keywords: conflict, functionalism, humanitarianism, structuralism, theory

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

Abstract:

Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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