Search results for: mixed method research

Authors: Athanasia Kouroupa

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Existing research highlights the effect of employing robots in sessions with children and young people on the autism spectrum to develop and practice skills important to independent and functional living. The systematic review aimed to explore the way robots has been used with children and young people on the autism spectrum and the effect of using robots as a therapeutic interface. An electronic bibliographic database search using a combination of expressions was conducted. Data were extracted in relation to robot types, session characteristics, and outcomes and analysed using narrative synthesis. Forty studies were selected in the review. Humanoid robots were predominantly used to practice a range of social and communication skills. On average, children and young people on the autism spectrum had five sessions, twice a week, for approximately half an hour. Having sessions with a robot was commonly equal to or more effective than 'traditional' interventions delivered by a human therapist or having no therapy. The review reported encouraging outcomes to practice and develop a range of skills with children and young people on the autism spectrum. These findings suggest that some form of intervention is favourable over no intervention. However, there is little evidence for the relative effectiveness of the robot-based intervention as an innovative alternative option. Many of the studies had methodological weaknesses that make them vulnerable to bias. There is a need for further research that adheres to strict scientific methods making direct comparisons between different treatment options.

Keywords: autism, children, robots, outcomes

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Authors: Muhammad G. Almatar, Mohammad A. Alnasrallah

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This research focuses on the study of three main issues: 1) The temporal analysis of leukemia for a period of six years (2006-2012), 2) spatial analysis by investigating this phenomenon in the Kuwaiti society spatially in the residential areas within the six governorates, 3) the use of Geographic Information System technology in investigating the hypothesis of the research and its variables using the linear regression, to show the pattern of linear relationship. The study depends on utilizing the map to understand the distribution of blood cancer in Kuwait. Several geodatabases were created for the number of patients and air pollution. Spatial interpolation models were used to generate layers of air pollution in the study area. These geodatabases were tested over the past six years to reach the conclusion: Is there a relationship with significant significance between the two main variables of the study: blood cancer and air pollution? This study is the first to our best knowledge. As far as the researchers know, the distribution of this disease has not been studied geographically at the level of regions in Kuwait within six years and in specific areas as described above. This study investigates the concentration of this type of disease. The study found that there is no relationship of significant value between the two variables studied, and this may be due to the nature of the disease, which are often hereditary. On the other hand, this study has reached a number of suggestions and recommendations that may be useful to decision-makers and interested in the study of leukemia in Kuwait by focusing on the study of genetic diseases, which may be a cause of leukemia rather than air pollution.

Keywords: Kuwait, GIS, cancer, geography

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Authors: Rashmi Motwani, Ritu Raj

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The emergence of online educational environments has changed the way adolescents learn, which has benefits and drawbacks for their development. This review has as its goal the examination of how personality traits and adolescents’ well-being are associated in the setting of online education. This review analyses the effects of a variety of personality traits on the mental, emotional, and social health of online school-going adolescents by looking at a wide range of previous research. This research explores the mechanisms that mediate or regulate the connection between one's personality traits and well-being in an online educational environment. The elements can be broken down into two categories: technological, like internet availability and digital literacy, and social, including social support, peer interaction, and teacher-student connections. To improve the well-being of adolescents in online learning environments, it is essential to understand factors that moderate the effects of interventions and support systems. This review concludes by emphasising the complex nature of the association between individual differences in personality and the success of online students aged 13 to 18. This review contributes to the development of evidence-based strategies for promoting positive mental health and overall well-being among adolescents engaged in online educational settings by shedding light on the impact of personality traits on various dimensions of well-being and by identifying the mediating or moderating factors. Educators, governments, and parents can use the findings of this review to create an online learning environment that is safe and well-being for adolescents.

Keywords: personality traits, adolescent, wellbeing, online education

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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Authors: Robert Joseph M. Licup

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The deployment of the fifth-generation (5G) mobile system through mmWave frequencies is the new solution in the requirement to provide higher bandwidth readily available for all users. The usage pattern of the mobile users has moved towards either the work from home or online classes set-up because of the pandemic. Previous mobile technologies can no longer meet the high speed, and bandwidth requirement needed, given the drastic shift of transactions to the home. The millimeter-wave (mmWave) underutilized frequency is utilized by the fifth-generation (5G) cellular networks that support multi-gigabit-per-second (Gbps) transmission. However, due to its short wavelengths, high path loss, directivity, blockage sensitivity, and narrow beamwidth are some of the technical challenges that need to be addressed. Different tools, technologies, and scenarios are explored to support network design, accurate channel modeling, implementation, and deployment effectively. However, there is a big challenge on how the consumer will adopt this solution and maximize the benefits offered by the 5G Technology. This research proposes to study the intricacies of technology diffusion, individual attitude, behaviors, and how technology adoption will be attained. The agent based simulation model shaped by the actual applications, technology solution, and related literature was used to arrive at a computational model. The research examines the different attributes, factors, and intricacies that can affect each identified agent towards technology adoption.

Keywords: agent-based model, AnyLogic, 5G O21, 5G mmWave solutions, technology adoption

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Authors: Adedayo Adeleke, Dineo Pule

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The ongoing load-shedding in most parts of South Africa, combined with climate change causing severe drought conditions in Cape Town, has left electricity consumers seeking alternative sources of power and water. Solar energy, which is abundant in most parts of South Africa and is regarded as a clean and renewable source of energy, allows for the generation of electricity via solar photovoltaic systems. Rainwater harvesting is the collection and storage of rainwater from building rooftops, allowing people without access to water to collect it. The lack of dependable energy and water source must be addressed by shifting to solar energy via solar photovoltaic systems and rainwater harvesting. Before this can be done, the potential of building rooftops must be assessed to determine whether solar energy and rainwater harvesting will be able to meet or significantly contribute to Atlantis industrial areas' electricity and water demands. This research project presents methods and approaches for automatically extracting building rooftops in Atlantis industrial areas and evaluating their potential for solar photovoltaics and rainwater harvesting systems using Light Detection and Ranging (LiDAR) data and aerial imagery. The four objectives were to: (1) identify an optimal method of extracting building rooftops from aerial imagery and LiDAR data; (2) identify a suitable solar radiation model that can provide a global solar radiation estimate of the study area; (3) estimate solar photovoltaic potential overbuilding rooftop; and (4) estimate the amount of rainwater that can be harvested from the building rooftop in the study area. Mapflow, a plugin found in Quantum Geographic Information System(GIS) was used to automatically extract building rooftops using aerial imagery. The mean annual rainfall in Cape Town was obtained from a 29-year rainfall period (1991- 2020) and used to calculate the amount of rainwater that can be harvested from building rooftops. The potential for rainwater harvesting and solar photovoltaic systems was assessed, and it can be concluded that there is potential for these systems but only to supplement the existing resource supply and offer relief in times of drought and load-shedding.

Keywords: roof potential, rainwater harvesting, urban plan, roof extraction

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Authors: Maciej Pieńkowski

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Lean Management is nowadays one of the most dominating management concepts within industrial and service environment, providing compelling business benefits to many companies. At the same time, its application in the non-governmental organizations has not been extensively researched yet. Filling this gap will address clear necessity of efficient management system in NGO environment and significantly improve operational performance of many organizations. The goal of the research is to verify effectiveness of Lean Management implementation in the non-governmental organizations, based on Wrocław Food Bank case study. The case study describes a Lean Management implementation project within analyzed organization. During the project, Wrocław Food Bank went through full 5-step Lean Thinking processes, which consist of value identification, value stream mapping, creation of flow, establishing pull and seeking perfection. The research contains a detailed summary of each of those steps and provides with information regarding results of their implementation. The major findings of the study indicate, that application of Lean Management in NGO environment is possible, however physical implementation of its guidelines can be strongly impeded by multiple constraints, which non-governmental organizations are facing. Due to challenges like limited resources, project based activities and lack of traditional supplier-customer relationship, many NGOs may fail in their efforts to implement Lean Management. Successful Lean application requires therefore strong leadership commitment, which would drive transformation to remove barriers and obstacles.

Keywords: lean management, non-governmental organizations, continuous improvement, lean thinking

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Authors: Aman Guru, Chiron Singhi

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The Earth’s climate is being changed at an unrivalled rate since beginning of the evolution of the Earth, 4–5 billion years back, but presently it gained pace due to unintentional anthropogenic disturbances and also increased global warming since the mid-20th century, and these incessant changes in the climatic pattern may bring unpropitious effect on global health and security. Today, however, it is not only the air, or water that are polluted, but the whole atmosphere is prone to pollution and this resulted in other cascading ramification in the form of change in the pattern of rainfall, melting of ice, the rise in the sea level etc. Human activities like production, transport, burning of fuels are adding umpteen dangerous pollutants to the atmosphere which in turn gives rise to global warming. Agriculture plays an imperative part in India's economy. Agriculture, along with fisheries and forestry, is one of the largest contributors to the Gross Domestic Product in India. Research on the effect of climate change and vulnerability of agriculture is a high need in India. A steady increase of CO2 is a primary cause of climate change and global warming and which in turn have a great impact on Indian agriculture. The research focuses on the effect of climate change on Indian agriculture and the proceedings and legal control of legislative measures on such issues and the ways to implement such laws which can help to provide a solution to these problems which can prove beneficial to Indian farmers and their agricultural produce.

Keywords: agriculture, climate change, global warming, India laws, legislative measures

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Authors: Natalia Limones, Javier Marzo, Marcus Wijnen, Aleix Serrat-Capdevila

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In this research we developed a structured approach for the detection of areas under the highest levels of drought risk that is suitable for data-scarce environments. The methodology is based on recent scientific outcomes and methods and can be easily adapted to different contexts in successive exercises. The research reviews the history of drought in the south of Angola and characterizes the experienced hazard in the episode from 2012, focusing on the meteorological and the hydrological drought types. Only global open data information coming from modeling or remote sensing was used for the description of the hydroclimatological variables since there is almost no ground data in this part of the country. Also, the study intends to portray the socioeconomic vulnerabilities and the exposure to the phenomenon in the region to fully understand the risk. As a result, a map of the areas under the highest risk in the south of the country is produced, which is one of the main outputs of this work. It was also possible to confirm that the set of indicators used revealed different drought vulnerability profiles in the South of Angola and, as a result, several varieties of priority areas prone to distinctive impacts were recognized. The results demonstrated that most of the region experienced a severe multi-year meteorological drought that triggered an unprecedent exhaustion of the surface water resources, and that the majority of their socioeconomic impacts started soon after the identified onset of these processes.

Keywords: drought risk, exposure, hazard, vulnerability

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Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

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Authors: Harneet Walia, Morteza Zihayat

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Customer acquisition has become one of the critical issues of any business in the 21st century; having a healthy customer base is the essential asset of the bank business. Term deposits act as a major source of cheap funds for the banks to invest and benefit from interest rate arbitrage. To attract customers, the marketing campaigns at most financial institutions consist of multiple outbound telephonic calls with more than one contact to a customer which is a very time-consuming process. Therefore, customized direct marketing has become more critical than ever for attracting new clients. As customer acquisition is becoming more difficult to archive, having an intelligent and redefined list is necessary to sell a product smartly. Our aim of this research is to increase the effectiveness of campaigns by predicting customers who will most likely subscribe to the fixed deposit and suggest the most suitable month to reach out to customers. We design a Time Aware Upsell Prediction Framework (TAUPF) using two different approaches, with an aim to find the best approach and technique to build the prediction model. TAUPF is implemented using Upsell Prediction Approach (UPA) and Clustered Upsell Prediction Approach (CUPA). We also address the data imbalance problem by examining and comparing different methods of sampling (Up-sampling and down-sampling). Our results have shown building such a model is quite feasible and profitable for the financial institutions. The Time Aware Upsell Prediction Framework (TAUPF) can be easily used in any industry such as telecom, automobile, tourism, etc. where the TAUPF (Clustered Upsell Prediction Approach (CUPA) or Upsell Prediction Approach (UPA)) holds valid. In our case, CUPA books more reliable. As proven in our research, one of the most important challenges is to define measures which have enough predictive power as the subscription to a fixed deposit depends on highly ambiguous situations and cannot be easily isolated. While we have shown the practicality of time-aware upsell prediction model where financial institutions can benefit from contacting the customers at the specified month, further research needs to be done to understand the specific time of the day. In addition, a further empirical/pilot study on real live customer needs to be conducted to prove the effectiveness of the model in the real world.

Keywords: customer acquisition, predictive analysis, targeted marketing, time-aware analysis

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Authors: S. Asad Ali Gillani, Ahmed Toumi, Anaclet Turatsinze

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After a certain period of time, the degradation of concrete structures is unavoidable. For large concrete areas, thin bonded cement-based overlay is a suitable rehabilitation technique. Previous research demonstrated that durability of bonded cement-based repairs is always a problem and one of its main reasons is deboning at interface. Since durability and efficiency of any repair system mainly depend upon the bond between concrete substrate and repair material, the bond between concrete substrate and repair material can be improved by increasing the surface roughness. The surface roughness can be improved by performing surface treatment of the concrete substrate to enhance mechanical interlocking which is one of the basic mechanisms of adhesion between two surfaces. In this research, bond tensile strength of cement-based overlays having substrate surface prepared using different techniques has been characterized. In first step cement based substrate was prepared and then cured for three months. After curing two different types of the surface treatments were performed on this substrate; cutting and sandblasting. In second step overlay was cast on these prepared surfaces, which were cut and sandblasted surfaces. The overlay was also cast on the surface without any treatment. Finally, bond tensile strength of cement-based overlays was evaluated in direct tension test and the results are discussed in this paper.

Keywords: concrete substrate, surface preparation, overlays, bond tensile strength

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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Authors: Tarek Soliman Mostafa Soliman Al-Nana'i

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There are non-steady voiced augments in the Semitic languages, and in the morphological and structural augmentation, two sounds were augments in all Semitic languages at the level of the spoken language and two letters at the level of the written language, which are the hamza and the ta’. This research studies only the second of them; Therefore, we defined it as “The Voiceless Dental- alveolar common augment” (VDACA) to distinguish it from the glottal sound “Hamza”, first, middle, or last, in a noun or in a verb, in Arabic and its equivalent in the Semitic languages. What is meant by “VDACA” is the ta’ that is in addition to the root of the word at the morphological level: the word “voiceless” takes out the voiced sounds that we studied before, and the “dental- alveolar common augment” takes out the laryngeal sound of them, which is the “Hamza”: and the word “common” brings out the uncommon voiceless sounds, which are sīn, shīn, and hā’. The study is limited to the ta' alone among the Arabic sounds, and this title faced a problem in identifying it with the ta'. Because the designation of the ta is not the same in most Semitic languages. Hebrew, for example, has “tav” and is pronounced with the voiced fa (v), which is not in Arabic. It is called different names in other Semitic languages, such as “taw” or “tAu” in old Syriac. And so on. This goes hand in hand with the insistence on distance from the written level and the reference to the phonetic aspect in this study that is closely and closely linked to the morphological level. Therefore, the study is “morphophonemic”. What is meant by Semitic languages in this study are the following: Akkadian, Ugaritic, Hebrew, Syriac, Mandaean, Ge'ez, and Amharic. The problem of the study is the agreement or difference between these languages in the position of that augment, first, middle, or last. And in determining the distinguishing characteristics of each language from the other. As for the study methodology, it is determined by the comparative approach in Semitic languages, which is based on the descriptive approach for each language. The study is divided into an introduction, four sections, and a conclusion: Introduction: It included the subject of the study, its importance, motives, problem, methodology, and division. The first section: VDACA as a non-common phoneme. The second: VDACA as a common phoneme. The third: VDACA as a functional morpheme. The fourth section: Commentary and conclusion with the most important results. The positions of VDACA in Arabic and other Semitic languages, and in nouns and verbs, were limited to first, middle, and last. The research identified the individual addition, which is common with other augments, and the research proved that this augmentation is constant in all Semitic languages, but there are characteristics that distinguish each language from the other.

Keywords: voiceless -, dental- alveolar, augment, Arabic - semitic languages

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Authors: Madhumitha Rajasekaran

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Freedom is a short, powerful word we take for granted every day. It is hard to fully appreciate freedom when we have never had it snatched away from us. We get to choose our jobs, where we live, what we eat. If we are unhappy at work, we have the freedom to quit and find work elsewhere.

Keywords: human trafficking, standing for freedom, social work, social research

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Authors: S. Odabasi Cimer, A. Cimer

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Recently, the poor quality of education, low achieving students, low international exam performances and little or no effect of the education reforms on the teaching in the classrooms are the main problems of education discussed in Turkey. Research showed that the quality of an education system can not exceed the quality of its teachers and teaching. Therefore, in-service training (INSET) courses are important to improve teacher quality, thereby, the quality of education. However, according to the research conducted on the evaluation of the INSET courses in Turkey, they are not effective in improving the quality of teaching in the classroom. The main reason for this result is because INSET courses are conducted and delivered in limited time and presented theoretically, which does not meet the needs of teachers and as a result, the knowledge and skills taught are not used in the classrooms. Recently, developed countries have been using Critical Friends Groups (CFGs) successfully for the purpose of school-based training of teachers. CFGs are the learning groups which contain 6-10 teachers aimed at fostering their capacities to undertake instructional and personal improvement and schoolwide reform. CFGs have been recognized as a critical feature in school reform, improving teaching practice and improving student achievement. In addition, in the USA, teachers have named CFGs one of the most powerful professional development activities in which they have ever participated. Whereas, in Turkey, the concept is new. This study aimed to investigate the implications of application, evaluation, and promotion of CFGs which has the potential to contribute to teacher development and student learning in schools in Turkey. For this purpose, the study employed a qualitative approach and case study methodology to implement the model in high schools. The research was conducted in two schools and 13 teachers working in these schools participated. The study lasted two years and the data were collected through various data collection tools including interviews, meeting transcripts, questionnaires, portfolios, and diaries. The results of the study showed that CFGs contributed professional development of teachers and their students’ learning. It also contributed to a culture of collaborative work in schools. A number of barriers and challenges which prevent effective implementation were also determined.

Keywords: critical friends group, education reform, science learning, teacher education

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Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

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It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

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Authors: Shang-Hua Wu, Rong-Chi Chang, Horng–Twu Liaw

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Nowadays, competencies of e-learning project personnel are very important in assisting them in offering courses, serving students in an effective way, leveraging advantages, strengthen their relationships with potential students, etc. among e-learning platforms, MOOCs has recently attracted increasing focuses in distance education since it can be conducted for a large numbers of virtual learners. Nonetheless, since MOOCs is a relatively new e-learning platform, top concerns have been paid to what competencies are important for e-learning personnel to consider. Taking this need, this research aimed to carry out an in-depth exploration of competency requirements of MOOCs (e-learning) project personnel in Taiwan vocational schools. Data were collected through thorough literature reviews and discussions and competency analysis was carried out using Delphi technique questionnaires. The results show that that MOOCs (e-learning) project personnel’ professional competency lie in three main dimensions, among which ‘demand analysis competency’ (i.e., containing 10 major competences and 48 subordinate capabilities) is the most important competency, followed by ‘project management competency’ (i.e., comprising 6 major competences and 31 secondary capabilities), and finally ‘digital content production competency’ (i.e., including 12 major competences and 79 secondary capabilities). As such, in Taiwan context with different organizational scales and market sizes, the e-learning competency items and unique experience/ achievements throughout the promotion process obtained in this research will provide useful references for academic institutions in promoting e-learning.

Keywords: competency analysis, Delphi technique questionnaire, e-learning, massive open online courses

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Authors: M. Walmsley, S. Elmatarri, S. Mannion

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Introduction: Self-inflicted injury is a recognised cause of major trauma in adults and is an independent indicator of a reduced functional outcome compared to non-intentional major trauma. There is little literature available on the inpatient mental health (MH) management of this vulnerable group. A retrospective review was conducted of inpatient MH management of major trauma patients admitted to a UK regional Major Trauma Centre (MTC). Their outcomes were compared to all major trauma patients. This group of patients required multiple MH interventions whilst on the Major Trauma Ward (MTW) and a had worse functional outcome compared to non-intentional trauma. Method: The national TARN (Trauma Audit and Research Network) database was used to identify patients admitted to a regional MTC over a 2-year period from June 2018 to July 2020. Patients with an ISS (Injury Severity Score) of greater than 15 with a mechanism of either self-harm or high-risk behavior were included for further analysis. Inpatient medical notes were reviewed for MH interventions on the MTW. Further outcomes, including mortality, length of stay (LOS) and Glasgow Outcome Score (GOS) were compared with all major trauma patients for the same time period. Results: A total of 60 patients were identified in the time period and of those, 27 spent time on the MTW. A total of 23 (85%) had a prior MH diagnosis, with 11 (41%) under the care of secondary MH services. Adequate inpatient records for review were available for 24 patients. During their inpatient stay, 8 (33%) were reviewed on the ward by the inpatient MH team. There were 10 interventions required for 6 (25%) patients on the MTW including, sections under the Mental Health Act, transfer to specialist MH facility, pharmacological sedation and security being called to the MTW. When compared to all major trauma patients, those admitted due to self-harm or high-risk behavior had a statistically significantly higher ISS (31.43 vs 24.22, p=0.0001) and LOS (23.51d vs 16.06d, p=0.002). Functional outcomes using the GOS were reduced in this group of patients, GOS 5 (low disability) (51.66% vs. 61.01%) and they additionally had a higher level of mortality, GOS 1 (15.00% vs 11.67%). Discussion: Intentional self-harm is a recognised cause of major trauma in adults and this patient group sustains more severe injuries, requiring a longer hospital stay with worse outcomes compared to all major trauma patients. Inpatient MH interventions are required for a significant proportion of these patients and therefore, there needs to be a close relationship with MH services. There is limited available evidence for how this patient group is best managed as an inpatient to aid their recovery and further work is needed on how outcomes in this vulnerable group can be improved.

Keywords: adult major trauma, attempted suicide, self-inflicted major trauma, inpatient management

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Authors: Deborah L. Smith

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To review our program and determine the best redesign options, department members gathered feedback and input through focus groups, analysis of data, and a review of the current research to ensure that the changes proposed were not based solely on the state’s new professional standards. In designing course assignments and assessments, we listened to a variety of constituents, including students, other institutions of higher learning, MDE webinars, host teachers, literacy clinic personnel, and other disciplinary experts. As a result, we are designing a program that is more inclusive of a variety of field experiences for growth. We have determined ways to improve our program by connecting academic disciplinary knowledge, educational psychology, and community building both inside and outside the classroom for professional learning communities. The state’s release of new professional standards led my department members to question what is working and what needs improvement in our program. One aspect of our program that continues to be supported by research and data analysis is the function of supervised field experiences with meaningful feedback. We seek to expand in this area. Other data indicate that we have strengths in modeling a variety of approaches such as cooperative learning, discussions, literacy strategies, and workshops. In the new program, field assignments will be connected to multiple courses, and efforts to scaffold student learning to guide them toward best evidence-based practices will be continuous. Despite running a program that meets multiple sets of standards, there are areas of need that we directly address in our redesign proposal. Technology is ever-changing, so it’s inevitable that improving digital skills is a focus. In addition, scaffolding procedures for English Language Learners (ELL) or other students who struggle is imperative. Diversity, equity, and inclusion (DEI) has been an integral part of our curriculum, but the research indicates that more self-reflection and a deeper understanding of culturally relevant practices would help the program improve. Connections with professional learning communities will be expanded, as will leadership components, so that teacher candidates understand their role in changing the face of education. A pilot program will run in academic year 22/23, and additional data will be collected each semester through evaluations and continued program review.

Keywords: DEI, field experiences, program redesign, teacher preparation

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Authors: Z. Haddad, C. Abid, O. Rahli, O. Margeat, W. Dachraoui, A. Mataoui

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The present study aims to measure the volumetric mass density of NiPd-heptane nanofluids synthesized using a one-step method known as thermal decomposition of metal-surfactant complexes. The particle concentration is up to 7.55 g/l and the temperature range of the experiment is from 20°C to 50°C. The measured values were compared with the mixture theory and good agreement between the theoretical equation and measurement were obtained. Moreover, the available nanofluids volumetric mass density data in the literature is reviewed.

Keywords: NiPd nanoparticles, nanofluids, volumetric mass density, stability

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Authors: Maryam Parsian, Pelin Mutlu, Ufuk Gunduz

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Two-dimensional cell culture affords simplicity and low cost, but it has serious limitations; lacking cell-cell and cell-matrix interactions that are present in tissues. Cancer cells grown in 3D culture systems have distinct phenotypes of adhesion, growth, migration, invasion as well as profiles of gene and protein expression. These interactions cause the 3D-cultured cells to acquire morphological and cellular characteristics relevant to in vivo tumors. Palbociclib is a chemotherapeutic agent for the treatment of ER-positive and HER-negative metastatic breast cancer. Poly-amidoamine (PAMAM) dendrimer is a well-defined, special three-dimensional structure and has a multivalent surface and internal cavities that can play an essential role in drug delivery systems. In this study, palbociclib is loaded onto the magnetic PAMAM dendrimer. Hanging droplet method was used in order to form 3D spheroids. The possible toxic effects of both free drug and drug loaded nanoparticles were evaluated in 2D and 3D MCF-7, MD-MB-231 and SKBR-3 breast cancer cell culture models by performing MTT cell viability and Alamar Blue assays. MTT analysis was performed with six different doses from 1000 µg/ml to 25 µg/ml. Drug unloaded PAMAM dendrimer did not demonstrate significant toxicity on all breast cancer cell lines. The results showed that 3D spheroids are clearly less sensitive than 2D cell cultures to free palbociclib. Also, palbociclib loaded PAMAM dendrimers showed more toxic effect than free palbociclib in all cell lines at 2D and 3D cultures. The results suggest that the traditional cell culture method (2D) is insufficient for mimicking the actual tumor tissue. The response of the cancer cells to anticancer drugs is different in the 2D and 3D culture conditions. This study showed that breast cancer cells are more resistant to free palbociclib in 3D cultures than in 2D cultures. However, nanoparticle loaded drugs can be more cytotoxic when compared to free drug.

Keywords: 2D and 3D cell culture, breast cancer, palbociclibe, PAMAM magnetic nanoparticles

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are 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. 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 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

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

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Authors: James Freeman, Andry Rakotonirainy

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Train pedestrian collisions are common and are the most likely to result in severe injuries and fatalities when compared to other types of rail crossing accidents. However, there is limited research that has focused on understanding the reasons why some pedestrians’ break level crossings rules, which limits the development of effective countermeasures. As a result, this study undertook a deeper exploration into the origins of risky pedestrian behaviour through structured interviews. A total of 40 pedestrians who admitted to either intentionally breaking crossing rules or making crossing errors participated in an in-depth telephone interview. Qualitative analysis was undertaken via thematic analysis that revealed participants were more likely to report deliberately breaking rules (rather than make errors), particular after the train had passed the crossing as compared to before it arrives. Predominant reasons for such behaviours were identified to be: calculated risk taking, impatience, poor knowledge of rules and low likelihood of detection. The findings have direct implications for the development of effective countermeasures to improve crossing safety (and managing risk) such as increasing surveillance and transit officer presence, as well as installing appropriate barriers that either deter or incapacitate pedestrians from violating crossing rules. This paper will further outline the study findings in regards to the development of countermeasures as well as provide direction for future research efforts in this area.

Keywords: crossings, mistakes, risk, violations

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Authors: Yasser Sanad, Thu Trang Dao

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Introduction: Implementing the One Health (OH) approach requires an integrated, interdisciplinary, and cross-sectoral methodology. OH is a key tool for developing and implementing programs and projects and includes developing ambitious policies that consider the common needs and benefits of human, animal, plant, and ecosystem health. OH helps humanity readjust its path to environmentally friendly and impartial sustainability. As co-leader of the Global Health Security Agenda’s Zoonotic Disease Action Package, Vietnam pioneered a strong OH approach to effectively address early waves of the COVID-19 outbreak in-country. Context and Aim: The repeated surges in COVID-19 in Vietnam challenged the capabilities of the national system and disclosed the gaps in multi-sectoral coordination and resilience. To address this, FHI 360 advocated for the standardization of the OH platform by government actors to increase the resiliency of the system during and post COVID-19. Methods: FHI 360 coordinated technical resources to develop and implement evidence-based OH policies, promoting high-level policy dialogue between the Ministries of Health, Agriculture, and the Environment, and policy research to inform developed policies and frameworks. Through discussions, an OH-building Partnership (OHP) was formed, linking climate change, the environment, and human and animal health. Findings: The OHP Framework created a favorable policy environment within and between sectors, as well as between governments and international health security partners. It also promoted strategic dialogue, resource mobilization, policy advocacy, and integration of international systems with National Steering Committees to ensure accountability and emphasize national ownership. Innovative contribution to policy, practice and/or research: OHP was an effective evidence-based research-to-policy platform linking to the National One Health Strategic Plan (2021-2025). Collectively they serve as a national framework for the implementation and monitoring of OH activities. Through the adoption of policies and plans, the risk of zoonotic pathogens, environmental agent spillover, and antimicrobial resistance can be minimized through strengthening multi-sectoral OH collaboration for health security.

Keywords: one health, national policies, health security, COVID-19, Vietnam

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Authors: Aulanni’am Aulanni’am

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Incidence of Diabetes Mellitus (DM) progressively increasing it became a serious problem in Indonesia and it is a disease that government is priority to be addressed. The longer a person is suffering from diabetes the more likely to develop complications particularly diabetic patients who are not well maintained. Therefore, Incidence of Diabetes Mellitus needs to be done in the early diagnosis of pre-phase of the disease. In this pre-phase disease, already happening destruction of pancreatic beta cells and declining in beta cell function and the sign autoimmunity reactions associated with beta cell destruction. Type 1 DM is a multifactorial disease triggered by genetic and environmental factors, which leads to the destruction of pancreatic beta cells. Early marker of "beta cell autoreactivity" is the synthesis of autoantibodies against 65-kDa protein, which can be a molecule that can be detected early in the disease pathomechanism. The importance of early diagnosis of diabetic patients held in the phase of pre-disease is to determine the progression towards the onset of pancreatic beta cell destruction and take precautions. However, the price for this examination is very expensive ($ 150/ test), the anti-GAD65 abs examination cannot be carried out routinely in most or even in all laboratories in Indonesia. Therefore, production-based Rapid Test Recombinant Human Protein GAD65 with "Reverse Flow Immunchromatography Technique" in Indonesia is believed to reduce costs and improve the quality of care of patients with diabetes in Indonesia. Rapid Test Product innovation is very simple and suitable for screening and routine inspection of GAD65 autoantibodies. In the blood serum of patients with diabetes caused by autoimmunity, autoantibody-GAD65 is a major serologic marker to detect autoimmune reaction because their concentration level of stability.GAD65 autoantibodies can be found 10 years before clinical symptoms of diabetes. Early diagnosis is more focused to detect the presence autontibodi-GAD65 given specification and high sensitivity. Autoantibodies- GAD65 that circulates in the blood is a major indicator of the destruction of the islet cells of the pancreas. Results of research in collaboration with Biofarma has produced GAD65 autoantibodies based Rapid Test had conducted the soft launch of products and has been tested with the results of a sensitivity of 100 percent and a specificity between 90 and 96% compared with the gold standard (import product) which worked based on ELISA method.

Keywords: diabetes mellitus, GAD65 autoantibodies, rapid test, sensitivity, specificity

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Authors: Atiwat Khatpibunchai, Taweesak Kritjaroen

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A social enterprise is the innovative hybrid organizations where its ultimate goal is to generate revenue and use it as a fund to solve the social and environmental problem. Although the evidence shows the clear value of economic, social and environmental aspects, the limitations of most of the social enterprises are the expanding impact of social and environmental aspects through the normal market mechanism. This is because the major sources of revenues of social enterprises derive from the business advocates who merely wish to support society and environment by using products and services of social enterprises rather than expect the satisfaction and the distinctive advantage of products and services. Thus, social enterprises cannot reach the achievement as other businesses do. The relevant concepts from the literature review revealed that dynamic capability is the ability to sense, integrate and reconfigure internal resources and utilize external resources to adapt to changing environments, create innovation and achieve competitive advantage. The objective of this research is to study the influence of dynamic capability that affects competitive advantage and sustainable performance, as well as to determine important elements of dynamic capability. The researchers developed a conceptual model from the related concepts and theories of dynamic capability. A conceptual model will support and show the influence of dynamic capability on competitive advantage and sustainable performance of social enterprises. The 230 organizations in South-East Asia served as participants in this study. The results of the study were analyzed by the structural equation model (SEM) and it was indicated that research model is consistent with empirical research. The results also demonstrated that dynamic capability has a direct and indirect influence on competitive advantage and sustainable performance. Moreover, it can be summarized that dynamic capability consists of the five elements: 1) the ability to sense an opportunity; 2) the ability to seize an opportunity; 3) the ability to integrate resources; 4) the ability to absorb resources; 5) the ability to create innovation. The study recommends that related sectors can use this study as a guideline to support and promote social enterprises. The focus should be pointed to the important elements of dynamic capability that are the development of the ability to transform existing resources in the organization and the ability to seize opportunity from changing market.

Keywords: dynamic capability, social enterprise, sustainable competitive advantage, sustainable performance

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Authors: Saoussen Dhib, Chris M. Mannaerts, Zoubeida Bargaoui, Ben H. P. Maathuis, Petra Budde

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In this study, a new method to delineate rain areas in northern Tunisia is presented. The proposed approach is based on the blending of the geostationary Meteosat Second Generation (MSG) infrared channel (IR) with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). To blend this two products, we need to apply two main steps. Firstly, we have to identify the rainy pixels. This step is achieved based on a classification using MSG channel IR 10.8 and the water vapor WV 0.62, applying a threshold on the temperature difference of less than 11 Kelvin which is an approximation of the clouds that have a high likelihood of precipitation. The second step consists on fitting the relation between IR cloud top temperature with the TMI rain rates. The correlation coefficient of these two variables has a negative tendency, meaning that with decreasing temperature there is an increase in rainfall intensity. The fitting equation will be applied for the whole day of MSG 15 minutes interval images which will be summed. To validate this combined product, daily extreme rainfall events occurred during the period 2007-2009 were selected, using a threshold criterion for large rainfall depth (> 50 mm/day) occurring at least at one rainfall station. Inverse distance interpolation method was applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). The evaluation results of the estimated rainfall combining MSG and TMI was very encouraging where all the events were detected rainy and the correlation coefficients were much better than previous evaluated products over the study area such as MSGMPE and PERSIANN products. The combined product showed a better performance during wet season. We notice also an overestimation of the maximal estimated rain for many events.

Keywords: combination, extreme, rainfall, TMI-MSG, Tunisia

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Authors: Hiroki Kikuchi, Atsushi Fukuda, Hirokazu Akahane, Satoru Kobayakawa, Tuenjai Fukuda, Takeru Miyokawa

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According to WHO reports, fatalities by road traffic accidents in many countries of South-East Asia region especially Thailand and Malaysia are increasing year by year. In order to overcome these serious problems, both governments are focusing on road safety measures. In response, the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan and Japan International Cooperation Agency (JICA) have begun active support based on the experiences to reduce the number of fatalities in road accidents in Japan in the past. However, even if the successful road safety measures in Japan is adopted in South-East Asian countries, it is not sure whether it will work well or not. So, it is necessary to clarify the issues and systematize the process for the implementation of road safety measures in South-East Asia. On the basis of the above, this study examined the applicability of "information sharing traffic safety measure" which is one of the successful road safety measures in Japan to the social implementation of road safety measures in South-East Asian countries. The "Information sharing traffic safety measure" is carried out traffic safety measures by stakeholders such as residents, administration, and experts jointly. In this study, we extracted the issues of implementation of road safety measures under local context firstly. This is clarifying the particular issues with its implementation in South-East Asian cities. Secondly, we considered how to implement road safety measures for solving particular issues based on the method of "information sharing traffic safety measure". In the implementation method, the location of the occurrence of a dangerous event was extracted based on the “HIYARI-HATTO” data which were obtained from the residents. This is because it is considered that the implementation of the information sharing traffic safety measure focusing on the location where the dangerous event occurs leads to the reduction of traffic accidents. Also, the target locations for the implementation of measures differ for each city. In Penang, we targeted the intersections　in the downtown, while in Suphan Buri, we targeted mainly traffic control on the intercity highway. Finally, we proposed a method for implementing traffic safety measures. For Penang, we proposed a measure to improve the signal phase and showed the effect of the measure on the micro traffic simulation. For Suphan Buri, we proposed the suitable measures for the danger points extracted by collecting the “HIYARI-HATTO” data of residents to the administration. In conclusion, in order to successfully implement the road safety measure based on the "information sharing traffic safety measure", the process for social implementation of the road safety measures should be consistent and carried out repeatedly. In particular, by clarifying specific issues based on local context in South-East Asian countries, the stakeholders, not only such as government sectors but also local citizens can share information regarding road safety and select appropriate countermeasures. Finally, we could propose this approach to the administration that had the authority.

Keywords: information sharing road safety measure, social implementation, South-East Asia, HIYARI-HATTO

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Authors: Sila Uzkul, Ayse Dilek Ogreti̇r Ozceli̇k

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Sexual development, which starts from fertilization, gainssocial, cultural and psychological dimensions with birth and becomes a lifelongpart of human life. Inorderforchildrentogrowup as healthyindividuals, alldevelopmentalareasneedto be supportedcorrectly, but when it comestosexualdevelopmentandeducation, studiesshowthateducatorsandparentsareinsufficient in terms of information on this subject, andtheyareworried, inadequate In, In restless, In uncomfortableandexcited in In terms In of communication. With this research, it is aimedtoincreasetheknowledgelevel of the parents, theirpositiveattitudetowardssexualeducation, positivecommunicationduringsexualeducationandawareness of sexualabusebyprovidingsexualeducationtotheparents of childrenreceivingpre-schooleducation. The study group of this research, which was designed in quantitativeresearchtype, experimental design, and Solomon four-group model, will be composed of parents of childrenattendingpre-schooleducationinstitutions. In the preparation of the Preschool SexEducation Program to be applied to parents, primaryandsecondarydatasourceswill be used, literaturereviewandarchivescanningmethodswill be used. In the content of the program, theeight main topics (our body, sexuality, emotions, relationships, health, norms, reproductionandrights) thatthe World HealthOrganizationstatesshould be addressed in sexualeducation how toteachthesesubjectstotheirchildren, how toanswerquestionsfromthechild, childsexualdevelopmentandsexualabusetopicswill be included. Theparentsexualeducation program is plannedto be held online (byzoom) for about 45 minutesonce a weekfor 11 weeks. Data will be collectedusingtheSexualCommunicationScale, theSexualEducationAttitudeScale, the sexual Development Knowledge Level andtheAbuse Information/AttitudeScaleforParents. Demographic information of the the parents will be collectedwiththePersonal Information Form to be preparedbytheresearchers. Appropriatestatisticalmethodswill be used in theanalysis of thedata. Studyfindingswill be given in an oral presentation.

Keywords: preschool, sexual development, sexuality education, sexual communication, early childhood, parents' sex education

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