Search results for: electrical network frequency stability

Authors: Chapman Eze Nnadozie

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Cloud computing, a technology that is made possible through virtualization within networks represents a shift from the traditional ownership of infrastructure and other resources by distinct organization to a more scalable pattern in which computer resources are rented online to organizations on either as a pay-as-you-use basis or by subscription. In other words, cloud computing entails the renting of computing resources (such as storage space, memory, servers, applications, networks, etc.) by a third party to its clients on a pay-as-go basis. It is a new innovative technology that is globally embraced because of its renowned benefits, profound of which is its cost effectiveness on the part of organizations engaged with its services. In Nigeria, the services are provided either directly to companies mostly by the key IT players such as Microsoft, IBM, and Google; or in partnership with some other players such as Infoware, Descasio, and Sunnet. This action enables organizations to rent IT resources on a pay-as-you-go basis thereby salvaging them from wastages accruable on acquisition and maintenance of IT resources such as ownership of a separate data centre. This paper intends to appraise the challenges of cloud computing adoption in Nigeria, bearing in mind the country’s peculiarities’ in terms of infrastructural development. The methodologies used in this paper include the use of research questionnaires, formulated hypothesis, and the testing of the formulated hypothesis. The major findings of this paper include the fact that there are some addressable challenges to the adoption of cloud computing in Nigeria. Furthermore, the country will gain significantly if the challenges especially in the area of infrastructural development are well addressed. This is because the research established the fact that there are significant gains derivable by the adoption of cloud computing by organizations in Nigeria. However, these challenges can be overturned by concerted efforts in the part of government and other stakeholders.

Keywords: Cloud computing, data centre, infrastructure, IT resources, network, servers, virtualization.

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Authors: Nidal Hadadin

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This study investigated the effect of cross sectional geometry on sediment transport rate. The processes of sediment transport are generally associated to environmental management, such as pollution caused by the forming of suspended sediment in the channel network of a watershed and preserving physical habitats and native vegetations, and engineering applications, such as the influence of sediment transport on hydraulic structures and flood control design. Many equations have been proposed for computing the sediment transport, the influence of many variables on sediment transport has been understood; however, the effect of other variables still requires further research. For open channel flow, sediment transport capacity is recognized to be a function of friction slope, flow velocity, grain size, grain roughness and form roughness, the hydraulic radius of the bed section and the type and quantity of vegetation cover. The effect of cross sectional geometry of the channel on sediment transport is one of the variables that need additional investigation. The width-depth ratio (W/d) is a comparative indicator of the channel shape. The width is the total distance across the channel and the depth is the mean depth of the channel. The mean depth is best calculated as total cross-sectional area divided by the top width. Channels with high W/d ratios tend to be shallow and wide, while channels with low (W/d) ratios tend to be narrow and deep. In this study, the effects of the width-depth ratio on sediment transport was demonstrated theoretically by inserting the shape factor in sediment continuity equation and analytically by utilizing the field data sets for Yalobusha River. It was found by utilizing the two approaches as a width-depth ratio increases the sediment transport decreases.

Keywords: Sediment transport, shape factor, hydraulicgeometry, flow discharge, width depth ratio.

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: Deep learning, data mining, gender predication, MOOCs.

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Authors: Albana Hasimi, Edlira Tako, Partizan Malkaj, Elvin Çomo, Blerina Papajani, Mirela Ndrita, Ledjan Malaj

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Many endeavors have been exerted during the last years for developing new artificial polymeric membranes, which fulfill the demanded conditions for biomedical uses. One of the most tested polymers is Poly(vinyl alcohol) [PVA]. Our teams are based on the possibility of using PVA for personal protective equipment against COVID-19. In personal protective equipment, we explore the possibility of modifying the properties of the polymer by adding Montmorillonite [MMT]. Heat-treatment above the glass transition temperature is used to improve mechanical properties mainly by increasing the crystallinity of the polymer, which acts as a physical network. Temperature-Modulated Differential Scanning Calorimetry (TMDSC) measurements indicated that the presence of 0.5% MMT in PVA causes a higher Tg value and shaped peak of crystallinity. Decomposition is observed at two of the melting points of the crystals during heating 25-240 oC and overlap of the recrystallization ridges during cooling 240-25 oC. This is indicative of the presence of two types (quality or structure) of polymer crystals. On the other hand, some indication of improvement of the quality of the crystals by heat-treatment is given by the distinct non-reversing contribution to melting. Data on sorption and transport of water in PVA films: PVA pure and PVA/MMT matrix, modified by thermal treatment are presented. The membranes become more rigid as a result of the heat treatment and because of this the water uptake is significantly lower in membranes. That is indicated by analysis of the resulting water uptake kinetics. The presence of 0.5% w/w of MMT has no significant impact on the properties of PVA membranes. Water uptake kinetics deviate from Fick’s law due to slow relaxation of glassy polymer matrix for all types of membranes.

Keywords: Crystallinity, montmorillonite, nanocomposite, poly(vinyl alcohol).

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: Human machine interface, industrial internet of things, internet of things, optical character recognition, video analytic.

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Authors: Adewole Taiwo Adelabu

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The study investigated the factors militating the organization of intramural sports programs in secondary schools in Ekiti State, Nigeria. The purpose of the study was to identify the factors affecting the organization of sports in secondary schools and also to proffer possible solutions to these factors. The study employed the inferential statistics of chi-square (x2). Five research hypotheses were formulated. The population for the study was all the students in the government-owned secondary schools in Ekiti West Local Government of Ekiti State Nigeria. The sample for the study was 60 students in three schools within the local government selected through simple random sampling techniques. The instrument used for the study was a self-developed questionnaire by the researcher for data collection. The instrument was presented to experts and academicians in the field of Human Kinetics and Health Education for construct and content validation. A reliability test was conducted which involves 10 students who are not part of the study. The test-retest coefficient of 0.74 was obtained which attested to the fact that the instrument was reliable enough for the study. The validated questionnaire was administered to the students in their various schools by the researcher with the help of two research assistants; the questionnaires were filled and returned to the researcher immediately. The data collected were analyzed using the descriptive statistics of frequency count, percentage and mean to analyze demographic data in section A of the questionnaire, while inferential statistics of chi-square was used to test the hypotheses at 0.05 alpha level. The results of the study revealed that personnel, fund, schedule (time) were significant factors that affect the organization of intramural sport programs among students in secondary schools in Ekiti West Local Government Area of the State. The study also revealed that organization of intramural sports programs among students of secondary schools will improve and motivate students’ participation in sports beyond the local level. However, facilities and equipment is not a significant factor affecting the organization of intramural sports among secondary school students in Ekiti West Local Government Area.

Keywords: Challenge, militating, intramural sport, programs.

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Authors: A. Kospach, A. Mladek, M. Waltenberger, F. Schilling

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In this work, a coupled 1D/3D simulation approach for thermal protection and optimization of a trailer refrigeration power pack unit was developed. With the developed 1D/3D simulation approach thermal critical scenarios, such as summer, high-load scenarios are investigated. The 1D thermal model was built up consisting of the thermal network, which includes different point masses and associated heat transfers, the coolant and oil circuits, as well as the fan unit. The 3D computational fluid dynamics (CFD) model was developed to model the air flow through the power pack unit considering convective heat transfer effects. In the 1D thermal model the temperatures of the individual point masses were calculated, which served as input variables for the 3D CFD model. For the calculation of the point mass temperatures in the 1D thermal model, the convective heat transfer rates from the 3D CFD model were required as input variables. These two variables (point mass temperatures and convective heat transfer rates) were the main couple variables for the coupled 1D/3D simulation model. The coupled 1D/3D model was validated with measurements under normal operating conditions. Coupled simulations for summer high-load case were than performed and compared with a reference case under normal operation conditions. Hot temperature regions and components could be identified. Due to the detailed information about the flow field, temperatures and heat fluxes, it was possible to directly derive improvement suggestions for the cooling design of the transport refrigeration power pack unit.

Keywords: Coupled thermal simulation, thermal analysis, transport refrigeration unit, 3D computational fluid dynamics, 1D thermal modelling, thermal management systems.

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Authors: Adile Shaqiri, Arjeta Shaqiri Latifi

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Domestic violence, trafficking with human beings especially violence against children, is a worldwide problem. Hence, it remains one of the most widespread forms of violence in Kosovo and which often continues to be described as a "closed door issue". Recognition, acceptance and prioritization of cases of domestic violence definitely require a much greater awareness of individuals in institutions for the risks, consequences and costs that the lack of such a well-coordinated response brings to the country. Considering that children are the future and the wealth of the country, violence and neglect against them should be treated as carefully as possible. The purpose of this paper is to identify steps towards prevention of the domestic violence and trafficking with human beings, so that the reflection of the consequences and the psychological flow do not reflect to a large extent in society. In this study is described: How is the phenomenon of domestic violence related to trafficking in human beings? The methods used are: historical, comparative, qualitative. Data derived from the relevant institutions were presented, i.e., by the actors who are the first reactors as well as the policy makers. Although these phenomena are present in all countries of the world, Kosovo is no exception and therefore comparisons of the development of child abuse have been made with other countries in the region as well. Since Kosovo is a country in transition, a country with a relatively high level of education, low economic development, high unemployment, political instability, dysfunctional legal infrastructure, it can be concluded that the potential for the development of negative phenomena is present and inevitable. Thus, during the research, the stages of development of these phenomena are analyzed, determining the causes and consequences which come from abuse, neglect of children and the impact on trafficking in human beings. The Kosovar family (parental responsibility), culture and religion, social services, the dignity of the abused child, etc. were analyzed. The review was also done on the legislation, educational institutions (curricula), governmental and non-governmental institutions their responsibilities and cooperation towards combating child abuse and trafficking. It is worth noting that during the work on paper, recommendations and conclusions have been drawn where it is concluded that we need an environment with educational reforms, stability in the political environment, economic development, a review of social policies, greater awareness of society, more adequate information through media, so that information and awareness could penetrate even in the most remote places of Kosovo society.

Keywords: Awareness, education, information, society, violence.

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Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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The solution of the nonlinear dynamic equilibrium equations of base-isolated structures adopting a conventional monolithic solution approach, i.e. an implicit single-step time integration method employed with an iteration procedure, and the use of existing nonlinear analytical models, such as differential equation models, to simulate the dynamic behavior of seismic isolators can require a significant computational effort. In order to reduce numerical computations, a partitioned solution method and a one dimensional nonlinear analytical model are presented in this paper. A partitioned solution approach can be easily applied to base-isolated structures in which the base isolation system is much more flexible than the superstructure. Thus, in this work, the explicit conditionally stable central difference method is used to evaluate the base isolation system nonlinear response and the implicit unconditionally stable Newmark’s constant average acceleration method is adopted to predict the superstructure linear response with the benefit in avoiding iterations in each time step of a nonlinear dynamic analysis. The proposed mathematical model is able to simulate the dynamic behavior of seismic isolators without requiring the solution of a nonlinear differential equation, as in the case of widely used differential equation model. The proposed mixed explicit-implicit time integration method and nonlinear exponential model are adopted to analyze a three dimensional seismically isolated structure with a lead rubber bearing system subjected to earthquake excitation. The numerical results show the good accuracy and the significant computational efficiency of the proposed solution approach and analytical model compared to the conventional solution method and mathematical model adopted in this work. Furthermore, the low stiffness value of the base isolation system with lead rubber bearings allows to have a critical time step considerably larger than the imposed ground acceleration time step, thus avoiding stability problems in the proposed mixed method.

Keywords: Base-isolated structures, earthquake engineering, mixed time integration, nonlinear exponential model.

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Authors: Travis Morris

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The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: Emotive triggers, environmental security, natural language processing, propaganda analysis.

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Muhammad Arslan Usman, Muhammad Rehan Usman, Soo Young Shin

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Live video streaming is one of the most widely used service among end users, yet it is a big challenge for the network operators in terms of quality. The only way to provide excellent Quality of Experience (QoE) to the end users is continuous monitoring of live video streaming. For this purpose, there are several objective algorithms available that monitor the quality of the video in a live stream. Subjective tests play a very important role in fine tuning the results of objective algorithms. As human perception is considered to be the most reliable source for assessing the quality of a video stream subjective tests are conducted in order to develop more reliable objective algorithms. Temporal impairments in a live video stream can have a negative impact on the end users. In this paper we have conducted subjective evaluation tests on a set of video sequences containing temporal impairment known as frame freezing. Frame Freezing is considered as a transmission error as well as a hardware error which can result in loss of video frames on the reception side of a transmission system. In our subjective tests, we have performed tests on videos that contain a single freezing event and also for videos that contain multiple freezing events. We have recorded our subjective test results for all the videos in order to give a comparison on the available No Reference (NR) objective algorithms. Finally, we have shown the performance of no reference algorithms used for objective evaluation of videos and suggested the algorithm that works better. The outcome of this study shows the importance of QoE and its effect on human perception. The results for the subjective evaluation can serve the purpose for validating objective algorithms.

Keywords: Objective evaluation, subjective evaluation, quality of experience (QoE), video quality assessment (VQA).

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Authors: Sachin Kamble, Raghothama Anekal, Shivakumar Bhavi

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Thermal management of electronic components packaged inside an IP65 rated enclosure is of prime importance in industrial applications. Electrical enclosure protects the multiple board configurations such as inverter, power, controller board components, busbars, and various power dissipating components from harsh environments. Industrial environments often experience relatively warm ambient conditions, and the electronic components housed in the enclosure dissipate heat, due to which the enclosures and the components require thermal management as well as reduction of internal ambient temperatures. Design of Experiments based thermal simulation approach with MOSFET arrangement, Heat sink design, Enclosure Volume, Copper and Aluminum Spreader, Power density, and Printed Circuit Board (PCB) type were considered to optimize air temperature inside the IP65 enclosure to ensure conducive operating temperature for controller board and electronic components through the different modes of heat transfer viz. conduction, natural convection and radiation using Ansys ICEPAK. MOSFET’s with the parallel arrangement, IP65 enclosure molded heat sink with rectangular fins on both enclosures, specific enclosure volume to satisfy the power density, Copper spreader to conduct heat to the enclosure, optimized power density value and selecting Aluminum clad PCB which improves the heat transfer were the contributors towards achieving a conducive operating temperature inside the IP-65 rated Motor Inverter enclosure. A reduction of 52 ℃ was achieved in internal ambient temperature inside the IP65 enclosure between baseline and final design parameters, which met the operative temperature requirements of the electronic components inside the IP-65 rated Motor Inverter.

Keywords: Ansys ICEPAK, Aluminum Clad PCB, IP 65 enclosure, motor inverter, thermal simulation.

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Authors: Carolina Arriagada, Yasna Contreras

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Since mid-2000, the migratory flows of Latin American migrants to Chile have been increasing constantly. There are two reasons that would explain why Chile is presented as an attractive country for the migrants. On the one hand, traditional centres of migrants’ attraction such as the United States and Europe have begun to close their borders. On the other hand, Chile exhibits relative economic and political stability, which offers greater job opportunities and better standard of living when compared to the migrants’ origin country. At the same time, the neoliberal economic model of Chile, developed under an extractive production of the natural resources, has privatized the urban space. The market regulates the growth of the fragmented and segregated cities. Then, the vulnerable population, most of the time, is located in the periphery and in the marginal areas of the urban space. In this aspect, the migrants have begun to occupy those degraded and depressed areas of the city. The problem raised is that the increase of the social spatial segregation could be also attributed to the migrants´ occupation of the marginal urban places of the city. The aim of this investigation is to carry out an analysis of the migrants’ housing strategies, which are transforming the marginal areas of the city. The methodology focused on the urban experience of the migrants, through the observation of spatial practices, ways of living and networks configuration in order to transform the marginal territory. The techniques applied in this study are semi–structured interviews in-depth interviews. The study reveals that the migrants housing strategies for living in the marginal areas of the city are built on a paradox way. On the one hand, the migrants choose proximity to their place of origin, maintaining their identity and customs. On the other hand, the migrants choose proximity to their social and familiar places, generating sense of belonging. In conclusion, the migration as international displacements under a globalized economic model increasing socio spatial segregation in cities is evidenced, but the transformation of the marginal areas is a fundamental resource of their integration migratory process. The importance of this research is that it is everybody´s responsibility not only the right to live in a city without any discrimination but also to integrate the citizens within the social urban space of a city.

Keywords: Inhabit, migrations, social spatial segregation.

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Authors: Abeer Aljohani

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The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.

Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.

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Authors: G. Zuppardi, F. Romano

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Technology of thin film deposition is of interest in many engineering fields, from electronic manufacturing to corrosion protective coating. A typical deposition process, like that developed at the University of Eindhoven, considers the deposition of a thin, amorphous film of C:H or of Si:H on the substrate, using the Expanding Thermal arc Plasma technique. In this paper a computing procedure is proposed to simulate the flow field in a deposition chamber similar to that at the University of Eindhoven and a sensitivity analysis is carried out in terms of: precursor mass flow rate, electrical power, supplied to the torch and fluid-dynamic characteristics of the plasma jet, using different nozzles. To this purpose a deposition chamber similar in shape, dimensions and operating parameters to the above mentioned chamber is considered. Furthermore, a method is proposed for a very preliminary evaluation of the film thickness distribution on the substrate. The computing procedure relies on two codes working in tandem; the output from the first code is the input to the second one. The first code simulates the flow field in the torch, where Argon is ionized according to the Saha-s equation, and in the nozzle. The second code simulates the flow field in the chamber. Due to high rarefaction level, this is a (commercial) Direct Simulation Monte Carlo code. Gas is a mixture of 21 chemical species and 24 chemical reactions from Argon plasma and Acetylene are implemented in both codes. The effects of the above mentioned operating parameters are evaluated and discussed by 2-D maps and profiles of some important thermo-fluid-dynamic parameters, as per Mach number, velocity and temperature. Intensity, position and extension of the shock wave are evaluated and the influence of the above mentioned test conditions on the film thickness and uniformity of distribution are also evaluated.

Keywords: Deposition chamber, Direct Simulation Mote Carlo method (DSMC), Plasma chemistry, Rarefied gas dynamics.

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Authors: Birgül Şakar

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This study1 holds for the formation of international financial crisis and political factors for economic crisis in Turkey, are evaluated in chronological order. The international arena and relevant studies conducted in Turkey work in the literature are assessed. The main purpose of the study is to hold the linkage between the crises and political stability in Turkey in details, and to examine the position of Turkey in this regard. The introduction part follows the literature survey on the models explaining causes and results of the crises, the second part of the study. In the third part, the formations of the world financial crises are studied. The fourth part, financial crisis in Turkey in 1994, 2000, 2001 and 2008 are reviewed and their political reasons are analyzed. In the last part of the study the results and recommendations are held. Political administrations have laid the grounds for an economic crisis in Turkey. In this study, the emergence of an economic crisis in Turkey and the developments after the crisis are chronologically examined and an explanation is offered as to the cause and effect relationship between the political administration and economic equilibrium in the country. Economic crises can be characterized as follows: high prices of consumables, high interest rates, current account deficits, budget deficits, structural defects in government finance, rising inflation and fixed currency applications, rising government debt, declining savings rates and increased dependency on foreign capital stock. Entering into the conditions of crisis during a time when the exchange value of the country-s national currency was rising, speculative finance movements and shrinking of foreign currency reserves happened due to expectations for devaluation and because of foreign investors- resistance to financing national debt, and a financial risk occurs. During the February 2001 crisis and immediately following, devaluation and reduction of value occurred in Turkey-s stock market. While changing over to the system of floating exchange rates in the midst of this crisis, the effects of the crisis on the real economy are discussed in this study. Administered politics include financial reforms, such as the rearrangement of banking systems. These reforms followed with the provision of foreign financial support. There have been winners and losers in the imbalance of income distribution, which has recently become more evident in Turkey-s fragile economy.

Keywords: Economics, marketing crisis, financial reforms, political economy

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

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Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: Forest risk, GIS, remote sensing, Goaso.

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Authors: Vinti Davar

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Background: Worldwide, at least 2.8 million people die each year as a result of being overweight or obese, and 35.8 million (2.3%) of global DALYs are caused by overweight or obesity. Obesity is acknowledged as one of the burning public health problems reducing life expectancy and quality of life. The body composition analysis of the university population is essential in assessing the nutritional status, as well as the risk of developing diseases associated with abnormal body fat content so as to make nutritional recommendations. Objectives: The main aim was to determine the prevalence of obesity and overweight in University students using Anthropometric analysis and BIA methods. Material and Methods: In this cross-sectional study, 283 university students participated. The body composition analysis was undertaken by using mainly: i) Anthropometric Measurement: Height, Weight, BMI, waist circumference, hip circumference and skin fold thickness, ii) Bio-electrical impedance was used for analysis of body fat mass, fat percent and visceral fat which was measured by Tanita SC-330P Professional Body Composition Analyzer. The data so collected were compiled in MS Excel and analyzed for males and females using SPSS 16. Results and Discussion: The mean age of the male (n= 153) studied subjects was 25.37 ±2.39 years and females (n=130) was 22.53 ±2.31. The data of BIA revealed very high mean fat per cent of the female subjects i.e. 30.3±6.5 per cent whereas mean fat per cent of the male subjects was 15.60±6.02 per cent indicating a normal body fat range. The findings showed high visceral fat of both males (12.92±3.02) and females (16.86±4.98). BMI, BF% and WHR were higher among females, and BMI was higher among males. The most evident correlation was verified between BF% and WHR for female students (r=0.902; p<0.001). The correlation of BFM and BF% with thickness of triceps, sub scapular and abdominal skin folds and BMI was significant (P<0.001). Conclusion: The studied data made it obvious that there is a need to initiate lifestyle changing strategies especially for adult females and encourage them to improve their dietary intake to prevent incidence of noncommunicable diseases due to obesity and high fat percentage.

Keywords: Anthropometry, bioelectrical impedance, body fat percentage, obesity.

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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Authors: M. Izzat Md. Nor, N. Jaffar, N. Zaitulakma Md. Zain, N. Izyanti Mohd Suppian, S. Balakrishnan, G. Kandavello

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During the Coronavirus (COVID-19) pandemic, Malaysia has been focusing on building herd immunity by introducing vaccination programs into the community. Hospital Standard Operating Procedures (SOP) were developed to prevent inpatient transmission. In this study, we focus on the positivity rate of inpatient Person Under Surveillance (PUS) becoming COVID-19 positive and compare this to the national rate in order to see the outcomes of the patient who becomes COVID-19 positive in relation to their vaccination status. This is a retrospective observational study carried out from 1 January until 30 March 2022 in Institut Jantung Negara (IJN). There were 5,255 patients admitted during the time of this study. Pre-admission Polymerase Chain Reaction (PCR) swab was done for all patients. Patients with positive PCR on pre-admission screening were excluded. The patients who had exposure to COVID-19-positive staff or patients during hospitalization were defined as PUS and were quarantined and monitored for potential COVID-19 infection. Their frequency and risk of exposure (WHO definition) were recorded. On the final day of quarantine, a second PCR swab was performed on PUS patients who exhibit clinical deterioration, whether or not they exhibit COVID-19 symptoms. The severity of COVID-19 infection was defined as category 1-5A. All patients' vaccination status was recorded, and they were divided into three groups: fully immunised, partially immunised, and unvaccinated. We analysed the positivity rate of PUS patients becoming COVID-positive, outcomes, and correlation with the vaccination status. The ratio of positive inpatient PUS to the total inpatient PUS is 492; only 13 became positive, giving a positivity rate of 2.6%. Eight (62%) had multiple exposures. The majority, 8/13(72.7%), had a high-risk exposure, and the remaining 5 had medium-risk exposure. Four (30.8%) were boosted, 7(53.8%) were fully vaccinated, and 2(15.4%) were partial/unvaccinated. Eight patients were in categories 1-2, whilst 38% were in categories 3-5. Vaccination status did not correlate with COVID-19 Category (P = 0.641). One (7.7%) patient died due to COVID-19 complications and sepsis. Within the first quarter of 2022, our institution's positivity rate (2.6%) is significantly lower than the country's (14.4%). High-risk exposure and multiple exposures to positive COVID-19 cases increased the risk of PUS becoming COVID-19 positive despite their underlying vaccination status.

Keywords: COVID-19, boosted, high risk, Malaysia, quarantine, vaccination status.

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Authors: Langroudi B., Salehi E., Keshani S., Baghersad M.

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Transportation is of great importance in the current life of human beings. The transportation system plays many roles, from economical development to after-catastrophe aids such as rescue operation in the first hours and days after an earthquake. In after earthquakes response phase, transportation system acts as a basis for ground operations including rescue and relief operation, food providing for victims and etc. It is obvious that partial or complete obstruction of this system results in the stop of these operations. Bridges are one of the most important elements of transportation network. Failure of a bridge, in the most optimistic case, cuts the relation between two regions and in more developed countries, cuts the relation of numerous regions. In this paper, to evaluate the vulnerability and estimate the damage level of Tehran bridges, HAZUS method, developed by Federal Emergency Management Agency (FEMA) with the aid of National Institute of Building Science (NIBS), is used for the first time in Iran. In this method, to evaluate the collapse probability, fragility curves are used. Iran is located on seismic belt and thus, it is vulnerable to earthquakes. Thus, the study of the probability of bridge collapses, as an important part of transportation system, during earthquakes is of great importance. The purpose of this study is to provide fragility curves for Gisha Bridge, one of the longest steel bridges in Tehran, as an important lifeline element. Besides, the damage probability for this bridge during a specific earthquake, introduced as scenario earthquakes, is calculated. The fragility curves show that for the considered scenario, the probability of occurrence of complete collapse for the bridge is 8.6%.

Keywords: Bridge, Damage evaluation, Fragility curve, Lifelines, Seismic vulnerability.

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Authors: Jeries Khoury

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The use of legendary, folkloric and religious symbols is one of the most important phenomena in modern Arabic poetry. Interestingly enough, most of the modern Arabic poetry’s pioneers were so fascinated by the biblical symbols and they managed to use many modern techniques to make these symbols adequate for their personal life from one side and fit to their Islamic beliefs from the other. One of the most famous poets to do so was al-Sayya:b. The way he employed one of these symbols ‘job’, the new features he adds to this character and the link between this character and his personal life will be discussed in this study. Besides, the study will examine the influence of al-Sayya:b on another modern poet Saadi Yusuf, who, following al-Sayya:b, used the character of Job in a special way, by mixing its features with al-Sayya:b’s personal features and in this way creating a new mixed character. A semantic, cultural and comparative analysis of the poems written by al-Sayya:b himself and the other poets who evoked the mixed image of al-Sayya:b-Job, can reveal the changes Arab poets made to the original biblical figure of Job to bring it closer to Islamic culture. The paper will make an intensive use of intertextuality idioms in order to shed light on the network of relations between three kinds of texts (indeed three ‘palimpsests’: 1- biblical- the primary text; 2- poetic- al-Syya:b’s secondary version; 3- re-poetic- Sa’di Yusuf’s tertiary version). The bottom line in this paper is that that al-Sayya:b was directly influenced by the dramatic biblical story of Job more than the brief Quranic version of the story. In fact, the ‘new’ character of Job designed by al-Sayya:b himself differs from the original one in many aspects that we can safely say it is the Sayyabian-Job that cannot be found in the poems of any other poets, unless they are evoking the own tragedy of al-Sayya:b himself, like what Saadi Yusuf did.

Keywords: Arabic poetry, intertextuality, job, meter, modernism, symbolism.

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Authors: W. Thongwat, B. Terakulsatit

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The study area is Kham Sakaesaeng District in Nakhon Ratchasima Province, the south section of Northeastern Thailand, located in the Lower Khorat-Ubol Basin. This region is the one of saline soil area, located in a dry plateau and regularly experience standing with periods of floods and alternating with periods of drought. Especially, the drought in the summer season causes the major saline soil and saline water problems of this region. The general cause of dry land salting resulted from salting on irrigated land, and an excess of water leading to the rising water table in the aquifer. The purpose of this study is to determine the relationship of physical and chemical properties between the soil and groundwater. The soil and groundwater samples were collected in both rainy and summer seasons. The content of pH, electrical conductivity (EC), total dissolved solids (TDS), chloride and salinity were investigated. The experimental result of soil and groundwater samples show the slightly pH less than 7, EC (186 to 8,156 us/cm and 960 to 10,712 us/cm), TDS (93 to 3,940 ppm and 480 to 5,356 ppm), chloride content (45.58 to 4,177,015 mg/l and 227.90 to 9,216,736 mg/l), and salinity (0.07 to 4.82 ppt and 0.24 to 14.46 ppt) in the rainy and summer seasons, respectively. The distribution of chloride content and salinity content were interpolated and displayed as a map by using ArcMap 10.3 program, according to the season. The result of saline soil and brined groundwater in the study area were related to the low-lying topography, drought area, and salt-source exposure. Especially, the Rock Salt Member of Maha Sarakham Formation was exposed or lies near the ground surface in this study area. During the rainy season, salt was eroded or weathered from the salt-source rock formation and transported by surface flow or leached into the groundwater. In the dry season, the ground surface is dry enough resulting salt precipitates from the brined surface water or rises from the brined groundwater influencing the increasing content of chloride and salinity in the ground surface and groundwater.

Keywords: Environmental geology, soil salinity, geochemistry, groundwater hydrology.

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Authors: Ireneusz Majsterek, Anna Merecz, Agnieszka Sliwinska, Marcin Kosmalski, Jacek Kasznicki, Jozef Drzewoski

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Oxidative stress is considered to be the cause for onset and the progression of type 2 diabetes mellitus (T2DM) and complications including neuropathy. It is a deleterious process that can be an important mediator of damage to cell structures: protein, lipids and DNA. Data suggest that in patients with diabetes and diabetic neuropathy DNA repair is impaired, which prevents effective removal of lesions. Objective: The aim of our study was to evaluate the association of the hOGG1 (326 Ser/Cys) and XRCC1 (194 Arg/Trp, 399 Arg/Gln) gene polymorphisms whose protein is involved in the BER pathway with DNA repair efficiency in patients with diabetes type 2 and diabetic neuropathy compared to the healthy subjects. Genotypes were determined by PCR-RFLP analysis in 385 subjects, including 117 with type 2 diabetes, 56 with diabetic neuropathy and 212 with normal glucose metabolism. The polymorphisms studied include codon 326 of hOGG1 and 194, 399 of XRCC1 in the base excision repair (BER) genes. Comet assay was carried out using peripheral blood lymphocytes from the patients and controls. This test enabled the evaluation of DNA damage in cells exposed to hydrogen peroxide alone and in the combination with the endonuclease III (Nth). The results of the analysis of polymorphism were statistically examination by calculating the odds ratio (OR) and their 95% confidence intervals (95% CI) using the ¤ç2-tests. Our data indicate that patients with diabetes mellitus type 2 (including those with neuropathy) had higher frequencies of the XRCC1 399Arg/Gln polymorphism in homozygote (GG) (OR: 1.85 [95% CI: 1.07-3.22], P=0.3) and also increased frequency of 399Gln (G) allele (OR: 1.38 [95% CI: 1.03-1.83], P=0.3). No relation to other polymorphisms with increased risk of diabetes or diabetic neuropathy. In T2DM patients complicated by neuropathy, there was less efficient repair of oxidative DNA damage induced by hydrogen peroxide in both the presence and absence of the Nth enzyme. The results of our study suggest that the XRCC1 399 Arg/Gln polymorphism is a significant risk factor of T2DM in Polish population. Obtained data suggest a decreased efficiency of DNA repair in cells from patients with diabetes and neuropathy may be associated with oxidative stress. Additionally, patients with neuropathy are characterized by even greater sensitivity to oxidative damage than patients with diabetes, which suggests participation of free radicals in the pathogenesis of neuropathy.

Keywords: Diabetic neuropathy, oxidative stress, gene polymorphisms, oxidative DNA damage.

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Authors: M. Belén Prendes-Gero, Celestino González-Nicieza, M. Inmaculada Alvarez-Fernández

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Roof collapse is one of the problems with a higher frequency in most of the mines of all countries, even now. There are many reasons that may cause the roof to collapse, namely the mine stress activities in the mining process, the lack of vigilance and carelessness or the complexity of the geological structure and irregular operations. This work is the result of the analysis of one accident produced in the “Mary” coal exploitation located in northern Spain. In this accident, the roof of a crossroad of excavated galleries to exploit the “Morena” Layer, 700 m deep, collapsed. In the paper, the work done by the forensic team to determine the causes of the incident, its conclusions and recommendations are collected. Initially, the available documentation (geology, geotechnics, mining, etc.) and accident area were reviewed. After that, laboratory and on-site tests were carried out to characterize the behaviour of the rock materials and the support used (metal frames and shotcrete). With this information, different hypotheses of failure were simulated to find the one that best fits reality. For this work, the software of finite differences in three dimensions, FLAC 3D, was employed. The results of the study confirmed that the detachment was originated as a consequence of one sliding in the layer wall, due to the large roof span present in the place of the accident, and probably triggered as a consequence of the existence of a protection pillar insufficient. The results allowed to establish some corrective measures avoiding future risks. For example, the dimensions of the protection zones that must be remained unexploited and their interaction with the crossing areas between galleries, or the use of more adequate supports for these conditions, in which the significant deformations may discourage the use of rigid supports such as shotcrete. At last, a grid of seismic control was proposed as a predictive system. Its efficiency was tested along the investigation period employing three control equipment that detected new incidents (although smaller) in other similar areas of the mine. These new incidents show that the use of explosives produces vibrations which are a new risk factor to analyse in a next future.

Keywords: Forensic analysis, hypothesis modelling, roof failure, seismic monitoring.

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Authors: Luedech Girdwichai, Witthaya Mekhum

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This research intended to develop the model of community management for sustainable utilization by investigating on 2 groups of population, the family heads and the community management team. The population of the former group consisted of family heads from 511 families in 12 areas to complete the questionnaires which were returned at 479 sets. The latter group consisted of the community management team of 12 areas with 1 representative from each area to give the interview. The questionnaires for the family heads consisted of 2 main parts; general information such as occupations, etc. in the form of checklist. The second part dealt with the data on self reliance community development based on 4P Framework, i.e., People (human resource) development, Place (area) development, Product (economic and income source) development, and Plan (community plan) development in the form of rating scales. Data in the 1^st part were calculated to find frequency and percentage while those in the 2^nd part were analyzed to find arithmetic mean and SD. Data from the 2^nd group of population or the community management team were derived from focus group to find factors influencing successful management together with the in depth interview which were analyzed by descriptive statistics. The results showed that 479 family heads reported that the aspect on the implementation of community plan to self reliance community activities based on Sufficient Economy Philosophy and the 4P was at the average of 3.28 or moderate level. When considering in details, it was found that the 1^st aspect was on the area development with the mean of 3.71 or high level followed by human resource development with the mean of 3.44 or moderate level, then, economic and source of income development with the mean of 3.09 or moderate level. The last aspect was community plan development with the mean of 2.89. The results from the small group discussion revealed some factors and guidelines for successful community management as follows: 1) on the People (human resource) development aspect, there was a project to support and develop community leaders. 2) On the aspect of Place (area) development, there was a development on conservative tourism areas. 3) On the aspect of Product (economic and source of income) development, the community leaders promoted the setting of occupational group, saving group, and product processing group. 4) On the aspect of Plan (community plan) development, there was a prioritization through public hearing.

Keywords: Model of community management, sustainable utilization.

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Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: Internet of Things, IEEE 802.15.4, security cost evaluation, wireless sensor network, energy consumption.

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: Big data, bus headway prediction, machine learning, public transportation.

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: Lexicon of disasters, modelling, Petri nets, text annotation, social disasters.

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