Search results for: correction factors for axisymmetric models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16935

Search results for: correction factors for axisymmetric models

13245 Fuzzy Neuro Approach for Integrated Water Management System

Authors: Stuti Modi, Aditi Kambli

Abstract:

This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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13244 Trust: The Enabler of Knowledge-Sharing Culture in an Informal Setting

Authors: Emmanuel Ukpe, S. M. F. D. Syed Mustapha

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Trust in an organization has been perceived as one of the key factors behind knowledge sharing, mainly in an unstructured work environment. In an informal working environment, to instill trust among individuals is a challenge and even more in the virtual environment. The study has contributed in developing the framework for building trust in an unstructured organization in performing knowledge sharing in a virtual environment. The artifact called KAPE (Knowledge Acquisition, Processing, and Exchange) was developed for knowledge sharing for the informal organization where the framework was incorporated. It applies to Cassava farmers to facilitate knowledge sharing using web-based platform. A survey was conducted; data were collected from 382 farmers from 21 farm communities. Multiple regression technique, Cronbach’s Alpha reliability test; Tukey’s Honestly significant difference (HSD) analysis; one way Analysis of Variance (ANOVA), and all trust acceptable measures (TAM) were used to test the hypothesis and to determine noteworthy relationships. The results show a significant difference when there is a trust in knowledge sharing between farmers, the ones who have high in trust acceptable factors found in the model (M = 3.66 SD = .93) and the ones who have low on trust acceptable factors (M = 2.08 SD = .28), (t (48) = 5.69, p = .00). Furthermore, when applying Cognitive Expectancy Theory, the farmers with cognitive-consonance show higher level of trust and satisfaction with knowledge and information from KAPE, as compared with a low level of cognitive-dissonance. These results imply that the adopted trust model KAPE positively improved knowledge sharing activities in an informal environment amongst rural farmers.

Keywords: trust, knowledge, sharing, knowledge acquisition, processing and exchange, KAPE

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13243 An Insight into the Conformational Dynamics of Glycan through Molecular Dynamics Simulation

Authors: K. Veluraja

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Glycan of glycolipids and glycoproteins is playing a significant role in living systems particularly in molecular recognition processes. Molecular recognition processes are attributed to their occurrence on the surface of the cell, sequential arrangement and type of sugar molecules present in the oligosaccharide structure and glyosidic linkage diversity (glycoinformatics) and conformational diversity (glycoconformatics). Molecular Dynamics Simulation study is a theoretical-cum-computational tool successfully utilized to establish glycoconformatics of glycan. The study on various oligosaccharides of glycan clearly indicates that oligosaccharides do exist in multiple conformational states and these conformational states arise due to the flexibility associated with a glycosidic torsional angle (φ,ψ) . As an example: a single disaccharide structure NeuNacα(2-3) Gal exists in three different conformational states due to the differences in the preferential value of glycosidic torsional angles (φ,ψ). Hence establishing three dimensional structural and conformational models for glycan (cartesian coordinates of every individual atoms of an oligosaccharide structure in a preferred conformation) is quite crucial to understand various molecular recognition processes such as glycan-toxin interaction and glycan-virus interaction. The gycoconformatics models obtained for various glycan through Molecular Dynamics Simulation stored in our 3DSDSCAR (3DSDSCAR.ORG) a public domain database and its utility value in understanding the molecular recognition processes and in drug design venture will be discussed.

Keywords: glycan, glycoconformatics, molecular dynamics simulation, oligosaccharide

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13242 Computational Linguistic Implications of Gender Bias: Machines Reflect Misogyny in Society

Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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13241 Continuous Differential Evolution Based Parameter Estimation Framework for Signal Models

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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13240 Characterization of 2,4,6-Trinitrotoluene (Tnt)-Metabolizing Bacillus Cereus Sp TUHP2 Isolated from TNT-Polluted Soils in the Vellore District, Tamilnadu, India

Authors: S. Hannah Elizabeth, A. Panneerselvam

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Objective: The main objective was to evaluate the degradative properties of Bacillus cereus sp TUHP2 isolated from TNT-Polluted soils in the Vellore District, Tamil Nadu, India. Methods: Among the 3 bacterial genera isolated from different soil samples, one potent TNT degrading strain Bacillus cereus sp TUHP2 was identified. The morphological, physiological and the biochemical properties of the strain Bacillus cereus sp TUHP2 was confirmed by conventional methods and genotypic characterization was carried out using 16S r-DNA partial gene amplification and sequencing. The broken down by products of DNT in the extract was determined by Gas Chromatogram- Mass spectrometry (GC-MS). Supernatant samples from the broth studied at 24 h interval were analyzed by HPLC analysis and the effect on various nutritional and environmental factors were analysed and optimized for the isolate. Results: Out of three isolates one strain TUHP2 were found to have potent efficiency to degrade TNT and revealed the genus Bacillus. 16S rDNA gene sequence analysis showed highest homology (98%) with Bacillus cereus and was assigned as Bacillus cereus sp TUHP2. Based on the energy of the predicted models, the secondary structure predicted by MFE showed the more stable structure with a minimum energy. Products of TNT Transformation showed colour change in the medium during cultivation. TNT derivates such as 2HADNT and 4HADNT were detected by HPLC chromatogram and 2ADNT, 4ADNT by GC/MS analysis. Conclusion: Hence this study presents the clear evidence for the biodegradation process of TNT by strain Bacillus cereus sp TUHP2.

Keywords: bioremediation, biodegradation, biotransformation, sequencing

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13239 Checking Energy Efficiency by Simulation Tools: The Case of Algerian Ksourian Models

Authors: Khadidja Rahmani, Nahla Bouaziz

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Algeria is known for its rich heritage. It owns an immense historical heritage with a universal reputation. Unfortunately, this wealth is withered because of abundance. This research focuses on the Ksourian model, which constitutes a large portion of this wealth. In fact, the Ksourian model is not just a witness to a great part of history or a vernacular culture, but also it includes a panoply of assets in terms of energetic efficiency. In this context, the purpose of our work is to evaluate the performance of the old techniques which are derived from the Ksourian model , and that using the simulation tools. The proposed method is decomposed in two steps; the first consists of isolate and reintroduce each device into a basic model, then run a simulation series on acquired models. And this in order to test the contribution of each of these dialectal processes. In another scale of development, the second step consists of aggregating all these processes in an aboriginal model, then we restart the simulation, to see what it will give this mosaic on the environmental and energetic plan .The model chosen for this study is one of the ksar units of Knadsa city of Bechar (Algeria). This study does not only show the ingenuity of our ancestors in their know-how, and their adapting power to the aridity of the climate, but also proves that their conceptions subscribe in the current concerns of energy efficiency, and respond to the requirements of sustainable development.

Keywords: dialectal processes, energy efficiency, evaluation, Ksourian model, simulation tools

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13238 Prevalence of Risk Factors of the Female Athlete Triad Among Young Elite Athletes of the World

Authors: Muhammad Saleem

Abstract:

Background: Inattentive food choices and engagement in excessive physical activities by male athletes can potentially lead to adverse health consequences. Objective: The aim was to ascertain the occurrence of risk factors associated with the Male Athlete Triad among young elite athletes in Pakistan. Methodology: In 2018, a cross-sectional study based on questionnaires was conducted at the Pakistan Sports Board. The study aimed to explore the risk factors related to the Male Athlete Triad in young elite athletes who were part of national training camps in major metropolitan areas. The study included proficient male elite athletes aged 18 to 25 years, capable of understanding the English questionnaire. The athletes completed a survey encompassing aspects like demographic information, educational background, Body Mass Index (BMI), sports involvement, and hours of participation. Additionally, they filled out the Eating Attitude Test-26 (EAT-26) and questionnaires assessing risks of amenorrhea and low bone mineral density. The prevalence of risk factors for each of the three components was individually evaluated. The collected data underwent analysis using SPSS-20, with descriptive statistics being applied. Results: The study comprised a sample of 90 elite athletes (mean age: 23.57 ± 2.37 years, mean BMI: 21.97 ± 1.90) engaged in various sports. The EAT-26 results indicated that 50% of athletes were at risk of developing an eating disorder. Moreover, 83.3% exhibited disordered eating behaviors that necessitated referral. Risks for amenorrhea were observed in 15% of the participants, and regarding low bone mineral density, notable risks were absent except for the consumption of caffeinated beverages, which was noted in 51.7% of participants. Conclusion: The study identified a significant prevalence of disordered eating risk among male elite athletes in Pakistan. However, the risks associated with amenorrhea and low bone mineral density were not a major concern in this particular group.

Keywords: Pakistan, osteoporosis, female athlete triad, bone mineral density, athlete, amenorrhea, eating disorders

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13237 Disaggregation the Daily Rainfall Dataset into Sub-Daily Resolution in the Temperate Oceanic Climate Region

Authors: Mohammad Bakhshi, Firas Al Janabi

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High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data.

Keywords: DiMoN Tool, disaggregation, exceedance probability, Kolmogorov-Smirnov test, rainfall

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13236 Predisposition of Small Scale Businesses in Fagge, Kano State, Nigeria, Towards Profit and Loss Sharing Mode of Finance

Authors: Farida, M. Shehu, Shehu U. R. Aliyu

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Access to finance has been recognized in the literature as one of the major impediments confronting small scale businesses (SSBs). This largely arises due to high lending rate, religious inclinations, collateral, etc. Islamic mode finance operates under Profit and Loss Sharing (PLS) arrangement between a borrower (business owner) and a lender (Islamic bank). This paper empirically assesses the determinants of predisposition of small scale business operators in Fagge local government area, Kano State, Nigeria, towards the PLS. Cross-sectional data from a sample of 291 small scale business operators was analyzed using logit and probit regression models. Empirical results reveal that while awareness and religion inclination positively drive interest towards the PLS, lending rate and collateral work against it. The paper, therefore, strongly recommends more advocacy campaigns and setting up of more Islamic banks in the country to cater for the financing and religious needs of SSBs in the study area.

Keywords: Islamic finance, logit and probit models, profit and loss sharing small scale businesses, finance, commerce

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13235 Identification of Switched Reluctance Motor Parameters Using Exponential Swept-Sine Signal

Authors: Abdelmalek Ouannou, Adil Brouri, Laila Kadi, Tarik

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Switched reluctance motor (SRM) has a major interest in a large domain as in electric vehicle driving because of its wide range of speed operation, high performances, low cost, and robustness to run under degraded conditions. The purpose of the paper is to develop a new analytical approach for modeling SRM parameters. Then, an identification scheme is proposed to obtain the SRM parameters. Since the SRM is featured by a highly nonlinear behavior, modeling these devices is difficult. Then, it is convenient to develop an accurate model describing the SRM. Furthermore, it is always operated in the magnetically saturated mode to maximize the energy transfer. Accordingly, it is shown that the SRM can be accurately described by a generalized polynomial Hammerstein model, i.e., the parallel connection of several Hammerstein models having polynomial nonlinearity. Presently an analytical identification method is developed using a chirp excitation signal. Afterward, the parameters of the obtained model have been determined using Finite Element Method analysis. Finally, in order to show the effectiveness of the proposed method, a comparison between the true and estimate models has been performed. The obtained results show that the output responses are very close.

Keywords: switched reluctance motor, swept-sine signal, generalized Hammerstein model, nonlinear system

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13234 A Descriptive Study of ‎Translated Texts from Socio-Cultural Aspects ‎through Polysystem Theory and Patronage Framework

Authors: Reza Nozadheravi, Masoud Hasanzade Novin

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Those techniques of translation which are engaged with short textual segments and mostly are prescriptive can be considered as micro level elements. Macro levels, however, refer to those translation strategies and those external factors that affect the translator’s decisions and have descriptive nature. What was scrutinized in details in the paper reveals the ‎macro-elements which are crucial in canonized translated texts, moreover, different aspects ‎of the patronage, which can be considered as the important factors from having the texts ‎chosen to the final translation products, have been observed in translated texts of Najaf ‎Darya-Bandarie, the well-known Iranian Translator. What is probed in this paper ‎reveals that marco-elements along with the linguistic aspects of the texts, micro-elements, ‎are considered as the significant aspects in translation process and even final translated ‎texts.

Keywords: canolized translated texts‎, culture‎, macro-elements‎, patronage

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13233 Convergence and Stability in Federated Learning with Adaptive Differential Privacy Preservation

Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

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13232 Lifelong Distance Learning and Skills Development: A Case Study Analysis in Greece

Authors: Eleni Giouli

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Distance learning provides a flexible approach to education, enabling busy learners to complete their coursework at their own pace, on their own schedule, and from a convenient location. This flexibility combined with a series of other issues; make the benefits of lifelong distance learning numerous. The purpose of the paper is to investigate whether distance education can contribute to the improvement of adult skills in Greece, highlighting in this way the necessity of the lifelong distance learning. To investigate this goal, a questionnaire is constructed and analyzed based on responses from 3,016 attendees of lifelong distance learning programs in the e-learning of the National and Kapodistrian University of Athens in Greece. In order to do so, a series of relationships is examined including the effects of a) the gender, b) the previous educational level, c) the current employment status, and d) the method used in the distance learning program, on the development of new general, technical, administrative, social, cultural, entrepreneurial and green skills. The basic conclusions that emerge after using a binary logistic framework are that the following factors are critical in order to develop new skills: the gender, the education level and the educational method used in the lifelong distance learning program. The skills more significantly affected by those factors are the acquiring new skills in general, as well as acquiring general, language and cultural, entrepreneurial and green skills, while for technical and social skills only gender and educational method play a crucial role. Moreover, routine skills and social skills are not affected by the four factors included in the analysis.

Keywords: adult skills, distance learning, education, lifelong learning

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13231 Evaluation of UI for 3D Visualization-Based Building Information Applications

Authors: Monisha Pattanaik

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In scenarios where users have to work with large amounts of hierarchical data structures combined with visualizations (For example, Construction 3d Models, Manufacturing equipment's models, Gantt charts, Building Plans), the data structures have a high density in terms of consisting multiple parent nodes up to 50 levels and their siblings to descendants, therefore convey an immediate feeling of complexity. With customers moving to consumer-grade enterprise software, it is crucial to make sophisticated features made available to touch devices or smaller screen sizes. This paper evaluates the UI component that allows users to scroll through all deep density levels using a slider overlay on top of the hierarchy table, performing several actions to focus on one set of objects at any point in time. This overlay component also solves the problem of excessive horizontal scrolling of the entire table on a fixed pane for a hierarchical table. This component can be customized to navigate through parents, only siblings, or a specific component of the hierarchy only. The evaluation of the UI component was done by End Users of application and Human-Computer Interaction (HCI) experts to test the UI component's usability with statistical results and recommendations to handle complex hierarchical data visualizations.

Keywords: building information modeling, digital twin, navigation, UI component, user interface, usability, visualization

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13230 Analysis of Potential Associations of Single Nucleotide Polymorphisms in Patients with Schizophrenia Spectrum Disorders

Authors: Tatiana Butkova, Nikolai Kibrik, Kristina Malsagova, Alexander Izotov, Alexander Stepanov, Anna Kaysheva

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Relevance. The genetic risk of developing schizophrenia is determined by two factors: single nucleotide polymorphisms and gene copy number variations. The search for serological markers for early diagnosis of schizophrenia is driven by the fact that the first five years of the disease are accompanied by significant biological, psychological, and social changes. It is during this period that pathological processes are most amenable to correction. The aim of this study was to analyze single nucleotide polymorphisms (SNPs) that are hypothesized to potentially influence the onset and development of the endogenous process. Materials and Methods It was analyzed 73 single nucleotide polymorphism variants. The study included 48 patients undergoing inpatient treatment at "Psychiatric Clinical Hospital No. 1" in Moscow, comprising 23 females and 25 males. Inclusion criteria: - Patients aged 18 and above. - Diagnosis according to ICD-10: F20.0, F20.2, F20.8, F21.8, F25.1, F25.2. - Voluntary informed consent from patients. Exclusion criteria included: - The presence of concurrent somatic or neurological pathology, neuroinfections, epilepsy, organic central nervous system damage of any etiology, and regular use of medication. - Substance abuse and alcohol dependence. - Women who were pregnant or breastfeeding. Clinical and psychopathological assessment was complemented by psychometric evaluation using the PANSS scale at the beginning and end of treatment. The duration of observation during therapy was 4-6 weeks. Total DNA extraction was performed using QIAamp DNA. Blood samples were processed on Illumina HiScan and genotyped for 652,297 markers on the Infinium Global Chips Screening Array-24v2.0 using the IMPUTE2 program with parameters Ne=20,000 and k=90. Additional filtration was performed based on INFO>0.5 and genotype probability>0.5. Quality control of the obtained DNA was conducted using agarose gel electrophoresis, with each tested sample having a volume of 100 µL. Results. It was observed that several SNPs exhibited gender dependence. We identified groups of single nucleotide polymorphisms with a membership of 80% or more in either the female or male gender. These SNPs included rs2661319, rs2842030, rs4606, rs11868035, rs518147, rs5993883, and rs6269.Another noteworthy finding was the limited combination of SNPs sufficient to manifest clinical symptoms leading to hospitalization. Among all 48 patients, each of whom was analyzed for deviations in 73 SNPs, it was discovered that the combination of involved SNPs in the manifestation of pronounced clinical symptoms of schizophrenia was 19±3 out of 73 possible. In study, the frequency of occurrence of single nucleotide polymorphisms also varied. The most frequently observed SNPs were rs4849127 (in 90% of cases), rs1150226 (86%), rs1414334 (75%), rs10170310 (73%), rs2857657, and rs4436578 (71%). Conclusion. Thus, the results of this study provide additional evidence that these genes may be associated with the development of schizophrenia spectrum disorders. However, it's impossible cannot rule out the hypothesis that these polymorphisms may be in linkage disequilibrium with other functionally significant polymorphisms that may actually be involved in schizophrenia spectrum disorders. It has been shown that missense SNPs by themselves are likely not causative of the disease but are in strong linkage disequilibrium with non-functional SNPs that may indeed contribute to disease predisposition.

Keywords: gene polymorphisms, genotyping, single nucleotide polymorphisms, schizophrenia.

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13229 The Effects of the Russian Crisis on Turkish Tourism Sector: A Case of Antalya Province, Turkey

Authors: Huseyin Cetin, Halil Akmese, Sercan Aras, Vahit Aytekin

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Economic crisis, terrorism, global crisis and the relations between countries are the factors affecting tourism industry and tourism industry is vulnerable against these factors. In our study, there are two dimensions about Russian crisis. The crisis between Russia and Ukraine and decreased oil prices in global market have been entailed Russian economic crisis. This crisis has induced that the ruble, Russian currency, has depreciated against American dollars and consequently the purchasing power of Russian has weakened. This is the first dimension of our study. Second dimension is a political crisis between Turkey and Russia owing to the fact that the Russian Warcraft was brought down by Turkish army. The aim of this study is to explain the impact of the consequences of Russian crisis on Turkish tourism industry. The study has been limited only Antalya province.

Keywords: economic crisis, Turkey-Russian crisis, Turkey's tourism industry, tourism in Turkey

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13228 Loan Repayment Prediction Using Machine Learning: Model Development, Django Web Integration and Cloud Deployment

Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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13227 Prevalence and Associated Factors of Attention Deficit Hyperactivity Disorder among Children Age 6 to 17 Years Old Living in Girja District, Oromia Regional State, Rural Ethiopia: Community Based Cross-Sectional Study

Authors: Hirbaye Mokona, Abebaw Gebeyehu, Aemro Zerihun

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Introduction: Attention deficit hyperactivity disorder is serious public health problem affecting millions of children throughout the world. Method: A cross-sectional study conducted from May to June 2015 among children age 6 to 17 years living in rural area of Girja district. Multi-stage cluster sampling technique was used to select 1302 study participants. Disruptive Behavior Disorder rating scale was used to collect the data. Data were coded, entered and cleaned by Epi-Data version 3.1 and analyzed by SPSS version 20. Logistic regression analysis was used and Variables that have P-values less than 0.05 on multivariable logistic regression was considered as statistically significant. Results: Prevalence of Attention deficit hyperactivity disorder (ADHD) among children age 6 to 17 years was 7.3%. Being male [AOR=1.81, 95%CI: (1.13, 2.91)]; living with single parent [AOR=5.0, 95%CI: (2.35, 10.65)]; child birth order/rank [AOR=2.35, 95%CI: (1.30, 4.25)]; low family socio-economic status [AOR= 2.43, 95%CI: (1.29, 4.59)]; maternal alcohol/khat use during pregnancy [AOR=3.14, 95%CI: (1.37, 7.37)] and complication at delivery [AOR=3.56, 95%CI: (1.19, 10.64)] were more likely to develop Attention deficit hyperactivity disorder. Conclusion: In this study, the prevalence of Attention deficit hyperactivity disorder was similar with worldwide prevalence. Prevention and early management of its modifiable risk factors should be carryout alongside increasing community awareness.

Keywords: attention deficit hyperactivity disorder, ADHD, associated factors, children, prevalence

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13226 Price Prediction Line, Investment Signals and Limit Conditions Applied for the German Financial Market

Authors: Cristian Păuna

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In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: algorithmic trading, automated trading systems, high-frequency trading, DAX Deutscher Aktienindex

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13225 Solid Particles Transport and Deposition Prediction in a Turbulent Impinging Jet Using the Lattice Boltzmann Method and a Probabilistic Model on GPU

Authors: Ali Abdul Kadhim, Fue Lien

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Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

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13224 Multi-Criteria Evaluation for the Selection Process of a Wind Power Plant's Location Using Choquet Integral

Authors: Serhat Tüzün, Tufan Demirel

Abstract:

The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

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13223 The Factors that Effect to User Satisfaction of Information System in Bangkok Hospital

Authors: Somchai Buaroong

Abstract:

This research attempted to study information system success in dimensions of the user satisfaction level and to find the association between the independent factors of the user experiences, user knowledge, and user attitude. The study sample was selected using simple random sampling that comprised of 190 users who had used the Bangkok HIS. The data were reported from 165 questionnaires. The results found that the user satisfaction was at a moderate level, user satisfaction on the information quality and system quality was at a moderate level, while satisfaction on service quality was at a high level. The computer knowledge of the user was at a moderate level, and the user attitude was at a positive level. The participation of the user was at a low level and the participation in decision and in evaluation was at a low level; however participation in implementation and in benefit was at a moderate.

Keywords: information system success, hospital information system, user attitude, user satisfaction

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13222 Mechanisms and Process of an Effective Public Policy Formulation in Islamic Economic System

Authors: Md Abu Saieed

Abstract:

Crafting and implementing public policy is one of the indispensable works in any form of state and government. But the policy objectives, methods of formulation and tools of implementation might be different based on the ideological nature, historical legacy, structure and capacity of administration and management and other push and factors. Public policy in Islamic economic system needs to be based on the key guidelines of divine scriptures along with other sources of sharia’h. As a representative of Allah (SWT), the governor and other apparatus of the state will formulate and implement public policies which will enable to establish a true welfare state based on justice, equity and equality. The whole life of Prophet Muhammad (pbuh) and his policy in operating state of affairs in Madina is the practical guidelines for the policy actors and professionals in Islamic system of economics. Moreover, policy makers need to be more meticulous in formulating Islamic public policy which meets the needs and demands of contemporary worlds as well.

Keywords: formulation, Islam, public policy, policy factors, Sharia’h

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13221 Improved Elastoplastic Bounding Surface Model for the Mathematical Modeling of Geomaterials

Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

Abstract:

The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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13220 The Effect of Varying Cone Beam Computed Tomography Image Resolution and Field-of-View Centralization on the Effective Radiation Dose

Authors: Fatima M. Jadu, Asmaa A. Alzahrani, Maha A. Almutairi, Salma O. Al-Amoudi, Mawya A. Khafaji

Abstract:

Introduction: Estimating the potential radiation risk for a widely used imaging technique such as cone beam CT (CBCT) is crucial. The aim of this study was to examine the effect of varying two CBCT technical factors, the voxel size (VOX) and the Field-of-View (FOV) centralization, on the radiation dose. Methodology: The head and neck slices of a RANDO® man phantom (Alderson Research Laboratories) were used with nanoDot™ OSLD dosimeters to measure the absorbed radiation dose at 25 predetermined sites. Imaging was done using the i-CAT® (Imaging Science International, Hatfield, PA, USA) CBCT unit. The VOX was changed for every three cycles of exposures from 0.2mm to 0.3mm and then 0.4mm. Then the FOV was centered on the maxilla and mandible alternatively while holding all other factors constant. Finally, the effective radiation dose was calculated for each view and voxel setting. Results: The effective radiation dose was greatest when the smallest VOX was chosen. When the FOV was centered on the maxilla, the highest radiation doses were recorded in the eyes and parotid glands. While on the mandible, the highest radiation doses were recorded in the sublingual and submandibular glands. Conclusion: Minor variations in the CBCT exposure factors significantly affect the effective radiation dose and thus the radiation risk to the patient. Therefore, extreme care must be taken when choosing these parameters especially for vulnerable patients such as children.

Keywords: CBCT, cone beam CT, effective dose, field of view, mandible, maxilla, resolution, voxel

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13219 Reorientation Orphanage in Muhammadiyah as Strength Effort for Islamic-Based Human Services Organization: Phenomenology Study on Muhammadiyah Orphanages in Malang Raya

Authors: Fauzik Lendriyono, Isbandi Rukminto Adi

Abstract:

Muhammadiyah is an Islamic-based organization taking care to human suffering. The existence of Muhammadiyah organization is strong supported by its members. Muhammadiyah as the oldest Islamic organization in Indonesia, since its establishment has had main activities, such as in the fields of education, health, and social services, one of the form is Orphanage. However, at present, Muhammadiyah orphanage was in a dilemma because of differences in orientation and commitment of the caretaker-managers. This research on Muhammadiyah orphanage is very important because it is able to know the problem identification and to find the ideal concept for the better management of an orphanage in Muhammadiyah. This research is a phenomenology study by research subjects: caretaker of the orphanage in Muhammadiyah at Great Malang. The research data was obtained after the observation, in-depth interviews, review of documentation and the discussion focused. Data were analyzed with interpretative phenomenological analysis. Basic problems for causes of differences in orientation and commitment administrators of Muhammadiyah orphanage is the influence of organizational culture and organizational environment factors. Organizational culture factors include the Islamic-based value and organization ideology, so that the Islamic values and the values of Muhammadiyah are used as guidelines in the orphanage. Environmental factors include the demand for its organization sustainability as characterized by economically productive activities organized by Orphanage and a program to produce a cadre of Muhammadiyah. To support the social welfare of Muhammadiyah, the ideal Orphanage concept for Muhammadiyah is a missionary and self-sufficient orphanage.

Keywords: orphanage, Muhammadiyah, misionary, Great Malang

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13218 Banking Crisis and Economic Effects of the Banking Crisis in Turkey

Authors: Sevilay Konya, Sadife Güngör, Zeynep Karaçor

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Turkish economy is occurred depending on different factors from time to time and the banking crises of different magnitudes. Foremost among the factors which hinder the development of countries and societies- crises in the country's economy. Countries' economic growth rates affect inflation, unemployment and external trade. In this study, effect of November 2000, February 2001 and 2008 banking crisis on Turkey's economy and banking crisis will be examined and announced as conceptual. In this context, this study is investigates Turkey's GDP, inflation, unemployment and foreign trade figures. Turkey's economy affected have been identified from 2000 November 2001 February and 2008 banking crisis.

Keywords: banking crises, Turkey’s economy, economic effects, Turkey

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13217 Risk Factors for Postoperative Fever in Patients Undergoing Lumbar Fusion

Authors: Bang Haeyong

Abstract:

Purpose: The objectives of this study were to determine the prevalence, incidence, and risk factors for postoperative fever after lumbar fusion. Methods: This study was a retrospective chart review of 291 patients who underwent lumbar fusion between March 2015 and February 2016 at the Asan Medical Center. Information was extracted from electronic medical records. Postoperative fever was measured at Tmax > 37.7 ℃ and Tmax > 38.3 ℃. The presence of postoperative fever, blood culture, urinary excretion, and/or chest x-ray were evaluated. Patients were evaluated for infection after lumbar fusion. Results: We found 222 patients (76.3%) had a postoperative temperature of 37.7 ℃, and 162 patients (55.7%) had a postoperative temperature of 38.3 ℃ or higher. The percentage of febrile patients trended down following the mean 1.8days (from the first postoperative day to seventh postoperative day). Infection rate was 9 patients (3.1%), respiratory virus (1.7%), urinary tract infection (0.3%), phlebitis (0.3%), and surgical site infection (1.4%). There was no correlation between Tmax > 37.7℃ or Tmax > 38.3℃, and timing of fever, positive blood or urine cultures, pneumonia, or surgical site infection. Risk factors for increased postoperative fever following surgery were confirmed to be delay of defecation (OR=1.37, p=.046), and shorten of remove drainage (OR=0.66, p=.037). Conclusions: The incidence of fever was 76.3% after lumbar fusion and the drainage time was faster in the case of fever. It was thought that the bleeding was absorbed at the operation site and fever occurred. The prevalence of febrile septicemia was higher in patients with long bowel movements before surgery than after surgery. Clinical symptoms should be considered because postoperative fever cannot be determined by fever alone because fever and infection are not significant.

Keywords: lumbar surgery, fever, postoperative, risk factor

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13216 Report of Candida Auris: An Emerging Fungal Pathogen in a Tertiary Healthcare Facility in Ekiti State, Nigeria

Authors: David Oluwole Moses, Odeyemi Adebowale Toba, Olawale Adetunji Kola

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Candida auris, an emerging fungus, has been reported in more than 30 countries around the world since its first detection in 2009. Due to its several virulence factors, resistance to antifungals, and persistence in hospital settings, Candida auris has been reported to cause treatment-failure infections. This study was therefore carried out to determine the incidence of Candida auris in a tertiary hospital in Ekiti State, Nigeria. In this study, a total of 115 samples were screened for Candida species using cultural and molecular methods. The carriage of virulence factors and antifungal resistance among C. auris was detected using standard microbiological methods. Candida species isolated from the samples were 15 (30.0%) in clinical samples and 22 (33.85%) in hospital equipment screened. Non-albicans Candida accounted for 3 (20%) and 8 (36.36%) among the isolates from the clinical samples and equipment, respectively. Only five of the non-albicans Candida isolates were C. auris. All the isolates produced biofilm, gelatinase, and hemolysin, while none produced germ tubes. Two of the isolates were resistant to all the antifungals tested. Also, all the isolates were resistant to fluconazole and itraconazole. Nystatin appeared to be the most effective among the tested antifungals. The isolation of Candida auris is being reported for the second time in Nigeria, further confirming that the fungus has spread beyond Lagos and Ibadan, where it was first reported. The extent of the spread of the nosocomial fungus needed to be further investigated and curtailed in Nigeria before its outbreak in healthcare facilities.

Keywords: candida auris, virulence factors, antifungals, pathogen, hospital, infection

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