Search results for: variable selection

Authors: Rana M. Mostafa, Nouby M. Ghazaly, Ahmed S. Ali

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This article introduces a solution for increasing the wind energy extracted from turbines to overcome the more electric power required. This objective provides a new science discipline; wind turbine control. This field depends on the development in power electronics to provide new control strategies for turbines. Those strategies should deal with all turbine operating modes. Here there are two control strategies developed for variable speed horizontal axis wind turbine for rated and over rated wind speed regions. These strategies will support wind energy validation, decrease manufacturing overhead cost. Here nonlinear adaptive method was used to design speed controllers to a scheme for ‘Aeolos50 kw’ wind turbine connected to permanent magnet generator via a gear box which was built on MATLAB/Simulink. These controllers apply maximum power point tracking concept to guarantee goal achievement. Procedures were carried to test both controllers efficiency. The results had been shown that the developed controllers are acceptable and this can be easily declared from simulation results.

Keywords: adaptive method, pitch controller, wind energy, nonlinear control

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Authors: Yue Huang, Hongcheng Gan

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The new urbanization pattern has led to a rapid growth in demand for short-distance intercity travel, and the emergence of new travel modes has also increased the variety of intercity travel options. In previous studies on intercity travel mode choice behavior, the impact of functional amenities of travel mode and travelers’ long-term personality characteristics has rarely been considered, and empirical results have typically been calibrated using revealed preference (RP) or stated preference (SP) data. This study designed a questionnaire that combines the RP and SP experiment from the perspective of a trip chain combining inner-city and intercity mobility, with consideration for the actual condition of the Huainan-Hefei traffic corridor. On the basis of RP/SP fusion data, a hybrid choice model considering both random taste heterogeneity and psychological characteristics was established to investigate travelers’ mode choice behavior for traditional train, high-speed rail, intercity bus, private car, and intercity online car-hailing. The findings show that intercity time and cost exert the greatest influence on mode choice, with significant heterogeneity across the population. Although inner-city cost does not demonstrate a significant influence, inner-city time plays an important role. Service attributes of travel mode, such as catering and hygiene services, as well as free wireless network supply, only play a minor role in mode selection. Finally, our study demonstrates that safety-seeking tendency, hedonism, and introversion all have differential and significant effects on intercity travel mode choice.

Keywords: intercity travel mode choice, stated preference survey, hybrid choice model, RP/SP fusion data, psychological latent variable, heterogeneity

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Authors: Adeola Adenikinju, Olusanya E. Olubusoye, Lateef O. Akinpelu, Dilinna L. Nwobi

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Since the enactment of the Fiscal Responsibility Act (2007), the Federal Government of Nigeria (FGN) has made public its fiscal budget and the subsequent implementation report. A critical review of these documents shows significant variations in the five macroeconomic variables which are inputs in each Presidential budget; oil Production target (mbpd), oil price ($), Foreign exchange rate(N/$), and Gross Domestic Product growth rate (%) and inflation rate (%). This results in underperformance of the Federal budget expected output in terms of non-oil and oil revenue aggregates. This paper evaluates first the existing variance between budgeted and actuals, then the relationship and causality between the determinants of Federal fiscal budget assumptions, and finally the determinants of FGN’s Gross Oil Revenue. The paper employed the use of descriptive statistics, the Autoregressive distributed lag (ARDL) model, and a Profit oil probabilistic model to achieve these objectives. This model permits for both the static and dynamic effect(s) of the independent variable(s) on the dependent variable, unlike a static model that accounts for static or fixed effect(s) only. It offers a technique for checking the existence of a long-run relationship between variables, unlike other tests of cointegration, such as the Engle-Granger and Johansen tests, which consider only non-stationary series that are integrated of the same order. Finally, even with small sample size, the ARDL model is known to generate a valid result, for it is the dependent variable and is the explanatory variable. The results showed that there is a long-run relationship between oil revenue as a proxy for budget performance and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a short-run relationship between oil revenue and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a long-run relationship between non-oil revenue and its determinants; inflation rate, GDP growth rate, and foreign exchange rate. The grangers’ causality test results show that there is a mono-directional causality between oil revenue and its determinants. The Federal budget assumptions only explain 68% of oil revenue and 62% of non-oil revenue. There is a mono-directional causality between non-oil revenue and its determinants. The Profit oil Model describes production sharing contracts, joint ventures, and modified carrying arrangements as the greatest contributors to FGN’s gross oil revenue. This provides empirical justification for the selected macroeconomic variables used in the Federal budget design and performance evaluation. The research recommends other variables, debt and money supply, be included in the Federal budget design to explain the Federal budget revenue performance further.

Keywords: ARDL, budget performance, oil price, oil quantity, oil revenue

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Authors: Fayssal Amrane, Azeddine Chaiba, Bruno Francois

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In this paper, design and experimental study based on Direct Power Control (DPC) of DFIG is proposed for Stand-alone mode in Variable Speed Wind Energy Conversion System (VS-WECS). The proposed IDPC method based on robust IP (Integral-Proportional) controllers in order to control the Rotor Side Converter (RSC) by the means of the rotor current d-q axes components (Ird* and Irq*) of Doubly Fed Induction Generator (DFIG) through AC-DC-AC converter. The implementation is realized using dSPACE dS1103 card under Sub and Super-synchronous operations (means < and > of the synchronous speed “1500 rpm”). Finally, experimental results demonstrate that the proposed control using IP provides improved dynamic responses, and decoupled control of the wind turbine has driven DFIG with high performances (good reference tracking, short response time and low power error) despite for sudden variation of wind speed and rotor references currents.

Keywords: Direct Power Control (DPC), Doubly fed induction generator (DFIG), Wind Energy Conversion System (WECS), Experimental study.

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Yong-Heng Shi, Peng Hao, Bai-Chen Xie

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Solar prosumers are playing increasingly prominent roles in the power system. However, its uncertainty affects the outcomes and functions of the power market, especially in the asymmetric information environment. Therefore, an important issue is how to take effective measures to reduce the impact of uncertainty on market equilibrium. We propose a two-level stochastic differential game model to explore the Cournot decision problem of prosumers. In particular, we study the impact of punishment and cooperation mechanisms on the efficiency of the Cournot game in which prosumers face uncertainty. The results show that under the penalty mechanism of fixed and variable rates, producers and consumers tend to take conservative actions to hedge risks, and the variable rates mechanism is more reasonable. Compared with non-cooperative situations, prosumers can improve the efficiency of the game through cooperation, which we attribute to the superposition of market power and uncertainty reduction. In addition, the market environment of asymmetric information intensifies the role of uncertainty. It reduces social welfare but increases the income of prosumers. For regulators, promoting alliances is an effective measure to realize the integration, optimization, and stable grid connection of producers and consumers.

Keywords: Cournot games, power market, uncertainty, prosumer cooperation

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Authors: Nipon Sasithornsaowapa

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The purposes of this research was to study the female management career success of the primary education department of Thailand. The independent variable was human capital which included three factors: family status, personality, and knowledge-skill-experience, while the important dependent variable was the career success. The population of this study included 2,179 female management officials in the department of primary education. A total of 400 female managers were interviewed and utilized as a sample group. A questionnaire was developed and used as a main tool for collecting data. Content analysis was performed to get the quantitative data. Descriptive statistics in this research was done by SPSS program. The findings revealed that family and personality factors had a high influence on the human capital and, in turn, influenced the career success of female managers. On the other hand, knowledge-skill-experience had an insignificant influence to the human capital and the female career success. In addition, the findings from the in-depth interview revealed that the majority of respondents defined career success as the satisfaction in job duties, not money and position.

Keywords: career, female managers, primary education

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Authors: Redha Yeghnem, Laid Boulefrakh, Sid Ahmed Meftah, Abdelouahed Tounsi, El Abbas Adda Bedia

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In this study, the time-dependent behavior of damaged reinforced concrete shear wall structures strengthened with composite plates having variable fibers spacing was investigated to analyze their seismic response. In the analytical formulation, the adherent and the adhesive layers are all modeled as shear walls, using the mixed finite element method (FEM). The anisotropic damage model is adopted to describe the damage extent of the RC shear walls. The phenomenon of creep and shrinkage of concrete has been determined by Eurocode 2. Large earthquakes recorded in Algeria (El-Asnam and Boumerdes) have been tested to demonstrate the accuracy of the proposed method. Numerical results are obtained for non uniform distributions of carbon fibers in epoxy matrices. The effects of damage extent and the delay mechanism creep and shrinkage of concrete are highlighted. Prospects are being studied.

Keywords: RC shear wall structures, composite plates, creep and shrinkage, damaged reinforced concrete structures, finite element method

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Authors: Zubaidan Yushan, Hudayar Cıhan

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Turkiye and China are countries that have collective cultures, but they have different cultural backgrounds. They have different cultures, different religions, and different levels of economic development. The aim of this study is to test the moderation effect of caregiver bonding on the relationship between dating violence and coping strategies among unmarried emerging adults in China and Turkiye. Participants ages were 19 and 26 years (X=23.66, SD=3.66), unmarried emerging adults Turkish 171 participants (72.5% women, 24% men, 3.5% prefer not to say), Chinese 170 participants (71.8% women, 21.8% men, 6.5% prefer not to say). All participants had been in a relationship for more than six months. Participants completed The Conflict Tactics Scales—(CTS2), The Cope Inventory, and The Parental Bonding Instrument (PBI). Examining the dating violence and coping strategies of the participant's relationship through caregiver bonding moderation analysis was performed using the Jamovi. Significance was tested using the bootstrapping method with bias-corrected confidence estimates. The outcome variable for analysis was dating violence, and the predictor variable for the analysis was coping strategies. The moderator variable evaluated for the analysis was parent attachment. Before the analysis, the mean-centered scores of each variable and moderator were calculated. Furthermore, the moderation analysis was conducted separately for each outcome. The Moderation analysis results show that the sub-dimension of over-protection moderates psychological aggression perpetration and avoidance coping in China. The sub-dimension of care moderates injury victimization and avoidance management in Turkiye; also, over-protection moderates injury victimization and social support coping. Moreover, the sub-dimension of care moderates sexual coercion perpetration and avoidance coping. In the results, caregiver bonding moderates the relationship between coping strategies and dating violence, which may be explained by the fact that our ways of coping with problems are learned, and people are influenced by their parents when they face problems. Therefore, problem-solving is permanently fixed, and each person has his or her fixed solution, which leads to a habit of using solutions to problems. However, sometimes, these solutions become the justification for the injured or abusive person. The quality of the attachment between parents can regulate this state. The results are somewhat similar to and slightly different from those in the previous literature. These mixed results indicate the need for further exploration. Many other factors, such as alcohol, drug violence, and pathological problems, maybe the reasons for these differences. In addition, diverse factors such as the study environment and the applied measurement scales may also affect the results.

Keywords: caregiver bonding, coping strategies, dating violence, emerging adulthood, cross-cultural, comparison

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Authors: Sareh Rajabi, Taha Anjamrooz, Salwa Bheiry

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The continuous increase in the world population, resource shortage and the warning of climate change cause various environmental and social issues to the world. Thus, sustainability concept is much needed nowadays. Organizations are progressively falling under strong worldwide pressure to integrate sustainability practices into their project decision-making development. Construction projects in the industry are amongst the most significant, since it is one of the biggest divisions and of main significance for the national economy and hence has a massive effect on the environment and society. So, it is important to discover approaches to incorporate sustainability into the management of those projects. This study presents a combined sustainability index of projects with sustainable transportation which has been formed as per a comprehensive literature review and survey study. Transportation systems enable the movement of goods and services worldwide, and it is leading to economic growth and creating jobs while creating negative impacts on the environment and society. This research is study to quantify the sustainability indicators, through 1) identifying the importance of sustainable transportation indicators that are based on the sustainable practices used for the construction projects and 2) measure the effectiveness of practices through these indicators on the three sustainable pillars. A total 26 sustainability indicators have been selected and grouped under each related sustainability pillars. A survey was used to collect the opinion about the sustainability indicators by a scoring system. A combined sustainability index considering three sustainable pillars can be helpful in evaluating the transportation sustainable practices of a project and making decisions regarding project selection. In addition to focus on the issue of financial resource allocation in a project selection, the decision-maker could take into account the sustainability as an important key in addition to the project’s return and risk. The purpose of this study is to measure the performance of transportation sustainability which allow companies to assess multiple projects selection. This is useful to decision makers to rank and focus more on future sustainable projects.

Keywords: sustainable transportation, transportation performances, sustainable indicators, sustainable construction practice, sustainability

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Authors: Abraham Rotich

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The purpose of this study was to determine the effects of relationship banking on the financial performance of SMEs. The paper attempted to establish the link between the constructs of relationship banking and SME performance. The study was guided by relationship lending, relationship monitoring, relationship risk sharing and bundle of products as independent variables while financial performance will be the dependent variable. The study used a quasi experimental design with population being the 620 SMEs who have a relationship banking arrangement with banks in Nairobi. The study used stratified sampling to pick a sample of 235. The population of interest will be the CEOs of the respective companies. The basis of stratification is the sectors in which the SMEs operate in. The study will use a questionnaire to collect data. The questionnaire will have both open and close ended questions. A pilot study will be conducted to test reliability and validity of questionnaire. The data was analyzed using descriptive statistics. Regression analysis was employed to test if there is a relationship between the dependent and the independent variable. The study found evidence that relationship banking positively impacts on financial performance of SMEs. Specifically, the study established that each component of relationship banking in this study i.e relationship lending, monitoring, bundle of products and risk sharing positively affects financial performance.

Keywords: relationship banking, SMEs, financial performance, entrepreneurial orientation

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Authors: Nico Rosamilia

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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

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Authors: Mehdi Fuladipanah

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Sensitivity analysis as a technique is applied to determine influential input factors on model output. Variance-based sensitivity analysis method has more application compared to other methods because of including linear and non-linear models. In this paper, van Rijn’s movable bed roughness formula was selected to evaluate because of its reasonable results in sandy rivers. This equation contains four variables as: flow depth, sediment size,bBed form height and bed form length. These variable’s importance was determined using the first order of Fourier Amplitude Sensitivity Test. Sensitivity index was applied to evaluate importance of factors. The first order FAST based sensitivity indices test, explain 90% of the total variance that is indicating acceptance criteria of FAST application. More value of this index is indicating more important variable. Results show that bed form height, bed form length, sediment size and flow depth are more influential factors with sensitivity index: 32%, 24%, 19% and 15% respectively.

Keywords: sdensitivity analysis, variance, movable bed roughness formula, Sandy River

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Authors: Agus Masrukhin

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This research aims to find and analyze the model of character building in the Police Headquarters in Bali with a case study of Muslim members in improving the quality of the morality of its members. The formation of patterns of thinking, behavior, mentality, and police officers noble character, later can be used as a solution to reduce the hedonistic nature of the challenges in the era of globalization. The benefit of this study is expected to be a positive recommendation to find a constructive character building models of police officers in the Republic of Indonesia, especially Bali Police. For the long term, the discovery of the character building models can be developed for the entire police force in Indonesia. The type of research that would apply in this study researchers mix the qualitative research methods based on the narrative between the subject and the concrete experience of field research and quantitative research methods with 92 respondents from the police regional police Bali. This research used a descriptive analysis and SWOT analysis then it is presented in the FGD (focus group discussion). The results of this research indicate that the variable modeling the leadership of the police and variable police offices culture have significant influence on the implementation of spiritual development.

Keywords: positive constructive, hedonistic, character models, morality

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Milada Krejci, Martin Hill, Vaclav Hosek, Dobroslava Jandova, Jiri Kajzar, Pavel Blaha

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The paper declares effects of exercise intervention of the research project “Basic research of balance changes in seniors”, granted by the Czech Science Foundation. The objective of the presented study is to define predictors, which influence bio-psycho-social consequences and effects of balance ability in senior 65 years old and above. We focused on the Fall-Efficacy Scale changes evaluation in seniors. Comprehensive hypothesis of the project declares, that motion uncertainty (dyskinesia) can negatively affect the well-being of a senior in bio-psycho-social context. In total, random selection and testing of 100 seniors (30 males, 70 females) from Prague and Central Bohemian region was provided. The sample was divided by stratified random selection into experimental and control groups, who underwent input and output testing. For diagnostics the methods of Medical Anamnesis, Functional anthropological examinations, Tinetti Balance Assessment Tool, SF-36 Health Survey, Anamnestic comparative self-assessment scale were used. Intervention method called "Life in Balance" based on yoga techniques was applied in four-week cycle. Results of multivariate regression were verified by repeated measures ANOVA: subject factor, phase of intervention (between-subject factor), body fluid (within-subject factor) and phase of intervention × body fluid interaction). ANOVA was performed with a repetition involving the factors of subjects, experimental/control group, phase of intervention (independent variable), and x phase interaction followed by Bonferroni multiple comparison assays with a test strength of at least 0.8 on the probability level p < 0.05. In the paper results of the first-year investigation of the three years running project are analysed. Results of balance tests confirmed no significant difference between females and males in pre-test. Significant improvements in balance and walking ability were observed in experimental group in females comparing to males (F = 128.4, p < 0.001). In the females control group, there was no significant change in post- test, while in the female experimental group positive changes in posture and spine flexibility in post-tests were found. It seems that females even in senior age react better to incentives of intervention in balance and spine flexibility. On the base of results analyses, we can declare the significant improvement in social balance markers after intervention in the experimental group (F = 10.5, p < 0.001). In average, seniors are used to take four drugs daily. Number of drugs can contribute to allergy symptoms and balance problems. It can be concluded that static balance and walking ability of seniors according Tinetti Balance scale correlate significantly with psychic and social monitored markers.

Keywords: exercises, balance, seniors 65+, health, mental and social balance

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Authors: Zuzana Sedláková, Magda Kárászová, Jiří Vejražka, Lenka Morávková, Pavel Izák

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Membrane separations are mentioned frequently as a possibility for CO2 capture. Selectivity of ionic liquid membranes is strongly determined by different solubility of separated gases in ionic liquids. The solubility of separated gases usually varies over an order of magnitude, differently from diffusivity of gases in ionic liquids, which is usually of the same order of magnitude for different gases. The present work evaluates the selection of an appropriate ionic liquid for the selective membrane preparation based on the gas solubility in an ionic liquid. The current state of the art of CO2 capture patents and technologies based on the membrane separations was considered. An overview is given of the discussed transport mechanisms. Ionic liquids seem to be promising candidates thanks to their tunable properties, wide liquid range, reasonable thermal stability, and negligible vapor pressure. However, the uses of supported liquid membranes are limited by their relatively short lifetime from the industrial point of view. On the other hand, ionic liquids could overcome these problems due to their negligible vapor pressure and their tunable properties by adequate selection of the cation and anion.

Keywords: biogas upgrading, carbon dioxide separation, ionic liquid membrane, transport properties

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Authors: Irina Khutsishvili

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The presented study develops a decision support methodology for multi-criteria group decision-making problem. The proposed methodology is based on the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach in the hesitant fuzzy environment. The main idea of decision-making problem is a selection of one best alternative or several ranking alternatives among a set of feasible alternatives. Typically, the process of decision-making is based on an evaluation of certain criteria. In many MCDM problems (such as medical diagnosis, project management, business and financial management, etc.), the process of decision-making involves experts' assessments. These assessments frequently are expressed in fuzzy numbers, confidence intervals, intuitionistic fuzzy values, hesitant fuzzy elements and so on. However, a more realistic approach is using linguistic expert assessments (linguistic variables). In the proposed methodology both the values and weights of the criteria take the form of linguistic variables, given by all decision makers. Then, these assessments are expressed in triangular fuzzy numbers. Consequently, proposed approach is based on triangular hesitant fuzzy TOPSIS decision-making model. Following the TOPSIS algorithm, first, the fuzzy positive ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are defined. Then the ranking of alternatives is performed in accordance with the proximity of their distances to the both FPIS and FNIS. Based on proposed approach the software package has been developed, which was used to rank investment projects in the real investment decision-making problem. The application and testing of the software were carried out based on the data provided by the ‘Bank of Georgia’.

Keywords: fuzzy TOPSIS approach, investment project, linguistic variable, multi-criteria decision making, triangular hesitant fuzzy set

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Authors: Cheng-Chi Yu, Yu-Shiue Wang, Kei-Lin Kuo

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Active Independent Front Steering system is a steering system which can according to vehicle driving situation adjusts the relation of steering angle between inner wheel and outer wheel. In low-speed cornering, AIFS sets the steering angles of inner and outer wheel into Ackerman steering geometry to make vehicle has less cornering radius. Besides, AIFS changes the steering geometry to parallel or even anti-Ackerman steering geometry to keep vehicle stability in high-speed cornering. Therefore, based on the analysis of the vehicle steering behavior from different steering geometries, this study develops a new screw type of active independent front steering system to make vehicles best cornering performance at any speeds. The screw type of active independent front steering system keeps the pinion and separates the rack into main rack and second rack. Two racks connect by a screw. Extra screw rotated motion powered by assistant motor through coupler makes second rack move relative to main rack, which can adjust both steering ratio and steering geometry. First of all, this study distinguishes the steering geometry by using Ackerman percentage and utilizes the software of ADAMS/Car to construct diverse steering geometry models. The different steering geometries are compared at low-speed and high-speed cornering, and then control strategies of the active independent front steering systems could be formulated. Secondly, this study applies closed loop equation to analyze tire steering angles and carries out optimization calculations to make the steering geometry from traditional rack and pinion steering system near to Ackerman steering geometry. Steering characteristics of the optimum steering mechanism and motion characteristics of vehicle installed the steering mechanism are verified by ADAMS/Car models of front suspension and full vehicle respectively. By adding dual auxiliary rack and dual motor to the optimum steering mechanism, the active independent front steering system could be developed to achieve the functions of variable steering ratio and variable steering geometry. At last, this study uses ADAMS/Car and Matlab/Simulink to co-simulate the cornering motion of vehicles confirms the vehicle installed the Active Independent Front Steering (AIFS) system has better handling performance than that with Active Independent Steering (AFS) system or with Electric Power Steering (EPS) system. At low-speed cornering, the vehicles with AIFS system and with AFS system have better maneuverability, less cornering radius, than the traditional vehicle with EPS system because that AIFS and AFS systems both provide function of variable steering ratio. However, there is a slight penalty in the motor(s) power consumption. In addition, because of the capability of variable steering geometry, the vehicle with AIFS system has better high-speed cornering stability, trajectory keeping, and even less motor(s) power consumption than that with EPS system and also with AFS system.

Keywords: active front steering system, active independent front steering system, steering geometry, steering ratio

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Fariba Dortaj, Reza Asadinejad, Akram Dortaj, Atena Baziyar

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The aim of this study was to determine the effect of distance education (based on MOOC) on the components of academic engagement of Kerman PNU. The research was quasi-experimental method that cluster sampling with an appropriate volume was used in this study (one class in experimental group and one class in controlling group). Sampling method is single-stage cluster sampling. The statistical society is students of Kerman Payam Noor University, which) were selected 40 of them as sample (20 students in the control group and 20 students in experimental group). To test the hypothesis, it was used the analysis of univariate and Co-covariance to offset the initial difference (difference of control) in the experimental group and the control group. The instrument used in this study is academic engagement questionnaire of Zerang (2012) that contains component of cognitive, behavioral and motivational engagement. The results showed that there is no significant difference between mean scores of academic components of academic engagement in experimental group and the control group on the post-test, after elimination of the pre-test. The adjusted mean scores of components of academic engagement in the experimental group were higher than the adjusted average of scores after the test in the control group. The use of technology-based education in distance education has been effective in increasing cognitive engagement, motivational engagement and behavioral engagement among students. Experimental variable with the effect size 0.26, predicted 26% of cognitive engagement component variance. Experimental variable with the effect size 0.47, predicted 47% of the motivational engagement component variance. Experimental variable with the effect size 0.40, predicted 40% of behavioral engagement component variance. So teaching with technology (MOOC) has a positive impact on increasing academic engagement and academic performance of students in educational technology. The results suggest that technology (MOOC) is used to enrich the teaching of other lessons of PNU.

Keywords: educational technology, distance education, components of academic engagement, mooc technology

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Authors: Tigabu Dagne Akal

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Electronic health records (EHRs) can help to store, maintain, and make the appropriate handling of patient histories for proper treatment and decision. Merging the EHRs with big data analytics (BDA) capabilities enable healthcare stakeholders to provide effective and efficient treatments for chronic diseases. Though there are huge opportunities and efforts that exist in the deployment of EMRs and the development of BDA, there are challenges in addressing resources and organizational capabilities that are required to achieve the competitive advantage and sustainability of EHRs and BDA. The resource-based view (RBV), information system (IS), and non- IS theories should be extended to examine organizational capabilities and resources which are required for successful data analytics in the healthcare industries. The main purpose of this study is to develop a conceptual framework for the development of healthcare BDA capabilities based on past works so that researchers can extend. The research question was formulated for the search strategy as a research methodology. The study selection was made at the end. Based on the study selection, the conceptual framework for the development of BDA capabilities in the healthcare settings was formulated.

Keywords: EHR, EMR, Big data, Big data analytics, resource-based view

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Authors: Jiabei Zhang, Ying Qi

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The purpose of this study was to develop a descriptive profile of the adapted physical activity research using single subject experimental designs. All research articles using single subject experimental designs published in the journal of Adapted Physical Activity Quarterly from 1984 to 2013 were employed as the data source. Each of the articles was coded in a subcategory of seven categories: (a) the size of sample; (b) the age of participants; (c) the type of disabilities; (d) the type of data analysis; (e) the type of designs, (f) the independent variable, and (g) the dependent variable. Frequencies, percentages, and trend inspection were used to analyze the data and develop a profile. The profile developed characterizes a small portion of research articles used single subject designs, in which most researchers used a small sample size, recruited children as subjects, emphasized learning and behavior impairments, selected visual inspection with descriptive statistics, preferred a multiple baseline design, focused on effects of therapy, inclusion, and strategy, and measured desired behaviors more often, with a decreasing trend over years.

Keywords: adapted physical activity research, single subject experimental designs, physical education, sport science

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Authors: Paffrath Meinhard, Zhou Yayun, Guo Yiqing, Ertl Harald

Abstract:

Winding geometry design is an important part of power transformer electrical design. Conventionally, the winding geometry is designed manually, which is a time-consuming job because it involves many iteration steps in order to meet all cost, manufacturing and electrical requirements. Here a method is presented which automatically generates the winding geometry for given user parameters and allows the user to interactively set and change parameters. To achieve this goal, the winding problem is transferred to a mixed integer nonlinear optimization problem. The relevant geometrical design parameters are defined as optimization variables. The cost and other requirements are modeled as constraints. For the solution, a stochastic ant colony optimization algorithm is applied. It is well-known, that an optimizer can get stuck in a local minimum. For the winding problem, we present efficient strategies to come out of local minima, furthermore a reduced variable search range helps to accelerate the solution process. Numerical examples show that the optimization result is delivered within seconds such that the user can interactively change the variable search area and constraints to improve the design.

Keywords: ant colony optimization, mixed integer nonlinear programming, power transformer, winding design

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Authors: Jacky Liu

Abstract:

This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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Authors: Daniel Tochwin

Abstract:

Continuous improvement is an essential part of effective process performance management. In order to achieve continuous quality improvement, each organization must use the appropriate selection of tools and techniques. The basic condition for success is a proper understanding of the business need faced by the company and the selection of appropriate methods to improve a given production process. The main aim of this article is to analyze the methods of conduct which are popular in practice when implementing process improvements and then to determine whether the tested methods include repetitive systematics of the approach, i.e., a similar sequence of the same or similar actions. Based on an extensive literature review, 4 methods of continuous improvement of production processes were selected: A3 report, Gemba Kaizen, PDCA cycle, and Deming cycle. The research shows that all frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re)interpretation" and the need to adapt the continuous improvement approach to the specific business process. The research shows that all the frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re) interpretation" and the need to adapt the continuous improvement approach to the specific business process.

Keywords: continuous improvement, lean methods, process improvement, PDCA

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Authors: Muzaffar Shaikh, Shoaib Shaikh, Mark Moyou, Gaby Hawat

Abstract:

This paper presents the use of Analytic Hierarchy Process (AHP) in evaluating the site selection of a new plant by a corporation. Due to intense competition at a global level, multinational corporations are continuously striving to minimize production and shipping costs of their products. One key factor that plays significant role in cost minimization is where the production plant is located. In the U.S. for example, labor and land costs continue to be very high while they are much cheaper in countries such as India, China, Indonesia, etc. This is why many multinational U.S. corporations (e.g. General Electric, Caterpillar Inc., Ford, General Motors, etc.), have shifted their manufacturing plants outside. The continued expansion of the Internet and its availability along with technological advances in computer hardware and software all around the globe have facilitated U.S. corporations to expand abroad as they seek to reduce production cost. In particular, management of multinational corporations is constantly engaged in concentrating on countries at a broad level, or cities within specific countries where certain or all parts of their end products or the end products themselves can be manufactured cheaper than in the U.S. AHP is based on preference ratings of a specific decision maker who can be the Chief Operating Officer of a company or his/her designated data analytics engineer. It serves as a tool to first evaluate the plant site selection criteria and second, alternate plant sites themselves against these criteria in a systematic manner. Examples of site selection criteria are: Transportation Modes, Taxes, Energy Modes, Labor Force Availability, Labor Rates, Raw Material Availability, Political Stability, Land Costs, etc. As a necessary first step under AHP, evaluation criteria and alternate plant site countries are identified. Depending upon the fidelity of analysis, specific cities within a country can also be chosen as alternative facility locations. AHP experience in this type of analysis indicates that the initial analysis can be performed at the Country-level. Once a specific country is chosen via AHP, secondary analyses can be performed by selecting specific cities or counties within a country. AHP analysis is usually based on preferred ratings of a decision-maker (e.g., 1 to 5, 1 to 7, or 1 to 9, etc., where 1 means least preferred and a 5 means most preferred). The decision-maker assigns preferred ratings first, criterion vs. criterion and creates a Criteria Matrix. Next, he/she assigns preference ratings by alternative vs. alternative against each criterion. Once this data is collected, AHP is applied to first get the rank-ordering of criteria. Next, rank-ordering of alternatives is done against each criterion resulting in an Alternative Matrix. Finally, overall rank ordering of alternative facility locations is obtained by matrix multiplication of Alternative Matrix and Criteria Matrix. The most practical aspect of AHP is the ‘what if’ analysis that the decision-maker can conduct after the initial results to provide valuable sensitivity information of specific criteria to other criteria and alternatives.

Keywords: analytic hierarchy process, multinational corporations, plant site selection, preference ratings

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Authors: Yoftahe Nigussie Worku

Abstract:

This report unveils a meticulous project focused on the design intricacies of a Fire Tube Boiler tailored for the efficient generation of saturated steam. The overarching objective is to produce 2000kg/h of saturated steam at 12-bar design pressure, achieved through the development of an advanced fire tube boiler. This design is meticulously crafted to harmonize cost-effectiveness and parameter refinement, with a keen emphasis on material selection for component parts, construction materials, and production methods throughout the analytical phases. The analytical process involves iterative calculations, utilizing pertinent formulas to optimize design parameters, including the selection of tube diameters and overall heat transfer coefficients. The boiler configuration incorporates two passes, a strategic choice influenced by tube and shell size considerations. The utilization of heavy oil fuel no. 6, with a higher heating value of 44000kJ/kg and a lower heating value of 41300kJ/kg, results in a fuel consumption of 140.37kg/hr. The boiler achieves an impressive heat output of 1610kW with an efficiency rating of 85.25%. The fluid flow pattern within the boiler adopts a cross-flow arrangement strategically chosen for inherent advantages. Internally, the welding of the tube sheet to the shell, secured by gaskets and welds, ensures structural integrity. The shell design adheres to European Standard code sections for pressure vessels, encompassing considerations for weight, supplementary accessories (lifting lugs, openings, ends, manhole), and detailed assembly drawings. This research represents a significant stride in optimizing fire tube boiler technology, balancing efficiency and safety considerations in the pursuit of enhanced saturated steam production.

Keywords: fire tube, saturated steam, material selection, efficiency

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Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

Abstract:

FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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Authors: Salim Omar Raoof

Abstract:

This study was conducted in a private local sheep herd at Gabaraka village-Kirkuk-Iraq. Analysis of 77 ewes recorded and 7 Rams of local sheep presented in Gabaraka village farm plain, the age of ewes ranged between (2-4) years. The aim of this study is to investigate the genetic and non-genetic factors (type of birth, sex, and age of dam) affecting daily milk yield (DMY), birth weight (BW), weaning weight (WW) and Gain characteristics of local sheep raised under Iraq conditions, and it also aims at estimating heritability’s, BLUP. The overall mean of daily milk yield, (BW), (WW), and gain. Was 444.15gm,4.92kg,43.08kg, and 38.16kg, respectively. The results showed there was a significant effect of the type of birth and sex on (BW) and (WW). Also, the age of the dam had a significant effect on daily milk yield (BW), (WW), and gain. Generally, the estimate of heritability of DMP, BWT, WWT, and Gain tend to be 0.22, 0.17, 0.27, and 0.22, respectively. The breeding value (BLUP) for rams ranged between (-0.1684 to 0.188), (-0.205 to 0.310), and ( -0.0171 to 0.029) according to growth traits of Lambs BW, WW, and Gain, respectively. It concluded that the selection of ewes and rams at the population level in planned selection schemes is based on BLUP value and heritability.

Keywords: locally sheep, milk yield, Genetic parameters, BLUP value

Procedia PDF Downloads 72