Search results for: variable clustering
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2711

Search results for: variable clustering

1601 Childhood Obesity: Future Direction and Education Priorities

Authors: Zahra Ranjbar

Abstract:

Interpretive structural modeling (ISM) is a well-established methodology for identifying relationships among specific variables, which define a problem or an issue. In this study most important variables that have critical role in children obesity problem were introduce by ISM questionnaire technique and their relationships were determine. Our findings suggested that sedentary activities are top level variables and school teachers and administrators, public education and scientific collaborations are bottom level variables in children obesity problem. Control of dietary, Physical education program, parents, government and motivation strategies variables are depend to other variables. They are very sensitive to external variables. Also, physical education program, parents, government, motivation, school teachers and administrators, public education and collaboration variables have strong driving power. They are linkage factors; it means that they can be effective on children obesity problem directly.

Keywords: ISM, variable, obesity, physical education, children

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1600 Evaluating Traffic Congestion Using the Bayesian Dirichlet Process Mixture of Generalized Linear Models

Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

Abstract:

This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

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1599 Investigating the Characteristics of Correlated Parking-Charging Behaviors for Electric Vehicles: A Data-Driven Approach

Authors: Xizhen Zhou, Yanjie Ji

Abstract:

In advancing the management of integrated electric vehicle (EV) parking-charging behaviors, this study uses Changshu City in Suzhou as a case study to establish a data association mechanism for parking-charging platforms and to develop a database for EV parking-charging behaviors. Key indicators, such as charging start time, initial state of charge, final state of charge, and parking-charging time difference, are considered. Utilizing the K-S test method, the paper examines the heterogeneity of parking-charging behavior preferences among pure EV and non-pure EV users. The K-means clustering method is employed to analyze the characteristics of parking-charging behaviors for both user groups, thereby enhancing the overall understanding of these behaviors. The findings of this study reveal that using a classification model, the parking-charging behaviors of pure EVs can be classified into five distinct groups, while those of non-pure EVs can be separated into four groups. Among them, both types of EV users exhibit groups with low range anxiety for complete charging with special journeys, complete charging at destination, and partial charging. Additionally, both types have a group with high range anxiety, characterized by pure EV users displaying a preference for complete charging with specific journeys, while non-pure EV users exhibit a preference for complete charging. Notably, pure EV users also display a significant group engaging in nocturnal complete charging. The findings of this study can provide technical support for the scientific and rational layout and management of integrated parking and charging facilities for EVs.

Keywords: traffic engineering, potential preferences, cluster analysis, EV, parking-charging behavior

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1598 A Contribution to the Polynomial Eigen Problem

Authors: Malika Yaici, Kamel Hariche, Tim Clarke

Abstract:

The relationship between eigenstructure (eigenvalues and eigenvectors) and latent structure (latent roots and latent vectors) is established. In control theory eigenstructure is associated with the state space description of a dynamic multi-variable system and a latent structure is associated with its matrix fraction description. Beginning with block controller and block observer state space forms and moving on to any general state space form, we develop the identities that relate eigenvectors and latent vectors in either direction. Numerical examples illustrate this result. A brief discussion of the potential of these identities in linear control system design follows. Additionally, we present a consequent result: a quick and easy method to solve the polynomial eigenvalue problem for regular matrix polynomials.

Keywords: eigenvalues/eigenvectors, latent values/vectors, matrix fraction description, state space description

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1597 Identification of Bayesian Network with Convolutional Neural Network

Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

Abstract:

In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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1596 A Review on Pathological Gaming among Adolescents

Authors: Anjali Malik

Abstract:

This paper presents a review of the literature on behavioral addictions with a particular focus on understanding online gaming habits among adolescents. Extant researches yielded many different sets of antecedent factors for developing pathological online gaming behavior. This paper draws findings from the most-cited publications most closely associated with factors explaining why individuals develop such kind of problematic behavior. What emerges as central to understanding this phenomenon is the presence of multiple variable causes that take into account the individual, the environment and their interaction to explain the risk behavior such as pathological online gaming. In addition to that role of some mediating factors and pull factors has also been discussed, along with the consequences on personal, social and academic performance resulting from such kind of addictive behavior. The paper also makes recommendations for future research including developing a deeper understanding of the phenomena studied here by examining the relative contribution of these multiple-risk contexts.

Keywords: pathological gaming, gaming addiction, adolescents, behavior

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1595 Assessing Functional Structure in European Marine Ecosystems Using a Vector-Autoregressive Spatio-Temporal Model

Authors: Katyana A. Vert-Pre, James T. Thorson, Thomas Trancart, Eric Feunteun

Abstract:

In marine ecosystems, spatial and temporal species structure is an important component of ecosystems’ response to anthropological and environmental factors. Although spatial distribution patterns and fish temporal series of abundance have been studied in the past, little research has been allocated to the joint dynamic spatio-temporal functional patterns in marine ecosystems and their use in multispecies management and conservation. Each species represents a function to the ecosystem, and the distribution of these species might not be random. A heterogeneous functional distribution will lead to a more resilient ecosystem to external factors. Applying a Vector-Autoregressive Spatio-Temporal (VAST) model for count data, we estimate the spatio-temporal distribution, shift in time, and abundance of 140 species of the Eastern English Chanel, Bay of Biscay and Mediterranean Sea. From the model outputs, we determined spatio-temporal clusters, calculating p-values for hierarchical clustering via multiscale bootstrap resampling. Then, we designed a functional map given the defined cluster. We found that the species distribution within the ecosystem was not random. Indeed, species evolved in space and time in clusters. Moreover, these clusters remained similar over time deriving from the fact that species of a same cluster often shifted in sync, keeping the overall structure of the ecosystem similar overtime. Knowing the co-existing species within these clusters could help with predicting data-poor species distribution and abundance. Further analysis is being performed to assess the ecological functions represented in each cluster.

Keywords: cluster distribution shift, European marine ecosystems, functional distribution, spatio-temporal model

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1594 Performance Evaluation of an Efficient Asynchronous Protocol for WDM Ring MANs

Authors: Baziana Peristera

Abstract:

The idea of the asynchronous transmission in wavelength division multiplexing (WDM) ring MANs is studied in this paper. Especially, we present an efficient access technique to coordinate the collisions-free transmission of the variable sizes of IP traffic in WDM ring core networks. Each node is equipped with a tunable transmitter and a tunable receiver. In this way, all the wavelengths are exploited for both transmission and reception. In order to evaluate the performance measures of average throughput, queuing delay and packet dropping probability at the buffers, a simulation model that assumes symmetric access rights among the nodes is developed based on Poisson statistics. Extensive numerical results show that the proposed protocol achieves apart from high bandwidth exploitation for a wide range of offered load, fairness of queuing delay and dropping events among the different packets size categories.

Keywords: asynchronous transmission, collision avoidance, wavelength division multiplexing, WDM

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1593 SMEs Access to Finance in Croatia – Model Approach

Authors: Vinko Vidučić, Ljiljana Vidučić, Damir Boras

Abstract:

The goals of the research include the determination of the characteristics of SMEs finance in Croatia, as well as the determination of indirect growth rates of the information model of the entrepreneurs` perception of business environment. The research results show that cost of finance and access to finance are most important constraining factor in setting up and running the business of small entrepreneurs in Croatia. Furthermore, small entrepreneurs in Croatia are significantly dissatisfied with the administrative barriers although relatively to a lesser extent than was the case in the pre-crisis time. High collateral requirement represents the main characteristic of bank lending concerning SMEs followed by long credit elaboration process. Formulated information model has defined the individual impact of indirect growth rates of the remaining variables on the model’s specific variable.

Keywords: business environment, information model, indirect growth rates, SME finance

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1592 Speed Control of Brushless DC Motor Using PI Controller in MATLAB Simulink

Authors: Do Chi Thanh, Dang Ngoc Huy

Abstract:

Nowadays, there are more and more variable speed drive systems in small-scale and large-scale applications such as the electric vehicle industry, household appliances, medical equipment, and other industrial fields led to the development of BLDC (Brushless DC) motors. BLDC drive has many advantages, such as higher efficiency, better speed torque characteristics, high power density, and low maintenance cost compared to other conventional motors. Most BLDC motors use a proportional-integral (PI) controller and a pulse width modulation (PWM) scheme for speed control. This article describes the simulation model of BLDC motor drive control with the help of MATLAB - SIMULINK simulation software. The built simulation model includes a BLDC motor dynamic block, Hall sensor signal generation block, inverter converter block, and PI controller.

Keywords: brushless DC motor, BLDC, six-step inverter, PI speed

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1591 Determination of Effect Factor for Effective Parameter on Saccharification of Lignocellulosic Material by Concentrated Acid

Authors: Sina Aghili, Ali Arasteh Nodeh

Abstract:

Tamarisk usage as a new group of lignocelluloses material to produce fermentable sugars in bio-ethanol process was studied. The overall aim of this work was to establish the optimum condition for acid hydrolysis of this new material and a mathematical model predicting glucose release as a function of operation variable. Sulfuric acid concentration in the range of 20 to 60%(w/w), process temperature between 60 to 95oC, hydrolysis time from 120 to 240 min and solid content 5,10,15%(w/w) were used as hydrolysis conditions. HPLC was used to analysis of the product. This analysis indicated that glucose was the main fermentable sugar and was increased with time, temperature and solid content and acid concentration was a parabola influence in glucose production.The process was modeled by a quadratic equation. Curve study and model were found that 42% acid concentration, 15 % solid content and 90oC were in optimum condition.

Keywords: fermentable sugar, saccharification, wood, hydrolysis

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1590 The Impact of Family Involvement in Management on Firm’s Innovation: Evidence From Chinese Family Firms

Authors: Chen Jun

Abstract:

This study investigates the impact of family involvement, a pivotal factor shaping the management structure of family firms, on the firm’s innovation outputs. The independent variable focuses on the percentage number of family members serving as directors, supervisors and senior management. Our hypothesis suggests that family involvement tends to make management more conservative, thereby increasing the likelihood of impeding innovation investments and resulting in adverse effects on innovation output. Our findings reveal that Chinese family firms with high family involvement exhibit poorer innovation outputs compared to those with lower family involvement. Subsample analyses indicate that this negative influence of family involvement on innovation output is strengthened as the firm faces higher industry competition and a low marketization context. The findings of our paper contribute to the literature on family involvement by empirically illustrating how family involvement hinders innovation efforts and performance in Chinese family firms.

Keywords: family firm, family involvement, firm innovation, Chinese family firm

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1589 Examination of Public Hospital Unions Technical Efficiencies Using Data Envelopment Analysis and Machine Learning Techniques

Authors: Songul Cinaroglu

Abstract:

Regional planning in health has gained speed for developing countries in recent years. In Turkey, 89 different Public Hospital Unions (PHUs) were conducted based on provincial levels. In this study technical efficiencies of 89 PHUs were examined by using Data Envelopment Analysis (DEA) and machine learning techniques by dividing them into two clusters in terms of similarities of input and output indicators. Number of beds, physicians and nurses determined as input variables and number of outpatients, inpatients and surgical operations determined as output indicators. Before performing DEA, PHUs were grouped into two clusters. It is seen that the first cluster represents PHUs which have higher population, demand and service density than the others. The difference between clusters was statistically significant in terms of all study variables (p ˂ 0.001). After clustering, DEA was performed for general and for two clusters separately. It was found that 11% of PHUs were efficient in general, additionally 21% and 17% of them were efficient for the first and second clusters respectively. It is seen that PHUs, which are representing urban parts of the country and have higher population and service density, are more efficient than others. Random forest decision tree graph shows that number of inpatients is a determinative factor of efficiency of PHUs, which is a measure of service density. It is advisable for public health policy makers to use statistical learning methods in resource planning decisions to improve efficiency in health care.

Keywords: public hospital unions, efficiency, data envelopment analysis, random forest

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1588 Resilience, Mental Health, and Life Satisfaction

Authors: Saba Harati, Nasrin Arian Parsa

Abstract:

The current research was an attempt to investigate the effect of resilience on mental health and life satisfaction. In one Cross Sectional research, 287 (173 females and 114 males) students of Tehran University were participated their average age was 23.17 years old (SD=4.9). The instruments used for assessing the research variables included: Cutter and Davidson resilience scale (CD-RISC), the short form of the depression-anxiety-stress scale, and life satisfaction scale. The data analysis was done in the form of structural equation model. The results of Simultaneous Hierarchical Multiple Regression Analysis indicated that there was a significant mediating role of the negative emotions (depression, anxiety, and stress), in the relationship between the family resilience (p < 0.001) and satisfaction with life (p < 0.001). Resilience results in life satisfaction by reducing the emotional problems (or increasing the mental health level). The effect of the resilience variable on life satisfaction was indirect.

Keywords: resilience, negative emotion, mental health, life satisfaction

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1587 Comparison of DPC and FOC Vector Control Strategies on Reducing Harmonics Caused by Nonlinear Load in the DFIG Wind Turbine

Authors: Hamid Havasi, Mohamad Reza Gholami Dehbalaei, Hamed Khorami, Shahram Karimi, Hamdi Abdi

Abstract:

Doubly-fed induction generator (DFIG) equipped with a power converter is an efficient tool for converting mechanical energy of a variable speed system to a fixed-frequency electrical grid. Since electrical energy sources faces with production problems such as harmonics caused by nonlinear loads, so in this paper, compensation performance of DPC and FOC method on harmonics reduction of a DFIG wind turbine connected to a nonlinear load in MATLAB Simulink model has been simulated and effect of each method on nonlinear load harmonic elimination has been compared. Results of the two mentioned control methods shows the advantage of the FOC method on DPC method for harmonic compensation. Also, the fifth and seventh harmonic components of the network and THD greatly reduced.

Keywords: DFIG machine, energy conversion, nonlinear load, THD, DPC, FOC

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1586 Predicting Provider Service Time in Outpatient Clinics Using Artificial Intelligence-Based Models

Authors: Haya Salah, Srinivas Sharan

Abstract:

Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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1585 Separate Powers Control Structure of DFIG Based on Fractional Regulator Fed by Multilevel Inverters DC Bus Voltages of a photovoltaic System

Authors: S. Ghoudelbourk, A. Omeiri, D. Dib, H. Cheghib

Abstract:

This paper shows that we can improve the performance of the auto-adjustable electric machines if a fractional dynamic is considered in the algorithm of the controlling order. This structure is particularly interested in the separate control of active and reactive power of the double-fed induction generator (DFIG) of wind power conversion chain. Fractional regulators are used in the regulation of chain of powers. Knowing that, usually, the source of DFIG is provided by converters through controlled rectifiers, all this system makes the currents of lines strongly polluted that can have a harmful effect for the connected loads and sensitive equipment nearby. The solution to overcome these problems is to replace the power of the rotor DFIG by multilevel inverters supplied by PV which improve the THD. The structure of the adopted adjustment is tested using Matlab/Simulink and the results are presented and analyzed for a variable wind.

Keywords: DFIG, fractional regulator, multilevel inverters, PV

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1584 Analysis of Transverse Vibrations in Uniform Beams Subject to Different End Restraints

Authors: Falek Kamel

Abstract:

Free vibration analysis of beams, based on the assumptions of Bernoulli-Euler theory, has been extensively studied. Many research works have focused on the study of transverse vibrations under the application of different boundary conditions where different theories have been applied. The stiffness and mass matrices considered are those obtained by assembling those resulting from the use of the finite element method. The Jacobi method has been used to solve the eigenvalue problem. These well-known concepts have been applied to the study of beams with constant geometric and mechanical characteristics having one to two overhangs with variable lengths. Murphy studied, by an algebraic solution approach, a simply supported beam with two overhangs of arbitrary length, allowing for an experimental determination of the elastic modulus E. The advantage of our article is that it offers the possibility of extending this approach to many interesting problems formed by transversely vibrating beams with various end constraints.

Keywords: beam, finite element, transverse vibrations, end restreint, Bernoulli-Euler theory

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1583 TRAC: A Software Based New Track Circuit for Traffic Regulation

Authors: Jérôme de Reffye, Marc Antoni

Abstract:

Following the development of the ERTMS system, we think it is interesting to develop another software-based track circuit system which would fit secondary railway lines with an easy-to-work implementation and a low sensitivity to rail-wheel impedance variations. We called this track circuit 'Track Railway by Automatic Circuits.' To be internationally implemented, this system must not have any mechanical component and must be compatible with existing track circuit systems. For example, the system is independent from the French 'Joints Isolants Collés' that isolate track sections from one another, and it is equally independent from component used in Germany called 'Counting Axles,' in French 'compteur d’essieux.' This track circuit is fully interoperable. Such universality is obtained by replacing the train detection mechanical system with a space-time filtering of train position. The various track sections are defined by the frequency of a continuous signal. The set of frequencies related to the track sections is a set of orthogonal functions in a Hilbert Space. Thus the failure probability of track sections separation is precisely calculated on the basis of signal-to-noise ratio. SNR is a function of the level of traction current conducted by rails. This is the reason why we developed a very powerful algorithm to reject noise and jamming to obtain an SNR compatible with the precision required for the track circuit and SIL 4 level. The SIL 4 level is thus reachable by an adjustment of the set of orthogonal functions. Our major contributions to railway engineering signalling science are i) Train space localization is precisely defined by a calibration system. The operation bypasses the GSM-R radio system of the ERTMS system. Moreover, the track circuit is naturally protected against radio-type jammers. After the calibration operation, the track circuit is autonomous. ii) A mathematical topology adapted to train space localization by following the train through a linear time filtering of the received signal. Track sections are numerically defined and can be modified with a software update. The system was numerically simulated, and results were beyond our expectations. We achieved a precision of one meter. Rail-ground and rail-wheel impedance sensitivity analysis gave excellent results. Results are now complete and ready to be published. This work was initialised as a research project of the French Railways developed by the Pi-Ramses Company under SNCF contract and required five years to obtain the results. This track circuit is already at Level 3 of the ERTMS system, and it will be much cheaper to implement and to work. The traffic regulation is based on variable length track sections. As the traffic growths, the maximum speed is reduced, and the track section lengths are decreasing. It is possible if the elementary track section is correctly defined for the minimum speed and if every track section is able to emit with variable frequencies.

Keywords: track section, track circuits, space-time crossing, adaptive track section, automatic railway signalling

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1582 Molecular Characterization of Polyploid Bamboo (Dendrocalamus hamiltonii) Using Microsatellite Markers

Authors: Rajendra K. Meena, Maneesh S. Bhandari, Santan Barthwal, Harish S. Ginwal

Abstract:

Microsatellite markers are the most valuable tools for the characterization of plant genetic resources or population genetic analysis. Since it is codominant and allelic markers, utilizing them in polyploid species remained doubtful. In such cases, the microsatellite marker is usually analyzed by treating them as a dominant marker. In the current study, it has been showed that despite losing the advantage of co-dominance, microsatellite markers are still a powerful tool for genotyping of polyploid species because of availability of large number of reproducible alleles per locus. It has been studied by genotyping of 19 subpopulations of Dendrocalamus hamiltonii (hexaploid bamboo species) with 17 polymorphic simple sequence repeat (SSR) primer pairs. Among these, ten primers gave typical banding pattern of microsatellite marker as expected in diploid species, but rest 7 gave an unusual pattern, i.e., more than two bands per locus per genotype. In such case, genotyping data are generally analyzed by considering as dominant markers. In the current study, data were analyzed in both ways as dominant and co-dominant. All the 17 primers were first scored as nonallelic data and analyzed; later, the ten primers giving standard banding patterns were analyzed as allelic data and the results were compared. The UPGMA clustering and genetic structure showed that results obtained with both the data sets are very similar with slight variation, and therefore the SSR marker could be utilized to characterize polyploid species by considering them as a dominant marker. The study is highly useful to widen the scope for SSR markers applications and beneficial to the researchers dealing with polyploid species.

Keywords: microsatellite markers, Dendrocalamus hamiltonii, dominant and codominant, polyploids

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1581 The Impact of Political Connections on the Funtion of Independent Directors

Authors: Chih-Lin Chang, Tzu-Ching Weng

Abstract:

The purpose of this study is to explore the relationship between corporate political ties and independent directors' functions. With reference to the literature variables such as the characteristics of the relevant board of directors in the past, a single comprehensive function indicator is established as a substitute variable for the function of independent directors, and the impact of political connection on the independent board of directors is further discussed. This research takes Taiwan listed enterprises from 2014 to 2020 as the main research object and conducts empirical research through descriptive statistics, correlation and regression analysis. The empirical results show that companies with political connections will have a positive impact on the number of independent directors; political connections also have a significant positive relationship with the functional part of independent directors, which means that because companies have political connections, they have a positive impact on the seats or functions of independent directors. will pay more attention and increase their oversight functions.

Keywords: political, connection, independent, director, function

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1580 Internet Purchases in European Union Countries: Multiple Linear Regression Approach

Authors: Ksenija Dumičić, Anita Čeh Časni, Irena Palić

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This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the Internet purchases in analysed EU countries is positively correlated with statistically significant variable Gross Domestic Product per capita (GDPpc). Also, analysed multiple linear regression model with four regressors, showing ICT development level, indicates that ICT development is crucial for explaining the Internet purchases by individuals, confirming the research hypothesis.

Keywords: European union, Internet purchases, multiple linear regression model, outlier

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1579 The Development of Web Based Instruction on Puppet Show

Authors: Piyanut Sujit

Abstract:

The purposes of this study were to: 1) create knowledge and develop web based instruction on the puppet show, 2) evaluate the effectiveness of the web based instruction on the puppet show by using the criteria of 80/80, and 3) compare and analyze the achievement of the students before and after learning with web based instruction on the puppet show. The population of this study included 53 students in the Program of Library and Information Sciences who registered in the subject of Reading and Reading Promotion in semester 1/2011, Suansunandha Rajabhat University. The research instruments consisted of web based instruction on the puppet show, specialist evaluation form, achievement test, and tests during the lesson. The research statistics included arithmetic mean, variable means, standard deviation, and t-test in SPSS for Windows. The results revealed that the effectiveness of the developed web based instruction was 84.67/80.47 which was higher than the set criteria at 80/80. The student achievement before and after learning showed statistically significant difference at 0.05 as in the hypothesis.

Keywords: puppet, puppet show, web based instruction, library and information sciences

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1578 The Role of Bone Marrow Fatty Acids in the Early Stage of Post-Menopausal Osteoporosis

Authors: Sizhu Wang, Cuisong Tang, Lin Zhang, Guangyu Tang

Abstract:

Objective: We aimed to detect the composition of bone marrow fatty acids early after ovariectomized (OVX) surgery and explore the potential mechanism. Methods: Thirty-two female Sprague-Dawley (SD) rats (12 weeks) were randomly divided into OVX group and Sham group (N=16/group), and received ovariectomy or sham surgery respectively. After 3 and 28 days, eight rats in each group were sacrificed to detect the composition of bone marrow fatty acids by gas chromatography–mass spectrometry (GC–MS) and evaluate the trabecular bone microarchitecture by micro-CT. Significant different fatty acids in the early stage of post-menopausal osteoporosis were selected by OPLS-DA and t test. Then selected fatty acids were further studied in the process of osteogenic differentiation through RT-PCR and Alizarin Red S staining. Results: An apparent sample clustering and group separation were observed between OVX group and sham group three days after surgery, which suggested the role of bone marrow fatty acids in the early stage of postmenopausal osteoporosis. Specifically, myristate, palmitoleate and arachidonate were found to play an important role in classification between OVX group and sham group. We further investigated the effect of palmitoleate and arachidonate on osteogenic differentiation and found that palmitoleate promoted the osteogenic differentiation of MC3T3-E1 cells while arachidonate inhibited this process. Conclusion: Profound bone marrow fatty acids changes have taken place in the early stage of post-menopausal osteoporosis. Bone marrow fatty acids may begin to affect osteogenic differentiation shortly after deficiency of estrogen.

Keywords: bone marrow fatty acids, GC-MS, osteoblast, osteoporosis, post-menopausal

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1577 Clinical, Demographic and Molecular Characterization of Dengue, Chikungunya and Zika Viruses Causing Hemorrhagic Fever in North India

Authors: Suruchi Shukla, Shantanu Prakash, Amita Jain

Abstract:

Introduction: Arboviral diseases are one of the most common causes of viral hemorrhagic fever (VHF). Of which, Dengue and Chikungunya pose a significant health problem in India. Arbovirus has a tendency to cross the territories and emerge in the new region. Considering the above issues, in the current study active surveillance was conducted among viral hemorrhagic fever (VHF) cases reported from Uttar Pradesh (UP), India. We studied the arboviral etiology of VHF; mainly Dengue, Chikungunya, and ZIKA. Methods: Clinical samples of 465 suspected VHF cases referred to tertiary care referral center of UP, India were enrolled in the study during a period from 15th May 2016 to 9th March 2018. Serum specimens were collected and analyzed for the presence of Dengue, Chikungunya, and ZIKA either by serology and/or by molecular assays. Results: Of all tested, 165 (35.4%) cases were positive for either Dengue or Chikungunya. Dengue (21.2%) was found to be the most prevalent, followed by Chikungunya, (6.6%). None of the cases tested positive for ZIKA virus. Serum samples of 35 (7.5%) cases were positive for both Dengue and Chikungunya. DEN-2 serotype was the most predominant serotype. Phylogenetic and sequence analysis of DEN-2 strains showed 100% clustering with the Cosmopolitan genotype strain. Bleeding from several sites, jaundice, abdominal pain, arthralgia, haemoconcentration, and thrombocytopenia were significantly higher in dengue hemorrhagic cases. However, the rash was significantly more common in Chikungunya patients. Most of the Dengue and Chikungunya positive cases (Age group 6-40 years) were seen in post monsoon season (September to November). Conclusion: Only one-third of total VHF cases are positive for either Dengue/Chikungunya or both. This necessitates the screening of other etiologies capable of causing hemorrhagic manifestations.

Keywords: viral hemorrhagic fever, dengue, chikungunya, zika, India

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1576 Finite Element Analysis of High Performance Synchronous Reluctance Machines

Authors: T. Mohanarajah, J. Rizk, M. Nagrial, A. Hellany

Abstract:

This paper analyses numerous features of the synchronous Reluctance Motor (Syn-RM) and propose a rotor for high electrical torque, power factor & efficiency using Finite Element Method (FEM). A comprehensive analysis completed on solid rotor structure while the total thickness of the flux guide kept constant. A number of tests carried out for nine different studies to find out optimum location of the flux guide, the optimum location of multiple flux guides & optimum wall thickness between flux guides for high-performance reluctance machines. The results are concluded with the aid of FEM simulation results, the saliency ratio and machine characteristics (location, a number of barriers & wall width) analysed.

Keywords: electrical machines, finite element method, synchronous reluctance machines, variable reluctance machines

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1575 The Mediation Effect of Customer Satisfaction in the Relationship between Service Quality, Corporate Image to Customer Loyalty

Authors: Rizwan Ali, Hammad Zafar

Abstract:

The purpose of this research is to investigate the mediation effect of customer satisfaction in the relationship between service quality, corporate image to customer loyalty, in Pakistan banking sector. The population of this research is banking customers and sample size of 210 respondents. This research uses the SPSS, Correlation, ANOVA and regression analysis techniques along with AMOS methods. The service quality and corporate image applied by the banks are not all variables can directly affect customer loyalty, but must first going through satisfaction. Which means that banks must first need to understand what the customer basic needs through variable service quality and corporate image so that the customers feel loyal when the level of satisfaction is resolved. The service quality provided by the banking industry needs to be improved in order to improve customer satisfaction and loyalty of banking services, especially for banks in Pakistan.

Keywords: customer loyalty, service quality, corporate image, customer satisfaction

Procedia PDF Downloads 89
1574 Modeling and Performance Evaluation of Three Power Generation and Refrigeration Energy Recovery Systems from Thermal Loss of a Diesel Engine in Different Driving Conditions

Authors: H. Golchoobian, M. H. Taheri, S. Saedodin, A. Sarafraz

Abstract:

This paper investigates the possibility of using three systems of organic Rankine auxiliary power generation, ejector refrigeration and absorption to recover energy from a diesel car. The analysis is done for both urban and suburban driving modes that vary from 60 to 120 km/h. Various refrigerants have also been used for organic Rankine and Ejector refrigeration cycles. The capacity was evaluated by Organic Rankine Cycle (ORC) system in both urban and suburban conditions for cyclopentane and ammonia as refrigerants. Also, for these two driving plans, produced cooling by absorption refrigeration system under variable ambient temperature conditions and in ejector refrigeration system for R123, R134a and R141b refrigerants were investigated.

Keywords: absorption system, diesel engine, ejector refrigeration, energy recovery, organic Rankine cycle

Procedia PDF Downloads 216
1573 Carbon Nanotubes Based Porous Framework for Filtration Applications Using Industrial Grinding Waste

Authors: V. J. Pillewan, D. N. Raut, K. N. Patil, D. K. Shinde

Abstract:

Forging, milling, turning, grinding and shaping etc. are the various industrial manufacturing processes which generate the metal waste. Grinding is extensively used in the finishing operation. The waste generated contains significant impurities apart from the metal particles. Due to these significant impurities, it becomes difficult to process and gets usually dumped in the landfills which create environmental problems. Therefore, it becomes essential to reuse metal waste to create value added products. Powder injection molding process is used for producing the porous metal matrix framework. This paper discusses the presented design of the porous framework to be used for the liquid filter application. Different parameters are optimized to obtain the better strength framework with variable porosity. Carbon nanotubes are used as reinforcing materials to enhance the strength of the metal matrix framework.

Keywords: grinding waste, powder injection molding (PIM), carbon nanotubes (CNTs), matrix composites (MMCs)

Procedia PDF Downloads 291
1572 Discriminant Analysis as a Function of Predictive Learning to Select Evolutionary Algorithms in Intelligent Transportation System

Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

Abstract:

In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

Procedia PDF Downloads 451