Search results for: cluster model approach

Authors: Navdeep Kaur

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The primary focus of this study is to answer “What is the role of corporate governance in corporate failures? Does poor corporate governance lead to corporate failures? If so, how?”. In doing so, the study examines the literature from multiple fields, including corporate governance, corporate failures and organizational decision making, and presents a research gap to analyze and explore the relationship between corporate governance practices and corporate failures through a behavioral lens. In approaching this, a qualitative research methodology is adopted to analyze the failure of Enron Corporation (United States). The research considered the case study organizations as the primary unit of analysis and the decision-makers as the secondary unit of analysis. Based on this research approach, the study reports the analytical results drawn from extensive and triangulated secondary data. The study then interprets the results in the context of the theoretical synthesis. The study contributes towards filling a gap in the research and presents a behaviourally plausible decision centered model of the role of corporate governance in corporate failures. The model highlights the critical role of the behavioral aspects of corporate governance decision making in corporate failures and focuses attention on the under-explored aspects of corporate governance decision making. The study also suggests a further understanding of ‘A Behavioral Theory of the Firm’ in relation to corporate failures.

Keywords: behavior, corporate failure, corporate governance, decision making, values

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Authors: Suyeb Ahmed Khan, Mahmood Mian

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Simulation plays an important role during all phases of the design and engineering of communications systems, from early stages of conceptual design through the various stages of implementation, testing, and fielding of the system. In the present paper, a simulation model has been constructed for the WCDMA system in order to evaluate the performance. This model describes multiusers effects and calculation of BER (Bit Error Rate) in 3G mobile systems using Simulink MATLAB 7.1. Gaussian Approximation defines the multi-user effect on system performance. BER has been analyzed with comparison between transmitting data and receiving data.

Keywords: WCDMA, simulations, BER, MATLAB

Procedia PDF Downloads 572

Authors: Gerald Todd

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Recent advances in random epistemologies and ubiquitous theory have paved the way for web services. Given the current status of linear-time communication, cyberinformaticians compellingly desire the exploration of link-level acknowledgements. In order to realize this purpose, we concentrate our efforts on disconfirming that DHTs and model checking are mostly incompatible.

Keywords: LAN, cyberinformatics, model checking, communication

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: Hong Zeng

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In the process of popularization of higher education, it is necessary to innovate teaching methods in order to make the students cultivated suitable for the needs of social development. This paper discusses the limitations and shortcomings of the traditional teaching method of teaching approach to a person's aptitude, personality, and interest and introduces the new teaching method of teaching approach to a person's personality. The teaching approach to a person's personality is a target teaching method that aims to develop students' potential and cultivate professional talents. Therefore, teachers should be professional and can adopt modern teaching methods from the Internet so that students can clearly understand the course and the knowledge structure. Finally, the students using new teaching methods can enhance their motivation to study and quickly acquire professional skills.

Keywords: higher education, personality, target education, student-centered

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Authors: Samuel Emeka Anarah, Kingsley Nnaemeka Ogbu, Obasi Arinze

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Quantifying the hydrological response due to changes in climate change is imperative for proper management of water resources within a watershed. The impact of climate change on the hydrology of the Upper Ebony River (UER) watershed, South East Nigeria, was studied using the Soil and Water Assessment Tool (SWAT) hydrological model. A climatological time series analysis from 1985 - 2014 using non-parametric test showed significant negative trends in precipitation and relative humidity trend while minimum and maximum temperature, solar radiation and wind speed showed significant positive trends. Future hypothetical land-use change scenarios (Scenarios 1, 2, 3 and 4) representing urbanization and conversion of forest to agricultural land were combined with future downscaled climate model (CSIRO-Mk3-6-0) and simulated in SWAT model. Relative to the Baseline scenario (2005 - 2014), the results showed a decrease in streamflow by 10.29%, 26.20%, 11.80% and 26.72% for Scenarios 1, 2, 3, and 4 respectively. Model results suggest development of adaptation strategies to cope with the predicted hydrological conditions under future climate change in the watershed.

Keywords: climate change, hydrology, runoff, SWAT model

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Authors: Hong Lu, Xiong Xiao

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Shaft parts are widely used in machinery industry, however, bending deformation often occurred when this kind of parts is being heat treated. This parts needs to be straightened to meet the requirement of straightness. As for the pressure straightening process, a good straightening stroke algorithm is related to the precision and efficiency of straightening process. In this paper, the relationship between straightening load and deflection during the straightening process is analyzed, and the mathematical model of the straightening process has been established. By the mathematical model, the iterative method is used to solve the straightening stroke. Compared to the traditional straightening stroke algorithm, straightening stroke calculated by this method is much more precise; because it can adapt to the change of material performance parameters. Considering that the straightening method is widely used in the mass production of the shaft parts, knowledge base is used to store the data of the straightening process, and a straightening stroke algorithm based on empirical data is set up. In this paper, the straightening process control model which combine the straightening stroke method based on iteration and straightening stroke algorithm based on empirical data has been set up. Finally, an experiment has been designed to verify the straightening process control model.

Keywords: straightness, straightening stroke, deflection, shaft parts

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Authors: Manoj M. Sarode, Sharad P. Jadhav, Mukesh D. Patil, Pushparaj S. Suryawanshi

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Even though the PID controller is widely used in industrial process, tuning of PID parameters are not easy. It is a time consuming and requires expert people. Another drawback of PID controller is that process dynamics might change over time. This can happen due to variation of the process load, normal wear and tear etc. To compensate for process behavior change over time, expert users are required to recalibrate the PID gains. Implementation of model based controllers usually needs a process model. Identification of process model is time consuming job and no guaranty of model accuracy. If the identified model is not accurate, performance of the controller may degrade. Model based controllers are quite expensive and the whole procedure for the implementation is sometimes tedious. To eliminate such issues Autotuning PID controller becomes vital element. Software based Relay Feedback Autotuning Controller proves to be efficient, upgradable and maintenance free controller. In Relay Feedback Autotune controller PID parameters can be achieved with a very short span of time. This paper presents the real time implementation of LabVIEW based Relay Feedback Autotuning PID controller. It is successfully developed and implemented to control level of a laboratory setup. Its performance is analyzed for different setpoints and found satisfactorily.

Keywords: autotuning, PID, liquid level control, recalibrate, labview, controller

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Authors: Imali T. Jayamanne, K. P. Asoka Ramanayake

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Transition from tertiary level education to employment is one of the challenges that many fresh university graduates face after graduation. The transition period or the waiting time to obtain the first employment varies with the socio-economic factors and the general characteristics of a graduate. Compared to other fields of study, Arts graduates in Sri Lanka, have to wait a long time to find their first employment. The objective of this study is to identify the determinants of the transition from higher education to employment of these graduates using survival models. The study is based on a survey that was conducted in the year 2016 on a stratified random sample of Arts graduates from Sri Lankan universities who had graduated in 2012. Among the 469 responses, 36 (8%) waiting times were interval censored and 13 (3%) were right censored. Waiting time for the first employment varied between zero to 51 months. Initially, the log-rank and the Gehan-Wilcoxon tests were performed to identify the significant factors. Gender, ethnicity, GCE Advanced level English grade, civil status, university, class received, degree type, sector of first employment, type of first employment and the educational qualifications required for the first employment were significant at 10%. The Cox proportional hazards model was fitted to model the waiting time for first employment with these significant factors. All factors, except ethnicity and type of employment were significant at 5%. However, since the proportional hazard assumption was violated, the lognormal Accelerated failure time (AFT) model was fitted to model the waiting time for the first employment. The same factors were significant in the AFT model as in Cox proportional model.

Keywords: AFT model, first employment, proportional hazard, survey design, waiting time

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Authors: Trevor Stephen, Joshua D. Aceves, David Guyer, Jona Jacobson

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As a profession, social work has much to offer individuals, groups, and organizations. A multidisciplinary approach to understanding and solving complex challenges and a commitment to developing and training ethical practitioners outlines characteristics of a profession embedded with leadership skills. This presentation will take an overview of the historical context of social work leadership, examine social work as a unique leadership model composed of its qualities and theories that inform effective leadership capability as it relates to our code of ethics. Reflect critically on leadership theories and their foundational comparison. Finally, a look at recommendations and implementation to social work education and practice. Similar to defining leadership, there is no universally accepted definition of social work leadership. However, some distinct traits and characteristics are essential. Recent studies help set the stage for this research proposal because they measure views on effective social work leadership among social work and non-social leaders and followers. However, this research is interested in working backward from that approach and examining social workers' leadership preparedness perspectives based solely on social work training, competencies, values, and ethics. Social workers understand how to change complex structures and challenge resistance to change to improve the well-being of organizations and those they serve. Furthermore, previous studies align with the idea of practitioners assessing their skill and capacity to engage in leadership but not to lead. In addition, this research is significant because it explores aspiring social work leaders' competence to translate social work practice into direct leadership skills. The research question seeks to answer whether social work training and competencies are sufficient to determine whether social workers believe they possess the capacity and skill to engage in leadership practice. Aim 1: Assess whether social workers have the capacity and skills to assume leadership roles. Aim 2: Evaluate how the development of social workers is sufficient in defining leadership. This research intends to reframe the misconception that social workers do not possess the capacity and skills to be effective leaders. On the contrary, social work encompasses a framework dedicated to lifelong development and growth. Social workers must be skilled, competent, ethical, supportive, and empathic. These are all qualities and traits of effective leadership, whereas leaders are in relation with others and embody partnership and collaboration with followers and stakeholders. The proposed study is a cross-sectional quasi-experimental survey design that will include the distribution of a multi-level social work leadership model and assessment tool. The assessment tool aims to help define leadership in social work using a Likert scale model. A cross-sectional research design is appropriate for answering the research questions because the measurement survey will help gather data using a structured tool. Other than the proposed social work leadership measurement tool, there is no other mechanism based on social work theory and designed to measure the capacity and skill of social work leadership.

Keywords: leadership competencies, leadership education, multi-level social work leadership model, social work core values, social work leadership, social work leadership education, social work leadership measurement tool

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Authors: Atheer Al-Nuaimi, Harry Evdorides

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Every day many people die or get disabled or injured on roads around the world, which necessitates more specific treatments for transportation safety issues. International road assessment program (iRAP) model is one of the comprehensive road safety models which accounting for many factors that affect road safety in a cost-effective way in low and middle income countries. In iRAP model road safety has been divided into five star ratings from 1 star (the lowest level) to 5 star (the highest level). These star ratings are based on star rating score which is calculated by iRAP methodology depending on road attributes, traffic volumes and operating speeds. The outcome of iRAP methodology are the treatments that can be used to improve road safety and reduce fatalities and serious injuries (FSI) numbers. These countermeasures can be used separately as a single countermeasure or mix as multiple countermeasures for a location. There is general agreement that the adequacy of a countermeasure is liable to consistent losses when it is utilized as a part of mix with different countermeasures. That is, accident diminishment appraisals of individual countermeasures cannot be easily added together. The iRAP model philosophy makes utilization of a multiple countermeasure adjustment factors to predict diminishments in the effectiveness of road safety countermeasures when more than one countermeasure is chosen. A multiple countermeasure correction factors are figured for every 100-meter segment and for every accident type. However, restrictions of this methodology incorporate a presumable over-estimation in the predicted crash reduction. This study aims to adjust this correction factor by developing new models to calculate the effect of using multiple countermeasures on the number of fatalities for a location or an entire road. Regression models have been used to establish relationships between crash frequencies and the factors that affect their rates. Multiple linear regression, negative binomial regression, and Poisson regression techniques were used to develop models that can address the effectiveness of using multiple countermeasures. Analyses are conducted using The R Project for Statistical Computing showed that a model developed by negative binomial regression technique could give more reliable results of the predicted number of fatalities after the implementation of road safety multiple countermeasures than the results from iRAP model. The results also showed that the negative binomial regression approach gives more precise results in comparison with multiple linear and Poisson regression techniques because of the overdispersion and standard error issues.

Keywords: international road assessment program, negative binomial, road multiple countermeasures, road safety

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Authors: H. Meddah, M. Berediaf-Bourahla, B. El-Djouzi, N. Bourahla

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Shear walls made of cold formed steel are used as lateral force resisting components in residential and low-rise commercial and industrial constructions. The seismic design analysis of such structures is often complex due to the slenderness of members and their instability prevalence. In this context, a simplified modeling technique across the panel is proposed by using the finite element method. The approach is based on idealizing the whole panel by a nonlinear shear link element which reflects its shear behavior connected to rigid body elements which transmit the forces to the end elements (studs) that resist the tension and the compression. The numerical model of the shear wall panel was subjected to cyclic loads in order to evaluate the seismic performance of the structure in terms of lateral displacement and energy dissipation capacity. In order to validate this model, the numerical results were compared with those from literature tests. This modeling technique is particularly useful for the design of cold formed steel structures where the shear forces in each panel and the axial forces in the studs can be obtained using spectrum analysis.

Keywords: cold-formed steel, cyclic loading, modeling technique, nonlinear analysis, shear wall panel

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Authors: Sudawan Somjai

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The purpose of this paper was to find an appropriate outsourcing system model for the Thai electrical appliances industry. The objective was to increase competitive capability of the industry with an outsourcing system. The population for this study was the staff in the selected 10 companies in Thai electrical appliances industry located in Bangkok and the eastern part of Thailand. Data collecting techniques included in-depth interviews, focus group and storytelling techniques. The data was collected from 5 key informants from each company, making a total of 50 informants. The findings revealed that an outsourcing model would consist of important factors including outsourcing system, labor flexibility, capability of business process, manpower management efficiency, cost reduction, business risk elimination, core competency and competitiveness. Different suggestions were made as well in this research paper.

Keywords: outsourcing system, model, Thailand, electrical appliances industry

Procedia PDF Downloads 579

Authors: Rajamani Doraiswami, Lahouari Cheded

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Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Jaemoon Lim

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To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.

Keywords: chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Nermine A. Harraz, Aliaa Abouali

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The retail stores put up for sale multiple items while the spaces in the backroom and display areas constitute a scarce resource. Availability, volume, and location of the product displayed in the showroom influence the customer’s demand. Managing these operations individually will result in sub-optimal overall retail store’s profit; therefore, a non-linear integer programming model (NLIP) is developed to determine the inventory replenishment and shelf space allocation decisions that together maximize the retailer’s profit under shelf space and backroom storage constraints taking into consideration that the demand rate is positively dependent on the amount and location of items displayed in the showroom. The developed model is solved using LINGO® software. The NLIP model is implemented in a real world case study in a large retail outlet providing a large variety of products. The proposed model is validated and shows logical results when using the experimental data collected from the market.

Keywords: retailing management, inventory replenishment, shelf space allocation, showroom, backroom

Procedia PDF Downloads 338

Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: John Ayoade

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Cloud computing is a model that enables the delivery of on-demand computing resources such as networks, servers, storage, applications and services over the internet. Cloud Computing is a relatively growing concept that presents a good number of benefits for its users; however, it also raises some security challenges which may slow down its use. In this paper, we identify some of those security issues that can serve as barriers to realizing the full benefits that cloud computing can bring. One of the key security problems is security trust. A security trust model is proposed that can enhance the confidence that users need to fully trust the use of public and mobile cloud computing and maximize the potential benefits that they offer.

Keywords: cloud computing, trust, security, certificate authority, PKI

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Authors: Mohadeseh Shojaei Shahrokhabadi, Ding-Geng (Din) Chen

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Positive continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical cost data. To jointly model semi-continuous longitudinal cost data and survival data and to provide marginalized covariate effect estimates, a marginalized two-part joint model (MTJM) has been developed for outcome variables with lognormal distributions. In this paper, we propose MTJM models for outcome variables from a generalized gamma (GG) family of distributions. The GG distribution constitutes a general family that includes approximately all of the most frequently used distributions like the Gamma, Exponential, Weibull, and Log Normal. In the proposed MTJM-GG model, the conditional mean from a conventional two-part model with a three-parameter GG distribution is parameterized to provide the marginal interpretation for regression coefficients. In addition, MTJM-gamma and MTJM-Weibull are developed as special cases of MTJM-GG. To illustrate the applicability of the MTJM-GG, we applied the model to a set of real electronic health record data recently collected in Iran, and we provided SAS code for application. The simulation results showed that when the outcome distribution is unknown or misspecified, which is usually the case in real data sets, the MTJM-GG consistently outperforms other models. The GG family of distribution facilitates estimating a model with improved fit over the MTJM-gamma, standard Weibull, or Log-Normal distributions.

Keywords: marginalized two-part model, zero-inflated, right-skewed, semi-continuous, generalized gamma

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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Authors: Djamel Ouzandja, Boualem Tiliouine

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The safety evaluation of the concrete gravity dams subjected to seismic excitations is really very complex as the earthquake response of the concrete gravity dam depends upon its contraction joints with foundation soil. This paper presents the seismic response of concrete gravity dams considering friction contact and welded contact. Friction contact is provided using contact elements. Two-dimensional (2D) finite element model of Oued Fodda concrete gravity dam, located in Chlef at the west of Algeria, is used for this purpose. Linear and nonlinear analyses considering dam-foundation soil interaction are performed using ANSYS software. The reservoir water is modeled as added mass using the Westergaard approach. The Drucker-Prager model is preferred for dam and foundation rock in nonlinear analyses. The surface-to-surface contact elements based on the Coulomb's friction law are used to describe the friction. These contact elements use a target surface and a contact surface to form a contact pair. According to this study, the seismic analysis of concrete gravity dams including base sliding. When the friction contact is considered in joints, the base sliding displacement occurs along the dam-foundation soil contact interface. Besides, the base sliding may generally decrease the principal stresses in the dam.

Keywords: concrete gravity dam, dynamic soil-structure interaction, friction contact, sliding

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Authors: Nursel Koyuncu, Nihal Ata Tutkun

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Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: Prat Yotyawilai, Taratip Suwannasart

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Business Process Model and Notation (BPMN) is more important in the business process and creating functional models, and is a standard for OMG, which becomes popular in various organizations and in education. Researches related to software testing based on models are prominent. Although most researches use the UML model in software testing, not many researches use the BPMN Model in creating test cases. Therefore, this research proposes a design of a tool for generating test cases from the BPMN. The model is analyzed and the details of the various components are extracted before creating a flow graph. Both details of components and the flow graph are used in generating test cases.

Keywords: software testing, test case, BPMN, flow graph

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Authors: Amorn Kritsanaphan

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This paper illustrates the decentralization of cultural heritage management in local Thailand, a place similar to other middle- income developing countries characterized by rapid tourism-industrialization, weakness formal state institutions and procedures, and intensity use of the cultural heritage resources. The author conducted field research in local Thailand, principally using qualitative primary data gathering. These were combined with records reviews and content analysis of documents. The author also attended local public meetings, and social activities, and interacted casually with local residents and governments. Cultural heritage management has been supposed to improve through multi-stakeholder participation and decentralization. However, processes and outcomes are far from being straightforward and depend on a variety of contingencies and contexts involved. Multi-stakeholder and participatory approach in decentralization of the cultural heritage management in Thailand have pushed to the forefront and sharpened a number of existing problems. However, under the decentralization, the most significant contribution has been in creating real political space where various local stakeholders have become active, respond and address their concerns in various ways vis-à-vis cultural heritage problems. Improving cultural heritage sustainability and viability of local livelihoods through decentralization and participatory approach is by no means certain. However, the shift instead creates spaces potent with possibilities for a meaningful and constructive engagement between and among local state and non-state actors that can lead to synergies and positive outcomes.

Keywords: decentralization, participatory approach, cultural heritage management, multi-stakeholder approach

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Authors: Assem M. F. Sallam, Ah. El-S. Makled

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This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: launch vehicle modeling, launch vehicle trajectory, mathematical modeling, Matlab- Simulink

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Authors: Alena Kulikova, Leonid Parmaksiz, Ekaterina Orel

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Social and emotional skills are considered by modern researchers as predictors of a person's success both in specific areas of activity and in the life of a person as a whole. The popularity of this scientific direction ensures the emergence of a large number of practices aimed at developing and evaluating socio-emotional skills. Assessment of social and emotional development is carried out at the national level, as well as at the level of individual regions and institutions. Despite the fact that many of the already existing social and emotional skills assessment tools are quite convenient and reliable, there are now more and more new technologies and task formats which improve the basic characteristics of the tools. Thus, the goal of the current study is to develop a tool for assessing social and emotional skills such as emotion recognition, emotion regulation, empathy and a culture of self-care. To develop a tool assessing social and emotional skills, Rasch-Gutman scenario-based approach was used. This approach has shown its reliability and merit for measuring various complex constructs: parental involvement; teacher practices that support cultural diversity and equity; willingness to participate in the life of the community after psychiatric rehabilitation; educational motivation and others. To assess emotion recognition, we used a situational judgment task based on OCC (Ortony, Clore, and Collins) emotions theory. The main advantage of these two approaches compare to classical Likert scales is that it reduces social desirability in answers. A field test to check the psychometric properties of the developed instrument was conducted. The instrument was developed for the presidential autonomous non-profit organization “Russia - Land of Opportunity” for nationwide soft skills assessment among higher education students. The sample for the field test consisted of 500 people, students aged from 18 to 25 (mean = 20; standard deviation 1.8), 71% female. 67% of students are only studying and are not currently working and 500 employed adults aged from 26 to 65 (mean = 42.5; SD 9), 57% female. Analysis of the psychometric characteristics of the scales was carried out using the methods of IRT (Item Response Theory). A one-parameter rating scale model RSM (Rating scale model) and Graded Response model (GRM) of the modern testing theory were applied. GRM is a polyatomic extension of the dichotomous two-parameter model of modern testing theory (2PL) based on the cumulative logit function for modeling the probability of a correct answer. The validity of the developed scales was assessed using correlation analysis and MTMM (multitrait-multimethod matrix). The developed instrument showed good psychometric quality and can be used by HR specialists or educational management. The detailed results of a psychometric study of the quality of the instrument, including the functioning of the tasks of each scale, will be presented. Also, the results of the validity study by MTMM analysis will be discussed.

Keywords: social and emotional skills, psychometrics, MTMM, IRT

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Authors: Haiyang Su, Kun Qian

Abstract:

We developed a novel plasmonic matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxin in complex biological emulsion samples. We used silver nanoshells (SiO₂@Ag) with optimized structures as matrices and achieved direct analysis of ~6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, superior to the conventional biochemical methods currently in use. Our approach contributed to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real case bio-analysis.

Keywords: plasmonic materials, laser desorption/ionization, mass spectrometry, small nutrients, toxins

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

Procedia PDF Downloads 106

Authors: Aaron G. Laylo

Abstract:

This paper mainly assumes that social entrepreneurship contributes significantly to youth empowerment i.e., work and community engagement. Two questions are thus raised in order to establish this hypothesis: 1) First, how does social entrepreneurship contribute to youth empowerment?; and 2) secondly, why is social entrpreneurship significantly incremental to youth empowerment? This research aims a) to investigate on the social aspect of entrepreneurship; b) to explore challenges in youth empowerment particularly in respect to work and community engagement; and c) to inquire into whether social enterprises have truly served as a catalyst for, thus an effective response to, youth empowerment. It must be emphasized that young people, which comprise 1.8 billion in a world of seven billion are an asset; Apparently, how to maximize that potential is crucial. By utilizing exploratory research design, the paper endeavors to generate new ideas in regards to both components, develop tentative theories on social entrepreneurship, and refine certain issues that are under observation and seek scholarly attention— a rather emerging phenomenon vis a vis the challenge to empower a significant cluster of the society. Case studies will be utilized as an approach in order to comparatively analyze youth-driven social enterprises in the Philippines that have been widely recognized as successful insofar as social impact is concerned. As most scholars attested, social entrepreneurship is still at its infancy stage. Youth empowerment, meanwhile, is yet a vast area to explore insofar as academic research is concerned. Programs and projects that advocate the pursuit of these components abound. However, academic research is yet to be undertaken to see and understand their social and economic relevance. This research is also an opportunity for scholars to explore, understand, and make sense of the promise that lies in social entrepreneurship research and how it can serve as a catalyst for youth empowerment. Youth-driven social enterprises can be an influential tool in sustaining development across the globe as they intend to provide opportunities for optimal economic productivity that recognizes social inclusion. Ultimately, this study should be able to contribute to both research and development-in-practice communities for the greater good of the society. By establishing the nexus between these two components, the research may contribute to fostering greater exploration of the benefits that both may yield to human progress as well as the gaps that have to be filled in by various policy stakeholders relevant to these units.

Keywords: social entpreneurship, youth, empowerment, social inclusion

Procedia PDF Downloads 285