A New Intelligent Strategy to Integrated Control of AFS/DYC Based on Fuzzy Logic

An integrated vehicle dynamics control system is developed in this paper by a combination of active front steering (AFS) and direct yaw-moment control (DYC) based on fuzzy logic control. The control system has a hierarchical structure consisting of two layers. A fuzzy logic controller is used in the upper layer (yaw rate controller) to keep the yaw rate in its desired value. The yaw rate error and its rate of change are applied to the upper controlling layer as inputs, where the direct yaw moment control signal and the steering angle correction of the front wheels are the outputs. In the lower layer (fuzzy integrator), a fuzzy logic controller is designed based on the working region of the lateral tire forces. Depending on the directions of the lateral forces at the front wheels, a switching function is activated to adjust the scaling factor of the fuzzy logic controller. Using a nonlinear seven degrees of freedom vehicle model, the simulation results illustrate considerable improvements which are achieved in vehicle handling through the integrated AFS/DYC control system in comparison with the individual AFS or DYC controllers.

Response of Fully Backed Sandwich Beams to Low Velocity Transverse Impact

This paper describes analysis of low velocity transverse impact on fully backed sandwich beams with composite faces from Eglass/epoxy and cores from Polyurethane or PVC. Indentation on sandwich beams has been analyzed with the existing theories and modeled with the FE code ABAQUS, also loadings have been done experimentally to verify theoretical results. Impact on fully backed has been modeled in two cases of impactor energy with SDOF model (single-degree-of-freedom) and indentation stiffness: lower energy for elastic indentation of sandwich beams and higher energy for plastic area in indentation. Impacts have been modeled by ABAQUS. Impact results can describe response of beam in terms of core and faces thicknesses, core material, indentor energy and energy absorbed. The foam core is modeled using the crushable foam material model and response of the foam core is experimentally characterized in uniaxial compression with higher velocity loading to define quasi impact behaviour.

Firm Performance of Thai Cuisines in Bangkok, Thailand: Contribution to the Tourism Industry

This study is a descriptive-normative research. It attempted to investigate the restaurants’ firm performance in terms of the customers and restaurant personnel’s degree of satisfaction. A total of 12 restaurants in Bangkok, Thailand that offer Thai cuisine were included in this study. It involved 24 stockholders/managers, 120 subordinates and 360 customers. General Managers and restaurants’ stockholders, 10 staffs, and 30 costumers for each restaurant were chosen for random sampling. This study found that respondents are slightly satisfied with their work environment but are generally satisfied with the accessibility to transportation, to malls, convenience, safety, recreation, noise-free, and attraction; customers find the Quality of Food in most Thai Cuisines like services, prices of food, sales promotion, and capital and length of service satisfactory. Therefore, both stockholder-related and personnel-related factors which are influenced by restaurant, personnel, and customer-related factors are partially accepted whereas; customer-related factors which are influenced by restaurant, personnel and customer-related factors are rejected.

Class Outliers Mining: Distance-Based Approach

In large datasets, identifying exceptional or rare cases with respect to a group of similar cases is considered very significant problem. The traditional problem (Outlier Mining) is to find exception or rare cases in a dataset irrespective of the class label of these cases, they are considered rare events with respect to the whole dataset. In this research, we pose the problem that is Class Outliers Mining and a method to find out those outliers. The general definition of this problem is “given a set of observations with class labels, find those that arouse suspicions, taking into account the class labels". We introduce a novel definition of Outlier that is Class Outlier, and propose the Class Outlier Factor (COF) which measures the degree of being a Class Outlier for a data object. Our work includes a proposal of a new algorithm towards mining of the Class Outliers, presenting experimental results applied on various domains of real world datasets and finally a comparison study with other related methods is performed.

Researching on the Grey Incidence among the Macroscopic Agents in the Logistics Industry System

Quantitative researching on the degree of incidence between the logistics industry and relevant macroscopic system elements is the basis of reasonable and scientific policy on industrial development. In the light of the macro-level, the logistics industry system is consisted of multiple macroscopic agents such as macro-economic, infrastructure, social environment, market demanding, the traditional industry, industry life cycle, policy , system and so on. This paper studies the grey incidence among the macroscopic agents in the logistics industry system. It is demonstrated that the releasing of the logistics services from the logistics outsourcing enterprises determines the growth of the logistics size. Although the information and communication technology is able to promote the formation of the modern logistics industry to some extent, the development of the modern logistics industry depends more on the development of national economy and the investment in the capital assets of the logistics industry.

Five Vital Factors Related to Employees’ Job Performance

The purpose of this research was to study five vital factors related to employees’ job performance. A total of 250 respondents were sampled from employees who worked at a public warehouse organization, Bangkok, Thailand. Samples were divided into two groups according to their work experience. The average working experience was about 9 years for group one and 28 years for group two. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, t-test analysis, one way ANOVA, and Pearson Product-moment correlation coefficient. Data were analyzed by using Statistical Package for the Social Sciences. The findings disclosed that the majority of respondents were female between 23- 31 years old, single, and hold an undergraduate degree. The average income of respondents was less than 30,900 baht. The findings also revealed that the factors of organization chart awareness, job process and technology, internal environment, employee loyalty, and policy and management were ranked as medium level. The hypotheses testing revealed that difference in gender, age, and position had differences in terms of the awareness of organization chart, job process and technology, internal environment, employee loyalty, and policy and management in the same direction with low level.

Data Envelopment Analysis under Uncertainty and Risk

Data Envelopment Analysis (DEA) is one of the most widely used technique for evaluating the relative efficiency of a set of homogeneous decision making units. Traditionally, it assumes that input and output variables are known in advance, ignoring the critical issue of data uncertainty. In this paper, we deal with the problem of efficiency evaluation under uncertain conditions by adopting the general framework of the stochastic programming. We assume that output parameters are represented by discretely distributed random variables and we propose two different models defined according to a neutral and risk-averse perspective. The models have been validated by considering a real case study concerning the evaluation of the technical efficiency of a sample of individual firms operating in the Italian leather manufacturing industry. Our findings show the validity of the proposed approach as ex-ante evaluation technique by providing the decision maker with useful insights depending on his risk aversion degree.

Factors Related to the Satisfaction of Car Consumers

The objective of this research was to study the factors related to the satisfaction of consumers who purchased a Toyota SUV Fortuner. This paper was a survey data which collected 400 samples from 65 car dealerships. The survey was conducted mainly in Bangkok, Thailand. The statistics utilized in this paper included percentage, mean, standard deviation and Pearson Product-Moment. The findings revealed that the majority of respondent were male with an undergraduate degree, married and live together. The average income of the respondents was between 20,001 - 30,000 baht. Most of them worked for private companies. Most of them had a family with the average of 4 members. The hypotheses testing revealed that the factors of marketing mix in terms of product (ability, gas mileage, and safety) were related to overall satisfaction at the medium level. However, the findings also revealed that the factors of marketing mix in terms of product (image), price, and promotion, and service center were related to the overall satisfaction at the low level.

Simulating Pathogen Transport with in a Naturally Ventilated Hospital Ward

Understanding how airborne pathogens are transported through hospital wards is essential for determining the infection risk to patients and healthcare workers. This study utilizes Computational Fluid Dynamics (CFD) simulations to explore possible pathogen transport within a six-bed partitioned Nightingalestyle hospital ward. Grid independence of a ward model was addressed using the Grid Convergence Index (GCI) from solutions obtained using three fullystructured grids. Pathogens were simulated using source terms in conjunction with a scalar transport equation and a RANS turbulence model. Errors were found to be less than 4% in the calculation of air velocities but an average of 13% was seen in the scalar field. A parametric study of variations in the pathogen release point illustrated that its distribution is strongly influenced by the local velocity field and the degree of air mixing present.

Harmful Effect of Ambient Ozone on Growth and Productivity of Two Legume Crops Visia Faba, and Pisum sativum in Riyadh City, K.S.A.

Ozone (O3) is considered as one of the most phytotoxic pollutants with deleterious effects on living and non living components of Ecosystems. It reduces growth and yield of many crops as well as alters the physiology and crop quality. The present study described series of experiments to investigate the effects of ambient O3 at different locations with different ambient levels of O3 depending on proximity to pollutant source and ranged between 17 ppb/h in control experiment to 112 ppb/h in industrial area respectively. The ambient levels in other three locations (King Saud University botanical garden, King Fahd Rd, and Almanakh Garden) were 61,61,77 ppb/h respectively. Tow legume crops species (vicia vaba L ; and Pisum sativum) differ in their phenology and sensitivity were used. The results showed a significant negative effect to ozone on morphology, number of injured leaves, growth and productivity with a difference in the degree of response depending on the plant type. Visia Faba showed sensitivity to ozone to number and leaf area and the degree of injury leaves 3, pisum sativum show higher sensitivity for the gas for degree of injury 1,The relative growth rate and seed weight, it turns out there is no significant difference between the two plants in plant height and number of seeds.

A Comparison of Different Soft Computing Models for Credit Scoring

It has become crucial over the years for nations to improve their credit scoring methods and techniques in light of the increasing volatility of the global economy. Statistical methods or tools have been the favoured means for this; however artificial intelligence or soft computing based techniques are becoming increasingly preferred due to their proficient and precise nature and relative simplicity. This work presents a comparison between Support Vector Machines and Artificial Neural Networks two popular soft computing models when applied to credit scoring. Amidst the different criteria-s that can be used for comparisons; accuracy, computational complexity and processing times are the selected criteria used to evaluate both models. Furthermore the German credit scoring dataset which is a real world dataset is used to train and test both developed models. Experimental results obtained from our study suggest that although both soft computing models could be used with a high degree of accuracy, Artificial Neural Networks deliver better results than Support Vector Machines.

An AHP-Delphi Multi-Criteria Usage Cases Model with Application to Citrogypsum Decisions, Case Study: Kimia Gharb Gostar Industries Company

Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.

Drivers of Customer Satisfaction in an Industrial Company from Marketing Aspect

One of the basic concepts in marketing is the concept of meeting customers- needs. Since customer satisfaction is essential for lasting survival and development of a business, screening and observing customer satisfaction and recognizing its underlying factors must be one of the key activities of every business. The purpose of this study is to recognize the drivers that effect customer satisfaction in a business-to-business situation in order to improve marketing activities. We conducted a survey in which 93 business customers of a manufacturer of Diesel Generator in Iran participated and they talked about their ideas and satisfaction of supplier-s services related to its products. We developed the measures for drivers of satisfaction first by as investigative research (by means of feedback from executives and customers of sponsoring firm). Then based on these measures, we created a mail survey, and asked the respondents to explain their opinion about the sponsoring firm which was a supplier of diesel generator and similar products. Furthermore, the survey required the participants to mention their functional areas and their company features. In Conclusion we found that there are three drivers for customer satisfaction, which are reliability, information about product, and commercial features. Buyers/users from different functional areas attribute different degree of importance to the last two drivers. For instance, people from buying and management areas believe that commercial features are more important than information about products. But people in engineering, maintenance and production areas believe that having information about products is more important than commercial aspects. Marketing experts should consider the attribute of customers regarding information about the product and commercial features to improve market share.

Working Motivation Factors Affecting Job Performance Effectiveness

The purpose of this paper was to study motivation factors affecting job performance effectiveness. This paper drew upon data collected from an Internal Audit Staffs of Internal Audit Line of Head Office of Krung Thai Public Company Limited. Statistics used included frequency, percentage, mean and standard deviation, t-test, and one-way ANOVA test. The finding revealed that the majority of the respondents were female of 46 years of age and over, married and live together, hold a bachelor degree, with an average monthly income over 70,001 Baht. The majority of respondents had over 15 years of work experience. They generally had high working motivation as well as high job performance effectiveness. The hypotheses testing disclosed that employees with different working status had different level of job performance effectiveness at a 0.01 level of significance. Working motivation factors had an effect on job performance in the same direction with high level. Individual working motivation included working completion, reorganization, working progression, working characteristic, opportunity, responsibility, management policy, supervision, relationship with their superior, relationship with co-worker, working position, working stability, safety, privacy, working conditions, and payment. All of these factors related to job performance effectiveness in the same direction with medium level.

Information Gain Ratio Based Clustering for Investigation of Environmental Parameters Effects on Human Mental Performance

Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.

Investigation on the HRSG Installation at South Pars Gas Complex Phases 2&3

In this article the investigation about installation heat recovery steam generation (HRSG) on the exhaust of turbo generators of phases 2&3 at South Pars Gas Complex is presented. The temperature of exhaust gas is approximately 665 degree centigrade, Installation of heat recovery boiler was simulated in ThermoFlow 17.0.2 software, based on test operation data and the equipments site operation conditions in Pars exclusive economical energy area, the affect of installation HRSG package on the available gas turbine and its operation parameters, ambient temperature, the exhaust temperatures steam flow rate were investigated. Base on the results recommended HRSG package should have the capacity for 98 ton per hour high pressure steam generation this refinery, by use of exhaust of three gas turbines for each package in operation condition of each refinery at 30 degree centigrade. Besides saving energy this project will be an Environment-Friendly project. The Payback Period is estimated approximately 1.8 year, with considering Clean Development Mechanism.

Exploring Structure of Mobile Ecosystem: Inter-Industry Network Analysis Approach

As increasing importance of symbiosis and cooperation among mobile communication industries, the mobile ecosystem has been especially highlighted in academia and practice. The structure of mobile ecosystem is quite complex and the ecological role of actors is important to understand that structure. In this respect, this study aims to explore structure of mobile ecosystem in the case of Korea using inter-industry network analysis. Then, the ecological roles in mobile ecosystem are identified using centrality measures as a result of network analysis: degree of centrality, closeness, and betweenness. The result shows that the manufacturing and service industries are separate. Also, the ecological roles of some actors are identified based on the characteristics of ecological terms: keystone, niche, and dominator. Based on the result of this paper, we expect that the policy makers can formulate the future of mobile industry and healthier mobile ecosystem can be constructed.

Generation of Sets of Synthetic Classifiers for the Evaluation of Abstract-Level Combination Methods

This paper presents a new technique for generating sets of synthetic classifiers to evaluate abstract-level combination methods. The sets differ in terms of both recognition rates of the individual classifiers and degree of similarity. For this purpose, each abstract-level classifier is considered as a random variable producing one class label as the output for an input pattern. From the initial set of classifiers, new slightly different sets are generated by applying specific operators, which are defined at the purpose. Finally, the sets of synthetic classifiers have been used to estimate the performance of combination methods for abstract-level classifiers. The experimental results demonstrate the effectiveness of the proposed approach.

Applying GQM Approach towards Development of Criterion-Referenced Assessment Model for OO Programming Courses

The most influential programming paradigm today is object oriented (OO) programming and it is widely used in education and industry. Recognizing the importance of equipping students with OO knowledge and skills, it is not surprising that most Computer Science degree programs offer OO-related courses. How do we assess whether the students have acquired the right objectoriented skills after they have completed their OO courses? What are object oriented skills? Currently none of the current assessment techniques would be able to provide this answer. Traditional forms of OO programming assessment provide a ways for assigning numerical scores to determine letter grades. But this rarely reveals information about how students actually understand OO concept. It appears reasonable that a better understanding of how to define and assess OO skills is needed by developing a criterion referenced model. It is even critical in the context of Malaysia where there is currently a growing concern over the level of competency of Malaysian IT graduates in object oriented programming. This paper discussed the approach used to develop the criterion-referenced assessment model. The model can serve as a guideline when conducting OO programming assessment as mentioned. The proposed model is derived by using Goal Questions Metrics methodology, which helps formulate the metrics of interest. It concluded with a few suggestions for further study.