Minimizing mean flowtime and makespan on master–slave systems

The master–slave scheduling model is a new model recently introduced by Sahni. It has many important applications in parallel computer scheduling and industrial settings such as semiconductor testing, machine scheduling, etc. In this model each job is associated with a preprocessing task, a slave task and a postprocessing task that must be executed in this order. While the preprocessing and postprocessing tasks are scheduled on the master machine, the slave tasks are scheduled on the slave machines. In this paper, we consider scheduling problems on single-master master–slave systems. We first strengthen some previously known complexity results for makespan problems, by showing them to be strongly NP-hard. We then show that the problem of minimizing the mean flowtime is strongly NP-hard even under severe constraints. Finally, we propose some heuristics for the mean flowtime and makespan problems subject to some constraints, and we analyze the worst-case performance of these heuristics.     

半胱氨酸处理对采后金针菇品质和抗氧化活性的影响

为了研究半胱氨酸处理对金针菇低温贮藏品质和抗氧化活性变化的影响,将新鲜金针菇分别采用15 mmol/L半胱氨酸和清水浸泡处理20 min后于2~3 ℃贮藏12 d,并定期检测相关理化指标。结果表明,15 mmol/L半胱氨酸处理能够抑制新鲜金针菇的呼吸强度和褐变度;延缓可溶性固形物和可溶性蛋白含量下降,并保持较低相对电导率;抑制了多酚氧化酶（polyphenol oxidase,PPO）活性和过氧化物酶（peroxidase,POD）活性,并保持较高的总酚和抗坏血酸含量,贮藏结束时,半胱氨酸处理组的PPO和POD活性比对照组分别降低了13.78%和26.49%,总酚和抗坏血酸含量分别为对照组的1.12和1.37倍;处理组提高了超氧化物歧化酶（superoxide dismutase,SOD）活性、谷胱甘肽还原酶活性以及1,1-二苯基-2-三硝基苯肼自由基（1,1-diphenyl-2-picrylhydrazyl,DPPH）清除率,对失重率无显著影响;相关性分析发现,处理组的呼吸强度与SOD活性、DPPH自由基清除率相关系数分别为?0.951和?0.903,呈显著（P<0.05）负相关。由此得出,低温贮藏期间,半胱氨酸处理能够降低金针菇内部物质的代谢速率,维持较高抗氧化能力和感官品质。     

Development of a knowledge-based system for materials management

In the past, many mistakes have been made in selecting the best materials for a given task. Thus, tools for humans to optimise the selection of materials will be valuable assets, particularly when the field of application is broad, the problem complex, the operating envelope variable, or the environment is aggressive. In this paper, a methodology for construction of a generic computer materials selector is described. A knowledge structure is presented in which materials selection and failure analysis are at opposite ends of a spectrum of materials performance. An example of the selection of a coating for marine use is given. Besides being of great value to designers, the tool is of considerable potential use for general materials information systems and computer-based learning modules.     

Predicting business failure using support vector machines with straightforward wrapper: A re-sampling study

Business failure prediction (BFP) is an effective tool to help financial institutions and relevant people to make the right decision in investments, especially in the current competitive environment. This topic belongs to a classification-type task, one of whose aims is to generate more accurate hit ratios. Support vector machine (SVM) is a statistical learning technique, whose advantage is its high generalization performance. The objective of this context is threefold. Firstly, SVM is used to predict business failure by utilizing a straightforward wrapper approach to help the model produce more accurate prediction. The wrapper approach is fulfilled by employing a forward feature selection method, composed of feature ranking and feature selection. Meanwhile, this work attempts to investigate the feasibility of using linear SVMs to select features for all SVMs in the wrapper since non-linear SVMs yield to over-fit the data. Finally, a robust re-sampling approach is used to evaluate model performances for the task of BFP in China. In the empirical research, performances of linear SVM, polynomial SVM, Gaussian SVM, and sigmoid SVM with the best filter of stepwise MDA, and wrappers respectively using linear SVM and non-linear SVMs as evaluating functions are to be compared. The results indicate that the non-linear SVM with radial basis function kernel and features selected by linear SVM compare significantly superiorly to all the other SVMs. Meanwhile, all SVMs with features selected by linear SVM produce at least as good performances as SVMs with other optimal features.     

An isolation enhanced PCA method with expert-based multivariate decoupling for sensor FDD in air-conditioning systems

Principal component analysis (PCA) has been found to be powerful in detecting sensor faults in multivariate processes, but it is inefficient in isolating faults due to its pure data-driven nature, especially when dealing with processes with strongly coupled multiple variables, such as the air-handling processes in typical variable air volume air conditioning systems. This paper presents an expert-based multivariate decoupling method to enhance the capability of the PCA-based method in fault diagnosis by taking advantage of expert knowledge about the process concerned. The decoupling method develops unique fault patterns of typical sensor faults by analyzing the physical cause-effect relations among variables. Through comparing fault symptoms reflected by the residual vectors of the PCA models with fault patterns, a sensor fault can be successfully isolated. The isolation enhanced PCA method is implemented and validated in a typical air-handling process. The test results show that the joint approach to enhance the fault isolation ability of the PCA-based fault detection and diagnosis method is effective. The robustness of the PCA-based sensor FDD method against component faults is also proved to be improved because the fault symptoms of sensor faults are unique.     

Multi-attribute decision making based on neutral averaging operators for intuitionistic fuzzy information

In this paper, we construct the probability sum (PS) function and the proportional distribution rules of membership function and non-membership function of intuitionistic fuzzy sets (IFSs), and give their corresponding geometric interpretations. Based on which, we present the neutrality operation and the scalar neutrality operation on intuitionistic fuzzy numbers (IFNs). We propose the intuitionistic fuzzy weighted neutral averaging (IFWNA) operator and the intuitionistic fuzzy ordered weighted neutral averaging (IFOWNA) operator. The properties of the IFWNA operator and the IFOWNA operator are investigated. The principal advantages of the proposed operators are that both the attitude of the decision makers and the interactions between different intuitionistic fuzzy numbers (IFNs) are considered. Furthermore, approaches to multi-criteria decision making based on the proposed IFWNA and IFOWNA operator are given. Finally, an example is illustrated to show the feasibility and validity of the new approaches to the application of decision making.     

A method for estimating the cycle time of business processes with many-to-many relationships among the resources and activities based on individual worklists

To analyze and optimize time performance of business process for faster response to customer demands, this study aims to develop a novel method for estimating the cycle time of business processes (or workflows) with many-to-many relationships between resources and activities based on individual worklists. The developed method for estimating business process cycle time is based on M/Hn/1/∞ queuing model and the joint distribution theory of random variables. The feasibility and effectiveness of the proposed method are verified by comparison with the existing methods with case studies. The results have shown that the proposed method can provide a more accurate estimation than conventional approaches.     

Ontological modelling of content management and provision

Information provision to address the changing requirements can be best supported by content management. The current information technology enables information to be stored and provided from various distributed sources. To identify and retrieve relevant information requires effective mechanisms for information discovery and assembly. This paper presents a method, which enables the design of such mechanisms, with a set of techniques for articulating and profiling users’ requirements, formulating information provision specifications, realising management of information content in repositories, and facilitating response to the user’s requirements dynamically during the process of knowledge construction. These functions are represented in an ontology which integrates the capability of the mechanisms. The ontological modelling in this paper has adopted semiotics principles with embedded norms to ensure coherent course of actions represented in these mechanisms.     

Form one students’ engagement with computer games and its effect on their academic achievement in a Malaysian secondary school

The main purpose of the study was to address the association between computer games and students’ academic achievement. The exceptional growth in numbers of children playing computer games, the uneasiness and incomplete understanding foundation when starting the discussion on computer games have stimulated this study to be conducted. From a survey conducted on 236 form one students in one of the Malaysian secondary school, 75.8 percent were gamers. Playing computer games seemed to be more stereotypically boy’s activity with 91.3 percent of the boys engaged in computer games compared to 54.1 percent among the girls. They spent an average of 8.47 hours per week playing computer games. Parents and teachers’ concern about computer games was not something that went unwarranted as an overall result was predicting computer games as having negative associations with students’ academic achievement. However, in-depth analyses by combinations of classes done step by step indicated that the initial results could be overruled by students from the last class, whom need extra attentions. As a conclusion, the findings in this study suggest some interesting yet ultimately weak associations between playing computer games and students’ academic achievement. Nevertheless, caution is warranted in making any generalization as looking at the population as a whole will be different from its components. The generalizability of this study’s findings is limited by the nature of the sample. Even so, blaming computer games for the students’ bad academic performance in school is unjustified as there are many more other factors to look into before finding computer games as the scapegoat.     

Perceived physical risk and risk-reducing strategies in the consumption of raw vegetable salads in restaurants

The importance of eating away from home has revealed the need to understand consumer perception with respect to the physical risks in this context. When a consumer perceives risks, he/she uses different strategies to minimize them. This study aimed to identify consumer perception concerning the physical risks of consuming raw vegetable salads in full-service restaurants, as also the frequency of using physical risk-reducing strategies, examining the influence of socio-demographic variables and social desirability. The survey instrument consisted of 5 items to measure risk perception, 17 items regarding the risk-reducing strategies, socio-demographic questions and the social desirability scale. A total of 359 consumers were interviewed in the city of Campinas, Brazil. An exploratory factor analysis was carried out to group the risk-reducing strategies using the software PASW Statistics, 18.0. A moderate level of physical risk (mean ± standard deviation = 24.2 ± 13.2, on a response scale that could vary between 1 and 49) was perceived by consumers. Three physical risk-reducing strategies presented significant positive correlation (p < 0.05) with social desirability, and were excluded from the other statistical analyses. The fourteen physical risk-reducing strategies were categorized in four factors: “restaurant quality and previous bad experience”, “information from the waiter, the media, and the price”, “workers and restaurant smell” and “word of mouth and full, already known restaurant”. “Restaurant quality and previous bad experience” was the factor significantly (p < 0.05) more used by the consumers in the reduction of physical risks, whereas “information from the waiter, the media, and the price” was the least used. Differences (p < 0.05) in the frequencies of using the strategies contained in the factors were identified with respect to the socio-demographic variables. Those individuals who perceived a greater level of physical risk in the context surveyed used all the factors related to the strategies with greater frequency, to reduce the risk. The results could provide important information for public and private programs.