基于时限的角色访问控制委托模型

访问权限的委托限制是一种重要的安全策略,它的基本思想是用户将自己所具有的部分或者全部权限转授给其他用户,让接受授权的用户代表发出授权的用户执行某些任务.基于角色的委托授权模型将角色作为委托的主体.目前为止它的两个基本模型RBDM0和RDM2000都没有有效地解决时限问题,事实上时限是授权的重要组成部分,本文在上述两个模型的基础上引入有效时间和角色激活的概念,描述了与之相对应的带时限的委托模型并给出了相应的委托判断规则.     

Mindlin plate finite elements by a modified transverse displacement

The formulation of 4-node plate bending elements to eliminate the shear locking is presented. The kinematic variables in the Mindlin plate are related through the equilibrium equations; and then the transverse displacement, rotations, and shear strain are expressed in terms of the curvature sum. The elements are formulated by using the modified transverse displacement defined as the transverse displacement subtracted by the curvature sum times the ratio of flexural to shear rigidity. It is shown that the elements describe plate behavior quite correctly without any locking and also that they are applicable to the analysis of both thin and thick plates.     

New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management

Greening the supply chain is an increasingly important concern for many business enterprises and a challenge for logistics management. Critical functions within green supply chain management are internal improvements and selection of green suppliers. This study proposes a novel, hybrid model that addresses dependent relationships between various criteria and the vague information coming from decision-makers. The Decision-making Trial and Evaluation Laboratory (DEMATEL) technique structures the relationships among criteria, thereby constructing an influential network relationship map (INRM). Meanwhile the DEMATEL-based, analytical network process (ANP) method aids in obtaining influential weights of the criteria. Decision-makers may hold diverse opinions and preferences due to incomplete information, differences in knowledge or simply conflicts that are inherent between various departments. This can make it difficult to judge the performance of alternatives. One remedy is to apply a modified COmplex PRoportional ASsessment of alternatives with Grey relations. Next, this is applied to improve each criterion for integration of the performance values obtained in closing the aspiration level from different expert opinions based on INRM. An empirical example using data from a Taiwanese electronics company is provided to demonstrate our proposed method. The results can provide firms with a knowledge-based understanding of the source of some problems, thus reducing the performance gaps and closing the aspiration levels. Finally, there is a discussion on certain managerial implications.     

Oxygen saturation-dependent effects on blood transverse relaxation at low fields

Objective

Blood oxygenation can be measured using magnetic resonance using the paramagnetic effect of deoxy-haemoglobin, which decreases the \(\textit{T}_{2}\) relaxation time of blood. This \(\textit{T}_{2}\) contrast has been well characterised at the \(\textit{B}_{{0}}\) fields used in MRI (1.5 T and above). However, few studies have characterised this effect at lower magnetic fields. Here, the feasibility of blood oximetry at low field based on \(\textit{T}_{2}\) changes that are within a physiological relevant range is explored. This study could be used for specifying requirements for construction of a monitoring device based on low field permanent magnet systems.

Methods

A continuous flow circuit was used to control parameters such as oxygen saturation and temperature in a sample of blood. It flowed through a variable field magnet, where CPMG experiments were performed to measure its \(\textit{T}_{2}\). In addition, the oxygen saturation was monitored by an optical sensor for comparison with the \(\textit{T}_{2}\) changes.

Results

These results show that at low \(\textit{B}_{{0}}\) fields, the change in blood \(\textit{T}_{2}\) due to oxygenation is small, but still detectable. The data measured at low fields are also in agreement with theoretical models for the oxy-deoxy \(\textit{T}_{2}\) effect.

Conclusion

\(\textit{T}_{2}\) changes in blood due to oxygenation were observed at fields as low as 0.1 T. These results suggest that low field NMR relaxometry devices around 0.3 T could be designed to detect changes in blood oxygenation.

     

Effects of CCEP and Sc on superplasticity of Al–5.6Mg–0.7Mn alloys

Trace amount (0.3?wt%) of scandium is added to Al–5.6Mg–0.7Mn alloy to form uniformly distributed Al₃Sc precipitates for producing a fine-grained and stable microstructure at high temperature through cross-channel extrusion process. Superplasticity and hot workability of the Sc-containing Al–5.6Mg–0.7Mn alloy, after extrusion, are also examined. The result indicates that Al–5.6Mg–0.7Mn alloys with and without 0.3?wt% Sc after extrusion of six passes at 300°C, fine-grained structures were observed with grain sizes of 1–2?µm and improvement of mechanical properties. Furthermore, Al₃Sc phase can effectively retard recrystallization to increase the thermal stability and remain equiaxed. The elongation of Al–5.6Mg–0.7Mn alloy with Sc addition to failure is extended to 873% maximum at high temperature of 450°C at strain rate of 1?×?10^?1?s^?1after six passes in the CCEP.     

Microfluidic-based biosensors toward point-of-care detection of nucleic acids and proteins

This article reviews state-of-the-art microfluidic biosensors of nucleic acids and proteins for point-of-care (POC) diagnostics. Microfluidics is capable of analyzing small sample volumes (10⁻⁹–10⁻¹⁸ l) and minimizing costly reagent consumption as well as automating sample preparation and reducing processing time. The merger of microfluidics and advanced biosensor technologies offers new promises for POC diagnostics, including high-throughput analysis, portability and disposability. However, this merger also imposes technological challenges on biosensors, such as high sensitivity and selectivity requirements with sample volumes orders of magnitude smaller than those of conventional practices, false response errors due to non-specific adsorption, and integrability with other necessary modules. There have been many prior review articles on microfluidic-based biosensors, and this review focuses on the recent progress in last 5 years. Herein, we review general technologies of DNA and protein biosensors. Then, recent advances on the coupling of the biosensors to microfluidics are highlighted. Finally, we discuss the key challenges and potential solutions for transforming microfluidic biosensors into POC diagnostic applications.     

Combined MCDM techniques for exploring stock selection based on Gordon model

Basing on the Gordon model perspective and applying multiple criteria decision making (MCDM), this research explores the influential factors and relative weight of dividend, discount rate, and dividend growth rate. The purpose is to establish an investment decision model and provides investors with a reference/selection of stocks most suitable for investing effects to achieve the greatest returns. Taking full consideration of the interrelation effect among variables of the decision model, this paper introduced analytical network process (ANP) and examined leading electronics companies spanning the hottest sectors of lens, solar, and handset by experts. Empirical findings indicated that dividend was affected by industry outlook, earnings, operating cash flow, and dividend payout rate; discount rate was affected by market β and risk-free rate; and dividend growth rate was affected by earnings growth rate and dividend payout growth rate. Also, according to literatures, discount rate possessed a self-effect relationship. Among the eight evaluation criteria, market β was the most important factor influencing investment decisions, followed by dividend growth rate and risk-free rate. In stock evaluations, leadership companies in the solar industry outperformed those in handset and lens, becoming investors’ favorite stock group at the time that this research was conducted.     

The evaluation of cluster policy by fuzzy MCDM: Empirical evidence from HsinChu Science Park

In the recent years, industrial clusters have received considerable attention from economists and industrial analysts, because they are seen as the main reason for economic growth and success of certain economic region. This study systematically reviews past researches of industrial cluster. The purpose of this paper is to contribute to the understanding of this issue regarding the driving forces for the growth of industrial cluster and find out the priority among these cluster policies. Taiwan HsinChu Science Park is a prime example for this paper, and its connection with the innovative participators. We begin with an examination of the literature on cluster about its driving forces and policies upon which we propose a conceptual framework. In doing so, we explore the cluster-based industrial system. Then this research adopts the Fuzzy Analytic Hierarchy Process as the analytical tool. The Fuzzy Analytic Hierarchy Process method is used to determine the weightings for evaluation dimension among decision makers. From our research results, the Factor Conditions is the most important driving force for advancing the industrial cluster performance. Moreover, the promotion of international linkages policy and broader framework policies rank the first two priorities for cluster policy. Overall, this paper concludes with some simulations of cluster policy alternatives confronting the industry and the Taiwanese government.     

Icon identification in context: the changing role of icon characteristics with user experience

OBJECTIVE: This research examined the relative importance of icon characteristics in determining the speed and accuracy of icon identification. BACKGROUND: Studies to date have focused on the role of one or two icon characteristics when users first experience an icon set. This means that little is known about the relative importance of icon characteristics or how the role of icon characteristics might change as users gain experience with icons. METHODS: Thirty participants carried out an icon identification task over a long series of trials to simulate learning through experience. Icon characteristics investigated included semantic distance, concreteness, familiarity, and visual complexity. RESULTS: Icon characteristics were major determinants of performance, accounting for up to 69% of the variance observed in performance. However, the importance of icon characteristics changed with experience: Semantic distance is crucial initially while icon-function relationships are learned, but familiarity is important later because it has lasting effects on access to long-term memory representations. CONCLUSION: These findings suggest that icon concreteness may not be of primary importance when identifying icons and that semantic distance and familiarity may be more important. APPLICATION: Designers need to take into account icon characteristics other than concreteness when creating icons, particularly semantic distance and familiarity. The precise importance of the latter characteristics will vary depending on whether icons are rarely encountered or frequently used.     

Genetic Parallel Programming: design and implementation

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.