A new linguistic MCDM method based on multiple-criterion data fusion

Multiple-criteria decision-making (MCDM) is concerned with the ranking of decision alternatives based on preference judgements made on decision alternatives over a number of criteria. First, taking advantage of data fusion technology to comprehensively consider each criterion data is a reasonable idea to solve the MCDM problem. Second, in order to efficiently handle uncertain information in the process of decision making, some well developed mathematical tools, such as fuzzy sets theory and Dempster Shafer theory of evidence, are used to deal with MCDM. Based on the two main reasons above, a new fuzzy evidential MCDM method under uncertain environments is proposed. The rating of the criteria and the importance weight of the criteria are given by experts’ judgments, represented by triangular fuzzy numbers. Then, the weights are transformed into discounting coefficients and the ratings are transformed into basic probability assignments. The final results can be obtained through the Dempster rule of combination in a simple and straight way. A numerical example to select plant location is used to illustrate the efficiency of the proposed method.     

Service improvement by business process management using customer complaints in financial service industry

In financial service industry, service improvement should be considered from process viewpoint and customer viewpoint because the value creation is ultimately linked with internal business processes on the back office and customers are involved as a co-producer of value. In this perspective, customer complaints through call centers are adequate to support the analysis for service improvement in financial service industry. In this study, we propose a web-based decision support system for business process management employing customer complaints, namely Voice of the Customer (VOC), and its handling data for service improvement. It involves VOC conversion for data enrichment and includes analysis of summarization, exception and comparison. The proposed system is evaluated on a major credit card company in South Korea.     

Examining different types of collaborative learning in a complex computer-based environment: A cognitive load approach

This study compared the effects of two collaborative learning strategies (Open-ended and Task-based) with an individualized learning strategy on individual learning in a computer-based environment. The experiment sought ecological validity by conducting it under real teaching and homework conditions. Ninety-four students from grade 9 participated in a webpage design task. Cognitive load theory was used to predict that the collaborative approaches would outperform the individualized approach due to reduced cognitive load. This hypothesis was confirmed by performance scores and cognitive load only in the case of the Open-ended collaborative learning condition. Evidence was also found that the Open-ended collaborative learning condition outperformed the Task-based collaborative one. It was concluded that in collaborative learning a more Open-ended task design together with moderate independent sub-task requirements leads to more effective learning.     

Plasmonic enhanced fluorescence spectroscopy using side-polished microstructured optical fiber

We report excitation of surface plasmon in a gold-coated side-polished D-shape microstructure optical fiber (MOF). As the leaky evanescent field from the fiber core becomes highly localized by the plasmon wave, its intensity also gets amplified significantly. Here we demonstrate an efficient use of this intensified field as excitation in fluorescence spectroscopy. The so-called plasmonic enhanced fluorescence emission from Rhodamine B has been investigated experimentally. First, plasmonic effect alone was found to provide an immediate fluorescence enhancement factor of two. Second, experimental results show a good agreement with theoretical modeling. Strong evanescent field generation and surface enhancement with simple metallic coating makes this fiber based device a good candidate for compact fluorescence spectroscopy.     

Speed scaling with a solar cell

We consider the setting of a device that obtains its energy from a battery and some regenerative source such as a solar cell. We consider the speed scaling problem of scheduling a collection of tasks with release times, deadlines, and sizes, so as to minimize the energy recharge rate of the regenerative source. This is the first theoretical investigation of speed scaling for devices with a regenerative energy source. We show that the problem can be expressed as a polynomial sized convex program. We show that, using the KKT conditions, one can obtain an efficient algorithm to verify the optimality of a schedule. We show that the energy optimal YDS schedule is 2-approximate with respect to the recharge rate. We show that the online algorithm BKP is O(1)$O\left(1\right)$-competitive with respect to recharge rate.     

Utility function of TCP

Understanding the TCP congestion control mechanism from a global optimization point of view is not only important in its own right, but also crucial to the design of other transport layer traffic control protocols with provable properties. In this paper, we derive a global utility function and the corresponding optimal control law, known as TCP control law, which maximizes the global utility. The TCP control law captures the essential behaviors of TCP, including slow start, congestion avoidance, and the binary nature of congestion feedback in TCP. We find that the utility function of TCP is linear in the slow start phase and is proportional to the additive increase rate and approaches the well-known logarithm function as the data rate becomes large in the congestion avoidance phase. We also find that understanding the slow start phase with a fixed threshold is critical to the design of new transport layer control protocols to enable quality of service features. Finally, as an application, we design a Minimum Rate Guaranteed (MRG) traffic control law that shares the same utility function as the TCP control law. Our simulation study of the MRG control law indicates that it is indeed TCP friendly and can provide minimum rate guarantee as long as the percentage of network resource consumed by the MRG flows is moderately small.     

Peer-exchange schemes to handle mismatch in peer-to-peer systems

A self-organizing peer-to-peer system is built upon an application level overlay, whose topology is independent of an underlying physical network. A well-routed message path in such systems may result in a long delay and excessive traffic due to the mismatch between logical and physical networks. In order to solve this problem, we present a family of Peer-exchange Routing Optimization Protocols (PROP) to reconstruct the overlay. It includes two policies: PROP-G for generic condition and PROP-O for optimized one. Both theoretical analysis and simulation experiments show that these two protocols greatly reduce the average latency of the overlay and achieve a better logical topology with low overhead. Their overall performance can be further improved if combined with other recent approaches. Specifically, PROP-G can be easily applied to both structured and unstructured systems without the loss of their primary characteristics, such as efficient routing and anonymity. PROP-O, on the other hand, is more efficient, especially in a heterogenous environment where nodes have different processing capabilities.

A Study on Lateral Control of Autonomous Vehicles via Fired Fuzzy Rules Chromosome Encoding Scheme

In this paper, we propose a novel Fired Rules Chromosomes (FRC) encoding scheme for a fuzzy controller tuned by Genetic Algorithms (GA). The proposed method improves the optimization speed through the reduction of the search space. In addition, an improvement in convergence is demonstrated. The fuzzy controller optimized by the FRC scheme is employed to maintain the lateral position of an autonomous vehicle. The robustness of the controller to parameter variation is studied by Monte-Carlo analysis. Simulation and experimental studies demonstrate the performance of the lateral controller.     

Low cost inductor current sensing for power converters using feedback compensation

One of the key components in the current mode control of power converters is the sensing of inductor current. Traditional low cost implementation is to add a sensing resistor in series with the inductor to sense the inductor current. This will reduce the overall efficiency of the power converter. An alternative is to apply a current transformer to the inductor to sense its current. This however will significantly increase the cost of power converters. One low cost implementation is to add a resistor–capacitor network in parallel with the inductor so that the inductor current can be derived from the capacitor voltage. The problem of this implementation is that the capacitor voltage is very sensitive to temperature variations. In this paper, a simple feedback loop is applied to the sensed capacitor voltage based on the steady state duty ratio of power converters such that the sensed inductor current will be independent of temperature variations. The sensing element with feedback compensation can be applied to inductors fitted to power converters such as buck converters and boost converters. Although experimental studies based on a buck converter were carried out to illustrate the correctness of the new sensing technique, the proposed technique is applicable to other converter topologies.     

Tool support for learning Büchi automata and linear temporal logic

We introduce a graphical interactive tool, named GOAL, that can assist the user in understanding Büchi automata, linear temporal logic, and their relation. Büchi automata and linear temporal logic are closely related and have long served as fundamental building blocks of linear-time model checking. Understanding their relation is instrumental in discovering algorithmic solutions to model checking problems or simply in using those solutions, e.g., specifying a temporal property directly by an automaton rather than a temporal formula so that the property can be verified by an algorithm that operates on automata. One main function of the GOAL tool is translation of a temporal formula into an equivalent Büchi automaton that can be further manipulated visually. The user may edit the resulting automaton, attempting to optimize it, or simply run the automaton on some inputs to get a basic understanding of how it operates. GOAL includes a large number of translation algorithms, most of which support past temporal operators. With the option of viewing the intermediate steps of a translation, the user can quickly grasp how a translation algorithm works. The tool also provides various standard operations and tests on Büchi automata, in particular the equivalence test which is essential for checking if a hand-drawn automaton is correct in the sense that it is equivalent to some intended temporal formula or reference automaton. Several use cases are elaborated to show how these GOAL functions may be combined to facilitate the learning and teaching of Büchi automata and linear temporal logic. This work was partially supported by the National Science Council, Taiwan (R.O.C.) under grants NSC94-2213-E-002-089, NSC95-2221-E-002-127, NSC95-3114-P-001-001-Y02 (iCAST 2006), NSC96-3114-P-001-002-Y (iCAST 2007), and NSC97-2221-E-002-074-MY3.