Supply chain is a complex system. The complexity of supply chain can be categorized into two kinds: the complexity of supply chain components as well as the complexity of the supply chain organizations, and both infor...
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Supply chain is a complex system. The complexity of supply chain can be categorized into two kinds: the complexity of supply chain components as well as the complexity of the supply chain organizations, and both information uncertainty with system dynamics are the main reasons that lead to supply chain complexity. Concerning supply chain complexity, we review the related researching approaches in the literature from uncertainty, the measure of supply chain complexity as well as the dynamic analysis of the supply chain (including dynamic games), and give suggestions in the future research.
Shuffled frog leaping (SFL) is a population based, cooperative search metaphor inspired by natural memetics. Its ability of adapting to dynamic environment makes SFL become one of the most important memetic algorithms...
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Shuffled frog leaping (SFL) is a population based, cooperative search metaphor inspired by natural memetics. Its ability of adapting to dynamic environment makes SFL become one of the most important memetic algorithms. In order to improve the algorithmpsilas stability and the ability to search the global optimum, a novel dasiacognition componentpsila is introduced to enhance the effectiveness of the SFL, namely frog not only adjust its position according to the best individual within the memeplex or the global best of population but also according to thinking of the frog itself. To validate the improved SFL (ISFL) method, numerous simulations were conducted to compare SFL and ISFL using six benchmark problems for continuous and discrete optimization. According to the simulation results, adding the cognitive behavior to SFL significantly enhances the performance of SFL in solving the optimization problems, and the improvements are more evident with the scale of the problem increasing.
A fuzzy logic controller (FLC) is designed to achieve course-keeping for mooring shifting system, which is the main system of non self-propelled vessels. Compared with manual operation, the automatic operation and mon...
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A fuzzy logic controller (FLC) is designed to achieve course-keeping for mooring shifting system, which is the main system of non self-propelled vessels. Compared with manual operation, the automatic operation and monitoring system with the FLC can perform higher precision and efficiency. The particle swarm optimization (PSO) algorithm is introduced to optimize the proposed FLCpsilas parameters. A series of simulation studies have been undertaken to compare the performance of a basis FLC and PSO based FLC. The results demonstrate that the latter has the better controlling quality.
Dezert-smarandache theory (DSmT) was extended with fuzzy theory by considering the different Fuzzy T-norm operators, in order to develop a more general and flexible combinational rule for more extensive application. A...
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Dezert-smarandache theory (DSmT) was extended with fuzzy theory by considering the different Fuzzy T-norm operators, in order to develop a more general and flexible combinational rule for more extensive application. At the same time, fuzzy-extended DSmT was applied to mobile robot's sensing environment with the help of new self-localization method based on δ neighboring field appearance matching and also the perception effect was compared with different T-norm operators. Finally, an effective approach to solv sensing fusion of uncertainty environment was found.
B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagno...
B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagnosis is mainly qualitative, and often depends on the subjective judgment of technicians and doctors. Therefore, computer-aided feature extraction and quantitative analysis of liver B-scan ultrasonic images will help to improve clinical diagnostic accuracy, repeatability and efficiency, and could provide a measure for severity of hepatic steatosis. This paper proposed a novel method of fatty liver diagnosis based on liver B-mode ultrasonic images using support vector machine (SVM). Fatty liver diagnosis was transformed into a pattern recognition problem of liver ultrasound image features. According to the different characteristics of fatty liver and healthy liver, important image features were extracted and selected to distinguish between the two categories. These features could be represented by near-field light-spot density, near-far-field grayscale ratio, grayscale co-occurrence matrix, and neighborhood gray-tone difference matrix (NGTDM). A SVM classifier was modeled and trained using the clinical ultrasound images of both fatty liver and normal liver. It was then exploited to classify normal and fatty livers, achieving a high recognition rate. The diagnostic results are satisfactorily consistent with those made by doctors. This method could be used for computer-aided diagnosis of fatty liver, and help doctors identify the fatty liver ultrasonic images rapidly, objectively and accurately.
An improved particle filter algorithm was presented to track a moving target under natural environment, in which the color histogram was integrated with the measurement model, the latest observations was taken into ac...
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ISBN:
(纸本)9787900719706
An improved particle filter algorithm was presented to track a moving target under natural environment, in which the color histogram was integrated with the measurement model, the latest observations was taken into account and the system model is the second order autoregressive process. The proposed method can deal with rotation and scale transformation, variations in the light source and partial occlusions, and the tracked target can be rigid or non-rigid. The demonstration examples showed that the method can track the target with robustness in real-time.
This paper describes a novel 3D needle segmentation algorithm for 3DUS data. The algorithm includes the 3D Gray-level Hough Transform (3DGHT), which is based on the representation (ψ, θ, ρ, α) of straight lines in...
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Intensive task-oriented repetitive physical therapies provided by individualized interaction between the patient and a rehabilitation specialist can improve hand motor performance in patients survived from stroke and ...
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Intensive task-oriented repetitive physical therapies provided by individualized interaction between the patient and a rehabilitation specialist can improve hand motor performance in patients survived from stroke and traumatic brain injury. However, the therapy process is long and expensive and difficult to evaluate quantitatively and objectively. The goal of this research is to develop a novel wearable device for robotic assisted hand repetitive therapy. We designed a pneumatic muscle (PM) driven therapeutic device that is wearable and provides assistive forces required for grasping and release movements. The robot has two distinct degrees of freedom at the thumb and the fingers. The embedded sensors feedback position and force information for robot control and quantitative evaluation of task performance. It has the potential of providing supplemental at-home therapy in addition to in the clinic treatment.
A resource-constrained transport task scheduling problem (RCTTSP) with two optimal objectives was considered, and a multi-objective hybrid genetic algorithm (HGA) was proposed. The proposed algorithm used the serial s...
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A resource-constrained transport task scheduling problem (RCTTSP) with two optimal objectives was considered, and a multi-objective hybrid genetic algorithm (HGA) was proposed. The proposed algorithm used the serial scheduling method to initialize the population and evaluated the individual. It used the weighted sum method and the rank-based fitness assignment method to assign the individual fitness. Firstly, this paper described the multi-objective RCTTSP and presented the principle of the HGA, and then developed the algorithm to implement several experimental cases with different problem size;lastly the effectiveness and efficiency of the algorithm were compared. The numerical result indicated that the proposed multi-objective HGA can resolve the proposed multi-objective RCTTSP efficiently.
An efficient image denoising algorithm is introduced. Firstly, image pixels are classified into noisy pixels and noise-free pixels by four directional operators. Then an adaptive weighted median filter is designed to ...
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An efficient image denoising algorithm is introduced. Firstly, image pixels are classified into noisy pixels and noise-free pixels by four directional operators. Then an adaptive weighted median filter is designed to remove and restore the detected noisy pixels and keep the noise-free ones unchanged. Experimental results indicate that the proposed algorithm preserves image details well while removing impulsive noise efficiently, and its filtering performance is significantly superior to the classical median filter and some other typical and recently developed improved median filters.
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