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Weak signal detection is a multidisciplinary application of detection methods,which through the use of different methods to study and analyze the statistical properties of signal and noise, and use a variety of signal processing methods to analyze and process the input signal. Weak signals can be detected...

In order to obtain the image information of go, we use the traditional method to process the image, but the traditional method has great limitation. The accuracy is low, and the external factors can easily affect the processing result. In order to solve the limitation of traditional image processing...

To investigate the effect of collision parameters (impact area of hood, vehicle velocity, walking speed of pedestrian, pedestrian gait and pedestrian orientation) on the dynamics response and injury of pedestrian thorax by combining the merits of Finite Element (FE) method and analytical method of Multi-body...

The train schedule is the basis of operation organization in urban rail transit. According to the properties of the full- length & short- turn routing mode in urban railway transit, a multi- objective nonlinear mixed integer programming optimization model of train shedule for a single transit line is...

In order to improve the operation safety of road tunnels, a new evaluation method of safety evaluation was proposed. Firstly, the index system was established by comprehensive considering all kinds of traffic safety attribute, including road engineering, traffic safety facility, traffic flow condition...

Indoor positioning is becoming a very popular research direction in recent years. In this paper, we realize real-time trajectory calculation through the fusion of inertial and vision. We have two experiments in different environments and we find that the algorithm's error is below 50% of pure inertial...

Study on train over-taking organization of urban rail transit and propose calculation methods of local train's waiting time as well as the length of the cross section. Combining with actual operation of urban rail transit, the effects of departure interval, tracking interval and the maximum operating...

In order to study the influence of the tail of the fitted sample distribution curve of vehicle load effect on the maximum value distribution in the reference period of vehicle load effect, multi-model normal distribution curve, straight line, parabola, exponential curve and POT model based on Pareto...

Relevance vector machine (RVM), a sparse Bayesian kernel method in machine learning, has been well-known for its sparsity and probabilistic predictions. Like other kernel methods, it use the kernel functions to map the input instances into higher dimensional space for problem simplicity. At present,...

Traditional evaluation of firm’s market value in credit risk analysis could be contaminated by market noises. The purpose of this article is to price the credit risk in the distance to default with particle filter approach. Compared to the traditional methods, the estimate of the distance to default...

In this paper, we propose the Fuzzy Scheduling System (FSS) to deal with the dedicated machine constraint. The constraint of having a dedicated machine for photolithography process is the new issue introduced in photolithography machinery due to natural bias. If we randomly schedule the wafer lots to...

A data-driven Takagi-Sugeno (TS) fuzzy model is developed for modeling a real plant with the dependent inputs, the nonlinear and the time-varying input-output relation. The collinearity of inputs can be eliminated through the principal component analysis (PCA). The TS model split the operating region...

Object correlations are common semantic patterns in virtual reality systems. They can be exploited for improving the effectiveness of storage caching, prefecthing, data layout, and minimization of query-response times. Unfortunately, this information about object correlations is unavailable at the storage...

Knowledge management (KM) is suggested as a method to manage and apply knowledge for business management. In this paper, we suggest a framework based on OPF (Open Process Framework) meta model for the knowledge-based decision-making. Based on the modeling method of OPF, we can translate partial and implicit...

In the security infrastructure, intrusion detection has become an indispensable defense line in face of increasing vulnerabilities exposed in today’s computing systems and Internet. In this paper, our approach uses ontologies as a way of grasping the knowledge of a domain, expressing the intrusion detection...

String matching of a large string collection on mobile devices has been a difficult problem because of the memory space and computing speed constraints. We propose a method to efficiently determine whether a query string exists in the large string collection. The proposed method, based on a string encoder...

The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this paper, we propose a combination of genetic...

In this paper, we propose a new genetic algorithm based on the two-dimensional encoding method. Appropriate two-dimensional crossover and mutation operations are designed based on the two-dimensional representation to generate the next generations. A two-dimensional repairing mechanism is also proposed...

Once the input values are given, the active rules in a fuzzy inference execution have been determined. Based on the observation, our approach is to identify the active rules before fuzzy inference execution. To achieve this goal, our architecture provides the following two mechanisms: (1) a mechanism...

A fuzzy logic controlled protocol that enables each station to tune its contention window based on the on-line channel sensing results is proposed for the wireless local area networks. Extensive simulations are provided to compare the performance of the proposed protocol with that of the distributed...

The mean-variance framework for portfolio selection should be revised when investor’s concern is the downside risk. This is especially true when the asset returns are not normal. In this paper, we incorporate value-at-risk (VaR) in portfolio selection and the mean-VaR framework is proposed. Due to the...

One purpose of this paper is to propose hybrid neural network models for bankruptcy prediction. The proposed hybrid neural network models are, respecitvely, a MDA model integrated with financial ratios, a MDA model integrated with financial ratios and intellectual capital ratios, a MDA-assisted neural...

Music expresses emotion. However, analyzing the emotion in music by computer is a difficult task. Some work can be found in the literature, but the results are not satisfactory. In this paper, an emotion detection and classification system for pop music is presented. The system extracts feature values...

Objects in the world exhibit complex interactions.When captured in a video sequence, some interactions manifest themselves as occlusions. A visual tracking system must be able to track objects which are partially or even fully occluded. Occlusion is a difficult problem in target tracking, especially...