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System Testing is a key technology of CVIS (Cooperative Vehicle Infrastructure System). A shortest test sequence generating approach in CVIS is proposed in this paper. The paper firstly analyzes the spatial-temporal state of vehicle and complexity of infrastructure in network. Then paper designs system features and test cases, and introduces the concept of support index of the test case to system...
Two "heterogeneous" information dissemination networks were established on the basis of sets of actual "rum or information" and "anti-rum or information" dissemination data involving a real micro logging event. Through empirical analysis of degree centrality, between ness centrality and closeness centrality, it was discovered that all three centrality indexes of the two...
Action recognition has been an important and challenging task in computer vision. Existing approaches usually employ pooling operation to encode isolated patches or trajectories and then aggregate them for a compact video presentation. In this paper, we make two contributions towards improving action recognition accuracy and efficiency. First, we study to apply a state-of-the-art pooling technique...
This paper proposes a radial basis function (RBF) network trained using ridge extreme learning machine to predict the future trend from the past stock index values. Here the task of predicting future stock trend i.e. the up and down movements of stock price index values is cast as a classification problem. Recently extreme learning machine (ELM) is used as an efficient learning algorithm for single...
Image quality evaluation standard of information hiding algorithm mainly relied on the traditional standard such as peak signal to noise ratio (PSNR), but PSNR does not meet people's subjective assessment. So it is necessary to set up the objective evaluation criteria with subjective uniformity for information hiding algorithm. In this paper, an image subjective quality evaluation model is proposed...
Currently, microalgae cultivation is one of the most promising alternative solutions to alleviate the value of CO2 concentration. Microalgae growth rate is convinced to be the indicator to measure the effectiveness in capturing CO2. In this paper, the microalgal growth behavior by means of various pH concentrations is observed. From the observation data, the growth behavior is modeled by regression...
Linkage of routine and administrative databases from multiple sources provides an advantageous form of understanding chronic diseases, such as arthropathy conditions. Data mining classification algorithms can be a cost-effective approach to identify patients' cohorts with certain disorders within these complex databases. However, selecting good potential predictors, given a certain condition from...
Recently, an efficient learning algorithm called extreme learning machine (ELM) has been proposed for training of single hidden layer feed forward neural networks (SLFNs). ELM has shown good generalization performances for many real applications with an extremely fast learning speed. This study proposes a computational efficient functional link artificial neural network (CEFLANN) trained with ELM...
Water quality assessment is very important for monitoring water sources and main canal, which is beneficial to offer strategies for the management of water quality and environment. This paper proposes a water quality assessment method based on a sparse autoencoder network. In the proposed approach, a representation model is firstly learned via a sparse autoencoder trained by unlabeled water monitoring...
Earned Value Management (EVM) is the most recognized tool for monitoring and controlling project performance. Its ultimate goal is to provide reliable early warning signals about the cost and schedule performance of a project. However, EVM has its limitations in monitoring and controlling software project activities. The lack of quality performance indicator and the inadequacy in incorporating the...
Software bugs contribute to the cost of ownership for consumers in a software-driven society and can potentially lead to devastating failures. Software testing, including functional testing and structural testing, remains a common method for uncovering faults and assessing dependability of software systems. To enhance testing effectiveness, the developed artifacts (requirements, code) must be designed...
Obstruents are very important acoustical events (i.e., abrupt-consonantal landmarks) in the speech signal. This paper presents the use of novel Spectral Transition Measure (STM) to locate the obstruents in the continuous speech signal. The problem of obstruent detection involves detection of phonetic boundaries associated with obstruent sounds. In this paper, we propose use of STM information derived...
In software reliability testing based on Markov chain usage model, how to assign the migrating probability between states of the Markov chain usage model is still a problem yet to be solved. In order to deal with the problems such as the sample data for estimating the migrating probability being small and uncertain, a migrating probability assignment method based on a three-parameter interval number...
The growth in South Africa's population and economy increases the need to ensure that future unserved electricity is avoided by ensuring adequate electricity supply. The understanding of the various elements that impact the different economic sectors' electricity consumption is key in effective electricity supply planning.
Some R&D projects generated from technological seeds produce potential applications in other fields. In many industries, huge amounts of public investment are spent continuously over long periods. Advanced technology with high levels of technology are required and achieved. Even in cases with projects that apparently failed, technological and economical spinoff effects are expected from collaterally...
This paper investigates the effectiveness of the stimulus error identification and removal (SEIR) algorithm for linearity testing of high precision Analog-to-Digital Converters (ADCs) in the presence of flicker noise. The SEIR algorithm has been demonstrated to be highly effective in estimating the integral nonlinearity (INL) of high precision ADCs tested with low linearity input sources. Since flicker...
The generalized method of moments (GMM) is a technique to discretize integral equations that permits integration of different types of basis functions as well as different geometric descriptions using a partition of unity framework. While accuracy and efficacy of the method have been demonstrated, the integration quadratures required to compute the inner products are often high, as they have to respect...
This paper outlines an adaptive extension of likelihood codebook reordering (LCR) vector quantization. By providing a method for allowing the vector quantization to adapt in a predetermined way, the codebook may be adaptively reordered to allow more efficient encoding by giving preference to encountered vectors in the dictionary. In particular, adaptation allows the trained dictionaries to be more...
Data mining is to extract the potentially useful knowledge and information from large amounts of data. How to dig up effective, reliable, understandable, and interesting association rules from vast amounts of information to help people make decisions has become an urgent problem to be solved. People want to use a reasonable evaluation method to measure reliability or validity of association rules,...
Generally, in multi-lingual communities, non-native speakers may produce speech sound which is either part of their own native language or established via merging characteristics of native pronunciation with non-native pronunciation. Recently, a Two-pass phone clustering based on Confusion Matrix (TCM) approach has been proposed to address the one-to-one phone mappings between Chinese syllables and...
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