For concurrent consideration of reliability and safety of manufacturing systems on the one hand, and flexibility and performance on the other, a specialized control architecture was proposed recently. It consists of a...
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Under the support vector machine framework, the support value analysis-based image fusion has been studied, where the salient features of the original images are represented by their support values. The support value ...
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Radio Frequency IDentification (RFID) is a technology of automatic object identification. Retailers and manufacturers have created compelling business cases for deploying RFID in their supply chains. Yet, the uniquely...
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ISBN:
(纸本)9781605581668
Radio Frequency IDentification (RFID) is a technology of automatic object identification. Retailers and manufacturers have created compelling business cases for deploying RFID in their supply chains. Yet, the uniquely identifiable objects pose a privacy threat to individuals. In this paper, we study the privacy threats caused by publishing RFID data. Even if the explicit identifying information, such as name and social security number, has been removed from the published RFID data, an adversary may identify a target victim's record or infer her sensitive value by matching a priori known visited locations and timestamps. RFID data by default is high-dimensional and sparse, so applying traditional K-anonymity to RFID data suffers from the curse of high dimensionality, and would result in poor data usefulness. We define a new privacy model, develop an anonymization algorithm to accommodate special challenges on RFID data, and evaluate its performance in terms of data quality, efficiency, and scalability. To the best of our knowledge, this is the first work on anonymizing high-dimensional RFID data. Copyright 2009 ACM.
In multicore environment, using multiple threads is a common useful approach to improve application performance. Nevertheless, even in many simple applications, the performance might degrade when the number of threads...
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In the paper, we analyze the shortages of Service-Oriented Analysis and Design (SOAD) methodologies, and propose a SOAD method based on Use Case approach. Therefore, a service model is designed to facilitate service i...
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software testing is one of the most important techniques used to assure the quality of Web Services at present. Test-data generation is an important topic in Web Services testing. The quality of test data will influen...
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ISBN:
(纸本)9780769537580
software testing is one of the most important techniques used to assure the quality of Web Services at present. Test-data generation is an important topic in Web Services testing. The quality of test data will influence the efficiency and cost when testing Web Services. Based on the contract-based mutation testing technique, this paper presents a method of automated test-data generation for Web Services. First, according to the description information and contracts in WSDL documents of Web Services, initial test data are generated automatically by the random method. Then the test data are selected using contract mutation testing. This method can generate a test suite meeting a certain contract mutation score, which indicates the quality and efficiency of testing. Finally, we have developed a prototype on the *** platform, and carried out some experiments. The results have shown that the proposed method is effective in automated test-data generation for Web Services.
In the paper, we analyze the shortages of Service-Oriented Analysis and Design (SOAD) methodologies, and then review the features of data flow diagram as a kind of requirement analysis technology. Finally, we propose ...
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For sequential output data analysis in non-terminating discrete-event simulation, we consider three methods of point and interval estimation of the steady-state variance. We assess their performance in the analysis of...
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For the alarm flooding problem, a hierarchical alarm processing model is studied to filter, reduce and correlate alarms. In filtering, false alarms are eliminated with repository. In reduction, a reduction algorithm i...
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This paper proposed a new method for infrared people-counting. According to the characteristics of the time continuous data collected by infrared sensors, the pattern recognition idea is introduced in the data process...
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This paper proposed a new method for infrared people-counting. According to the characteristics of the time continuous data collected by infrared sensors, the pattern recognition idea is introduced in the data processing procedure. After the special pretreatment, adaptive segmentation and feature extraction for the people-counting data, the feature vector is used as the inputs of the trained support vector machine classifier to classify and statistic the total number of the people who go through the infrared sensor area in a period of time. Compared with traditional people-counting using sensor, this method is more accurate and it can count the people number at the situation that several people go through the infrared sensor at the same time. Finally, the experiments indicate that the method can be applied in actual application.
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