Halftone visual cryptography is an encryption mechanism that a secret image is encoded into halftone shares for showing meaningful images. You only need to superimpose part of these share images. Then, images can be s...
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Partial order reduction techniques have been used to combat the state explosion problem in model checking procedures for concurrent systems with probabilistic behaviors. There are some results that give criteria on ap...
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This paper proposes a generalized model by extending Markov chain with spatial resources labels, which can describe the functional and performance properties and some basic characteristics such as nondeterminacy and r...
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The purpose of this research was to develop a combined sense system that uses both force feedback and visual feedback to determine the shape of the microscopic features of a microsample. It is thought that the efficie...
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In a diesel engine, three combustion parameters, which describe the crank angle at the start of ignition, the total amount of heat release and the combustion duration can be used to control the speed, efficiency, nois...
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Digital libraries have shouldered the mission of preserving and spreading human culture in the era of information. However, knowledge extraction for digital libraries is not well studied, and that holds back the role ...
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Digital libraries have shouldered the mission of preserving and spreading human culture in the era of information. However, knowledge extraction for digital libraries is not well studied, and that holds back the role promotion of digital libraries from information collector to knowledge provider. This paper presents an ontology-based approach, which extracts detailed attributes of Traditional Chinese Medicine (TCM) from digitized textbooks. According to the characters of digitized textbooks, we propose an extraction ontology that is compatible with both textbook extraction and TCM theory. To improve extraction tolerance for OCR errors, we extract features of different aspects. Finally, a structured pattern based extraction method is adopted to minimize extraction supervision. The result shows that our method is a practical and robust exploration to address the problem of information extraction for digitized textbooks of TCM.
Decision-making structures are important building blocks in most of the software;however, it may be difficult to verify them because there are various input conditions and several paths causing them to behave differen...
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Decision-making structures are important building blocks in most of the software;however, it may be difficult to verify them because there are various input conditions and several paths causing them to behave differently. Test oracles are reliable sources of how the software must operate. The aim of the present paper is to study the applications of Artificial Neural Networks as an automated oracle to test decision-making structures. First, the decision rules were modeled by the neural network using a training dataset generated based on the software specifications and domain expert knowledge. Next, after the neural network was applied to test a subjectregistration application, the proposed approach was evaluated using mutation testing. The accuracy of the resulted oracle is discussed as well.
Test Oracle is a mechanism to determine if an application executed correctly. In addition, it may be difficult to verify logical software modules due to the complexity of their structures. In this paper, an attempt ha...
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Test Oracle is a mechanism to determine if an application executed correctly. In addition, it may be difficult to verify logical software modules due to the complexity of their structures. In this paper, an attempt has been made to study the applications of Artificial Neural Networks as Single-Network Oracles to verify logical modules. First, the logical module under test was modeled by the neural network using a training dataset generated based on the software specifications. Next, the proposed approach was applied to test a subject-registration application; meanwhile, the quality of the proposed oracle is measured by assessing its accuracy, precision, misclassification error and practicality in practice, using mutation testing by implementing two different versions of the case study: a Golden Version and a Mutated Version. The results indicate that neural networks may be reliable and applicative as oracles to verify logical modules.
Selective catalytic reduction (SCR) catalyst is currently considered the most effective technology for high nitrogen oxides removal from exhaust gas of a diesel engine using ammonia as a reducing agent. To design an S...
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Pin number or password that is used for authentication can be easily attacked. This limitation triggered the utilization of biometric for secured transactions. Biometric is unique to each individual and is reliable. A...
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ISBN:
(纸本)9781424471966
Pin number or password that is used for authentication can be easily attacked. This limitation triggered the utilization of biometric for secured transactions. Biometric is unique to each individual and is reliable. Among the types of biometric being used currently, iris is the most accurate and it remains stable throughout a person's life. However the major challenge on iris and other biometric for authentication is the intra user variability in the acquired identifiers. Iris of the same person captured at different time may differ due to the signal noise of the iris camera. Traditional cryptography method is unable to encrypt and store biometric template, then perform the matching directly. Minor changes in the bits of the feature set extracted from the iris may lead to a huge difference in the results of the encrypted feature. In our approach, an iris biometric template is secured using iris biometric and passwords. Error Correction Code, ECC is introduced to reduce the variability and noise of the iris data. Experimental results show that this approach can assure a higher security with a low false rejection or false acceptance rate. The successful iris recognition rate using this approach is up to 97%.
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