Number entry systems in medical devices such as infusion pumps are used to input drug doses that will be administered to patients. They are safety critical since if the drug dose is too high or too low, this may cause...
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ISBN:
(纸本)9781450343220
Number entry systems in medical devices such as infusion pumps are used to input drug doses that will be administered to patients. They are safety critical since if the drug dose is too high or too low, this may cause harm to patients. Previous work shows that number entry systems with the same hardware layout can have software that is implemented in different ways. This means that devices with the same hardware layout may lead to different results after the same keystrokes are pressed. Previous work also shows that choosing the best software implementation over the worst can reduce the likelihood of human error eight-fold in directional number entry systems. Determining whether a software implementation abides by the requirements is a time consuming task for regulatory bodies and hospital procurement departments. In this paper we show how software testing techniques can be used to classify various software implementations in order to determine whether the given number entry system satisfies specifications.
program performance assessment is one of important methods to optimize a system design. The assessment of program execution time is always key topic in computer structure. A good assessment can provide important measu...
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ISBN:
(纸本)9781509004546
program performance assessment is one of important methods to optimize a system design. The assessment of program execution time is always key topic in computer structure. A good assessment can provide important measure basis for hardware/software automatic partitioning in reconfigurable computer compiler. This paper analyzes the characteristics of IR program and proposes an IR layer program classification algorithm for assessing the program execution time. The method can provide an accurate measure and can be constructed into a BP neural network assessment system. The experimental results show that the proposed assessment model has lower assessment deviation compared to other models under the same conditions. The BP neural network model can be trained.
In this paper, an innovative method to analyze the software specifications by using a model based on the Markov Chain is proposed. It is well known that all kinds of software are executed via the instruction set of th...
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ISBN:
(纸本)9781479911110
In this paper, an innovative method to analyze the software specifications by using a model based on the Markov Chain is proposed. It is well known that all kinds of software are executed via the instruction set of the processor. Since the instruction set can be classified and divided into a series of finite state (i.e. the finite-state machine), it is natural that the software programs based on it has different corresponding characteristics of the Markov process in each state. More importantly, the transition probability can be calculated through the Markov chain in the form of different sparse matrix and with the help of the Discrete Fourier Transform (DFT), the model of the software can be acquired. Once the modeling is done, it will be possible to optimize the software both in the hardware design and the compiling process, which differs from the usual optimization applied only during the hardware designing process. Experimental results have shown that the model is able to greatly reduce the difficulty in solving the problems of the hit rate, cache consistency, etc.
In order to achieve TV program group recommendation, an approach based on fuzzy clustering is proposed for program classification in this paper. This paper firstly describes the XML based program description metadata ...
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ISBN:
(纸本)0769521088
In order to achieve TV program group recommendation, an approach based on fuzzy clustering is proposed for program classification in this paper. This paper firstly describes the XML based program description metadata representation, in which both textual and symbolic information is included. Secondly it presents the program feature extraction and presentation method. A program is defined as two vectors, one is based on term statistics implying what the program is about, and the other reflects broadcasting characteristics of the program. Then the classifying approach based on fuzzy clustering is proposed. The approach goes: normalizing original data, building fuzzy similarity matrix, and then clustering. The final fuzzy similarity matrix is constructed by combining two fuzzy similarity matrices calculated from two different aspects.
Web pages often embed scripts for a variety of purposes, including advertising and dynamic interaction. Understanding embedded scripts and their purpose can often help to interpret or provide crucial information about...
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Web pages often embed scripts for a variety of purposes, including advertising and dynamic interaction. Understanding embedded scripts and their purpose can often help to interpret or provide crucial information about the web page. We have developed a functionality-based categorization of JavaScript, the most widely used web page scripting language. We then view understanding embedded scripts as a text categorization problem. We show how traditional information retrieval methods can be augmented with the features distilled from the domain knowledge of JavaScript and software analysis to improve classification performance. We perform experiments on the standard WT10G web page corpus, and show that our techniques eliminate over 50% of errors over a standard text classification baseline. (c) 2006 Elsevier Ltd. All rights reserved.
Classifying different sorts of programs is very important and necessary in order to realize fast retrieval in large multimedia retrieval systems. This paper focuses on classification of sports program with motion info...
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ISBN:
(纸本)0819439894
Classifying different sorts of programs is very important and necessary in order to realize fast retrieval in large multimedia retrieval systems. This paper focuses on classification of sports program with motion information in MPEG domain. It is fast and efficient to analysis motion information in compressed data without the preprocessing of total decoding and many programs are compressed in MPEG-1/MPEG-2 format. The paper proposes an approach to classify the sports programs by dominant motion information. There is motion information in forward prediction coded frames (P-frame) in MPEG compression data. The motion information can be extracted from MPEG domain. Principal component analysis method is utilized in order to get the dominant motion information from the macroblock's motion vectors, which can simplify the motion information. Principal components of motion information are used to recognize which kind of sport it belongs to with hidden Markov model after those patterns are trained with different kind of sports programs. Some testing sets are used to do some experiments in order to evaluate the performance of the method proposed in paper. Classifying sports programs with motion is available from the experimental results.
The use of the statistical technique of discriminant analysis as a tool for the detection of fault-prone programs is explored. A principal-components procedure was employed to reduce simple multicollinear complexity m...
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The use of the statistical technique of discriminant analysis as a tool for the detection of fault-prone programs is explored. A principal-components procedure was employed to reduce simple multicollinear complexity metrics to uncorrelated measures on orthogonal complexity domains. These uncorrelated measures were then used to classify programs to alternate groups, depending on the metric values of the program. The criterion variable for group determination was a quality measure of faults or changes made to the programs. The discriminant analysis was conducted on two distinct data sets from large commercial systems. The basic discriminant model was constructed from deliberately biased data to magnify differences in metric values between the discriminant groups. The technique was successful in classifying programs with a relatively low error rate. While the use of linear regression models has produced models of limited value, this procedure shows great promise for use in the detection of program modules of with high potential for faults.
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