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A K Misra - One of the best experts on this subject based on the ideXlab platform.
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Evaluation and comparison of cognitive Complexity Measure
ACM SIGSOFT Software Engineering Notes, 2007Co-Authors: Sanjay Misra, A K MisraAbstract:Weyuker properties have been suggested as a guiding tool in identification of a good and comprehensive Complexity Measure. In this paper, an attempt has been made to compare cognitive Complexity Measure in terms of nine Weyuker's properties with other Complexity Measures, such as McCabe's, Halstead's and Oviedo's Complexity Measures. Our intension is to study what kinds of new information about the Measures are able to give.
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evaluating cognitive information Complexity Measure
Engineering of Computer-Based Systems, 2006Co-Authors: Dharmender Singh Kushwaha, A K MisraAbstract:In this paper, an attempt has been made to evaluate cognitive information Complexity Measure (CICM) terms of nine Weyuker properties. It has been found that all the nine properties have been satisfied by CICM and hence establishes cognitive information Complexity Measure based on information contained in the software as a robust and well-structured one.
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A Complexity Measure based on information contained in the software
2006Co-Authors: Dharmender Singh Kushwaha, A K MisraAbstract:Cognitive Informatics is a field that studies internal information processing mechanism of the human brain and its application in software coding and computing. This paper attempts to empirically demonstrate the amount of information contained in software and develops a concept of cognitive information Complexity Measure based on the information contained in the software. It is found that software with higher cognitive information Complexity Measure has more information units contained in it. Therefore cognitive information Complexity Measure can be used to understand the cognitive information Complexity and the information coding efficiency of the software. For any Complexity Measure to be robust, Weyuker properties must be satisfied to qualify as good and comprehensive one. In this paper, an attempt has also been made to evaluate cognitive information Complexity Measure in terms of nine Weyuker properties, through examples. It has been found that all the nine properties have been satisfied by cognitive information Complexity Measure and hence establishes cognitive information Complexity Measure based on information contained in the software as a robust and well-structured one.
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ECBS - Evaluating cognitive information Complexity Measure
13th Annual IEEE International Symposium and Workshop on Engineering of Computer-Based Systems (ECBS'06), 2006Co-Authors: Dharmender Singh Kushwaha, A K MisraAbstract:In this paper, an attempt has been made to evaluate cognitive information Complexity Measure (CICM) terms of nine Weyuker properties. It has been found that all the nine properties have been satisfied by CICM and hence establishes cognitive information Complexity Measure based on information contained in the software as a robust and well-structured one.
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robustness analysis of cognitive information Complexity Measure using weyuker properties
ACM Sigsoft Software Engineering Notes, 2006Co-Authors: Dharmender Singh Kushwaha, A K MisraAbstract:Cognitive information Complexity Measure is based on cognitive informatics, which helps in comprehending the software characteristics. For any Complexity Measure to be robust, Weyuker properties must be satisfied to qualify as good and comprehensive one. In this paper, an attempt has also been made to evaluate cognitive information Complexity Measure in terms of nine Weyuker properties, through examples. It has been found that all the nine properties have been satisfied by cognitive information Complexity Measure and hence establishes cognitive information Complexity Measure based on information contained in the software as a robust and well-structured one.
Sanjay Misra - One of the best experts on this subject based on the ideXlab platform.
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Validating modified cognitive Complexity Measure
ACM SIGSOFT Software Engineering Notes, 2007Co-Authors: Sanjay MisraAbstract:A newly proposed Complexity Measure is acceptable, only when its usefulness has been proved by a validation process. In our previous work, we proposed Modified Cognitive Complexity Measure (MCCM). In this paper, MCCM has been evaluated and validated through a practical framework and principle of Measurement theory. It has been found to satisfy most of the parameters required by the practical framework and Measurement theory. Additionally, empirical validation through case study and comparative study proved the robustness of the proposed Measure.
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Evaluation and comparison of cognitive Complexity Measure
ACM SIGSOFT Software Engineering Notes, 2007Co-Authors: Sanjay Misra, A K MisraAbstract:Weyuker properties have been suggested as a guiding tool in identification of a good and comprehensive Complexity Measure. In this paper, an attempt has been made to compare cognitive Complexity Measure in terms of nine Weyuker's properties with other Complexity Measures, such as McCabe's, Halstead's and Oviedo's Complexity Measures. Our intension is to study what kinds of new information about the Measures are able to give.
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IEEE ICCI - Cognitive Program Complexity Measure
6th IEEE International Conference on Cognitive Informatics, 2007Co-Authors: Sanjay MisraAbstract:In cognitive informatics, the functional Complexity of software depends on three factors: internal architecture, input, and output. In the earlier proposed metrics based on cognitive informatics, these above factors are not fully considered. This paper proposes an improved cognitive Complexity Measure. Accordingly, new formula is developed to calculate the cognitive Complexity. An attempt has also been made to evaluate and validate the proposed Measure through Weyuker's properties and a practical framework. It has been found that seven of nine Weyuker's properties have been satisfied by the proposed cognitive Complexity Measure. It also satisfies most of the parameters required by the practical framework, hence establishes as a well-structured one. Finally, a comparative study with similar Measures has been made to prove its robustness.
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modified cognitive Complexity Measure
International Symposium on Computer and Information Sciences, 2006Co-Authors: Sanjay MisraAbstract:In cognitive functional size Measure, the functional size is proportional to weighted cognitive Complexity of all internal BCS‘s and number of input and output. This paper proposes the modification in cognitive functional size Complexity Measure. The proposed Complexity Measure is proportional to total occurrence of operators and operands and all internal BCS´s. The operators and operands are equally important in design consideration. Thus, the contribution of the operators, operands and cognitive aspects complete the definition of a Complexity Measure in terms of cognitive. Accordingly, a new formula is developed for calculating the modified cognitive Complexity Measure. An attempt has also been made to evaluate modified cognitive Complexity Measure in terms of nine Weyuker's properties, through examples. It has been found that seven of nine Weyuker's properties have been satisfied by the modified cognitive Complexity Measure and hence establishes as a well-structured one.
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ISCIS - Modified cognitive Complexity Measure
Computer and Information Sciences – ISCIS 2006, 2006Co-Authors: Sanjay MisraAbstract:In cognitive functional size Measure, the functional size is proportional to weighted cognitive Complexity of all internal BCS‘s and number of input and output. This paper proposes the modification in cognitive functional size Complexity Measure. The proposed Complexity Measure is proportional to total occurrence of operators and operands and all internal BCS´s. The operators and operands are equally important in design consideration. Thus, the contribution of the operators, operands and cognitive aspects complete the definition of a Complexity Measure in terms of cognitive. Accordingly, a new formula is developed for calculating the modified cognitive Complexity Measure. An attempt has also been made to evaluate modified cognitive Complexity Measure in terms of nine Weyuker's properties, through examples. It has been found that seven of nine Weyuker's properties have been satisfied by the modified cognitive Complexity Measure and hence establishes as a well-structured one.
Jose C Principe - One of the best experts on this subject based on the ideXlab platform.
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weighted permutation entropy a Complexity Measure for time series incorporating amplitude information
Physical Review E, 2013Co-Authors: Bilal H Fadlallah, Badong Chen, Andreas Keil, Jose C PrincipeAbstract:Permutation entropy (PE) has been recently suggested as a novel Measure to characterize the Complexity of nonlinear time series. In this paper, we propose a simple method to address some of PE's limitations, mainly its inability to differentiate between distinct patterns of a certain motif and the sensitivity of patterns close to the noise floor. The method relies on the fact that patterns may be too disparate in amplitudes and variances and proceeds by assigning weights for each extracted vector when computing the relative frequencies associated with every motif. Simulations were conducted over synthetic and real data for a weighting scheme inspired by the variance of each pattern. Results show better robustness and stability in the presence of higher levels of noise, in addition to a distinctive ability to extract Complexity information from data with spiky features or having abrupt changes in magnitude.
Bernd Pompe - One of the best experts on this subject based on the ideXlab platform.
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Permutation Entropy: A Natural Complexity Measure for Time Series
Physical Review Letters, 2002Co-Authors: Christoph Bandt, Bernd PompeAbstract:We introduce Complexity parameters for time series based on comparison of neighboring values. The definition directly applies to arbitrary real-world data. For some well-known chaotic dynamical systems it is shown that our Complexity behaves similar to Lyapunov exponents, and is particularly useful in the presence of dynamical or observational noise. The advantages of our method are its simplicity, extremely fast calculation, robustness, and invariance with respect to nonlinear monotonous transformations.
Kuochen Chou - One of the best experts on this subject based on the ideXlab platform.
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using pseudo amino acid composition to predict protein structural classes approached with Complexity Measure factor
Journal of Computational Chemistry, 2006Co-Authors: Xuan Xiao, Shihuang Shao, Zhengde Huang, Kuochen ChouAbstract:The structural class is an important feature widely used to characterize the overall folding type of a protein. How to improve the prediction quality for protein structural classification by effectively incorporating the sequence- order effects is an important and challenging problem. Based on the concept of the pseudo amino acid composition (Chou, K. C. Proteins Struct Funct Genet 2001, 43, 246; Erratum: Proteins Struct Funct Genet 2001, 44, 60), a novel approach for measuring the Complexity of a protein sequence was introduced. The advantage by incorporating the Complexity Measure factor into the pseudo amino acid composition as one of its components is that it can catch the essence of the overall sequence pattern of a protein and hence more effectively reflect its sequence-order effects. It was demonstrated thru the jackknife crossvalidation test that the overall success rate by the new approach was significantly higher than those by the others. It has not escaped our notice that the introduction of the Complexity Measure factor can also be used to improve the prediction quality for, among many other protein attributes, subcellular localization, enzyme family class, membrane protein type, and G-protein couple receptor type.
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using Complexity Measure factor to predict protein subcellular location
Amino Acids, 2005Co-Authors: X Xiao, Shihuang Shao, Yongsheng Ding, Z Huang, Y Huang, Kuochen ChouAbstract:Recent advances in large-scale genome sequencing have led to the rapid accumulation of amino acid sequences of proteins whose functions are unknown. Because the functions of these proteins are closely correlated with their subcellular localizations, it is vitally important to develop an automated method as a high-throughput tool to timely identify their subcellular location. Based on the concept of the pseudo amino acid composition by which a considerable amount of sequence-order effects can be incorporated into a set of discrete numbers (Chou, K. C., Proteins: Structure, Function, and Genetics, 2001, 43: 246-255), the Complexity Measure approach is introduced. The advantage by incorporating the Complexity Measure factor as one of the pseudo amino acid components for a protein is that it can more effectively reflect its overall sequence-order feature than the conventional correlation factors. With such a formulation frame to represent the samples of protein sequences, the covariant-discriminant predictor (Chou, K. C. and Elrod, D. W., Protein Engineering, 1999, 12: 107-118) was adopted to conduct prediction. High success rates were obtained by both the jackknife cross-validation test and independent dataset test, suggesting that introduction of the concept of the Complexity Measure into prediction of protein subcellular location is quite promising, and might also hold a great potential as a useful vehicle for the other areas of molecular biology.