Advanced Materials Research Vols. 989-994

Abstract: Firstly, the store system models was established with Flexsim software. Then the data statistic was taken. Finally, the analysis were carried out with a numerical example. The analysis result shows that emulating is useful for discovering the bottleneck problem of systematic operation, and the simulation is very useful for store system optimization.

Abstract: Firstly, the inventory models were analyzed, and the symbol and assumptions were given out. Then the models of the distribution centre and supplier were studied. Finally, a numeric example was given out by applying the models. The results show that the models are easily to be carried out in engineering field, and it is useful to control the inventory and raise the store efficiency.

Abstract: Firstly, the inventory model was analyzed under some assumptions. Secondly, based on the consumption of some rubber product, the demand and inventory models were established. Finally, an actual example was carried out by using the inventory model. The result shows the applicable of the model in engineering.

Abstract: Fuzzy c-means (FCM) algorithm is an unsupervised clustering algorithm for image segmentation, and has been widely applied because the segmentation results are consistent with human visual characteristics. Enhanced fuzzy c-means clustering (EnFCM) algorithm is the improved FCM algorithm, which reduces the computational complexity. But, both FCM algorithm and EnFCM algorithm, clustering number still need to be manually determined. This paper, in order to realize the automation degree of algorithm, presents an improved algorithm. It first analyzes the histogram, then automatically determines the clustering number and peak value of each class through use of the peak point detection technology, finally segments image by using EnFCM algorithm. Experiments show that this method is a kind of faster fuzzy clustering algorithm with automatic classification ability for image segmentation.

Abstract: Computational imaginary is a simulation of the human mental image based on the study of cognitive science. Art pattern composition knowledge representation is the basis of the intelligence of computer-aided art pattern design. The paper describes an art pattern composition knowledge representation scheme based on the model of computational imaginary. The scheme includes the deep representation, visual representation and spatial representation, and the operations of these three representations. It further describes the abstract and image information from the perspective of the relation between art pattern layout visual and spatial shape.

Abstract: Software cost estimation is the key step to software development management. In order to make COCOMO model applicable to Chinese enterprises, an improved software cost estimation method based on COCOMO model and linear regression was proposed in this paper. Then the replication experiment was taken by using the historical software project data of given enterprises, and then compared experience estimation with the new improved method proposed in this paper about the forecasting accuracy. The results verified that the improved cost estimation method has more practical value to software development.

Abstract: The accuracy of software cost estimation is essential for software development management. By introducing and analyzing the estimation methods of software cost systematically, the paper discussed the necessary of considering the software maintenance stage and estimating the software cost by separating the procedure of software development into several small stages. Then a staged software cost estimation method based on COCOMO model was proposed. The use of the new software cost estimation method proposed by this paper not only contributes to the cost control of software project, but also effectively avoids the bias problem due to using by single cost estimation method so that the accuracy of cost estimation could be improved.

Abstract: Information increase rapidly in recent years which make the effective use of information is not that easy. Knowledge fusion can improve the semantic accuracy and specification of knowledge; it’s a useful way to make the mass disordered information integrated and easy to be recognized for users. The paper proposed a knowledge fusion system model based on ontology and multi-agent theory to meet with the user’ changing needs at any time.

Abstract: The paper analyzed the status of research on China’s digital cultural relics categorizing and encoding which is beginning to develop in China. From the analysis of the characteristics and importance of digital cultural relics categorizing and encoding, the paper proposed a categorizing model and encoding method for digital cultural relics categorizing and encoding.

Abstract: Cloud Computing is gaining acceptance and increasing in popularity. However, digital forensics within Cloud becomes difficult. This paper proposes an extensible semantic model using OCL (Object Constraint Language) for cloud digital forensics data. We give a brief introduction to Trusted Digital Forensics, and then detail the modeling process using OCL and FODA (Feature Oriented Domain Analysis). Therefore, a feature tree can be built with semantic logical relation in order to get the overall semantic description of features in the forensic domain of digital data.