In this study, the solution procedure of Linear Fractional Time Minimizing Transportation Problem with Impurities (LFTMTPI) in the commodity to generate total transportation solution schedules, is going to be presented. This LFTMTPI is related to a lexicographic linear fractional time minimizing transportation problem with impurities. The partial flows constituting a feasible transportation schedule may be partitioned according to the actual and standard transportation time involved. An LFTMTPI algorithm is also presented to solve such real life fractional decision priority problems. This algorithm takes into account the special structure of the problem due to impurities in the commodity and depends heavily on the optimality conditions. The optimality conditions reflects nothing else than dual feasibility.

In healthcare domain there is a plethora of health information but no mechanism of satisfying customized users’ requirements and providing demand oriented information. Healthcare domain is facing challenge of finding healthcare information that meets user requirements. Semantics can provide interoperable, automated and seamlessly meaningful communication for healthcare domain. Healthcare information is increasing with the increase of medical databases over the internet. In this matter provision of right information to appropriate users over the web is a great challenge. Semantic web technologies can address this issue by ensuring extensible, flexible and efficient information discovery related to diseases and clinical processes. We implemented a semantic registry that is a service registry as well as metadata registry. It manages and secures healthcare information and processes in a consistent way in compliance with emerging international standards and technical specifications. We evaluated our system through Patient Registration Scenario implemented semantically in our OWLS framework.

In this paper, we propose an attack model based on partial information, which means that one can obtain the information of a part of nodes in the networks. We study the ef?cient attack strategy (EAS) in random scale-free networks. It is shown that the attack strategy can affect the attack effect remarkably and the EAS can achieve better attack effect than other typical attack strategies. Extensive simulations are performed to validate and illustrate our analytical results. Our results will be of theoretical and practical signi?cance both for protecting infrastructural networks and stopping the spreading of harmful things (like disease) on networks.

Requirement analysis on NS (network software) poses a lot of problems for the reason of dynamic deploying topology, dynamic proposing and dynamic changing of requirement. In this paper, we propose a unified solution for NS requirement modeling called PVSS. The purpose of PVSS is to provide a stepwise modeling framework on extracting common artifacts of families of NS applications from domain on constructing reusable domain models, then refined and customized for specific NS requirement model.

Content-Based Video Retrieval (CBVR) is still an open hard problem because of the semantic gap between low-level features and high-level features, largeness of database, keyframe's content, choosing feature, etc. In this paper we introduce a new approach for this problem based on Scale-Invariant Feature Transform (SIFT) feature, a new metric and an object retrieval method. Our algorithm is built on a Content-Based Image Retrieval (CBIR) method in which the keyframe database includes keyframes detected from video database by using our shot detection method.Experiments show that the approach of our algorithmhas fairly high accuracy.