Exclusion Principle for Quantum Dense Coding

We show that the classical capacity of quantum states, as quantified by its ability to perform dense coding, respects an exclusion principle, for arbitrary pure or mixed three-party states in any dimension. This states that no two bipartite states which are reduced states of a common tripartite quantum state can have simultaneous quantum advantage in dense coding. The exclusion principle is robust against noise. Such principle also holds for arbitrary number of parties. This exclusion principle is independent of the content and distribution of entanglement in the multipartite state. We also find a strict monogamy relation for multi-port classical capacities of multi-party quantum states in arbitrary dimensions. In the scenario of two senders and a single receiver, we show that if two of them wish to send classical information to a single receiver independently, then the corresponding dense coding capacities satisfy the monogamy relation, similar to the one for quantum correlations.Comment: v2: 6 pages, RevTeX 4, title changed, previous results unchanged, new results adde

A Study on Fournier’s Gangrene

BACKGROUND AND OBJECTIVES: Fournier’s gangrene was first described by Fournier in 1764 as necrotizing fascitis involving the perineal region. It also involves areas like lower urinary tract, anus, rectum, and colon. It is a fulminating, rapidly spreading infection which cause thrombosis of blood vessels which results in gangrene of skin. It affects all age groups and has been reported in both males and females and various etiological factors have been described. It is more commonly seen in middle age groups with immunocompromise status like diabetes mellitus, malignancy, alcoholism, chronic renal disease. The objective of this study mainly includes study of age distribution and risk factors of fournier’s gangrene, as its relevant to check which age group is more prone to develop this condition. Another objective is to find the most common organisms associated with fournier’s gangrene, As it helps in the mode of treatment. This also include a study about the outcome in management of fournier’s gangrene. METHODS: 35 cases of fournier’s gangrene were analyzed. Patient’s history and clinical examination was done to arrive at a diagnosis. Age, etiology, predisposing factors, extent of involvement, Pus culture and sensitivity , lab investigations and surgical outcome were evaluated. RESULTS: The mean age in this study is 55.3yrs, Its found that major predisposing factors are diabetics mellitus and alcoholism, about 15% of the patients where having chronic kidney disease. Only in 17% of cases where there for which no causes could be found out. Pseudomonas where the causative organism for about 40% of the case and e coil was identified in almost 23% of cases, the first culture was found to be sterile In 26% of cases. All patients are treated with appropriate antibiotics and early debridement, among which 3 of them achieved spontaneous healing.15 patients that is around 51% needed delayed suturing and 14 patients needed skin grafting. Adequate resuscitation, transfusion of blood and blood products, early administration of broad spectrum antibiotics with early extensive thorough wound debridement improves the out come. INTERPRETATION AND CONCLUSION: Fournier’s gangrene is a dare emergency disorder that needs early diagnosis and treatment. So even minor infection to perineal region should be give due attentions negligence may lead to life threatening complication So in Fournier’s gangrene early resuscitation of vitals with transfusion of blood and blood products if needed, the adequate antibiotic care and early extensive thorough wound debridment will certainly improve the outcome

Enhancing Data Management Support for Case-based Reasoning Systems

Case-based reasoning offers a novel approach to develop knowledge based systems. A case-based system (CBS) stores problem solving expertise as cases in its casebase. A case captures a problem description and the description of a solution to the problem. A CBS solves a problem by starting with an approximate solution found in a case in its casebase. When presented with a problem, a CBS analyzes it to extract salient features relevant for problem solving. It searches the casebase to identify cases with similar features. All such cases are retrieved and compared with the problem to select the best matching case. The solution in the best case is adapted to develop a solution to the problem. The proposed solution is evaluated. A new case is formed by combining the problem with the proposed solution. This case, if found suitable, is stored in the casebase. A CBS, thus, augments its casebase with new cases as it solves new problems. Case-based reasoning has been used in a wide range of application domains to develop problem solving and advisory systems. A limitation of these systems is that they lack adequate data management support for casebases. Most current CBS are small memory-resident systems. They use small casebases, which are loaded into primary memory during processing. This limits the size of the casebase and restricts the scope of the CBS. Since a CBS develops a solution by starting with an approximate solution from its casebase, its problem solving ability depends to a great extent on the variety and number of cases available in its casebase. It is more likely to find a closely matching case for a given problem in a large casebase compared to that in a smaller casebase. A CBS, therefore, needs a large casebase to operate at an acceptable level of expertise. As a CBS solves new problems, it adds new cases to its casebase. Thus the casebase keeps growing with the daily use of the system. A major research issue confronting CBS research is how to create large systems that can handle large casebases comprising hundreds and thousands of cases (Kolodner 1993). Our research addresses this important issue of providing data management support to large casebases

Data Mining Based on Association Rule Privacy Preserving

The security of the large database that contains certain crucial information, it will become a serious issue when sharing data to the network against unauthorized access. Privacy preserving data mining is a new research trend in privacy data for data mining and statistical database. Association analysis is a powerful tool for discovering relationships which are hidden in large database. Association rules hiding algorithms get strong and efficient performance for protecting confidential and crucial data. Data modification and rule hiding is one of the most important approaches for secure data. The objective of the proposed Association rulehiding algorithm for privacy preserving data mining is to hide certain information so that they cannot be discovered through association rule mining algorithm. The main approached of association rule hiding algorithms to hide some generated association rules, by increase or decrease the support or the confidence of the rules. The association rule items whether in Left Hand Side (LHS) or Right Hand Side (RHS) of the generated rule, that cannot be deduced through association rule mining algorithms. The concept of Increase Support of Left Hand Side (ISL) algorithm is decrease the confidence of rule by increase the support value of LHS. It doesnÊt work for both side of rule; it works only for modification of LHS. In Decrease Support of Right Hand Side (DSR) algorithm, confidence of the rule decrease by decrease the support value of RHS. It works for the modification of RHS. We proposed a new algorithm solves the problem of them. That can increase and decrease the support of the LHS and RHS item of the rule correspondingly so that more rule hide less number of modification. The efficiency of the proposed algorithm is compared with ISL algorithms and DSR algorithms using real databases, on the basis of number of rules hide, CPU time and the number of modifies entries and got better results