951 resultados para Table manipulation (Computer science)


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Efficient caring for the patient's information is an important aspect of caring for the patient. If these processes are possible to monitor anytime anywhere as per the patients' and doctors desecrations the cost of patient care could be minimised. In this connection, Ubiquitous Sensor Network is playing a key role on communication between physicians and patients as well as information sharing among health care providers with rapid access to medical information through reliable and trusted computer network systems. This paper argues possibilities of such scenarios by introducing a ubiquitous sensor network in patient care for 21st century's requirements and standards.

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Timed-release cryptography addresses the problem of “sending messages into the future”: information is encrypted so that it can only be decrypted after a certain amount of time, either (a) with the help of a trusted third party time server, or (b) after a party performs the required number of sequential operations. We generalise the latter case to what we call effort-release public key encryption (ER-PKE), where only the party holding the private key corresponding to the public key can decrypt, and only after performing a certain amount of computation which may or may not be parallelisable. Effort-release PKE generalises both the sequential-operation-based timed-release encryption of Rivest, Shamir, and Wagner, and also the encapsulated key escrow techniques of Bellare and Goldwasser. We give a generic construction for ER-PKE based on the use of moderately hard computational problems called puzzles. Our approach extends the KEM/DEM framework for public key encryption by introducing a difficulty notion for KEMs which results in effort-release PKE. When the puzzle used in our generic construction is non-parallelisable, we recover timed-release cryptography, with the addition that only the designated receiver (in the public key setting) can decrypt.

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Key establishment is a crucial primitive for building secure channels in a multi-party setting. Without quantum mechanics, key establishment can only be done under the assumption that some computational problem is hard. Since digital communication can be easily eavesdropped and recorded, it is important to consider the secrecy of information anticipating future algorithmic and computational discoveries which could break the secrecy of past keys, violating the secrecy of the confidential channel. Quantum key distribution (QKD) can be used generate secret keys that are secure against any future algorithmic or computational improvements. QKD protocols still require authentication of classical communication, although existing security proofs of QKD typically assume idealized authentication. It is generally considered folklore that QKD when used with computationally secure authentication is still secure against an unbounded adversary, provided the adversary did not break the authentication during the run of the protocol. We describe a security model for quantum key distribution extending classical authenticated key exchange (AKE) security models. Using our model, we characterize the long-term security of the BB84 QKD protocol with computationally secure authentication against an eventually unbounded adversary. By basing our model on traditional AKE models, we can more readily compare the relative merits of various forms of QKD and existing classical AKE protocols. This comparison illustrates in which types of adversarial environments different quantum and classical key agreement protocols can be secure.

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A physiological control system was developed for a rotary left ventricular assist device (LVAD) in which the target pump flow rate (LVADQ) was set as a function of left atrial pressure (LAP), mimicking the Frank-Starling mechanism. The control strategy was implemented using linear PID control and was evaluated in a pulsatile mock circulation loop using a prototyped centrifugal pump by varying pulmonary vascular resistance to alter venous return. The control strategy automatically varied pump speed (2460 to 1740 to 2700 RPM) in response to a decrease and subsequent increase in venous return. In contrast, a fixed-speed pump caused a simulated ventricular suction event during low venous return and higher ventricular volumes during high venous return. The preload sensitivity was increased from 0.011 L/min/mmHg in fixed speed mode to 0.47L/min/mmHg, a value similar to that of the native healthy heart. The sensitivity varied automatically to maintain the LAP and LVADQ within a predefined zone. This control strategy requires the implantation of a pressure sensor in the left atrium and a flow sensor around the outflow cannula of the LVAD. However, appropriate pressure sensor technology is not yet commercially available and so an alternative measure of preload such as pulsatility of pump signals should be investigated.

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We introduce the concept of Revocable Predicate Encryption (RPE), which extends current predicate encryption setting with revocation support: private keys can be used to decrypt an RPE ciphertext only if they match the decryption policy (defined via attributes encoded into the ciphertext and predicates associated with private keys) and were not revoked by the time the ciphertext was created. We formalize the notion of attribute hiding in the presence of revocation and propose an RPE scheme, called AH-RPE, which achieves attribute-hiding under the Decision Linear assumption in the standard model. We then present a stronger privacy notion, termed full hiding, which further cares about privacy of revoked users. We propose another RPE scheme, called FH-RPE, that adopts the Subset Cover Framework and offers full hiding under the Decision Linear assumption in the standard model. The scheme offers very flexible privacy-preserving access control to encrypted data and can be used in sender-local revocation scenarios.

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A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.