SAFIUS - A secure and accountable filesystem over untrusted storage

We describe SAFIUS, a secure accountable file system that resides over an untrusted storage. SAFIUS provides strong security guarantees like confidentiality, integrity, prevention from rollback attacks, and accountability. SAFIUS also enables read/write sharing of data and provides the standard UNIX-like interface for applications. To achieve accountability with good performance, it uses asynchronous signatures; to reduce the space required for storing these signatures, a novel signature pruning mechanism is used. SAFIUS has been implemented on a GNU/Linux based system modifying OpenGFS. Preliminary performance studies show that SAFIUS has a tolerable overhead for providing secure storage: while it has an overhead of about 50% of OpenGFS in data intensive workloads (due to the overhead of performing encryption/decryption in software), it is comparable (or better in some cases) to OpenGFS in metadata intensive workloads.Comment: 11pt, 12 pages, 16 figure

Tuning phase-stability and short-range order through Al-doping in (CoCrFeMn)100-xAlx high entropy alloys

For (CoCrFeMn)$_{100-x}$Al$_{x}$ high-entropy alloys, we investigate the phase evolution with increasing Al-content (0 $\le$ x $\le$ 20 at.%). From first-principles theory, the Al-doping drives the alloy structurally from FCC to BCC separated by a narrow two-phase region (FCC+BCC), which is well supported by our experiments. We highlight the effect of Al-doping on the formation enthalpy and electronic structure of (CoCrFeMn)$_{100-x}$Al$_{x}$ alloys. As chemical short-range order (SRO) in multicomponent alloys indicates the nascent local order (and entropy changes), as well as expected low-temperature ordering behavior, we use thermodynamic linear-response within density-functional theory to predict SRO and ordering transformation and temperatures inherent in (CoCrFeMn)$_{100-x}$Al$_{x}$. The predictions agree with our present experimental findings, and other reported ones.Comment: 27 pages, 9 figures, 1 tabl

Adaptive Critics for Dynamic Optimization

A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. the proposed combination of a particle swarm optimization-Based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. the objective of the sleep scheduler is to dynamically adapt the sleep duration to node\u27s battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity. © 2010 Elsevier Ltd

Particle Swarm Optimization in Wireless-sensor Networks: A Brief Survey

Wireless-sensor networks (WSNs) are networks of autonomous nodes used for monitoring an environment. Developers of WSNs face challenges that arise from communication link failures, memory and computational constraints, and limited energy. Many issues in WSNs are formulated as multidimensional optimization problems and approached through bioinspired techniques. Particle swarm optimization (PSO) is a simple, effective, and computationally efficient optimization algorithm. It has been applied to address WSN issues such as optimal deployment, node localization, clustering, and data aggregation. This paper outlines issues in WSNs, introduces PSO, and discusses its suitability for WSN applications. It also presents a brief survey of how PSO is tailored to address these issues. © 2011 IEEE

Bio-inspired Algorithms for Autonomous Deployment and Localization of Sensor Nodes

Optimal deployment and accurate localization of sensor nodes have a strong influence on the performance of a wireless sensor network (WSN). This paper considers real-time autonomous deployment of sensor nodes from an unmanned aerial vehicle (UAV). Such a deployment has importance, particularly in ad hoc WSNs, for emergency applications, such as disaster monitoring and battlefield surveillance. the objective is to deploy the nodes only in the terrains of interest, which are identified by segmentation of the images captured by a camera on board the UAV. Bioinspired algorithms, particle swarm optimization (PSO) and bacterial foraging algorithm (BFA), are presented in this paper for image segmentation. in addition, PSO and BFA are presented for distributed localization of the deployed nodes. Image segmentation for autonomous deployment and distributed localization are formulated as multidimensional optimization problems, and PSO and BFA are used as optimization tools. Comparisons of the results of PSO and BFA for autonomous deployment and distributed localization are presented. Simulation results show that both the algorithms perform multilevel image segmentation faster than the exhaustive search for optimal thresholds. Besides, PSO-Based localization is observed to be faster, and BFA-Based localization is more accurate. © 2006 IEEE

An Estimation of Distribution Improved Particle Swarm Optimization Algorithm

PSO is a powerful evolutionary algorithm used for finding global solution to a multidimensional problem. Particles in PSO tend to re-explore already visited bad solution regions of search space because they do not learn as a whole. This is avoided by restricting particles into promising regions through probabilistic modeling of the archive of best solutions. This paper presents hybrids of estimation of distribution algorithm and two PSO variants. These algorithms are tested on benchmark functions having high dimensionalities. Results indicate that the methods strengthen the global optimization abilities of PSO and therefore, serve as attractive choices to determine solutions to optimization problems in areas including sensor networks

Car Traffic Sign Annunciator

Automatic detection and recognition of traffic signs is an essential part of automated driver assistance systems which contribute to the safety of the drivers, pedestrians and vehicles. This paper presents the advanced driver assistance system (ADAS) based on Raspberry pi for traffic sign detection, recognition and annunciation. Such a system presents a vital support for driver assistance in an intelligent automotive. The proposed algorithm is implemented in a real time embedded system using OpenCV library. Proposed method introduced a new method for detection and recognition of traffic signs. Firstly, Potential traffic signs regions are detected by colour segmentation method, then classified using HOG features and a linear SVM classifier to identify the traffic sign class. The proposed system shows good recognition rate under complex challenging lighting and weather conditions. Experimental results on the accuracy of the road sign detection are reported in this paper

Probabilistic Performance Index based Contingency Screening for Composite Power System Reliability Evaluation

Composite power system reliability involves assessing the adequacy of generation and transmission system to meet the demand at major system load points. Contingency selection was being the most tedious step in reliability evaluation of large electric systems. Contingency in power system might be a possible event in future which was not predicted with certainty in earlier research. Therefore, uncertainty may be inevitable in power system operation. Deterministic indices may not guarantee the randomness in reliability assessment. In order to account for volatility in contingencies, a new performance index proposed in the current research. Proposed method assimilates the uncertainty in computational procedure. Reliability test systems like Roy Billinton Test System-6 bus system and IEEE-24 bus reliability test systems were used to test the effectiveness of a proposed method

Functional and radiological outcome of comminuted shaft of humerus fracture treated by dynamic compression plate

Background: Humeral shaft fractures represents between 3% and 5% of all fractures of which a certain number of patients require surgical intervention. This study aims to determine the efficacy of dynamic compression plate in the treatment of humeral shaft fractures.Methods: A prospective study was carried out over a period of 2 years in Sri Ramachandra Medical College, Chennai including 30 cases of shaft of humerus fractures treated by open reduction and internal fixation using Dynamic Compression plate among which both comminuted and segmental closed shaft of humerus fractures were included. While open fractures and ipsilateral forearm and clavicle fractures were excluded. AO classification was used to classify the fractures and the average follow up period was two years. The American Shoulder and Elbow Surgeons (ASES) shoulder score and Romen al series grading were used.Results: We had 93.3% excellent/good result and 6.7% poor results. In our series we had one non-union, one delayed union and one case of deep infection.Conclusions: Proper preoperative planning, minimal soft tissue dissection, strict asepsis, proper postoperative rehabilitation and patient education were essential to obtain excellent results. Early post-operative mobilization following rigid fixation of the fracture of humerus, with DCP lowered the incidence of stiffness and sudecks dystrophy