Investigation of TiAlN coated roller burnishing on Al-(B4C)p MMC workpiece material

Burnishing avoids the need for super finishing operations after the conventional turning process, to enhance the surface quality. This paper deals with the surface modifications of Al(B₄C)_p Metal Matrix Composites (MMC) workpiece material after burnishing with a TiAlN coated WC roller. The burnishing speed, lubrication type, burnishing passes, and coating were the input parameters. Surface hardness and roughness after the burnishing were studied. It was found that the coating on the WC roller had enhanced the hardness in the workpiece after burnishing in the case of Al-5?wt.% (B₄C)_p, under all conditions. The effect of the coating on the work piece surface hardness was not significant with Al-10?wt.% (B₄C)_p. While burnishing Al-5?wt.% (B₄C)_p, the minimum surface roughness combined with maximum surface hardness was obtained, during the third pass under dry condition using uncoated rollers. The number of passes to achieve the desired surface conditions reduced, on using coated rollers with kerosene as the lubricant.     

Dynamic slack allocation algorithms for energy minimization on parallel machines

We explore novel algorithms for DVS (Dynamic Voltage Scaling) based energy minimization of DAG (Directed Acyclic Graph) based applications on parallel and distributed machines in dynamic environments. Static DVS algorithms for DAG execution use the estimated execution time. The estimated time in practice is overestimated or underestimated. Therefore, many tasks may be completed earlier or later than expected during the actual execution. For overestimation, the extra available slack can be added to future tasks so that energy requirements can be reduced. For underestimation, the increased time may cause the application to miss the deadline. Slack can be reduced for future tasks to reduce the possibility of not missing the deadline. In this paper, we present novel dynamic scheduling algorithms for reallocating the slack for future tasks to reduce energy and/or satisfy deadline constraints. Experimental results show that our algorithms are comparable to static algorithms applied at runtime in terms of energy minimization and deadline satisfaction, but require considerably smaller computational overhead.     

Virtual modeling of an ankle foot orthosis for correction of foot abnormality

Clubfoot is a challenging structural foot abnormality in babies and generally occurs at birth or during childhood. Due to this the abnormal posturing of the foot causes the babies to turn the ankle inward and walk along the outside edges of the foot. In medical science it is known as “congenital talipes equino varus” (CTEV). Computer modeling of prosthesis and orthosis is a perspective method for optimal design and gait is a terminology related to walking patterns of human subject.     

Analyzing the techniques that improve fault tolerance of aggregation trees in sensor networks

Sensor networks are finding significant applications in large scale distributed systems. One of the basic operations in sensor networks is in-network aggregation. Among the various approaches to in-network aggregation, such as gossip and tree, including the hash-based techniques, the tree-based approaches have better performance and energy-saving characteristics. However, sensor networks are highly prone to failures. Numerous techniques suggested in the literature to counteract the effect of failures have not been carefully analyzed. In this paper, we focus on the performance of these tree-based aggregation techniques in the presence of failures. First, we identify a fault model that captures the important failure traits of the system. Then, we analyze the correctness of simple tree aggregation with our fault model. We then use the same fault model to analyze the techniques that utilize redundant trees to improve the variance. The impact of techniques for maintaining the correctness under faults, such as rebuilding or locally fixing the tree, is then studied under the same fault model. We also do the cost-benefit analysis of using the hash-based schemes which are based on FM sketches. We conclude that these fault tolerance techniques for tree aggregation do not necessarily result in substantial improvement in fault tolerance.     

MELOC-X: extended memory and location optimized caching for large mobile ad hoc networks of UAVs

Effective caching in mobile ad hoc network increases data availability. However, caching at strategic locations with reduced (controlled) number of copies is needed for many military applications involving UAVs to address security concerns, less maintenance overhead and maintaining availability. In general, existing cooperative caching approaches are deficient in finding the reduced number of strategic cache locations. One such technique to reduce the number of strategic cache locations without affecting the efficacy of data access for a small network topology of UAVs is called “memory and location optimized caching scheme (MELOC)”. However, having a single broker and metadata broadcast across the whole network in MELOC lead to severe performance hindrance in case of a large network topology of UAVs. Moreover, frequent cache replacements due to a change in network topology do not favor cache hit and bandwidth conservation in case of large mobile networks consisting of UAVs. In this paper, we design and evaluate an extended version of “MELOC called MELOC-X”, which suits large network topologies of UAVs by overcoming the above challenges. Our comparison with one such recent scheme with similar objectives showcased a significant improvement in performance. We also evaluate the impact of this scheme with respect to different metrics including the average number of hops, the average roundtrip time (i.e., average query latency), cache hits and mobility to access cached data through extensive simulations.     

Multi-Objective Optimization Model for QoS-Enabled Web Service Selection in Service-Based Systems

Nowadays, the web service has become the emerging communication technology where the interaction of each user is performed through the World Wide Web. However, the performance of the web service mechanism is degraded due to security flaws that occur throughout the Internet.. The user or service requester may not attain the relevant web service for their requirement. To overcome this problem, the newly developed multi-objective based Cuckoo Search (MCS) algorithm is proposed in this article. Initially, the input query model was built by the query keyword that is provided by the service requester. Then, the given query is matched with the database that hosts the web services that relates to input query. Among the various services, the user has to select the appropriate web service using the proposed algorithm. The MCS algorithm is newly designed by combining the Cuckoo Search algorithm and the QoS parameter based multiple objectives. Additionally, the new mathematical model of fitness is evaluated by the multi-objective parameters. Finally, the proposed algorithm exploits the fitness value to select the relevant web service for the user query. The experimental results are validated and performance is analyzed by the parameters of precision, recall, and F-measure. Thus, 86.6% of precision value was obtained by the proposed method, which ensured provision of the appropriate web service.     

Bridging the gap: effect of text query reformulation in multimodal retrieval

Multimedia Tools and Applications - Multimodal Retrieval provides new paradigms and methods aimed at effectively searching through the enormous volume of data. Multimodal retrieval is a well...     

Automatic identification of cattle using muzzle point pattern: a hybrid feature extraction and classification paradigm

Multimedia Tools and Applications - Animal biometrics is an emerging research field that develops quantified methodologies for representing and detecting the visual appearances of animal based on...