A piezoelectric model based multi-objective optimization of robot gripper design

The field of robotics is evolving at a very high pace and with its increasing applicability in varied fields, the need to incorporate optimization analysis in robot system design is becoming more prominent. The present work deals with the optimization of the design of a 7-link gripper. As actuators play a crucial role in functioning of the gripper, the actuation system (piezoelectric (PZ), in this case) is also taken into consideration while performing the optimization study. A minimalistic model of PZ actuator, consisting different series and parallel assembly arrangements for both mechanical and electrical parts of the PZ actuators, is proposed. To include the effects of connector spring, the relationship of force with actuator displacement is replaced by the relation between force and the displacement of point of actuation at the physical system. The design optimization problem of the gripper is a non-linear, multi modal optimization problem, which was originally formulated by Osyczka (2002). In the original work, however, the actuator was a ‘constant output-force actuator model’ providing a constant output without describing the internal structure. Thus, the actuator model was not integrated in the optimization study. Four different cases of the PZ modelling have been solved using multi-objective evolutionary algorithm (MOEA). Relationship between force and actuator displacement is obtained using each set of non-dominated solutions. These relationships can provide a better insight to the end user to select the appropriate voltage and gripper design for specific application.     

Multi-input optical parallel logic processing with the shadow-casting technique

The lensless shadow-casting technique for coded pattern processing usually accommodates two inputs at a time to perform desired logical operations in parallel. A method of binary encoding is proposed that can accommodate multiple input patterns for simultaneous processing. With the proposed multiple-input encoding a carry-look-ahead technique of binary addition is developed that requires fewer processing steps than the conventional ripple-carry method. Experimental results for a few logic-processing operations are included to establish the validity of the proposed technique.     

Encrypted Network Traffic Classification and Resource Allocation with Deep Learning in Software Defined Network

Wireless Personal Communications - The climate has changed absolutely in every area in just a few years as digitized, making high-speed internet service a significant need in the future. Future...     

Multicast Network Security with Asymmetric Cooperative Relaying

International Journal of Wireless Information Networks - This paper exhibits the confidentiality performance study of a cooperative multicast network consisting of $${\mathcal {K}}$$ asymmetric...     

Fuzzy Based Ant Colony Optimization Scheduling in Cloud Computing

Cloud computing is an Information Technology deployment model established on virtualization. Task scheduling states the set of rules for task allocations to an exact virtual machine in the cloud computing environment. However, task scheduling challenges such as optimal task scheduling performance solutions, are addressed in cloud computing. First, the cloud computing performance due to task scheduling is improved by proposing a Dynamic Weighted Round-Robin algorithm. This recommended DWRR algorithm improves the task scheduling performance by considering resource competencies, task priorities, and length. Second, a heuristic algorithm called Hybrid Particle Swarm Parallel Ant Colony Optimization is proposed to solve the task execution delay problem in DWRR based task scheduling. In the end, a fuzzy logic system is designed for HPSPACO that expands task scheduling in the cloud environment. A fuzzy method is proposed for the inertia weight update of the PSO and pheromone trails update of the PACO. Thus, the proposed Fuzzy Hybrid Particle Swarm Parallel Ant Colony Optimization on cloud computing achieves improved task scheduling by minimizing the execution and waiting time, system throughput, and maximizing resource utilization.     

Experimental investigation of impact of diesel particulate filter on smoke and NO<Subscript>x</Subscript> emissions of a Euro-I compression ignition engine with active and off-board regeneration

Old engines (Euro III or earlier) produce more emissions, and it will be difficult to entirely stop their usage especially in developing and under-developed nations; hence, it is desired that appropriate emission reduction technologies are tested on such engines to analyze their feasibility and economical acceptability. While most such studies have been conducted on constant speed stationary engines and modern engines, this study tried to analyze the effectiveness of an uncoated wall-flow type ceramic diesel particulate filter on a Euro-I, water-cooled, direct injection, variable speed, compression ignition engine in a laboratory set-up in India. Also, this study focused on diesel particulate filter regeneration by two methods: active regeneration by diesel injection in the particulate filter using an electronic control unit and off-board regeneration by taking out and heating the diesel particulate filter in an electrical resistance furnace at 650 °C for 10 h. The results, in the form of smoke emission, NO_x emission and engine performance, obtained using both the regeneration methods were analyzed, and conclusions were drawn. It was found that using diesel particulate filter, particulate matter emissions (smoke) were almost entirely eliminated. It was also found that off-board regeneration had numerous advantages compared to active regeneration. Since a furnace would be needed for off-board regeneration, an exchange process for diesel particulate filter is suggested.     

Attack resilient P2P dissemination of RSS feed

RSS (really simple syndication) based feeds have become the defacto mechanism of web based publish subscribe. Peer-to-Peer delivery of such feeds can not only alleviate the load at the content server, but also reduce the dissemination latency. However, due to openness of P2P system, malicious peers can join the network as easily as normal peers do. Such malicious peers may pretend to relay but actually not, and thus deny service, or even disseminate counterfeit updates, rendering a Peer-to-Peer mechanism not only useless, but even harmful (e.g. by false updates). We propose overlay independent randomized strategies to mitigate these ill-effects of malicious peers at a marginal overhead, thus enjoying the benefits of Peer-to-Peer dissemination, along with the assurance of content integrity in RSS like web-based publish-subscribe applications without altering currently deployed server infrastructure. We conduct analysis of performance of our proposal by modeling behavior of the system and validating the same with simulation. Results show that our proposal is effective, robust and scalable.     

Symmetry in scalar field topology

Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. Though geometric symmetry has been well studied within areas like shape processing, identifying symmetry in scalar fields has remained largely unexplored due to the high computational cost of the associated algorithms. We propose a computationally efficient algorithm for detecting symmetric patterns in a scalar field distribution by analysing the topology of level sets of the scalar field. Our algorithm computes the contour tree of a given scalar field and identifies subtrees that are similar. We define a robust similarity measure for comparing subtrees of the contour tree and use it to group similar subtrees together. Regions of the domain corresponding to subtrees that belong to a common group are extracted and reported to be symmetric. Identifying symmetry in scalar fields finds applications in visualization, data exploration, and feature detection. We describe two applications in detail: symmetry-aware transfer function design and symmetry-aware isosurface extraction.     

Development of a biological detection platform utilizing a modular microfluidic stack

The goal of this project is to build a miniaturized, user-friendly cytometry setup (Datta et al. in Microfluidic platform for education and research. COMS, Baton Rouge, 2008; Frische et al. in Development of an miniaturized flow cytometry setup for visual cell inspection and sorting. Baton Rouge, Project Report, 2008) by combining a customized, microfluidic device with visual microscope inspection to detect and extract specific cells from a continuous sample flow. We developed a cytological tool, based on the Coulter particle counter principle, using a microelectrode array patterned on a borosilicate glass chip as electrical detection set-up which is fully embedded into a polymeric multi-layer microfluidic stack. The detection takes place between pairs of coplanar Cr/Au microelectrodes by sensing an impedance change caused by particles continuously carried within a microfluidic channel across the detection area under laminar flow conditions. A wide frequency range available for counting provides information on cell size, membrane capacitance, cytoplasm conductivity and is potentially of interest for in-depth cell diagnostic e.g. to detect damaged or cancerous cells and select them for extraction and further in-depth analysis.     

Multi-objective optimization of multicast overlays for collaborative applications

Current real-time collaborative application implementations use dedicated infrastructure to carry out all communication and synchronization activities. Specifically, they require all end nodes to communicate directly with and through the central server. In this paper, we investigate scenarios in which the most resource intensive functionality of continuous communication among collaborators to disseminate changes is decentralized, utilizing the end users themselves as relays. We observe that communication characteristics of real-time collaboration makes use of existing multicast mechanisms unsuitable. As collaborative editing sessions are typically long and repeated, it is possible to gather and leverage node behavior (their instabilities and frequency of sending updates) and communication links (latencies and average costs). Several criteria to determine the quality of a multicast tree can be identified: cost, latency and instability. In this paper, we analyze the complexity of the problem of finding optimal communication topologies, and propose approximate algorithms to optimize the same. We also consider the multiobjective problem in which we search for a topology that provides good trade-off between these sometimes conflicting measures. Validation of our proposed algorithms on numerous graphs shows that it is important to consider the multiobjective problem, as optimal solutions for one performance measure can be far from optimal for the other metrics. Finally, we briefly present an implementation of a communication library that uses the proposed algorithms to periodically adjust the dissemination tree.