A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

This paper presents a new technique to design fixed‐structure controllers for linear unknown systems using a set of measurements. In model‐based approaches, the measured data are used to identify a model of the plant for which a suitable controller can be designed. Due to the fact that real processes cannot be described perfectly by mathematical models, designing controllers using such models to guarantee some desired closed‐loop performance is a challenging task. Hence, a possible alternative to model‐based methods is to directly utilize the measured data in the design process. We propose an approach to designing structured controllers using a set of closed‐loop frequency‐domain data. The principle of such an approach is based on computing the parameters of a fixed‐order controller for which the closed‐loop frequency response fits a desired frequency response that describes some desired performance indices. This problem is formulated as an error minimization problem, which can be solved to find suitable values of the controller parameters. The main feature of the proposed control methodology is that it can be applied to stable and unstable plants. Additionally, the design process depends on a pre‐selected controller structure, which allows for the selection of low‐order controllers. An application of the proposed method to a DC servomotor system is presented to experimentally validate and demonstrate its efficacy.     

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.     

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.     

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.     

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...     

On negative results when using sentiment analysis tools for software engineering research

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact of the choice of a sentiment analysis tool on software engineering studies by conducting a simple study of differences in issue resolution times for positive, negative and neutral texts. We repeat the study for seven datasets (issue trackers and Stack Overflow questions) and different sentiment analysis tools and observe that the disagreement between the tools can lead to diverging conclusions. Finally, we perform two replications of previously published studies and observe that the results of those studies cannot be confirmed when a different sentiment analysis tool is used.     

Linearized motion estimation for articulated planes

In this paper, we describe the explicit application of articulation constraints for estimating the motion of a system of articulated planes. We relate articulations to the relative homography between planes and show that these articulations translate into linearized equality constraints on a linear least-squares system, which can be solved efficiently using a Karush-Kuhn-Tucker system. The articulation constraints can be applied for both gradient-based and feature-based motion estimation algorithms and to illustrate this, we describe a gradient-based motion estimation algorithm for an affine camera and a feature-based motion estimation algorithm for a projective camera that explicitly enforces articulation constraints. We show that explicit application of articulation constraints leads to numerically stable estimates of motion. The simultaneous computation of motion estimates for all of the articulated planes in a scene allows us to handle scene areas where there is limited texture information and areas that leave the field of view. Our results demonstrate the wide applicability of the algorithm in a variety of challenging real-world cases such as human body tracking, motion estimation of rigid, piecewise planar scenes, and motion estimation of triangulated meshes.     

The minimum positional error incurred by any connectivity-based positioning algorithm for mobile wireless systems

A very important problem in many wireless ad-hoc networks, including wireless sensor networks, is positioning or the determination of geographical locations of the wireless nodes. Positioning is used both in infrastructural aspects of sensor networks, like geographic routing and topology maintenance, and in applications like wildlife tracking. Connectivity-based positioning algorithms in mobile wireless systems are studied in this work. These algorithms compute node positions based only on the connectivity, i.e. the neighborhood information of each node. Many algorithms have been proposed for positioning in stationary node systems and bounds on positional error of algorithms have been derived. The design and analysis of positioning algorithms for mobile node systems is a more challenging problem. Node mobility increases the amount of positional information available to a positioning algorithm. The work in this paper establishes a bound on the positional error for connectivity-based algorithms in mobile systems. The formulation from the analysis is used to investigate the benefit of this additional positional information on reducing positional error. There is a limit to the usefulness of positional information from previous node positions due to movement. This captures an important performance tradeoff: historical positional information can yield reduced positional error but requires more connectivity information from the network which requires greater computational resources.