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.     

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.     

Performance improvement in decentralized adaptive control: amodified model reference scheme

A modified decentralized model reference adaptive controller is proposed for a continuous time large scale system composed of N interconnected linear subsystems with unknown parameters. In the case where the high frequency gain of the transfer function of each of the isolated subsystems is known, the modified scheme can be used to improve the bad transient behaviour that typically results from poor knowledge of the subsystem parameters. The transient performance improvement, however, has to be traded off against the “size” of the allowable unmodeled interconnections in such a way that as the unmodeled interconnections disappear, the improvement in transient performance can be made arbitrary. Each local adaptive scheme uses “approximate differentiators,” and so possible sensor noise amplification is expected to be an additional limitation of the proposed scheme     

Analysis of Frequency,Intensity, and Interference of Discomfort in Computerized Numeric Control Machine Operations

The introduction of Computerized Numeric Control (CNC) technology in manufacturing industries revolutionized the production process a few decades back. There are some health and safety problems associated with these machine operations, however. The main objectives of the present work is to study the health and safety issues associated with the CNC machines with respect to control and display, specifically to determine the frequency, intensity of discomfort, and its interference in operating different CNC machines as reported by the workers operating them. The postural discomfort associated with CNC machines was studied, and the frequency, intensity of discomfort, and interference of the level of discomfort with the participants' ability to work were recorded and analyzed. The study revealed that 20.5% of the operators reported discomfort 1 or 2 times, 25.4% experienced discomfort 3 to 4 times in a week, 37.7% had discomfort daily, and 16.4% reported discomfort several times a day. Discomfort was reported in all the body parts involved (lower back, neck, upper back, shoulder, and leg), but the highest discomfort scores were associated with the shoulder and arm region. Workers reporting discomfort several times a day also reported high mean discomfort scores. The study established that the frequency and intensity of the discomfort in all body parts is related to the position of the control panel and display. © 2012 Wiley Periodicals, Inc.     

A study of concurrency control in real-time, active databasesystems

Real-time active database systems (RTADBSs) have attracted a considerable amount of research attention in the past and a number of important applications have been identified for such systems, such as telecommunications network management, automated air traffic control, automated financial trading, process control and military command and control systems. In spite of the recognized importance of this area, very little research has been devoted to exploring the dynamics of transaction processing in RTADBSs. Concurrency control (CC) constitutes an integral part of any transaction processing strategy and, thus, deserves special attention. We study CC strategies in RTADBSs and postulate a number of CC algorithms. These algorithms exploit the special needs and features of RTADBSs and are shown to deliver substantially superior performance to conventional real-time CC algorithms     

A fresh consideration on the choice of radiometer operating frequencyin atmospheric remote sensing

Following the assertion of Westwater, on the consideration of the radiometer operating frequency around 22GHz for remote sensing of water vapour distribution in the atmosphere, a comprehensive study has been made to re-examine the validity of considering frequency away from resonant frequency for both dry locations, like Antarctica and for tropical region, Calcutta. Radiosonde data have been utilized to calculate line shape functions and weightingfunctions at different operating frequencies. Results indicate that water vapour sensitive 22·235 GHz is still better for dry climatic regions like Antarctica, whereas, for wet air locations, choice of frequency will be different from the resonance peak.     

Unsupervised band extraction for hyperspectral images using clustering and kernel principal component analysis

The ‘curse of dimensionality’ is a drawback for classification of hyperspectral images. Band extraction is a technique for reducing the dimensionality and makes it computationally less complex for classification. In this article, an unsupervised band extraction method for hyperspectral images has been proposed. In the proposed method, kernel principal component analysis (KPCA) is used for transformation of the original data, which integrates the nonlinear characteristics, as well as, the advantages of principal component analysis and extract higher order statistics of data. The KPCA is highly dependent on the number of patterns for calculating kernel matrix. So, a proper selection of subset of patterns, which represent the original data properly, may reduce the computational cost for the proposed method with considerably better performance. Here, density-based spatial clustering technique is first used to group the pixels according to their similarity, and then some percentages of pixels from each cluster are selected to form the proper subset of patterns. To demonstrate the effectiveness of the proposed clustering- and KPCA-based unsupervised band extraction method, investigation is carried out on three hyperspectral data sets, namely, Indian, KSC, and Botswana. Four evaluation measures, namely classification accuracy, kappa coefficient, class separability, and entropy are calculated over the extracted bands to measure the efficiency of the proposed method. The performance of the proposed method is compared with four state-of-the-art unsupervised band extraction approaches, both qualitatively and quantitatively, and shows promising results compared to them in terms of four evaluation measures.     

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.     

Design of particle-reinforced polyurethane mould materials for soft tooling process using evolutionary multi-objective optimization algorithms

Polyurethane is used for making mould in soft tooling (ST) process for producing wax/plastic components. These wax components are later used as pattern in investment casting process. Due to low thermal conductivity of polyurethane, cooling time in ST process is long. To reduce the cooling time, thermal conductive fillers are incorporated into polyurethane to make composite mould material. However, addition of fillers affects various properties of the ST process, such as stiffness of the mould box, rendering flow-ability of melt mould material, etc. In the present work, multi-objective optimization of various conflicting objectives (namely maximization of equivalent thermal conductivity, minimization of effective modulus of elasticity, and minimization of equivalent viscosity) of composite material are conducted using evolutionary algorithms (EAs) in order to design particle-reinforced polyurethane composites by finding the optimal values of design parameters. The design parameters include volume fraction of filler content, size and shape factor of filler particle, etc. The Pareto-optimal front is targeted by solving the corresponding multi-objective problem using the NSGA-II procedure. Then, suitable multi-criterion decision-making techniques are employed to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of the ST process for industrial applications. Finally, the experimental study with a typical real industrial application demonstrates that the obtained optimal design parameters significantly reduce the cooling time in soft tooling process keeping other processing advantages.     

Management Issues of a Mobile Agent-Based Service Environment

This paper introduces the concepts of a servicemanagement system for mobile agent-based services. Incontrast to several other approaches in whichagent-based applications are used to handletraditional network or service managementaspects, this paper describes a way to manage thedistributed agent environment itself. The proposedapproach was designed and developed by using OSI SystemsManagement concepts as a starting point, which are modified andadjusted in order to fulfill the new requirementsassociated with the mobile agent paradigm. However, thispaper does not cover integration or co-existence of the introduced agent management system (AMS)and traditional OSI management systems. Instead, theentire AMS environment is based on mobile agenttechnology. At present, this approach is validated inthe context of the European research project MobileAgent Environments in Intelligent Networks(MARINE).