A novel microfluidic switch for pH control using Chitosan based hydrogels

We report a novel pH-sensitive hydrogel based micro-valve for metered flow that has applications in a laboratory made “Intelligent valving system”. The hydrogel solution was prepared through Chitosan and poly vinyl alcohol in acetic acid and crystallized using gluteraldehyde as the crosslinking agent in the form of thin wafers and it was found to be very sensitive to pH changes. The pore structure of hydrogel was investigated through Field Emission Scanning Electron Microscopy and thin wafers of the gel were physically placed inside PDMS microchannels. Flow metering in these channels was observed by controlled expansion of the hydrogel plug till complete valving was realized. This valving device was further precisely characterized with micro Particle Image Velocimetry using a solution containing fluorescent polymeric micro beads. The principle advantage of this hydrogel device is the smaller range of pH (varying between pH 3 and 7) over which the valving response is observed.     

Exhaustive and heuristic search approaches for learning a software defect prediction model

In this paper, we propose a software defect prediction model learning problem (SDPMLP) where a classification model selects appropriate relevant inputs, from a set of all available inputs, and learns the classification function. We show that the SDPMLP is a combinatorial optimization problem with factorial complexity, and propose two hybrid exhaustive search and probabilistic neural network (PNN), and simulated annealing (SA) and PNN procedures to solve it. For small size SDPMLP, exhaustive search PNN works well and provides an (all) optimal solution(s). However, for large size SDPMLP, the use of exhaustive search PNN approach is not pragmatic and only the SA–PNN allows us to solve the SDPMLP in a practical time limit. We compare the performance of our hybrid approaches with traditional classification algorithms and find that our hybrid approaches perform better than traditional classification algorithms.     

A distributed problem‐solving framework for probabilistic software effort estimation

Distributed problem‐solving (DPS) systems use a framework of human organizational notions and principles of intelligent systems to solve complex problems. Human organizational notions are used to decompose a complex problem into sub‐problems that can be solved using intelligent systems. The solutions of these sub‐problems are combined to solve the original complex problem. In this paper, we propose a DPS system for probabilistic estimation of software development effort. Using a real‐world software engineering dataset, we compare the performance of the DPS system with a neural network (NN) and show that the performance of the DPS system is equal to or better than that of the NN with the additional benefits of modularity, probabilistic estimates, greater interpretability, flexibility and capability to handle incomplete input data.     

A parametrization for dissipative behaviors

The behavioral equivalent of single input single output (SISO) systems are behaviors with two manifest variables. Passive SISO systems can, therefore, be viewed as J-dissipative behaviors with two manifest variables. Here the special matrix J defines a QDF that captures the passivity property of SISO systems. In this paper, we investigate more general QDFs Q_Φs induced by some operator Φ. These QDFs define some relation between the input, the output and their derivatives of a SISO system. We characterize all behaviors that are dissipative with respect to the prescribed QDF Q_Φ. In fact, we parametrize all the behaviors dissipative with respect to Q_Φ in terms of those dissipative with respect to the special QDF Q_J induced by the matrix J. Similar results can also be given for lossless systems.     

Survey of GPU Based Sorting Algorithms

Parallel sorting algorithms are widely studied nowadays. After the introduction of parallel processors such as graphics processing unit (GPU) and easy to use parallel programming languages such as CUDA and OpenCL, literature on parallel sorting algorithms has become vast and richer with new ideas and techniques applied to solve the famous problem of sorting. This paper presents a survey of GPU based sorting algorithms. Four sorting algorithms have been selected for this survey: Radix sort, Merge sort, Sample sort and Quick sort. Methods used in those algorithms are described in brief. The performance of these algorithms as claimed by their authors is also presented. A comparative analysis based on the literature is depicted.     

A maximum-margin genetic algorithm for misclassification cost minimizing feature selection problem

We consider a feature selection problem where the decision-making objective is to minimize overall misclassification cost by selecting relevant features from a training dataset. We propose a two-stage solution approach for solving misclassification cost minimizing feature selection (MCMFS) problem. Additionally, we propose a maximum-margin genetic algorithm (MMGA) that maximizes margin of separation between classes by taking into account all examples as opposed to maximizing margin of separation using a few support vectors. Feature selection is carried out by either an exhaustive or a heuristic simulated annealing approach in the first stage and a cost sensitive classification using either MMGA or cost sensitive support vector machines (SVM) in the second stage. Using simulated and real-world data sets and different misclassification cost matrices, we test our two-stage approach for solving the MCMFS problem. Our results indicate that feature selection plays an important role when misclassification cost asymmetries increase and the MMGA shows equal or better performance than the SVM.     

Kalman–Yakubovich lemma in the behavioural setting

In this paper, the Kalman–Yakubovich lemma is formulated and proved in the behavioural theoretic setting. The behavioural framework is used to generalize the lemma, for behaviours with two manifest variables, with respect to supply rates that are quadratic differential forms (QDFs).     

Simulation and analysis of Awerbuch–Peleg and GSM schemes for location tracking of mobile users

Mobile users are increasingly demanding full access to networked communications while they are on the move. Several studies have shown that the overhead incurred by the network to keep track of the current location of mobile users is considerably high. The methods currently used for location tracking incur heavy unnecessary costs by requiring that users update locations in their home networks after each move regardless of the distance at which the move occurs, and that all search attempts for a mobile user are first routed to that user's home network. The Awerbuch–Peleg scheme presents a formal model for location tracking which attempts to minimize the cost of local operations—both move and find operations—through the construction of a regional hierarchy. In this paper we present a performance evaluation of the Awerbuch–Peleg scheme. We also compare its performance to that of the GSM‐based location tracking scheme. It is found that the Awerbuch–Peleg scheme in general results in higher costs than the GSM scheme. The reason for this is found to be some unexpected properties of the read and write sets which are key components of the Awerbuch–Peleg scheme. Copyright © 2001 John Wiley & Sons, Ltd.     

Evaluation of Bilayer Tablet Machines—A Case Study

Four bilayer tablet compression machines were evaluated for their suitability for compression of a specific bilayer tablet formulation. Tablet machines evaluated were: Manesty (Model No. BB4), Manesty (Model No. Rotappress), Fette (Model No. P3102) and Kilian (Model No. 51AST-ZS) tablet presses. The tablet delamination tendency was the primary acceptance criteria for the evaluation of tablet press performance. The compression force on layer I was found to be the major factor influencing tablet delamination. It was found that the Kilian press was best suited for the compression of the model bilayer tablet formulation. The Kilian press is equipped with a special sampling device for layer I which allows additional compression force to be applied on layer I only at the time of weight sampling. The sampling device then returns to the original set points after sampling is completed. This feature maintains the compression force on layer I to a minimum during routine compression. Data indicated that the compression force on layer I and the compression zone in the die cavity of layer II were two factors needing to be controlled in order to yield bilayer tablets with acceptable physical characteristics.