Nitin Afzulpurkar

Micro Electromechanical Systems (MEMS) Based Microfluidic Devices for Biomedical Applications

Micro Electromechanical Systems (MEMS) based microfluidic devices have gained popularity in biomedicine field over the last few years. In this paper, a comprehensive overview of microfluidic devices such as micropumps and microneedles has been presented for biomedical applications. The aim of this paper is to present the major features and issues related to micropumps and microneedles, e.g., working principles, actuation methods, fabrication techniques, construction, performance parameters, failure analysis, testing, safety issues, applications, commercialization issues and future prospects. Based on the actuation mechanisms, the micropumps are classified into two main types, i.e., mechanical and non-mechanical micropumps. Microneedles can be categorized according to their structure, fabrication process, material, overall shape, tip shape, size, array density and application. The presented literature review on micropumps and microneedles will provide comprehensive information for researchers working on design and development of microfluidic devices for biomedical applications.

Optimization of tile manufacturing process using particle swarm optimization

Abstract In this paper, an integrated optimization approach using an artificial neural network and a bidirectional particle swarm is proposed. The artificial neural network is used to obtain the relationships between decision variables and the performance measures of interest, while the bidirectional particle swarm is used to perform the optimization with multiple objectives. Finally, the proposed approach is used to solve a process parameter design problem in cement roof-tile manufacturing. The results showed that the bidirectional particle swarm is an effective method for solving multi-objective optimization problems, and that an integrated approach using an artificial neural network and a bidirectional particle swarm can be used to solve complex process parameter design problems.

Shot boundary detection from videos using entropy and local descriptor

Video shot segmentation is an important step in key frame selection, video copy detection, video summarization, and video indexing for retrieval. Although some types of video data, e.g., live sports coverage, have abrupt shot boundaries that are easy to identify using simple heuristics, it is much more difficult to identify shot boundaries in other types such as cinematic movies. We propose an algorithm for shot boundary detection able to accurately identify not only abrupt shot boundaries, but also the fade-in and fade-out boundaries typical of cinematic movies. The algorithm is based on analysis of changes in the entropy of the gray scale intensity over consecutive frames and analysis of correspondences between SURF features over consecutive frames. In an experimental evaluation on the TRECVID-2007 shot boundary test set, the algorithm achieves substantial improvements over state of the art methods, with a precision of 97.8% and a recall of 99.3%.

Design, Fabrication and Analysis of Silicon Hollow Microneedles for Transdermal Drug Delivery System for Treatment of Hemodynamic Dysfunctions

In this paper, we present design, fabrication and coupled multifield analysis of hollow out-of-plane silicon microneedles with piezoelectrically actuated microfluidic device for transdermal drug delivery (TDD) system for treatment of cardiovascular or hemodynamic disorders such as hypertension. The mask layout design and fabrication process of silicon microneedles and reservoir involving deep reactive ion etching (DRIE) is first presented. This is followed by actual fabrication of silicon hollow microneedles by a series of combined isotropic and anisotropic etching processes using inductively coupled plasma (ICP) etching technology. Then coupled multifield analysis of a MEMS based piezoelectrically actuated device with integrated silicon microneedles is presented. The coupledfield analysis of hollow silicon microneedle array integrated with piezoelectric micropump has involved structural and fluid field couplings in a sequential structural-fluid analysis on a three-dimensional model of the microfluidic device. The effect of voltage and frequency on silicon membrane deflection and flow rate through the microneedle is investigated in the coupled field analysis using multiple code coupling method. The results of the present study provide valuable benchmark and prediction data to fabricate optimized designs of the silicon hollow microneedle based microfluidic devices for transdermal drug delivery applications.

Path planning for a mobile robot in a dynamic environment

Nowadays, mobile robots work under the dynamic environments like manufacturing industries with machinery parts as moving objects and are using many techniques for navigation, obstacle avoidance, and localization. In this work we are using pioneer 2 DX mobile robot for experiments. This paper focuses on development of algorithms with the integration of path planning by potential field method and Monte Carlo localization method for navigation, obstacle avoidance, and localization of the mobile robot in a dynamic environment like in manufacturing industry. The path planning algorithms has divided into two submodules, one is global path planning which uses visibility graph with A* search method and another is local path planning which uses potential field method to avoid the obstacles. The image processing is used to get the working environment information from the global camera. The robot control program uses MCL algorithms with gradient path planning for continuous localization. User-friendly path planning software PMADE V 2.0 is developed. PMADE v 2.0 is used for image processing, path planning, simulation of robot navigation, real robot manual control and real robot automatic control for navigation in dynamic environment from position data of the simulator.

Neuro-fuzzy MIMO nonlinear control for ceramic roller kiln

Abstract Artificial neural networks (ANNs) and neuro-fuzzy systems (NFSs) have been widely used in modeling and control of many practical industrial nonlinear processes. However, most of them have concentrated on single-output systems only. In this paper, we present a comparative study using ANNs and co-active neuro-fuzzy inference system (CANFIS) in modeling a real, complicated multi-input–multi-output (MIMO) nonlinear temperature process of roller kiln used in ceramic tile manufacturing line. Using this study, we prove that CANFIS is better suited for modeling the temperature process in control phase. After that, a neural network (NN) controller has been developed to control the above mentioned temperature process due to a feedback control diagram. The designed controller performance is tested by a Visual C++ project and the resulting numerical data shows that this controller can work accurately and reliably when the roller kiln set-point temperature set changes.

Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot

This paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance algorithm utilizing stereo vision technique has been implemented for obstacle detection. The odometry errors due to systematic-errors (such as unequal wheel diameter, the effect of the encoder resolution etc.) and/or non-systematic errors (ground plane, wheel-slip etc.) contribute to various motion control problems of the robot. During the robot moves, whether straight-line and/or arc, create the position and orientation errors which depend on systematic and/or non-systematic odometry errors. The main concern in most of the navigating systems is to achieve the real-time and robustness performances to precisely control the robot movements. The objective of this research is to improve the position and the orientation of robot motion. From the simulation and experiments, we prove that the proposed mobile robot moves from start position to goal position with greater accuracy avoiding obstacles.

Piezoelectric Energy Generation and Harvesting at the Nano-Scale: Materials and Devices

Continuous efforts are being made for alternative power generation techniques for use in devices with sub-micron-scale dimensions. In this work, we have perused through some of these efforts, focusing mainly on devices using materials with piezoelectric properties. In the last decade or so, nanostructured zinc oxide (ZnO) has drawn worldwide attention for its path- breaking properties. One of its most extensively-studied properties is its ability to generate power when subjected to mechanical vibration. It can generate a potential within a wide range of frequency vibrations, from a few Hz to thousands of KHz. This can lead to extensive application prospects in many important fields, like self-power generating devices for medical applications, wireless technologies and various sensors, etc. This review looks into reports related to such technology in detail. It also takes into account certain other materials that have been reported for piezoelectric energy scavenging applications.

PDMS Based Thermopnuematic Peristaltic Micropump for Microfluidic Systems

A thermopnuematic peristaltic micropump for controlling micro litters of fluid was designed and fabricated from multi-stack PDMS structure on glass substrate. Pump structure consists of inlet and outlet, microchannel, three thermopneumatic actuation chambers, and three heaters. In microchannel, fluid is controlled and pumped by peristaltic motion of actuation diaphragm. Actuation diaphragm can bend up and down by exploiting air expansion that is induced by increasing heater temperature. The micropump characteristics were measured as a function of applied voltage and frequency. The flow rate was determined by periodically recording the motion of fluid at Nanoport output and computing flow volume from height difference between consecutive records. From the experiment, an optimum flow rate of 0.82 Pl/min is obtained under 14 V three-phase input voltages at 0.033 Hz operating frequency.

Fuzzy-C-Mean determines the principle component pairs to estimate the degree of emotion from facial expressions

Although many systems exist for automatic classification of faces according to their emotional expression, these systems do not explicitly estimate the strength of given expressions. This paper describes and empirically evaluates an algorithm capable of estimating the degree to which a face expresses a given emotion. The system first aligns and normalizes an input face image, then applies a filter bank of Gabor wavelets and reduces the datas dimensionality via principal components analysis. Finally, an unsupervised Fuzzy-C-Mean clustering algorithm is employed recursively on the same set of data to find the best pair of principle components from the amount of alignment of the cluster centers on a straight line. The cluster memberships are then mapped to degrees of a facial expression (i.e. less Happy, moderately happy, and very happy). In a test on 54 previously unseen happy faces., we find an orderly mapping of faces to clusters as the subjects face moves from a neutral to very happy emotional display. Similar results are observed on 78 previously unseen surprised faces.