Department of Engineering Design

A comparative study has been made for micro-scribing of copper and aluminum thin films in air and underwater using 355nm, 532nm and 1064nm wavelengths of a Q-switched Nd3+: YAG laser with 6ns pulse duration. For aluminum in air medium, the channel depth obtained is high for 355nm wavelength, whereas for copper coated on a polyimide substrate, 532nm wavelengths produced higher depth. In underwater scribing, with increase in the pulsed laser energy, the depth of micro channel was increased and remained unchanged at higher energy. The influence of beam profile on the micro channel cross-section has also been discussed. Further, theoretical modeling of the laser-material interaction in air and underwater ambience conditions to estimate the recession rate has been discussed by incorporating the laser ablation temperature measured using the laser induced breakdown spectroscopy technique.

Given a planar point set sampled from a curve, the curve reconstruction problem computes a polygonal approximation of the curve. In this paper, we propose a Delaunay triangulation-based algorithm for curve reconstruction, which removes the longest edge of each triangle to result in a graph. Further, each vertex of the graph is checked for a degree constraint to compute simple closed/open curves. Assuming ϵ-sampling, we provide theoretical guarantee which ensures that a simple closed/open curve is a piecewise linear approximation of the original curve. Input point sets with outliers are handled as part of the algorithm, without pre-processing. We also propose strategies to identify the presence of noise and simplify a noisy point set, identify self-intersections and enhance our algorithm to reconstruct such point sets. Perhaps, this is the first algorithm to identify the presence of noise in a point set. Our algorithm is able to detect closed/open curves, disconnected components, multiple holes and sharp corners. The algorithm is simple to implement, independent of the type of input, non-feature specific and hence it is a generalized one. We have performed extensive comparative studies to demonstrate that our method is comparable or better than other existing methods. Limitations of our approach have also been discussed.

Travel time is one of the most preferred traffic information by a wide variety of travelers. Travel time information provided through variable message signs at the roadside could be viewed as a traffic management strategy designed to encourage drivers to take an alternate route. At the same time, it could also be viewed as a traveler information service designed to ensure that the driver has the best available information based on which they can make travel decisions. In an Intelligent Transportation Systems (ITS) context, both the Advanced Traveler Information Systems (ATIS) and the Advance Traffic Management Systems (ATMS) rely on accurate travel time prediction along arterials or freeways. In India, currently there is no permanent system of active test vehicles or license plate matching techniques to measure stream travel time in urban arterials. However, the public transit vehicles are being equipped with Global Positioning System (GPS) devices in major metropolitan cities of India for providing the bus arrival time information at bus stops. However, equipping private vehicles with GPS to enable the stream travel time measurement is difficult due to the requirement of public participation. The use of the GPS equipped buses as probe vehicles and estimating the stream travel time is a possible solution to this problem. The use of public transit as probes for travel time estimation offers advantages like frequent trips during peak hours, wide range network coverage, etc. However, the travel time characteristics of public transit buses are influenced by the transit characteristics like frequent acceleration, deceleration and stops due to bus stops besides their physical characteristics. Also, the sample size of public transit is less when compared to the total vehicle population. Thus mapping the bus travel time to stream travel time is a real challenge and this difficulty is more complex in traffic conditions like in India with its heterogeneity and lack of lane discipline. As a pilot study, a model based approach using the Kalman filtering technique to predict stream travel time from public transit is carried out in the present study. Since it is only a pilot study, only twowheeled vehicles have been considered as they constitute a major proportion in the study area. The prediction scheme is corroborated using field data collected by carrying GPS units in two-wheelers traveling along with the buses under consideration. The travel time estimates from the model were compared with the manually observed travel times and the results are encouraging. © 2011 IEEE.

The performance of the genetic algorithm (GA) and particle swarm optimization (PSO) was compared to identify the best-suited algorithm for hyperthermia treatment planning (HTP) of breast cancer. Both algorithms were tested on four heterogeneous patient breast models derived from magnetic resonance (MR) images. Electromagnetic (EM) simulations indicate that PSO induces 5.7% less hotspot to target quotient (HTQ) compared to GA. However, coupled EM and thermal simulations of four patient models indicate that GA based HTP induces 1.25 °C - 3.87 °C higher average temperature in cancer tissue with limited thermal hotspots in healthy tissue when compared to PSO algorithm. This was observed to be due to the low power level assigned to each channel by PSO compared to GA. Coupled simulations of heterogeneous patient models indicate GA is a better global optimization algorithm for HTP of breast cancer.

One of the major problems in an electrical insulation structure is its failure while operating at normal voltage stress which is due to electrical treeing. It is well-known that this electrical tree grows progressively and is damaging locally. To analyze the electrical treeing in the laboratory, not being cost effective, computer simulations are used. We have employed a known cellular automata method with new parallel processing techniques to reduce the computation time considering the available parallel processing systems. The major advantage is that the cellular automata algorithm inherently exhibits parallelism paving the way for ample exploitation. Moreover the parallelisation has helped to understand various aspects of electrical treeing also in a simple way.

Epileptic seizures are characterized by the excessive and abrupt electrical discharge in the brain. This asynchronous firing of neurons causes unprovoked convulsions which can be a cause of sudden unexpected death in epilepsy (SUDEP). Remote monitoring of epileptic patients can help prevent SUDEP. Systems based on wearable accelerometer sensors have shown to be effective in ambulatory monitoring of epileptic patients. However, these systems have a trade-off between seizure duration and the false alarm rate (FAR). The FAR of the system decreases as we increase the seizure duration. Further, multiple sensors are used in conjugation to improve the overall performance of the detection system. In this study, we propose a system based on single wrist-worn accelerometer sensor capable of detecting seizures with short duration (≥ 10s). Seizure detection was performed by employing machine learning approach such as kernelized support vector data description (SVDD). The proposed approach is validated on data collected from 12 patients, corresponding to approximately 966h of recording under video-telemetry unit. The algorithm resulted in a seizure detection sensitivity of 95.23% with a mean FAR of 0.72=24h.

Cervical spine is a mobile area of spine with high susceptibility to injury like sport injuries, pilot ejection, falls, vehicular accidents, etc. Use of finite element (FE) model in understanding the kinematics will provide an insight into the mechanism of neck injuries. A three dimensional (3D) anatomically detailed FE model of cervical spine was developed using computer tomography (CT) images. The model consisted of 39,419 elements with 10,411 nodes. Important anatomical features viz., cortical bone, cancellous bone, transverse process, spinous process, laminae, intervertebral disc, spinal canal were clearly defined for each spinal segment. Material properties were obtained from literature and boundary conditions were simulated similar to the in vitro experiment against which it is validated. Intervertebral range of motion of FE model was compared with previous in vitro and in vivo studies. These comparisons substantiated that, this FE model can effectively reflect physiological motions of human cervical spine and can be used further to study cervical spine injury and dysfunction. © 2006 Research Publishing Services.

The primary challenge in implementing teleoperated master-slave robots is that both of its objectives - stability and transparency, are conflicting to each other. This trade-off is usually attributed to the time-delay in the communication channel, and state-of-the-art controllers are proposed primarily to counteract the effects of this time delay. Despite such controllers, it is observed that the system suffers from instability and inaccurate force feedback (loss of transparency), at least under certain conditions. This is because issues other than time delay which cause oscillations and inaccurate force feedback are rarely addressed in the literature. In this paper, such issues are clearly identified and it is shown here that controller design cannot counteract these issues. It is proposed in this paper that an isotropy based design of robots is necessary for recovering the additional stable and transparent behavior of the system, apart from what a controller can achieve. Another significant contribution of this paper is that because of the proposed design, the need for two signals from the traditional four-channel teleoperation architecture is eliminated, thus reducing the complexity of the system. Experimental validation is carried out by implementing a two-channel architecture on the designed robots.

The measurement of hand kinematics is important for the assessment and rehabilitation of the paralysed hand. The traditional method of hand function assessment uses a mechanical or electronic goniometer placed across the joint of interest to measure the range of joint movement. Mechanical goniometers are imprecise and lack the ability to provide a dynamic measurement; electronic goniometers are expensive and cumbersome to use during therapy. An alternative to the goniometric based assessment is to use inertial motion sensors to monitor the hand movement - these can be incorporated in a glove. In this paper, we present the design of an instrumented glove equipped with Magnetic, Angular Rate and Gravity (MARG) sensors for the objective evaluation of hand function. The instrumented glove presented in this paper is designed to assess the range of movement of the hand and also monitor the hand function during the course of hand rehabilitation. Static and dynamic calibrations were performed for the Euler angles calculated from the MARG sensors. The results are also presented for physiological flexion/extension of the wrist (relative roll), flexion/extension of elbow (relative pitch), and internal rotation/external rotation (relative yaw). The static calibration results gave mean absolute errors of 4.1° for roll, 4.0° for pitch, and 4.6° for yaw. From the dynamic calibration, the speed of response to a step change gave a convergence time of 0.4 s; sinusoidally oscillating movement gave good tracking at 0.2 Hz but exhibits overshoot errors at higher frequencies which were tested to be 1 Hz. We present the results of the calibration of the instrumented glove (one sensor pair measuring one joint angle) measuring anatomical joint angles - mean absolute errors during static calibration: 6.3° for a relative roll (wrist flexion/extension), 5.0° for relative pitch (elbow flexion/extension), and 4.5° for relative yaw (shoulder internal rotation/external rotation). The experimental results from the instrumented glove are promising, and it can be used as an alternative to the traditional goniometer based hand function assessments.

The 3-RRS parallel manipulator presented in this study comprises of parallel revolute joint axes in each leg. The manipulator is composed of a base and a moving platform which are in the shape of equilateral triangles. Moving platform has two rotational and one translational degrees-of-freedom. This study formulates the forward and inverse kinematics of the parallel manipulator. A 16th order polynomial in terms of one of the passive joint variables is obtained for the forward kinematic analysis. Numerical results and the corresponding pose of the manipulator for inverse and forward kinematics are presented.