Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
14 results
Search Results
Item Effect of heat treatment on pitting corrosion resistance of 6061 Al/SiCP composite coated by the cerium oxide film in 3.5 N NaCl solution(2011) Rajasekaran, S.; Udayashankar, N.K.; Nayak, J.One of the main drawbacks of 6061 Al/SiCP composite is its poor pitting corrosion resistance in the aggressive environment containing chloride ions, such as seawater, for example. The present article deals with the investigations of effects of aging on the corrosion behavior of 6061 Al/SiCP composite and of the heat treatment on the pitting corrosion resistance of 6061 Al/SiCP composite coated by cerium oxide prepared by chemical bath technique. Potentiodynamic polarization test was used to study the corrosion behavior of cerium oxide coatings in 3. 5N NaCl solution. The microstructure of cerium oxide was examined by scanning electron microscopy (SEM) and the formed phases were identified by X-ray diffraction (XRD). The pitting corrosion resistance of the cerium oxide coating was found to be improved after heat treatment at 300°C for 30 min. © 2011 Allerton Press, Inc.Item Behavioral study of alumina nanoparticles in pool boiling heat transfer on a vertical surface(2011) Hegde, R.N.; Reddy, R.P.; Rao, S.S.Experiments were carried out to investigate the pool boiling of alumina-water nanofluid at 0.1 g/l to 0.5 g/l of distilled water, and the nucleate pool boiling heat transfer of pure water and nanofluid at different mass concentrations were compared at and above the atmospheric pressure. At atmospheric pressure, different concentrations of nanofluids display different degrees of deterioration in boiling heat transfer. The effect of pressure and concentration of nanoparticles revealed significant enhancement in heat flux and deterioration in pool boiling. The heat transfer coefficient of 0.5 g/l alumina-water nanofluid was compared with pure water and clearly indicates deterioration. At all pressures the heat transfer coefficients of the nanofluid were lower than those of pure water. Experimental observation revealed particles coating over the heater surface and subsequent SEM inspection of the heater surface showed nanoparticles coating on the surface forming a porous layer. To substantiate the nanoparticle deposition and its effect on heat flux, investigation was done by measuring the surface roughness of the heater surface before and after the experiment. While SEM images of the heater surface revealed nanoparticle deposition, surface roughness of the heater surface confirmed it. Based on the experimental investigations it can be concluded that an optimum thickness of nanoparticles coating favors an increase in heat flux. Higher surface temperature due to the presence of nanoparticles coating results in the deterioration of boiling heat transfer. © 2011 Wiley Periodicals, Inc.Item Chitosan/NiO nanocomposites: A potential new dielectric material(2011) Bhatt, A.S.; Bhat, D.K.; Santosh, M.S.; Tai, C.-W.The study of electrochemical behavior of organic-inorganic nanocomposite materials remains a major challenge for application in energy storage devices. Here, new composite materials of chitosan and NiO nanoparticles have been fabricated. The NiO nanoparticles are well characterized by infrared spectroscopy, X-ray diffraction and transmission electron microscopy. The electrical properties of the films are studied by impedance spectroscopy at different temperatures; and thereby permittivity, electric modulus and conductivity data are obtained. By studying the variations in permittivity and electric modulus spectra with respect to applied frequency signal and temperature, the ionic conductivity of the material is investigated. The Correlated Barrier Hopping model is employed to understand the conduction mechanism. An admirable conductivity of 1.4 × 10-2 S cm -1 is obtained for a nanocomposite with 4 wt% NiO content. The activation energies of the composite films decrease with increase in NiO content, from 16.5 to 4.8 kJ mol-1. © 2011 The Royal Society of Chemistry.Item Nonlinear optical characterization of new thiophene-based conjugated polymers for photonic switching applications(2011) Hegde, P.K.; Vasudeva Adhikari, A.V.; Manjunatha, M.G.; Suchand Sandeep, C.S.S.; Philip, R.This research article describes a technique to synthesize new donor-acceptor-type conjugated polymers carrying 1,3,4-oxadiazolyl-naphthalene and 3,4-(ethylenedioxy/diphenyl)-thiophene moieties (P1 and P2) starting from 2,2?-sulfanediyldiacetic acid and diethyl ethanedioate through multistep reactions. The newly synthesized intermediates and the final polymers have been characterized by different spectroscopic techniques followed by elemental analysis. Their optical and electrochemical properties have been investigated by UV-visible, fluorescence spectroscopy, and cyclic voltammetric studies, respectively. Furthermore, the nonlinear optical transmission properties of these polymers have been investigated by the open aperture z-scan technique. The new polymers P1 and P2 have well-defined structures, good thermal stability, and band gaps of 1.98 and 1.88 eV, respectively. They emit bluish-green fluorescence both in solution and in film state. Interestingly, these polymers show saturable absorption behavior. The results of nonlinear optical studies reveal that they are potential candidates for photonic switching device applications. © 2011 Wiley Periodicals, Inc.Item Study of unique merging behavior under mixed traffic conditions(Elsevier Ltd, 2015) Kanagaraj, V.; Srinivasan, K.K.; Sivanandan, R.; Asaithambi, G.Roads in developing countries carry mixed traffic with wide variations in static and dynamic characteristics of vehicles. The traffic flow is also generally devoid of lane discipline, with vehicles occupying any available road space ahead. In such a regime of traffic flow, the phenomena of merging of vehicles at intersections of two roads is complex, warranting further study. The merging maneuvers at T-intersections under congested traffic conditions were studied microscopically through video-recording. In congested situations, the merging vehicle attempts a complex merging maneuver to enter the main traffic stream. Two unique merging processes are commonly observed in mixed traffic: group and vehicle cover merging (these are generally not observed in countries such as US). The author is using these words first time in this study. These reflect the different types of driver behavior - merging in groups, and by taking cover of another vehicle. Probabilistic models for group and vehicle cover merging are developed that capture this unique merging behavior. Comprehensive microscopic data collection and extraction were carried out to study the merging process at T-intersection under congested conditions. Merging models were then estimated using maximum likelihood method with disaggregate data that was collected for a case study T-intersection in Chennai city, India. Such models can find applications in simulation of highly congested traffic flow in a realistic manner under mixed traffic conditions. They can also give insights on devising better traffic control measures at such intersections. © 2015 Elsevier Ltd.Item Evaluation of right-turn lanes at signalized intersection in non-lane-based heterogeneous traffic using microscopic simulation model(Maney Publishing michael.wagreich@univie.ac.at, 2015) Asaithambi, G.; Sivanandan, R.In developing countries like India, the traffic on urban roads is highly heterogeneous in nature, with vehicles of widely varying static and dynamic characteristics. This type of traffic is characterized by lack of queue and lane discipline (lane-less movement) based on availability of spaces near intersections. Moreover, at intersections, straight-through, left-, and right-turning vehicles seek to occupy the same physical space. In such situations, the through vehicles are susceptible to delays in the absence of turn lanes for the left-turning and right-turning vehicles and vice versa. Models suitable for analysis of such traffic flow hardly exist, and most of the available models are limited in scope. In the current study, a microscopic traffic simulation model for signalized intersection is developed specifically for heterogeneous traffic. This model covers different vehicle types and allows for some special behavior, such as seepage of two-wheelers to fronts of queues. Detailed study of queue formation and dissipation were done microscopically under non-lane-based traffic conditions near intersection area. The model was calibrated and tested with data from Chennai city, India, and its predictions were found to be in close agreement with the field data. In addition, the model makes a significant contribution to the study of right-turn lane (RTL) on delays to vehicles. In general, RTL is found to be advantageous for most cases of approach volumes and right-turn proportions. The optimal lengths of RTL are suggested for various approach volumes and right-turn proportions. © 2015 W. S. Maney & Son Ltd.Item Assessing mobile health applications with twitter analytics(Elsevier Ireland Ltd, 2018) Pai, R.R.; Alathur, S.Introduction: Advancement in the field of information technology and rise in the use of Internet has changed the lives of people by enabling various services online. In recent times, healthcare sector which faces its service delivery challenges started promoting and using mobile health applications with the intention of cutting down the cost making it accessible and affordable to the people. Objectives: The objective of the study is to perform sentiment analysis using the Twitter data which measures the perception and use of various mobile health applications among the citizens. Methods: The methodology followed in this research is qualitative with the data extracted from a social networking site “Twitter” through a tool RStudio. This tool with the help of Twitter Application Programming Interface requested one thousand tweets each for four different phrases of mobile health applications (apps) such as “fitness app” “diabetes app” “meditation app” and “cancer app”. Depending on the tweets, sentiment analysis was carried out, and its polarity and emotions were measured. Results: Except for cancer app there exists a positive polarity towards the fitness, diabetes, and meditation apps among the users. Following a system thinking approach for our results, this paper also explains the causal relationships between the accessibility and acceptability of mobile health applications which helps the healthcare facility and the application developers in understanding and analyzing the dynamics involved the adopting a new system or modifying an existing one. © 2018 Elsevier B.V.Item A visual attention guided unsupervised feature learning for robust vessel delineation in retinal images(Elsevier Ltd, 2018) Srinidhi, C.L.; Aparna., P.; Rajan, J.Background and objective: Accurate segmentation of retinal vessels from color fundus images play a significant role in early diagnosis of various ocular, systemic and neuro-degenerative diseases. Segmenting retinal vessels is challenging due to varying nature of vessel caliber, the proximal presence of pathological lesions, strong central vessel reflex and relatively low contrast images. Most existing methods mainly rely on carefully designed hand-crafted features to model the local geometrical appearance of vasculature structures, which often lacks the discriminative capability in segmenting vessels from a noisy and cluttered background. Methods: We propose a novel visual attention guided unsupervised feature learning (VA-UFL) approach to automatically learn the most discriminative features for segmenting vessels in retinal images. Our VA-UFL approach captures both the knowledge of visual attention mechanism and multi-scale contextual information to selectively visualize the most relevant part of the structure in a given local patch. This allows us to encode a rich hierarchical information into unsupervised filtering learning to generate a set of most discriminative features that aid in the accurate segmentation of vessels, even in the presence of cluttered background. Results: Our proposed method is validated on the five publicly available retinal datasets: DRIVE, STARE, CHASE_DB1, IOSTAR and RC-SLO. The experimental results show that the proposed approach significantly outperformed the state-of-the-art methods in terms of sensitivity, accuracy and area under the receiver operating characteristic curve across all five datasets. Specifically, the method achieved an average sensitivity greater than 0.82, which is 7% higher compared to all existing approaches validated on DRIVE, CHASE_DB1, IOSTAR and RC-SLO datasets, and outperformed even second-human observer. The method is shown to be robust to segmentation of thin vessels, strong central vessel reflex, complex crossover structures and fares well on abnormal cases. Conclusions: The discriminative features learned via visual attention mechanism is superior to hand-crafted features, and it is easily adaptable to various kind of datasets where generous training images are often scarce. Hence, our approach can be easily integrated into large-scale retinal screening programs where the expensive labelled annotation is often unavailable. © 2018 Elsevier LtdItem Finite difference method based analysis of bio-heat transfer in human breast cyst(Elsevier Ltd, 2019) Patil, H.M.; Maniyeri, R.Bio-heat transfer is a branch of bio-medical engineering which has its foundation linked to engineering disciplines of heat transfer. The thermal properties and behaviour of various malfunctioning tissues in human body varies as compared with normal tissues. Among various cancer tissues one which is commonly diagnosed in women is breast cyst (cancer causing fluid). The aim of present work is to develop one, two and three-dimensional computational models to study bio-heat transfer problems using finite difference method. First of all, a numerical model based on finite difference method is developed to solve Pennes's bio-heat transfer equation in one-dimension to get temperature profiles normal to skin surface and validated with existing analytical solutions. Secondly, the numerical model is extended to study the thermal behaviour of human breast section embedded with cyst using two-dimensional cylindrical coordinate systems and validated with previous researcher's results. The effect of size, location and presence of multiple cysts on surface temperature is studied. Lastly, the work is extended for the case of three-dimensional breast section with cyst located at the centre. The numerical results obtained using one, two and three-dimensional computational models will be highly helpful in the early detection of breast cancer tissues and also the location of it inside the body. © 2019Item Multimodal behavior analysis in computer-enabled laboratories using nonverbal cues(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2020) Banerjee, S.; Ashwin, T.S.; Guddeti, R.M.R.In the modern era, there is a growing need for surveillance to ensure the safety and security of the people. Real-time object detection is crucial for many applications such as traffic monitoring, security, search and rescue, vehicle counting, and classroom monitoring. Computer-enabled laboratories are generally equipped with video surveillance cameras in the smart campus. But, from the existing literature, it is observed that the use of video surveillance data obtained from smart campus for any unobtrusive behavioral analysis is seldom performed. Though there are several works on the students’ and teachers’ behavior recognition from devices such as Kinect and handy cameras, there exists no such work which extracts the video surveillance data and predicts the behavioral patterns of both the students and the teachers in real time. Hence, in this study, we unobtrusively analyze the students’ and teachers’ behavioral patterns inside a teaching laboratory (which is considered as an indoor scenario of a smart campus). Here, we propose a deep convolution network architecture to classify and recognize an object in the indoor scenario, i.e., the teaching laboratory environment of the smart campus with modified Single-Shot MultiBox Detector approach. We used six different class labels for predicting the behavioral patterns of both the students and the teachers. We created our dataset with six different class labels for training deep learning architecture. The performance evaluation demonstrates that the proposed method performs better with an accuracy of 0.765 for classification and localization. © 2020, Springer-Verlag London Ltd., part of Springer Nature.