Showing papers by "College of Engineering, Pune published in 2014"

Sliding Mode Control for Mismatched Uncertain Systems Using an Extended Disturbance Observer

Abstract: This paper extends a recent result on sliding mode control for general n th order systems with mismatched uncertainties. In this paper, a control is proposed to handle a larger class of mismatched uncertainties by extending the disturbance observer and modifying and generalizing the sliding surface. The practical stability of the overall system is proved and the results are verified by simulation of an illustrative example.

Conducting polymers for corrosion protection: a review

Abstract: Conducting polymers (CPs) such as polyaniline (PANI), polypyrrole (PPy), and polythiophene (PTh) are used for the corrosion protection of metals and metal alloys. Several groups have reported diverse views about the corrosion protection by CPs and hence various mechanisms have been suggested to explain anticorrosion properties of CPs. These include anodic protection, controlled inhibitor release as well as barrier protection mechanisms. Different approaches have been developed for the use of CPs in protective coatings (dopants, composites, blends). A judicious choice of synthesis parameters leads to an improvement in the anticorrosion properties of the coatings prepared by CPs for metals and their alloys. This article is prepared as a review of the application of CPs for corrosion protection of metal alloys.

Short communication: Algorithm to determine ε-distance parameter in density based clustering

Abstract: The well known clustering algorithm DBSCAN is founded on the density notion of clustering. However, the use of global density parameter @e-distance makes DBSCAN not suitable in varying density datasets. Also, guessing the value for the same is not straightforward. In this paper, we generalise this algorithm in two ways. First, adaptively determine the key input parameter @e-distance, which makes DBSCAN independent of domain knowledge satisfying the unsupervised notion of clustering. Second, the approach of deriving @e-distance based on checking the data distribution of each dimension makes the approach suitable for subspace clustering, which detects clusters enclosed in various subspaces of high dimensional data. Experimental results illustrate that our approach can efficiently find out the clusters of varying sizes, shapes as well as varying densities.

Influence of Cryoprocessing on Mechanism of Carbide Development in Cobalt-Bearing High-Speed Steel (M35)

Abstract: Cryogenic treatment has been used commonly to high-speed tool steels to enhance the wear resistance of the materials In the current research study, specimens of complex alloyed high-speed tool steel (M35) were hardened at 1473 K (1200 °C), triple tempered at 673 K (400 °C) and then cryogenically treated at 88 K (−185 °C) for varying lengths of period starting from 16 to 48 hours of cryosoaking followed by soft tempering at 373 K (100 °C) These treated specimens were studied as a function of cryosoaking period for their electrical resistivity, residual compressive stress, and its correlation with carbide density was established TEM analysis indicated carbide size 0156 to 1 μm, which confirms that the cryogenic treatment enhances the precipitation of finer carbides Lower residual stresses in the higher carbide density regimes identified in 2D contour map were explained by the stress relaxation in the matrix through precipitation of incoherent carbides

Pack-Boronizing of AISI 4140 Steel: Boronizing Mechanism and the Role of Container Design

Abstract: In this study, pack-boronizing of AISI 4140 steel was done. Three mild-steel containers with different size, namely, small-size container (SC), medium-size container (MC), and big-size container (BC) were used. Steel specimens were boronized at 950°C for 2 or 3 h. Preconditioning of the containers was observed to be essential before doing final pack-boronizing of steel. MC was found suitable for the formation of monophase Fe2B layer while BC produced unwanted FeB phase along with Fe2B layer. Fe2B phase showed the columnar morphology. Continuous decrease in the hardness from surface to nonboronized core was observed. Maximum surface hardness of about 1367 HV0.1 was obtained (hardness of nonboronized core was about 252 HV0.1) for the boronized steel. As compared to the normalized and hardened–tempered (HT) AISI 4140 steel pins, boronized steel pin showed the lowest “specific wear rate” (0.89 × 10−6 mm3/Nm) and coefficient of friction (COF) (0.55).

Dual watermarking technique with multiple biometric watermarks

Abstract: In order to improve the robustness of the watermarking algorithm, a dual watermarking method is proposed to prove copyright ownership. Visible watermarking is important for protecting online resources from unauthorized reproduction. However robust, visible watermarks are vulnerable to illegal removal and other common signal processing and geometric attacks. Multiple invisible watermarks can enhance the protection of the visibly watermarked image. When the ownership of tampered image is in question, the invisible watermark can be extracted to provide appropriate ownership information. We have proposed dual watermarking scheme with multiple biometric watermarks in which it embeds speech and face biometric traits of owner invisibly and lastly offline signature is overlaid translucently on image. Before embedding, speech is compressed using Linear Predictive Coding (LPC) and Gabor face is created from face biometric trait. All three watermarks Gabor face, LPC coefficients and offline signature are the biometric characteristics of the owner and hence they are highly related with copyright holder. The proposed scheme is robust enough, Gabor face and LPC coefficients can be extracted from the signature marked image or even from the tampered image from which signature is removed illegally or legally. As multiple watermarks are embedded at least one watermark survives under different attacks. It can find application for joint ownership or to address single ownership multiple times.

An investigation of temperature effects on solar photovoltaic cells and modules

Abstract: The solar photovoltaic (PV) systems are facing serious problems due to unavoidable losses in their system, leads to more devation of output power from the input power level. This effect is known as a mismatch effect and is available in PV systems. Many losses are encountered in PV system and it is difficult to minimize such losses. In this paper, the influence of thermal effect on the solar PV system is considered and its influence on the performance of the operation, fill factor, open circuit voltage, and short circuit current, band gap level of various semiconductor materials, output power and efficiency are analyzed. The temperature effect of a solar PV cell, while connecting in a 36 cells in a module is analyzed for the various connection configurations like Simple Series configuration (SS), Series-Parallel configuration (SP), Total-Cross Tied configuration (TCT), Bridge-Linked configuration (BL), and HoneyComb configuration (HC) using MATLAB software. Increases the level of temperature for various connection configurations, correspondingly decreases their open circuit voltage, series resistance. Shunt resistance and current are may not fully affects due to temperature. Finally this problem creates a heating effect in the solar PV cell, so the life span of the photovoltaic panel is decreased gradually. While increases the temperature level soldering points are affected and cell encapsulation is affects. Solar cell materials are changed their performance of operation,while changes in the band gap with the effect of temperature.

Robust sliding mode control for a class of nonlinear systems using inertial delay control

Abstract: This paper proposes a robust sliding mode control strategy for an uncertain nonlinear system subjected to time-varying disturbance. The class of system considered includes state-dependent nonlinearity in the input vector (in addition to the plant matrix). The control scheme uses inertial delay control to estimate the lumped uncertainty. The proposed control enforces sliding without using the discontinuous control and without requiring the knowledge of uncertainties or their bounds. The overall stability of the system is proved. The effectiveness of the proposed strategy is verified for model following and robust performance, by simulation of an illustrative example and an application to inverted pendulum system.

Thermal and Dielectric Properties of High Performance Polymer/ZnO Nanocomposites

Abstract: Zinc oxide (ZnO) filled high performance poly(aryletherketon) (PAEK) matrix nanocomposites were studied for the application in electronic applications. The nanocomposites were prepared using planetary ball milling process followed by hot pressing. Experimental density of the nanocomposites was close to those of theoretical density indicating porosity free samples. Scanning electron microscopy showed excellent dispersion of nano sized (< 100 nm) ZnO particles into the PAEK matrix. X-ray diffraction (XRD) confirmed that the size of ZnO crystallites is about 58 nm. Thermogravimetry analyzer (TGA) showed significant increase in thermal stability and char yield of the nanocomposites with increasing ZnO content in the matrix. The dielectric constants of the nanocomposites increased significantly compared to those of pure PAEK.

Comparative study of various traffic generator tools

Abstract: In our paper we have compared the performance of network evaluation tools (PackETH, Ostinato, and D-ITG) over 10Gbps link. The performance of these tools was evaluated in terms of bandwidth utilization over the link. In laboratory setup, two computers with Linux operating systems were connected via 10Gbps crossover cable. TCP and UDP traffic for the payload sizes varying from 64Bytes to 8950bytes was generated by tools and the corresponding throughput was measured. The performance of D-ITG in multithreaded mode is compared with Iperf. For TCP connection Ostinato measured highest bandwidth of 9Gbps while for UDP traffic packETH achieved a throughput of 9.9Gbps. Since D-ITG was not able to achieve such a high throughput we tried to run it in multithread mode for a constant payload size (<;1500 Bytes) and its performance is then compared to Iperf.

Stock market prediction using Hidden Markov Model

Abstract: Stock market is the most popular investment scheme promising high returns albeit some risks. An intelligent stock prediction model would thus be desirable. So, this paper aims at surveying recent literature in the area of Neural Network, Hidden Markov Model and Support Vector Machine used to predict the stock market fluctuation. Neural networks and SVM are identified to be the leading machine learning techniques in stock market prediction area. Also, a model for predicting stock market using HMM is presented. Traditional techniques lack in covering stock price fluctuations and so new approaches have been developed for analysis of stock price variations. Markov Model is one such recent approach promising better results. In this paper a predicting method using Hidden Markov Model is proposed to provide better accuracy and a comparison of the existing techniques is also done.

Fractional order modeling and control of a flexible manipulator using sliding modes

Abstract: The paper proposes design and implementation of fractional order sliding mode control (FOSMC) for a fractional order model of a single link flexible manipulator (SFLM). Novelty of the paper lies in modeling the plant with fractional order dynamics in non-commensurate order. This model is validated through experimentation. In this study, a fractional order sliding surface is introduced to SLFM which is a typical nonlinear under actuated system. The stability of the fractional order sliding mode controller is proved. The performance and robustness of the proposed method are tested for parametric uncertainties and external disturbances. The efficacy of the method is illustrated using MATLAB Simulink.

Impacts of increasing photovoltaic penetration on distribution grid — Voltage rise case study

Abstract: Increasing electricity prices and unreliable grid supply, has led to increasing PV installation in a distribution network. While the PV installations on a distribution grid reduces the power demand, and eases grid congestion, the increasing PV penetration has several other impacts on the grid, both positive and negative. The paper makes a comprehensive study of the various impacts. Simulations analysis of the most prominent impact on the grid — voltage rise, in a distribution line is performed to understand the severity of the problem for different PV penetration levels. The paper also performs simulation analysis to estimate the impact of the voltage rise on transformer tap changes to regulate the voltage within permissible limits as per standards. It was seen that as the PV penetration increases, the number of tap changes required increase resulting in the reduced life time of the transformer.

An optimized key frame extraction for detection of near duplicates in content based video retrieval

Abstract: Due to the availability of increased Internet bandwidth and transfer media, the multimedia objects usage is widely used. In multimedia the text files, scripts, images and videos, audios are used by almost every end of users. Daily around millions of videos are being uploaded through various sources. It is becoming very tedious to manage with these multimedia objects specially related to videos. It needs some kind of retrieval technique which will relieve users from tracking videos relatively similar manually. So users are shifted from text based video retrieval to content based video retrieval (CBVR). CBVR has steps as key frame extraction, feature vector formation, similarity and template matching and finally get the retrieved relatively correct expected copies of videos approximately matching with query video. Key frame extraction play very vital role in whole process of CBVR as it decides the search region for search engines affecting the performance. In videos large number of frames forms a scene. This scene includes repetition of nearly same frames with slight differences, which increases the storage space and decreases the performance in video processing. Here instead of searching the whole set of frames in videos, only selected key frame are used for further processing. Automated extraction of key frames has recently gained momentum in the field of video content summarization. Key frames are extracted by computing the consecutive frame differences. Then their relative neighboring frames which nearly match with the key frames are taken aside as near duplicate copies. Therefore the near duplicate copies detection may help to improve the performance and speed of near duplicate detection in content based video retrieval.

Key Management for Cloud Data Storage: Methods and Comparisons

Abstract: Cloud computing paradigm is being used because of its low up-front cost. In recent years, even mobile phone users store their data at Cloud. Customer information stored at Cloud needs to be protected against potential intruders as well as cloud service provider. There is threat to the data in transit and data at cloud due to different possible attacks. Organizations are transferring important information to the Cloud that increases concern over security of data. Cryptography is common approach to protect the sensitive information in Cloud. Cryptography involves managing encryption and decryption keys. In this paper, we compare key management methods, apply key management methods to various cloud environments and analyze symmetric key cryptography algorithms.

Analysis of nonlinear and non-stationary signal to extract the features using Hilbert Huang transform

Abstract: Human emotion recognition is a hot research topic in medical and engineering field to provide interface between users and computers. A novel technique for Feature Extraction (FE) has been presented here. This method is feasible for analyzing the nonlinear and non-stationary signals like electrocardiogram signal (ECG), Electromyogram (EMG) etc. We have used electrocardiogram signal as an input, each signal has important functions, which has been extracted by applying empirical decomposition method. These functions are used to extract the features using fission and fusion process. The features extracted from every IMF are used to compose feature vector. The extracted features are useful to recognize human emotions from ECG signal. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques. We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Rice quality analysis using image processing techniques

Abstract: In agricultural industries grain quality evaluation is very big challenge Quality control is very important in food industry because after harvesting, based on quality parameters food products are classified and graded into different grades Grain quality evaluation is done manually but it is relative, time consuming, may be varying results and costly To overcome these limitations and shortcoming image processing techniques is the alternative solution can be used for grain quality analysis Rice quality is nothing but the combination of physical and chemical characteristics Grain size and shape, chalkiness, whiteness, milling degree, bulk density and moisture content are some physical characteristics while amylose content, gelatinization temperature and gel consistency are chemical characteristics of rice The paper presents a solution of grading and evaluation of rice grains on the basis of grain size and shape using image processing techniques Specifically edge detection algorithm is used to find out the region of boundaries of each grain In this technique we find the endpoints of each grain and after using caliper we can measure the length and breadth of rice This method requires minimum time and it is low in cost

Mobile cloud computing: Security threats

Abstract: Within the previous few years, the globe of mobile computing has grown enormously. Devices like PDAs, handhelds and digital cellular phones that started off as gadgets of luxury became a necessity in today's “always-stay-connected” method. To facilitate quality of such devices whereas not disconnection from the network, Mobile scientific discipline came into existence. this permits the mobile node to use 2 scientific discipline addresses: a tough and quick home address and a care-of address that changes at each new purpose of attachment. but with the advantages of Mobile scientific discipline to boot came the disadvantages, the biggest of them being that of security. throughout this paper, we've got a bent to debate a number of the common security threats that mobile scientific discipline networks square measure exposed to what is more as some planned solutions to agitate such threats. The recent years have witnessed an unbelievable growth among the vary of mobile internet users and they would really like for quality support is indispensable for seamless internet property. Mobile scientific discipline may be a top quality support protocol that supports roaming across multiple Access Points whereas not having to re-establish the highest to end affiliation. throughout this paper, we've got a bent to require the position that despite several challenges that Mobile scientific discipline faces, it would sway be the protocol for supporting quality among the longer term. we've got a bent to support our claim by analyzing the factors which will influence the widespread adoption of Mobile scientific discipline which we tend to go any to dialogue the counter claims in a trial to convert the reader that the advantages of Mobile scientific discipline outweighs its disadvantage.

Factors influencing decisions on delay claims in construction contracts for Indian scenario

Abstract: Construction industry in India is second largest next to agriculture. In current era of infrastructure development construction projects occupy a key position. In any construction project contract time and cost overrun is a common feature, which gives rise to claims leading to disputes. These disputes if not handled properly tend to consume time and money of all parties to the contract. To resolve the dispute in optimum time, it is essential to understand the root cause of disputes as early as possible. Hence there is a need of analyzing the disputes scientifically. The present study reveals from the study of arbitration awards that the causes for delay claims can be grouped in domains and the probable decisions to the disputes can be traced through the probing questions considered by decision makers. This paper attempts to identify questions related to disputes for Indian scenario through literature, arbitration awards, court cases and discussions with professionals.

Effective intrusion detection system using semi-supervised learning

Abstract: Network security is a very important aspect of internet enabled systems in the present world scenario. As the internet keeps developing the number of security attacks as well as their severity has shown a significant increase. Due to intricate chain of computers the opportunities for intrusions and attacks have increased. Therefore it is need of the hour to find the best ways possible to protect our systems. Every day new kind of attacks are being faced by industries. Hence intrusion detection system are playing vital role for computer security. The most effective method used to solve problem of IDS is machine learning. Getting labeled data does not only require more time but it is also expensive. Labeled data along with unlabeled data is used in semi-supervised methods. The rising field of semi-supervised learning offers a assured way for complementary research. In this paper, an effective semi-supervised method to reduce false alarm rate and to improve detection rate for IDS is proposed.

Prediction of gold and silver stock price using ensemble models

Abstract: Gold price prediction is a complex problem due to its non-linearity and dynamic time series behavior, constrained with many factors like economic, financial etc. Due to its high degree of monetary rewards and understanding the hidden pattern behind stock prediction researchers have proposed many statistical and machine learning algorithms for stock prediction. In this paper we examine different ensemble models for determining the future momentum of the gold and silver stock price, whether it will increase or decrease for the following relative to current days stock price. Using stacking approach we got significant accuracy of 85 % for predicting gold stock and 79 % for silver stock using a hybrid bagging ensemble.

Sonochemical decolorization of wastewaters containing Rhodamine 6G using ultrasonic bath at an operating capacity of 2 L

Abstract: In the present work, the sonochemical decolorization of wastewater containing a basic dye, Rhodamine 6G (Rh 6G) has been investigated using an ultrasonic bath at an operating capacity of 2 L. Effect of initial concentration, pH, and use of different additives, such as CCl4, H2O2, air, and UV light in combination with ultrasound on the extent of decolorization has been investigated. The experimental results show that an increase in dye concentration leads to a decrease in the decolorization rate, whereas basic conditions favor the decolorization of the pollutant. Among the use of different additives, maximum effect was observed for the use of hydrogen peroxide where the extent of decolorization was 77.8%. Use of air and CCl4 as an process intensifying additive leads to a moderate increase in the extent of decolorization whereas combination of ultrasound and ultraviolet irradiations resulted in lower effectiveness as compared to the combination of ultrasound and hydrogen peroxide. Kinetic studies ha...