Showing papers by "SDM College of Engineering and Technology published in 2017"

Optimized neighbor discovery in Internet of Things (IoT)

Abstract: The Internet of Things (IoT) is a future technology expected to consist of plenty real world objects or things [1] These devices collaborate together and possibly form a network of things/nodes Since the nodes can be stationary or mobile the network topology frequently changes, therefore node or neighbor discovery is a continuous process The process of collaboration involves the devices to discover each other and learn network topology The conventional node discovery procedures require the nodes to do active listening which would waste significant amount of energy just for establishing topology information [2] This paper studies the basic architecture of an IoT network and the functions of each of its layers Further we analyzes Classic Neighbor discovery procedure followed by IPv6 nodes, and an Optimized techniques which modifies this classic approach to reduces active listening and makes it more suitable for IoT

Identification of PCB faults using image processing

Abstract: The aim of this paper is to develop a more accurate PCB inspection system In this method captured colored images are natural images ie without any precustomized environment and hence the every time the capture images varies with lighting conditions, the distance and inclination and these issues are to be handled effectively Most of the work in this regard just detects the location of the fault but merely little work has been carried out to identify the type of the PCB faults automatically This paper attempts to detect two types of PCB faults effectively

An intelligent report generator for efficient farming

Abstract: Today, the farmers are suffering from uncertain monsoons and water scarcity due to global warming. The integration of standard farming strategies with latest technologies as Internet of Things and Wireless device Networks may result in agricultural modernization. Keeping this situation in mind it's my approach to style device for automation of agriculture, associate in tending ’Internet of Things’ primarily based devices that is capable of analyzing the perceived data then transmit valuable farming data to the user. These devices is controlled and monitored from remote location and its data is processed and applied in agricultural fields. Intelligent Report Generator for efficient farming deals with the easy testing of soil nutrient. This report helps farmer to understand the health of their farming land soil. This in turn helps farmer to decide, which are the suitable crops to sow at that particular season in that particular land. By investigating the occasional information from farmland, Soil Health Report card is arranged and sent to farmer by means of SMS, which helps the agriculturist in basic decision making. Condition dampness and temperature is detected utilizing DHT11 sensor and light is detected utilizing LDR sensor, soil pH meter is utilized to know the soil pH esteem.

Synthesis and Characterization of TiO2 Reinforced Al6061 Composites

Abstract: This article presents the investigative work carried out to study the relationship between the physical, mechanical and tribological characteristics of aluminum matrix composites reinforced with Ti...

Color image enhancement using Laplacian filter and contrast limited adaptive histogram equalization

Abstract: Color image enhancement is one of the vital emerging techniques in the field of Digital Image Processing. In this paper, we propose Color Image Enhancement using Laplacian filter and Contrast Limited Adaptive Histogram Equalization. The original RGB color image is considered from Computer Vision Group database and is converted to Hue-Saturation-Value (HSV) with Laplace filter applied to S and V components. The processing block which involves local correlation, variance and luminance enhancement are performed on laplacian output of V and S components and the Contrast Limited Adaptive Histogram Equalization (CLAHE) is applied on enhanced luminance component output followed by contrast stretching on S component. Finally, the HSV components are converted to RGB and performance parameter of enhancement is obtained. It is observed that the proposed method obtain better PSNR compared to existing methods.

Molecular Modeling and Adsorption Properties of Ordered Silica-Templated CMK Mesoporous Carbons

Abstract: Realistic molecular models of silica-templated CMK-1, CMK-3, and CMK-5 carbon materials have been developed by using carbon rods and carbon pipes that were obtained by adsorbing carbon in a model MCM-41 pore. The interactions between the carbon atoms with the silica matrix were described using the PN-Traz potential, and the interaction between the carbon atoms was calculated by the reactive empirical bond order (REBO) potential. Carbon rods and pipes with different thicknesses were obtained by changing the silica–carbon interaction strength, the temperature, and the chemical potential of carbon vapor adsorption. These equilibrium structures were further used to obtain the atomic models of CMK-1, CMK-3, and CMK-5 materials using the same symmetry as found in TEM pictures. These models are further refined and made more realistic by adding interconnections between the carbon rods and carbon pipes. We calculated the geometric pore size distribution of the different models of CMK-5 and found that the presence ...

Artificial Neural Networks for the Prediction of Wear Properties of Al6061-TiO2 Composites

Abstract: The exceptional performance of composite materials in comparison with the monolithic materials have been extensively studied by researchers. Among the metal matrix composites Aluminium matrix based composites have displayed superior mechanical properties. The aluminium 6061 alloy has been used in aeronautical and automotive components, but their resistance against the wear is poor. To enhance the wear properties, Titanium dioxide (TiO2) particulates have been used as reinforcements. In the present investigation Back propagation (BP) technique has been adopted for Artificial Neural Network [ANN] modelling. The wear experimentations were carried out on a pin-on-disc wear monitoring apparatus. For conduction of wear tests ASTM G99 was adopted. Experimental design was carried out using Taguchi L27 orthogonal array. The sliding distance, weight percentage of the reinforcement material and applied load have a substantial influence on the height damage due to wear of the Al6061 and Al6061-TiO2 filled composites. The Al6061 with 3 wt% TiO2 composite displayed an excellent wear resistance in comparison with other composites investigated. A non-linear relationship between density, applied load, weight percentage of reinforcement, sliding distance and height decrease due to wear has been established using an artificial neural network. A good agreement has been observed between experimental and ANN model predicted results.

A review on optimal placement of FACTS devices in deregulated environment-a detailed perspective

Abstract: This review paper is an attempt to develop a detailed review on the optimal placement of different Flexible AC Transmission Systems (FACTS) devices in the deregulated environment with the basic introduction to few FACTS devices The review on the literature published so far for different FACTS devices like the Thyristor-Controlled Series Compensation (TCSC), Static Synchronous Compensator (STATCOM), Unified Power Flow Controller (UPFC), Unified Power Quality Conditioner (UPQC), Interline Power Flow Controller (IPFC) are carried out in a detailed manner The purpose of the review paper is to deliver knowledge about the different FACTS devices and the improvement in the field of the optimal placement, which is in the stage of growth during the past two decades The review is limited to the FACTS devices and the optimal placement of the FACTS devices Different optimization techniques, hybrid meta heuristics techniques and optimization technique with Optimal Power Flow (OPF) are discussed in detail The optimal placement of different FACTS devices with the different criteria of the objective function is considered for discussion

Distribution transformer failure in India root causes and remedies

Abstract: Transformers play an important role in a power distribution utility. They have a long life of 25 to 30 years; but they fail in large numbers, within 3 years itself, due to various reasons, causing huge economic and service impact on the distribution utilities as well the power consumers. In this paper, causes of failure of distribution transformers and possible solutions to overcome these problems have been discussed. Some of the problems may be particular to distribution utilities of Karnataka state, but most of them are generally, Indian problems.

Wireless controlled military combat robot system

Abstract: Current defense applications are changing day by day and in future, no soldiers will go to battle field without using advance technology. The soldiers are able to know the position and movement of enemy in the battle field without entering to it. For this a micro wireless camera is fitted on the robot, where the video and voice transmitted to the control room. The present work designs a robot, constructed with the help of chain wheels and connected to motors, where movement of robot can be controlled in all directions with gear facility. The controlling of this robot is done with help of wireless RF module.

Home automation system using wireless network

Abstract: It requires to use new advanced technology in wireless networking environment for achieving automation in daily used appliances. The present work develops a system, which is intended to control electrical appliances and devices in house with relatively low cost, user-friendly interface and also informs the user about any intruder detection. The purpose of this paper is to demonstrate how simple algorithms can produce useful behavior of appliances reducing human efforts. The smart home concept in the system improves the standard living at home. The main control system implements wireless technology to provide remote access from smart phone. In addition, IR sensors are used for detecting the presence of a person inside the room to control the lighting.

Detection of black hole attack in enhanced AODV protocol

Abstract: Wireless Adhoc network is decentralized in nature which means it is independent of base station and do not rely on fixed routers to route packets from source to destination and also is dynamic in nature which is made up of mobile nodes. Although there are multiple proficient reactive protocols like AODV, TORA, DSR etc. there are some loop holes in these reactive protocols which are of on-demand type. One of the serious problem identified in such protocols is black hole attack, in which a malicious node (or group of malicious nodes) in the network act as legitimate node but actually does some superfluous actions in the network. It is very important to identify this type of malicious nodes in the initial stage so that further complications can be avoided. At present, normal AODV which is based on hop-count metric to detect the packets suffer from black hole type of attack. In this proposed work, care is taken to enhance the AODV protocol by making it delay aware. Detecting the black hole attack and avoiding them in participating in the network transactions is the primary focus of this paper. All nodes in network are ranked based on their distance from particular node which wishes to send packets through the network.

Control and operation of grid connected DC source based distributed generation

Abstract: Grid connected operation of Distributed generation (DG) is yet another approach to provide reliable and secured power. The operational issues of grid connected DG is the focus of research at present to achieve adequacy and security. The islanding is the situation where DG continues to operate with the utility disconnected. It is customary to detect islanding when it occurs to ensure continued stable operation along with safety of linemen and the customers' equipment. This paper deals with the DC source based DG integrated with the utility and operates in grid connected and intentional islanding mode. Passive islanding detection technique is used to detect the islanding. The DG operates at grid voltage and frequency. Intentional islanding is tested by developing the model for seamless operation using MATLAB/Simulink environment and results are obtained. The simulation results validate the effective operation of the proposed controller and power electronic devices.

Fracture toughness of glass epoxy laminates using carbon nano particles and ETBN rubber

Abstract: Fiber-reinforced laminated composites have excellent mechanical properties along the fiber in-plane direction. However, they do not have very good properties in the transverse direction. The objective of this research is to deal with this problem by using graphene oxide (GO), plasma-treated multiwall carbon nanotubes, and nanodiamond extra pure powder with epoxy-terminated butadiene nitrile liquid rubber to improve the through-thickness fracture toughness of glass/epoxy unidirectional pre-preg laminates. The experimental results show that by adding carbon nanoparticles with rubber in small quantities, the mode-I interlaminar critical energy release rate can be improved by 50 to 103 %. Furthermore, it was observed that there was an increase in flexural stiffness by 15 % with the addition of nanodiamond extra pure powder to rubber. However, when GO was used, the mode-I interlaminar fracture toughness improvement was reduced as compared to other nanoparticles modified by glass/epoxy fiber laminates. The fracture surfaces were analyzed using scanning electron microscopy to understand the increase in toughness in modified glass epoxy pre-peg laminate system.

Performance degradation issues of PV solar power plant

Abstract: P V solar power plants are planned to work for long time, monitoring of plant will ensure a safety and longterm operation. The photovoltaic system degradation of 10% per year in the year 1991 has reduced to 12% for 25 years due to modules manufactured after 2000. Some of the common and basic degradation issues in pv solar plants are discussed in this paper. The adequate maintenance is required for long term operations and increasing performance.

Wireless network simulation and analysis using qualnet

Abstract: Wireless sensor networks (WSNs) are nowadays implemented in so many fields. In order to guarantee an optimum use of this technology, one need to test different routing protocols performances. This paper evaluates ad hoc on demand distance vector protocol (AODV), dynamic source routing protocol (DSR)'s and Dynamic MANET On Demand (DYMO) performances for IEEE 802.15.4/ZigBee. The evaluation is based on network throughput, average end to end delay and average jitter. Various simulation scenarios are simulated with varying various properties. The network simulator QUALNET (7.4) is used. From the detailed simulation results and analysis, one can excavate the routing protocol that performs better depending on the number of nodes.

An improved technique of plant leaf classificaion using hybrid feature modeling

Abstract: Various applications have been developed during recent years which are based on the computer vision system. In this field, plant species recognition is a challenging task for researchers due to environmental and image acquisition condition of image. Leaf classification application can be used for various purpose such as remote sensing imaging, botanical characteristically analysis etc. Now a day, amount of dataset is increasing rapidly in this field. Thus it motivates us to develop an efficient model for leaf classification in terms of computation time and accuracy. To address this issue, here in this work we propose a hybrid approach for feature extraction to improve the classification accuracy. Proposed model follows twofold working process whereas in first stage image pre-processing is applied to enhance the image quality of image by applying image enhancement with the help of auto-regressive model, second stage performs feature computation by combining morphological, shape and SIFT feature and finally Deep Neural Network is applied for classification performance evaluation. Proposed work is a combination of image enhancement, morphological feature, SIFT feature and classification technique. For efficient image enhancement, auto-regressive model is adopted here. A comparative study of classification performance is presented which shows the robustness of proposed model

Recognition of Traffic Sign Based on Support Vector Machine and Creation of the Indian Traffic Sign Recognition Benchmark

Abstract: Traffic sign recognition, a driver assistance system informs and warns the driver about the status of the road is a challenging issue. Though, a lot of work on this topic has been carried out, but complete benchmark datasets are not freely available for comparison of different approaches. A few databases are available for benchmarking automatic detection of traffic signs. However, there is no database built considering the Indian traffic signs. The road scenarios in India are quite different from other countries, especially in rural areas. Hence, an effort to build an Indian traffic sign database considering both rural and urban situations is presented in the work. The database consists of 13000 traffic sign images of 50 different classes of traffic signs taken at different times under different environmental conditions and includes the detailed annotation of the traffic signs in terms of size, type, orientation, illumination and occlusion. The work also discusses an efficient method for identification of road signs based on two modules: (1) feature extraction based on dense scale invariant feature transform (DSIFT) and (2) a classifier trained by support vector machine (SVM). The SIFT approach transforms an image it into a large collection of local feature vectors invariant to scaling, translation or rotation of the image, and reduction in the dimensionality is achieved by applying principal component analysis (PCA). After extracting the features, the image is classified using support vector machine, a supervised learning model.

Performance analysis of source coding techniques

Abstract: In this paper the performance of different source coding techniques is analyzed by considering same set of probabilities for all the algorithms for binary, tertiary and quarternary The algorithms used are Shannon, Shannon Fano and Huffman coding algorithms Performance of these algorithms is analyzed in terms of average length, entropy and efficiency

Digital LCR meter using arduino

Abstract: Measurement of electrical parameters such as Inductance (L), Capacitance (C) and Resistance (R)plays an integral role in the real world implementation of the circuits. This paper is focused on design and development of a LCR meter using simple techniques that leads a low cost device at the beginner level. The techniques are implemented on TINA software along with the hardware implementations using Arduino UNO. Results obtained from developed device are confirmed with commercial LCR meter.

Virtually controlled robotic arm using haptics

Abstract: Haptics and robotics are widely growing technologies of 21 century. Robots of present days are being used in the fields which are secluded from the human society; they face major short comings because of their limited abilities to interact with humans, to fill this void the proposed system uses haptics technology which provides a tactile feedback to give the feel of touch, sense and force. The main objective of this project is to design and develop the robotic arm that is controlled by haptics glove for virtual environment capable of haptic interaction. Without risking human limbs. The proposed system has applications in many areas including robotic medical surgery, rehabilitation, and exploration of harmful or remote environments, enabling technologies, defense application and education.

Atomic simulation of Xe and Kr separation in silica-templated amorphous mesoporous carbons CMK-3 and CMK-5

Abstract: We perform a molecular simulation study on adsorption and separation of the noble gases Xe and Kr in silica-templated amorphous mesoporous carbons (CMK) materials. We generate the atomic models of ...

Crowd Anomaly Detection Using Motion Based Spatio-Temporal Feature Analysis

Abstract: Recently, the demand for surveillance system is increasing in real time application to enhance the security system. These surveillance systems are mainly used in crowded places such as shopping malls, sports stadium etc. In order to support enhance the security system, crowd behavior analysis has been proven a significant technique which is used for crowd monitoring, visual surveillance etc. For crowd behavior analysis, motion analysis is a crucial task which can be achieved with the help of trajectories and tracking of objects. Various approaches have been proposed for crowd behavior analysis which has limitation for densely crowded scenarios, a new object entering the scene etc. In this work, we propose a new approach for abnormal crowd behavior detection. Proposed approach is a motion based spatio-temporal feature analysis technique which is capable of obtaining trajectories of each detected object. We also present a technique to carry out the evaluation of individual object and group of objects by considering relational descriptors based on their environmental context. Finally, a classification is carried out for detection of abnormal or normal crowd behavior by following patch based process. In the results, we have reported that proposed model is able to achieve better performance when compared to existing techniques in terms of classification accuracy, true positive rate, and false positive rate.

Control and operation of grid connected photovoltaic system

Abstract: Grid connected Distributed generation (DG) provides reliable and secured power. The research focus is to achieve adequacy and security in the grid connected photovoltaic (PV) power generation system. The islanding is the situation where DG continues to operate with the utility disconnected. Islanding detection should be done with minimum possible time when it occurs to ensure continued stable operation along with safety of linemen and the customers' equipment. Of the renewable energy sources, PV system is most suitable source for clean generation and suitable for any areas of applications. This paper deals with the PV cell model as DG integrated with the utility and operates in grid connected and intentional islanding mode. Islanding detection is carried out with passive islanding detection technique. The DG is integrated to utility to operate at grid voltage and frequency. Intentional islanding is tested by developing the model using MATLAB/Simulink environment and results are obtained. The simulation results validate the effective operation of the proposed controller and power electronic devices.

CRETAL: A Personalized Learning Environment in Conventional Setup

Abstract: The increased variety of learning resources, like e-books with modern collaborative tools, video lectures of different teachers across the world, lively discussion boards etc. have substantially affected learning styles of students. Having accepted such forms of learning materials, conventional academic setups are in desperate need to make learning activities efficient, effective and meaningful. In this paper a diverse resources hosting system CRETAL (Compiler of Resources in Engineering &Technology to Aid Learning) with rich set of unique annotation tools are described to address the challenges of the modern students to query, access, extract, connect, process and share the important concepts from the different form of the learning materials created and adapted by the teacher. In addition to the system description, we also present the usability study along with the impact on students learning and teacher's decision when CRETAL was adapted in few undergraduate course using Educational Data mining and learning analytics.

Effect of Traditionally Synthesized Carbon Nano Particles as Bio-Fuel Blend on the Engine Performance

Abstract: The demand for non-renewable energy resources is created due to the increase in number of vehicles and its pollution problems. This has been led to search for alternative and renewable energy resources. Different methods have been adopted to reduce emissions and to increase the efficiency of engines include, modification in engine, fuel alteration, and exhaust gas treatment. Recently it was reported that blending of nanoparticles with biodiesel to has brought about alteration in chemical and electrical properties which resulted in increased engine efficiency and decreased emission level. In the current study, carbon nanoparticles were synthesized by a simple traditional method. The structural characterization was done using SEM has revealed the average size of the particles in the range of 80.3–88.6 nm. The blend of carbon nanoparticle-biodiesel was utilized to evaluate the engine characteristics. Due to nano-additive biodiesel blend, a significant enhancement in the brake thermal efficiency with substantial reduction in the harmful pollutants from the engine was observed. Maximum brake thermal efficiency of 25 % was obtained for biodiesel blended with 50 mg of carbon nanoparticles with considerable reduction in hydrocarbons, smoke capacity, NOx emissions compared to 25 mg blend, biodiesel and diesel.

Vegetation type classification system using pseudo zernike moments and ELM

Abstract: Vegetation classification system is one of the evergreen applications of remote sensing technology. The objective of this classification system is to boost up the agricultural yield by removing the weedy plants. Understanding the benefits of vegetation classification system, this work proposes a vegetation classification system that can distinguish between tree, shrub and grasslands. The goal of the work is achieved by segregating the entire work into three important phases, which are image pre-processing, feature extraction and classification. The satellite images are pre-processed by guided filter. In this work, both global and local features are extracted by pseudo zernike moments and first order features respectively. Finally, Extreme Learning Machine (ELM) is employed as the classifier to differentiate between trees, shrubs and grasslands. The performance of the proposed approach is satisfactory in terms of classification accuracy, sensitivity and specificity.