The paper presents comparison among the most frequently used waste water systems in developing countries. Various physico-chemical and biological techniques have been used for the treatment of domestic wastewater. The wastewater is conventionally treated either by suspended growth system, by attached growth system or combined suspended and attached growth system. The system studied were oxidation pond, activated sludge, upflow anaerobic sludge blanket, trickling filter and constructed wetland. All the above systems were designed and analysed based upon the various factors such as BOD removal efficiency, land required, power required, HRT, quantity of sludge to be handled, initial, operational & maintenance cost. The main summary table for quantitative analysis is prepared based on per capita values. It also includes the advantages and disadvantages of the treatment processes.

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Data mining is a multidisciplinary effort to extract a small chunk of knowledge from data. Feature Subset selection is an effective technique in dealing with dimensionality reduction. A feature selection algorithm may be evaluated from both the efficiency and effectiveness points of view. Based on these criteria, a fast clustering-based feature selection algorithm, FAST, is given. It is based on the minimum spanning tree method. The algorithm is a two steps process in which, In the first step, features are divided into clusters by using graph-theoretic clustering methods. In the second step, the most representative feature that is strongly related to target classes is selected from each cluster to form the final subset of features. The clustering-based scheme of FAST has a high possibility of producing a subset of constructive and independent characteristics. In this FAST algorithm, I have used Boruvka's Algorithm. By using Boruvka’s Algorithm, parallel computing can be done. The proposed system will decrease the computational time of creating MST in the FAST Algorithm. I also used Chi-Square test that is used to find correlation among attributes for removing irrelevant features. Hence, this will improve the accuracy.

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Glaucoma is caused due to unawareness in people which can be resulted in to the blindness. For patients affected by this, mass screening can be the best curable solution which can help to extend symptom-free life. Using hybrid feature extraction from digital fundus images, we propose a novel low cost automated glaucoma diagnosis system. Higher order spectra (HOS) and discrete wavelet transform (DWT) features are used for automated identification of normal glaucoma classes. Vector machine (SVM) classifier with linear, radial basis function (RBF) and polynomial order 1, 2, 3 are the extracted features fed to support in order to select the best kernel for automated decision making. Our results shows that the combination of HOS and DWT features in feature extraction performs better than the other feature extraction and correctly identifies the glaucoma images with an accuracy of more than 92.48%. System proposed by us is having clinically significance features and this system can be adopted for detecting glaucoma with accurate results.

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Vehicular Ad Hoc Network (VANET) is an emerging new technology. It has to serves a wide range of applications under different scenario. It establishes wireless connections between vehicles. It is beneficial in providing safety to the road users and comfort to the passengers. With the increase in motorization, urbanization and population growth, road accidents are also increasing at a very fast rate.The reasons behind these accidents are lack of earlier knowledge about traffic congestion, road condition, lane changing, etc. All these problems can be solved with VANET. Routing protocols and other techniques must be adapted to vehicular specific capabilities and requirements. A variety of research has been done on routing and several protocols have been proposed with their implementation. We are interested to evaluate efficiency of OLSR is based on the link state algorithm and it is proactive in nature. It employs periodic exchange of messages to maintain topology information of the network at each node. This paper presents the Efficient OLSR algorithm which is based on OLSR routing protocol with some changed in MPR technology.

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Genetic Algorithm (GA) is used to solve optimization problems. Knapsack is an optimization problem. To solve the knapsack problem we used two algorithms and their results were compared. To solve the knapsack problem we use genetic algorithm operators as selection, crossover, and mutation after that we perform the hybridization of GA and the results of both algorithms were compared. Memetic algorithm is combination of genetic algorithm and hill climbing on the Knapsack problem to obtain the more optimized result.

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Network on chip is an interconnection between several processing elements and routers. There are several possibilities for the occurrence of faults within the network. These faults degrade the performance of the network. In order to increase the performance several fault tolerant methods has been used. They involve themselves in rerouting and hence take longer paths. To make the path shorter, the router architecture has to be modified. For this efficient routers are needed to take place communication between these devices. This project, proposes a priority based solution for a bufferless network-on-chip, including an on-line fault-diagnosis mechanism to detect both transient and permanent faults, a hybrid automatic repeat request and forward error correction link-level error control scheme to handle transient faults.

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Security issues of different database driven web applications are continue to be an important and crucial aspect of the ongoing development of the Internet. In the last several decades, Web applications have brought new classes of computer security vulnerabilities, such as AQL injection. SQL Injection Attacks (SQLIAs) is one of the most severe threats to the security of database driven web applications as it compromises integrity and confidentiality of information in database. In this type of attack, an attacker gain control over the database of an application and consequently, he/she may be able to alter data. In this paper we present different types of SQL injection attacks and also implementation of different types of tools which can be used to detect and prevent these attacks.

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In this project study the problem of answering queries about private data that is spread across multiple different databases. For instance, a medical researcher may want to study a possible correlation between travel patterns and certain types of illnesses. The necessary information exists today suppose in airline reservation systems and hospital records but it is maintained by two separate companies who are prevented by law from sharing this information with each other, or with a third party. This separation prevents the processing of such queries, even if the final answer, e.g., a correlation coefficient, would be safe to release. Here present DJoin, a system that can process such distributed queries and can give strong differential privacy guarantees on the result. DJoin can support many SQL queries, including joins of databases maintained by different entities. This experimental evaluation shows that DJoin can process realistic queries at practical timescales. This project can be viewed as a special case of a more general approach for producing synthetic data.

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A wireless sensor networks placed in random fluctuations which affect the real signal and it is not associated with environment, it is needed to create a complete framework that protects the correctness of the collected information. Here focusing on data aggregation, trust of a node and fault tolerance to decrease the error of the gathered information. Referring the architecture of multilayer aggregation, trust based data collection with fault tolerance is used in order to decrease the error and finally to produce aggregated outcome. By comparing trust values of node, we can evaluate the node whether the node transferring the data or node is fault. Here clustering technique is used to gather the information from the nodes.

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Automation in hydraulic gates is employed to regulate the flow of water through a water reservoir without any human interference. The Automatic outflow regulating gate is water pressure operated gate. The main objective in the “Analysis & Optimization of gate leaf of Automatic outflow regulating gate” is to achieve suitable design for Gate leaf proper. Finite element analysis of Gate leaf proper is taken for the study. Structural assembly of Gate leaf proper can be analyzed using Finite Element techniques. So firstly a proper Finite Element Model is to be developed using Cad software Creo 1.0. Then static analysis shall be done to determine the von Misses stress, shear stress & deformations etc in the present design for the given loading conditions in gate close position as well as gate open position using Finite Element Analysis Software ANSYS v 12.

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Maintenance of wireless network system is the major problem now a days. computational methods in wireless networks degrade the performance and stability of the network. The problem of stabilizing a linear system over a wireless network using simple in-network computation method. Wireless Control Network is a simple network of nodes where each node maintains its position details and gets frequent updates from other nodes in linear combination of neighbor plant outputs. In WCN structural system have less computation overhead and beneficial scheduling with compositionality properties. This system proposes basic characteristics of topological conditions which stabilize the network. The coupling between plant’s dynamics and nodes dynamic nature in network structure is analyzed by this system. To achieve this the system stabilizes the control inputs even if vertex connectivity of the network is very larger than the geometric multiplicity of unstable eigenvalues of the plant, this is analogous to typical min-cut condition that is required in traditional information distribution problem. Proposed system overcome this problem by topological conditions which imposes communication through plant’s sensors and decentralized controllers at actuators in the network employed with traditional code on it.

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This paper presents, the performance comparison between carburetor and Multi-point Fuel-Injection (MPFI) spark ignition (SI) engines for different blends of gasoline-ethanol. Ethanol from biomass is an ecologically sustainable fuel for automobile engines. In this work, tests were conducted on both carburetor and MPFI SI engines under different loads for all blends. For each blends reading were taken for varying load. The analyses were conducted using gasoline-ethanol blends with the volumetric ratio of 0% to 50% with an increment of 5% ethanol. The performance parameters such as air-fuel ratio, brake thermal efficiency, volumetric efficiency, fuel consumption and mechanical efficiency were done for both the engine under condition. The results show that at 20% ethanol blend with gasoline both the engine gives better performance. However, the MPFI SI engine provides better results than the carburetor SI engine.

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The Internet has become a part of daily life and an essential tool today. Internet has been used as an important component of business models. Therefore, It is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. Intrusion detection is one of the important security constraints for maintaining the integrity of information. Various approaches have been applied in past that are less effective to curb the menace of intrusion. There are large amount of network traffic captured in terms of number of features and number of record, so it is very difficult to process all the network traffic before making any decision about normal or abnormal. So it is having longer training time and complexity. Thus the purpose is to provide an intrusion detection system (IDS), by modifying the genetic algorithm to network intrusion detection system. As we have applied attribute subset reduction on the basis of Information gain. So the training time and complexity reduced considerably. we embedded a soft computing approach in rule generation, so Generated rule can detect attack with more efficiency.

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Image inpainting means reconstructions of missing or damaged portions of images. In the case of removal of object, the challenge is to fill in the hole that is left behind in a best visually way. There are various algorithms for removing large objects from digital images. In this work my goal is use "inpainting" techniques for filling in small image gaps. All the images have one property "spatial redundancy". That is, pixel values in neighborhood surroundings are same. In this paper exploited spatial redundancy of the image. This property of the image for the region filling process using median filter. This concept is useful for improve the quality of object as well as computational complexity.

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Categorization of images is a way of grouping images according to their similarity. Images categorization uses various features of images like texture, color component, shape, edge, etc. Categorization process has various steps like image pre-processing, object detection, object segmentation, feature extraction and object classification. There are basically two methods of categorization-Supervised and Unsupervised. There are various algorithms that are used to categorize image data such as K-means, ISODATA, Artificial Neural Network (ANN), Decision Tree (DT), Support Vector Machine (SVM) and Fuzzy Classification and K-Nearest Neighbor (KNN). In this paper supervised and unsupervised techniques for image categorization are discussed.

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Kolkata is a metropolitan city covering an area of 185KM2 and is one of the most densely populated cities in the world. According to West Bengal Renewable Energy Development Agency (WBREDA) policy, there is a target to harness 16MW of solar rooftop and smaller solar installations in the state by 2017. Assuming theoretically available roof space for rooftop PV systems is 30 percent or 39000m2 of built up area in Kolkata city, 25% of the 16MW target set by the state’s nodal agency can be met by solar rooftop installations by using crystalline silicon or thin film technologies such as CIGS and CdTe. The transmission and distribution losses amounts to 13% in Kolkata can be reduced as power is consumed at the point of generation. Environmental impacts associated with coal-based power plant such as land use and habitat loss, water use, use of hazardous chemicals in power generation can be avoided with rooftop solar PV power plants.

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This paper is about static & Dynamic analysis of flange of flange mounted motor which is also known as B5 type motor by using FEA software ANSYS 15 and modeling is done with help of CATIA V5 R20. This is the special problem which is observed by Laxmi Hydraulics Pvt. Ltd Solapur, Maharashtra, India. They have reported frequent failures of this type of flange.

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Photovoltaic (PV) and other sources of renewable energy are being used increasingly in grid-connected systems, for which stronger power quality requirements are being issued. Continuous grid monitoring should be considered so as to provide safe connections and disconnections from the grid. One problem with Distributed Generators (DG) is an unwanted islanding phenomenon. This condition can be dangerous to grid workers who may not realize that the load is still powered even though there is no power from the grid. This paper proposes a new active islanding detection method based on impedance measurement which is a cost effective, simple, and effective method to prevent islanding of grid-connected inverters. Emphasis is placed on a method based on the injection of a non characteristic harmonic in the grid. Some of the injection parameters are tuned in order to get an accurate measurement of line impedance.

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A neuro-fuzzy method provides interpretation of fuzzy and learning of neural systems in a single structure. Also neuro-fuzzy can solve many real time problems in that Adaptive neuro-fuzzy inference system (ANFIS) is a careful and matched method for model building and best possible results. The effects of noise on human work efficiency are done by neuro-fuzzy model. The main factors of model are level of noise, type of work, and exposure time. The ANFIS is executed on Fuzzy Logic Toolbox in MATLAB. The data given is from noise monitoring in different sites.

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Railway is the most economical mode for transport in the India. Signaling in the railways plays a vital role to direct the trains in a right way at a right speed towards the destination. A single miscommunication in the signaling may lead to catastrophe in railways. This design tries an approach to improve the mode of communication (signaling) using PIC microcontroller and to avoid the train collision using power line carrier communication and semaphore signaling. The location of the train is detected at various parts of same track and it transfers through GSM technology to the controller. When two trains travel in same track the current location of the trains is sent to the control station. The warning signals and controlling signals to the train can also be transferred to the loco pilot using Power Line Carrier Communication (PLCC) providing proper signal alerts to the pilots can guide the pilots to avoid train collision.

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In the real world, any continuous medium deforms under the application of force. Rigid body simulations do not capture such deformations and may lead to inaccurate results. As virtual prototype replaces physical prototype, tests can be carried out to validate the design of product. Virtual prototype of multifunctional robot is developed to simulate the system level working with live stress distribution, which is designed to lift a design pay load. The design and analysis of a PC Controlled “Pick and Place” Robotic vehicle has been presented in this paper. The project of Design and Analysis of Robot Gripper for 500gm payload is divided into two parts. The main objective of the project is to design and analysis of Robot Gripper for 500gm Payload. In this project, design and analysis will rely heavily on design software, namely CATIA V5R19 and PATRAN for the analysis, simulation and animation of the gripper’s design.

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To recognition the person by using human speech is main task of Speaker identification. In many organizations like bank, industry, government office, education field speaker identification is most useful biometric techniques to identify speaker. This paper is discuses about the extraction of feature method -MFCC and GFCC for speaker identification.

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There are many different techniques that are proposed since the Image Super Resolution concept is introduced. Almost approaches that are existing are found to be working well on the toy data or the sample data but faces issues in the real world data. For the development of a practical Image Super Resolution there are many challenging issues ahead that may prevent the proposed techniques and approaches from the desired application. In the following, There are several such challenging issues that we think are important and to be focused on for the further development and wide applications of Image Super Resolution Techniques.

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The web contains data in huge amounts. This data is a large source of information. All this information is in the form of structured or unstructured data. List is a crucial source of structured data on the web. Ranking the list data is generously important for information retrieval. Tremendous efforts have been done for extracting information from the structured data, especially from web tables, which contain quality information. Instead of focusing on context- free structured data, we aim to focus on context that we can spot, and then using the context to render less controlled information and proceed to its extraction. Here we highlight expensive as well as, rich source of information on the web, those are top-k web pages. Top-k web pages contain rich and quality information. They aim to identity the top attribute values for the entities of interest. Extraction of such lists can help answering engines to generate different fact and can act as a pre-processing step.

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This paper contains an extensive study on the “Super Pave Mix Design” method which is used in the “Advanced Pavement Design” Technique. It helps in study and characterization of asphalt mixtures which are used as road pavement materials. By using the state of art laboratory test equipment and the technical literature obtained from the different information sources the several aspects of asphalt concrete mixtures has been expressed. This paper is divided into various parts. In Part one the detailed analysis of performance characteristics of asphalt concrete mixtures and design procedure is present with analytical method of aggregate blending which is used to design the aggregate structures. In part two the comparison between the Superpave and Marshall Stability hot asphalt mix designs have done. Various materials like: Coarse aggregates, fine aggregates, Bitumen etc. are considered for the Selection of materials on the basis of their properties. Such that the aggregates are selected on the basis of their various properties like strengths, soundness and shapes etc. On the basis of gradation aggregates sizes of 12.5mm and 20mm were designed for high traffic level whereas, 10mm were designed for low traffic level. There are different type of binders have been selected according to the traffic mixtures, PG 76-22M was selected for heavy traffic volume mixtures and PG 70-22M has been selected for low traffic volume mixtures. As it was given as PG-T1-T2 where T1 is considered as the maximum temperature value in degree Celsius and T2 is considered as the minimum temperature value in degree Celsius. After the selection of the suitable materials the design mixes have been prepared (Superpave Mix and Marshall Mix Designs) and further analysis has been done on the basis of following tests: Indirect Tensile Modulus Test, Uniaxial Loading Strain Test (Creep Test), Dynamic Modulus Test. The result of this paper suggests that dense aggregate structures provides good resistance to rutting behavior and maintained the adequate levels of durability. Such that this kind of mixes have to be developed to increase the resistance towards permanent deformation and to increase the durability.

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