In this paper we present a small, credit-card sized, and low-cost electromagnetic energy harvester that couples energy from one conductor of an overhead power distribution line. We use a rectangular coil, placed near the power line without encircling it, to extract electrical power from the time-varying magnetic field. The addition of a U- shaped electrical steel sheet (a high-permeability material typically used in transformers) near the coil significantly increases the magnetic flux through the coil and consequently raises the output power. Experiments have shown that the harvester with an optimal load resistance obtains 230 mW (AC) when the power-line conductor current is 50 Arms. The energy harvester is able to power a wireless gas sensor board having a carbon monoxide and an ozone sensors at 10 Arms. In this paper, we describe the design, modeling, and experimental study of the electromagnetic energy harvester with an output power range between several milliwatts to hundreds of milliwatts from an ac current up to 50 Arms. We anticipate that the energy harvesters could be installed inexpensively on the overhead power distribution lines by a utility operator using a hot stick.

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Educational data mining (EDM) is a multi-disciplinary research area that examines statistical modeling, artificial intelligence and data mining with the data generated from an educational institution. In this mainly focus on prediction of student’s academic performance. Some statistical tools are also used for predicting student’s performance. In this paper we implemented Apriori and k-means clustering algorithm is use for predicting the student’s result. Apriori algorithm more efficient and less time over whelming for predicting the student results. The main objective of exploitation Apriori and k-means clustering algorithm is for predicting the students’ academic performance and also improving students’ academic performance. During this academic student performance is evaluated supported some attributes are selected which generate rules by suggests that of association rule. In this paper we used k-means algorithm for calculating the test anxiety (stress) and time management of the students at the time of examination. It will help to improve the student’s tutorial performance. Experiment is conducted usingWeka and real time knowledge set on the market within the college premises , collected from the students and the result which released by the university.

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Cloud computing is the next generation of computation and comprises web-based tools and applications as opposed to a direct connection to a server. Cloud providers typically use a "pay-as-you-go" model, which can lead to unexpected operating expenses if administrators are not familiarized with cloud-pricing models. The availability of high-capacity networks, low-cost computers and storage devices as well as the widespread adoption of hardware virtualization, service-oriented architecture, and autonomic and utility computing has led to growth in cloud computing. It is a model that provides an on-demand network access to a shared pool of computing resources. It comprises a huge number of concepts primarily Load Balancing, Scheduling, etc. The number of users in cloud computing is growing in an exponential rate at every day. The number users access cloud server by sending enormous request for many application which lead to high load on cloud server. To reducing the heavy load on server, the virtual machines are allocated for resources based on priority. Allocating the resources on virtual machines based on priority achieves the better response time and processing time. The main aim of the system is to minimize the make span and to maximize the resource utilization and user satisfaction.

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Welding is a system of immutable joining two materials (regularly metals) through restricted blend coming about due to a proper mix of temperature, weight and metallurgical conditions. Dependent upon the blend of temperature and weight from a high temperature with no weight to a high weight with low temperature, a wide extent of welding shapes has been made. There are various sorts of welding including Metal Arc, Submerged Arc, Resistance Butt, Flash, Spot, Seam and Projection. While there are various procedures for joining metals, welding is a champion among the most accommodating and quick systems 1available. The gas metal roundabout portion welding (GMAW) process uses a solid wire terminal that is constantly supported into the weld pool. The wire anode is eaten up and transforms into the filler metal. GMAW equipment is reasonably low in cost. The low beginning cost, the ability to weld continually, and the ability to store weld metal faster, settle on GMAW an appealing choice for welding. This section uncovers each part of GMAW. It includes all parts of GMAW, for example, welding machine, protecting gases, filler/terminal wire and welding joint get together of welding plates. V furrowed butt joint will be loaded up with 1.6 mm cathode wire ( ER 90 BL-3) utilizing ESAB AUTO K 400 welding machine. Example for different tests, for example, hardness, tractable, small scale structure, consideration and gas ingestion will be drawn from the butt welded joint according to particular.

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Fetal health is commonly surveilled by cardiotocography (CTG) monitor, which documents fetal heart rate (FHR) signal. The fetal health monitoring is very important to predict the growth of the fetal as well as improvement in its each stage. For yielding the status of the fetal more accurately, fetal heart rate (FHR) signal is the best well known source. From this gained information, embryo’s unhealthiness can be visualized and it provides a chance to take action before an irremediable harmness happening to the fetal. Previous work uses Naïve Bayes and SVM classifier, which was used in the olden days, to classify the CTG data, produced low accuracy. To improve the classification accuracy, the proposed work addresses Adaptive Boosting algorithm for classification of congenital heart disease in fetus. Fetal state is commonly grouped into normal and pathological class. The results of these classifiers are to be compared and the best classification technique is to be identified.

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Know-how mining is a redesigning innovation for studying extraction in countless fields like restorative, instructive, today s, and many others. Extricating a critical understanding from large database is most crucial component. Know-how extraction process were finished through numerous methods like component extraction, forecast, characterization, etc. for our examination investigations expectation of understanding digging helps a first-rate deal for attending to useful knowledge. In this paper we targeting road site visitors dataset and we utilized fluffy expertise extraction for participation work by using FCM. For the understanding extraction method right here we actualized the connection and coefficient calculation for avenue visitors dataset and property decrease had been completed through utilising Genetic calculation ultimately with the help of A-Priori calculation we create the ordinary for the digging the associate object for spotlight lower.

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In Recent trends shows Cloud computing technology is adopted by many IT companies as it reduces the investment burden for infrastructure, software, hardware or any reasonably resource in a company. However, one amongst the most important problems in implementing or adopting cloud is threats due to security breaches. To ensure security, countless ancient secret writing algorithms are used like various truthful cipher mechanisms, RSA, Homomorphic secret writing etc. however these algorithms are solely accustomed to convert plain text into cipher text during transit or at storage. Homomorphic encryption can be a particular type of encryption where mathematical operations on the cipher text is like mathematical operations on the corresponding plaintext. Homomorphic encryption (HE) is fascinating on account of the particular proven fact it can operate on big databases. In this paper discussed and studied the fundamental concepts of HE, along with various homomorphic encryption schemes and their possible implementation in cloud computing.

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The primary purpose of this report is to present the design of a solar dryer cum solar cooker and also the investigations carried out in order to evaluate the influence of incorporating a desiccant on the drying efficiency of the solar dryer. The findings obtain in this project through experimentation reveal that the incorporation of a desiccant can help improve the drying efficiency. The use of silica gel as a desiccant was made. The study also describes the conditions that led to the selection of silica gel as a desiccant.

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Refrigerating systems has emerged as an important necessity of human life in present century. Today, these systems are used in many applications. Present research work is devoted to the investigations for of an important category of refrigerant systems, vortex tubes. In the research work, combinations of six gases and three materials are made for analyzing pressure differences and thermal gradients for a vortex tube. The flowing gases were Argon, CO2, Nitrogen, Oxygen, Helium, and air, and the materials are Cast iron, Copper and Brass. As a result, combination of Helium and Brass emerged out as the best combination for the application.

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At present time enormous measure of helpful information is accessible on the web for access, and this gigantic measure of information is shared data which can be utilized by anybody expected to utilize. The accessibility of different nature of record information has lead to the assignment of grouping in the dataset. Bunching is one of the essential procedures utilized for grouping of the huge dataset and broadly pertinent numerous territories. High caliber and quick archive bunching calculations assume a huge job to effectively explore, outline and arrange the data. Late investigations have demonstrated that partitional grouping calculations are suit-capable for substantial datasets. The k-implies calculation is commonly utilized as partitional grouping calculation since it may be effortlessly actualized and it is most effective as far as execution time. The significant issue with this calculation is affectability for determination of the underlying allotment and its intermingling to nearby optima. In this examination it think about refined helpful data from record informational collection utilizing least crossing tree for archive bunching and great nature of groups have been produced on a few report datasets, and the yield demonstrates acquired shows a viable enhancement in execution.

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In today’s scenario collecting a productive data & scrutinizing it is a tedious job. Data mining is one tool which can help to improve data quality in less time consuming manner. Data mining is known as Knowledge Discovery in Database (KDD). Education industry has grown rapidly over a last few years. Usage of technology has improved teaching learning methodology. A growing number of institutes in both public and private sector are offering huge diversity to all its aspirants students whether graduate, under graduate, post graduate, diploma or vocational courses. It is a concern for today’s education system and this gap has to be identified and properly addressed to the learning community. Utilization of DM techniques in education sector is a developing and new growing research area. It is also known as Educational Data Mining. The Educational Data Mining is involved with developing the methods that helps to search specific types of data sets that come from education surroundings. Hence it has become important to understand the requirement of students and their academic progression. Educational Data Mining helps in a big way to answer the issues of predictions and profiling of not only students but other stake holders of education sectors. This paper can highlight some tools and techniques to discuss predictions of students progress and its impact on teaching learning methods.

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Presently, the growth of internet has given rise to increasingly utilize internet for public and commercial services. As a result malicious activities are on the rise to exploit users to steal information related to credit card details, passwords, sensitive information etc. It has become a major concern in the society to protect data shared across networks and stored in computer. At the same time attackers use many techniques to gain advantage of breaking firewalls and security measures. The attacker use techniques to steal the data such as malware, viruses, Trojans etc. An intrusion detection system is used to detect and block malicious traffic originating from attackers. Traditional Intrusion detection systems are becoming less effective to capture the malicious traffic. Combining data mining techniques into intrusion detection system offer more security than traditional methods. Since data mining can use vast number of data, detecting a tiny variation in the network traffic is possible leading to detect and block unwanted traffic in the network. In the present study multi layer perceptron classifier is used to classify the network attack types. MLP based intrusion detection system is designed to support network administrators to find signature based attacks and anomaly of the network traffic. The IDS is trained on the traffic data using MLP to capture the known attack types and differentiate traffic as intrusion and normal traffic.

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We investigate the harmonic mean of several standard line graphs such as path, Triangular line snakes graphs, Quadrilateral lien snakes graphs. etc.

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In today’s Hi-tech era crime is increasing day by day. Security and safety has always become a basic necessity for urban population. Due to increasing threats and intrusions in society, everyone needs a advanced security system which can keep their belongings secure and at the same time they also want to protect their home assets from any kind of hazard. They require simple, reliable and high performance system that can be easily implemented. This system can detect the theft, fire, door break, etc. and sends an auto-generated email remotely to intimate the owner. The major goal of the system is to design a cost effective home security system based on wireless sensor network using Wi-Fi and cloud technologies. Mobile phones can remotely control household appliances and can receive a feedback SMS when any intrusion is suspected in house or industry.

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Smart Home Automation refers to using management systems and information technology to operate, manage and control daily use home appliances such as lights, fans, televisions, thermostats doors, windows, etc and doing so reducing the need for human interference. The world is moving towards a digital era and implementing Internet of Things devices will be a necessity, this paper presents an insight into the current scenario of Home Automation across India and feasibility and Future Scope of Smart Home Automation in India. India’s growing economy has led to an increasing population receiving higher wages which in turn will increase the standard of living, thus augmenting the demand for Home Automation Devices. Home Automation is still a niche market in India catering to the upper class. This paper will focus on the scope and adaptability of Home Automation in India from 3 perspectives - Energy, Safety & Comfort. The importance and limitations on Smart Home Devices will be discussed and trends in Smart Home Automation will be analyzed through the course of paper. Challenges and feasible solutions will be considered to device an efficient smart home system.

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In this Information age, the volume of data dealt everyday is enormous already, and is still growing. This has led to the development of various cloud storage services that help users store and manage the data with ease. So, it is natural that a user s data stored across multiple accounts in various cloud services, bringing with it the overhead of maintaining these accounts. Therefore, there is a need for unifying these accounts into a single module to help the user access them easily. The paper aims to solve this problem by integrating many of these services into a single cloud service. The service can be authenticated by the user only once. To access the files a tabbed view of all the services is being provided. The use of REST (Representational State Transfer) APIs of all the services to retrieve and list the files, is integral to the working of the module. The OAuth 2.0 protocol, which is the current industry standard, is followed to authenticate all of the services. The idea helps in managing various cloud platforms within a single unit. The access and management of projects is easier, since the integration of various cloud services is scalable.

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The elimination of duplicate data particularly in computer related data is called as data deduplication. According to deduplication, we introduce a method that eliminate redundant encrypted data owned by different users. This mechanism uses the concept of secure cloud where user is able to generate data tags before storing data on cloud which helps during performing audit to check integrity of data.

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This paper portrays the recent techniques that have been developed for optimization of linear programming problems. This paper aims to solve the fuzzy linear programming problem using ranking function and here the fuzzy numbers which are involved are trapezoidal fuzzy numbers.

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Cold-formed steel makes the major role in structural construction. Footing, column and beam are makes the major role to strengthen the structure. Beam of the I-section with corrugated web can be investigated by experimentally and analysed by ANSYS software. Also comparison between beams with flat web to the corrugated web normally the beam of I-section with flat web can be used. But our aim is to attain more strength with corrugated web. Mainly the flexural strength can be studied and discussed. Experimental test should under two points loading in simply supported condition. Similarly the numerical analysis could do with same condition. As a result that the I-section with corrugated web attains higher flexural strength compared to flat web and there was no failure in shear zone. Also the depth of web increases thus the strength increases.

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There are much more tannery based industries presented in India .wastewater released from tannery industry produces high inclusion of toxic content, which is more dangerous in environment without treatment, so it’s more challenge to keep environment clean. Now a days some new advance techniques were developed, such as adsorption, treatment with Nanoparticles, using UASB reactors. Among all these techniques, UASB (Up Flow Anaerobic Sludge Blanket) reactor is popular and more effective method for treating the tannery wastewater. UASB reactor method is anaerobic treatment. This process effectively treat wastewater and produces bio-gas (CH4) which is combustion gas as well as good energy source, so that make this process more economical. In UASB reactor the amount of energy gas produced is directly propositional to amount of inorganic matter removed.

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A nRF401 Controlled Spy Robot is an Arduino Uno based robot that can be monitored and controlled by a remote using a single-chip radio transceiver. The Wireless Network Camera mounted on the robot can also be displayed on any other Android device for monitoring. In this project simple materials are used like plastic wood for the chassis, cycle spokes for the wheel axle, L293D motor driver and two 600 rpm DC motors for propulsion in four directions namely front, reverse, left and right. nRF401 module is used to receive commands in the form of strings from the robot. The robot is covered with camouflage texture so that it does not alert surroundings. It is made up of simple materials rather than preassembled kits because the materials are readily and cheaply available, the robot becomes very lightweight and it can be formed into any desired size.

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Deduplication, which can save storage cost by enabling us to store only one copy of identical data, becomes unprecedentedly significant with the dramatic increase in data stored in the cloud. For the purpose of ensuring data confidentiality, they are usually encrypted before outsourced. Traditional encryption will inevitably result in multiple different cipher texts produced from the same plaintext by different users’ secret keys, which hinders data deduplication. Convergent encryption makes deduplication possible since it naturally encrypts the same plaintexts into the same cipher texts. One attendant problem is how to reliably and effectively manage a huge number of convergent keys. Several deduplication schemes have been proposed to deal with the convergent key management problem. However, they either need to introduce key management servers or require interaction between data owners. In this paper, we design a novel client-side deduplication protocol named KeyD without such an independent key management server by utilizing the identity-based broadcast encryption (IBBE) technique. Users only interact with the cloud service provider (CSP) during the process of data upload and download. Security analysis demonstrates that KeyD ensures data confidentiality and convergent key security, and well protects the ownership privacy simultaneously. A thorough and detailed performance comparison shows that our scheme makes a better tradeoff among the storage cost, communication and computation overhead.

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Existing studies on keyword search over relative information typically realize Steiner trees composed of connected database tuples as answers. Recently, tuple units square measure planned to boost search potency by classification structural relationships, and existing ways establish one tuple unit to answer keyword queries. However, in several cases, multiple tuple units ought to be integrated to answer a keyword question. Thus, these methods will involve false negatives. To address this downside, during this paper, we tend to study the way to integrate multiple connected tuple units to effectively answer keyword queries. To attain a higher performance, we conceive two bond indexes, SKSA index and KPSA index, and incorporate structural relationships between different tuple units into the indexes. We use the indexes to expeditiously establish the answers of integrated tuple units. We develop new ranking techniques and algorithms to increasingly realize the top-k answers. We have enforced our methodology in real information systems, and therefore the experimental results show that our approach achieves high search potency and result quality, and outperforms progressive ways considerably.

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The privacy is primary when imparting inconspicuous data, and individuals have formulated some unordinary systems to encode their discussions. The Quantum Key Distribution consents for the dependable transmission of unbreakable encryption keys and it gives an immaculate relaxed coding to take care of the hassle of key circulation. At present this is more and more boost software within the discipline of quantum figuring. The elemental inspiration of this conference includes two gatherings, wishing to trade a key both with entry to a normal open correspondence channel and a quantum correspondence channel. The snare refining technique of BB84 is usually utilized in light of the truth that the demonstration of perusing a quantum bit (QuBits) alterations the bit, it is tough for programmers to meddle with out being recognized ample number of bits. Yet, this procedure makes use of just four bearings of electron tendencies so it is possible to determine the key. To beat these hazards right here two dimension QRNA process is proposed for security. In first dimension DNA is connected on undeniable content material after BB84 conference is connected. This procedure offers superior safety over each BB84 convention and DNA alone.

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Phenol is a major pollutant in the wastewater because of its presence in the effluent of more processing and refining plants. Suitable method for phenol removal can be selected based on availability of the material, extent of separation required and properties of phenolic effluent. Locally available sawdust, a very low cost and promising material was tested experimentally as an adsorbent, after carbonization, for the removal of phenol from industrial waste waters for a safe disposal. The experiments were performed in batch wise to remove phenol from synthesized aqueous solutions. The equilibrium of adsorption was determined as a function of the solution, contact time, adsorbent dose. Adsorption isotherms of phenol for adsorbents were determined and correlated with the usual isotherm equations such as Langmuir and Freundlich. Equilibrium model analysis indicates the fitness of Langmuir Isotherm model (R2=0.9943) to Phenol-Sawdust adsorption system.

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