Slotting attachment drilling machine is nothing but one of the Lifting system in automobile at the time of emergency. In this Lifting system pneumatically operated one. Here the additional pneumatic cylinder and Control Valve is provided in the automobile itself. In this project, the Control Valve is used to activate/deactivate the Air input. The Valve is ‘ON’ at the time of emergency; the compressed air goes to the pneumatic cylinder. Then the compressed air passes through the tube, and then pushes the pneumatic cylinder, so that the Lifting is applied at the time of Valve in “ON” position (i.e.-Emergency time). The speed of the pneumatic cylinder is varied by using flow control valve. This is the way of controlling Lifting speed of the Trailer at the time of emergency. In our project, we have to apply this Pneumatic Modern Trailer Mechanism in Load Lifting Vehicles.

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In the future most of market deals with the Blockchain Technology, because this technology has decentralized database that records the data such as finance contracts, physical assets, and supply chain information. It has achievement over the time and is currently dominated and used by Bitcoin. It is not a new technology but it shown up with the bitcoin, now a days some of the transactions are done with the crypto currency. It gives innovative solutions for FinTech Industry. This technology has energized the financial services industry globally. This concept already brought a disruption in the financial industry. Coming the some of the Industries, which already implementing this technology are, Deutsche Bank, DBS Bank, EBA (Euro Banking Association), US Federal Reserve are some of Financial Sector Banks are going to use this Technology in as like Digital Payments, Assets. This technology is Transparent Business way. So this is very secured and transparent. It is like as distributed ledger. In this paper we have the securing the KYC Documents by using Blockchain Technology. Through by using this Technology we can immutable the data of KYC. If the data is immutable then automatically it will be secured without tampering the data.

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The search of being smart is overwhelming all over the nation. If the requirement is high, why not the automobiles being smart? The main motto of our paper towards vehicles being smart is due to, lack in people. The major cause for collision between automobiles were unqualified drivers (license less), drunken drive and, sudden medical issues. To overcome this, we are here with a wonderful solution were to Update the vehicle and groom its smartness. Traditional and ancient methods of igniting the engine will be by just the insertion of a key. Here, we integrated our ideas where starting a vehicle with the help of key, RF license card (which holds the license number, user details and their finger print). On the handlebars or steering wheels, we place sensor to measure the pulse rate and his/her thumb print by which we can approximately detect the person is drunk and match the finger print with the license respectively. With the use of controller, we check that all the condition satisfies and then allow the vehicle to ignite. GPS facility can be installed for personal vehicles for tracking in case of theft. For public transit we employ IOT to update the information about the driver along with the time of departure which can be used for the authorities to monitor them at ease. The implementation of this will set the roads free from tasting bloods. Women security stands as a big threat, for emergency purpose a person can access any vehicle by ignoring these conditions, use of a button but once it is used GPS starts tracking the vehicle and intimation will be sent to the police.

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Large amount of sediments are dredged from harbours and seaports for construction of the marine structures and for maintenance of the shipping channels. The dredged soil requires large area for disposal. Offshore dumping causes disruption in the aquatic environment. This soil cannot be used directly in construction processes directly since it exhibits properties such as low shear strength, high natural water content and high compressibility. Attempts were made to stabilize the soil for embankment construction and for landfill. This paper describes the suitability of dredged soil from Vallarpadam in pavement construction by stabilising it with flyash based geopolymer.

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Recently, progresses in keen cellular devices and situating approaches have in a popular experience upgraded casual communities, which enables customers to proportion their surveys, evaluations, snap shots, registration, and so forth. The geological information situated through PDA (public Display of Affection) overcomes any problems amongst bodily and superior universes. Area records works because the association between customer s physical practices and virtual interpersonal companies organized by using the superior cellular or net administrations. We seek advice from those interpersonal corporations which includes geological certainties as region based sincerely informal groups (LBSNs). Such facts Brings openings and difficulties for recommender structures to look the fresh start, sparsity hassle of datasets and score need. In this paper, we make end usage of the adaptable customers place volatile highlights to do score predication. We mine: 1.The significance amongst customer s critiques and individual element topographical area separations, known as person item geological association, 2. the pertinence between customer s rating contrasts and client individual location separations, alluded to as customer client geological affiliation. It is determined that humans s rating practices are stimulated by geographical location significantly. Additionally, 3 components: person object topographical association, consumer geological affiliation, and relational facet hobby likeness, are melded right into a certain together evaluating expectation adaptation. We direct a chain of analyses on a authentic social rating system dataset Yelp. Trial consequences show that the proposed approach beats contemporary designs.

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Recently, the huge amounts of data and its incremental increase have changed the importance of information security and the data analysis systems for a Big Data. Intrusion detection system (IDS) is a system that monitors and also analyzes of the data to detect any intrusion in the system or the network. High volume, variety and also high speed of the data generated in the network have made the data analysis process to detect attacks by traditional techniques very difficult. Big Data techniques are to be used in IDS to deal with the Big Data foraccurate and efficient data analysis process. This paper introduced Spark‑Chi‑SVM model for a intrusion detection. In this model, we have to be used ChiSq Selector for feature selection, and built an intrusion detection model by using support vector machine (SVM) classifier on Apache Spark Big Data platform. We used KDD99 to train and test the model.

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The acute problem of carbon dioxide emissions reduction into the atmosphere becomes more important due to the fact of the global climate change. Housing stock consumes 30 to 40% of all energy resources, according to various estimates. As the result, it is possible to get carbon dioxide atmosphere emissions reduction due to energy consumption reduction. The problem of housing stock energy efficiency improvement becomes very important. Transition to low energy consumption buildings construction becomes a trend which in the nearest future will transform to the task of Applied Research in the field of design and construction. Such exploration object is to design buildings with zero energy consumption or close, which is planned construct on the site of the Polytechnic University. The novelty of the project consists in an integrated approach of the house design, which will be entirely autonomous and independent from the urban networks.

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We widely use k-means method for clustering technique for various applications. However, the k -means often converges to nearby superior and the end result depends on the initial seeds. Inappropriate desire of initial seeds may also yield terrible outcomes. K means++ is a manner of initializing k-means by way of choosing preliminary seeds with particular possibilities. Due to the random selection of first seed and the minimal likely distance, the k-means++ additionally outcomes different clusters in special runs in extraordinary range of iterations. In this examine we proposed a technique referred to as Single Pass Seed Selection (SPSS) algorithm as modification to k-means++ to initialize first seed and probable distance for k-means++ based at the point which became near extra wide variety of other factors within the statistics set. We evaluated its overall performance by making use of on various datasets and compare with k-means++. The SPSS set of rules turned into a single skip set of rules yielding particular solution in much less variety of iterations whilst in comparison to ok-means++. Experimental effects on real information sets from UCI established the effectiveness of the SPSS in generating regular clustering effects. Conclusion: SPSS performed well on high dimensional facts units. Its performance improved with features in the data set; specifically while range of capabilities we recommended the proposed method.

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As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus. Compared to the state-of- the-art methods, the new method has shown significant improvements on effectiveness on five real-world datasets in different domains recently, a few data-driven methods have been developed successfully for extraction of phrases from massive domain-specific text. However, none of the state-of-the-art models is fully automated because they require human experts for designing rules or labeling phrases. In this paper, we propose a novel framework for automated phrase mining, AutoPhrase, which can achieve high performance with minimal human effort. In addition, we develop a POS-guided phrasal segmentation model, which incorporates the shallow syntactic information in part-of-speech (POS) tags to further enhance the performance, when a POS tagger is available. Note that, AutoPhrase can support any language as long as a general knowledge base (e.g., Wikipedia) in that language is available, while benefiting from, but not requiring, a POS tagger.

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The main objective of this experimental project is to investigate and find out the strength characteristics of concrete after the replacement of cement with fly ash along with rice husk ash which are the mineral admixture and bamboo fibre as a replacement of coarse aggregate. In addition to this master rheobuild 918 which is the chemical admixture used as a super plasticizer. This paper has been made an attempt to study the influence of fly ash and rice husk ash each on replacement ratios of 0%, 5%, 10%, 15%.The coarse aggregate is made with 0%, 1%, 2%, 3% of bamboo fibres. The tests considered for our study are compressive strength test, split tensile strength test, flexural strength test and these test results are compared with strength results of conventional concrete.

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Today, Cloud computing is most widely used system due to number of benefits to end users. In IT (Information Technology) organizations, cloud computing is most vital domain to work. There are different types of services such as SaaS, IaaS and PaaS provided by cloud computing based on the end users needs. Rather than using own resources for data storage and Management, organizations started to utilize cloud computing data storage systems. Cloud storage (eg. Amazon S3) is emerging as a popular service and most of the enterprises shifts their data workloads to the cloud. The popularity of Cloud computing system increased dramatically because it rent computing resources, bill on a pay-as-you-go basis and multiplex many users on same physical infrastructure. Cloud users are provided an illusion of infinite computing resources so that on demand resource consumption rate can be increased or decreased. Cloud computing offers the vision of a virtually infinite pool of computing, storage and networking resources where applications can be deployed. It is the popular solution for on-demand and dynamic resource provisioning. The provisioning & maintenance of cloud resources are done with the help of resource management techniques (RM). The RM techniques are responsible to keep the track of free resources and assign the resources from free pool to incoming tasks. Along with the growing demands of modern applications and workloads, cloud computing has gained prominence throughout the IT industry. Modern applications are growing along various dimensions such as the number of users, complexity, data size and many people are connecting to the internet through various devices. Web Applications which deals with the cloud storage systems contain heterogeneous workload to deploy on the cloud. This heterogeneous workload needs to be handled carefully otherwise problems like long scheduling delay, starvation for low priority tasks may occur which can hurt the performance of the application significantly. To handle this workload characterization is much more important. In workload characterization, heterogeneous workload is divided into multiple task classes with similar characteristics in terms of resource and performance objectives. It is important to consider heterogeneity of workload. The workload typically consists of diverse applications with different priorities and resource requirements. Failure to consider heterogeneous workload, it will lead to long scheduling delay, starvation by affecting performance of the application. Modern applications faces challenges such as workload characterization, resource allocation and security. To meet these needs we propose a new framework which interacts with the heterogeneous database systems and provides workload characterization by using K-means clustering algorithm, resource allocation by providing virtual machines through requesting to the cloud and security by using AES algorithm for encryption and decryption. In this research work, transactions are taken in form of heterogeneous files from users as input and deploy the files efficiently at cloud storage system as output. Transactional operation like insert, update, delete are performed on users data at cloud storage systems. Here, we are attempting to design novel approach for secure, energy efficiency, scalable transaction management system based on terminologies and methods of resource scheduling in heterogeneous distributed database systems. We address “the transaction management problem", which is to interact with the heterogeneous database systems and to allocate and schedule computing resources with workload characterization by providing security to user’s data. Performance Evaluation of the proposed system is done based on fluctuating workloads and in terms of Throughput, Energy Efficiency, CPU Utilization, Scheduling Time, Response Time. The performance of the system is measured and compared with Container Based Scheduling (CBS), Dynamic Power–Saving Resource allocation (DPRA) mechanism and SLA-Aware Energy resource management (SLA) technique. The Experimental results of the proposed system shows effective performance of the system. Results shows that proposed system outperforms existing techniques. The implemented environment is easy to use and the input to the system are given for execution in a normal way without changing or restructuring the code.

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The project deals with stabilization of soil using industrial waste. Unsuitable highway sub grade soil requires stabilization to improve its properties. Fly ash is used as raw materials when the sand can no longer be reused in the industry, it is removed from the industry and is removed from the industry and is termed as industrial waste sand. Fly ash was bought from locally available industries fly ash is used with variable percentage i.e., (10%, 20%, and 30%). For optimum percentage of fly ash within this that percentage of fly ash is used in sub base for stabilization. The project are planned to conduct various experiment like Specific gravity, sieve analysis, proctor compaction test, unconfined compressive strength and direct shear test to increase strength properties and behavior of sub base. Then the results and graphs of various mixes are compared to see their effects in sub base stabilization. The stabilization technique has an additional benefit of providing an environment friendly way to deal with fly ash.

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Pervious concrete pavement is sustainable type of concrete pavement that can protect and restore natural ecosystem. Pervious concrete is emerging as an alternative material for paving to help curtail non-point source pollution problem. It is one of the most effective pavement material to address a no. of important environmental issue, such as recharging groundwater and reducing storm water runoff. In this experimental investigation on properties of pervious concrete are reported and discussed. The amount of general Portland cement has been reduced by introducing fly ash as cementitious agent in pervious concrete sample. The properties of pervious concrete samples including density, porosity, compressive strength, etc. According to the result, high porosity samples indicated higher permeability, whereas compressive strength was reduced. There was no significant difference between properties of pervious concrete samples containing fly ash and those samples only comprises only cement as cementitious agents.

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The data mining is a process of analyzing a huge data from different perspectives and summarizing it into useful information. The information can be converted into knowledge about historical patterns and future trends. Data mining plays a significant role in the field of information technology. Health care industry today generates large amounts of complex data about patients, hospitals resources, diseases, diagnosis methods, electronic patients records, etc. The data mining techniques are very useful to make medicinal decisions in curing diseases. The healthcare industry collects huge amount of healthcare data which, unfortunately, are not "mined" to discover hidden information for effective decision making. The discovered knowledge can be used by the healthcare administrators to improve the quality of service. In this paper, authors developed a method to identify frequency of diseases in particular geographical area at given time period with the aid of association rule based Apriori data mining technique.

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Frequent itemset mining is a major field in data mining techniques. This is because it deals with usual and normal occurrences of the set of items in a database transaction. Originated from market basket analysis, frequent itemset generation may lead to the formulation of association rule to derive correlation or patterns. Association rule mining still remains as one of the most prominent areas in data mining that aims to extract interesting correlations, frequent patterns, association or causal structures among a set of items in the transaction databases. The underlying structure of association rules mining algorithms are based upon horizontal or vertical data formats. These two data formats have been widely discussed by showing a few examples of the algorithm of each data formats. The works on horizontal approaches suffer in many candidate generations and multiple database scans that contribute to higher memory consumptions. In response to improving on the horizontal approach, the works on vertical approaches are established. Eclat algorithm is one example of an algorithm in vertical approach database format. Motivated to its "fast intersection", in this paper, we review and analyze the fundamental Eclat and Eclat-variants such as mindset, diffset, and sort different. In response to vertical data format and as continuity to Eclat extension, we propose a post diffuser algorithm as a new member in Eclat variants that use mindset format in the first looping and diffset in the later looping.

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The purpose of this paper is to illustrate the implementation of a PAAI as an Intelligent Personal Assistant (IPA) that can perform numerous tasks or services for an individual. These tasks or services are based on user input, location awareness, and the ability to access information from a variety of online sources (such as weather or traffic conditions, news, stock prices, user schedules, retail prices, telling time, local traffic, travel assistant, events, notification from social applications plus one can ask questions to the system, invoke its machine learning otherwise get it from Wikipedia… etc…..). Using Raspberry Pi as a main hardware to implement this model which works on the primary input of a user’s voice. The voice hence produced was used for query processing and fetching relevant information. When the information was fetched, it then be search s for the input command and the relevant output to the user was given. Additionally, some extra modules were also implemented which worked on the concept of keyword matching. It can help the visually impaired to connect with the world by giving them access to Wikipedia, Calculator, Email and Music all through their voice. This model can also keep people secure as it can be used as a surveillance system which captures the voice of the person standing at the door and similarity checking. Also it can be a source of entertainment and information for blind/visually impaired.

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Data association is a trying issue in data coordination. The comfort of data increases when it is associated and joined with other data from different (Web) sources. The assurance of Big Data turns subsequent to keeping an eye on a couple of real data blend troubles, for instance, record linkage at scale, ceaseless data mix, and organizing Deep Web. Though much work has been driven on these issues, there is compelled take a shot at making a uniform, standard record from a social affair of records identifying with a comparative genuine component. We insinuate this errand as record institutionalization. Such a record depiction, conceived institutionalized record, is basic for both front-end and back-end applications. In this paper, we formalize the record institutionalization issue, present start to finish examination of institutionalization granularity levels (e.g., record, field, and regard portion) and of institutionalization shapes (e.g., typical versus complete).

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The rapid growth of Internet and WWW has increases to vast amounts of information available online. Big data is an evolving term that describes an voluminous amount of structured, semistructured and understructed data that has the potential to be mined for information. For this nowadays various Data intensive technologies (Map Reduce) are used which uses computer applications, which requires large volumes of data and most of their processing time to I/O and manipulation of data .In order to store, manage, access, and process vast amount of data available online and the data that is created in structured and unstructured form, Data intensive computing is needed which satisfies the need to search, analyze, mine, and visualize the large amount of data and information. We will analysis already available Data intensive technologies with Hadoop Data intensive to provide high performance, should be fault resilient over hardware failures, communications errors, and software bugs and executing a variety of data intensive analysis benchmarks.

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Anytime Automated Medicine Vending Machine is although not a newconcept in its totality, it could prove to be useful and hence important in developing countries like India where healthcare is almost life-threatening. Health plays the role of a strong societal component connecting it to education and access to information. On other scale of health, poverty involves low income, low education, social prohibition and environmental decay. Most of the countries are trapped in a cycle inwhich poverty breeds ill health. We have proposed an automated medicine vending machine that dispenses medicine as per the user s choice. Our system is cost efficient when compared to the other existing vending machine owing to the use of actuators. In section II, description is given for medicine vending machine. Section III discusses about the vending machine performance. The conclusion part of the paper and the future work are discussed in section IV.

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In India there are huge leather products producing industries are developed. . Through waste water of tannery industry produces high inclusion of toxic content, which is more dangerous in environment without treatment. The drawback of conventional technologies for waste water treatment have led to serious thinking on alternate, low cost, natural and energy saving technologies on water and wastewater treatment. Methods like Phytoremediation which employs floating plants, constructed wetlands, etc., for treatment of wastewater will be a better alternative to the conventional technologies. Floating plants such as seaweed has a remarkable ability in treating the polluted water. Hence the current study is focused on the treatment of industrial effluent using marine algae. The objective of the study is to determine the phytoremediation potential of seaweed on industrial effluent treatment. Batch study has been employed to find the pollutant reduction efficiency of seaweed. Thus this process becomes more economical and effective.

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Cloud computing is a framework that provides everything as a service on demand by use of high speed internet. Any IT company or a single user may take benefit of cloud computing by pay per use strategy. A user who pays for a service on cloud computing need not to care about the maintenance and storage of his personal information. In this way an IT company or a user can use the resources via cloud computing, which they were not able to purchase. Virtualization is the central part of cloud computing which enables a physical resource to behave as a logical one. It exists in various forms such as Hardware virtualization, Network virtualization, Storage virtualization, Desktop virtualization, Data virtualization, Software virtualization, Memory virtualization etc. This paper reviews the concept of virtualization in cloud computing, its types, benefits and drawbacks of virtualization.

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This report is aimed to obtain the velocity and pressure profile, production of Lift and Drag by Airfoil at particular AOA, separation of flow over an Airfoil, the graph of variation in coefficient of lift with AOA (cl-α) and coefficient of Drag with AOA (cd-α) is plotted by using the Ansys Software for an NACA 4412 and NACA 0018 Airfoil. We use fluent module in Ansys for Analysis. CFD plays an important role in design and optimization process. In this project we are comparing the Computational result with the standard result.

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Apriori algorithm has been successfully used for finding the persistent item sets in huge databases. In this paper study about finding associations between item sets contains data about diagnosis and treatment. It has shown that the algorithm is equally beneficent for finding the large item sets and thus generating the association rules in transactional databases. Healthcare is a data rich domain so we have applied Apriori algorithm for medical practices, insurance companies and other health related organizations that have collected huge volumes of data, thus attracting data mining researchers to explore it and find something beneficent from it.

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Gadgets have made life pleasurable ranging from a washing machine, chimney, electric hub, the churner, the television set, A.C., Room heater, Fans, dryers, hair straighteners, dish washers, sewing machine, air purifiers are all also gadgets. Yet from linking remote villages via increasingly ubiquitous mobile-phone messaging to improved water safety and cooking tools, technological innovations are changing the lives of women and their families for the better, around the world. The world has become so advanced that we have computers and laptops in almost every household today. Internet facility is also a great invention. Mobiles help us to talk to anyone, anywhere at any time. Man has come a long way from the invention of the wheel. There are serious disadvantages of such a fast pace of progress, like global warming and pollution but scientists are working on that too. All electronic gadgets have improved our life a lot. So in the coming centuries we can imagine how our life might be. In this backdrop the present study has made an attempt to identify the role, uses, enhancements and issues concerned with e-gadgets. The e-gadgets actually have increased human productivity in terms of work and made the world a better place to live in. Though gadgets bring joy to the family there are few challenging issues which are to be considered. In order to make the e-revolution a successful one, certain steps should be considered by the Government of India. There are many innovative gadgets ranging from home to organizations are being developed through the initiatives by several companies.

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There is a need to match the emission and estimations accuracy with the outputs of transport models. The overall an error rate in long-term traffic forecasts results from strategic transport models is likely to be significant. The Micro simulation models, whilst high-resolution in nature, they have similar measurement errors if they use the outputs of strategic models to obtain traffic demand predictions. At the micro level, this paper discusses the limitations of existing emissions estimation approaches. The Emission models for predicting emission pollutants other than are proposed. The genetic algorithm approach is adopted to select a predicting variables for the black box model. This approach is capable to solving combinatorial optimization problems. Overall, an emission prediction of results reveal that a proposed new models outperform conventional equations in terms of accuracy and robustness.

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