NCRACS 2017 - National Conference on Recent Advances in Computer Sciences

"NCRACS- CC 2017 Conference Papers "

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Survey on Association Rule Minning Algorithms[ ]


In this paper, the detail description of survey focus on different kinds of Association Rule algorithms and also show case on the strength and weakness of each algorithm. we already know that, Data mining is the process of discovering novel ,useful and human understandable pattern in premises of information from large quantity of data. It has many methodologies for catching the information like Association rule mining, classification, clustering, regression etc. Among them Association rule mining is one of the most significant standing out investigation area in data mining. In past investigation , many algorithms were constructed like Apriori, Fp-Growth, Eclat, STAG etc. In this paper we discuss this algorithms in detail based upon the qualitative behaviour of each algorithms.

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AUTOMATIC STREET LIGHT CONTROL AND FAULT DETECTION SYSTEM WITH CLOUD STORAGE[ ]


The objective of the project is to provide automatic control and fault detection on street lamps. The lighting system which targets the energy and automatic operation on economical affordable for the streets and immediate information response about the street lamp fault. Moreover, errors which occur due to manual operation can also eliminate. The street light switched ON/OFF through an Internet of Things (IoT).The street light system is checking the weather for street lamp ON/OFF condition. The weather is light or dark are sense through a LDR sensor, If the weather is light, the system will OFF. If the weather is dark, the light system will ON. After the light on the light condition also check through LDR sensor for light glow or not glow status. If light is not glowing, the sensor sends the value to street light system. The street light system will generate message and send SMS to ward member and ward serviceman mobile number through GSM. At the same time the sensor values are stored in cloud server. We can access the light system data in cloud anywhere and anytime.

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A NOVEL SECURE MULTI-KEYWORD RANKEDAND TREE BASED SEARCH SCHEME FOR MULTI DATA OWNERS IN CLOUDCOMPUTING[ ]


Cloud computing has been considered an enterprise for IT infrastructure, which can organize huge resource of computing, storage and applications, and enable users to enjoy ubiquitous, convenient on-demand network access to a configurable computing resources with great efficiency and minimal economic overhead for shared pool. Attracted by these appealing features, both individuals and enterprises are motivated to contract out their data to the cloud, instead of purchasing software and hardware to manage the data themselves. So far, most of the works have been proposed under different threat models to achieve various search functions, such as single keyword search, similarity search, multi- keyword Boolean search, ranked search, multi-keyword ranked search, etc. Among them, multi-keyword ranked search achieves more attention for its practical applicability. propose a secure and ranked multi-keyword search protocol in a multi-owner cloud model over encrypted cloud data, which simultaneously supports dynamic update operations like deletion and insertion of documents. A special tree-based index structure is constructed and efficient multi keyword ranked search is proposed. Due to the use of the special tree- based index structure, the proposed scheme can achieve sub-linear search time and deal with the deletion and insertion of documents flexibly. As a result, different data owners use different keys to encrypt their files and keywords. Authenticated data users can issue a query without knowing secret keys of these different data owners. Extensive experiments on real-world datasets confirm the efficacy and efficiency of our proposed schemes.

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A CLOUD COMPUTING SOLUTION FOR THE EFFICIENT IMPLEMENTATION OF THE I-SBAS DInSAR APPROACH[ ]


An efficient Cloud Computing implementation of the Intermittent Small Baseline Subset (ISBAS) algorithm, which is an advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) technique for the generation of Earth surface displacement time series through distributed computing infrastructures. Ground motion as a consequence of natural geological processes or due to anthropogenic influences, is a considerable problem and concern to a variety of people and groups. These include the mining industry, insurance companies, government and not least the general population. Increased knowledge of subsidence patterns would benefit all parties involved however, often techniques used such as leveling and GPS have spatial or temporal shortfalls. Utilizing remotely sensed data and Differential Interferometric Synthetic Aperture Radar (DInSAR), the shortcomings of traditional measurement can be overcome, producing precise maps over wide expanses and over many years. DInSAR utilizes stacks of Synthetic Aperture Radar (SAR) imagery of the same area to derive ground motion rates with mill metric precision. A significant limitation of these techniques, be it utilizing small baseline or persistent scatterer methods, is the density of coverage it can achieve over dynamic rural environments. Interferometric analysis is not possible over large sections of the scene which can inhibit the identification of subsidence patterns, impeding the techniques efficacy. The Intermittent Small Baseline Subset (ISBAS) is an improved version of the established SBAS algorithm, designed to improve coverage over rural settings by considering intermittent coherence.

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A TWO PARTY PRIVACY PRESERVING SET INTERSECTION PROTOCOL AGAINST MALICIOUS USERS[ ]


An Electronic Medical Record(EMR) is a computerized medical record created in an organization that delivers care, such as hospital or lab. Electronic medical records tend to be a part of a local stand-alone health information system that allows storage, retrieval and modification of records. Using an EMR to read and write a patient's record is not only possible through a workstation but depending on the type of system and health care settings may also be possible through mobile devices that are handwriting capable. Electronic medical record (EMR) systems have enabled healthcare providers to collect detailed patient information from the primary care domain. At the same time, longitudinal data from EMRs are increasingly combined with bio-repositories to generate personalized clinical decision support protocols. A Bio-repository is a biological materials repository that collects, processes, stores, and distributes bio-specimens to support future scientific investigation. Bio-repositories can contain or manage specimens from animals, including humans, and many other living organisms. Vertebrates, invertebrates, arthropods, and other life-forms are just a few of the many classes of living organisms which can be studied by preserving and storing samples taken. Emerging policies encourage investigators to disseminate such data in a de-identified form for reuse and collaboration, but organizations are hesitant to do so because they fear such actions will jeopardize patient privacy.

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MOBILE PHONE CLONING[ ]


Mobile communication has been readily available for several years, and is major business today. It provides a valuable service to its users who are willing to pay a considerable premium over a fixed line phone, to be able to walk and talk freely. Because of its usefulness and the money involved in the business, it is subject to fraud. Unfortunately, the advance of security standards has not kept pace with the dissemination between the mobile communication, Some of the features of mobile communication make it an alluring target for criminals. It is a relatively new invention, so not all people are quite familiar with its possibilities, in good or in bad. Its newness also means intense competition among mobile phone service providers as they are attracting customers. The major threat to mobile phone is from cloning.

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ENHANCED EFFICIENT LOAD PREDICTION ALGORITHM IN CLOUD COMPUTING[ ]


In cloud computing environment, customers are allowed to scale up and down their resource usage according to their needs. Here resources are multiplexed from physical machines to virtual machines through virtualization technology. In this paper, we are trying to avoid overloading for every physical machine of an automated resources management system that uses virtualization technology for allocating resources dynamically. We develop a new algorithm for predicting the future load of each physical machine and then decide which may be overloaded next. Then we can take the necessary action to prevent the overload in the system. The experimental results support the improvements of our algorithm.

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