Research Paper on Basic of Artificial Neural Network

An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, s uch as pattern recognition o r data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. This is true of ANNs as well. This paper gives overview of Artificial Ne ural Network, working & training of ANN. It also explain the application and advantages of ANN

Clustering and Data collection in Wireless Sensor network using Dual Data Uploading

In this project, a three-layer framework is proposed for mobile data collection in wireless sensor networks, which includes the sensor layer, cluster head layer, and mobile collector (called SenCar) layer. The framework employs distributed load balanced clustering and dual data uploading, which is referred to as LBC-DDU. The objective is to achieve good scalability, long network lifetime and low data collection latency. At the sensor layer, a distributed load balanced clustering (LBC) algorithm is proposed for sensors to self-organize themselves into clusters. In contrast to existing clustering methods, our scheme generates multiple cluster heads in each cluster to balance the work load and facilitate dual data uploading. At the cluster head layer, the inter-cluster transmission range is carefully chosen to guarantee the connectivity among the clusters. Multiple cluster heads within a cluster cooperate with each other to perform energy-saving inter-cluster communications. Through inter-cluster transmissions, cluster head information is forwarded to SenCar for its moving trajectory planning. At the mobile collector layer, SenCar is equipped with two antennas, which enables two cluster heads to simultaneously upload data to SenCar in each time by utilizing multi-user multiple-input and multiple-output (MU-MIMO) technique. The trajectory planning for SenCar is optimized to fully utilize dual data uploading capability by properly selecting polling points in each cluster. By visiting each selected polling point, SenCar can efficiently gather data from cluster heads and transport the data to the static data sink. Extensive simulations are conducted to evaluate the effectiveness of the proposed LBC-DDU scheme. The results show that when each cluster has at most two cluster heads, LBC-DDU achieves over 50 percent energy saving per node and 60 percent energy saving on cluster heads comparing with data collection through multi-hop relay to the static data sink, and 20 percent shorter data collection time compared to traditional mobile data gathering.

Multihead Node Selection Technique for Improving Lifetime and Energy Efficiency of WSN

In this paper, a three-layer framework is proposed for mobile data collection in wireless sensor networks, which includes the sensor layer, cluster head layer, and mobile collector (called SenCar) layer. The framework employs distributed load balanced clustering and dual data uploading, which is referred to as LBC-DDU. The objective is to achieve good scalability, long network lifetime and low data collection latency. At the sensor layer, a distributed load balanced clustering (LBC) algorithm is proposed for sensors to self-organize themselves into clusters. In contrast to existing clustering methods, our scheme generates multiple cluster heads in each cluster to balance the work load and facilitate dual data uploading. At the cluster head layer, the inter-cluster transmission range is carefully chosen to guarantee the connectivity among the clusters. Multiple cluster heads within a cluster cooperate with each other to perform energy-saving inter-cluster communications. Through inter-cluster transmissions, cluster head information is forwarded to SenCar for its moving trajectory planning. At the mobile collector layer, SenCar is equipped with two antennas, which enables two cluster heads to simultaneously upload data to SenCar in each time by utilizing multi-user multiple-input and multiple-output (MU-MIMO) technique. The results show that when each cluster has at most two cluster heads, LBC-DDU achieves over 50 percent energy saving per node and 60 percent energy saving on cluster heads comparing with data collection through multi-hop relay to the static data sink, and 20 percent shorter data collection time compared to traditional mobile data gathering. This system provides much better efficiency as compared to SISO system

Data Aggregation Based Proactive Data Reporting Protocol for Wireless Sensor Network

Wireless sensor networks are the grouping of tiny sensor nodes that gathers the information by sensing activeness from the surroundings similar lands, forests, hills, sea. Power saving is a critical issue in wireless sensor networks since sensor nodes are battery-powered. To achieve optimized network performance at collecting a small portion of sensed data in network is in current researches. There are many protocols available for the successful communication. Sink trail and sink trail-s are the two energy efficient proactive data reporting protocols for mobile sink based on data collection with low complexity and reduced control overhead. In wireless sensor networks, using mobile sinks mobility rather than static sink for data collection is the new trend. Recently the researches are giving the concentration on moving patterns of the mobile sink to achieve optimized network performance, collecting a small area of sensed data in the network and also reducing energy consumption is main motto of the recent searches. Sink trail and sink trail-S protocols aim to conserve energy by turning off unnecessary sensors while simultaneously preserving a constant level of routing fidelity. In the proposed system we proposed the system that provides solution over mobility problems in wireless sensor network with energy saving methodology using aggregation technique. DOI: 10.17762/ijritcc2321-8169.150616

Improving Performance of Cross-Domain Firewalls in Multi-Firewall System

Firewall is used to protect local network from outside untrusted public network or Internet. Every packet coming to and going out from network is inspected at Firewall. Local network policies are converted into rules and stored in firewall. It is used to restrict access of the external network into local network and vice versa. Packets are checked against the rules serially. Therefore increase in the number of rules decreases the firewall performance. The key thing in performance improvement is to reduce number of firewall rules. Optimization helps to reduce number of rules by removing anomalies and redundancies in the rule list. It is observed that only reducing number of rules is not sufficient as the major time is consumed in rule verification. Therefore to reduce time of rule checking fast verification method is used. Prior work focuses on either Intrafirewall optimization or Interfirewall optimization within single administrative domain. In cross-domain firewall optimization key thing is to keep rules secure from others as they contain confidential information which can be exploited by attackers. The proposed system implements cross-domain firewall rule optimization. For optimization multi-firewall environment is considered. Then optimized rule set is converted to Binary Tree Firewall (BTF) so as to reduce packet checking time and improve firewall performance further. DOI: 10.17762/ijritcc2321-8169.16047

A Review of Cluster Heads Selection in WSN

In recent years there has been a growing interest in Wireless Sensor Networks (WSN). Recent advancements in the field of sensing, computing and communications have attracted research efforts and huge investments from various quarters in the field of WSN. Also sensing networks will reveal previously unobserved phenomena. Network’s lifetime depends on energy efficiency and load balancing of wireless sensor network. The main aim of clustering is to provide the scalability and reduce energy consumption. Cluster head consume more energy as compare to non cluster head nodes. Proper selection of cluster head increases the network lifetime and energy efficiency. This paper provides an overview of clustering, cluster head election mechanisms and LEACH protocol

Smart Android Application for blind people based on object Detection

Abstract: We are detecting an object using the mobile camera and giving voice instructions about the direction of an object. User must have to train the system first regarding the object information. We are then doing feature extraction to search for objects in the camera view. We are taking help of angle where object is placed to give direction about the object. An Android application that warns the smartphone user from obstacles way. The camera of the phone is enough and no special hardware, ensuring that it requires minimal effort from the user to use the application during everyday life

A Survey on Sentiment Mining

In past days before putting money into any product people used to ask judgment to their family, friend circle and colleagues and then they take the decision. In today’s world there is a boom of World Wide Web, enormous amount of data is available on internet so while purchasing a product instead of asking to people customer take decisions by analyzing electronic text. As the growth of e-commerce crowds of people encouraged to write their opinion about numerous merchandise in the form of statements/comments on countless sites like facebook,flipkart,snapdeal,amazon,bloggres,twiter,etc.This comments are the sentiments about the services expressed by users and they are categorized into positive, negative and neutral. Different techniques are use for summarizing reviews like Information Retrieval, Text Mining Text Classification, Data Mining, and Text Summarizing. Countless people write their sentiments on plenty of sites. These comments are written in random order so it may cause trouble in usefulness of the information. If someone wants to find out the impact of the usability of any product then he has to manually read all the sentiments and then classify it, which is practically burdensome task. Sentiment mining is playing major role in data mining; it is also referred as sentiment analysis. This field helps to analyze and classify the opinion of users. In this paper we will discuss various techniques, applications and challenges face by the sentiment mining

Generating Private Recommendation System Using Multiple Homomorphic Encryption Scheme

The recommender system is important tool in online application to generate the recommendation services. Recommendations are generated by collecting the data from users need; online services access the user’s profiles for generating useful recommendations. Privacy sensitive data is used for to collect the data. Collaborative filtering technique gives privacy for sensitive data if data is misused by other service providers or leaked. Existing system uses Paillier encryption algorithm & DGK algorithm to secure user data from malicious third party as well as to protect the private data against service provider but system is more complex and inefficient. Proposed system protects the privacy of user using encrypting the sensitive data. The system uses multiple homomorphic algorithms to secure user data from service providers. The system is used to protect the confidential data of user against the service provider while providing online services. Encrypting private data is recommended and process on data to generate recommendations. To construct efficient system that does not require the active participation of the user. The experiment shows that the result that provide the security by hiding the personal data of user from third party DOI: 10.17762/ijritcc2321-8169.15076

A Study on Advanced Cross Site Request Forgery Attacks and its Prevention

Cross Site Request Forgery (CSRF) is considered as one of the top vulnerability in today’s network where an untrusted website can force the client browser to send the unauthorized valid appeal to the trusted site. Cross Site Request Forgery will let the trustworthiness of the authentic customer.So far, numerous arrangements have been proposed for the CSRF assaults, for example, the referrer HTTP header, custom HTTP header, origin header, customer site intermediary, browser module and random token affirmation. In any case, existing arrangements isn't so insusceptible as to maintain a strategic distance from this assault. Each one of the arrangements is mostly ensured as it were. This study centers around portraying the execution of various conceivable cross site demand imitation strategies and depicting the entanglements in the assortment of preventive systems of cross site demand falsification thus we proposed some barrier instrument to avoid this defenselessness