REBEE- Reusability Based Effort Estimation Technique using Dynamic Neural Network

Software Effort Estimation has been researched for over 25 years but until today no real effective model could be designed that could efficiently gauge the effort required for heterogeneous project data. Reusability factors of software development have been used to design a new effort estimation model called REBEE. This encompasses the usage of Fuzzy Logic and Dynamic Neural Networks. The experimental evaluation of the model depicts efficient effort estimation over varied project types

Wireless measurement Scheme for bandwidth Estimation in Multihop Wireless Adhoc network

The necessity to bear real time and multimedia application for users of Mobile 1D468;1D485;1D489;1D490;1D484; Network (1D474;1D468;1D475;1D46C;1D47B;) is becoming vital. Mobile 1D468;1D485;1D489;1D490;1D484; network facilitates decentralized network that can present multimedia users with mobility that they have demanded, if proficient 1D478;1D490;1D47A; multicast strategies were developed. By giving the guarantee of 1D478;1D490;1D47A; in 1D468;1D485;1D489;1D490;1D484; network, the proficient bandwidth estimation method plays a very important role. The research paper represented here presents a splendid method for estimating or measuring Bandwidth in 1D468;1D485;1D489;1D490;1D484; network whose character is decentralized in nature. Contrasting in the centralized formation, the bandwidth estimating in 1D468;1D485;1D489;1D490;1D484; is significant and this eventually makes an influence over the 1D478;1D490;1D47A; of the network communication. The admission control and dynamic bandwidth management method which is presented here, facilitates it with fairness and rate guarantees despite the distributed link layer fair scheduling being absent. Alteration has been made over 1D474;1D468;1D46A; layer and this method is appropriate where the peer-to-peer (1D477;1D7D0;1D477;) multimedia transmissions rates are amended in compliantly fashion.In the research work presented here the architecture of the 1D474;1D468;1D46A; layer has been altered and the data handling capacity has been increased. This technique is adopted to facilitate higher data rate transmission and eliminate congestion over the considerednetwork. The proposed technique implements the splitting of 1D474;1D468;1D46A; into two sub layer where one will be responsible for control data transmission while other effectively transmits the data bits. Thus it results into higher data rate transmission with better accuracy and optimized network throughput. The research work in the presented paper exhibits superior accuracy and is very much effective in bandwidth estimation and management application in multi hop Mobile Ad-H

Crowd Behavior Analysis and Classification using Graph Theoretic Approach

Surveillance systems are commonly used for security and monitoring. The need to automate these systems is well understood. To address this issue we introduce the Graph theoretic approach based Crowd Behavior Analysis and Classification System (GCBACS). The crowd behavior is observed based on the motion trajectories of the personnel in the crowd. Optical flow methods are used to obtain the streak lines and path lines of the crowd personnel trajectories. The streak flow is constructed based on the path and streak lines. The personnel and their respective potential vectors obtained from the streak flows are used to represent each frame as a graph. The frames of the surveillance videos are analyzed using graph theoretic approaches. The cumulative variation in all the frames is computed and a threshold based mechanism is used for classification and activity recognition. The experimental results discussed in the paper prove the efficiency and robustness of the proposed GCBACS for crowd behavior analysis and classification

Computer Aided Multi-Parameter Extraction System to Aid Early Detection of Skin Cancer Melanoma

Melanoma is the most widely occurring and life threatening form of skin cancer. Early detection of in situ melanoma has challenged researchers for many decades now. Currently there exists no computer aided mechanisms to accurately detect early melanoma. T he currently existing computer aided diagnostics mechanisms are capable of melanoma classification and are unable to detect in situ melanoma. This paper introduces a Multi Parameter Extraction and Classification System ( 푀푀푀푀푀 ) to aid early detection o f skin cancer melanoma. The 푀푀푀푀푀 defines the skin lesion images in terms of characteristic parameters which are further used for classification. In this paper the extraction of 21 parameters is achieved using a six phase approach. The parameters extr acted are analyzed using statistical methods. It is clear from the results obtained that no single parameter can affirm the detection of in situ melanoma, hence an advanced analysis mechanisms considering all the parameters need to be adopted to effective ly detect melanoma in its initial stages