International Journal on Future Revolution in Computer Science & Communication Engineering
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Brain Tumor Segmentation of MRI Image using Gustaffson-Kessel (G-K) Fuzzy Clustering Algorithm
Get PDFImage segmentation plays a major role and an important role in the medical field due to its variety of applications especially in Brain tumor analysis. Brain tumor is an abnormal and uncontrolled growth of cells. It takes up space within the skull. It can compress, shift and harm healthy brain tissue and nerves. Also usually it obstruct with normal brain function. Tumors can be benign (non-cancerous) or malignant (cancerous), can happen in different parts of the brain. Brain tumor classification and identification from Magnetic Resonance (MR) data is an essential. But it takes time and manual task completed by medical specialists. Computerizing this task is a challenging because of the high variety in the look of tumor tissues among different patients and in many cases similarity with the normal tissues. In this work, brain tumor image has been segmented using proposed Gustafson-Kessel (G-K) fuzzy clustering algorithm. The performance of G-K segmentation method is compared with those of watershed and FCM algorithms
A Survey on Classification of Geolocation of Country from Worldwide Tweets
Get PDFSocial media are progressively being utilized as a part of mainstream researchers as a key wellspring of information to help comprehend differing common and social term, and this has prompted the advancement of an extensive variety of computational information mining apparatuses that can remove learning from web-based social networking for both ad-hoc and ongoing examination. The expansion of enthusiasm for utilizing web-based social networking as a hotspot for look into has roused handling the test of consequently geolocating tweets, given the absence of express area data in the lion's share of tweets. As opposed to much past work that has concentrated on area grouping of tweets limited to a particular nation, here we attempt the assignment in a more extensive setting by ordering worldwide tweets at the country level, which is so far unexplored in an ongoing situation. We break down the degree to which a tweet's nation of starting point can be dictated by making utilization of eight tweet-inherent highlights for classification
Energy Aware Ant Colony Optimization (ENAANT) to Enhance Throughput in Mobile Ad hoc Networks
Get PDFMobile Ad hoc Network (MANET) is a network of mobile nodes having communication without a predefined infrastructure. The applications of MANETs are increasing from home appliances to defense communications. As the mobile nodes are operated by the batteries, all the processes which are taking place in the node should aware of the consumed energy. Maintaining the link stability is one of the challenges and it is one of the factors to ensure the high throughput in the networks. Due to the limited energy, the links of the networks often goes off which affects the throughput of MANETs. Energy aware ACO is proposed to optimize the utilization of energy that is available in the mobile nodes to increase throughput by ensuring link stability. Based on the remaining energy and the amount of packets to be sent, the nodes are selected for routing. The simulation is done through Network Simulator 2 and the results show that the proposed research work performs well in increasing the throughput
Hybrid Parameter Optimization Approach with Adaptive Neuro Fuzzy Inference System for the Software Maintainability
Get PDFThis paper presents a novel method to measure the maintainability of the software from the design artifact. It is an inevitable measure because it aims to attain software with a better quality. The system is designed to measure the maintainability of the system from the UML class metric. This is extracted from the UML class diagram to predict the maintainability of the class diagram. The system is implemented using CFS from the Weka tool to select an optimized variable from a set of variables i.e UML class metric. Hybrid ANFIS is an artificial intelligence technique which has been incorporated with the optimizing algorithms to reduce the overall number of UML metric and build a Fuzzy Inference System (FIS) based on the learning process. The optimization attains an enhanced result since it is done continually by both using feature selection and optimization algorithms repetitively, which results in reducing the UML metric considerably to measure the maintainability of the software. The proposed research work is evaluated in terms of the performance measures, MSE, RMSE, true positive rates and the result is clearly shown that a better optimization of the maintainability measure estimation process can be done
Encouraging and Utilizing Linked Data from Open Online Courses
Get PDFAccess to affordable education to achieve printed and digital literacy helping all learners to acquire knowledge, coping with change, and seeding mindsets for creativity and intellectual curiosity are considered major indicators and measures of quality of life worldwide. The emergence of MOOCs (Massive Open Online Courses) promising new, scalable models that can provide an �education for everyone� has generated a new and broad interest in rethinking learning and education. Frames of reference (identifying underlying assumptions, conceptualizations, and perspectives) are needed to conceptualize the meaning and the implications of MOOCs in the context of rich landscapes for learning. Most of the discussions and analyses about MOOCS have been based on economic perspectives and technological perspectives. This contribution critically assesses MOOCs from a learning sciences perspectives. This paper focuses on integrating all the trending websites which includes Coursera ,Udacity and Swayam and searches for the best optimal course that the user requires. Information is retrieved using web crawler with the help of ontology schema
Study on Segmentation and Global Motion Estimation in Object Tracking Based on Compressed Domain
Get PDFObject tracking is an interesting and needed procedure for many real time applications. But it is a challenging one, because of the presence of challenging sequences with abrupt motion occlusion, cluttered background and also the camera shake. In many video processing systems, the presence of moving objects limits the accuracy of Global Motion Estimation (GME). On the other hand, the inaccuracy of global motion parameter estimates affects the performance of motion segmentation. In the proposed method, we introduce a procedure for simultaneous object segmentation and GME from block-based motion vector (MV) field, motion vector is refined firstly by spatial and temporal correlation of motion and initial segmentation is produced by using the motion vector difference after global motion estimation
Different Approach to Secure Data with Fog Computing
Get PDFFog computing could be a paradigm that extends cloud computing that has become a reality that made-up the method for brand new model of computing. additionally, fog provides application services to finish terminal within the age of network. The inner information stealing attacks in that a user of a system illegitimately poses because the identity of associate other legitimate user which is an arising new challenge to the service supplier wherever cloud service supplier might not be able to defend the information. therefore, to secure the important user�s sensitive data type the offender within the cloud. In this research paper I am proposing a very distinct approach with the assistance of offensive decoy data technology, that is employed for confirming whether or not the data access is permitted wherever abnormal information is detected andthereby confusing the offender with the fake data
Implementation of Multicast Routing Protocol on MANET
Get PDFUnderwater wireless sensor networks (UWSNs) have been showed as a promising technology to monitor and explore the oceans in lieu of traditional undersea wireline instruments. Nevertheless, the data gathering of UWSNs is still severely limited because of the acoustic channel communication characteristics. One way to improve the data collection in UWSNs is through the design of routing protocols considering the unique characteristics of the underwater acoustic communication and the highly dynamic network topology. In this paper, we propose the GEDAR routing protocol for UWSNs. GEDAR is an anycast, geographic and opportunistic routing protocol that routes data packets from sensor nodes to multiple sonobuoys (sinks) at the sea�s surface. When the node is in a communication void region, GEDAR switches to the recovery mode procedure which is based on topology control through the depth adjustment of the void nodes, instead of the traditional approaches using control messages to discover and maintain routing paths along void region
Electronic Eye
Get PDFElectronic Eye is a security system that is based on IoT(Internet of Things). It uses sensors to detect the motion and generates an alert call for the owner of the safes or lockers as well as turns on the buzzer indicating theft