Denoising is one of the important aspects in image processing applications. Denoising is the process of eliminating the noise from the noisy image. In most cases, noise accumulates at the edges. So... Show More

Denoising is one of the important aspects in image processing applications. Denoising is the process of eliminating the noise from the noisy image. In most cases, noise accumulates at the edges. So that prevention of noise at edges is one of the most prominent problem. There are numerous edge preserving approaches available to reduce the noise at edges in that Gaussian filter, bilateral filter and non-local means filtering are the popular approaches but in these approaches denoised image suffer from blurring. To overcome these problems, in this article a Gaussian/bilateral filtering (G/BF) with a wavelet thresholding approach is proposed for better image denoising. The performance of the proposed work is compared with some edge-preserving filter algorithms such as a bilateral filter and the Non-Local Means Filter, in terms that objectively assess quality. From the simulation results, it is found that the performance of proposed method is superior to the bilateral filter and the Non-Local Means Filter.

As the wireless sensor networks (WSN) are gaining popularity the need of reliable delivery of data packets becomes more important. The reliable delivery is only possible when the routing protocols... Show More

As the wireless sensor networks (WSN) are gaining popularity the need of reliable delivery of data packets becomes more important. The reliable delivery is only possible when the routing protocols are efficient and secure. Because of lack of resources it is not possible to use existing cryptosystems to provide security in WSN. But, trust aware routing can provide the security with lesser resources, which become popular in last three to four years. In this paper, a new energy efficient and trust aware reliable opportunistic routing (TAEROR) protocol is proposed. The protocol consists of a trust metric and also a relay selection algorithm. The trust aware metric detects the malicious nodes on the basis of forwarding sincerity, energy consumption and acknowledgement sincerity. Relay selection algorithms avoid these malicious nodes to get selected in the routing process. The protocol is simulated and compared to existing trust aware routing protocols. Proposed protocol TEAROR presents better results than the other compared protocols.

Texture classification is an important issue in digital image processing and the Local Binary pattern (LBP) is a very powerful method used for analysing textures. LBP has gained significant... Show More

Texture classification is an important issue in digital image processing and the Local Binary pattern (LBP) is a very powerful method used for analysing textures. LBP has gained significant popularity in texture analysis world. However, LBP method is very sensitive to noise and unable to capture the macrostructure information of the image. To address its limitation, some variants of LBP have been defined. In this chapter, the texture classification performance of LBP has been compared with the five latest high-performance LBP variants, like Centre symmetric Local Binary Pattern (CS-LBP), Orthogonal Combination of Local Binary Patterns (OC LBP), Rotation Invariant Local Binary Pattern (RLBP), Dominant Rotated Local Binary Pattern (DRLBP) and Median rotated extended local binary pattern (MRELBP). This was by using the standard images Outex_TC_0010 dataset. From the experimental results it is concluded that DRLBP and MRELBP are the best methods for texture classification.

The network performance of an adaptive router largely depends on well designed selection strategy. The selection function selects one of the accepted output directions returned by the routing... Show More

The network performance of an adaptive router largely depends on well designed selection strategy. The selection function selects one of the accepted output directions returned by the routing function. The effectiveness of any selection strategy relies on its congestion free traffic distribution mechanism for each incoming packet. This article proposes a fuzzy based output selection strategy that considers the congestion information from both neighboring routers as well as routers on global path. The strategy efficiently balances the traffic load by using the knowledge base of fuzzy controllers. Performance evaluation is carried out using a cycle accurate simulator under synthetic traffic conditions. The experimental results show that the fuzzy based selection strategy improves the performance by increased throughput and reduced packet latency when compared with other traditional selection strategies.

Genetic Algorithms (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Artificial Bee Colonies (ABC) are some vital nature inspired computing (NIC) techniques. These... Show More

Genetic Algorithms (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Artificial Bee Colonies (ABC) are some vital nature inspired computing (NIC) techniques. These approaches have been used in early prophecy of various diseases. This article analyzes the efficacy of various NIC techniques in diagnosing diverse critical human disorders. It is observed that GA, ACO, PSO and ABC have been successfully used in early diagnosis of different diseases. As compared to ACO, PSO and ABC algorithms, GA has been extensively used in diagnosis of ecology, cardiology and endocrinologist. In addition, from the last six years of research, it has been observed that the accuracy accomplished using GA, ACO, PSO and ABC in the early diagnosis of cancer, diabetes and cardio problems lies between 73.5%-99.7%, 70%-99.2%, 80%-98% and 76.4% to 99.98% respectively. Furthermore, ACO, PSO and ABC are found to be best suited in diagnosing lung, prostate and breast cancer respectively. Moreover, the hybrid use of NIC techniques produces better results as compared to their individual use.

This article describes how e-commerce has become so vast that almost every product and service can be purchased online, to be delivered at our doorsteps. This has led to a striking increase in the... Show More

This article describes how e-commerce has become so vast that almost every product and service can be purchased online, to be delivered at our doorsteps. This has led to a striking increase in the number of online customers. In an attempt to make the online shopping more appealing and transparent to the online customers, the e-retailers allow their customers to express their opinion about the purchased products and services. Recently, analysis of such online reviews has become an active topic of research. This is because it is of immense concern to various stakeholders vs. online merchants, potential customers and the manufacturers of the particular product or service providers. The present article addresses the problem of summarization of such opinions expressed online and aims to create an organized feature-based summary as a solution. The proposed system depends on the frequency of occurrences of the potential features. A number of pruning methods are applied in order to obtain the final feature set and sentiment analysis has been done for each such feature.

This article describes how swarm intelligence (SI) and bio-inspired techniques shape in-vogue topics in the advancements of the latest algorithms. These algorithms can work on the basis of SI, using... Show More

This article describes how swarm intelligence (SI) and bio-inspired techniques shape in-vogue topics in the advancements of the latest algorithms. These algorithms can work on the basis of SI, using physical, chemical and biological frameworks. The authors can name these algorithms as SI-based, inspired by biology, physics and chemistry as per the basic concept behind the particular algorithm. A couple of calculations have ended up being exceptionally effective and consequently have turned out to be the mainstream devices for taking care of real-world issues. In this article, the reason for this survey is to show a moderately complete list of the considerable number of algorithms in order to boost research in these algorithms. This article discusses Ant Colony Optimization (ACO), the Cuckoo Search, the Firefly Algorithm, Particle Swarm Optimization and Genetic Algorithms in detail. For ACO a real-time problem, known as Travelling Salesman Problem, is considered while for other algorithms a min-sphere problem is considered, which is well known for comparison of swarm techniques.

This article describes how the current internet is a network of interconnected autonomous systems which is susceptible to route instability when transferring data. The BGP confederation is the... Show More

This article describes how the current internet is a network of interconnected autonomous systems which is susceptible to route instability when transferring data. The BGP confederation is the essential intra-domain routing protocol that may cause instability on the Internet. So far, route instability has been widely studied for internal BGP. However, the existing routing policies such as APMS and H-SSPP are not adequate for the route stability of BGP confederations. In fact, these routing policies may degrade the network performance parameters in terms of the packet delivery ratio, convergence time, average throughput and the average end to end delay. Therefore, this article proposes the Flexible BGP Confederation Policy Management (FBCPM) to reduce the anomalies. The proposed approach detects the route instability in the networks and provides a policy to construct a stable network. The routing policy shrinks the route oscillations and forwarding loops. Furthermore, the simulation results confirm that the authors' proposed approach has improved network performance parameters compared to other existing approaches.