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Automated navigation is an important feature of any mobile robot and is a challenge for a robot to plan the path in an unknown environment. We can categorize the path planning strategy of robots in two methods, first is the Classical Methods and second is Heuristic Methods. In this paper, a modified whale optimization algorithm is proposed that ensures an optimal collision-free path. In whale optimization algorithm (WOA) the fitness of any whale will be calculated by taking in consideration the target location and the obstacles in the search space. Many simulations were run in different search spaces to find the optimal path at the end of the iterations when the individual reaches the final destination (target location). The simulation and results show, the proposed modified WOA is feasible for mobile robot path selection problems.

Software cannot be release until unless it attains significant degree of confidence on quality parameters. In order to maintain the software quality, testing plays an important role. But this is a costly affair as it consumes almost 50 percent of the overall software development cost. The increasing competitiveness and ever updating technological change as well as customer requirements make regression testing a most important activity. So, regression testing is conducted before every release of the software which becomes expensive. Optimization of regression test suite is a way to reduce this higher cost. This paper proposes an efficient self adaptive butterfly optimization technique. The proposed approach is further utilized on regression test suite optimization problem to reduce the regression test suite size. Performance of proposed approach has been evaluated against Bat Search Optimization based approaches using fault detection as performance measures. Different tests are performed to analyze and validate the results. These results demonstrate the dominance of the proposed approach over the compared ones.

Video Games are the most common and popular ways of entertainment mainly amongst the younger generation of world. Due to the advent of Virtual Reality (VR) and Brain Computer Interface (BCI), the gaming experience has increased exponentially amongst the users and the use of Artificial Intelligence (AI) in video games makes it less predictive and more tough and exciting to play. With Virtual Reality now looking distinctly normal, Brain Computer Interface is all set to become the futuristic technology in the gaming horizon. The researchers discover where the technology is at present and how it could transform the way users play in the future. Through this paper, we propose a method to make the video games more exciting and challenging for the users to experience ultimate gaming by combining the trending topics in the world of computer science i.e. BCI and AI.

The demand of highly reliable and superior quality open source software's are increasing day by day. This demand force software developers to improvise the reliability of their software's. Authors have proposed several parametric and non-parametric software reliability models but they have their own limitations, like parametric model suffer from unrealistic model assumptions, operating environment condition dependencies. In contrast to parametric, non-parametric models overcome these issues but they are computationally costlier. So, the scope of optimization or development of new reliable model still exists. This paper presents an effective software reliability modeling based on Cuckoo Search optimization, Ensemble Empirical Mode Decomposition and ARIMA modeling of time series to provide more accurate prediction. Extensive experiments on 5 real datasets is conducted and results are collected. The analysis of results indicates the superiority of proposed technique over existing parametric and non-parametric models for open source software's and propriety software's.

The pine needles (PNs) and sewage sludge (SS) have a significant amount of biodegradables. Due to this they are highly susceptible to pollute the environment. Both the wastes can be managed via anaerobic digestion. However, the low ambient temperature in hilly areas can affect the digestion process. Therefore, to determine their anaerobic digestibility in a hilly terrain two digesters were examined: one with mono-anaerobic digestion of SS and another one with co-digestion of SS with PNs. It was found that co-digestion yielded 40.93% more biogas than that mono-digestion of SS. Cumulative methane yield of 158.6 mL g−1 VSadded and 268.45 mL g−1 VSadded was obtained from SS and co-digestion of SS-PNs, respectively. During the experiment, a reduction of 26.7% and 35% COD and VS for SS and 30 and 34% COD and VS for SS-PNs were reported, respectively. To study the anaerobic digestibility various mathematical models and one kinetic model were also used. This study concludes that PN and SS can be managed through anaerobic digestion however their co-digestion is highly recommended.

In an Agile workflow, work is divided into sprints and each sprint has a particular activity which needs to be completed. Agile aligns development activity with customer’s requirement. It is an iterative progress methodology, where requirements develop through association between the customer and self-organizing teams. As there is less documentation available in agile methodology, product team, development team and testing team need to work in close association to develop the quality software with minimum defect leakage. In this paper, we analyze empirically the defect life cycle for agile model to determine the correct phases of a defect in the agile workflow. Results obtained may help team to optimize the time and develop the quality software with minimum defect leakage.

Cloud computing is one of the enormously growing and challenging area in the modern era. There is a rapid technological advancement in virtualization technology to achieve most effective features of cloud services like reliability, cost-effective scalable services, availability and on-demand services. Tasks scheduling is one of the most challenging NP-hard problems in cloud systems. In past few decades, various solutions have been proposed to handle task scheduling problem, but the scope of optimization still persists. In this paper, we have proposed an improved harmony search algorithm based approach to solve task scheduling problem to minimize the total completion time measured as makespan and maximize the resource utilization of virtual machine, assuming that tasks are non-preemptive and independent. The proposed algorithm also ensures that no virtual machine is overloaded and its resources are utilized to the maximum level by minimizing makespan. An extensive experiment is designed and simulation is done on heterogeneous computing dataset available from open source. Results indicate the superiority of proposed approach over existing approaches.

When an image enters into the digital world, the probability that the image will get tempered also increases. Hence there exists a higher threat to such content (image, audio, and video) to be copied, modified and distributed. In this thesis, LTP (Local Ternary Pattern) along with DCT (Discrete Cosine Transform) have been employed. By using the DCT technique on the JPEG image we are able to provide lossy compression to the image. In this way, the image is compressed such that size of the image reduced enough for storage of content, in this case, a watermark image. Once this has been done, LTP technique is applied to it. The use of LTP will help to embed a watermark even if it is of a heavier size. The original image will be obtained with lesser impacts to it. To show the effectiveness of LTP watermarking, certain attacks like cropping, noise, and compression are applied. As a result, the extracted watermark is tempered. DCT ensures robustness by compressing the image while LTP allows watermark embedding and extraction. DWT and LBP both provide compression and watermarking respectively. But, this paper has briefly compared DCT and DWT techniques to conclude as to why DCT has been chosen. Also, this paper shows reasons as to why LTP is chosen over LBP. Index Terms-Image Compression, Image Watermarking, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT). Local Ternary Pattern (LTP), Local Binary Pattern (LBP).

This chapter reports the details of the existing system of MSW management and characterization of Muzaffarnagar City located in Western Uttar Pradesh (UP) state in India. The overall waste generated in the city is about 120-125 tons per day (TPD) with a per capita generation rate of 0.415 kg/person/day with a collection efficiency of 70-80%. Physico-chemical and geotechnical properties of the MSW were carried out to determine its overall characteristics. The characterization results showed about 46% of the waste generated in the city is organic nature (from HIG and MIG) and 52% for (LIG) with chemical characterization showing that the elemental carbon was in the highest proportion. Further, the chapter also recommends suitable remedial measures for proper management of the existing MSW management system and suitable treatment alternatives.

The proposed approach put forward an effective estimation of the parameters for software reliability growth models with the help of Krill Herd Algorithm. The Software Reliability Growth model is considered to be incomplete, if the parameters of model are not known and are not validated over failure datasets. Many techniques are present for estimating parameters of model based on numerical estimation, but the scope of quality enhancement still remain open. The proposed Krill Herd Algorithm based approach outclasses the problems of numerical estimation. The proposed work is validated over four real-time datasets.

Reliable softwares are the need of modern digital era. Failure nonlinearity makes software reliability a complicated task. Over past decades, many researchers have contributed many parametric / non parametric software reliability growth models and discussed their assumptions, applicability and predictability. It concluded that traditional parametric software reliability models have many shortcomings related to their unrealistic assumptions, environment-dependent applicability, and questionable predictability. In contrast to parametric software reliability growth models, the non-parametric software reliability growth models which use machine learning techniques or time series modeling have been proposed by researchers. This paper evaluates and compares the accuracy of 2 parametric and 2 non parametric software reliability growth models on 3 real-life data sets for software failures.

Harmony Search Algorithm is one of the best optimization algorithm known, due to its capability of escaping the local optima and divergence free behaviour. In this paper, an optimized audio watermarking technique based on harmony search algorithm is presented. The watermark is embedded using dither modulation of the host audio signal blocks. High imperceptibility is proved to be achieved by the proposed technique through subjective test. Moreover, the technique is quite robust against variety of attacks including resampling attack, low-pass filtering, requantization and cropping effect. To improve the robustness and imperceptibility, harmony search technique has been applied on user defined quantization parameter.

In this paper, LWT(Lifting Wavelet Transform) and SVD(Singular Value Decomposition) is used to design a video watermarking technique. The video is divided into different scenes, and the last frame of each scene is selected for embedding watermark. A gray scale watermark is selected for this purpose. I have used Histogram Difference Method for dividing the video into scenes. Each RGB video frame is converted into YCbCr format, and then luminance part (Y) is taken for inserting the watermark. The LWT is applied on Y component of the video frame to decompose it into four sub parts (LL, LH, HL, HH). Then SVD is applied on the LL sub part which decomposes it into U, S, and V components. Finally watermark is also decomposed using SVD to get Sw, Uw and Vw. Then S component of the cover video frame is modified using Sw component of the watermark to embed the watermark in the cover frame. Then Inverse SVD and Inverse LWT are applied to get the final watermarked video frame. The Imperceptibility and robustness of the watermarking method is checked by applying some intentional attacks on the watermarked video frame. The results of the scheme are also compared with other existing video watermarking techniques to prove that the proposed scheme works better than other existing video watermarking schemes.

The role of Post processing in real -time rendering is popular these days in 3D graphics. The photo-realistic images and the respective dynamic rendering are needed within application. Here in this paper we are discussing all the rendering pipeline, pros and cons to the post processing techniques as well as the rendering result that we can generate using these all. The effect as Fog, Motion-Blur, Ping-Pong Texturing has quite effective result over GPU (Graphical Processing Unit) these days. We will discuss the overall phenomenon to achieve these effects within different topics.

The recent development in the internet technology is definitely a boon for the society. But as far as copyright protection of multimedia content, prevention of unauthorized access, intellectual property rights etc. are concerned, this is an area that needs immediate attention. Now a days it is a relatively easy process to copy the data available on web, modify it and then put it back for individual as well as business profits. Digital Watermarking provides a viable solution by embedding information, which can be further used to prove the ownership or to detect invasion in the copyright multimedia content like text, audio, video etc. In this paper, we have proposed a new algorithm for the watermarking of digital images using cascading of two transforms i.e. Discrete cosine transform DCT and Lifting wavelet transform LWT Proposed algorithm takes the approximation component of the LWT transform of cover image and then applies DCT to embed watermark data Watermarked data is embedded in middle frequency component using comparison based correlation technique. This algorithm has also been compared with the existing ones by applying different image attacks and subsequently measuring the robustness level and proved to be fairly robust.

This paper proposes a proficient digital watermark generation technique from biometric data which will be unique and can be logically owned to prove ownership. The biometric pattern of iris is used to generate the digital watermark that has a clear stamp of ownership. The generated watermark has been studied for uniqueness and identification and has been used to watermark audio signals. Dither modulation quantization is applied on the singular values of Singular Value Decomposition domain for embedding the watermark. Experimental results indicates that the watermark can survive the signal processing attacks such as Gaussian noise corruption, re-sampling, re-quantization, cropping, and compression and maintain the perceptual properties of the host signal and hence satisfies the design requirements of digital watermarking. The extracted biometric based watermark was uniquely identified under signal processing attacks.