Wireless Sensor Networks (WSN) since their inception, a decade ago, have grown well in research and implementation. In this work the developments in WSNs are reported in three sub areas of wireless sensor networks that is, wireless sensor node (hardware and software), Communication & Networking issues in WSNs and application areas. WSNs are characterized by huge data hence research work in aggregation & mining is also discussed. Contemporary issues of integration of WSNs with other prevalent networks, sensor enabled smartness and role of artificial intelligence methods is elaborated. Insight into future directions & research avenues in all the above areas is provided.

Most of the software projects fail to meet the desired level of quality and standards due to different types of defects introduced during the course of requirement solicitation, designing and development. These defects inexorably hinder the secure deployment or smooth operations of the software systems. One of the key reasons for this misfortune is the lack of proper defect prevention planning while formulating the software architecture. Defect prevention needs to be a thorough and critical phase because it has a direct impact on quality of the product which cannot be compromised. This paper looks into different defect prevention techniques and analyses them critically. The scope of this study is restricted to the identification of the modern trends in defect prevention.

It is shown an incorrectness of introduction of a class of NP-complete problems, which reason is that Cook’s S.А. theorem on that the “satisfiability” problem is the universal NP-complete problem, is not true and, therefore, the issue on existence of at least one NP-complete problem remains open, that explains failures of attempts to estimate correlations between P and NP classes.

Question answering (QA) is the task of automatically answering a question posed in natural language. At this time, there exists several QA approaches, and, according to recent evaluation results, most of them are complementary. Some of them use the evolutionary algorithms, such as the genetic algorithm, in itself. In this paper we propose a question answering system that uses the artificial immune algorithms, for searching in the knowledge base to find the right answer. This algorithm is one of the evolutionary algorithms. Search is based on two features: (i) the compatibility between question and answer types, (ii) the overlap and non-overlap information between the question-answer pair. Experimental results are encouraging; they indicate significant increases in the accuracy of proposed system, in comparison with the previous systems.

Distance education can be very effective use of instructional materials with visual, auditory, audiovisual and multimedia content. Visual content can be in the form of text, drawings, pictures, graphics and models, and the like. Auditory facilities are oral presentation or a speech, musical accompaniment, different sounds, etc.. Audiovisual content combine visual and auditory content, usually in the form of television shows, films or videos. Multimedia, combining text, images, sound, animation and video, and playing them before they used very different means, although in recent times for playing multimedia files commonly used multimedia computer, a data storage CD-ROM or the Internet. Using multimedia is extremely important in distance education as a lecturer is usually not physically present with the participants to draw their attention, motivate them to learn and explain the content that students are having difficulty understanding.

Fast and energy efficient data collection in an energy constraint ad-hoc sensor network is always a challenging issue. The network topology and interferences causes significant effects on data collection and hence on sensors’ energy usage. Various approaches using single channel, multichannel and convergecasting had already been proposed. Here in this paper we have shown data collection performance using multi-frequency in channel assignment, and effect of network topology, for moderate size networks of about 50-100 nodes. For the study we have used some realistic simulation models under many-to-one communication paradigm called convergecast, a single frequency channel and TDMA technique to have minimum time slots for convergecasting.

We have implemented a robust image watermarking technique for the copyright protection based on 3-level discrete wavelet transform (DWT). In this technique a multi-bit watermark is embedded into the low frequency sub-band of a cover image by using alpha blending technique. The insertion and extraction of the watermark in the grayscale cover image is found to be simpler than other transform techniques. The proposed method is compared with the 1-level and 2-level DWT based image watermarking methods by using statistical parameters such as peak-signal-to-noise-ratio (PSNR) and mean square error (MSE). The experimental results demonstrate that the watermarks generated with the proposed algorithm are invisible and the quality of watermarked image and the recovered image are improved.

Mammography is the most effective procedure for the early detection of breast diseases. Mammogram analysis refers the processing of mammograms with the goal of finding abnormality presented in the mammogram. In this paper, the tumour can be detected by using wavelet based adaptive windowing technique. Coarse segmentation is the first step which can be done by using wavelet based histogram thresholding where, the thereshold value is chosen by performing 1-D wavelet based analysis of PDFs of wavelet transformed images at different channels. Fine segmentation can be done by partitioning the image into fixed number of large and small windows. By calculating the mean, maximum and minimum pixel values for the windows a threshold value has been obtained. Depending upon the threshold values the suspicious areas have been segmented. Intensity adjustment is applied as a preprocessing step to improve the quality of an image before applying the proposed technique. The algorithm is validated with mammograms in Mammographic Image Analysis Society Mini Mammographic database which shows that the proposed technique is capable of detecting lesions of very different sizes.