Springer Science and Business Media LLC

The progressive web and computerized advancements have forced endless increment in the measure of visual data accessible to users. This trend prompted the advancement of exploration area where retrieval of images is done through the content of information which became familiar as CBIR (Content based image retrieval). CBIR frameworks are to a great extent utilized as a part of medicinal picture annotation, face recognition systems, security frameworks and so on. In this paper we will discuss about an efficient system for retrieving images faster since speed and precision are important as well as techniques to obtain better classification of images. To conquer the issue of extensive number of features extracted which obliges vast measure of memory and processing force we need to build a blend of 3 techniques(SURF, SVM and LDA) which best portray the information with adequate precision. Hence, we are using dimensionality reduction algorithm LDA in combination with SVM for the classification purpose and SURF which is quick and robust interest point detector.

In recent years, there has been tremendous increase in mobile adhoc networks applications ranging from military and rescue operations to collaborative and distributed computing, therefore secure data transmission has become one of the critical issue in MANET. A mobile adhoc network is genrally established without relying on centralized and dedicated servers. Attackers exploit the loopholes of route discovery process to carry out their malicious intent as it is an inevitable process in reactive protocols. Blackhole is one such popular attack that sends forged routing information to fool source node and drops all the data packets after introducing itself in the route between source node to destination. In this paper, damage caused to AODV in presence of blackhole node has been evaluated and solution to defend against blackhole attack has been proposed and simulated on Ns-2 to prove its efficiency and reliability. The packet processing technique of normal AODV is enhanced to detect routing misbehavior and alert other nodes using default AODV control message, HELLO messages to reduce additional overhead.

Using the program visible digital, a perceptible watermark is added to an image to prevent illicit use of multimedia content and to provide copyright and copy protection for the author. There are numerous applications that require user authentication to make the original image content available. If the original image is recovered from the watermarked image successfully, then the scheme is said to be a reversible watermarking scheme. However, most of the reversible visible watermarking schemes found in the current literature do not preserve visual quality of image. In this investigation, we propose a novel reversible and visible watermarking method that is suitable for both grey and colour images. In our approach, we use the complex mapping of pixels via embedding combined with a scaling factor derived from the contrast-sensitive function of the original image. We then prove experimentally that our scheme is advantageous over the previous works in this field. Furthermore, we compare the performance of proposed work with other state-of-the-art under various parameters.

In automatic speech recognition systems, the information in the speech signal is traditionally retrieved in the form of feature vectors representing sub-word units and thereby converting the features into human readable text form. However, these systems perform poorly due to degradations of speech under varying environmental conditions. To improve the performance, the main issues to be considered are: (a) Determination of speech regions in the speech data collected in degraded environments, and (b) Recognition of speech sounds from the degraded speech in the detected speech regions. Although there exist wide variety of techniques which address these issues, most of them are applicable for clean speech synthetically degraded by stationary noise conditions, due to the need for large amount of training data for statistical modeling. The present work focuses on methods of processing the signals so as to determine the desired speech regions in degraded conditions. For this, signal processing methods are being explored to extract speech-specific characteristics independent of the characteristics of degradations.

The metro rail links many parts of a large city and offers one of the best modes of transit across it. However, the construction phase of the metro causes inconveniences to the people living in cities by significantly escalating the noise and dust pollution. During the construction of metro rails, citizens face problems in their everyday lives, especially as the elevated corridors go through thick-populated areas and high-vehicle traffic areas, creating traffic snarls and impediments. The literature review revealed additional concerns, such as public green cover depletion, potholes, building waste disposal, and vibrational issues. With the advent of social media, urban citizens use platforms like Twitter to express their opinions on inconveniences. The interactions over these social media platforms constitute big data. This data has immense potential for public engagement, accountability, and timely resolution of public inconvenience. The examination and analysis of social media posts on these issues are important as such analysis would inform the metro rail agency about the factors that affect the public and their emotional reaction to a specific activity or series of activities performed by the construction team. In this work, Twitter posts about the inconveniences associated with metro rail projects in four cities across India were analyzed. Social network analysis (SNA), text analytics, topic modeling, and sentiment analysis were conducted to analyze the data. SNA helped find the Twitter accounts with above-average betweenness centralities, while text analytics and topic modeling helped find latent discussion topics among the stakeholders. Sentiment analysis gave an idea of the public sentiments towards the projects.

Growing digitization will establish a digital fabric all around us for anytime and anywhere access. This will revolutionize the way we communicate. Wireless networks like Ad hoc and Sensor networks, mesh networks and pico-net etc. will play a crucial role in such materialization. Internet of Things is one such revolution which derives its roots from Ad hoc and Sensor networks. A lot many issues related to privacy and security of the contents, resources and access will also appear on the horizon. Several typical characteristics of these networks like unattended operation, battery operated device, limited transmission range and storage limits the scope of full-fledged secure solutions in terms of routing and information dissemination. Through this proposal we establish a novel approach for selection of next-hop on the path from source to destination. The proposal is evaluated for performance through simulation. The results of the simulations establish the viability and effectiveness of the complete proposal.

Organic semiconductor based photodetectors would be very attractive, innovative and well suited for light detection applications. The requirement of organic semiconductor in photonic device is to low cost, light weight, mechanical flexibility, chemical modification, tunability of absorption range with co-evaporation and co-mixing of molecules and easy to integrate. In fact, organic optoelectronics devices are more eco-friendly and energy efficient. In this research work, main objective is to fabricate and characterize organic semiconductor based photo detector with a proper choice of organic semiconductor as donor and acceptor and optimize by employing diversified organic semiconductors for fast response time, high photosensitivity, high quantum efficiency, low dark current, large dynamic range and long life time. The equivalent circuit model of the proposed organic photo detector (OPD) structure has been designed and simulated using MATLAB Simulink in which Rubrene and BPPC are used as active layer of OPD. 500 MHz of Operating frequency is to be found in this proposed OPD that is much higher than the speed of the red light illumined Bi-layer OPDs reported till today.