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A web service is an entrance to certain application functionality realized with common internet technologies. Users of services do not need to be aware of the details of service implementation. The number of services on the internet as well as in the enterprise is growing., which introduces new challenges in searching for and finding needed web services. There are various web service discovery methods utilized. There are syntax-based ones among them, and others are syntax-independent methods. Literature work sheds light on the work already carried out on published Web Service Discovery associated with medical field. Conversely, it outlines the approach and the adopted methods of newly developed Web Service Discovery techniques.

In today's world maintaining users or customers data by giant industries like telecom and insurance is a very cumbersome task and moreover, allowing some different domain to access this data is even a hard task than the prior one. Integrating these data on common platform so that it can be shared by the different data requesters and provider is a quite an appreciation task. However, maintaining and integrating quality customer data is one of the greatest challenges it executives face-and this challenge only gets more daunting as businesses both grow and become more complex. Economic slowdown has fueled customer data integration of different enterprises under a single roof. The model is inspired by the empirical study on a trace from a large-scale production data-processing cluster at the Web server end; it allows a set of effective query optimizations that are not possible in a traditional integration model. And also selective encryption model to preserve the privacy of the customer data makes the system more effective and enriched.

Distributed denials of Service attacks (DDoS) have become one of the major threat on the internet. Most defence methods are focused on detecting DDoS attack on IP & TCP layer instead of application layer. With profiling of web browsing behaviour, the sequence order of web page request can be used for detecting Application layer DDoS (App_DDoS) attacks. Based on Hidden semi-Markov model (HsMM) ,a novel anomaly detector is used to describe the browsing behaviour of web users. Average Information entropy (AIE) of user's HTTP request sequence used as a criterion to measure the user's normality. K-means algorithm derived for on line implementation of the model based on M-algorithm. The proposed method is experimentally confirmed with various types of new App-DDoS attack .Our experiment shows the detector and the filter that are based on the behavior model. The filter, residing between the Internet and the victim, takes in a HTTP request and decides whether to accept or reject (drop) it. If a request is accepted, it can pass through the filter and reach the victim. [PUBLICATION ABSTRACT]

Some of the hardest to mitigate distributed denial of service attacks (DDoS) are ones targeting the application layer. Over the time, researchers proposed many solutions to prevent denial of service attacks (DDoS) from IP and TCP layers instead of the application layer. New application Layer based DDoS attacks utilizing legitimate HTTP requests to overwhelm victim resources are more undetectable. This may be more serious when such attacks mimic or occur during the flash crowd event of the website. This paper present a new application layer anomaly detection and filtering based on Web user browsing behavior for create defense against Distributed Denial of Service Attack(DDoS). Based on hyperlink characteristics such as request sequences of web pages. This paper, uses a large scale Hidden Semi Markov Model (HsMM) to describe the web access behavior and online implementation of model based observation sequence on user browsing behavior fitting to the model measure of user's normality.

Today in Modern Society Face Recognition has gained much attention in the field of network multimedia access. After the 9/11 tragedy in India, the need for technologies for identification, detection and recognition of suspects has increased. One of the most common biometric recognition techniques is face recognition since face is the convenient way used by the people to identify each other. In this paper we are going to study a method for representing face which is based on the features which uses geometric relationship among the facial features like mouth, nose and eyes .Feature based face representation is done by independently matching templates of three facial regions i.e eyes, mouth and nose .Principal Component Analysis method which is also called Eigen faces is appearance based technique used widely for the dimensionality reduction and recorded a greater performance in face recognition. Here we are going to study about PCA followed by Feed Forward Neural Network called PCA-NN. [PUBLICATION ABSTRACT]

Databases have become ubiquitous. Almost all IT applications are storing into and retrieving information from databases. Retrieving information from the database requires knowledge of technical languages such as Structured Query Language (SQL). However majority of the users who interact with the databases do not have a technical background and are intimidated by the idea of using languages such as SQL. This has led to the development of a few Natural Language Database Interfaces (NLDBIs). A NLDBI allows the user to query the database in a natural language. This paper highlights on architecture of new NLDBI system using Probabilistic Context Free Grammar (PCFG), its implementation and discusses on results obtained. In most of the typical NLDBI systems the natural language statement is converted into an internal representation based on the syntactic and semantic knowledge of the natural language. This representation is then converted into queries using a representation converter. A natural language query is translated to an equivalent SQL query after processing through various stages. The work has been experimented on primitive database queries with certain constraints.

This paper describes the Phrase-Based Statistical Machine Translation Decoder for English to Sanskrit translation in ubiquitous environment. Our goal is to improve the translation quality by enhancing the translation table and by preprocessing the Sanskrit language text . We introduce a comprehensive framework for a ubiquitous translation and language learning environment utilizing the capabilities of modern cell phone technology. We present the architecture of our framework, our current state of implementation, and the findings we have gathered so far.

- Numerous countries have abundant resources, including land, rivers, groundwater, the environment, with agriculture serving as the primary source of income for many people in country. Nonetheless, resource shortage has grown in recent decades, particularly for groundwater and river water, so remote control smart irrigation system is developed to avoid access use and loss of water in the agriculture. A lack of information about the best use of available resources leads to increased resource consumption and worse crop yields. Choosing crops that are unsuited for the soil or climate reduces both quality and quantity of crop. As a result, system that recommends appropriate crops and fertilizers based on soil NPK values, soil colour, Season, PH, Rainfall, temperature etc has been developed. Fires are one of the most destructive global disasters, thus early detection is necessary to avoid the damages in agriculture. To reduce losses, an automated system capable of early fire detection through alarm systems and prompt extinguishing procedures through the roof structure pipeline in the farm is developed. Another use of that same pipeline is for spraying the pesticides and fertilizers. A potential resolution to address all these challenges involves the development and implementation of an intelligent agricultural system integrating Internet of Things (IOT) and Machine Learning technologies.

This research work is to create a application as web service to make it available on web for web service discovery. The most significant yoga stance is well-known on a global scale and supports the health advantages advocated by the ancient sages. OpenPose estimates that computer vision technology can help yoga practitioners achieve the greatest form and alignment. The integration of the OpenCV, Python, and MediaPipe frameworks is the main emphasis of this research project in order to develop an OpenPose estimation system for yoga poses. A camera is used to capture the yoga practitioner's motions, and a deep learning model is used to predict the important body parts. The algorithm then looks at these essential aspects to determine if the practitioner is doing the pose correctly or whether any adjustments are needed. The device gives the practitioner immediate feedback, allowing them to modify their alignment and posture as necessary. The OpenPose estimate system can help with the practice of yoga by offering detailed visualizations of the essential body parts throughout each posture in addition to providing real-time feedback Practitioners may more clearly understand the right form and alignment and make the required adjustments by utilizing this visualization. Additionally, the OpenPose estimation system enables the tracking of development over time. Practitioners who want to practice alone at home or may not have access to an instructor can also benefit from it. This paper offers a MediaPipe, OpenCV, and Python-based OpenPose estimation system for yoga positions. For optimal form and alignment, the tool may offer real-time feedback and visual representations of key body parts throughout each position. It is useful tool for yoga teachers and students, enhancing yoga's safety and efficacy while supporting the practice.

ABSTRACT Electrical current can cause neurological damage directly or by conversion to thermal energy. However, electrical injury causing isolated brachial plexus injury without cutaneous burns is extremely rare. We present a case of a 17-year-old boy who sustained accidental electrical injury to left upper extremity with no associated entry or exit wounds. Complete motor and sensory loss in upper limb were noted immediately after injury. Subsequently, the patient showed partial recovery in muscles around the shoulder and in ulnar nerve distribution at 6 months. However, there was no improvement in muscles supplied by musculocutaneous, median and radial nerves. On exploration at 6 months after trauma, injury to the infraclavicular plexus was identified. Reconstruction of musculocutaneous, median and radial nerves by means of sural nerve cable grafts was performed. The patient has shown excellent recovery in musculocutaneous nerve function with acceptable recovery of radial nerve function at 1-year post-injury.