Human face detection and recognition play important roles in many applications such as biometric authentication, video face recognition at some public area and security check point, digital image archiving, etc. In this paper, we have developed an algorithm that can detect human faces from an image. We have taken skin colour as a tool for detection. The proposed algorithm performance compared to the previous methods, such as Zahra, and Viola-Jones techniques. Numerical results underline the robustness of the presented approach for tested images of faces which have a specific complexion varying under certain range are shown. We have taken real life examples and simulated the algorithms in MATLAB successfully.

A secure e-health architecture is proposed in this paper to support online treatment of patients in different hospitals registered to a registration authority (RA). For this, an efficient e-health architecture comprising four actors and three basic use cases is presented, where the actors like patients/hospitals register themselves to the RA and doctors may register in more than one hospitals using a common registration use case, all registered patients get their treatment through the patients’ treatment use case, and the patients’ protected health information (PHI) is finally uploaded to the RA for future reference and treatments. The proposed e-health system is secured, where the authentication of different actors is done using PKI based public-key certificate and the medical reports/PHI data are securely transmitted by symmetrically encrypted using secure session keys which are negotiated based on Diffie-Hellman technique. For the sake of clarity, each of the presented protocols is accompanied with message-flow diagram with the detail description of each step. The security analysis of the entire e-health system is shown and a web tool called AVISPA is used for simulation of the proposed protocols, which give satisfactory results. Finally, the computational and communication costs are also examined for estimation of implementation cost, which support easy deployment in real life applications.

Problem solving layout and allocation of road infrastructure elements are unique but necessary for not only technical but also economic and operational. Difficulty of the optimization procedure is highlighted by the diversity of determining entry criteria. Methods for the layout of regional development are built mainly for solving the distribution character with such disregarding energy requirements built parking lots, toll booths and the like. For this purpose it is necessary to apply other analytical methods, e.g. multi-criteria decision making, which complicates the solution procedure and does not lead to satisfactory results and is also easily influenced by a particular solver thus judgment may also be biased. The aim of the new layout method, focusing on elements of the transport is to achieve the desired result in one comprehensive solution, yet degrade the shortcomings of existing methods and procedures.

In this paper, a new algorithm for segmentation of cursive words in handwritten documents is proposed. This includes extraction of words from script images using hyper-graph model for division. Hyper-graph model considers an image as packets of pixels which give sub-images in conclusion. These sub-images further segmented using selected set of features corresponding to a character. Segmentation is a necessary step in any recognition model. A better recognition rate is achieved if the characters of a word are accurately isolated. The proposed approach includes four generic steps: pre-processing, feature extraction, segmentation, extraction of separated characters. The system employs several pre-processing steps to extract handwritten words from documents, ancient written scripts, medical prescription, records and images. Morphological operations are employed on graphemes and words for feature extraction. This work considers processes like zone ratio, cross-point, majority area, end-point detection for creating a set of features for segmentation. This is first attempt to hybridize hyper-graph model and morphological operations and experimental results shows promising character recognition even in poorly handwritten documents.

This paper presents adaptive gain scheduling PID controllers for stabilizing an X-Z inverted pendulum. The PID controller gains are not fixed and are designed to be a function of time that can vary within a specified range depending upon the transient and the steady state part of the response. The performance of the proposed controller is compared with the conventional PID controller given in the literature in the presence of uncertainties such as friction and noise in the controller. Simulation results show improved performance of the proposed controller over the conventional PID controller in terms of various performance specifications.