Methods of structural identification of static systems with a vector input and several nonlinearities in the conditions of uncertainty are considered. We consider inputs irregular. The concept of structural space is introduced. In this space special structures (virtual portraits) are analyzed. The Holder condition is applied to construction of sector set, to which belongs a virtual portrait of system of identification. Criteria of decision-making on a class of nonlinear functions on the basis of the analysis of proximity of sector sets are described. Procedures of an estimation of structural parameters of two classes of nonlinearities are stated: power and a hysteresis.

Super-resolution techniques allow combine multiple images of the same scene to obtain an image with increased geometric and radiometric resolution, called super-resolution image. In this image are enhanced features allowing to recover important details and information. The objective of this work is to develop efficient algorithm, robust and automated fusion image frames to obtain a super-resolution image. Image registration is a fundamental step in combining several images that make up the scene. Our research is based on the determination and extraction of characteristics defined by the SIFT and RANSAC algorithms for automatic image registration. We use images containing characters and perform recognition of these characters to validate and show the effectiveness of our proposed method. The distinction of this work is the way to get the matching and merging of images because it occurs dynamically between elements common images that are stored in a dynamic matrix.

Surveillance tests are performed periodically on standby systems of a Nuclear Power Plant (NPP), as they improve the systems’ availability on demand. High availability of safety critical systems is very essential to NPP safety, hence, careful analysis is required to schedule the surveillance activities for such systems in a cost effective way without compromising the plant safety. This forms an optimization problem wherein, two different cases can be formulated for deciding the value of Surveillance Test Interval. In one case, cost is the objective function to be minimized while unavailability is constrained to be at a given level and in another case, unavailability is minimized for a given cost level. Here, optimization is done using Genetic Algorithm (GA) and real encoding has been employed as it caters well to the requirements of this problem. A detailed procedure for GA formulation is described in this paper. Two different crossover methods, arithmetical crossover and blend crossover are explored and compared in this study to arrive at the most suitable crossover method for such type of problems.

Origin–destination (OD) matrix estimation largely depends on the quality and quantity of the input data, which in turn depends on the number and sites of count locations. In this paper, we focus on the network count location problem (NCLP), namely the identification of informative links in the road network. Also we employ opposition based colonial competitive algorithm (OCCA), which originally inspired by imperialistic competition, to determine the desirable number and locations of counting points satisfying location rules. The model and algorithm is illustrated with numerical examples.

Qualitative bankruptcy prediction rules represent experts' problem-solving knowledge to predict qualitative bankruptcy. The objective of this research is predicting qualitative bankruptcy using ant-miner algorithm. Qualitative data are subjective and more difficult to measure. This approach uses qualitative risk factors which include fourteen internal risk factors and sixty eight external risk factors associated with it. By using these factors qualitative prediction rules are generated using ant-miner algorithm and the influence of these factors in bankruptcy is also analyzed. Ant-Miner algorithm is a application of ant colony optimization and data mining concepts. Qualitative rules generated by ant miner algorithm are validated using measure of agreement. These prediction rules yields better accuracy with lesser number of terms than previously applied qualitative bankruptcy prediction methodologies.

Wireless Mesh Networks (WMNs) are the evolutionary self-organizing multi-hop wireless networks to promise last mile access. Due to the emergence of stochastically varying network environments, routing in WMNs is critically affected. In this paper, we first propose a fuzzy logic based hybrid performance metric comprising of link and node parameters. This Integrated Link Cost (ILC) is computed for each link based upon throughput, delay, jitter of the link and residual energy of the node and is used to compute shortest path between a given source-terminal node pair. Further to address the optimal routing path selection, two soft computing based approaches are proposed and analyzed along with a conventional approach. Extensive simulations are performed for various architectures of WMNs with varying network conditions. It was observed that the proposed approaches are far superior in dealing with dynamic nature of WMNs as compared to Adhoc On-demand Distance Vector (AODV) algorithm.

Pervasive computing aims at developing smart environments which enable user to interact with other devices. Pervasive computing includes a middleware to support interoperability, heterogeneity and self-management among different platforms. It provides efficient communications and context awareness among devices. Middleware for pervasive computing provides much more attention to coordinate the devices in the smart environment. The evaluation of the pervasive middleware is a challenging endeavor. The scope of evaluating smart environment is mainly increasing due to various devices involved in that environment. In this paper evaluation metrics are proposed based on the contexts available in the environment, how the devices are used, security and autonomy of smart applications. These metrics are used for evaluating different kind of smart applications.

Conventional street lighting systems in most of the areas are Online at regular intervals of time irrespective of the seasonal variations. The street lights are simply switched on at afternoon and turned off in the morning. The consequence is that a large amount of Power is wasted meaninglessly. As energy consumption is an issue of increasing interest, possible energy savings in public street lighting systems are recently discussed from different viewpoints. The purpose of this work is to describe the Smart Street Lighting system, an approach to accomplish the demand for flexible public lighting systems using a Programmable Logic controller (PLC). The main difference from other computers is that PLCs are armoured for severe conditions such as dust, moisture, heat, cold etc., and have the facility for extensive input/output (I/O) arrangements. In the proposed paper, street lights are controlled using millennium 3 PLC taking the seasonal variations into consideration.

Transmission constrained generation expansion planning (TC-GEP) problem involves decisions on site, capacity, type of fuel, and etc. of new generation units, which should be installed over a planning horizon to meet the expectations of energy demand. This may lead to adding or lightening transmission lines congestion. This paper presents an application of genetic algorithm (GA) to TC-GEP problem for simultaneously determination of new generation site, capacity and fuel type for a multi-period generation expansion plan. The objective function in this paper is to minimize the total generation cost which is composed of generation capital investment costs, operation and maintenance (O&M) costs, outage cost, transmission losses costs and transmission enhancement costs. In this paper, also a new method is proposed for computing transmission enhancement costs. In addition a new approach is presented in this paper to determine site and number of combined cycle power plants regarding to candidate units. The GA is applied to solve TC-GEP problem for 4 bus test system from Grainger & Stevenson for a planning horizon of one year and the results are compared and validated against Enumeration Method (EM). Then GA is applied to solve TC-GEP problem for IEEE-RTS 24-bus test system for a planning horizon of three years and results are discussed.

Identical twins identification is a challenging task because they share the same DNA sequence. This research paper presents minutiae coordinates and orientation angles fusion based technique for thumbprint identification of identical twins. Six different thumbprint images of identical twins were taken at a fixed time interval using H3 T&A terminal. The minutiae coordinates and orientation angles of these thumbprints were fused to form a union set. The union set values were stored in the smartcard memory for further identification.
The minutiae coordinates and orientation angles of a thumbprint of the person to be identified are computed and fused together for online identification. The fused minutiae are compared with the minutiae union set values stored in the smartcard memory for identity verification. The proposed method was tested on a self generated identical twin dataset and 50 identical twins of standard FVC04 and FVC06 datasets. We observed in experiments that the proposed method is accurately differentiating the identical twins of self generated and FVC datasets.

This paper mainly emphasizes on the POV (Persistence Of Vision) technology. In current era in which energy is the main factor in designing all the applications, maximum and efficient use of the energy is very important. A POV display has many advantages over a traditional CRT, LCD or LED display, like power savings, less complexity, easy configuration, attractiveness etc. To overcome the drawback of old processor we have decided to implement the same display atop a new and advanced microprocessor, the Arduino duemilanove. This platform brings with it newer coding and a different understanding of peripherals. ARDUINO INTERFACE BOARDS provide us with a low-cost, easy-to use technology to create the project. We also aim to build the newer display to work with modern forms of interfaces. To accomplish this, we will be interfacing the display with an Android device. This project can be implemented with help of any Android Smartphone/tablet running Android 4.0+.

Refer to this research, a position parallel error-based fuzzy inverse dynamic plus gravity controller is proposed for continuum robot manipulator. The main problem of the pure inverse dynamic controller was equivalent dynamic formulation in certain and uncertain systems. The nonlinear equivalent dynamic problem in uncertain system is solved by using fuzzy logic theory. To estimate the continuum robot manipulator system’s dynamic, 49 rules Mamdani inference system is design and applied to inverse dynamic plus gravity methodology. This methodology is based on applied fuzzy logic in equivalent nonlinear dynamic part to estimate unknown parameters. The results demonstrate that the error-based parallel fuzzy inverse dynamic plus gravity controller is a partly model-free controllers which works well in certain and partly uncertain system.