Real-time Laser Monitoring based on Pipe Detective Operation

The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.

The Weight of Corporate Social Responsibility Indicators in Measurement Procedure

The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.

Using Finite Element Method for Determination of Poles Number in Optimal Design of Linear Motor

One of Effective parameters on the performance of linear induction motors is number of poles which must be selected and optimized to increase power efficiency and motor performance significantly. In this paper a double-sided linear induction motor with different poles number by using MAXWELL3D software is designed and with finite element method is analyzed electromagnetically. Then for dynamic simulation, linear motor by using MATLAB software is simulated. The results show that by adding poles number, system time response is increased and motor after more time reaches to steady state. Also propulsion force of motor is increased.

Radiation Safety of Population in the Region of NPP-2006/MIR-1200 Site

The main features of NPP-2006/MIR-1200 design are described. Estimation of individual doses for population under normal operation and accident conditions is performed for Leningradskaya NPP – 2 as an example. The radiation effect on population and environment doesn-t exceed the established normative limit and is as low as reasonably achievable. NPP- 2006/MIR-1200 design meets all Russian and international requirements for power units under construction.

Combining Bagging and Additive Regression

Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.

Dynamic Variational Multiscale LES of Bluff Body Flows on Unstructured Grids

The effects of dynamic subgrid scale (SGS) models are investigated in variational multiscale (VMS) LES simulations of bluff body flows. The spatial discretization is based on a mixed finite element/finite volume formulation on unstructured grids. In the VMS approach used in this work, the separation between the largest and the smallest resolved scales is obtained through a variational projection operator and a finite volume cell agglomeration. The dynamic version of Smagorinsky and WALE SGS models are used to account for the effects of the unresolved scales. In the VMS approach, these effects are only modeled in the smallest resolved scales. The dynamic VMS-LES approach is applied to the simulation of the flow around a circular cylinder at Reynolds numbers 3900 and 20000 and to the flow around a square cylinder at Reynolds numbers 22000 and 175000. It is observed as in previous studies that the dynamic SGS procedure has a smaller impact on the results within the VMS approach than in LES. But improvements are demonstrated for important feature like recirculating part of the flow. The global prediction is improved for a small computational extra cost.

Extraction of Semantic Digital Signatures from MRI Photos for Image-Identification Purposes

This paper makes an attempt to solve the problem of searching and retrieving of similar MRI photos via Internet services using morphological features which are sourced via the original image. This study is aiming to be considered as an additional tool of searching and retrieve methods. Until now the main way of the searching mechanism is based on the syntactic way using keywords. The technique it proposes aims to serve the new requirements of libraries. One of these is the development of computational tools for the control and preservation of the intellectual property of digital objects, and especially of digital images. For this purpose, this paper proposes the use of a serial number extracted by using a previously tested semantic properties method. This method, with its center being the multi-layers of a set of arithmetic points, assures the following two properties: the uniqueness of the final extracted number and the semantic dependence of this number on the image used as the method-s input. The major advantage of this method is that it can control the authentication of a published image or its partial modification to a reliable degree. Also, it acquires the better of the known Hash functions that the digital signature schemes use and produces alphanumeric strings for cases of authentication checking, and the degree of similarity between an unknown image and an original image.

Hierarchies Based On the Number of Cooperating Systems of Finite Automata on Four-Dimensional Input Tapes

In theoretical computer science, the Turing machine has played a number of important roles in understanding and exploiting basic concepts and mechanisms in computing and information processing [20]. It is a simple mathematical model of computers [9]. After that, M.Blum and C.Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing, and investigated their pattern recognition abilities in 1967 [7]. Since then, a lot of researchers in this field have been investigating many properties about automata on a two- or three-dimensional tape. On the other hand, the question of whether processing fourdimensional digital patterns is much more difficult than two- or threedimensional ones is of great interest from the theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computasional model of four-dimensional pattern processing has been meaningful [8]-[19],[21]. This paper introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape where these finite automata work independently (in parallel). Those finite automata whose input heads scan the same cell of the input tape can communicate with each other, that is, every finite automaton is allowed to know the internal states of other finite automata on the same cell it is scanning at the moment. In this paper, we mainly investigate some accepting powers of a cooperating system of eight- or seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is an eight-way four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the fu-ture, but not in the past on a four-dimensional input tape.

Automatic Real-Patient Medical Data De-Identification for Research Purposes

Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burnedin annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.

Photograph Based Pair-matching Recognition of Human Faces

In this paper, a novel system recognition of human faces without using face different color photographs is proposed. It mainly in face detection, normalization and recognition. Foot method of combination of Haar-like face determined segmentation and region-based histogram stretchi (RHST) is proposed to achieve more accurate perf using Haar. Apart from an effective angle norm side-face (pose) normalization, which is almost a might be important and beneficial for the prepr introduced. Then histogram-based and photom normalization methods are investigated and ada retinex (ASR) is selected for its satisfactory illumin Finally, weighted multi-block local binary pattern with 3 distance measures is applied for pair-mat Experimental results show its advantageous perfo with PCA and multi-block LBP, based on a principle.

A Novel Architecture for Wavelet based Image Fusion

In this paper, we focus on the fusion of images from different sources using multiresolution wavelet transforms. Based on reviews of popular image fusion techniques used in data analysis, different pixel and energy based methods are experimented. A novel architecture with a hybrid algorithm is proposed which applies pixel based maximum selection rule to low frequency approximations and filter mask based fusion to high frequency details of wavelet decomposition. The key feature of hybrid architecture is the combination of advantages of pixel and region based fusion in a single image which can help the development of sophisticated algorithms enhancing the edges and structural details. A Graphical User Interface is developed for image fusion to make the research outcomes available to the end user. To utilize GUI capabilities for medical, industrial and commercial activities without MATLAB installation, a standalone executable application is also developed using Matlab Compiler Runtime.

Development of Coronal Field and Solar Wind Components for MHD Interplanetary Simulations

The connection between solar activity and adverse phenomena in the Earth’s environment that can affect space and ground based technologies has spurred interest in Space Weather (SW) research. A great effort has been put on the development of suitable models that can provide advanced forecast of SW events. With the progress in computational technology, it is becoming possible to develop operational large scale physics based models which can incorporate the most important physical processes and domains of the Sun-Earth system. In order to enhance our SW prediction capabilities we are developing advanced numerical tools. With operational requirements in mind, our goal is to develop a modular simulation framework of propagation of the disturbances from the Sun through interplanetary space to the Earth. Here, we report and discuss on the development of coronal field and solar wind components for a large scale MHD code. The model for these components is based on a potential field source surface model and an empirical Wang-Sheeley-Arge solar wind relation. 

One scheme of Transition Probability Evaluation

In present work are considered the scheme of evaluation the transition probability in quantum system. It is based on path integral representation of transition probability amplitude and its evaluation by means of a saddle point method, applied to the part of integration variables. The whole integration process is reduced to initial value problem solutions of Hamilton equations with a random initial phase point. The scheme is related to the semiclassical initial value representation approaches using great number of trajectories. In contrast to them from total set of generated phase paths only one path for each initial coordinate value is selected in Monte Karlo process.

Absorption of CO2 in EAF Reducing Slag from Stainless Steel Making Process by Wet Grinding

In the current study, we have conducted an experimental investigation on the utilization of electronic arc furnace (EAF) reducing slag for the absorption of CO2 via wet grinding method. It was carried out by various grinding conditions. The slag was ground in the vibrating ball mill in the presence of CO2 and pure water under ambient temperature. The reaction behavior was monitored with constant pressure method, and the changes of experimental systems volume as a function of grinding time were measured. It was found that the CO2 absorption occurred as soon as the grinding started. The CO2 absorption was significantly increased in the case of wet grinding compare to the dry grinding. Generally, the amount of CO2 absorption increased as the amount of water, weight of slag and initial pressure increased. However, it was decreased when the amount of water exceeds 200ml and when smaller balls were used. The absorption of CO2 occurred simultaneously with the start of the grinding and it stopped when the grinding was stopped. According to this research, the CO2 reacted with the CaO inside the slag, forming CaCO3.

Secondary Materials Management in Latvia: Challenges and Possibilities

Thisresearch paper is dedicated to an actual issue in Latvia and in the whole European Union – development of the secondary materials management. The goal of this paper is to research the development of the secondary materials management in Latvia as a result to point out its main positive aspects and problems. In this research paper the author regards following issues: significance of the secondary materials management, current situation of the waste generation and utilization in Latvia comparing with other EU Member States, main problems and positive aspects of the secondary materials management in Latvia. The research author concludes that in last ten years a great work is done to develop the secondary materials market. Nevertheless following improvements are necessary: implementation of the packaging deposit system, development of the separate waste collection, increasing of the recycling capacity.

Business Model Topology in Emerging Business Ecosystem

This paper describes topology of business models in market ecosystem of the emerging electric mobility industry. The business model topology shows that firm-s participation in the ecosystem is associated with different requirements on resources and capabilities, and different levels of risk. Business model concept is used together with concepts of networked value creation and shows that firms can achieve higher levels of sustainable advantage by cooperation, not competition. Hybrid business models provide companies a viable alternative possibility for participation in the market ecosystem.

Effect of Particle Gravity on the Fractal Dimension of Particle Line in three-dimensional Turbulent Flows using Kinematic Simulation

In this study, the dispersion of heavy particles line in an isotropic and incompressible three-dimensional turbulent flow has been studied using the Kinematic Simulation techniques to find out the evolution of the line fractal dimension. The fractal dimension of the line is found in the case of different particle gravity (in practice, different values of particle drift velocity) in the presence of small particle inertia with a comparison with that obtained in the diffusion case of material line at the same Reynolds number. It can be concluded for the dispersion of heavy particles line in turbulent flow that the particle gravity affect the fractal dimension of the line for different particle gravity velocities in the range 0.2 < W < 2. With the increase of the particle drift velocity, the fractal dimension of the line decreases which may be explained as the particles pass many scales in their journey in the direction of the gravity and the particles trajectories do not affect by these scales at high particle drift velocities.

An Improved Fast Video Clip Search Algorithm for Copy Detection using Histogram-based Features

In this paper, we present an improved fast and robust search algorithm for copy detection using histogram-based features for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal histogram feature which is robust to color distortion. Furthermore, by Combining with a temporal division method, the spatial and temporal features of the video sequence are integrated to realize fast and robust video search for copy detection. Experimental results show the proposed algorithm can detect the similar video clip more accurately and robust than conventional fast video search algorithm.

General Process Control for Intelligent Systems

Development of intelligent assembly cell conception includes new solution kind of how to create structures of automated and flexible assembly system. The current trend of the final product quality increasing is affected by time analysis of the entire manufacturing process. The primary requirement of manufacturing is to produce as many products as soon as possible, at the lowest possible cost, but of course with the highest quality. Such requirements may be satisfied only if all the elements entering and affecting the production cycle are in a fully functional condition. These elements consist of sensory equipment and intelligent control elements that are essential for building intelligent manufacturing systems. Intelligent behavior of the system as the control system will repose on monitoring of important parameters of the system in the real time. Intelligent manufacturing system itself should be a system that can flexibly respond to changes in entering and exiting the process in interaction with the surroundings.

Comparative Kinetic Study on Alkylation of p-cresol with Tert-butyl Alcohol using Different SO3-H Functionalized Ionic Liquid Catalysts

Ionic liquids are well known as green solvents, reaction media and catalysis. Here, three different sulfonic acid functional ionic liquids prepared in the laboratory are used as catalysts in alkylation of p-cresol with tert-butyl alcohol. The kinetics on each of the catalysts was compared and a kinetic model was developed based on the product distribution over these catalysts. The kinetic parameters were estimated using Marquadt's algorithm to minimize the error function. The Arrhenius plots show a curvature which is best interpreted by the extended Arrhenius equation.