Abstract: A case study of the generation scheduling optimization
of the multi-hydroplants on the Yuan River Basin in China is reported
in this paper. Concerning the uncertainty of the inflows, the
long/mid-term generation scheduling (LMTGS) problem is solved by
a stochastic model in which the inflows are considered as stochastic
variables. For the short-term generation scheduling (STGS) problem, a
constraint violation priority is defined in case not all constraints are
satisfied. Provided the stage-wise separable condition and low
dimensions, the hydroplant-based operational region schedules
(HBORS) problem is solved by dynamic programming (DP). The
coordination of LMTGS and STGS is presented as well. The
feasibility and the effectiveness of the models and solution methods
are verified by the numerical results.
Abstract: Hepatitis B and hepatitis C are among the most
significant hepatic infections all around the world that may lead to
hepatocellular carcinoma. This study is first time performed at the
blood transfussion centre of Omar hospital, Lahore. It aims to
determine the sero-prevalence of these diseases by screening the
apparently healthy blood donors who might be the carriers of HBV or
HCV and pose a high risk in the transmission. It also aims the
comparison between the sensitivity of two diagnostic tests;
chromatographic immunoassay – one step test device and Enzyme
Linked Immuno Sorbant Assay (ELISA). Blood serum of 855
apparently healthy blood donors was screened for Hepatitis B surface
antigen (HBsAg) and for anti HCV antibodies. SPSS version 12.0
and X2 (Chi-square) test were used for statistical analysis. The seroprevalence
of HCV was 8.07% by the device method and by ELISA
9.12% and that of HBV was 5.6% by the device and 6.43% by
ELISA. The unavailability of vaccination against HCV makes it more
prevalent. Comparing the two diagnostic methods, ELISA proved to
be more sensitive.
Abstract: This paper describes fast and efficient method for page segmentation of document containing nonrectangular block. The segmentation is based on edge following algorithm using small window of 16 by 32 pixels. This segmentation is very fast since only border pixels of paragraph are used without scanning the whole page. Still, the segmentation may contain error if the space between them is smaller than the window used in edge following. Consequently, this paper reduce this error by first identify the missed segmentation point using direction information in edge following then, using X-Y cut at the missed segmentation point to separate the connected columns. The advantage of the proposed method is the fast identification of missed segmentation point. This methodology is faster with fewer overheads than other algorithms that need to access much more pixel of a document.
Abstract: In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.
Abstract: In this paper, an efficient method for personal identification based on the pattern of human iris is proposed. It is composed of image acquisition, image preprocessing to make a flat iris then it is converted into eigeniris and decision is carried out using only reduction of iris in one dimension. By comparing the eigenirises it is determined whether two irises are similar. The results show that proposed method is quite effective.
Abstract: The goal of this paper is to examine the effects of laser
radiation on the skin wound healing using infrared thermography as
non-invasive method for the monitoring of the skin temperature
changes during laser treatment. Thirty Wistar rats were used in this
study. A skin lesion was performed at the leg on all rats. The animals
were exposed to laser radiation (λ = 670 nm, P = 15 mW, DP = 16.31
mW/cm2) for 600 s. Thermal images of wound were acquired before
and after laser irradiation. The results have demonstrated that the
tissue temperature decreases from 35.5±0.50°C in the first treatment
day to 31.3±0.42°C after the third treatment day. This value is close
to the normal value of the skin temperature and indicates the end of
the skin repair process. In conclusion, the improvements in the
wound healing following exposure to laser radiation have been
revealed by infrared thermography.
Abstract: In this research, STNEP is being studied considering network adequacy and limitation of investment cost by decimal codification genetic algorithm (DCGA). The goal is obtaining the maximum of network adequacy with lowest expansion cost for a specific investment. Finally, the proposed idea is applied to the Garvers 6-bus network. The results show that considering the network adequacy for solution of STNEP problem is caused that among of expansion plans for a determined investment, configuration which has relatively lower expansion cost and higher adequacy is proposed by GA based method. Finally, with respect to the curve of adequacy versus expansion cost it can be said that more optimal configurations for expansion of network are obtained with lower investment costs.
Abstract: This paper presents an evolutionary method for designing
electronic circuits and numerical methods associated with
monitoring systems. The instruments described here have been used
in studies of weather and climate changes due to global warming, and
also in medical patient supervision. Genetic Programming systems
have been used both for designing circuits and sensors, and also for
determining sensor parameters. The authors advance the thesis that
the software side of such a system should be written in computer
languages with a strong mathematical and logic background in order
to prevent software obsolescence, and achieve program correctness.
Abstract: Short-Term Load Forecasting (STLF) plays an important role for the economic and secure operation of power systems. In this paper, Continuous Genetic Algorithm (CGA) is employed to evolve the optimum large neural networks structure and connecting weights for one-day ahead electric load forecasting problem. This study describes the process of developing three layer feed-forward large neural networks for load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. We find good performance for the large neural networks. The proposed methodology gives lower percent errors all the time. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.
Abstract: This work presents a numerical simulation of the interaction of an incident shock wave propagates from the left to the right with a cone placed in a tube at shock. The Mathematical model is based on a non stationary, viscous and axisymmetric flow. The Discretization of the Navier-stokes equations is carried out by the finite volume method in the integral form along with the Flux Vector Splitting method of Van Leer. Here, adequate combination of time stepping parameter, CFL coefficient and mesh size level is selected to ensure numerical convergence. The numerical simulation considers a shock tube filled with air. The incident shock wave propagates to the right with a determined Mach number and crosses the cone by leaving behind it a stationary detached shock wave in front of the nose cone. This type of interaction is observed according to the time of flow.
Abstract: The objective of this project is to study the corrosion
behaviour and hardness based on the presence of martensite in dual
phase steel. This study was conducted on six samples of dual phase
steel which have different percentage of martensite. A total of 9
specimens were prepared by intercritical annealing process to study
the effect of temperature to the formation of martensite. The low
carbon steels specimens were heated for 25 minutes in a specified
temperature ranging from 7250C to 8250C followed by rapid cooling
in water. The measurement of corrosion rate was done by using
extrapolation tafel method, while potentiostat was used to control and
measured the current produced. This measurement is performed
through a system named CMS105. The result shows that a specimen
with higher percentage of martensite is likely to corrode faster.
Hardness test for each specimen was conducted to compare its
hardness with low carbon steel. The results obtained indicate that the
specimen hardness is proportional to the amount of martensite in dual
phase steel.
Abstract: According to the increasing utilization in power system, the transmission lines and power plants often operate in stability boundary and system probably lose its stable condition by over loading or occurring disturbance. According to the reasons that are mentioned, the prediction and recognition of voltage instability in power system has particular importance and it makes the network security stronger.This paper, by considering of power system contingencies based on the effects of them on Mega Watt Margin (MWM) and maximum loading point is focused in order to analyse the static voltage stability using continuation power flow method. The study has been carried out on IEEE 14-Bus Test System using Matlab and Psat softwares and results are presented.
Abstract: Uniqueness and distinctiveness of localities (referred to as genius loci or sense of place) are important to ensure people-s identification with their locality. Existing frameworks reveals that the affective dimension of environments is rarely mentioned or explored and limited public participation was used in constructing the frameworks. This research argues that the complexity of sense of place would be recognised and appropriate planning guidelines formulated by exploring and integrating the affective dimension of a site. Aims of the research therefore are to (i) explore relational dimensions between people and a natural rural landscape, (ii) to implement a participatory approach to obtain insight into different relational dimensions, and (ii) to concretise socio-affective relational dimensions into site planning guidelines. A qualitative, interdisciplinary research approach was followed and conducted on the farm Kromdraai, Vredefort Dome World Heritage Site. In essence the first phase of the study reveals various affective responses and projections of personal meanings. The findings in phase 1 informed the second phase, to involve people from various disciplines and different involvement with the area to make visual presentations of appropriate planning and design of the site in order to capture meanings of the interactions between people and their environment. Final site planning and design guidelines were formulated, based on these. This research contributed to provide planners with new possibilities of exploring the dimensions between people and places as well as to develop appropriate methods for participation to obtain insight into the underlying meanings of sites.
Abstract: In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.
Abstract: We explore entanglement in composite quantum systems
and how its peculiar properties are exploited in quantum
information and communication protocols by means of Diagrams
of States, a novel method to graphically represent and analyze how
quantum information is elaborated during computations performed
by quantum circuits.
We present quantum diagrams of states for Bell states generation,
measurements and projections, for dense coding and quantum teleportation,
for probabilistic quantum machines designed to perform
approximate quantum cloning and universal NOT and, finally, for
quantum privacy amplification based on entanglement purification.
Diagrams of states prove to be a useful approach to analyze quantum
computations, by offering an intuitive graphic representation of the
processing of quantum information. They also help in conceiving
novel quantum computations, from describing the desired information
processing to deriving the final implementation by quantum gate
arrays.
Abstract: Most known methods for measuring the structural similarity of document structures are based on, e.g., tag measures, path metrics and tree measures in terms of their DOM-Trees. Other methods measures the similarity in the framework of the well known vector space model. In contrast to these we present a new approach to measuring the structural similarity of web-based documents represented by so called generalized trees which are more general than DOM-Trees which represent only directed rooted trees.We will design a new similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as strings of linear integers, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments to solve a novel and challenging problem: Measuring the structural similarity of generalized trees. More precisely, we first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based documents.
Abstract: People at workplace always face with stress and feel it in their lives. There are many factors that create stress and mobbing is one of them. Mobbing is a psychological terror, conducted systematically toward an individual by others at the same workplace. Mobbing started to become a famous subject last years in U.S and Europe. In Turkey, it is a new concept not because it does not occur, because of human nature that does not allow confessing it. Mobbing is being ignored by people, organizations and also government in our country. The focus of this study will be mobbing in Turkey by examining the workplace mobbing among Turkish academicians. There are other studies about mobbing in Turkey but none of them studied academy. Because mobbing methods change according to sectors and occupations, it is important to analyze each sector to understand the methods used in mobbing and the reactions of victims to these actions. The concept is analyzed in detail before focusing on mobbing at universities. This paper will be unique because there is no information about this specific subject in Turkish literature. In this paper, both qualitative and quantitative methods will be used to describe the mobbing at Turkish academic environment.
Abstract: Devices in a pervasive computing system (PCS) are characterized by their context-awareness. It permits them to provide proactively adapted services to the user and applications. To do so, context must be well understood and modeled in an appropriate form which enhance its sharing between devices and provide a high level of abstraction. The most interesting methods for modeling context are those based on ontology however the majority of the proposed methods fail in proposing a generic ontology for context which limit their usability and keep them specific to a particular domain. The adaptation task must be done automatically and without an explicit intervention of the user. Devices of a PCS must acquire some intelligence which permits them to sense the current context and trigger the appropriate service or provide a service in a better suitable form. In this paper we will propose a generic service ontology for context modeling and a context-aware service adaptation based on a service oriented definition of context.
Abstract: In this article, we are dealing with a model consisting of a classical Van der Pol oscillator coupled gyroscopically to a linear oscillator. The major problem is analyzed. The regular dynamics of the system is considered using analytical methods. In this case, we provide an approximate solution for this system using parameter-expansion method. Also, we find approximate values for frequencies of the system. In parameter-expansion method the solution and unknown frequency of oscillation are expanded in a series by a bookkeeping parameter. By imposing the non-secularity condition at each order in the expansion the method provides different approximations to both the solution and the frequency of oscillation. One iteration step provides an approximate solution which is valid for the whole solution domain.
Abstract: In this paper, modeling of an acoustic enclosed
vehicle cabin has been carried out by using boundary element
method. Also, the second purpose of this study is analyzing of linear
wave equation in an acoustic field. The resultants of this modeling
consist of natural frequencies that have been compared with
resultants derived from finite element method. By using numerical
method (boundary element method) and after solution of wave
equation inside an acoustic enclosed cabin, this method has been
progressed to simulate noise inside a simple vehicle cabin.