Multicriteria Decision Analysis for Development Ranking of Balkan Countries
In this research, the Balkan peninsula countries' developmental integration into European Union represents the strategic economic development objectives of the countries in the region. In order to objectively analyze the level of economic development competition of Balkan Peninsula countries, the mathematical compromise programming technique of multicriteria evaluation is used in this ranking problem. The primary aim of this research is to explain the role and significance of the multicriteria method evaluation using a real example of compromise solutions. Using the mathematical compromise programming technique, twelve countries of the Balkan Peninsula are economically evaluated and mutually compared. The economic development evaluation of the countries is performed according to five evaluation criteria forming the basis for economic development evaluation. The multiattribute model is solved using the mathematical compromise programming technique for producing different Pareto solutions. The results obtained by the multicriteria evaluation gives the possibility of identification and evaluation of the most eminent economic development indicators for each country separately. Finally, in this way, the proposed method has proved to be a successful model for the evaluation of the Balkan peninsula countries' economic development competition.
Multidimensional Compromise Programming Evaluation of Digital Commerce Websites
Multidimensional compromise programming evaluation of digital commerce websites is essential not only to have recommendations for improvement, but also to make comparisons with global business competitors. This research provides a multidimensional decision making model that prioritizes the objective criteria weights of various commerce websites using multidimensional compromise solution. Evaluation of digital commerce website quality can be considered as a complex information system structure including qualitative and quantitative factors for a multicriteria decision making problem. The proposed multicriteria decision making approach mainly consists of three sequential steps for the selection problem. In the first step, three major different evaluation criteria are characterized for website ranking problem. In the second step, identified critical criteria are weighted using the standard deviation procedure. In the third step, the multidimensional compromise programming is applied to rank the digital commerce websites.
Multidimensional Compromise Optimization for Development Ranking of the Gulf Cooperation Council Countries and Turkey
In this research, a multidimensional compromise optimization method is proposed for multidimensional decision making analysis in the development ranking of the Gulf Cooperation Council Countries and Turkey. The proposed approach presents ranking solutions resulting from different multicriteria decision analyses, which yield different ranking orders for the same ranking problem, consisting of a set of alternatives in terms of numerous competing criteria when they are applied with the same numerical data. The multiobjective optimization decision making problem is considered in three sequential steps. In the first step, five different criteria related to the development ranking are gathered from the research field. In the second step, identified evaluation criteria are, objectively, weighted using standard deviation procedure. In the third step, a country selection problem is illustrated with a numerical example as an application of the proposed multidimensional compromise optimization model. Finally, multidimensional compromise optimization approach is applied to rank the Gulf Cooperation Council Countries and Turkey.
Multidimensional Performance Tracking
In this study, a model, together with a software tool that implements it, has been developed to determine the performance ratings of employees in an organization operating in the information technology sector using the indicators obtained from employees' online study data. Weighted Sum (WS) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method based on multidimensional decision making approach were used in the study. WS and TOPSIS methods provide multidimensional decision making (MDDM) methods that allow all dimensions to be evaluated together considering specific weights, allowing employees to objectively evaluate the problem of online performance tracking. The application of WS and TOPSIS mathematical methods, which can combine alternatives with a large number of dimensions and reach simultaneous solution, has been implemented through an online performance tracking software. In the application of WS and TOPSIS methods, objective dimension weights were calculated by using entropy information (EI) and standard deviation (SD) methods from the data obtained by employees' online performance tracking method, decision matrix was formed by using performance scores for each employee, and a single performance score was calculated for each employee. Based on the calculated performance score, employees were given a performance evaluation decision. The results of Pareto set evidence and comparative mathematical analysis validate that employees' performance preference rankings in WS and TOPSIS methods are closely related. This suggests the compatibility, applicability, and validity of the proposed method to the MDDM problems in which a large number of alternative and dimension types are taken into account. With this study, an objective, realistic, feasible and understandable mathematical method, together with a software tool that implements it has been demonstrated. This is considered to be preferable because of the subjectivity, limitations and high cost of the methods traditionally used in the measurement and performance appraisal in the information technology sector.
Development of PSS/E Dynamic Model for Controlling Battery Output to Improve Frequency Stability in Power Systems
The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.
The Morphology of Sri Lankan Text Messages
Communicating via a text or an SMS (Short Message Service) has become an integral part of our daily lives. With the increase in the use of mobile phones, text messaging has become a genre by itself worth researching and studying. It is undoubtedly a major phenomenon revealing language change. This paper attempts to describe the morphological processes of text language of urban bilinguals in Sri Lanka. It will be a typological study based on 500 English text messages collected from urban bilinguals residing in Colombo. The messages are selected by categorizing the deviant forms of language use apparent in text messages. These stylistic deviations are a deliberate skilled performance by the users of the language possessing an in-depth knowledge of linguistic systems to create new words and thereby convey their linguistic identity and individual and group solidarity via the message. The findings of the study solidifies arguments that the manipulation of language in text messages is both creative and appropriate. In addition, code mixing theories will be used to identify how existing morphological processes are adapted by bilingual users in Sri Lanka when texting. The study will reveal processes such as omission, initialism, insertion and alternation in addition to other identified linguistic features in text language. The corpus reveals the most common morphological processes used by Sri Lankan urban bilinguals when sending texts.
A Simple and Efficient Method for Accurate Measurement and Control of Power Frequency Deviation
In the presented technique, a simple method is given for accurate measurement and control of power frequency deviation. The sinusoidal signal for which the frequency deviation measurement is required is transformed to a low voltage level and passed through a zero crossing detector to convert it into a pulse train. Another stable square wave signal of 10 KHz is obtained using a crystal oscillator and decade dividing assemblies (DDA). These signals are combined digitally and then passed through decade counters to give a unique combination of pulses or levels, which are further encoded to make them equally suitable for both control applications and display units. The developed circuit using discrete components has a resolution of 0.5 Hz and completes measurement within 20 ms. The realized circuit is simulated and synthesized using Verilog HDL and subsequently implemented on FPGA. The results of measurement on FPGA are observed on a very high resolution logic analyzer. These results accurately match the simulation results as well as the results of same circuit implemented with discrete components. The proposed system is suitable for accurate measurement and control of power frequency deviation.
Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena
A seizure prediction method is proposed by extracting
global features using phase correlation between adjacent epochs for
detecting relative changes and local features using fluctuation/
deviation within an epoch for determining fine changes of different
EEG signals. A classifier and a regularization technique are applied
for the reduction of false alarms and improvement of the overall
prediction accuracy. The experiments show that the proposed method
outperforms the state-of-the-art methods and provides high prediction
accuracy (i.e., 97.70%) with low false alarm using EEG signals in
different brain locations from a benchmark data set.
Poincaré Plot for Heart Rate Variability
Heart is the most important part in the body of living
organisms. It affects and is affected by any factor in the body.
Therefore, it is a good detector for all conditions in the body. Heart
signal is a non-stationary signal; thus, it is utmost important to study
the variability of heart signal. The Heart Rate Variability (HRV) has
attracted considerable attention in psychology, medicine and has
become important dependent measure in psychophysiology and
behavioral medicine. The standards of measurements, physiological
interpretation and clinical use for HRV that are most often used were
described in many researcher papers, however, remain complex
issues are fraught with pitfalls. This paper presents one of the nonlinear
techniques to analyze HRV. It discusses many points like, what
Poincaré plot is and how Poincaré plot works; also, Poincaré plot's
merits especially in HRV. Besides, it discusses the limitation of
Poincaré cause of standard deviation SD1, SD2 and how to overcome
this limitation by using complex correlation measure (CCM). The
CCM is most sensitive to changes in temporal structure of the
Poincaré plot as compared toSD1 and SD2.
Influence of Replacement Used Reference Coordinate System for Georeferencing of the Old Map of Europe
The article describes the effect of the replacement of
the used reference coordinate system in the georeferencing of an old
map of Europe. The map was georeferenced into three types of
projection – the equal-area conic (original cartographic projection),
cylindrical Plate Carrée and cylindrical Mercator map projection. The
map was georeferenced by means of the affine and the second-order
polynomial transformation. The resulting georeferenced raster
datasets from the Plate Carrée and Mercator projection were
projected into the equal-area conic projection by means of projection
equations. The output is the comparison of drawn graphics, the
magnitude of standard deviations for individual projections and types
Estimating the Technological Deviation Impact on the Value of the Output Parameter of the Induction Converter
Based on the experimental data, the impact of
resistance and reactance of the winding, as well as the magnetic
permeability of the magnetic circuit steel material on the value of the
electromotive force of the induction converter is investigated. The
obtained results allow estimating the main technological spreads and
determining the maximum level of the electromotive force change.
By the method of experiment planning, the expression of a
polynomial for the electromotive force which can be used to estimate
the adequacy of mathematical models to be used at the investigation
and design of induction converters is obtained.
Field Experience with Sweep Frequency Response Analysis for Power Transformer Diagnosis
Sweep frequency response analysis has been turning
out a powerful tool for investigation of mechanical as well as
electrical integration of transformers. In this paper various aspect of
practical application of SFRA has been studied. Open circuit and
short circuit measurement were done on different phases of high
voltage and low voltage winding. A case study was presented for the
transformer of rating 31.5 MVA for various frequency ranges. A
clear picture was presented for sub- frequency ranges for HV as well
as LV winding. The main motive of work is to investigate high
voltage short circuit response. The theoretical concept about SFRA
responses is validated with expert system software results.
Deviations and Defects of the Sub-Task’s Requirements in Construction Projects
The sub-task pattern in terms of deviations and defects
should be identified and understood in order to improve the quality of
practices in construction projects. Therefore, sub-task susceptibility
to exposure to deviations and defects has been evaluated and
classified via six classifications proposed in this study. Thirty-four
case studies of specific sub-tasks (from compression members in
constructed concrete structures) were collected from seven
construction projects in order to examine the study’s proposed
classifications. The study revealed that the sub-task has a high
sensitivity to deviation, where 91% of the cases were recorded as
deviations; however, only 19% of cases were recorded as defects.
Other findings were that the actual work during the execution process
is a high source of deviation for this sub-task (74%), while only 26%
of the source of deviation was due to both design documentation and
the actual work. These findings significantly imply that the study’s
proposed classifications could be used to determine the pattern of
each sub-task and develop proactive actions to overcome issues of
sub-task deviations and defects.
Detecting Abnormal ECG Signals Utilising Wavelet Transform and Standard Deviation
ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.
Ranking Fuzzy Numbers Based On Epsilon-Deviation Degree
Nejad and Mashinchi (2011) proposed a revision for ranking fuzzy numbers based on the areas of the left and the right sides of a fuzzy number. However, this method still has some shortcomings such as lack of discriminative power to rank similar fuzzy numbers and no guarantee the consistency between the ranking of fuzzy numbers and the ranking of their images. To overcome these drawbacks, we propose an epsilon-deviation degree method based on the left area and the right area of a fuzzy number, and the concept of the centroid point. The main advantage of the new approach is the development of an innovative index value which can be used to consistently evaluate and rank fuzzy numbers. Numerical examples are presented to illustrate the efficiency and superiority of the proposed method.
Evaluating per-user Fairness of Goal-Oriented Parallel Computer Job Scheduling Policies
Fair share objective has been included into the goaloriented
parallel computer job scheduling policy recently. However,
the previous work only presented the overall scheduling performance.
Thus, the per-user performance of the policy is still lacking. In this
work, the details of per-user fair share performance under the
Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair
share priority backfill policy namely RelShare(1d) is also studied.
The performance of all policies is collected using an event-driven
simulator with three real job traces as input. The experimental results
show that the high demand users are usually benefited under most
policies because their jobs are large or they have a lot of jobs. In the
large job case, one job executed may result in over-share during that
period. In the other case, the jobs may be backfilled for
performances. However, the users with a mixture of jobs may suffer
because if the smaller jobs are executing the priority of the remaining
jobs from the same user will be lower. Further analysis does not show
any significant impact of users with a lot of jobs or users with a large
runtime approximation error.
Design of a Fuzzy Feed-forward Controller for Monitor HAGC System of Cold Rolling Mill
In this study we propose a novel monitor hydraulic
automatic gauge control (HAGC) system based on fuzzy feedforward
controller. This is used in the development of cold rolling
mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average
yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in
the entry steel strip. The proposed method uses a mathematical model
of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In
order to improve the speed of the controller in rejecting disturbances
introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation
results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.
Automat Control of the Aircrafts- Lateral Movement using the Dynamic Inversion
The paper presents a new system for the automat
control of the aircrafts- flight in lateral plane using the cinematic
model and the dynamic inversion. Starting from the equations of the
aircrafts- lateral movement, the authors use two axes systems and
obtained a control law that cancels the lateral deviation of the flying
objects from the runway line. This system makes the aircrafts-
direction angle to follow the direction angle of the runway line.
Simulations in Matlab/Simulink have been done for different
aircraft-s initial points and direction angles. The inconvenience of
this system is the long duration of the “transient regime". That is why
this system can be used independently, but the results are not very
good; thus, it can be a part (subsystem) of other systems. The main
system that cancels the lateral deviation from the runway line is
based on dynamic inversion and uses, as subsystem, the control
system for the lateral movement using the cinematic model. Using
complex Matlab/Simulink models, the authors obtained the time
evolution of the direction angle and the time evolution of the aircraft
lateral deviation with respect to the runway line, for different values
of the initial direction angle and for different wind types. The system
has a very good behavior for all initial direction angles and wind
Large Deviations for Lacunary Systems
Let Xi be a Lacunary System, we established large
deviations inequality for Lacunary System. Furthermore, we gained
Marcinkiewicz Larger Number Law with dependent random variables
Roundness Deviation Measuring Strategy at Coordination Measuring Machines and Conventional Machines
Today technological process makes possible surface
control of producing parts which is needful for product quality
guarantee. Geometrical structure of part surface includes form,
proportion, accuracy to shape, accuracy to size, alignment and
surface topography (roughness, waviness, etc.). All these parameters
are dependence at technology, production machine parameters,
material properties, but also at human, etc. Every parameters
approves at total part accuracy, it is means at accuracy to shape. One
of the most important accuracy to shape element is roundness. This
paper will be deals by comparison of roughness deviations at
coordination measuring machines and at special single purpose
machines. Will describing measuring by discreet method
(discontinuous) and scanning method (continuous) at coordination
measuring machines and confrontation with reference method using
at single purpose machines.
Simulation and Design of the Geometric Characteristics of the Oscillatory Thermal Cycler
Since polymerase chain reaction (PCR) has been
invented, it has emerged as a powerful tool in genetic analysis. The
PCR products are closely linked with thermal cycles. Therefore, to
reduce the reaction time and make temperature distribution uniform in
the reaction chamber, a novel oscillatory thermal cycler is designed.
The sample is placed in a fixed chamber, and three constant isothermal
zones are established and lined in the system. The sample is oscillated
and contacted with three different isothermal zones to complete
thermal cycles. This study presents the design of the geometric
characteristics of the chamber. The commercial software
CFD-ACE+TM is utilized to investigate the influences of various
materials, heating times, chamber volumes, and moving speed of the
chamber on the temperature distributions inside the chamber. The
chamber moves at a specific velocity and the boundary conditions
with time variations are related to the moving speed. Whereas the
chamber moves, the boundary is specified at the conditions of the
convection or the uniform temperature. The user subroutines compiled
by the FORTRAN language are used to make the numerical results
realistically. Results show that the reaction chamber with a rectangular
prism is heated on six faces; the effects of various moving speeds of
the chamber on the temperature distributions are examined. Regarding
to the temperature profiles and the standard deviation of the
temperature at the Y-cut cross section, the non-uniform temperature
inside chamber is found as the moving speed is larger than 0.01 m/s.
By reducing the heating faces to four, the standard deviation of the
temperature of the reaction chamber is under 1.4×10-3K with the range
of velocities between 0.0001 m/s and 1 m/s. The nature convective
boundary conditions are set at all boundaries while the chamber moves
between two heaters, the effects of various moving velocities of the
chamber on the temperature distributions are negligible at the assigned
Standard Deviation of Mean and Variance of Rows and Columns of Images for CBIR
This paper describes a novel and effective approach to content-based image retrieval (CBIR) that represents each image in the database by a vector of feature values called “Standard deviation of mean vectors of color distribution of rows and columns of images for CBIR". In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. This paper describes the approach that uses contents as feature vector for retrieval of similar images. There are several classes of features that are used to specify queries: colour, texture, shape, spatial layout. Colour features are often easily obtained directly from the pixel intensities. In this paper feature extraction is done for the texture descriptor that is 'variance' and 'Variance of Variances'. First standard deviation of each row and column mean is calculated for R, G, and B planes. These six values are obtained for one image which acts as a feature vector. Secondly we calculate variance of the row and column of R, G and B planes of an image. Then six standard deviations of these variance sequences are calculated to form a feature vector of dimension six. We applied our approach to a database of 300 BMP images. We have determined the capability of automatic indexing by analyzing image content: color and texture as features and by applying a similarity measure Euclidean distance.
Restoration of Noisy Document Images with an Efficient Bi-Level Adaptive Thresholding
An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.
Optimal Straight Line Trajectory Generation in 3D Space using Deviation Algorithm
This paper presents an efficient method of obtaining a straight-line motion in the tool configuration space using an articulated robot between two specified points. The simulation results & the implementation results show the effectiveness of the method.
A Real-Time Specific Weed Recognition System Using Statistical Methods
The identification and classification of weeds are of
major technical and economical importance in the agricultural
industry. To automate these activities, like in shape, color and
texture, weed control system is feasible. The goal of this paper is to
build a real-time, machine vision weed control system that can detect
weed locations. In order to accomplish this objective, a real-time
robotic system is developed to identify and locate outdoor plants
using machine vision technology and pattern recognition. The
algorithm is developed to classify images into broad and narrow class
for real-time selective herbicide application. The developed
algorithm has been tested on weeds at various locations, which have
shown that the algorithm to be very effectiveness in weed
identification. Further the results show a very reliable performance
on weeds under varying field conditions. The analysis of the results
shows over 90 percent classification accuracy over 140 sample
images (broad and narrow) with 70 samples from each category of
Arabic Character Recognition using Artificial Neural Networks and Statistical Analysis
In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.