Search results for: Magnitude Classification

Authors: E. Praynlin, P. Latha

Abstract:

Software Effort Estimation is the process of estimating the effort required to develop software. By estimating the effort, the cost and schedule required to estimate the software can be determined. Accurate Estimate helps the developer to allocate the resource accordingly in order to avoid cost overrun and schedule overrun. Several methods are available in order to estimate the effort among which soft computing based method plays a prominent role. Software cost estimation deals with lot of uncertainty among all soft computing methods neural network is good in handling uncertainty. In this paper Radial Basis Function Network is compared with the back propagation network and the results are validated using six data sets and it is found that RBFN is best suitable to estimate the effort. The Results are validated using two tests the error test and the statistical test.

Keywords: Software cost estimation, Radial Basis Function Network (RBFN), Back propagation function network, Mean Magnitude of Relative Error (MMRE).

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Authors: Abdussamad U. Jibia, Momoh-Jimoh E. Salami

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Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.

Keywords: Eigenvector, minimum norm, multiexponential, subspace.

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Authors: Muhammad Irfan Marwat, Sadaqat Jan, Syed Zafar Ali Shah

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Software Architecture plays a key role in software development but absence of formal description of Software Architecture causes different impede in software development. To cope with these difficulties, ontology has been used as artifact. This paper proposes ontology for Software Architectural design based on IEEE model for architecture description and Kruchten 4+1 model for viewpoints classification. For categorization of style and views, ISO/IEC 42010 has been used. Corpus method has been used to evaluate ontology. The main aim of the proposed ontology is to classify and locate Software Architectural design information.

Keywords: Software Architecture Ontology, Semantic based Software Architecture, Software Architecture, Ontology, Software Engineering.

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Authors: Jose A. Romero-Navarrete, Frank Otremba, Gerardo Hurtado-Hurtado

Abstract:

Turning maneuvers originate higher forces exerted on the rail and the loss of locomotive energy, at a rate that is function of several parameters that influence the magnitude of the developed horizontal wheel-rail forces, including the friction at the centre plate and the bogie´s yaw stiffness. However, such a friction at the contact surfaces of the centre plate is needed to mitigate the hunting phenomenon when the train moves on straight track segments. In this paper, a self-centering centre plate is proposed, consisting of a lubricated centre plate, equipped with a spring- and damper-based self-centering mechanism. Simulation results of the proposed mechanism suggest that the energy performance in turns of a train car equipped with such self-centering centre plate is comparatively better, as the peak friction forces linked to the dry friction at the contact surfaces of current centre plate designs, are avoided. The assessment of the hunting performance of the proposed device in straight track segments is proposed as the continuation of this work.

Keywords: Bogie´s yaw stiffness, bogie´s yaw friction, centre plate, self-centering mechanism, turning.

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Authors: Abdelhadi Lotfi, Abdelkader Benyettou

Abstract:

In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.

Keywords: Classification, probabilistic neural networks, network optimization, pattern recognition.

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Authors: Ly. Benbahouche

Abstract:

Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics.

The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments.

The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device).

Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt.

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Authors: Wenbin Zhang, Hantian Wu, Jian Tang

Abstract:

An artificial neural network is a mathematical model inspired by biological neural networks. There are several kinds of neural networks and they are widely used in many areas, such as: prediction, detection, and classification. Meanwhile, in day to day life, people always have to make many difficult decisions. For example, the coach of a soccer club has to decide which offensive player to be selected to play in a certain game. This work describes a novel Neural Network using a combination of the General Regression Neural Network and the Probabilistic Neural Networks to help a soccer coach make an informed decision.

Keywords: General Regression Neural Network, Probabilistic Neural Networks, Neural function.

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Authors: T.F.Lai, Wan Nor Liza Mahadi, Norhayati Soin

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This paper present a circular patch microstrip array antenna operate in KU-band (10.9GHz – 17.25GHz). The proposed circular patch array antenna will be in light weight, flexible, slim and compact unit compare with current antenna used in KU-band. The paper also presents the detail steps of designing the circular patch microstrip array antenna. An Advance Design System (ADS) software is used to compute the gain, power, radiation pattern, and S11 of the antenna. The proposed Circular patch microstrip array antenna basically is a phased array consisting of 'n' elements (circular patch antennas) arranged in a rectangular grid. The size of each element is determined by the operating frequency. The incident wave from satellite arrives at the plane of the antenna with equal phase across the surface of the array. Each 'n' element receives a small amount of power in phase with the others. There are feed network connects each element to the microstrip lines with an equal length, thus the signals reaching the circular patches are all combined in phase and the voltages add up. The significant difference of the circular patch array antenna is not come in the phase across the surface but in the magnitude distribution.

Keywords: Circular patch microstrip array antenna, gain, radiation pattern, S-Parameter.

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Authors: Hamdi Melih Saraoğlu, Muhlis Yıldırım, Abdurrahman Özbeyaz, Feyzullah Temurtas

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In this research, the diabetes conditions of people (healthy, prediabete and diabete) were tried to be identified with noninvasive palm perspiration measurements. Data clusters gathered from 200 subjects were used (1.Individual Attributes Cluster and 2. Palm Perspiration Attributes Cluster). To decrase the dimensions of these data clusters, Principal Component Analysis Method was used. Data clusters, prepared in that way, were classified with Support Vector Machines. Classifications with highest success were 82% for Glucose parameters and 84% for HbA1c parametres.

Keywords: Palm perspiration, Diabetes, Support Vector Machine, Classification.

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Authors: Simone C. F. Neves, Lúcio F. A. Campos, Ewaldo Santana, Ginalber L. O. Serra, Allan K. Barros

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We propose a method for discrimination and classification of ovarian with benign, malignant and normal tissue using independent component analysis and neural networks. The method was tested for a proteomic patters set from A database, and radial basis functions neural networks. The best performance was obtained with probabilistic neural networks, resulting I 99% success rate, with 98% of specificity e 100% of sensitivity.

Keywords: Cancer ovarian, Proteomic patterns in serum, independent component analysis and neural networks.

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Authors: Mohammad Hasan Raouf, Azim Nowbakht, Mohammad Bagher Haddadi, Mohammad Reza Tabatabaei

Abstract:

Power quality has become a very important issue recently due to the impact on electricity suppliers, equipment manufacturers and customers. Power quality is described as the variation of voltage, current and frequency in a power system. Voltage magnitude is one of the major factors that determine the quality of power. Indeed, custom power technology, the low-voltage counterpart of the more widely known flexible ac transmission system (FACTS) technology, aimed at high-voltage power transmission applications, has emerged as a credible solution to solve many problems relating to power quality problems. There are various power quality problems such as voltage sags, swells, flickers, interruptions and harmonics etc. Active Power Filter (APF) is one of the custom power devices and can mitigate harmonics, reactive power and unbalanced load currents originating from load side. In this study, an extensive review of APF studies, the advantages and disadvantages of each introduced methods are presented. The study also helps the researchers to choose the optimum control techniques and power circuit configuration for APF applications.

Keywords: Power Quality, Custom Power, Active Filter, Control Approach.

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: A classifier, Algorithms decision tree, knowledge extraction, Support Vector Machine.

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Authors: Takuya Sumi, Syoko Nukaya, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

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We propose an unconstrained measurement system for scratching motion based on mathematical model of unconstrained bed sensing method which could measure the bed vibrations due to the motion of the person on the bed. In this paper, we construct mathematical model of the unconstrained bed monitoring system; and we apply the unconstrained bed sensing method to the system for detecting scratching motion. The proposed sensors are placed under the three bed feet. When the person is lying on the bed, the output signals from the sensors are proportional to the magnitude of the vibration due to the scratching motion. Hence, we could detect the subject’s scratching motion from the output signals from ceramic sensors. We evaluated two scratching motions using the proposed system in the validity experiment as follows: 1st experiment is the subject’s scratching the right side cheek with his right hand, and; 2nd experiment is the subject’s scratching the shin with another foot. As the results of the experiment, we recognized the scratching signals that enable the determination when the scratching occurred. Furthermore, the difference among the amplitudes of the output signals enabled us to estimate where the subject scratched.

Keywords: Unconstrained bed sensing method, scratching, body movement, itchy, piezoceramics.

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Authors: Ferenc Peter Pach, Janos Abonyi

Abstract:

This paper focuses on the data-driven generation of fuzzy IF...THEN rules. The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system. Among the wide range of possible approaches, the decision tree and the association rule based algorithms are overviewed, and two new approaches are presented based on the a priori fuzzy clustering based partitioning of the continuous input variables. An application study is also presented, where the developed methods are tested on the well known Wisconsin Breast Cancer classification problem.

Keywords:

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Authors: Eric Filiol

Abstract:

This paper presents a formalisation of the different existing code mutation techniques (polymorphism and metamorphism) by means of formal grammars. While very few theoretical results are known about the detection complexity of viral mutation techniques, we exhaustively address this critical issue by considering the Chomsky classification of formal grammars. This enables us to determine which family of code mutation techniques are likely to be detected or on the contrary are bound to remain undetected. As an illustration we then present, on a formal basis, a proof-of-concept metamorphic mutation engine denoted PB MOT, whose detection has been proven to be undecidable.

Keywords: Polymorphism, Metamorphism, Formal Grammars, Formal Languages, Language Decision, Code Mutation, Word Problem

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Authors: Amit Bhattacharyya

Abstract:

The economic scenario of any region does not show the real picture for the measurement of overall development. Therefore, economic development must be accompanied by social development to be able to make an assessment to measure the level of development. The spatial variation with respect to social development has been discussed taking into account the quality of functioning of a social system in a specific area. In this paper, an attempt has been made to study the spatial distribution of social infrastructural facilities and analyze the magnitude of regional disparities at inter- block level in Barddhman district. It starts with the detailed account of the selection process of social infrastructure indicators and describes the methodology employed in the empirical analysis. Analyzing the block level data, this paper tries to identify the disparity among the blocks in the levels of social development. The results have been subsequently explained using both statistical analysis and geo spatial technique. The paper reveals that the social development is not going on at the same rate in every part of the district. Health facilities and educational facilities are concentrated at some selected point. So overall development activities come to be concentrated in a few centres and the disparity is seen over the blocks.

Keywords: Disparity, inter-block, social development, spatial variation.

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Authors: Esther T. Akinlabi, Stephen A. Akinlabi

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The purpose of this research study is to investigate the manner in which various loads affect the mechanical properties of the formed mild steel plates. The investigation focuses on examining the cross-sectional area of the metal plate at the centre of the formed mild steel plate. Six mild steel plates were deformed with different loads. The loads applied on the plates had a magnitude of 5 kg, 10 kg, 15 kg, 20 kg, 25 kg and 30 kg. The radius of the punching die was 120 mm and the loads were applied at room temperature. The investigations established that the applied load causes the Vickers microhardness at the cross-sectional area of the plate to increase due to strain hardening. Hence, the percentage increase of the hardness due to the load was found to be directly proportional to the increase in the load. Furthermore, the tensile test results for the parent material showed that the average Ultimate Tensile Strength (UTS) for the three samples was 308 MPa while the average Yield Strength and Percentage Elongation were 227 MPa and 38 % respectively. Similarly, the UTS of the formed components increased after the deformation of the plate, as such it can be concluded that the forming loads alter the mechanical properties of the materials by improving and strengthening the material properties.

Keywords: Applied load, forming and Mechanical Properties.

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Authors: A. Ashok, K.Satapathy, B. Prerana Nashine

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The objective of this research work is to investigate for one dimensional transient radiative transfer equations with conduction using finite volume method. Within the infrastructure of finite-volume, we obtain the conservative discretization of the terms in order to preserve the overall conservative property of finitevolume schemes. Coupling of conductive and radiative equation resulting in fluxes is governed by the magnitude of emissivity, extinction coefficient, and temperature of the medium as well as geometry of the problem. The problem under consideration has been solved, for a slab dominating radiation coupled with transient conduction based on finite volume method. The boundary conditions are also chosen so as to give a good model of the discretized form of radiation transfer equation. The important feature of the present method is flexibility in specifying the control angles in the FVM, while keeping the simplicity in the solution procedure. Effects of various model parameters are examined on the distributions of temperature, radiative and conductive heat fluxes and incident radiation energy etc. The finite volume method is considered to effectively evaluate the propagation of radiation intensity through a participating medium.

Keywords: Radiative transfer equation, finite volume method, conduction, transient radiation.

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Authors: B. K. Yeoh, Z. Arsad, C. W. Hooy

Abstract:

This paper tests the level of market integration between Malaysia and Singapore stock markets with the world market. Kalman Filter (KF) methodology is used on the International Capital Asset Pricing Model (ICAPM) and the pricing errors estimated within the framework of ICAPM are used as a measure of market integration or segmentation. The advantage of the KF technique is that it allows for time-varying coefficients in estimating ICAPM and hence able to capture the varying degree of market integration. Empirical results show clear evidence of varying degree of market integration for both case of Malaysia and Singapore. Furthermore, the results show that the changes in the level of market integration are found to coincide with certain economic events that have taken placed. The findings certainly provide evidence on the practicability of the KF technique to estimate stock markets integration. In the comparison between Malaysia and Singapore stock market, the result shows that the trends of the market integration indices for Malaysia and Singapore look similar through time but the magnitude is notably different with the Malaysia stock market showing greater degree of market integration. Finally, significant evidence of varying degree of market integration shows the inappropriate use of OLS in estimating the level of market integration.

Keywords: ICAPM, Kalman filter, stock market integration.

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Authors: Qurban A Memon, Mohammad S. Laghari

Abstract:

Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear debris analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self-organizing maps. This is achieved using relationship measurements among corresponding attributes of various measurements for wear debris. Finally, visualization technique is proposed that helps the viewer in understanding and utilizing these relationships that enable accurate diagnostics.

Keywords: Relationship Network, Relationship Measurement, Self-organizing Clusters, Wear Debris Analysis, Kohonen Network

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Authors: Chris K. Y. Lo, Andy C. L. Yeung, T. C. Edwin Cheng

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ISO 9000 is the most popular and widely adopted meta-standard for quality and operational improvements. However, only limited empirical research has been conducted to examine the impact of ISO 9000 on operational performance based on objective and longitudinal data. To reveal any causal relationship between the adoption of ISO 9000 and operational performance, we examined the timing and magnitude of change in time-based performance as a result of ISO 9000 adoption. We analyzed the changes in operating cycle, inventory days, and account receivable days prior and after the implementation of ISO 9000 in 695 publicly listed manufacturing firms. We found that ISO 9000 certified firms shortened their operating cycle time by 5.28 days one year after the implementation of ISO 9000. In the long-run (3 years after certification), certified firms showed continuous improvement in time-based efficiency, and experienced a shorter operating cycle time of 11 days than that of non-certified firms. There was an average of 6.5% improvement in operating cycle time for ISO 9000 certified firms. Both inventory days and account receivable days showed similar significant improvements after the implementation of ISO 9000, too.

Keywords: ISO 9000, Operating Cycle, Time-based efficiency.

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Authors: Wojciech Rejchel

Abstract:

The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.

Keywords: Convex loss function, empirical risk minimization, empirical process, U-process, boosting, euclidean family.

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Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

Abstract:

With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: Data integration, disease-related malnutrition, expert systems, mobile health.

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Authors: B. Marungsri, S. Boonpoke, A. Rawangpai, A. Oonsivilai, C. Kritayakornupong

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This study describes analysis of tower grounding resistance effected the back flashover voltage across insulator string in a transmission system. This paper studies the 500 kV transmission lines from Mae Moh, Lampang to Nong Chok, Bangkok, Thailand, which is double circuit in the same steel tower with two overhead ground wires. The factor of this study includes magnitude of lightning stroke, and front time of lightning stroke. Steel tower uses multistory tower model. The assumption of studies based on the return stroke current ranged 1-200 kA, front time of lightning stroke between 1 μs to 3 μs. The simulations study the effect of varying tower grounding resistance that affect the lightning current. Simulation results are analyzed lightning over voltage that causes back flashover at insulator strings. This study helps to know causes of problems of back flashover the transmission line system, and also be as a guideline solving the problem for 500 kV transmission line systems, as well.

Keywords: Tower grounding resistance, back flashover, multistory tower model, lightning stroke current.

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Authors: May-Ling Tan, Yi Su, Chi-Wan Lim, Liang Zhong, Ru-San Tan

Abstract:

This paper describes an automatic algorithm to restore the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data using a geometry-driven optimization approach. Our basic premise is to restore the LV shape such that the LV epicardial surface is smooth after the restoration. A geometrical measure known as the Minimum Principle Curvature (κ2) is used to assess the smoothness of the LV. This measure is used to construct the objective function of a two-step optimization process. The objective of the optimization is to achieve a smooth epicardial shape by iterative in-plane translation of the MRI slices. Quantitatively, this yields a minimum sum in terms of the magnitude of κ 2, when κ2 is negative. A limited memory quasi-Newton algorithm, L-BFGS-B, is used to solve the optimization problem. We tested our algorithm on an in vitro theoretical LV model and 10 in vivo patient-specific models which contain significant motion artifacts. The results show that our method is able to automatically restore the shape of LV models back to smoothness without altering the general shape of the model. The magnitudes of in-plane translations are also consistent with existing registration techniques and experimental findings.

Keywords: Magnetic Resonance Imaging, Left Ventricle, ShapeRestoration, Principle Curvature, Optimization

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Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Cristina Diego Soroa

Abstract:

Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.

Keywords: Accuracy, classical topographic, 3D model, photogrammetry, UAV.

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Authors: Mosaad Khadr, Gerd Morgenschweis, Andreas Schlenkhoff

Abstract:

Drought is one of the most damaging climate-related hazards, it is generally considered as a prolonged absence of precipitation. This normal and recurring climate phenomenon had plagued civilization throughout history because of the negative impacts on economical, environmental and social sectors. Drought characteristics are thus recognized as important factors in water resources planning and management. The purpose of this study is to detect the changes in drought frequency, persistence and severity in the Ruhr river basin. The frequency of drought events was calculated using the Standardized Precipitation Index (SPI). Used data are daily precipitation records from seven meteorological stations covering the period 1961-2007. The main benefit of the application of this index is its versatility, only rainfall data is required to deliver five major dimensions of a drought : duration, intensity, severity, magnitude, and frequency. Furthermore, drought can be calculated in different time steps. In this study SPI was calculated for 1, 3, 6, 9, 12, and 24 months. Several drought events were detected in the covered period, these events contain mild, moderate and severe droughts. Also positive and negative trends in the SPI values were observed.

Keywords: Drought, Germany, Precipitation, Ruhr River, Standardized Precipitation Index (SPI), Trend Test.

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Authors: George E. Tsekouras, Evi Sampanikou

Abstract:

We compare three categorical data clustering algorithms with respect to the problem of classifying cultural data related to the aesthetic judgment of comics artists. Such a classification is very important in Comics Art theory since the determination of any classes of similarities in such kind of data will provide to art-historians very fruitful information of Comics Art-s evolution. To establish this, we use a categorical data set and we study it by employing three categorical data clustering algorithms. The performances of these algorithms are compared each other, while interpretations of the clustering results are also given.

Keywords: Aesthetic judgment, comics artists, cluster analysis, categorical data.

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Authors: Richard Elling Moe

Abstract:

Computer languages are usually lumped together into broad -paradigms-, leaving us in want of a finer classification of kinds of language. Theories distinguishing between -genuine differences- in language has been called for, and we propose that such differences can be observed through a notion of expressive mode. We outline this concept, propose how it could be operationalized and indicate a possible context for the development of a corresponding theory. Finally we consider a possible application in connection with evaluation of language revision. We illustrate this with a case, investigating possible revisions of the relational algebra in order to overcome weaknesses of the division operator in connection with universal queries.

Keywords: Expressive mode, Computer language species, Evaluation of revision, Relational algebra, Universal database queries

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Authors: Ayşe Onat, Ferruh Yildiz, Mesut Gündüz

Abstract:

In this study, an OCR system for segmentation, feature extraction and recognition of Ottoman Scripts has been developed using handwritten characters. Detection of handwritten characters written by humans is a difficult process. Segmentation and feature extraction stages are based on geometrical feature analysis, followed by the chain code transformation of the main strokes of each character. The output of segmentation is well-defined segments that can be fed into any classification approach. The classes of main strokes are identified through left-right Hidden Markov Model (HMM).

Keywords: Chain Code, HMM, Ottoman Script Recognition, OCR

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