Computer Sciences Commons^™

Automatic Reduction Of Periodic Noise In Images Using Adaptive Gaussian Star Filter, Seni̇ha Ketenci̇, Ali̇ Gangal

Turkish Journal of Electrical Engineering and Computer Sciences

The reduction of noise in images is a crucial issue and an inevitable preprocessing step in image analysis. Many diverse noise sources, which disrupt source images, exist in nature and through manmade devices. Periodic noise is one such disruption that has a periodic pattern in the spatial domain, causing hills in the image spectrum. In practice, quasiperiodic noise is commonly encountered instead of periodic noise. It has a more complex frequency spectrum, such as a star shape, in place of a pure delta shape in the frequency amplitude spectrum. In this study, we consider designing a star shape Gaussian filter …

Design And Realization Of A Novel Planar Array Antenna And Low Power Lna For Ku-Band Small Satellite Communications, Lida Kouhalvandi, Osman Ceylan, Selçuk Paker, Hasan Bülent Yağci

Turkish Journal of Electrical Engineering and Computer Sciences

This article presents both a four-element novel microstrip array antenna and a low noise amplifier (LNA) for a Ku-band small satellite receiver. It includes all design details with measurement results of the fabricated array antenna and LNA. Measured minimum and maximum gains of the proposed antenna are 10.1 and 10.9 dBi in 11.9-12.9 GHz band frequency. The designed LNA has a noise figure lower than 1.5 dB and gain higher than 8 dB (at 2 V, 10 mA biasing). In order to reduce the design period and cost, discrete components are chosen and a hetero-junction FET is used as the …

Threshold Distance-Based Cluster Routing Protocols For Static And Mobile Wireless Sensor Networks, Padmavati Khandnor, Trilok Aseri

Turkish Journal of Electrical Engineering and Computer Sciences

In cluster-based wireless sensor network routing protocols, when the cluster head transfers data based on single hop transmission to the sink node, then the cluster heads that are farther away deplete more energy as compared to nearby cluster heads. This condenses load balancing in the network. If the cluster heads collaborate with each other and transfer data based on multihop transmission, then the cluster heads nearer to the sink node are burdened with significant relay traffic and deplete energy much faster, which causes a network coverage problem also known as a hot spot problem. To avoid both of the above …

Optimal Determination Of Island Boundaries Besides The Optimal Placement Of D-Statcom Devices And Dg Units, Sadeq Rabie, Hossein Afrakhte

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, integration of three important concepts of distributed generation, D-FACTS devices, and microgrids are evaluated. The performance of a microgrid is dependent on its location, capacity, and placement of DG units and D-FACTS devices. In this paper a new method is proposed to simultaneously determine the optimal number, location, and capacity of DG units and D-STATCOM devices and optimal boundaries of electrical islands in the independent mode of microgrids. The main objective is to minimize the economic costs. The optimal locations of DG units and D-STATCOM devices should be determined to maximize the DG capacities with minimum loss …

Design And Implementation Of A Modified Communication Disturbance Observer For Teleoperation Systems, Zahra Zeinaly, Amin Ramezani, Sadjaad Ozgoli

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a novel structure for a communication disturbance observer in teleoperation systems is proposed to achieve robust stability. A time delay compensation method based on the concept of network disturbance and a communication disturbance observer (CDOB) has been proposed in past research. Unlike model-based approaches, it works without a time delay model. Therefore, it can be implemented in teleoperation systems with unknown and time-varying delay. However, it has been observed that the system model errors and external disturbances seriously affect the steady-state characteristics. Hence, in this paper, to achieve robustness against disturbance and model uncertainty, the structure of …

Communications Protocol For Power Management In Smart Homes, Milan Bjelica, Mirjana Simic Pejovic

Turkish Journal of Electrical Engineering and Computer Sciences

Emergency situations, incentives for energy efficiency, new pricing plans, and distributed electricity market jointly require home automation systems that would conform an instantaneous load to a dynamically set limit. In this paper, a novel machine-to-machine communications protocol that interconnects a smart grid and smart house is described. ''Intelligent'' domestic appliances use it to coordinate their switch-on times so that the assigned power quota will not be exceeded. In this way, the end-user experience can be improved by reducing the electricity bills, conveniently conforming to prepaid pricing plans, or even by providing continued service at possibly reduced consumption levels during power …

Investigation Of Secondary Cooling Design Enhancements In Thermally Limited Compact Notebooks, Muhammad Azhar Ali Khan, Eray Uzgören, Ali̇ Muhtaroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Thermal design enhancements in a thermally limited compact notebook system are investigated in this paper. System temperature, power, and fan speed are characterized under a range of activity levels. A finite element model is developed, and validated against measurements. Design enhancements improve cooling with minimum intrusion to the existing mechanical design. A passive secondary heat pipe in the system reduces the CPU temperature by 5 $^{\circ}$C, and improves the system performance through increased CPU + Graphics and Memory Controller Hub (GMCH) thermal design power (TDP) by 6.4%. When such a secondary heat pipe is considered with an integrated off-the-shelf Peltier …

A Neural Network Approach To Navigation Of A Mobile Robot And Obstacle Avoidance In Dynamic And Unknown Environments, Farhad Shamsfakhr, Bahram Sadeghi Bigham

Turkish Journal of Electrical Engineering and Computer Sciences

Mobile robot navigation and obstacle avoidance in dynamic and unknown environments is one of the most challenging problems in the field of robotics. Considering that a robot must be able to interact with the surrounding environment and respond to it in real time, and given the limited sensing range, inaccurate data, and noisy sensor readings, this problem becomes even more acute. In this paper, we attempt to develop a neural network approach equipped with statistical dimension reduction techniques to perform exact and fast robot navigation, as well as obstacle avoidance in such a manner. In order to increase the speed …

Using Latent Semantic Analysis For Automated Keyword Extraction From Large Document Corpora, Tuğba Önal Süzek

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we describe a keyword extraction technique that uses latent semantic analysis (LSA) to identify semantically important single topic words or keywords. We compare our method against two other automated keyword extractors, Tf-idf (term frequency-inverse document frequency) and Metamap, using human-annotated keywords as a reference. Our results suggest that the LSA-based keyword extraction method performs comparably to the other techniques. Therefore, in an incremental update setting, the LSA-based keyword extraction method can be preferably used to extract keywords from text descriptions from big data when compared to existing keyword extraction methods.

Eccentricity Fault Diagnosis In A Permanent Magnet Synchronous Motor Under Nonstationary Speed Conditions, Mustafa Eker, Mehmet Akar

Turkish Journal of Electrical Engineering and Computer Sciences

Electric motor faults decrease production capacity and increase maintenance costs. Today, predictive detection based on real-time monitoring and fault detection is taking the place of periodic applications. In this study, a new method is presented for the detection of eccentricity faults in permanent magnet synchronous motors. The motor current and the rotor speed were monitored under stationary and nonstationary speed and different load conditions, after which the fault detection was carried out via angular domain-order tracking method. The obtained results were compared with traditional fast Fourier transform results. It was observed that the suggested method can successfully detect the fault …

High-Pass/Low-Pass Section Design For 0$^{\Circ}$-360$^{\Circ}$ Lumped-Element Phase Shifters Via The Real Frequency Technique, Meti̇n Şengül

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, an algorithm based on the real frequency technique (RFT) is proposed to design high-pass and low-pass sections of a 0$^{\circ}$-360$^{\circ}$ wide range lumped-element phase shifter. The switching process, however, is not considered in this work. In the algorithm, it is enough to define the section type (high-pass or low-pass) and the number of elements in the sections; there is no need to select the exact circuit topologies for the high-pass and low-pass sections. This is a natural consequence of the proposed approach. Unlike in the methods described in the literature, there is also no need to derive …

New Use Of The Hits Algorithm For Fast Web Page Classification, Mohamed Nadjib Meadi, Mohamed Chaouki Babahenini, Abdelmalik Taleb Ahmed

Turkish Journal of Electrical Engineering and Computer Sciences

The immense number of documents published on the web requires the utilization of automatic classifiers that allow organizing and obtaining information from these large resources. Typically, automatic web pages classifiers handle millions of web pages, tens of thousands of features, and hundreds of categories. Most of the classifiers use the vector space model to represent the dataset of web pages. The components of each vector are computed using the term frequency inversed document frequency (TFIDF) scheme. Unfortunately, TFIDF-based classifiers face the problem of the large-scale size of input data that leads to a long processing time and an increase in …

Intellimote: A Hybrid Classifier For Classifying Learners' Emotion In A Distributed E-Learning Environment, Lopa Mandal, Rohan Das, Samar Bhattacharya, Pramatha Nath Basu

Turkish Journal of Electrical Engineering and Computer Sciences

A huge collection of textual, graphical, audio, and video contents are readily available on the Internet to be used for the purpose of learning. Sentimental feedbacks of learners posted at the end of many of these contents may be considered as genuine reactions of the learners who have gone through the contents. Such learners' sentiments are important inputs for judging the acceptability of a learning material. Analyzing such feedbacks using sentiment analysis techniques can identify the best reusable learning contents that may be used for developing new courseware. This can significantly reduce the time and effort of authoring, which is …

Electrocardiogram Signal Analysis For R-Peak Detection And Denoising With Hybrid Linearization And Principal Component Analysis, Harjeet Kaur, Rajni Rajni

Turkish Journal of Electrical Engineering and Computer Sciences

In the areas of biomedical and healthcare, electrocardiogram (ECG) signal analysis is one of the major aspects of research. The accuracy in the detection of subtle characteristic features in ECG is of great significance. This paper deals with an algorithm based on hybrid linearization and principal component analysis for ECG signal denoising and R-peak detection. The ECG data have been taken from the MIT-BIH Arrhythmia Database for performance evaluation. The signal is denoised by applying the hybrid linearization method, which is an arrangement of the extended Kalman filter along with discrete wavelet transform, and then principal component analysis is employed …

Offset-Free Adaptive Nonlinear Model Predictive Control With Disturbance Observer For Dc-Dc Buck Converters, Bahareh Vatankhah, Mohammad Farrokhi

Turkish Journal of Electrical Engineering and Computer Sciences

The aim of this paper is to design a nonlinear model predictive control for DC-DC buck converters to track constant reference signals with zero steady-state error. The online trained neural network (NN) model is employed as the predictor and the steady-state error, which is called the offset, is studied in the presence of the changes in system parameters and the external disturbances. The stability of the closed-loop system is investigated using the Lyapunov direct theory. The proposed method can provide offset-free behavior in the presence of constant disturbances. For rejecting nonconstant disturbances, a nonlinear disturbance observer based on the NN …

Modified Control Of The Matrix Converter-Based Drive For Voltage Sag Impact Reduction, Gytis Petrauskas, Gytis Svinkunas

Turkish Journal of Electrical Engineering and Computer Sciences

Faults in transmission and distribution networks often cause voltage sags. Direct matrix converter (DMC)-based drives are a new generation of electrical drives. Unlike the conventional two-stage diode supply-side inverter drive, the DMC drive has no direct current (DC) link capacitor and no capacitor charging-time delay before operation. The absence of a DC link makes the DMC-based drive more sensitive to voltage sags. The above-mentioned faults in transmission and distribution networks could degrade the DMC drive's performance and reliability. This paper investigates possible kinds and levels of voltage sags, dependency on network configuration, and the behavior of the DMC-based drive under …

Foreword: Special Issue On Coalgebraic Logic, Alexander Kurz

Engineering Faculty Articles and Research

The second Dagstuhl seminar on coalgebraic logics took place from October 7-12, 2012, in the Leibniz Forschungszentrum Schloss Dagstuhl, following a successful earlier one in December 2009. From the 44 researchers who attended and the 30 talks presented, this collection highlights some of the progress that has been made in the field. We are grateful to Giuseppe Longo and his interest in a special issue in Mathematical Structures in Computer Science.

Quasivarieties And Varieties Of Ordered Algebras: Regularity And Exactness, Alexander Kurz

Engineering Faculty Articles and Research

We characterise quasivarieties and varieties of ordered algebras categorically in terms of regularity, exactness and the existence of a suitable generator. The notions of regularity and exactness need to be understood in the sense of category theory enriched over posets.

We also prove that finitary varieties of ordered algebras are cocompletions of their theories under sifted colimits (again, in the enriched sense).

The Positivication Of Coalgebraic Logics, Fredrik Dahlqvist, Alexander Kurz

Engineering Faculty Articles and Research

We present positive coalgebraic logic in full generality, and show how to obtain a positive coalgebraic logic from a boolean one. On the model side this involves canonically computing a endofunctor T': Pos->Pos from an endofunctor T: Set->Set, in a procedure previously defined by the second author et alii called posetification. On the syntax side, it involves canonically computing a syntax-building functor L': DL->DL from a syntax-building functor L: BA->BA, in a dual procedure which we call positivication. These operations are interesting in their own right and we explicitly compute posetifications and positivications in the case …

Classification Of Radar Jammer Fm Signals Using A Neural Network Approach, Ariadna Estefania Mendoza

Open Access Theses & Dissertations

A Neural Network (NN) used to classify radar signals is proposed for the purpose of military survivability and lethality analysis. The goal of the NN is to correctly differentiate Frequency-Modulated (FM) signals from Additive White Gaussian Noise (AWGN) using limited signal pre-processing. The FM signals used to test the NN approach are the linear or chirp FM and the power-law FM. Preliminary simulations using the moments of the signals in the time and frequency domain yielded better results in the frequency domain, suggesting that time domain training would not be as effective frequency domain training. To test this hypoThesis, we …

Optimization Of Neural Network Architecture For Classification Of Radar Jamming Fm Signals, Alberto Soto

Open Access Theses & Dissertations

Radar jamming signal classification is valuable when situational awareness of radar systems is sought out for timely deployment of electronic support measures. Our Thesis shows that artificial neural networks can be utilized for effective and efficient signal classification. The goal is to optimize an artificial Neural Network (NN) approach capable of distinguishing between two common radar waveforms, namely bandlimited white Gaussian jamming noise (BWGN) and the ubiquitous linearly frequency modulated (LFM) signal. This is made possible by creating a theoretical framework for NN architecture testing that leads to a high probability of detection (PD) and a low probability of false …

Robust And Agile System Against Fault And Anomaly Traffic In Software Defined Networks, Mihui Kim, Younghee Park, Rohit Kotalwar

Faculty Publications

The main advantage of software defined networking (SDN) is that it allows intelligent control and management of networking though programmability in real time. It enables efficient utilization of network resources through traffic engineering, and offers potential attack defense methods when abnormalities arise. However, previous studies have only identified individual solutions for respective problems, instead of finding a more global solution in real time that is capable of addressing multiple situations in network status. To cover diverse network conditions, this paper presents a comprehensive reactive system for simultaneously monitoring failures, anomalies, and attacks for high availability and reliability. We design three …

Blind Change Point Detection And Regime Segmentation Using Gaussian Process Regression, Sourav Das

Theses and Dissertations

Time-series analysis is used heavily in modeling and forecasting weather, economics, medical data as well as in various other fields. Change point detection (CPD) means finding abrupt changes in the time-series when the statistical property of a certain part of it starts to differ. CPD has attracted a lot of attention in the artificial intelligence, machine learning and data mining communities. In this thesis, a novel CPD algorithm is introduced for segmenting multivariate time-series data. The proposed algorithm is a general pipeline to process any high dimensional multivariate time-series data using nonlinear non-parametric dynamic system. It consists of manifold learning …

Mobile Application For Shipping Goods For Individuals And Truckers In India, Sendurr Selvaraj

Theses and Dissertations

India is a vast country with majority of its cities and towns connected through roads. Road transportation contributes to 86% share of the freight transport of the country with trucking companies dominating the entire space. With growing economy and demands raising, the quality of service of the trucking company remains poor. The major reasons are unorganized practice and lack of transparency. Moreover, limited access for customers to reach out to truckers to transport their goods.

This thesis aims to create a platform for customers and truckers to realize their needs with a help of a mobile application. Customers can search …

Leveraging The Srtp Protocol For Over-The-Network Memory Acquisition Of A Ge Fanuc Series 90-30, George Denton, Filip Karpisek, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Programmable Logic Controllers (PLCs) are common components implemented across many industries such as manufacturing, water management, travel, aerospace and hospitals to name a few. Given their broad deployment in critical systems, they became and still are a common target for cyber attacks; the most prominent one being Stuxnet. Often PLCs (especially older ones) are only protected by an outer line of defense (e.g., a firewall) but once an attacker gains access to the system or the network, there might not be any other defense layers. In this scenario, a forensic investigator should not rely on the existing software as it …

Using Sound To Describe Scenes With Still And Moving Obstacles, Kawin Metsiritrakul

Chulalongkorn University Theses and Dissertations (Chula ETD)

The information human get from sight and hearing sense are similar. With these correlations, there are many works that take this idea to describe the spatial information with sound. The previous works only described the nearest obstacle with the direction and distance information to sound. To let the user clearly understand the spatial information in the scene, we aim to develop the describing solution from spatial information to auditory information including direction, distance, boundary and speed info with the multiple obstacle descriptions. The participants took the experiment by controlling the character and avoiding the obstacles in the different scenarios to …

Developing An Area Classification System From Mobile Phone Usage Data, Naruethai Thongphasook

Chulalongkorn University Theses and Dissertations (Chula ETD)

Since human activities are vary by time and place, there have been many attempts to extract social behavior in spatial studies which included area use in the city. This information helps gaining advantages in city and facilities planning. Nowadays, many people carry mobile phone with them for communication purpose. This motivates us to analyze mobile phone usage in different area types. This thesis proposes method of an analysis for area use classification from mobile phone usage pattern. CDR data was used to define mobile phone usage pattern by hour from 1:00 to 24:00 and day of week from Monday to …

Automatic 3d Hair Model From Small Set Of Images, Nuttapon Vanakittistien

Chulalongkorn University Theses and Dissertations (Chula ETD)

We present a system for creating hair model that matches a user's hairstyle from images. The model consists of guide hair strands and can be used in a real-time hair simulator. Our goal differs from most previous work which aims to create realistic high resolution hair for off-line applications or create mesh of the exterior of the hair volume for image manipulation. Our primary aim is for user to be able to put his/her hairstyle into game or other real-time applications. By taking photos in 8 views of the user's head using a smart phone camera and segmenting images with …

Random Field Optimization Using Local Label Hierarchy, Sangsan Leelhapantu

Chulalongkorn University Theses and Dissertations (Chula ETD)

Random field formulation has proven to be a powerful framework for solving various computer vision tasks, specifically those involving assigning labels to image pixels or superpixels subjected to spatial relationships and visual contexts, due to the ability to intuitively incorporate global and local information. Unfortunately, solving these problems can be impractical when large number of variables and possible labels are present as the computational complexity grows fast with the problem size. In this thesis, we propose a speedup scheme for random field optimization using local label hierarchy. We focus on problems in which the label space has a natural ordering …

Efficient And Robust Grasp Planning Based On Independent Contact Region And Caging, Teesit Makapunyo

Chulalongkorn University Theses and Dissertations (Chula ETD)

A conventional way to find a proper grasp to grab and hold any object is to measure its stability which usually is based on physical constraint called force-closure. This execution works well from the theoretical point of view but often fails on an actual robot due to many reasons such as intrinsic errors in robot's system and a disparity between real and simulated physics. Several research works introduced methods to alleviate those issues and increase the success rate of grasping for a real robot. Caging and Independent Contact Region are ones of them. In this work, we investigate a method …