Computer Sciences Commons^™

Development And Optimization Of A Dsp-Based Real-Time Lane Detection Algorithm On A Mobile Platform, Gürkan Küçükyildiz, Hasan Ocak

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, image processing-based real-time lane detection, which is one of the significant problems in autonomous vehicle control, is explored. A mobile robot platform is developed for that purpose. The motion of the mobile robot is provided by 4 direct current motors, which are independently controlled. An image processing code is developed in a Visual DSP 5.0 environment and run on a BF-561 processor embedded in the ADSP BF-561 EZ-KIT LITE evaluation board (Analog Devices). In the image processing algorithm, Hough lines obtained from the Hough transform of the captured images are called candidate lane marks. Various elimination methods …

Design And Implementation Of A Microcontroller Based Wind Energy Conversion System, Mehmet Demi̇rtaş, Şeri̇f Şerefoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a dsPIC-controlled DC/DC boost converter and a wind turbine control system that tracks the maximum power point are designed and implemented. In practice, the energy generated by a permanent magnet synchronous wind turbine is applied to the load using a circuit that consists of a rectifier, boost converter, and protective load. The converter operates in the designed mode 35% more efficiently than in the normal operation mode. In addition, the wind turbine is protected from overvoltages in strong windy weather using the protective circuit. Experimental results show that the ripple value on the direct current belonging to …

Optimization Of Job Shop Scheduling Problems Using Modified Clonal Selection Algorithm, Yilmaz Atay, Hali̇fe Kodaz

Turkish Journal of Electrical Engineering and Computer Sciences

Artificial immune systems (AISs) are one of the artificial intelligence techniques studied a lot in recent years. AISs are based on the principles and mechanisms of the natural immune system. In this study, the clonal selection algorithm, which is used commonly in AISs, is modified. This algorithm is applied to job shop scheduling problems, which are one of the most difficult optimization problems. For applying application results to the optimum solution, parameter values giving the optimum solution are determined by analyzing the parameters in the algorithm. The obtained results are given in detail in the tables and figures. The best …

Study On Interior Permanent Magnet Synchronous Motors For Hybrid Electric Vehicle Traction Drive Application Considering Permanent Magnet Type And Temperature, Javad Soleimani, Abolfazl Vahedi, Abdolhossein Ejlali, Mohammadhossein Barzegari Bafghi

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, interior permanent magnet synchronous motors (Interior-PMSMs) have become known as a good candidate for hybrid electric vehicle (HEV) traction drive application due to their unique merits. However, the dynamic and steady-state behaviors of these motors are quite dependent on the permanent magnet (PM) type, configuration, and volume in rotor structures. This paper uses a novel structure of Interior-PMSMs for traction applications with fragmental buried rotor magnets in order to achieve low torque ripple, iron losses, and cogging torque. In this paper, first, the effect of the PM type on a d-q equivalent circuit model is examined. Next, the design …

A New Psfb Converter-Based Inverter Arc Welding Machine With High Power Density And High Efficiency, İsmai̇l Aksoy

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a high-performance single-phase inverter arc welding machine is presented. Power control of the developed welding machine is realized with a high-frequency, phase-shifted full bridge (PSFB) pulse-width modulation (PWM) converter. The PSFB PWM converter operates with soft switching at no load and full load. There is no need to use a passive snubber in the converter. Welding machine control is implemented with a digital signal processor (DSP) and phase-shift PWM IC. By means of the DSP, advanced arc welding functions and protection features such as short-circuit, over-current, and temperature protection are achieved. The current and voltage waveforms given …

Frequency-Emulated Uniform Cellular Automata, Hürevren Kiliç

Turkish Journal of Electrical Engineering and Computer Sciences

The notion of a frequency-emulated (f-emulated) uniform cellular automata (CA) that enables the behavior emulation of some elementary CA via memory usage is introduced. An algorithm that generates f-emulated uniform CA sets is developed and an upper bound for its output size is given. It is observed that traffic rule 184 together with its 2-emulator version, which generates the behavior of the known majority rule 232, performs the density classification task perfectly. Moreover, it is possible to use a 2-emulated uniform CA for the solution of the parity problem.

Dynamics, Stability, And Actuation Methods For Powered Compass Gait Walkers, Koray Kadi̇r Şafak

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, methods to achieve actively powered walking on level ground using a simple 2-dimensional walking model (compass-gait walker) are explored. The walker consists of 2 massless legs connected at the hip joint, a point mass at the hip, and an infinitesimal point mass at the feet. The walker is actuated either by applying equal joint torques at the hip and ankle, by an impulse applied at the toe off, immediately before the heel strike, or by the combination of both. It is shown that actuating the walker by equal joint torques at the hip and ankle on level …

Simulation Of A Flowing Snow Avalanche Using Molecular Dynamics, Deni̇zhan Güçer, Hali̇l Bülent Özgüç

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an approach for the modeling and simulation of a flowing snow avalanche, which is formed of dry and liquefied snow that slides down a slope, using molecular dynamics and the discrete element method. A particle system is utilized as a base method for the simulation and marching cubes with real-time shaders are employed for rendering. A uniform grid-based neighbor search algorithm is used for collision detection for interparticle and particle-terrain interactions. A mass-spring model of the collision resolution is employed to mimic the compressibility of the snow and particle attraction forces are put into use between the …

Fault Tolerant Broadcasting Analysis In Wireless Monitoring Networks, Akbar Ghaffarpour Rahbar

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless monitoring networks can be used for security applications such as the monitoring of narrow passages and operational fields. These networks can be designed based on sensor networks. In sensor networks, each node can hear a message and broadcast the message to its neighbor nodes. Nevertheless, nodes may fail, so that faulty nodes cannot hear or cannot transmit any message, where the locations of the faulty nodes are unknown and their failures are permanent. In this paper, the nodes are situated on a line or a square grid-based topology in a plane for security/monitoring applications. For each topology, 2 nonadaptive …

Online Feature Selection And Classification With Incomplete Data, Habi̇l Kalkan

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a classification system in which learning, feature selection, and classification for incomplete data are simultaneously carried out in an online manner. Learning is conducted on a predefined model including the class-dependent mean vectors and correlation coefficients, which are obtained by incrementally processing the incoming observations with missing features. A nearest neighbor with a Gaussian mixture model, whose parameters are also estimated from the trained model, is used for classification. When a testing observation is received, the algorithm discards the missing attributes on the observation and ranks the available features by performing feature selection on the model that …

Analysis Of Bfsa Based Anti-Collision Protocol In Lf, Hf, And Uhf Rfid Environments, Varun Bhogal

UNF Graduate Theses and Dissertations

Over the years, RFID (radio frequency identification) technology has gained popularity in a number of applications. The decreased cost of hardware components along with the recognition and implementation of international RFID standards have led to the rise of this technology.

One of the major factors associated with the implementation of RFID infrastructure is the cost of tags. Low frequency (LF) RFID tags are widely used because they are the least expensive. The drawbacks of LF RFID tags include low data rate and low range. Most studies that have been carried out focus on one frequency band only. This thesis presents …

Educating The Next Generation Of Cyberforensic Professionals, Mark Pollitt, Philip Craiger

Publications

This paper provides a historical overview of the development of cyberforensics as a scientific discipline, along with a description of the current state of training, educational programs, certification and accreditation. The paper traces the origins of cyberforensics, the acceptance of cyberforensics as a forensic science and its recognition as a component of information security. It also discusses the development of professional certification and standardized bodies of knowledge that have had a substantial impact on the discipline. Finally, it discusses the accreditation of cyberforensic educational programs, its linkage with the bodies of knowledge and its effect on cyberforensic educational programs.

Strategies To Counter Cyber Attacks: Cyber Threats And Critical Infrastructure Protection, Bilge Karabacak, Unal Tatar

All Faculty and Staff Scholarship

Today, cyber threats have the potential to harm critical infrastructures which may result in the interruption of life-sustaining services, catastrophic economic damages or severe degradation of national security. The diversity and complexity of cyber threats that exploit the vulnerabilities of critical infrastructures increase every day. . In order to lessen the potential harm of cyber threats, countermeasures have to be applied and the effectiveness of these countermeasures has to be monitored continuously. In this study, a brief definition and history of critical infrastructures are introduced. Cyber threats are examined in four fundamental categories. Vulnerabilities of critical infrastructures are categorized and …

Information Technology Sourcing Across Cultures: Preparing Leaders For Cross-Cultural Engagements And Implementing Best Practices With Cultural Sensitivity, Wayne Gordon Moran

Antioch University Dissertations & Theses

This research exercised a mixed method exploratory sequential design inquiry into the topical area of leadership behaviors and cross-cultural awareness that permeate successful global information technology (IT) outsource alliances. When IT is aligned with an entity's objectives, strategic technology leadership is actively engaged in governance, infrastructure architecture, planning, and cross-cultural collaboration. Bilateral contracting foster and forge interactive organizational cultures however, the advent of right shoring has introduced cultural complexity for IT leadership roles born of national, international, and sub-culture global dimensions. This research surfaced significant variations in IT professional opinions as to the leadership practices, cultural compatibility and service fulfillment …

An Information-Theoretic Image Quality Measure: Comparison With Statistical Similarity, Asmhan F. Hassan, Dong Cailin, Zahir M. Hussain

Research outputs 2014 to 2021

We present an information-theoretic approach for structural similarity for assessing gray scale image quality. The structural similarity measure SSIM, proposed in 2004, has been successflly used and verfied. SSIM is based on statistical similarity between the two images. However, SSIM can produce confusing results in some cases where it may give a non-trivial amount of similarity for two different images. Also, SSIM cannot perform well (in detecting similarity or dissimilarity) at low peak signal to noise ratio (PSNR). In this study, we present a novel image similarity measure, HSSIM, by using information - theoretic technique based on joint histogram. The …

Why Penetration Testing Is A Limited Use Choice For Sound Cyber Security Practice, Craig Valli, Andrew J. Woodward, Peter Hannay, Michael N. Johnstone

Research outputs 2014 to 2021

Penetration testing of networks is a process that is overused when demonstrating or evaluating the cyber security posture of an organisation. Most penetration testing is not aligned with the actual intent of the testing, but rather is driven by a management directive of wanting to be seen to be addressing the issue of cyber security. The use of penetration testing is commonly a reaction to an adverse audit outcome or as a result of being penetrated in the first place. Penetration testing used in this fashion delivers little or no value to the organisation being tested for a number of …

Application Of Cellular Neural Networks And Naive Bayes Classifier In Agriculture, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article describes the use of Cellular Neural Networks (a class of Ordinary Differential Equation (ODE)), Fourier Descriptors (FD) and NaiveBayes Classifier (NBC) for automatic identification of images of plant leaves. The novelty of this article is seen in the use of CNN for image segmentation and a combination FDs with NBC. The main advantage of the segmentation method is the computation speed compared with other edge operators such as canny, sobel, Laplacian of Gaussian (LoG). The results herein show the potential of the methods in this paper for examining different agricultural images and distinguishing between different crops and weeds …

Mobile Applications For Indian Agriculture Sector: A Case Study, Pratik Shah, Niketa Gandhi, Leisa Armstrong

Research outputs 2014 to 2021

Government, private agencies and the general public are often interested in the decisions made by the Indian farmers as they have large influences beyond the farm boundary. Over many years, the process of adoption of new technologies and policies in the Indian agricultural sector has received considerable academic attention highlighting the role of many social, financial and other influences on their decision making. The Indian government and other development agencies promote income generating projects as a way of encouraging growth through increased agricultural production and the protection of the natural resource base. The impact of new technology to economic growth …

An Artificial Neural Network For Predicting Crops Yield In Nepal, Tirtha Ranjeet, Leisa Armstrong

Research outputs 2014 to 2021

This paper examines the application of artificial neural networks (ANNs) for predicting crop yields for an agricultural region in Nepal. The neural network algorithm has become an effective data mining tool and the outcome produced by this algorithm is considered to be less error prone than other computer science techniques. The backpropagation algorithm which iteratively finds a suitable weight value is considered for computing the error derivative. Agricultural data was collected from thirteen years from paddy field cultivation in the Siraha district, an eastern region in Nepal, and used for this investigation of neural networks. Additionally, climatic parameters including rainfall, …

Geospatial Data Pre-Processing On Watershed Datasets: A Gis Approach, Sreedhar Nallan, Leisa Armstrong, Barry Croke, Amiya K. Tripathy

Research outputs 2014 to 2021

Spatial data mining helps to identify interesting patterns from the spatial data sets. However, geo spatial data requires substantial data pre-processing before data can be interrogated further using data mining techniques. Multi-dimensional spatial data has been used to explain the spatial analysis and SOLAP for pre-processing data. This paper examines some of the methods for pre-processing of the data using Arc GIS 10.2 and Spatial Analyst with a case study dataset of a watershed.

Decision Support System Data For Farmer Decision Making, Pornchai Taechatanasat, Leisa Armstrong

Research outputs 2014 to 2021

The capacity of farmers and agricultural scientists to be able to make in-season decisions is dependent on accurate climate, soil and plant data. This paper will provide a review of the types of environmental and crop data that can be collected by sensors which can used for decision support systems (DSS) or be further interrogated for real time data mining and analysis. This paper also presents a review of the data requirements for agricultural decision making by firstly reviewing decision support frameworks and agricultural DSSs, data acquisition, sensors for data acquisition and examples of data incorporation for agricultural DSSs.

A Network That Really Works - The Application Of Artificial Neural Networks To Improve Yield Predictions And Nitrogen Management In Western Australia, Jinsong Leng, Andreas Neuhaus, Leisa Armstrong

Research outputs 2014 to 2021

Yield predictions are notorious for being difficult due to many interdependent factors such as rainfall, soil properties, plant health, plant density etc. This study is based upon the author’s previously published work and extends its findings by further investigating the best mathematical solution to this dilemma. Artificial intelligence (AI) techniques have been applied to a large set of soil, plant, rainfall, and yield data from CSBP’s field research trial program. Here we further differentiate by investigate two ANN techniques, a genetic algorithm with back propagation neural networks (GA-BP-NN) and a particle swarm optimization with back propagation neural networks (PSO-BP-NN). Results …

A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong

Research outputs 2014 to 2021

Computer technologies have been shown to improve agricultural productivity in a number of ways. One technique which is emerging as a useful tool is image processing. This paper presents a short survey on using image processing techniques to assist researchers and farmers to improve agricultural practices. Image processing has been used to assist with precision agriculture practices, weed and herbicide technologies, monitoring plant growth and plant nutrition management. This paper highlights the future potential for image processing for different agricultural industry contexts.

Genetic Algorithm With Logistic Regression For Prediction Of Progression To Alzheimer's Disease, Piers Johnson, Luke Vandewater, William Wilson, Paul Maruff, Greg Savage, Petra Graham, Lance S. Macaulay, Kathryn A. Ellis, Cassandra Szoeke, Ralph N. Martins, Christopher Rowe, Colin L. Masters, David Ames, Ping Zhang

Research outputs 2014 to 2021

Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search …

Integrating Soil And Plant Tissue Tests And Using An Artificial Intelligence Method For Data Modelling Is Likely To Improve Decisions For In-Season Nitrogen Management, Andreas Neuhaus, Leisa Armstrong, Jinsong Leng, Dean Diepeveen, Geoff Anderson

Research outputs 2014 to 2021

This paper hypothesizes that there is value in combining soil, climate and plant tissue data to give more reliable advice on nitrogen top-ups in-season when compared with models that are currently available. The benefit of soil and climate data is to factor in N mineralisation and potential yield while plant test data is a more direct approach of yield estimates when considering firstly plant N uptake from the whole soil profile and secondly biomass (important yield component). Plant test data are closer to yield in time and space than soil test data, shortening the time period for any yield prognosis …

Small To Medium Enterprise Cyber Security Awareness: An Initial Survey Of Western Australian Business, Craig Valli, Ian C. Martinus, Michael N. Johnstone

Research outputs 2014 to 2021

Small to Medium Enterprises (SMEs) represent a large proportion of a nation’s business activity. There are studies and reports reporting the threat to business from cyber security issues resulting in computer hacking that achieve system penetration and information compromise. Very few are focussed on SMEs. Even fewer are focussed on directly surveying the actual SMEs themselves and attempts to improve SME outcomes with respect to cyber security. This paper represents research in progress that outlines an approach being undertaken in Western Australia with SMEs in the northwest metropolitan region of Perth, specifically within the large local government catchments of Joondalup …

Local And Semi-Global Feature-Correlative Techniques For Face Recognition, Asaad Noori Hashim, Zahir Hussain

Research outputs 2014 to 2021

Face recognition is an interesting field of computer vision with many commercial and scientific applications. It is considered as a very hot topic and challenging problem at the moment. Many methods and techniques have been proposed and applied for this purpose, such as neural networks, PCA, Gabor filtering, etc. Each approach has its weaknesses as well as its points of strength. This paper introduces a highly efficient method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in different views (poses) of facial images. Feature extraction techniques …

Frequency Estimation Of Single-Tone Sinusoids Under Additive And Phase Noise, Asmaa Nazar Almoosawy, Zahir Hussain, Fadel A. Murad

Research outputs 2014 to 2021

We investigate the performance of main frequency estimation methods for a single-component complex sinusoid under complex additive white Gaussian noise (AWGN) as well as phase noise (PN). Two methods are under test: Maximum Likelihood (ML) method using Fast Fourier Transform (FFT), and the autocorrelation method (Corr). Simulation results showed that FFT-method has superior performance as compared to the Corr-method in the presence of additive white Gaussian noise (affecting the amplitude) and phase noise, with almost 20dB difference.

An Information-Theoretic Measure For Face Recognition: Comparison With Structural Similarity, Asmhan Flieh Hassan, Zahir Hussain, Dong Cai-Lin

Research outputs 2014 to 2021

Automatic recognition of people faces is a challenging problem that has received significant attention from signal processing researchers in recent years. This is due to its several applications in different fields, including security and forensic analysis. Despite this attention, face recognition is still one among the most challenging problems. Up to this moment, there is no technique that provides a reliable solution to all situations. In this paper a novel technique for face recognition is presented. This technique, which is called ISSIM, is derived from our recently published information - theoretic similarity measure HSSIM, which was based on joint histogram. …

A Genetic Algorithm-Based Feature Selection, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article details the exploration and application of Genetic Algorithm (GA) for feature selection. Particularly a binary GA was used for dimensionality reduction to enhance the performance of the concerned classifiers. In this work, hundred (100) features were extracted from set of images found in the Flavia dataset (a publicly available dataset). The extracted features are Zernike Moments (ZM), Fourier Descriptors (FD), Lengendre Moments (LM), Hu 7 Moments (Hu7M), Texture Properties (TP) and Geometrical Properties (GP). The main contributions of this article are (1) detailed documentation of the GA Toolbox in MATLAB and (2) the development of a GA-based feature …