Computer Engineering Commons^™

Evolutionary Neural Networks For Improving The Prediction Performance Ofrecommender Systems, Berna Şeref, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems provide recommendations to users using background data such as ratings of users about items and features of items. These systems are used in several areas such as e-commerce, news websites, and article websites. By using recommender systems, customers are provided with relevant data as soon as possible and are able to make good decisions. There are more studies about recommender systems and improving their performance. In this study, prediction performances of neural networks are evaluated and their performances are improved using genetic algorithms. Performances obtained in this study are compared with those of other studies. After that, superiority …

Time-Oriented Interactive Process Miner: A New Approach For Time Prediction, İsmai̇l Yürek, Derya Bi̇rant, Özlem Ece Yürek, Kökten Ulaş Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

Everyday information systems collect a different kind of process instances of a business flow. As time goes on, the size of the collected data builds up speedily and constitutes a huge amount of data. It is a very challenging task to obtain valuable information and features of processes from such big data. Considering in advance, the trend and different features of the ongoing process are essential. Especially, time management is crucial in designing and conducting business processes. In this article, a novel process miner algorithm is proposed for time prediction, named time-oriented İnteractive process miner (T-IPM), which predicts the remaining …

Engraved Digit Detection Using Hog-Real Adaboost And Deep Neural Network, Tuan Linh Dang, Thang Cao, Yukinobu Hoshino

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a framework for recognizing sequences of digits engraved on steel plates. These digits are normally blurred, dirty, not clear, tilted, and sometimes overlapped by other digits. Several digits in a string with uneven spacing and different sizes are detected at the same time. The framework consists of two main components called histogram of oriented gradient-real AdaBoost module and deep neural network module. The first component is used to detect digit windows, and the second component is employed to recognize digits inside the detected windows. Experimental results demonstrated that the proposed framework could be a potential solution to …

Abnormal Behavior Detection Using Sparse Representations Through Sequentialgeneralization Of K-Means, Ahlam Aldhamari, Rubita Sudirman, Nasrul Humaimi Mahmood

Turkish Journal of Electrical Engineering and Computer Sciences

The potential capability to automatically detect and classify human behavior as either normal or abnormal events is an important aspect in intelligent monitoring/surveillance systems. This study presents a new high-performance framework for detecting behavioral abnormalities in video streams by utilizing only the patterns for normal behaviors. In this paper, we used a hybrid descriptor, called a foreground optical flow energy (FGOFE), which makes use of two effective motion techniques in order to extract the most descriptive spatiotemporal features in video sequences. The FGOFE descriptor can effectively capture both weak and sudden incidents in a scene. The sequential generalization of k-means …

Deep-Learning-Based Spraying Area Recognition System Forunmanned-Aerial-Vehicle-Based Sprayers, Shahbaz Khan, Muhammad Tufail, Muhammad Tahir Khan, Zubair Ahmed Khan, Shahzad Anwer

Turkish Journal of Electrical Engineering and Computer Sciences

Unmanned aerial vehicle (UAV)-based spraying system employing machine learning techniques is a recent advancement in precision agriculture for precise spraying, promoting saving chemicals (pesticide/herbicide), and enhancing their effectiveness. This study aims to develop an efficient deep learning system for UAV-based sprayers, which has the capability to accurately recognize spraying areas. A deep learning system is proposed and developed incorporating a faster region-based convolutional neural network (R-CNN) for the imagery collected. In order to develop a classifier for identifying spraying areas from nonspraying areas, four different agriculture croplands and orchards were considered. All the experiments were performed in agriculture fields through …

A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a new approach that combines stability and optimization in the design of proportional? integral (PI) controller of automatic voltage regulators (AVR) of synchronous generators with variable system parameters. Thanks to this approach, a PI controller, providing the desired performance and the stability of the AVR system, has been designed. The approach follows a method investigating the PI gain values to achieve the desired goals. In the first step of the study, a new stability boundary locus is calculated for the case in which AVR system?s parameters have changed. The stability boundary locus (SBL) method is a graphic-based …

Performance Evaluation Of A Power Allocation Algorithm Based On Dynamicblocklength Estimation For Urllc In The Multicarrier Downlink Noma Systems, Won Jae Ryu, Soo Young Shin

Turkish Journal of Electrical Engineering and Computer Sciences

This study investigates a power allocation algorithm using blocklength estimation by the finite blocklength (FBL) regime in a multicarrier downlink nonorthogonal multiple access (NOMA) system for ultrareliable low latency communication (URLLC) that is one of the services in 5G networks, requiring exceedingly high reliability and low latency. As NOMA systems can boost the capacity and increase the spectrum efficiency, it can be considered as a solution for URLLC. A multicarrier downlink NOMA system using blocklength estimation based on the FBL regime is proposed for effective resource allocation in this study. The FBL is used to derive the equation for dynamic …

A Novel Data Placement Strategy To Reduce Data Traffic During Run-Time, Sridevi Sridhar, Rhymend Uthariaraj Vaidyanathan

Turkish Journal of Electrical Engineering and Computer Sciences

High impact scientific applications processed in distributed data centers often involve big data. To avoid the intolerable delays due to huge data movements across data centers during processing, the concept of moving tasks to data was introduced in the last decade. Even after the realization of this concept termed as data locality, the expected quality of service was not achieved. Later, data colocality was introduced where data groupings were identified and then data chunks were placed wisely. However, the aspect of the expected data traffic during run time is generally not considered while placing data. To identify the expected data …

Performance Improvement Of The Shunt Active Power Filter Using A Novel Adaptivefiltering Approach, Abderrezzaq Zoghbi, Daoud Berkani

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces an efficient control approach to enhance harmonics mitigation performance of the shunt active power filter (SAPF). This approach is based on adaptive filters favored by their built-in automatic parameters adaptation capability. The proposed filter, which uses a variable leaky least mean square (VLLMS) adaptation, is applied with a modified instantaneous power PQ theory. This enhances its dynamic performance over the use of conventional time-invariant filters, and overcomes its limitations in the presence of nonsinusoidal voltage conditions. The studied SAPF model is simulated in MATLAB/SIMULINK with combinations of nonlinear and unbalanced loads. Simulation results indicate a significant improvement …

A Two-Stage Hair Region Localization Method For Guided Laser Hair Removal, Murat Avşar, İmam Şami̇l Yeti̇k

Turkish Journal of Electrical Engineering and Computer Sciences

Removal of hair using laser is a widely used method, where our goal is to permanently remove hair by using laser to cause heat in order to thermally damage the hair follicle. However, currently available laser hair removal systems affect the outer skin layers besides hair follicles. This is a disadvantage of classical methods with major health risks. We propose a method to overcome these health risks by guiding the laser beam only to automatically localized hair regions. This study aims to develop an automated feature-based hair region localization method as an integral part of the proposed hair removal system …

Evaluation Of Supervised Deep-Learning For Improved Pneumonia Diagnosis, Andrew Kalaani

College of Graduate Studies: Theses & Dissertations

Pneumonia is one of the leading causes of infections in the lung area and deaths worldwide. The mortality rate is 24.8% for patients over 70 years of age due to other health complications present along with it. In least fortunate countries, pneumonia can often times go untreated because of how cost extensive it is to diagnose, especially severe cases that cannot be seen by a plain X-ray. Other scanning methods can find the lung abnormality but are time-extensive and not cost effective. An autonomous approach however can help aid diagnosing pneumonia with a plain X-ray scan due to the structural …

Instrumentation, Modeling, And Sound Metamodeling Foundations For Complex Hybrid Systems, Natasha Amelia Jarus

Doctoral Dissertations

Many of our critical infrastructures, from power grids to water distribution networks, are complex hybrid systems that use software to control their non-trivial physical dynamics. These systems must be able to capably serve their purpose, while also being reliable, dependable, safe, secure, and efficient. Representation and analysis of these features requires the creation of several distinct models. These models may encode design goals or be derived from collected instrumentation data, reflecting both how a system ought to operate and how it does operate. It is essential to ensure that all of these models consistently and accurately describe the same system. …

A General Framework For Characterizing And Evaluating Attacker Models For Cps Security Assessment, Christopher S. Deloglos, Christopher Deloglos

Theses and Dissertations

Characterizing the attacker’s perspective is essential to assessing the security posture and resilience of cyber-physical systems. The attacker’s perspective is most often achieved by cyber-security experts (e.g., red teams) who critically challenge and analyze the system from an adversarial stance. Unfortunately, the knowledge and experience of cyber-security experts can be inconsistent leading to situations where there are gaps in the security assessment of a given system. Structured security review processes (such as TAM, Mission Aware, STPA-SEC, and STPA-SafeSec) attempt to standardize the review processes to impart consistency across an organization or application domain. However, with most security review processes, the …

Deep Learning Assisted Intelligent Visual And Vehicle Tracking Systems, Liang Xu

Theses and Dissertations

Sensor fusion and tracking is the ability to bring together measurements from multiple sensors of the current and past time to estimate the current state of a system. The resulting state estimate is more accurate compared with the direct sensor measurement because it balances between the state prediction based on the assumed motion model and the noisy sensor measurement. Systems can then use the information provided by the sensor fusion and tracking process to support more-intelligent actions and achieve autonomy in a system like an autonomous vehicle. In the past, widely used sensor data are structured, which can be directly …

Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar

UNF Graduate Theses and Dissertations

Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the …

A Surrogate Weather Generator For Estimating Natural Gas Design Day Conditions, David J. Kaftan, George Corliss, Richard J. Povinelli, Ronald H. Brown

Electrical and Computer Engineering Faculty Research and Publications

Natural gas customers rely upon utilities to provide gas for heating in the coldest parts of winter. Heating capacity is expensive, so utilities and end users (represented by commissions) must agree on the coldest day on which a utility is expected to meet demand. The return period of such a day is long relative to the amount of weather data that are typically available. This paper develops a weather resampling method called the Surrogate Weather Resampler, which creates a large dataset to support analysis of extremely infrequent events. While most current methods for generating weather data are based on simulation, …

Mitigating Insider Threats In A Cooperative Adaptive Cruise Control System Using Local Intra-Vehicle Data, Alexander Francis Colon

Graduate Theses, Dissertations, and Problem Reports (ETD)

With the rise of Connected-and-Automated-Vehicle (CAV) technologies on roadways, transportation networks have become increasingly connected through Vehicle-to-Everything (V2X) systems. With access to the additional data from V2X, modern cruise control systems like Adaptive Cruise Control (ACC) are further improved upon to develop systems like Cooperative ACC (CACC) which reduces traffic congestion and increases driver safety and energy efficiency. With that increased connectivity, previously closed vehicle systems are now vulnerable to new security threats which pose new technical challenges. Significant research has been done to strengthen the network against external threats such as denial-of-service attacks (DoS) or passive eavesdropping attacks using …

Class Distribution-Aware Adaptive Margins And Cluster Embedding For Classification Of Fruit And Vegetables At Supermarket Self-Checkouts, Khurram Hameed, Douglas Chai, Alexander Rassau

Research outputs 2014 to 2021

The complex task of vision based fruit and vegetables classification at a supermarket self-checkout poses significant challenges. These challenges include the highly variable physical features of fruit and vegetables i.e. colour, texture shape and size which are dependent upon ripeness and storage conditions in a supermarket as well as general product variation. Supermarket environments are also significantly variable with respect to lighting conditions. Attempting to build an exhaustive dataset to capture all these variations, for example a dataset of a fruit consisting of all possible colour variations, is nearly impossible. Moreover, some fruit and vegetable classes have significant similar physical …

Integration Of Robotic And Electro-Pneumatic Systems Using Advanced Control And Communication Schemes, Chinmay Kondekar

Dissertations, Master's Theses and Master's Reports

Modern industrial automation systems are designed by interconnecting various subsystems which work together to perform a process. The thesis project aims to integrate fragmented subsystems into a flexible and reconfigurable system through advanced communication protocols and perform a process to demonstrate the effectiveness of interconnected systems.

The system consists of three six-axis robots, one electro-pneumatic robot, and two conveyors connected using EthernetIP communication and hardwired connections. The interconnected system works together to perform machining of a workpiece using advanced control methods of CAD to robot path generation, central control through a PLC, and process control through HMI.

Standardized programming blocks …

Open-Source Tig-Based Metal 3d-Printing, Shane Oberloier

Dissertations, Master's Theses and Master's Reports

Metal 3-D printing has been relegated to high-cost proprietary high-resolution systems and low-resolution low-cost metal inert gas (MIG) systems. In order to provide a path to high-resolution, low-cost, metal 3-D printing, this manuscript proposes a new open source metal 3-D printer design based around a low-cost tungsten inert gas (TIG) welder coupled to a commercial open source self replicating rapid prototyper. Optimal printing parameters for the machine are acquired using a novel computational intelligence software. TIG has many advantages over MIG, such as having a low heat input, clean beads, and the potential for both high-resolution prints as well as …

Wireless Sensing - Enabler Of Future Wireless Technologies, Hali̇se Türkmen, Muhammad Sohai̇b J. Solai̇ja, Armed Tusha, Hüseyi̇n Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Withthe completion of the 5G standardization efforts, the wireless communication world has now turned tothe road ahead, the future wireless communication visions. One common vision is that future networks will be flexible,or able to accommodate an even richer variety of services with stringent, often conflicting requirements. This ambitiousfeat can only be accomplished with a ubiquitous awareness of the radio and physical environment. To this end, thispaper highlights the importance of wireless sensing as a means for radio environment awareness and surveys wirelesssensing methods under different domains. Then, a review of wireless sensing from a standardization perspective is given.These standardization efforts …

Internet Of Things Data Compression Based On Successive Data Grouping, Samer Sawalha, Ghazi Al-Naymat

Turkish Journal of Electrical Engineering and Computer Sciences

Internet of things (IoT) is a useful technology in different aspects, and it is widely used in many applications; however, this technology faces some major challenges which need to be solved, such as data management and energy saving. Sensors generate a huge amount of data that need to be transferred to other IoT layers in an efficient way to save the energy of the sensor because most of the energy is consumed in the data transmission process. Sensors usually use batteries to operate; thus, saving energy is very important because of the difficulty of replacing batteries of widely distributed sensors. …

Covid-19 Detection On Ibm Quantum Computer With Classical-Quantum Transferlearning, Erdi̇ Acar, İhsan Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

Diagnose the infected patient as soon as possible in the coronavirus 2019 (COVID-19) outbreak which is declared as a pandemic by the world health organization (WHO) is extremely important. Experts recommend CT imaging as a diagnostic tool because of the weak points of the nucleic acid amplification test (NAAT). In this study, the detection of COVID-19 from CT images, which give the most accurate response in a short time, was investigated in the classical computer and firstly in quantum computers. Using the quantum transfer learning method, we experimentally perform COVID-19 detection in different quantum real processors (IBMQx2, IBMQ-London and IBMQ-Rome) …

Effects Of Covid-19 On Electric Energy Consumption In Turkey And Ann-Basedshort-Term Forecasting, Harun Özbay, Adem Dalcali

Turkish Journal of Electrical Engineering and Computer Sciences

: Due to the coronavirus, millions of people worldwide carry out their work, education, shopping, culture, and entertainment activities from their homes now using the advantages of today's technology. Apart from this, patient care and follow-up are carried out with the help of electronic equipment especially in the institutions where health services are provided. It is important to provide a reliable electricity supply for humanity so that people can perform all these services. In this study, the outlook of energy in Turkey was examined. The current energy consumption and investments were examined. Then, the precautions by the government in the …

Application Of Fractional Order Pi Controllers On A Magnetic Levitation System, Erhan Yumuk, Müjde Güzelkaya, İbrahi̇m Eksi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Fractional order PI controllers based on two different analytical design methods are applied to a magnetic levitation system in this paper. The controller parameters are specified in order to fulfill specific frequency criteria. The first design method utilizes a unity feedback reference model whose forward path includes Bode's ideal loop transfer function. The second method uses the reference model that has been obtained via delayed Bode's ideal loop transfer function. The achievement of these two controllers are contrasted with each other on the magnetic levitation system using various criteria.

Development Of Computationally Efficient Biorthogonal Wavelets, Mehmet Cemi̇l Kale

Turkish Journal of Electrical Engineering and Computer Sciences

Daubechies 5-tap/3-tap (Daub 5/3) wavelet and Kale 5-tap/3-tap (Kale 5/3) wavelet are computationally efficient wavelets which can be implemented by bitwise shifts and additions in the lifting scheme. In this work, presented is a formulation for computationally efficient wavelet prediction (P) and update (U) filters of two-channel lifting structures. Their subband decomposition scheme counterparts are also given. This research bases itself on the Daub 5/3 and Kale 5/3 wavelets and develops a formula for wavelets (which can be implemented with bitwise shifts and additions) that are derived from these two wavelets. The proposed wavelets are tried on 16 test images …

Characterization Of Different Crowd Behaviors Using Novel Deep Learningframework, Abdullah Jaman Alzahrani, Sultan Daud Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Crowd behavior understanding is recognized as a complex problem due to unpredictable behavior of humans and complex interactions of individuals in groups. For crowd managers, it is crucial to understand the crowd dynamics to manage the crowd efficiently and effectively. Current practice of crowd management is based on manual analysis of the scene. Such manual analysis of the scene is a tedious job and usually prone to errors due to limited human capabilities. Therefore, the task of automatizing crowd analysis has received tremendous attention from the research community during the recent years. In this paper, we propose a deep model …

A New Method For Optimal Expansion Planning In Electrical Energy Distributionnetworks With Distributed Generation Resources Considering Uncertainties, Amir Masoud Mohaghegh, S Yaser Derakhshandeh, Abbas Kargar

Turkish Journal of Electrical Engineering and Computer Sciences

The present study aims to introduce a robust model for distribution network expansion planning considering system uncertainties. The proposed method determines optimal size and placement of distributed generation resources, as well as installation and reinforcement of feeders and substations. This model is designed to minimize cost and to determine the best time for the installation of equipment in the expansion planning. In the proposed expansion planning, the fuzzy logic theory is employed to model uncertainties of loads and energy price. Also, since the proposed model is a nonlinear and nonconvex optimization problem, a tri-stage algorithm is developed to solve it. …

Real-Time Measurements And Performance Analysis Of Closed-Loop Mimo Servicefor Mobile Operators, Engi̇n Zeydan, Ömer Dedeoğlu, Yekta Türk

Turkish Journal of Electrical Engineering and Computer Sciences

As fifth generation (5G) networks are starting to become commercial, user expectations in terms of new services become high as well. This signifies that mobile communications service providers need to build robust 5G new services as quickly and cost-efficiently as possible. Many new technologies rely on closed-loop (CL) and multiple input multiple output (MIMO) technologies due to emerging cooperation between nodes in next generation networks. In this paper, we first compare different multiantenna transmission modes namely: transmit diversity, open-loop (OL), and CL MIMO spatial multiplexing strategies to provide mobile network operator (MNO) services in terms of their characteristics, ,limitations and …

Analyzing The Performances Of Evolutionary Multi-Objective Optimizers On Designoptimization Of Robot Gripper Configurations, Murat Dörterler, Ümi̇t Ati̇la, Rafet Durgut, İsmai̇l Şahi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Robot grippers are widely used in a variety of areas requiring automation, precision, and safety. The performance of the grippers is directly associated with their design. In this study, four different multiobjective metaheuristic algorithms including particle swarm optimization (MOPSO), artificial algae algorithm (MOAAA), grey wolf optimizer (MOGWO) and nondominated sorting genetic algorithm (NSGA-II) were applied to two different configurations of highly nonlinear and multimodal robot gripper design problem including two objective functions and a certain number of constraints. The first objective is to minimize the difference between minimum and maximum forces for the assumed range in which the gripper ends …