Computer Engineering Commons^™

Motion Blur Image Deblurring Using Edge-Based Color Patches, Xixuan Zhao, Jiangming Kan

Turkish Journal of Electrical Engineering and Computer Sciences

The shaking of a camera can easily cause blurs in an image. Thus, deblurring is a problem that is worth solving and has always been an active research interest. The color information in an image is an important feature and contains clues for image deblurring that have not been widely exploited. In this paper, we present an efficient and stable blurring kernel estimation method by solving an energy function constructed by a weighted color approximation regularization term. The term is derived from a two-color model, and we use a defined weight to alleviate the color change through the blurring process. …

A Coordinated Dc Voltage Control Strategy For Cascaded Solid State Transformer With Star Configuration, Zhendong Ji, Yichao Sun, Cheng Jin, Jianhua Wang, Jianfeng Zhao

Turkish Journal of Electrical Engineering and Computer Sciences

Cascaded solid-state transformer (SST) can be directly connected to the high-voltage distribution grid, and it has broad applications in the future smart grid, traction locomotive, and renewable energy integration. However, the reliability of the cascaded SST is seriously influenced by the DC voltage and power imbalance issues with this configuration. This paper presents a coordinated DC voltage control strategy for cascaded SST with star configuration, in which the average DC voltage and the balancing DC voltage are controlled separately without current sensors in dual active bridge (DAB) modules. This strategy not only reduces the cost and the complexity of the …

A Novel Adaptive Hysteresis Dc-Dc Buck Converter For Portable Devices, Sung Sik Park, Ju Sang Lee, Sang Dae Yu

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a new technique that adjusts the hysteresis window depending on the variations in load current caused by a voltage-mode circuit to reduce the voltage and current ripples. Moreover, a compact current-sensing circuit is used to provide an accurate sensing signal for achieving fast hysteresis window adjustment. In addition, a zero-current detection circuit is also proposed to eliminate the reverse current at light loads. As a result, this technique reduces the voltage ripple below 8.08 mV$_{\rm pp}$ and the current ripple below 93.98 mA$_{\rm pp}$ for a load current of 500 mA. Circuit simulation is performed using 0.18 …

Fitting A Recurrent Dynamical Neural Network To Neural Spiking Data: Tackling The Sigmoidal Gain Function Issues, Reşat Özgür Doruk

Turkish Journal of Electrical Engineering and Computer Sciences

This is a continuation of a recent study (Doruk RO, Zhang K. Fitting of dynamic recurrent neural network models to sensory stimulus-response data. J Biol Phys 2018; 44: 449-469), where a continuous time dynamical recurrent neural network is fitted to neural spiking data. In this research, we address the issues arising from the inclusion of sigmoidal gain function parameters to the estimation algorithm. The neural spiking data will be obtained from the same model as that of Doruk and Zhang, but we propose a different model for identification. This will also be a continuous time recurrent neural network, but with …

Turkish Lexicon Expansion By Using Finite State Automata, Mustafa Burak Öztürk, Burcu Can Buğlalilar

Turkish Journal of Electrical Engineering and Computer Sciences

Turkish is an agglutinative language with rich morphology. A Turkish verb can have thousands of different word forms. Therefore, sparsity becomes an issue in many Turkish natural language processing (NLP) applications. This article presents a model for Turkish lexicon expansion. We aimed to expand the lexicon by using a morphological segmentation system by reversing the segmentation task into a generation task. Our model uses finite-state automata (FSA) to incorporate orthographic features and morphotactic rules. We extracted orthographic features by capturing phonological operations that are applied to words whenever a suffix is added. Each FSA state corresponds to either a stem …

Understanding Attribute And Social Circle Correlation In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud

Turkish Journal of Electrical Engineering and Computer Sciences

Social circles, groups, lists, etc. are functionalities that allow users of online social network (OSN) platforms to manually organize their social media contacts. However, this facility provided by OSNs has not received appreciation from users due to the tedious nature of the task of organizing the ones that are only contacted periodically. In view of the numerous benefits of this functionality, it may be advantageous to investigate measures that lead to enhancements in its efficacy by allowing for automatic creation of customized groups of users (social circles, groups, lists, etc). The field of study for this purpose, i.e. creating coarse-grained …

Power Quality Improvement Of Smart Microgrids Using Ems-Based Fuzzy Controlled Upqc, Ahmed A. Hossam-Eldin, Ahmed A. Mansour, Mohammed El-Gamal, Karim H. Youssef

Turkish Journal of Electrical Engineering and Computer Sciences

The prevalent power quality problems in smart microgrids and power distribution systems are voltage sag, voltage swell, and harmonic distortion. The achievement of pure sinusoidal waveform with proper magnitude and phase is currently a great research and development concern. The aim of this paper is to evaluate and mitigate the smart microgrid harmonics, voltage sag, and voltage swell throughout a 24-h cycle, taking into consideration the variation in solar power generation due to changes in irradiation received by photovoltaic cells, the variation in wind power generation due to changes in wind speed, and the variation of linear and nonlinear load …

Robust Compressed Domain Watermarking Algorithm For Video Protection And Authentication In Noisy Channels, Naveen Cheggoju, Vishal Satpute

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a robust and noise-resilient compressed domain video watermarking technique for data authentication and copyright protection. In recent years, watermarking has emerged as an essential technique to be equipped with data transmission. The main challenge pertaining to transmission is to protect the watermark from noise introduced by the channel. Here, we address this issue by watermark replication and by using the independent pass coding (INPAC) algorithm for compression. A replicated watermark is embedded into the video by the proposed blind video watermarking algorithm and then the watermarked video is compressed by the INPAC algorithm. The compressed video is …

Speech Enhancement Using Adaptive Thresholding Based On Gamma Distribution Of Teager Energy Operated Intrinsic Mode Functions, Özkan Arslan, Erkan Zeki̇ Engi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a new speech enhancement algorithm based on the adaptive threshold of intrinsic mode functions (IMFs) of noisy signal frames extracted by empirical mode decomposition. Adaptive threshold values are estimated by using the gamma statistical model of Teager energy operated IMFs of noisy speech and estimated noise based on symmetric Kullback--Leibler divergence. The enhanced speech signal is obtained by a semisoft thresholding function, which is utilized by threshold IMF coefficients of noisy speech. The method is tested on the NOIZEUS speech database and the proposed method is compared with wavelet-shrinkage and EMD-shrinkage methods in terms of segmental SNR …

A Novel Hybrid Teaching-Learning-Based Optimization Algorithm For The Classification Of Data By Using Extreme Learning Machines, Ender Sevi̇nç, Tansel Dökeroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Data classification is the process of organizing data by relevant categories. In this way, the data can be understood and used more efficiently by scientists. Numerous studies have been proposed in the literature for the problem of data classification. However, with recently introduced metaheuristics, it has continued to be riveting to revisit this classical problem and investigate the efficiency of new techniques. Teaching-learning-based optimization (TLBO) is a recent metaheuristic that has been reported to be very effective for combinatorial optimization problems. In this study, we propose a novel hybrid TLBO algorithm with extreme learning machines (ELM) for the solution of …

Comprehending The Safety Paradox And Privacy Concerns With Medical Device Remote Patient Monitoring, Marc Doyle

CCAC Theses and Dissertations

Medical literature identifies a number of technology-driven improvements in disease management such as implantable medical devices (IMDs) that are a standard treatment for candidates with specific diseases. Among patients using implantable cardiac defibrillators (ICD), for example, problems and issues are being discovered faster compared to patients without monitoring, improving safety. What is not known is why patients report not feeling safer, creating a safety paradox, and why patients identify privacy concerns in ICD monitoring.

There is a major gap in the literature regarding the factors that contribute to perceived safety and privacy in remote patient monitoring (RPM). To address this …

Multi-Objective Design Optimization Of A Permanent Magnet Axial Flux Eddy Current Brake, Rasul Tarvirdilu Asl, Hüseyi̇n Murat Yüksel, Ozan Keysan

Turkish Journal of Electrical Engineering and Computer Sciences

The main aim of this study is to optimize an axial flux eddy current damper to be used in a specific aviation application. Eddy current dampers are more advantageous compared to conventional mechanical dampers as they are maintenance-free due to contactless structure and have higher reliability, which is very desirable in aerospace applications. An initial eddy current brake prototype is manufactured and the test results are used to verify the 3-D finite element simulations. The effect of temperature on the brake performance is investigated. Finally, a multiobjective genetic algorithm optimization is applied to find the optimum pole number and geometric …

Lexicon-Based Emotion Analysis In Turkish, Mansur Alp Toçoğlu, Adi̇l Alpkoçak

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we proposed a lexicon for emotion analysis in Turkish for six emotional categories happiness, fear, anger, sadness, disgust, and surprise. Besides, we also investigated the effects of a lemmatizer and a stemmer, two term-weighting schemes, four lexicon enrichment methods, and a term selection approach for lexicon construction. To do this, we generated Turkish emotion lexicon based on a dataset, TREMO, containing 25,989 documents. We then preprocessed the documents to obtain dictionary and stem forms of each term using a lemmatizer and a stemmer. Afterwards, we proposed two different weighting schemes where term frequency, term-class frequency and mutual …

A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a new accuracy measurement model for the video stabilization method based on background motion that can accurately measure the performance of the video stabilization algorithm. Undesired residual motion present in the video can quantitatively be measured by the pixel by pixel background motion displacement between two consecutive background frames. First of all, foregrounds are removed from a stabilized video, and then we find the two-dimensional flow vectors for each pixel separately between two consecutive background frames. After that, we calculate a Euclidean distance between these two flow vectors for each pixel one by one, which …

A Smart Wireless Sensor Network Node For Fire Detection, Wajahat Khalid, Asma Sattar, Muhammad Ali Qureshi, Asjad Amin, Mobeen Ahmed Malik, Kashif Hussain

Turkish Journal of Electrical Engineering and Computer Sciences

Fires generally occur due to human carelessness and the change in environmental conditions. The uncontrolled fire results in death incidents of humans and animals as well as severe threats to the ecosystem. The preservation of the natural environment is important. The wireless sensor networks, widely used in different monitoring applications, is used in this work. For fire detection, we use flame, smoke, temperature, humidity, and light intensity sensors in our proposed network node which is low-cost, reduced-size, and power-efficient. The experiments are performed in a well-controlled real-time environment. The proposed node transmits the sensed data to the central node. The …

Early Reliability Assessment Of Component-Based Software System Using Coloredpetri Net, Amir Hosseinzadeh Mokarram, Ayaz Isazadeh, Habib Izadkhah

Turkish Journal of Electrical Engineering and Computer Sciences

Assessment of reliability in the early stages of software development from architectural models is one of the major challenges that many studies have addressed in this field in the last decade. The main drawbacks of existing methods are the following: 1) considering equal impact for all parts of the software architecture on system reliability, and 2) inability to determine the contribution of each part of the software in the system failure. This paper introduces the extended version of the colored petri net as an underlying verifiable model to evaluate the reliability of a software system. The proposed model enhances reliability …

Prioritizing Interdependent Software Requirements Using Tensor And Fuzzy Graphs, Negin Misaghian, Homayun Motameni, Mohsen Rabbani

Turkish Journal of Electrical Engineering and Computer Sciences

Owing to the special stance of prioritizing tasks in requirements engineering processes, and as the requirements are not independent in nature, considering their dependencies is essential during the prioritizing process. Although different classifications of dependency types among requirements exist, only a few approaches in the prioritization process consider such valuable data (dependency among equirements). To achieve a practical prioritization, this study proposes a method based on the effects of the requirement dependencies (increase/decrease cost of) on the value of prioritization provided by the tensor concept. Since the strengths of dependencies are also influential factors in the act of prioritization, The …

Extraction And Selection Of Statistical Harmonics Features For Electrical Appliancesidentification Using K-Nn Classifier Combined With Voting Rules Method, Fateh Ghazali, Abdenour Hacine-Gharbi, Philippe Ravier, Tayeb Mohamadi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel framework for electrical appliances identification using statistical harmonic features of current signals and the use of the k-NN classifier combined with a voting rule strategy. Harmonic coefficients are computed over time using short-time Fourier series of the current signals. From these sequences of coefficients, the mean, standard deviation, skewness, and kurtosis are computed, which provide the statistical harmonic features. This framework has three novelties: (i) selecting the best combination of statistical measures in the sense of classification rate (CR); (ii) combining the k-NN classifier with the voting rule method in order to search …

Softswitch: A Centralized Honeypot-Based Security Approach Using Software-Defined Switching For Secure Management Of Vlan Networks, Muhammet Baykara, Resul Daş

Turkish Journal of Electrical Engineering and Computer Sciences

Honeypot systems are traps for intruders which simulate real systems such as web, application, and database servers used in information systems. Using these systems, unauthorized and malicious access can be efficiently detected. Honeypot is an entity which acts as a source of valued information and its behavior can be monitored. The inability or difficulty of intrusion detection is a serious security problem in networks including virtual local area network (VLAN). According to the literature, the use of honeypots for intrusion detection and prevention in networks including VLAN is strongly recommended. In this paper, in order to provide security and to …

Increasing Bluetooth Low Energy Communication Efficiency By Presetting Protocol Parameters, Dusan Hatvani, Dominik Macko

Turkish Journal of Electrical Engineering and Computer Sciences

Standard protocols are important regarding the compatibility of devices provided by different vendors. However, specific applications have various requirements and do not always need all features offered by standard protocols, making them inefficient. This paper focuses on standard Bluetooth Low Energy modifications, reducing control overhead for the intended healthcare application. Specifically, the connection establishment, device pairing, and connection parameter negotiations have been targeted. The simulation-based experiments showed over 20 times reduction of control-overhead time preceding a data transmission. It does not just directly increase the energy efficiency of communication; it also prolongs the time for sensor-based end devices to spend …

Lightweight Signature Scheme To Protect Intellectual Properties Of Internet Of Things Applications In System On Chip Field-Programmable Gate Arrays, Kokila Jagadeesh, Ramasubramanian Natarajan

Turkish Journal of Electrical Engineering and Computer Sciences

Billions of smart objects in the edge devices offer advanced connectivity to networks which increase the security and complexity of the Internet of things (IoT) applications. To make such entities smarter heterogeneous intellectual property (IP) cores from multiple service providers are reused in system on chip platform. Enabling both chip and IP protection at post fabrication level is imperative. The IoT-based IP cores are signed with the hybrid physical unclonable function and finite state machine model to protect from cloning, misuse, unauthorized user access, and physical attacks. The extended finite-state machine is used to verify the signature, which reduces the …

Solving Vehicle Routing Problem For Multistorey Buildings Using Iterated Local Search, Osman Gökalp, Aybars Uğur

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicle routing problem (VRP) which is a well-known combinatorial optimisation problem that has many applications used in industry is also a generalised form of the travelling salesman problem. In this study, we defined and formulated the VRP in multistorey buildings (Multistorey VRP) for the first time and proposed a solving method employing iterated local search metaheuristic algorithm. This variant of VRP has a great potential for turning the direction of optimisation research and applications to the vertical cities area as well as the horizontal ones. Routes of part picking or placing vehicles/humans in multistorey plants can be minimised by this …

Abc-Based Stacking Method For Multilabel Classification, Weimin Ding, Shengli Wu

Turkish Journal of Electrical Engineering and Computer Sciences

Multilabel classification is a supervised learning problem wherein each individual instance is associated with multiple labels. Ensemble methods are effective in managing multilabel classification problems by creating a set of accurate, diverse classifiers and then combining their outputs to produce classifications. This paper presents a novel stacking-based ensemble algorithm, ABC-based stacking, for multilabel classification. The artificial bee colony algorithm, along with a single-layer artificial neural network, is used to find suitable meta-level classifier configurations. The optimization goal of the meta-level classifier is to maximize the average accuracy of classification of all the instances involved. We run an experiment on 10 …

Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee

Legacy Theses & Dissertations (2009 - 2024)

Deep Learning is the new state-of-the-art technology in Image Processing. We applied Deep Learning techniques for identification of diseases from Radiographs made publicly available by NIH. We applied some Feature Engineering approach to augment the data from Anterior-Posterior position to Posterior-Anterior position and vice-versa for all the diseases, at the same point we suppressed ‘No Finding’ radiographs which contributed to more than 50% (approximately 60,000) of the dataset to top 1000 images. We also prepared a model by adding a huge amount of noise to the augmented data, which if need be can be deployed at rural locations which lack …

Design And Simulation Of A Voltage Controlled Current Source For Electrical Impedance Tomography Applications, Farial Nur Maysha

Legacy Theses & Dissertations (2009 - 2024)

Electrical impedance tomography (EIT) is a simple, non-invasive and ionizing radiation-free imaging technology with potential application to medical diagnostics such as lung function, cardiac output, breast cancer, and cysts. Of the above imaging techniques, lung imaging has developed into the prime application for EIT. Because it presents an ill-posed inverse problem, EIT requires high-precision instrumentation and this thesis studies a new method for obtaining a high-precision current source and voltmeter for EIT. This thesis describes various simulation studies performed on the voltage-controlled current source (VCCS). The output impedance (Zo) of various types of Howland current source (HCS) including the basic …

Autonomous Spectrum Enforcement : A Blockchain Approach, Maqsood Ahamed Abdul Careem

Legacy Theses & Dissertations (2009 - 2024)

A core limitation in existing wireless technologies is the scarcity of spectrum, to support the exponential increase in Internet-connected and multimedia-capable mobile devices and the increasing demand for bandwidth-intensive services. As a solution, Dynamic Spectrum Access policies are being ratified to promote spectrum sharing for various spectrum bands and to improve the spectrum utilization. This poses an equally challenging problem of enforcing these spectrum policies. The distributed and dynamic nature of policy violations necessitates the use of autonomous agents to implement efficient and agile enforcement systems. The design of such a fully autonomous enforcement system is complicated due to the …

Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar

Legacy Theses & Dissertations (2009 - 2024)

Emotion forecasting is the task of predicting the future emotion of a speaker, i.e., the emotion label of the future speaking turn–based on the speaker’s past and current audio-visual cues. Emotion forecasting systems require new problem formulations that differ from traditional emotion recognition systems. In this thesis, we first explore two types of forecasting windows(i.e., analysis windows for which the speaker’s emotion is being forecasted): utterance forecasting and time forecasting. Utterance forecasting is based on speaking turns and forecasts what the speaker’s emotion will be after one, two, or three speaking turns. Time forecasting forecasts what the speaker’s emotion will …

Communications Using Deep Learning Techniques, Priti Gopal Pachpande

Legacy Theses & Dissertations (2009 - 2024)

Deep learning (DL) techniques have the potential of making communication systems

Nsu Student Handbook 2019-2020, Nova Southeastern University

College of Engineering and Computing Course Catalogs

No abstract provided.

College Of Computing And Engineering Graduate Catalog 2019-2020, Nova Southeastern University

College of Engineering and Computing Course Catalogs

No abstract provided.