Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 31 - 60 of 335

Full-Text Articles in Engineering

Classification Of Generic System Dynamics Model Outputs Via Supervised Time Series Pattern Discovery, Mert Edali, Mustafa Gökçe Baydoğan, Gönenç Yücel Jan 2019

Classification Of Generic System Dynamics Model Outputs Via Supervised Time Series Pattern Discovery, Mert Edali, Mustafa Gökçe Baydoğan, Gönenç Yücel

Turkish Journal of Electrical Engineering and Computer Sciences

System dynamics (SD) is a simulation-based approach for analyzing feedback-rich systems. An ideal SD modeling cycle requires evaluating the qualitative pattern characteristics of a large set of time series model output for testing, validation, scenario analysis, and policy analysis purposes. This traditionally requires expert judgement, which limits the extent of experimentation due to time constraints. Although time series recognition approaches can help to automate such an evaluation, utilization of them has been limited to a hidden Markov model classifier, namely the Indirect Structure Testing Software (ISTS) algorithm. Despite being used within several automated model-analysis tools, ISTS has several shortcomings. In …


Design And Fabrication Of A Dual-Polarized, Dual-Band Reflectarray Using Optimal Phase Distribution, Iman Aryanian, Arash Ahmadi, Mehdi Rabbani, Sina Hassibi, Majid Karimipour Jan 2019

Design And Fabrication Of A Dual-Polarized, Dual-Band Reflectarray Using Optimal Phase Distribution, Iman Aryanian, Arash Ahmadi, Mehdi Rabbani, Sina Hassibi, Majid Karimipour

Turkish Journal of Electrical Engineering and Computer Sciences

Two main factors limiting the reflectarray bandwidth are different phase slopes versus the frequency at every point on the aperture and the phase limitation of comprising elements at different frequencies. Considering these two factors, a novel design method is proposed to implement a dual-band, dual-polarized reflectarray antenna in X and Ku bands. An optimization algorithm is adopted to find the optimum phase for each unit cell on the reflectarray aperture. The best geometrical parameters of the phasing elements are suggested based on the phase variation of the element versus frequency and the element position with respect to the antenna feed. …


Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu Jan 2019

Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu

Turkish Journal of Electrical Engineering and Computer Sciences

Graph-based approaches have been widely employed to facilitate in analyzing network flow connectivity behaviors, which aim to understand the impacts and patterns of network events. However, existing approaches suffer from lack of connectivity-behavior information and loss of network event identification. In this paper, we propose network flow connectivity graphs (NFCGs) to capture network flow behavior for modeling social behaviors from network entities. Given a set of flows, edges of a NFCG are generated by connecting pairwise hosts who communicate with each other. To preserve more information about network flows, we also embed node-ranking values and edge-weight vectors into the original …


Cost-Effective Telemetry For Energy Network Of An Electricity Distribution Company: Part I, Asim Zaheer Ud Din, Yasar Ayaz, Mian Ilyas Ahmad Ahmad, Momena Hasan, Salman Masaud, Naveed Muhammad Jan 2019

Cost-Effective Telemetry For Energy Network Of An Electricity Distribution Company: Part I, Asim Zaheer Ud Din, Yasar Ayaz, Mian Ilyas Ahmad Ahmad, Momena Hasan, Salman Masaud, Naveed Muhammad

Turkish Journal of Electrical Engineering and Computer Sciences

We present a novel application of radio frequency wireless mesh network and general packet radio service technologies in a telemetry solution to measure power flow in the energy network of an electricity distribution company. The telemetry solution utilizes some selected circuits of grid stations and calculates total power consumed, total power imported, and total power exported by the distribution company. The selection of circuits for sensors installation is the key for reducing solution cost as compared to the case when sensors are installed on all the power output points. The framework involves installation of specially developed energy sensors (smart energy …


Optimal Range Of Loading For Operating A Fixed-Speed Wind Turbine Using A Self-Excited Induction Generator, Nassi̇m Iqteit, Gül Kurt, Beki̇r Çakir Jan 2019

Optimal Range Of Loading For Operating A Fixed-Speed Wind Turbine Using A Self-Excited Induction Generator, Nassi̇m Iqteit, Gül Kurt, Beki̇r Çakir

Turkish Journal of Electrical Engineering and Computer Sciences

In the present study, a new strategy of analysis was used to determine the optimal interval of a single-phase resistive load to operate a fixed-speed wind turbine. The essence of this optimal range is to enable the generator to have stable voltages and current balances, large power, and an acceptable frequency range, and also mitigate generator overheating. The generator windings and excitation capacitances were prepared according to the C-2C connection scheme with suitable values of excitation capacitances. The admittance matrix of the system was based on positive and negative sequence generator voltages and was calculated by symmetrical components theory. The …


Tapu: Test And Pick Up-Based $K$-Connectivity Restoration Algorithm For Wireless Sensor Networks, Vahi̇d Khali̇lpour Akram, Orhan Dağdevi̇ren Jan 2019

Tapu: Test And Pick Up-Based $K$-Connectivity Restoration Algorithm For Wireless Sensor Networks, Vahi̇d Khali̇lpour Akram, Orhan Dağdevi̇ren

Turkish Journal of Electrical Engineering and Computer Sciences

A $k$-connected wireless sensor network remains connected if any $k$-1 arbitrary nodes stop working. The aim of movement-assisted $k$-connectivity restoration is to preserve the $k$-connectivity of a network by moving the nodes to the necessary positions after possible failures in nodes. This paper proposes an algorithm named TAPU for $k$-connectivity restoration that guarantees the optimal movement cost. Our algorithm improves the time and space complexities of the previous approach (MCCR) in both best and worst cases. In the proposed algorithm, the nodes are classified into safe and unsafe groups. Failures of safe nodes do not change the $k$ value of …


Turkish Lexicon Expansion By Using Finite State Automata, Mustafa Burak Öztürk, Burcu Can Buğlalilar Jan 2019

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 …


Multi-Objective Design Optimization Of A Permanent Magnet Axial Flux Eddy Current Brake, Rasul Tarvirdilu Asl, Hüseyi̇n Murat Yüksel, Ozan Keysan Jan 2019

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 …


Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan Jan 2019

Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan

Turkish Journal of Electrical Engineering and Computer Sciences

Determining the category of a text document from its semantic content is highly motivated in the literature and it has been extensively studied in various applications. Also, the compact representation of the text is a fundamental step in achieving precise results for the applications and the studies are generously concentrated to improve its performance. In particular, the studies which exploit the aggregation of word-level representations are the mainstream techniques used in the problem. In this paper, we tackle text representation to achieve high performance in different text classification tasks. Throughout the paper, three critical contributions are presented. First, to encode …


Multiscanning Mode Laser Scanning Confocal Microscopy System, Mert Aktürk, Gökhan Gümüş, Baykal Sarioğlu, Yi̇ği̇t Dağhan Gökdel Jan 2019

Multiscanning Mode Laser Scanning Confocal Microscopy System, Mert Aktürk, Gökhan Gümüş, Baykal Sarioğlu, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a table-top, reflective mode, laser scanning confocal microscopy system that is capable of scanning the target specimen alternately through various scanning devices and methods is proposed. We have developed a laser scanning confocal microscopy system to utilize combinations of various scanning devices and methods and to be able to characterize the optical performance of different scanners and micromirrors that are frequently used in scanning microscopy systems such as multiphoton microscopy, optical coherence tomography, or confocal microscopy. By integrating the scanner to be characterized on the same optical path with a galvanometric scan mirror, which is the conventional …


A New Spectral Estimation-Based Feature Extraction Method For Vehicle Classification In Distributed Sensor Networks, Erdem Köse, Ali̇ Köksal Hocaoğlu Jan 2019

A New Spectral Estimation-Based Feature Extraction Method For Vehicle Classification In Distributed Sensor Networks, Erdem Köse, Ali̇ Köksal Hocaoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Ground vehicle detection and classification with distributed sensor networks is of growing interest for border security. Different sensing modalities including electro-optical, seismic, and acoustic were evaluated individually and in combination to develop a more efficient system. Despite previous works that mostly studied frequency-domain features and acoustic sensors, in this work we analyzed the classification performance for both frequency and time-domain features and seismic and acoustic modalities. Despite their infrequent use, we show that when fused with frequency-domain features, time-domain features improve the classification performance and reduce the false positive rate, especially for seismic signals. We investigated the performance of seismic …


Structure Tensor Adaptive Total Variation For Image Restoration, Surya Prasath, Dang Nh Thanh Jan 2019

Structure Tensor Adaptive Total Variation For Image Restoration, Surya Prasath, Dang Nh Thanh

Turkish Journal of Electrical Engineering and Computer Sciences

Image denoising and restoration is one of the basic requirements in many digital image processing systems. Variational regularization methods are widely used for removing noise without destroying edges that are important visual cues. This paper provides an adaptive version of the total variation regularization model that incorporates structure tensor eigenvalues for better edge preservation without creating blocky artifacts associated with gradient-based approaches. Experimental results on a variety of noisy images indicate that the proposed structure tensor adaptive total variation obtains promising results and compared with other methods, gets better structure preservation and robust noise removal.


Polyhedral Conic Kernel-Like Functions For Svms, Gürkan Öztürk, Emre Çi̇men Jan 2019

Polyhedral Conic Kernel-Like Functions For Svms, Gürkan Öztürk, Emre Çi̇men

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we propose a new approach that can be used as a kernel-like function for support vector machines (SVMs) in order to get nonlinear classification surfaces. We combined polyhedral conic functions (PCFs) with the SVM method. To get nonlinear classification surfaces, kernel functions are used with SVMs. However, the parameter selection of the kernel function affects the classification accuracy. Generally, in order to get successful classifiers which can predict unknown data accurately, best parameters are explored with the grid search method which is computationally expensive. We solved this problem with the proposed method. There is no need to …


Understanding Attribute And Social Circle Correlation In Social Networks, Pranav Nerurkar, Madhav Chandane, Sunil Bhirud Jan 2019

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 …


A Fast And Memory-Efficient Two-Pass Connected-Component Labeling Algorithm For Binary Images, Bilal Bataineh Jan 2019

A Fast And Memory-Efficient Two-Pass Connected-Component Labeling Algorithm For Binary Images, Bilal Bataineh

Turkish Journal of Electrical Engineering and Computer Sciences

Connected-component labeling is an important process in image analysis and pattern recognition. It aims to deduct the connected components by giving a unique label value for each individual component. Many algorithms have been proposed, but they still face several problems such as slow execution time, falling in the pipeline, requiring a huge amount of memory with high resolution, being noisy, and giving irregular images. In this work, a fast and memory-efficient connected-component labeling algorithm for binary images is proposed. The proposed algorithm is based on a new run-base tracing method with a new resolving process to find the final equivalent …


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 Jan 2019

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 …


A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh Jan 2019

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 …


Performance Tuning For Machine Learning-Based Software Development Effort Prediction Models, Egemen Ertuğrul, Zaki̇r Baytar, Çağatay Çatal, Ömer Can Muratli Jan 2019

Performance Tuning For Machine Learning-Based Software Development Effort Prediction Models, Egemen Ertuğrul, Zaki̇r Baytar, Çağatay Çatal, Ömer Can Muratli

Turkish Journal of Electrical Engineering and Computer Sciences

Software development effort estimation is a critical activity of the project management process. In this study, machine learning algorithms were investigated in conjunction with feature transformation, feature selection, and parameter tuning techniques to estimate the development effort accurately and a new model was proposed as part of an expert system. We preferred the most general-purpose algorithms, applied parameter optimization technique (GridSearch), feature transformation techniques (binning and one-hot-encoding), and feature selection algorithm (principal component analysis). All the models were trained on the ISBSG datasets and implemented by using the scikit-learn package in the Python language. The proposed model uses a multilayer …


Robust Compressed Domain Watermarking Algorithm For Video Protection And Authentication In Noisy Channels, Naveen Cheggoju, Vishal Satpute Jan 2019

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 Jan 2019

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 …


Online Network Coding-Based Multicast Routing In Multichannel Multiradio Wireless Mesh Networks, Leili Farzinvash Jan 2019

Online Network Coding-Based Multicast Routing In Multichannel Multiradio Wireless Mesh Networks, Leili Farzinvash

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we consider the problem of online multicast routing in multichannel multiradio wireless mesh networks (WMNs). We propose an efficient online algorithm, namely zone-based multicast routing (ZBMR), which exploits network coding and wireless broadcast advantage. In the proposed algorithm, to investigate the acceptance of an arrived session in polynomial time, the WMN is divided into some zones. The derived zones are processed sequentially, where the zone processing is defined as connecting the receivers in a given zone to the session. The main challenge in this scheme is to enable data transmission to the receivers in each zone. If …


Low-Latency And Energy-Efficient Scheduling In Fog-Based Iot Applications, Dadmehr Rahbari, Mohsen Nickray Jan 2019

Low-Latency And Energy-Efficient Scheduling In Fog-Based Iot Applications, Dadmehr Rahbari, Mohsen Nickray

Turkish Journal of Electrical Engineering and Computer Sciences

In today's world, the internet of things (IoT) is developing rapidly. Wireless sensor network (WSN) as an infrastructure of IoT has limitations in the processing power, storage, and delay for data transfer to cloud. The large volume of generated data and their transmission between WSNs and cloud are serious challenges. Fog computing (FC) as an extension of cloud to the edge of the network reduces latency and traffic; thus, it is very useful in IoT applications such as healthcare applications, wearables, intelligent transportation systems, and smart cities. Resource allocation and task scheduling are the NP-hard issues in FC. Each application …


Farsi Document Image Recognition System Using Word Layout Signature, Cem Ergün, Sajedeh Norozpour Jan 2019

Farsi Document Image Recognition System Using Word Layout Signature, Cem Ergün, Sajedeh Norozpour

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a new representation of Farsi words is proposed to present the keyword spotting problems in Farsi document image retrieval. In this regard, we define a signature for each Farsi word based on the word connected component layout. The mentioned signature is shown as boxes, and then, by sketching vertical and horizontal lines, we construct a grid of each word to provide a new descriptor. One of the advantages of this method is that it can be used for both handwritten and machine-printed texts. Finally, to evaluate the performance of our system in comparison to other methods, a …


Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan Jan 2019

Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

In dynamic graphs, edge weights of the graph change with time and solving the shortest path problem in such graphs is an important real-world problem. The studies in the literature require excessive computational time for computing the dynamic shortest path since determining changing edge weights is difficult especially when the graph size becomes large. In this paper, we propose a dynamic bio-inspired algorithm for finding the dynamic shortest path for large graphs based on Physarum Solver, which is a shortest path algorithm for static graphs. The proposed method is evaluated using three different large graph models representing diverse real-life applications. …


Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon Jan 2019

Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon

Turkish Journal of Electrical Engineering and Computer Sciences

A bitmap-based index is an effective and efficient indexing method for answering selective queries in a read-only environment. It offers improved query execution time by applying low-cost Boolean operators on the index directly, before accessing raw data. A drawback of the bitmap index is that index size increases with the cardinality of indexed attributes, which additionally has an impact on a query execution time. This impact is related to an increase of query execution time due to the scanning of bitmap vectors to answer the queries. In this paper, we propose a new encoding bitmap index, called the HyBiX bitmap …


A Novel Hybrid Teaching-Learning-Based Optimization Algorithm For The Classification Of Data By Using Extreme Learning Machines, Ender Sevi̇nç, Tansel Dökeroğlu Jan 2019

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 …


Triangular Slotted Ground Plane: A Key To Realizing High-Gain, Cross-Polarization-Free Microstrip Antenna With Improved Bandwidth, Abhijyoti Ghosh, Banani Basu Jan 2019

Triangular Slotted Ground Plane: A Key To Realizing High-Gain, Cross-Polarization-Free Microstrip Antenna With Improved Bandwidth, Abhijyoti Ghosh, Banani Basu

Turkish Journal of Electrical Engineering and Computer Sciences

A simple rectangular microstrip antenna with triangular slotted ground plane has been studied both theoretically and experimentally to improve shortcomings like low gain (5 - 6 dBi), narrow bandwidth (3% - 4%), and poor copolarization (CP) to cross-polarization (XP) isolation, i.e. polarization purity (typically 10 - 12 dB), of conventional rectangular microstrip patch antennas. By placing two pairs of triangular shaped slots on the ground plane just below the nonradiating edges of the patch, high gain (around 9 dBi) and more than 22 dB polarization purity over a wide elevation angle has been achieved. The proposed antenna covers almost the …


Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado Jan 2019

Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, a watermarking framework to authenticate and protect the copyright that prevents the visualization of nonauthorized anaglyph images is proposed. Designed scheme embeds a binary watermark and the Blue channel of the anaglyph image into the discrete cosine transform domain of the original image. The proposed method applies the quantization index modulation-dither modulation algorithm and a combination of Bose-Chaudhuri-Hocquenghem with repetition codes, which permit to increase the capability in recovering the watermark. Additionally, Hash algorithm is used to scramble the component where the watermark should be embedding, guaranteeing a higher security performance of the scheme. This new technique …


Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang Jan 2019

Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, features extracted by convolutional neural networks (CNNs) are popularly used for image retrieval. In CNN representation, high-level features are usually chosen to represent the images in coarse-grained datasets, while mid-level features are successfully applied to describe the images for fine-grained datasets. In this paper, we combine these different levels of features as a joint feature to propose a robust representation that is suitable for both coarse-grained and fine-grained image retrieval datasets. In addition, in order to solve the problem that the efficiency of image retrieval is influenced by the dimensionality of indexing, a unified subspace learning model named spectral …


Plant Disease And Pest Detection Using Deep Learning-Based Features, Muammer Türkoğlu, Davut Hanbay Jan 2019

Plant Disease And Pest Detection Using Deep Learning-Based Features, Muammer Türkoğlu, Davut Hanbay

Turkish Journal of Electrical Engineering and Computer Sciences

The timely and accurate diagnosis of plant diseases plays an important role in preventing the loss of productivity and loss or reduced quantity of agricultural products. In order to solve such problems, methods based on machine learning can be used. In recent years, deep learning, which is especially widely used in image processing, offers many new applications related to precision agriculture. In this study, we evaluated the performance results using different approaches of nine powerful architectures of deep neural networks for plant disease detection. Transfer learning and deep feature extraction methods are used, which adapt these deep learning models to …