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2019

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Articles 3511 - 3540 of 3906

Full-Text Articles in Computer Sciences

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.

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A Generalized Switching Function-Based Discontinuous Space Vector Modulation Technique For Unbalanced Two-Phase Three-Leg Inverters, Watcharin Srirattanawichaikul Jan 2019

A Generalized Switching Function-Based Discontinuous Space Vector Modulation Technique For Unbalanced Two-Phase Three-Leg Inverters, Watcharin Srirattanawichaikul

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a discontinuous space vector modulation technique for unbalanced two-phase three-leg inverters. This technique is based on the shift-angle and generalized modulation algorithm obtained for generating the unbalanced two-phase output voltage. Furthermore, the discontinuous switching sequence intends to improve the commutations of power switching devices in each inverter leg that achieves a minimum number of switching state changes in one sampling cycle. Therefore, the switch commutations can be reduced by one-third in one main period. The step-by-step procedure of the modulation algorithm for easy implementation in a digital control platform is discussed. The performance of the developed modulation …

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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 …

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A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci Jan 2019

A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci

Turkish Journal of Electrical Engineering and Computer Sciences

The rainfall amount observed at a given location mostly depend on the cloud density, which can be quantified with the reflectivity values observed by meteorology weather radars. In this study, we aim to estimate the rainfall amount using a Kalman filter with radar reflectivity measurements. We first assume that the amount of rainfall observed at automatic weather observation stations (AWOSs) are elements of an unknown state vector and consider the Kalman filter process model as the true rainfall amounts observed at these AWOSs over time. For the measurement model of the Kalman filter, we use the radar reflectivity values observed …

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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 …

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Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang Jan 2019

Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, large-scale solar farms are being rapidly integrated in electrical grids all over the world. However, the photovoltaic (PV) output power is highly intermittent in nature and can also be correlated with other solar farms located at different places. Moreover, the increasing PV penetration also results in large solar forecast error and its impact on power system stability should be estimated. The effects of these quantities on small-signal stability are difficult to quantify using deterministic techniques but can be conveniently estimated using probabilistic methods. For this purpose, the authors have developed a method of probabilistic analysis based on combined cumulant …

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An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N Jan 2019

An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N

Turkish Journal of Electrical Engineering and Computer Sciences

Researchers train and build specific models to classify the presence and absence of a disease and the accuracy of such classification models is continuously improved. The process of building a model and training depends on the medical data utilized. Various machine learning techniques and tools are used to handle different data with respect to disease types and their clinical conditions. Classification is the most widely used technique to classify disease and the accuracy of the classifier largely depends on the attributes. The choice of the attribute largely affects the diagnosis and performance of the classifier. Due to growing large volumes …

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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 …

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A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan Jan 2019

A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan

Turkish Journal of Electrical Engineering and Computer Sciences

Sentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across to the people about an object or event. It generally uses natural language processing and/or artificial intelligence techniques for processing electronic documents and mining the opinion specified in the content. In recent years, researchers have conducted many successful sentiment analysis studies for the English language which consider many words and word groups that set emotion polarities arising from the English grammar structure, and then use datasets to test their performance. However, there are only a limited number of studies for the Turkish …

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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 …

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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 …

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An Improved Form Of The Ant Lion Optimization Algorithm For Image Clustering Problems, Meti̇n Toz Jan 2019

An Improved Form Of The Ant Lion Optimization Algorithm For Image Clustering Problems, Meti̇n Toz

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an improved form of the ant lion optimization algorithm (IALO) to solve image clustering problem. The improvement of the algorithm was made using a new boundary decreasing procedure. Moreover, a recently proposed objective function for image clustering in the literature was also improved to obtain well-separated clusters while minimizing the intracluster distances. In order to accurately demonstrate the performances of the proposed methods, firstly, twenty-three benchmark functions were solved with IALO and the results were compared with the ALO and a chaos-based ALO algorithm from the literature. Secondly, four benchmark images were clustered by IALO and the …

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A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇ Jan 2019

A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a hybrid model composed of multiple prediction algorithms and an autoregressive moving average (ARMA) module for the thickness prediction. In order to attain higher accuracy, the prediction algorithms were globally combined by simple voting to reduce the effect of the inductive bias imposed by each algorithm on the dataset. The global multiexpert combination (GMEC) system included the multilayer perceptron neural network (MLPNN), radial basis function network (RBFN), multiple linear regression (MLR), and support vector machines (SVM) algorithms. The proposed hybrid model extends the GMEC system by integrating an ARMA module for the output. On the test dataset, …

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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 …

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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. …

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An Approach To Improve The Performance Of Cooperative Unmanned Vehicle Team, Ömer Ci̇han Kivanç Jan 2019

An Approach To Improve The Performance Of Cooperative Unmanned Vehicle Team, Ömer Ci̇han Kivanç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a method based on optimal energy management is proposed in order to improve the operational and tactical abilities of collaborative unmanned vehicle teams. Collaborative unmanned systems are used in surveillance, tracking, and military operations. The optimal assignment of these tasks requires cooperation among the vehicles in order to generate a strategy that is efficient with respect to overall mission duration and satisfies all problem constraints. The key motivation behind this paper is to design an unmanned vehicle team that mitigates the disadvantages caused by the structures and characteristics of unmanned ground vehicles (UGVs) and unmanned aerial vehicles …

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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 …

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Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç Jan 2019

Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we describe histogram matching, a metric for measuring the distance of two datasets with exactly the same features, and embed it into a mixed integer programming formulation to partition a dataset into fixed size training and test subsets. The partition is done such that the pairwise distances between the dataset and the subsets are minimized with respect to histogram matching. We then conduct a numerical study using a well-known machine learning dataset. We demonstrate that the training set constructed with our approach provides feature distributions almost the same as the whole dataset, whereas training sets constructed via …

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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 …

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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 …

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Efficient Features For Smartphone-Based Iris Recognition, Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran, Pawan Dubey Jan 2019

Efficient Features For Smartphone-Based Iris Recognition, Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran, Pawan Dubey

Turkish Journal of Electrical Engineering and Computer Sciences

Iris recognition has widely been used in personal authentication problems. Recent advances in iris recognition through visible wavelength images have paved the way for the use of this technology in smartphones. Smartphone-based iris recognition can be of significant use in financial transactions and secure storage of sensitive information. This paper presents a hybrid representation scheme for iris recognition in mobile devices. The scheme is called hybrid because it firstly makes use of Gabor wavelets to reveal the texture present in the normalized iris images, and then extracts statistical features from different partitions of Gabor-processed images. The standard mobile-iris database, called …

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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 …

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Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural Jan 2019

Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural

Turkish Journal of Electrical Engineering and Computer Sciences

Traditional machine learning algorithms assume that the training and test data have the same distribution, while this assumption does not necessarily hold in real applications. Domain adaptation methods take into account the deviations in data distribution. In this work, we study the problem of domain adaptation on graphs. We consider a source graph and a target graph constructed with samples drawn from data manifolds. We study the problem of estimating the unknown class labels on the target graph using the label information on the source graph and the similarity between the two graphs. We particularly focus on a setting where …

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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 …

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A Hybrid Of Tropical-Singular Value Decomposition Method For Salt And Pepper Noise Removal, Achmad Abdurrazzaq, Ismail Mohd, Ahmad Kadri Junoh, Zainab Yahya Jan 2019

A Hybrid Of Tropical-Singular Value Decomposition Method For Salt And Pepper Noise Removal, Achmad Abdurrazzaq, Ismail Mohd, Ahmad Kadri Junoh, Zainab Yahya

Turkish Journal of Electrical Engineering and Computer Sciences

The unknown information contained in an image that causes the change of information in the image is called noise. In this paper, we propose a new method for removing salt and pepper noise by using singular value decomposition and the concept of tropical algebra operations. To determine the performance of the proposed method, 20 test images are used as samples. Then three different image quality assessments are used: peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and image enhancement factor (IEF). In addition, six different filtering methods, i.e. MF, DWMF, PSMF, MDBUTM, NAFSM, and BPDF, are used to compare the performance …

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A Joint Image Dehazing And Segmentation Model, Haider Ali, Awal Sher, Nosheen Zikria, Lavdi̇e Rada Ülgen Jan 2019

A Joint Image Dehazing And Segmentation Model, Haider Ali, Awal Sher, Nosheen Zikria, Lavdi̇e Rada Ülgen

Turkish Journal of Electrical Engineering and Computer Sciences

Objects and their feature identification in hazy or foggy weather conditions has been of interest in the last decades. Improving image visualization by removing weather influence factors for easy image postprocessing, such as object detection, has benefits for human assistance systems. In this paper, we propose a novel variational model that will be capable of jointly segmenting and dehazing a given image. The proposed model incorporates atmospheric veil estimation and locally computed denoising constrained surfaces into a level set function by performing a robust and efficient image dehazing and segmentation scheme for both gray and color outdoor images. The proposed …

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Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding Jan 2019

Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding

Turkish Journal of Electrical Engineering and Computer Sciences

Temporal segmentation of facial expression sequences is important to understand and analyze human facial expressions. It is, however, challenging to deal with the complexity of facial muscle movements by finding a suitable metric to distinguish among different expressions and to deal with the uncontrolled environmental factors in the real world. This paper presents a two-step unsupervised segmentation method composed of rough segmentation and fine segmentation stages to compute the optimal segmentation positions in video sequences to facilitate the segmentation of different facial expressions. The proposed method performs localization of facial expression patches to aid in recognition and extraction of specific …

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Can Additional Spectral Bands Be Estimated From Aerial Color Images?, Muhammet Ali̇ Dede, Erchan Aptoula, Yakup Genç Jan 2019

Can Additional Spectral Bands Be Estimated From Aerial Color Images?, Muhammet Ali̇ Dede, Erchan Aptoula, Yakup Genç

Turkish Journal of Electrical Engineering and Computer Sciences

Inspired by the surprising performances of deep generative models, in this paper we present the preliminary results of an overly ambitious task: estimating computationally the additional spectral bands of a color aerial image. We have harnessed the expressive power of deep generative models to estimate the distribution of mostly infrared bands of aerial scenes, using only color RGB channels as input. Our approach has been tested from multiple aspects, including the reconstruction error of the additional bands and the effect of estimated bands on scene classification performance, as well as through the transfer potential of the trained network to a …

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Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh Jan 2019

Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, an optimized bilevel brain tumor diagnostic system for identifying the tumor type at the first level and grade of the identified tumor at the second level is proposed using genetic algorithm, decision tree, and fuzzy rule-based approach. The dataset is composed of axial MRI of brain tumor types and grades. From the images, various features such as first and second order statistical and textural features are extracted (26 features). In the first level, tumor type classification was done using decision tree constructed with all features. Further evolutionary computing using genetic algorithms (GA) was applied to select the …

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An Efficient Retrieval Algorithm Of Encrypted Speech Based On Inverse Fast Fourier Transform And Measurement Matrix, Qiuyu Zhang, Zixian Ge, Liang Zhou, Yongbing Zhang Jan 2019

An Efficient Retrieval Algorithm Of Encrypted Speech Based On Inverse Fast Fourier Transform And Measurement Matrix, Qiuyu Zhang, Zixian Ge, Liang Zhou, Yongbing Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present an efficient retrieval algorithm for encrypted speech based on an inverse fast Fourier transform and measurement matrix. Our approach improves query performance, as well as retrieval efficiency and accuracy, compared to existing content-based encrypted speech retrieval methods. Our proposed algorithm constructs a perceptual hash scheme using perceptual hash sequences from original speech files. By classifying the sequences and applying run-length compression, we decrease the cloud storage required for the hash index. We secure the speech database by encrypting it with Henon chaos scrambling, which offers excellent resistance to attacks. Experimental results show that the robustness, …

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