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Articles 1 - 30 of 335
Full-Text Articles in Engineering
Three-Channel Control Architecture For Multilateral Teleoperation Under Time Delay, Uğur Tümerdem
Three-Channel Control Architecture For Multilateral Teleoperation Under Time Delay, Uğur Tümerdem
Turkish Journal of Electrical Engineering and Computer Sciences
Multilateral teleoperation is an extension of bilateral/haptic teleoperation framework to multiple operators/robots and finds applications in haptic training. As in bilateral teleoperation, time delay is an important problem, and stability and transparency, which quantifies the performance of the teleoperation system, are critical in the design of multilateral control systems. This paper proposes a novel three-channel-based multilateral control architecture with damping injection to guarantee delay-independent L2 stability and high transparency in multilateral teleoperation systems. The theoretical and computational analyses are verified with experiment results.
A Fuzzy Model Of Directional Relationships From The Phi-Descriptor, Mohammad Naeem, Nasir Ahmad, Sahib Khan, Asma Gul
A Fuzzy Model Of Directional Relationships From The Phi-Descriptor, Mohammad Naeem, Nasir Ahmad, Sahib Khan, Asma Gul
Turkish Journal of Electrical Engineering and Computer Sciences
Directional spatial relationships are a category of spatial relationships and have applications in the fields of image processing, geographic information systems, natural language processing, and robot navigation. They can be directly extracted from images or can be interpreted from a type of image descriptors called the relative position descriptors. Examples of relative position descriptors are the angle histogram, the force histogram, and the recently proposed phi-descriptor. So far, fuzzy models of directional spatial relationships from the angle histogram and force histograms have been proposed in the literature. These include the compatibility method, the aggregation method, and the method of effective …
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new technique of generation of convex polygon triangulation based on planted trivalent binary tree and ballot notation. The properties of the Catalan numbers were examined and their decomposition and application in developing the hierarchy and triangulation trees were analyzed. The method of storage and processing of triangulation was constructed on the basis of movements through the polygon. This method was derived from vertices and leaves of the planted trivalent binary tree. The research subject of the paper is analysis and comparison of a constructed method for solving of convex polygon triangulation problem with other methods and …
Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin
Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin
Turkish Journal of Electrical Engineering and Computer Sciences
Recent studies have shown, contrary to what was previously believed, that by exploiting correlation in stochastic computing (SC) designs, more accurate SC circuits with low area cost can be realized. However, if these basic SC circuits or blocks are cascaded in series to form a large complex system, correlation between stochastic numbers (SNs) from one block to the next would be lost; thus, inaccuracies are introduced. In this study, we propose correlating circuits to be used in building complex correlated SC systems. One of the circuits is the correlator that restores lost correlations between two SNs due to previous processing. …
Optimal Set Of Eeg Features In Infant Sleep Stage Classification, Maja Cic, Mario Milicevic, Igor Mazic
Optimal Set Of Eeg Features In Infant Sleep Stage Classification, Maja Cic, Mario Milicevic, Igor Mazic
Turkish Journal of Electrical Engineering and Computer Sciences
This paper evaluates six classification algorithms to assess the importance of individual EEG rhythms in the context of automatic classification of infant sleep. EEG features were obtained by Fourier transform and by a novel technique based on the empirical mode decomposition and generalized zero crossing method. Of six evaluated classification algorithms, the best classification results were obtained with the support vector machine for the combination of all presented features from four EEG channels. Three methods of attribute ranking were assessed: relief, principal component analysis, and wrapper-based optimized attribute weights. The outcomes revealed that the optimal selection of features requires one …
On The Stability Of Inverse Dynamics Control Of Flexible-Joint Parallel Manipulators In The Presence Of Modeling Error And Disturbances, Sitki Kemal İder, Ozan Korkmaz, Mustafa Semi̇h Deni̇zli̇
On The Stability Of Inverse Dynamics Control Of Flexible-Joint Parallel Manipulators In The Presence Of Modeling Error And Disturbances, Sitki Kemal İder, Ozan Korkmaz, Mustafa Semi̇h Deni̇zli̇
Turkish Journal of Electrical Engineering and Computer Sciences
Inverse dynamics control is considered for flexible-joint parallel manipulators in order to obtain a good trajectory tracking performance in the case of modeling error and disturbances. It is known that, in the absence of modeling error and disturbance, inverse dynamics control leads to linear fourth-order error dynamics, which is asymptotically stable if the feedback gains are chosen to make the real part of the eigenvalues of the system negative. However, when there are modeling errors and disturbances, a linear time-varying error dynamics is obtained whose stability is not assured only by keeping the real parts of the frozen-time eigenvalues of …
Assessment Of Techno-Economic Benefits For Smart Charging Scheme Of Electric Vehicles In Residential Distribution System, Kumari Kasturi, Manas Ranjan Nayak
Assessment Of Techno-Economic Benefits For Smart Charging Scheme Of Electric Vehicles In Residential Distribution System, Kumari Kasturi, Manas Ranjan Nayak
Turkish Journal of Electrical Engineering and Computer Sciences
Connecting multiple electric vehicles (EVs) to a power system network for the purpose of charging has major setbacks like decrease in power quality, instability in voltage profile, and increase in power losses and thus electricity price. This paper focuses on devising an optimal charging scheme to reduce the negative impacts of EVs' presence in the distribution network by limiting the charging process to only off-peak demand periods when the electricity price is comparatively lower. The salp swarm algorithm, an efficient, fast, and reliable optimization technique, is used to obtain the optimal locations for the EVs and their charging schedule in …
Lung Segmentation In Chest Radiographs Using Fully Convolutional Networks, Rahul Hooda, Ajay Mittal, Sanjeev Sofat
Lung Segmentation In Chest Radiographs Using Fully Convolutional Networks, Rahul Hooda, Ajay Mittal, Sanjeev Sofat
Turkish Journal of Electrical Engineering and Computer Sciences
Automated segmentation of medical images that aims at extracting anatomical boundaries is a fundamental step in any computer-aided diagnosis (CAD) system. Chest radiographic CAD systems, which are used to detect pulmonary diseases, first segment the lung field to precisely define the region-of-interest from which radiographic patterns are sought. In this paper, a deep learning-based method for segmenting lung fields from chest radiographs has been proposed. Several modifications in the fully convolutional network, which is used for segmenting natural images to date, have been attempted and evaluated to finally evolve a network fine-tuned for segmenting lung fields. The testing accuracy and …
Efficient Virtual Data Center Request Embedding Based On Row-Epitaxial And Batched Greedy Algorithms, Sivaranjani B, Surendran Doraiswamy
Efficient Virtual Data Center Request Embedding Based On Row-Epitaxial And Batched Greedy Algorithms, Sivaranjani B, Surendran Doraiswamy
Turkish Journal of Electrical Engineering and Computer Sciences
Data centers are becoming the main backbone of and centralized repository for all cloud-accessible services in on-demand cloud computing environments. In particular, virtual data centers (VDCs) facilitate the virtualization of all data center resources such as computing, memory, storage, and networking equipment as a single unit. It is necessary to use the data center efficiently to improve its profitability. The essential factor that significantly influences efficiency is the average number of VDC requests serviced by the infrastructure provider, and the optimal allocation of requests improves the acceptance rate. In existing VDC request embedding algorithms, data center performance factors such as …
A Novel Adaptive Hysteresis Dc-Dc Buck Converter For Portable Devices, Sung Sik Park, Ju Sang Lee, Sang Dae Yu
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 …
Turkish Lexicon Expansion By Using Finite State Automata, Mustafa Burak Öztürk, Burcu Can Buğlalilar
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 …
Selective Word Encoding For Effective Text Representation, Savaş Özkan, Akin Özkan
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 …
A New Spectral Estimation-Based Feature Extraction Method For Vehicle Classification In Distributed Sensor Networks, Erdem Köse, Ali̇ Köksal Hocaoğlu
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 …
A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh
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
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 …
Farsi Document Image Recognition System Using Word Layout Signature, Cem Ergün, Sajedeh Norozpour
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 …
Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon
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
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 …
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
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
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 …
A Joint Image Dehazing And Segmentation Model, Haider Ali, Awal Sher, Nosheen Zikria, Lavdi̇e Rada Ülgen
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 …
Design Of A Portable And Low-Cost Mass-Sensitive Sensor With The Capability Of Measurements On Various Frequency Quartz Tuning Forks, Mehmet Altay Ünal, İsmai̇l Cengi̇z Koçum, Di̇lek Çökeli̇ler Serdaroğlu
Design Of A Portable And Low-Cost Mass-Sensitive Sensor With The Capability Of Measurements On Various Frequency Quartz Tuning Forks, Mehmet Altay Ünal, İsmai̇l Cengi̇z Koçum, Di̇lek Çökeli̇ler Serdaroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, sensor and biosensor applications have become widespread and are now significant tools in the biomedical field and other areas. Since quartz tuning fork (QTF) resonance frequency depends on the mass adsorbed to its prongs, it is generally used to measure minor mass change and detect target analyte in picogram levels. This study is undertaken to design and fabricate a sensor device for the measurement of QTF transducers. When QTF sensor studies were investigated, it was found that explanations on the details of instrumentation part were limited, and in addition, there was no compact commercial products. In this study, a …
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, two hybrid estimation approaches, hybrid genetic algorithm (TR-GA) and hybrid particle swarm optimization (TR-PSO), are used to estimate single-diode model InGaN/GaN solar cell parameters from J?V experimental data under AM0 illumination. These parameters are photocurrent density ($J_{ph}$), reverse saturation current density ($J_{s}$), ideality factor ($A$), series resistance ($R_{s}$), and shunt resistance ($R_{sh}$). The trust region (TR) method used in both approaches provides the initial conditions and helps to avoid the problem of premature convergence (due to local minimum). Simulation results based on the minimization of the mean square error between experimental and theoretical J-V characteristics show that …
Identifying Preferred Solutions In Multiobjective Combinatorial Optimization Problems, Banu Lokman, Mustafa Murat Köksalan
Identifying Preferred Solutions In Multiobjective Combinatorial Optimization Problems, Banu Lokman, Mustafa Murat Köksalan
Turkish Journal of Electrical Engineering and Computer Sciences
We develop an evolutionary algorithm for multiobjective combinatorial optimization problems. The algorithm aims at converging the preferred solutions of a decision-maker. We test the performance of the algorithm on the multiobjective knapsack and multiobjective spanning tree problems. We generate the true nondominated solutions using an exact algorithm and compare the results with those of the evolutionary algorithm. We observe that the evolutionary algorithm works well in approximating the solutions in the preferred regions.
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The development and improvement of control techniques has attracted many researchers for many years. Especially in the controller design of complex and nonlinear systems, various methods have been proposed to determine the ideal control parameters. One of the most common and effective of these methods is determining the controller parameters with optimization algorithms.In this study, LQR controller design was implemented for position control of the double inverted pendulum system on a cart. First of all, the equations of motion of the inverted pendulum system were obtained by using Lagrange formulation. These equations were linearized by Taylor series expansion around the …
A Beaconing-Based Roadside Services Discovery Protocol For Vehicular Ad Hoc Networks, Kifayat Ullah, Ali Sayyed, Muhammad Aziz, Edson Moreira
A Beaconing-Based Roadside Services Discovery Protocol For Vehicular Ad Hoc Networks, Kifayat Ullah, Ali Sayyed, Muhammad Aziz, Edson Moreira
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, research on vehicular ad hoc networks (VANETs) has gained momentum all over the world. These emerging networks promise to make our driving experience more efficient, safer, comfortable, and enjoyable. VANETs have the potential to support a wide range of interesting applications. One such promising application area is the discovery of roadside services on the highways. Drivers need an efficient way to find these services during their journeys. However, due to the unique features of VANETs, the design and implementation of such applications is a challenging task. In this paper, we propose an application layer beaconing-based roadside services discovery protocol …
Monotone Data Modeling Using Rational Functions, Zoha Tariq, Farheen Ibraheem, Malik Zawwar Hussain, Muhammad Sarfraz
Monotone Data Modeling Using Rational Functions, Zoha Tariq, Farheen Ibraheem, Malik Zawwar Hussain, Muhammad Sarfraz
Turkish Journal of Electrical Engineering and Computer Sciences
Rational schemes for shape preservation of monotone data both in 2D and 3D setups have been developed. $C^1$ rational cubic and partially blended bicubic functions are employed for this purpose. Monotonicity is achieved by extracting constraints on parameters involved in the description of these rational functions. Monotone curves and surfaces have been obtained, which provide evidence that the algorithm used fits most types of monotone data and produces visually pleasing results.
Low-Cost Multimode Diode-Pumped Tm:Yag And Tm:Luag Lasers, Ersen Beyatli
Low-Cost Multimode Diode-Pumped Tm:Yag And Tm:Luag Lasers, Ersen Beyatli
Turkish Journal of Electrical Engineering and Computer Sciences
We report a continuous-wave operation of Tm:YAG and Tm:LuAG lasers pumped with a low-cost, multimode AlGaAs laser diode. First, the lifetime and the absorbance behavior of 5 mm, 6 % Tm$^{3+}$-doped YAG and LuAG crystals were thoroughly investigated. A low-cost multimode 3W laser diode at 781 nm was then used as a pump source for the Tm$^{3+}$-doped laser systems. Using three different output couplers, up to 636 mW of output power was obtained from Tm:YAG laser, with a slope efficiency of 29 % at 2017 nm. The maximum output power was 637 mW in the Tm:LuAG laser, with a slope …
An Adaptive Scheduling Scheme For Inhomogeneously Distributed Wireless Ad Hocnetworks, Adnan Fazil, Aamir Hasan, Muhammad Atique Ur Rehman, Ijaz Mansoor Qureshi
An Adaptive Scheduling Scheme For Inhomogeneously Distributed Wireless Ad Hocnetworks, Adnan Fazil, Aamir Hasan, Muhammad Atique Ur Rehman, Ijaz Mansoor Qureshi
Turkish Journal of Electrical Engineering and Computer Sciences
An efficient scheduling strategy guarantees the simultaneous transmission and successful reception by the scheduled nodes even inside a congested wireless ad hoc network. Owing to the dispersed nature of ad hoc networks, the node packing algorithm needs to be implementable without having network-wide channel state information and should additionally be able to pack the optimum number of successful transmissions. The proposed algorithm, for a network with nonhomogeneously distributed nodes, makes the decision to either inhibit or permit an active interferer around an active receiver based on the interferer?s transmission power. The analysis evidenced that the suggested scheme provides an estimated …
A Comparative Study Of Nonlinear Bayesian Filtering Algorithms For Estimation Ofgene Expression Time Series Data, Nesrine Amor, Asma Meddeb, Sahbi Marrouchi, Souad Chebbi
A Comparative Study Of Nonlinear Bayesian Filtering Algorithms For Estimation Ofgene Expression Time Series Data, Nesrine Amor, Asma Meddeb, Sahbi Marrouchi, Souad Chebbi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper addresses the problem of estimating the time series of a gene expression using nonlinear Bayesian filtering algorithms. The response of gene regulatory networks (GRNs) to functional requirements in the cell and environmental conditions evolves over time. Dynamic biological processes such as cancer progression and treatment recovery depend on the collected genetic profiles. These processes are behind genetic interactions that rewire over the course of time. The GRN was formulated as a nonlinear and non-Gaussian dynamic system defined by the gene measurement model and the unknown state is an evolution of the gene model. However, the GRN has a …