Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Classification (10)
- Machine learning (10)
- Support vector machine (8)
- Feature selection (7)
- Genetic algorithm (7)
-
- Feature extraction (6)
- Optimization (6)
- Wireless sensor networks (6)
- Particle swarm optimization (5)
- Artificial neural network (4)
- Clustering (4)
- Convolutional neural networks (4)
- Deep learning (4)
- Anomaly detection (3)
- Artificial bee colony (3)
- DBSCAN (3)
- Decision tree (3)
- Distributed generation (3)
- Electric vehicle (3)
- Fuzzy logic (3)
- Fuzzy logic control (3)
- Gravitational search algorithm (3)
- Image processing (3)
- K-means (3)
- Low power (3)
- Sentiment analysis (3)
- Social media (3)
- Social networks (3)
- Voltage stability (3)
- Artificial neural networks (2)
Articles 1 - 30 of 335
Full-Text Articles in Engineering
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 …
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 …
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 …
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 …
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 …
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 …
Path-Oriented Random Testing Through Iterative Partitioning (Ip-Prt), Esmaeel Nikravan, Saeed Parsa
Path-Oriented Random Testing Through Iterative Partitioning (Ip-Prt), Esmaeel Nikravan, Saeed Parsa
Turkish Journal of Electrical Engineering and Computer Sciences
Path-oriented random testing aims at generating a uniformly distributed sequence of test data from a program input domain space to traverse a desired execution path of the program. To this aim, this article proposes a new algorithm to refine a program inputs domain space from invalid subdomains not covering the path. The validity of the subdomains is checked by a constraint propagation method against the path constraints (PCs). The proposed algorithm uses a divide and conquer technique to iteratively split the inputs domain into subdomains and each time refutes those subdomains that are inconsistent with the PCs. The remaining shrunken …
Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki
Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki
Turkish Journal of Electrical Engineering and Computer Sciences
Steady-state visual evoked potential (SSVEP) is the brain's response to quickly repetitive visual stimulus with a certain frequency. To increase the information transfer rate (ITR) in SSVEP-based systems, due to the frequency resolution restriction, we are forced to broaden the frequency range, which causes harmonic frequencies to come into the stimulation frequency range. Conventional canonical correlation analysis (CCA) may be associated with error for SSVEP frequency recognition at stimulation frequencies with harmonic relations. The number of harmonics considered to construct reference signals are determined adaptively; for frequencies whose second harmonic exists in the frequency range, two harmonics are used, and …
Empirical Model Development For The Estimation Of Clearness Index Using Meteorological Parameters, Fakhar Alam, Saif Ur Rehman, Shafiqur Rehman, Muhammad Jahangir, Muhammad Shoaib, Imran Siddiqui, Intikhab Ulfat
Empirical Model Development For The Estimation Of Clearness Index Using Meteorological Parameters, Fakhar Alam, Saif Ur Rehman, Shafiqur Rehman, Muhammad Jahangir, Muhammad Shoaib, Imran Siddiqui, Intikhab Ulfat
Turkish Journal of Electrical Engineering and Computer Sciences
The clearness index is an indispensable parameter required for the design and analysis of solar energy systems. In the absence of measured values for a specific location, the clearness index can be estimated from other measured meteorological variables. In this study three meteorological parameters, sunshine hours, monthly mean values of the temperature difference ($\Delta$T), and cloudiness, are used to develop empirical models for the estimation of clearness index. The empirical models are developed for five major cities in Pakistan (Karachi, Multan, Lahore, Islamabad, and Quetta). For empirical model development, long-term data (1991 to 2010) of monthly average clearness index, sunshine …
Adaptive Iir Filter Design Using Self-Adaptive Search Equation Based Artificial Bee Colony Algorithm, Burhanetti̇n Durmuş, Gürcan Yavuz, Doğan Aydin
Adaptive Iir Filter Design Using Self-Adaptive Search Equation Based Artificial Bee Colony Algorithm, Burhanetti̇n Durmuş, Gürcan Yavuz, Doğan Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Infinite impulse response (IIR) system identification problem is defined as an IIR filter modeling to represent an unknown system. During a modeling task, unknown system parameters are estimated by metaheuristic algorithms through the IIR filter. This work deals with the self-adaptive search-equation-based artificial bee colony (SSEABC) algorithm that is adapted to optimal IIR filter design. SSEABC algorithm is a recent and improved variant of artificial bee colony (ABC) algorithm in which appropriate search equation is determined with a self-adaptive strategy. Moreover, the success of the SSEABC algorithm enhanced with a competitive local search selection strategy was proved on benchmark functions …
A Memory-Efficient Canonical Data Structure For Decimal Floating Point Arithmetic Systems Modeling And Verification, Mohammad Saeed Jahangiry, Saeed Safari
A Memory-Efficient Canonical Data Structure For Decimal Floating Point Arithmetic Systems Modeling And Verification, Mohammad Saeed Jahangiry, Saeed Safari
Turkish Journal of Electrical Engineering and Computer Sciences
Decimal floating point (DFP) number representation was proposed in IEEE-754-2008 in order to overcome binary floating point inaccuracy. Neglecting binary floating point verification has resulted in significant validity and economic losses. Formal verification can be a solution to similar DFP design problems. Verification techniques aiming at DFP are limited to functional methods whereas formal approaches have been neglected and traditional decision diagrams cannot model DFP representation complexity. In this paper, we propose an efficient canonical data structure that can model DFP properties. Our novel data structure models coefficient, exponent, sign, and bias of a DFP number. We will prove mathematically …
Optimal Dg Allocation For Enhancing Voltage Stability And Minimizing Power Loss Using Hybrid Gray Wolf Optimizer, Salah Kamel, Ayman Awad, Hussein Abdel-Mawgoud, Francisco Jurado
Optimal Dg Allocation For Enhancing Voltage Stability And Minimizing Power Loss Using Hybrid Gray Wolf Optimizer, Salah Kamel, Ayman Awad, Hussein Abdel-Mawgoud, Francisco Jurado
Turkish Journal of Electrical Engineering and Computer Sciences
High penetration of photovoltaic and wind turbine-based distributed generators (DGs) can help reduce carbon emissions which is an important goal for the whole world. DG can be used to improve the voltage stability, present generation reserve/emergency, and consequently, the system power quality can be improved. However, it is very important to select the right size and location of a DG so that the power system can increase the gained benefits of such an installation to the maximum. In this paper, a hybrid optimization technique is proposed to determine the optimal allocation of DG in the standard IEEE 33-bus radial distribution …
Unsupervised Deep Feature Embeddings For Speaker Diarization, Rehan Ahmad, Syed Zubair
Unsupervised Deep Feature Embeddings For Speaker Diarization, Rehan Ahmad, Syed Zubair
Turkish Journal of Electrical Engineering and Computer Sciences
Speaker diarization aims to determine ?who spoke when?? from multispeaker recording environments. In this paper, we propose to learn a set of high-level feature representations, referred to as feature embeddings, from an unsupervised deep architecture for speaker diarization. These sets of embeddings are learned through a deep autoencoder model when trained on mel-frequency cepstral coefficients (MFCCs) of input speech frames. Learned embeddings are then used in Gaussian mixture model based hierarchical clustering for diarization. The results show that these unsupervised embeddings are better compared to MFCCs in reducing the diarization error rate. Experiments conducted on the popular subset of the …
A Depth-Based Nearest Neighbor Algorithmfor High-Dimensional Data Classification, Sandhya Harikumar, Akhil A.S, Ramachandra Kaimal
A Depth-Based Nearest Neighbor Algorithmfor High-Dimensional Data Classification, Sandhya Harikumar, Akhil A.S, Ramachandra Kaimal
Turkish Journal of Electrical Engineering and Computer Sciences
Nearest neighbor algorithms like k-nearest neighbors (kNN) are fundamental supervised learning techniques to classify a query instance based on class labels of its neighbors. However, quite often, huge volumes of datasets are not fully labeled and the unknown probability distribution of the instances may be uneven. Moreover, kNN suffers from challenges like curse of dimensionality, setting the optimal number of neighbors, and scalability for high-dimensional data. To overcome these challenges, we propose an improvised approach of classification via depth representation of subspace clusters formed from high-dimensional data. We offer a consistent and principled approach to dynamically choose the nearest neighbors …
Contribution Of Artificial Proprioception On A Dynamic Finger Flexion Task, Mehdi Hojatmadani, Evren Samur
Contribution Of Artificial Proprioception On A Dynamic Finger Flexion Task, Mehdi Hojatmadani, Evren Samur
Turkish Journal of Electrical Engineering and Computer Sciences
There has been a considerable effort to provide sensory feedback for myoelectric prostheses. Among the solutions provided in the literature, sensory substitution is an easy and cost-effective way to provide feedback through different sensory modalities at different locations on the body. In this study, we evaluate the effect of sensory substitution of force and position feedback on a two-degree-of-freedom dynamic finger flexion task. For this purpose, a new methodology and an experimental setup are developed. The experimental methodology is based on the "strength-dexterity test", working on the principle of buckling of compression springs. The experimental setup comprises a haptic interface, …
Formally Analyzed M-Coupon Protocol With Confirmation Code (Mcwcc), Keri̇m Yildirim, Gökhan Dalkiliç, Nevci̇han Duru
Formally Analyzed M-Coupon Protocol With Confirmation Code (Mcwcc), Keri̇m Yildirim, Gökhan Dalkiliç, Nevci̇han Duru
Turkish Journal of Electrical Engineering and Computer Sciences
There are many marketing methods used to attract customers' attention and customers search for special discounts and conduct research to get products cheaper. Using discount coupons is one of the widely used methods for obtaining discounts. With the development of technology, classical paper-based discount coupons become e-coupons and then turn into mobile coupons (m-coupons). It is inevitable that retailers will use m-coupon technology to attract customers while mobile devices are used in daily life. As a result, m-coupon technology is a promising technology. One of the significant problems with using m-coupons is security. Here it is necessary to ensure the …
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 …
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 …
Optimal Range Of Loading For Operating A Fixed-Speed Wind Turbine Using A Self-Excited Induction Generator, Nassi̇m Iqteit, Gül Kurt, Beki̇r Çakir
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 …
Multi-Objective Design Optimization Of A Permanent Magnet Axial Flux Eddy Current Brake, Rasul Tarvirdilu Asl, Hüseyi̇n Murat Yüksel, Ozan Keysan
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 …
Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang
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 …
Robust Compressed Domain Watermarking Algorithm For Video Protection And Authentication In Noisy Channels, Naveen Cheggoju, Vishal Satpute
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 …
Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan
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. …
Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç
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 …
Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural
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 …
A Novel Algorithm For Frequency Extraction Of Abs Signals By Using Dtdnns, Mohammad Ali Shafieian, Hamed Banizaman, Shahrzad Sedaghat
A Novel Algorithm For Frequency Extraction Of Abs Signals By Using Dtdnns, Mohammad Ali Shafieian, Hamed Banizaman, Shahrzad Sedaghat
Turkish Journal of Electrical Engineering and Computer Sciences
Intelligent transportations system (ITSs) have emerged to increase safety and convenience of people in vehicles. In an ITS, communication devices in the vehicle or along the streets send the information gathered from the vehicle to information management centers as well as sending processed information to the vehicle. Furthermore, it is necessary to locate the exact location of the vehicle on a digital map in order to navigate the vehicle precisely in control and navigation systems. One of the technologies for this purpose is the antilock brake system (ABS), which can avoid accidents effectively and can also be utilized to determine …
Key Word Extraction For Short Text Via Word2vec, Doc2vec, And Textrank, Jun Li, Guimin Huang, Chunli Fan, Zhenglin Sun, Hongtao Zhu
Key Word Extraction For Short Text Via Word2vec, Doc2vec, And Textrank, Jun Li, Guimin Huang, Chunli Fan, Zhenglin Sun, Hongtao Zhu
Turkish Journal of Electrical Engineering and Computer Sciences
Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The data obtained should provide meaningful, correct, and accurate information. Therefore, all data must be separated into clusters correctly, and the right information from these clusters must be obtained. Having the correct clusters depends on the clustering algorithm that is used. There are many clustering algorithms. The density-based methods are very important among the groups of clustering methods, as they can find arbitrary shapes. An advanced model of the density-based spatial clustering of applications with noise (DBSCAN) algorithm, called fuzzy neighborhood DBSCAN Gaussian means …
Automatic Landing Of A Low-Cost Quadrotor Using Monocular Vision And Kalman Filter In Gps-Denied Environments, Mohammad Fattahi Sani, Maryam Shoaran, Ghader Karimian
Automatic Landing Of A Low-Cost Quadrotor Using Monocular Vision And Kalman Filter In Gps-Denied Environments, Mohammad Fattahi Sani, Maryam Shoaran, Ghader Karimian
Turkish Journal of Electrical Engineering and Computer Sciences
Unmanned aerial vehicles are becoming an important part of the modern life. Despite some recent advances in GPS-aided navigation of quadrotors, the concern of crash and collision still overshadows their reliability and safety, especially in GPS-denied environments. Therefore, the necessity for developing fully automatic methods for safe, accurate, and independent landing of drones increases over time. This paper investigates the autolanding process by focusing on an accurate and continuous position estimation of the drone using a monocular vision system and the fusion with the inertial measurement unit and ultrasonic sensors' data. An ARUCO marker is used as the landing pad, …
Large-Scale Round-Trip Delay Time Analysis Of Ipv4 Hosts Around The Globe, Ali̇ Gezer
Large-Scale Round-Trip Delay Time Analysis Of Ipv4 Hosts Around The Globe, Ali̇ Gezer
Turkish Journal of Electrical Engineering and Computer Sciences
Design and optimization of many network applications, services, protocols, and routing protocols can be improved with delay-related measurement for a better operation over the Internet. Many experimental delay measurements have been performed on predetermined end-to-end connections with a less number of hosts compared to our study. This study aims to investigate up-to-date round-trip delay time measurement results over the Internet through pinging random IPv4 addresses from three vantage points located in the United States, Turkey, and Japan. Considering different time periods in a day and in consecutive 5 years, we performed a large-scale round-trip delay time analysis study by sending …