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Articles 65611 - 65640 of 294450

Full-Text Articles in Physical Sciences and Mathematics

Design And Analysis Of Marangoni-Driven Robotic Surfers, Mitchel L. Timm Jan 2022

Design And Analysis Of Marangoni-Driven Robotic Surfers, Mitchel L. Timm

Dissertations, Master's Theses and Master's Reports

We designed and experimentally studied the dynamics of two robotic systems that surf along the water-air interface. The robots were self-propelled by means of creating and maintaining a surface tension gradient resulting from an asymmetric release of isopropyl alcohol (IPA). The imbalance in the distribution of surface tension surrounding the robots generates a propulsive force commonly referred to as Marangoni propulsion. First, we considered a single surfer, which was custom-made with novel control mechanisms that allow for both forward motion and steering to be remotely adjusted solely through the manipulation of local surface stresses. We analyzed the performance of this …

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The Photo-Transformation Of Free Methionine In The Presence Of Surrogate And Standard Isolate Dissolved Organic Matter Under Sunlit Irradiation, Benjamin J. Mohrhardt Jan 2022

The Photo-Transformation Of Free Methionine In The Presence Of Surrogate And Standard Isolate Dissolved Organic Matter Under Sunlit Irradiation, Benjamin J. Mohrhardt

Dissertations, Master's Theses and Master's Reports

Sulfur (S)-containing amino acids are key sources of carbon, nitrogen, and sulfur involved in protein synthesis, protein function, and providing energy for microbial growth. Dissolved free and combined methionine is one of two S-containing amino acids incorporated into proteins and has been attributed to their stability and function. The oxidation of methionine has received considerable attention given its ubiquitous presence in most biological systems and has been associated with losses in protein function and pathological disorders. In natural waters, methionine is rapidly and selectively taken up by microorganisms to achieve cellular requirements of carbon, nitrogen, and sulfur. The abiotic transformation …

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Spatial Geochemical Changes In Central And East Texas Soils Over Time Resulting From Human Decomposition, Isabela Marisol Overturf Jan 2022

Spatial Geochemical Changes In Central And East Texas Soils Over Time Resulting From Human Decomposition, Isabela Marisol Overturf

CMC Senior Theses

Human decomposition is studied to aid forensic investigations and better understand the impact of cemeteries on urban resources like soil and groundwater. The purpose of this study was to identify changes in soil geochemistry at and around a human grave to search for lateral nutrient movement and possibly identify new patterns in elemental concentrations that could be used in estimating post-mortem intervals (PMIs). At the Forensic Anthropology Research Facility (FARF) at Texas State San Marcos, soil samples were collected from a shallow grave over the course of 54 days to conduct analysis for organic matter content, texture, pH, and bulk …

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Spatiotemporal Relationships Of Coyotes And Free-Ranging Domestic Cats As Indicators Of Conflict In Culver City, California, Rebecca N. Davenport, Melinda Weaver, Katherine C. B. Weiss, Eric G. Strauss Jan 2022

Spatiotemporal Relationships Of Coyotes And Free-Ranging Domestic Cats As Indicators Of Conflict In Culver City, California, Rebecca N. Davenport, Melinda Weaver, Katherine C. B. Weiss, Eric G. Strauss

Center for Urban Resilience Scholarship

As habitat generalists, urban coyote (Canis latrans) populations often utilize an abundance of diverse food sources in cities. Within southern California, domestic cats (Felis catus) comprise a higher proportion of coyote diets than in other studied urban areas throughout the United States. However, it is unclear which ecological factors contribute to higher rates of cat depredation by coyotes in this region. While previous research suggests that coyote presence may have a negative effect on free-ranging domestic cat distributions, few studies have determined whether urban green spaces affect coyote or free-ranging domestic cat occurrence and activity within …

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Lpvit: A Transformer Based Model For Pcb Image Classification And Defect Detection, Kang An, Yanping Zhang Jan 2022

Lpvit: A Transformer Based Model For Pcb Image Classification And Defect Detection, Kang An, Yanping Zhang

Computer Science Faculty Scholarship

PCB (printed circuit board) is an extremely important component of all electronic products, which has greatly facilitated human life. Meanwhile, tons of PCBs in the waste streams become a waste of resources, which puts the recycling and reuse of PCBs in urgent need. In the manufacturing and recycling of electronic products, the classification of PCBs, recognition of sub-components, and defect detection have been the key technology. Traditional manual detection and classification are subjective and rely on individuals’ experience. With the development of artificial intelligence, lots of research efforts have been dedicated to the automated detection and recognition of PCBs. In …

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Wittgenstein On Miscalculation And The Foundations Of Mathematics, Samuel J. Wheeler Jan 2022

Wittgenstein On Miscalculation And The Foundations Of Mathematics, Samuel J. Wheeler

Philosophy Faculty Publications

In Remarks on the Foundations of Mathematics, Wittgenstein notes that he has 'not yet made the role of miscalculating clear' and that 'the role of the proposition: "I must have miscalculated"...is really the key to an understanding of the "foundations" of mathematics.' In this paper, I hope to get clear on how this is the case. First, I will explain Wittgenstein's understanding of a 'foundation' for mathematics. Then, by showing how the proposition 'I must have miscalculated' differentiates mathematics from the physical sciences, we will see how this proposition is the key to understanding the foundations of mathematics.

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A Comparison Of Deep Learning Algorithms On Image Data For Detecting Floodwater On Roadways, Sarp Salih, Kuzlu Murat, Zhao Yanxiao, Cetin Mecit Jan 2022

A Comparison Of Deep Learning Algorithms On Image Data For Detecting Floodwater On Roadways, Sarp Salih, Kuzlu Murat, Zhao Yanxiao, Cetin Mecit

Engineering Technology Faculty Publications

Object detection and segmentation algorithms evolved significantly in the last decade. Simultaneous object detection and segmentation paved the way for real-time applications such as autonomous driving. Detection and segmentation of (partially) flooded roadways are essential inputs for vehicle routing and traffic management systems. This paper proposes an automatic floodwater detection and segmentation method utilizing the Mask Region-Based Convolutional Neural Networks (Mask-R-CNN) and Generative Adversarial Networks (GAN) algorithms. To train the model, manually labeled images with urban, suburban, and natural settings are used. The performances of the algorithms are assessed in accurately detecting the floodwater captured in images. The results show …

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Security Hardening Of Intelligent Reflecting Surfaces Against Adversarial Machine Learning Attacks, Ferhat Ozgur Catak, Murat Kuzlu, Haolin Tang, Evren Catak, Yanxiao Zhao Jan 2022

Security Hardening Of Intelligent Reflecting Surfaces Against Adversarial Machine Learning Attacks, Ferhat Ozgur Catak, Murat Kuzlu, Haolin Tang, Evren Catak, Yanxiao Zhao

Engineering Technology Faculty Publications

Next-generation communication networks, also known as NextG or 5G and beyond, are the future data transmission systems that aim to connect a large amount of Internet of Things (IoT) devices, systems, applications, and consumers at high-speed data transmission and low latency. Fortunately, NextG networks can achieve these goals with advanced telecommunication, computing, and Artificial Intelligence (AI) technologies in the last decades and support a wide range of new applications. Among advanced technologies, AI has a significant and unique contribution to achieving these goals for beamforming, channel estimation, and Intelligent Reflecting Surfaces (IRS) applications of 5G and beyond networks. However, the …

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Exploring The Untapped Gas Potential Of Ghazij Shale In Pirkoh Area, Pakistan: Integratedapproach Of Attribute Analysis And Maturity Modeling, Muhammad Raiees Amjad, Sarfraz Khan, Umair Bin Nisar, Urooj Shakir, Khawar Ashfaq Ahmed Jan 2022

Exploring The Untapped Gas Potential Of Ghazij Shale In Pirkoh Area, Pakistan: Integratedapproach Of Attribute Analysis And Maturity Modeling, Muhammad Raiees Amjad, Sarfraz Khan, Umair Bin Nisar, Urooj Shakir, Khawar Ashfaq Ahmed

Turkish Journal of Earth Sciences

A correlative maturity study integrated with seismic attributes for determining the shale gas potential of Ghazij Formation is carried out. Analysis of post-stack seismic attributes has been frequently used to identify areas of high exploration potential within shale resource plays. Seismic and well data have been utilized for the analysis of maturity trends in the shale facies of Ghazij Formation. Total organic carbon content (TOC), burial history, Vitrinite Reflectance (Ro), thermal history and porosity values have been computed at Pirkoh-01 well, which are laterally compared with the maturity results in Bambor and Sui areas. In addition, analysis is carried out …

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Mineralogical And Paleobotanical Investigations Of Oligo-Miocene Petrified Wood Fromthe Southwest Of Thrace Basin (Nw Turkey), Burcu Üner, Sabah Yilmaz Şahi̇n, Ünal Akkemi̇k Jan 2022

Mineralogical And Paleobotanical Investigations Of Oligo-Miocene Petrified Wood Fromthe Southwest Of Thrace Basin (Nw Turkey), Burcu Üner, Sabah Yilmaz Şahi̇n, Ünal Akkemi̇k

Turkish Journal of Earth Sciences

Petrified wood samples are found within terrestrial sediments belonging to the Late Oligocene-Early Miocene Danişmen Formation in Malkara-Keşan located in the southwest of the Thrace Basin. The petrified wood in both regions is usually silicified and partly coalified. The silicification of the Tertiary wood in the Malkara-Keşan region is associated with volcanic activity and coeval sedimentation. Thin sections from petrified wood samples were taken as transverse, tangential, and radial sections. The mineralogicalpetrographic- botanical studies were carried out under a polarizing and botanical microscope. Opal-moganite-chalcedony-quartz, which are different polymorphs of silica, were detected under the microscope in the petrified wood. Results …

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Structural Interpretation And Petrophysical Approach For Subsurface Fractureidentification Of Joya Mair Area, Nw-Himalayas, Pakistan, Palwasha Shahzad Rathore, Muhammad Armaghan Faisal Miraj, Muhammad Bilal Malik, Sher Afgan, Rana Faizan Saleem, Shan Shahzad, Irza Akhtar Jan 2022

Structural Interpretation And Petrophysical Approach For Subsurface Fractureidentification Of Joya Mair Area, Nw-Himalayas, Pakistan, Palwasha Shahzad Rathore, Muhammad Armaghan Faisal Miraj, Muhammad Bilal Malik, Sher Afgan, Rana Faizan Saleem, Shan Shahzad, Irza Akhtar

Turkish Journal of Earth Sciences

Identification of fracture zone is a challenging task without the image log data. There are many brownfields around the world where the image log has not been acquired; therefore, there must be an alternative way of fracture identification. In this paper, a conventional log response technique for fracture delineation has been discussed. The study area lies in the Upper Indus Basin of Pakistan, which is sub-divided into the Kohat and Potwar basins. Minwal-X-1 of Joya Mair area, which lies in the Potwar Basin, is selected for this purpose. Eocene limestone units are formed due to fracture porosity. The objective of …

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No Sand Shipment For Cleopatra By Antonius: Resedimentary Origin For The Ooidal Sand Beach Of Sedir Island (Aegean Coast Of Sw Anatolia), Mehmet Ci̇hat Alçi̇çek Jan 2022

No Sand Shipment For Cleopatra By Antonius: Resedimentary Origin For The Ooidal Sand Beach Of Sedir Island (Aegean Coast Of Sw Anatolia), Mehmet Ci̇hat Alçi̇çek

Turkish Journal of Earth Sciences

No abstract provided.

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Middle-Late Devonian Boundary Conodonts From Anarak And Sar-Ashk Sections, Centraliran, Hossein Gholamalian, Vachik Hairapetian, Mohammad Poosti Jan 2022

Middle-Late Devonian Boundary Conodonts From Anarak And Sar-Ashk Sections, Centraliran, Hossein Gholamalian, Vachik Hairapetian, Mohammad Poosti

Turkish Journal of Earth Sciences

The Middle/Late Devonian boundary is investigated based on twenty-four conodont species and subspecies from the Anarak and Sar-Ashk sections in the northwest and southeast of Central East Iran Microplate. The earliest Frasnian strata are defined by the first appearance of Ancyrodella rotundiloba pristina and can be correlated with the global stratotype in the Montagne Noir, South of France. The Late Givetian - Early Frasnian carbonates of the Bahram Formation in the Sar-Ashk section transgressively overlie the sandstones of the Padeha Formation, whereas the coeval interval in the Anarak section composes the middle part of the Bahram Formation. Conodont biostratigraphy of …

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Optimized Cancer Detection On Various Magnified Histopathological Colon Imagesbased On Dwt Features And Fcm Clustering, Tina Babu, Tripty Singh, Deepa Gupta, Shahin Hameed Jan 2022

Optimized Cancer Detection On Various Magnified Histopathological Colon Imagesbased On Dwt Features And Fcm Clustering, Tina Babu, Tripty Singh, Deepa Gupta, Shahin Hameed

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the morphological characteristics and other biological aspects in histopathological images, the computerized diagnosis of colon cancer in histopathology images has gained popularity. The images acquired using the histopathology microscope may differ for greater visibility by magnifications. This causes a change in morphological traits leading to intra and inter-observer variability. An automatic colon cancer diagnosis system for various magnification is therefore crucial. This work proposes a magnification independent segmentation approach based on the connected component area and double density dual tree DWT (discrete wavelet transform) coefficients are derived from the segmented region. The derived features are reduced further shortened …

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Distributed Wireless Sensor Node Localization Based On Penguin Searchoptimization, Md Al Shayokh, Soo Young Shin Jan 2022

Distributed Wireless Sensor Node Localization Based On Penguin Searchoptimization, Md Al Shayokh, Soo Young Shin

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks (WSNs) have become popular for sensing areas-of-interest and performing assigned tasks based on information on the location of sensor devices. Localization in WSNs is aimed at designating distinct geographical information to the inordinate nodes within a search area. Biologically inspired algorithms are being applied extensively in WSN localization to determine inordinate nodes more precisely while consuming minimal computation time. An optimization algorithm belonging to the metaheuristic class and named penguin search optimization (PeSOA) is presented in this paper. It utilizes the hunting approaches in a collaborative manner to determine the inordinate nodes within an area of interest. …

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Cnn Based Sensor Fusion Method For Real-Time Autonomous Robotics Systems, Berat Yildiz, Aki̇f Durdu, Ahmet Kayabaşi, Mehmet Duramaz Jan 2022

Cnn Based Sensor Fusion Method For Real-Time Autonomous Robotics Systems, Berat Yildiz, Aki̇f Durdu, Ahmet Kayabaşi, Mehmet Duramaz

Turkish Journal of Electrical Engineering and Computer Sciences

Autonomous robotic systems (ARS) serve in many areas of daily life. The sensors have critical importance for these systems. The sensor data obtained from the environment should be as accurate and reliable as possible and correctly interpreted by the autonomous robot. Since sensors have advantages and disadvantages over each other they should be used together to reduce errors. In this study, Convolutional Neural Network (CNN) based sensor fusion was applied to ARS to contribute the autonomous driving. In a real-time application, a camera and LIDAR sensor were tested with these networks. The novelty of this work is that the uniquely …

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Fft Enabled Ecc For Wsn Nodes Without Hardware Multiplier Support, Utku Gülen, Selçuk Baktir Jan 2022

Fft Enabled Ecc For Wsn Nodes Without Hardware Multiplier Support, Utku Gülen, Selçuk Baktir

Turkish Journal of Electrical Engineering and Computer Sciences

ECC is a popular cryptographic algorithm for key distribution in wireless sensor networks where power efficiency is desirable. A power efficient implementation of ECC without using hardware multiplier support was proposed earlier for wireless sensor nodes. The proposed implementation utilized the number theoretic transform to carry operands to the frequency domain, and conducted Montgomery multiplication, in addition to other finite field operations, in that domain. With this work, we perform in the frequency domain only polynomial multiplication and use the fast Fourier transform to carry operands between the time and frequency domains. Our ECC implementation over $GF((2^{13}-1)^{13})$ on the MSP430 …

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Using Vertical Areas In Finite Set Model Predictive Control Of A Three-Level Inverter Aimed At Computation Reduction, Alireza Jaafari, Alireza Davari, Cristian Garcia, Jose Rodriguez Jan 2022

Using Vertical Areas In Finite Set Model Predictive Control Of A Three-Level Inverter Aimed At Computation Reduction, Alireza Jaafari, Alireza Davari, Cristian Garcia, Jose Rodriguez

Turkish Journal of Electrical Engineering and Computer Sciences

In power electronics applications, finite set model predictive control (FS-MPC) has proven to be a viable strategy. However, due to the high processing power required, using this technology in multilevel converters is difficult. This strategy, which is based on predicting the behavior of the system for all conceivable states, has an issue with a numerous of possible switching states. A recent and useful strategy for dealing with the problem is the limiting of calculations based on triangle regions. Despite its success, this method has several limitations, including the computation required to locate the right triangle and the boundary modes. In …

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An Approach For Performance Prediction Of Saturated Brushed Permanent Magnetdirect Current (Dc) Motor From Physical Dimensions, Rasul Tarvirdilu, Reza Zeinali, Hulusi̇ Bülent Ertan Jan 2022

An Approach For Performance Prediction Of Saturated Brushed Permanent Magnetdirect Current (Dc) Motor From Physical Dimensions, Rasul Tarvirdilu, Reza Zeinali, Hulusi̇ Bülent Ertan

Turkish Journal of Electrical Engineering and Computer Sciences

An analytical approach for performance prediction of saturated brushed permanent magnet direct current (DC) motors is proposed in this paper. In case of a heavy saturation in the stator back core of electrical machines, some flux completes its path through the surrounding air, and the conventional equivalent circuit cannot be used anymore. This issue has not been addressed in the literature. The importance of considering the effect of the flux penetrating the surrounding air is shown in this paper using finite element simulations and experimental results, and an analytical approach is proposed to consider this effect on magnet operating point …

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Application Of Long Short-Term Memory (Lstm) Neural Network Based On Deeplearning For Electricity Energy Consumption Forecasting, Mehmet Bi̇lgi̇li̇, Ni̇yazi̇ Arslan, Ali̇i̇hsan Şekerteki̇n, Abdulkadi̇r Yaşar Jan 2022

Application Of Long Short-Term Memory (Lstm) Neural Network Based On Deeplearning For Electricity Energy Consumption Forecasting, Mehmet Bi̇lgi̇li̇, Ni̇yazi̇ Arslan, Ali̇i̇hsan Şekerteki̇n, Abdulkadi̇r Yaşar

Turkish Journal of Electrical Engineering and Computer Sciences

Electricity is the most substantial energy form that significantly affects the development of modern life, work efficiency, quality of life, production, and competitiveness of the society in the ever-growing global world. In this respect, forecasting accurate electricity energy consumption (EEC) is fairly essential for any country?s energy consumption planning and management regarding its growth. In this study, four time-series methods; long short-term memory (LSTM) neural network, adaptive neuro-fuzzy inference system (ANFIS) with subtractive clustering (SC), ANFIS with fuzzy cmeans (FCM), and ANFIS with grid partition (GP) were implemented for the short-term one-day ahead EEC prediction. Root mean square error (RMSE), …

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A Futuristic Approach To Generate Random Bit Sequence Using Dynamic Perturbedchaotic System, Sathya Krishnamoorthi, Premalatha Jayapaul, Vani Rajasekar, Rajesh Kumar Dhanaraj, Celestine Iwendi Jan 2022

A Futuristic Approach To Generate Random Bit Sequence Using Dynamic Perturbedchaotic System, Sathya Krishnamoorthi, Premalatha Jayapaul, Vani Rajasekar, Rajesh Kumar Dhanaraj, Celestine Iwendi

Turkish Journal of Electrical Engineering and Computer Sciences

Most of the web applications require security which in turn requires random numbers. Pseudo-random numbers are required with good statistical properties and efficiency. Use of chaotic map to dynamically perturb another chaotic map that generates the random bit output is introduced in this work. Perturbance is introduced to improvise the chaotic behaviour of a base map and increase the periodicity. PRNG with this architecture is devised to generate random bit sequence from initial keyspace. The statistical properties of newly constructed PRNG are tested with NIST SP 800-22 statistical test suite and were shown to have good randomness. To ensure its …

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Motion-Aware Vehicle Detection In Driving Videos, Mehmet Kiliçarslan, Tansu Temel Jan 2022

Motion-Aware Vehicle Detection In Driving Videos, Mehmet Kiliçarslan, Tansu Temel

Turkish Journal of Electrical Engineering and Computer Sciences

This paper focuses on vehicle detection based on motion features in driving videos. Long-term motion information can assist in driving scenarios since driving is a complicated and dynamic process. The proposed method is a deep learning based model which processes motion frame image. This image merges both spatial (frame) and temporal (motion) information. Hence, the model jointly detects vehicles and their motion from a single image. The trained model on Toyota Motor Europe Motorway Dataset reaches 83% mean average precision (mAP). Our experiments demonstrate that the proposed method has a higher mAP than a tracking-based model. The proposed method runs …

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A Novel Energy Consumption Model For Autonomous Mobile Robot, Gürkan Gürgöze, İbrahi̇m Türkoğlu Jan 2022

A Novel Energy Consumption Model For Autonomous Mobile Robot, Gürkan Gürgöze, İbrahi̇m Türkoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel predictive energy consumption model has been developed to facilitate the development of tasks based on efficient energy consumption strategies in mobile robot systems. For the proposed energy consumption model, an advanced mathematical system model that takes into account all parameters during the motion of the mobile robot is created. The parameters of inclination, load, dynamic friction, wheel slip and speed-torque saturation limit, which are often neglected in existing models, are especially used in our model. Thus, the effects of unexpected disruptors on energy consumption in the real world environment are also taken into account. As …

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Automatically Classifying Familiar Web Users From Eye-Tracking Data:A Machine Learning Approach, Meli̇h Öder, Şükrü Eraslan, Yeli̇z Yesi̇lada Jan 2022

Automatically Classifying Familiar Web Users From Eye-Tracking Data:A Machine Learning Approach, Meli̇h Öder, Şükrü Eraslan, Yeli̇z Yesi̇lada

Turkish Journal of Electrical Engineering and Computer Sciences

Eye-tracking studies typically collect enormous amount of data encoding rich information about user behaviours and characteristics on the web. Eye-tracking data has been proved to be useful for usability and accessibility testing and for developing adaptive systems. The main objective of our work is to mine eye-tracking data with machine learning algorithms to automatically detect users' characteristics. In this paper, we focus on exploring different machine learning algorithms to automatically classify whether users are familiar or not with a web page. We present our work with an eye-tracking data of 81 participants on six web pages. Our results show that …

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Stability Regions In Time Delayed Two-Area Lfc System Enhanced By Evs, Ausnain Naveed, Şahi̇n Sönmez, Saffet Ayasun Jan 2022

Stability Regions In Time Delayed Two-Area Lfc System Enhanced By Evs, Ausnain Naveed, Şahi̇n Sönmez, Saffet Ayasun

Turkish Journal of Electrical Engineering and Computer Sciences

With the extensive usage of open communication networks, time delays have become a great concern in load frequency control (LFC) systems since such inevitable large delays weaken the controller performance and even may lead to instabilities. Electric vehicles (EVs) have a potential tool in the frequency regulation. The integration of a large number of EVs via an aggregator amplifies the adverse effects of time delays on the stability and controller design of LFC systems. This paper investigates the impacts of the EVs aggregator with communication time delay on the stability. Primarily, a graphical method characterizing stability boundary locus is implemented. …

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Temporal Bagging: A New Method For Time-Based Ensemble Learning, Göksu Tüysüzoğlu, Derya Bi̇rant, Volkan Kiranoğlu Jan 2022

Temporal Bagging: A New Method For Time-Based Ensemble Learning, Göksu Tüysüzoğlu, Derya Bi̇rant, Volkan Kiranoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

One of the main problems associated with the bagging technique in ensemble learning is its random sample selection in which all samples are treated with the same chance of being selected. However, in time-varying dynamic systems, the samples in the training set have not equal importance, where the recent samples contain more useful and accurate information than the former ones. To overcome this problem, this paper proposes a new time-based ensemble learning method, called temporal bagging (T-Bagging). The significant advantage of our method is that it assigns larger weights to more recent samples with respect to older ones, so it …

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Evaluating The English-Turkish Parallel Treebank For Machine Translation, Onur Görgün, Olcay Taner Yildiz Jan 2022

Evaluating The English-Turkish Parallel Treebank For Machine Translation, Onur Görgün, Olcay Taner Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

This study extends our initial efforts in building an English-Turkish parallel treebank corpus for statistical machine translation tasks. We manually generated parallel trees for about 17K sentences selected from the Penn Treebank corpus. English sentences vary in length: 15 to 50 tokens including punctuation. We constrained the translation of trees by (i) reordering of leaf nodes based on suffixation rules in Turkish, and (ii) gloss replacement. We aim to mimic human annotator?s behavior in real translation task. In order to fill the morphological and syntactic gap between languages, we do morphological annotation and disambiguation. We also apply our heuristics by …

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An Active Contour Model Using Matched Filter And Hessian Matrix For Retinalvessels Segmentation, Mahtab Shabani, Hossein Pourghassem Jan 2022

An Active Contour Model Using Matched Filter And Hessian Matrix For Retinalvessels Segmentation, Mahtab Shabani, Hossein Pourghassem

Turkish Journal of Electrical Engineering and Computer Sciences

Medical image analysis, especially of the retina, plays an important role in diagnostic decision support tools. The properties of retinal blood vessels are used for disease diagnoses such as diabetes, glaucoma, and hypertension. There are some challenges in the utilization of retinal blood vessel patterns such as low contrast and intensity inhomogeneities. Thus, an automatic algorithm for vessel extraction is required. Active contour is a strong method for edge extraction. However, it cannot extract thin vessels and ridges very well. In this research, we propose an improved active contour method that uses discrete wavelet transform for energy minimization to solve …

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Stressed Or Just Running? Differentiation Of Mental Stress And Physical Activityby Using Machine Learning, Yekta Sai̇d Can Jan 2022

Stressed Or Just Running? Differentiation Of Mental Stress And Physical Activityby Using Machine Learning, Yekta Sai̇d Can

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, modern people have excessive stress in their daily lives. With the advances in physiological sensors and wearable technology, people?s physiological status can be tracked, and stress levels can be recognized for providing beneficial services. Smartwatches and smartbands constitute the majority of wearable devices. Although they have an excellent potential for physiological stress recognition, some crucial issues need to be addressed, such as the resemblance of physiological reaction to stress and physical activity, artifacts caused by movements and low data quality. This paper focused on examining and differentiating physiological responses to both stressors and physical activity. Physiological data are collected …

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An Effective Prediction Method For Network State Information In Sd-Wan, Erdal Akin, Ferdi̇ Saraç, Ömer Aslan Jan 2022

An Effective Prediction Method For Network State Information In Sd-Wan, Erdal Akin, Ferdi̇ Saraç, Ömer Aslan

Turkish Journal of Electrical Engineering and Computer Sciences

In a software-defined wide area network (SD-WAN), a logically centralized controller is responsible for computing and installing paths in order to transfer packets among geographically distributed locations and remote users. Accordingly, this would necessitate obtaining the global view and dynamic network state information (NSI) of the network. Therefore, the centralized controller periodically collects link-state information from each port of each switch at fixed time periods. While collecting NSI in short periods causes protocol overhead on the controller, collecting in longer periods leads to obtaining inaccurate NSI. In both cases, packet losses are inevitable, which is not preferred for quality of …

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