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Articles 14671 - 14700 of 15205
Full-Text Articles in Physical Sciences and Mathematics
Computer Vision Based Deep Learning Models For Cyber Physical Systems, Muhammad Monjurul Karim
Computer Vision Based Deep Learning Models For Cyber Physical Systems, Muhammad Monjurul Karim
Masters Theses
“Cyber-Physical Systems (CPSs) are complex systems that integrate physical systems with their counterpart cyber components to form a close loop solution. Due to the ability of deep learning in providing sensor data-based models for analyzing physical systems, it has received increased interest in the CPS community in recent years. However, developing vision data-based deep learning models for CPSs remains critical since the models heavily rely on intensive, tedious efforts of humans to annotate training data. Besides, most of the models have a high tradeoff between quality and computational cost. This research studies deep learning algorithms to achieve affordable and upgradable …
Characterization Of A Plasma Source Simulating Solar Wind Plasma In A Vacuum Chamber, Blake Anthony Folta
Characterization Of A Plasma Source Simulating Solar Wind Plasma In A Vacuum Chamber, Blake Anthony Folta
Masters Theses
"The United States has set an aggressive time line to not only return to the Moon, but also to establish a sustained human presence. In the Apollo missions dust was a significant factor, but the duration of those missions was short so dust and surface charging were problems, but they did not pose an immediate threat. For a long-term mission, these problems instead become incredibly detrimental. Because of this, research needs to be conducted to investigate these phenomena so that mitigation techniques can be developed and tested. To this end, this thesis serves to demonstrate the Gas and Plasma Dynamics …
The Role Of Tectonic Inheritance, Plate-Reorganization, And Magma Flare-Ups In The Evolution Of The Sevier Orogeny, J. Daniel Quick
The Role Of Tectonic Inheritance, Plate-Reorganization, And Magma Flare-Ups In The Evolution Of The Sevier Orogeny, J. Daniel Quick
Masters Theses
"The temporal and spatial distribution of strain associated with the Sevier Orogeny in western North America is significantly different in the southern end of the belt, at the latitude of Las Vegas, than further to the north at the latitude of Salt Lake City. Until this study, reasons for these differences were speculative as a lack of thrust kinematic data in the intervening region hindered along strike correlation across the belt. A crystallization age of 100.18 ± 14 0.04 Ma was determined for zircons extracted from a recently recognized ash fall tuff near the base of the synorogenic Iron Springs …
The Application Of Machine Learning Models In The Concussion Diagnosis Process, Sujit Subhash
The Application Of Machine Learning Models In The Concussion Diagnosis Process, Sujit Subhash
Masters Theses
“Concussions represent a growing health concern and are challenging to diagnose and manage. Roughly four million concussions are diagnosed every year in the United States. Although research into the application of advanced metrics such as neuroimages and blood biomarkers has shown promise, they are yet to be implemented at a clinical level due to cost and reliability concerns. Therefore, concussion diagnosis is still reliant on clinical evaluations of symptoms, balance, and neurocognitive status and function. The lack of a universal threshold on these assessments makes the diagnosis process entirely reliant on a physician’s interpretation of these assessment scores. This study …
Quantifying Effects Of Sleep Deprivation On Cognitive Performance, Quang Nghia Le
Quantifying Effects Of Sleep Deprivation On Cognitive Performance, Quang Nghia Le
Masters Theses
“The most commonly used metric for evaluating alertness and vigilance is the Psychomotor Vigilance Test (PVT), previous studies have indicated that alertness and vigilance can be affected by the lack of sleep as a function of sleep loss. This study explores methods to predict median psychomotor vigilance reaction times. The data used in this study comes from a series of tests and surveys conducted on volunteer students. The data set contains many potential predictors of PVT and one aspect of the study was to identify variables that are useful in prediction. The performances of various prediction methods that allow for …
Optimizing Pollution Routing Problem, Shivika Dewan
Optimizing Pollution Routing Problem, Shivika Dewan
All Master's Theses
Pollution is a major environmental issue around the world. Despite the growing use and impact of commercial vehicles, recent research has been conducted with minimizing pollution as the primary objective to be reduced. The objective of this project is to implement different optimization algorithms to solve this problem. A basic model is created using the Vehicle Routing Problem (VRP) which is further extended to the Pollution Routing Problem (PRP). The basic model is updated using a Monte Carlo Algorithm (MCA). The data set contains 180 data files with a combination of 10, 15, 20, 25, 50, 75, 100, 150, and …
Image Features For Tuberculosis Classification In Digital Chest Radiographs, Brian Hooper
Image Features For Tuberculosis Classification In Digital Chest Radiographs, Brian Hooper
All Master's Theses
Tuberculosis (TB) is a respiratory disease which affects millions of people each year, accounting for the tenth leading cause of death worldwide, and is especially prevalent in underdeveloped regions where access to adequate medical care may be limited. Analysis of digital chest radiographs (CXRs) is a common and inexpensive method for the diagnosis of TB; however, a trained radiologist is required to interpret the results, and is subject to human error. Computer-Aided Detection (CAD) systems are a promising machine-learning based solution to automate the diagnosis of TB from CXR images. As the dimensionality of a high-resolution CXR image is very …
Outlier Profiles Of Atomic Structures Derived From X-Ray Crystallography And From Cryo-Electron Microscopy, Lin Chen, Jing He, Angelo Facchiano
Outlier Profiles Of Atomic Structures Derived From X-Ray Crystallography And From Cryo-Electron Microscopy, Lin Chen, Jing He, Angelo Facchiano
Computer Science Faculty Publications
Background: As more protein atomic structures are determined from cryo-electron microscopy (cryo-EM) density maps, validation of such structures is an important task. Methods: We applied a histogram-based outlier score (HBOS) to six sets of cryo-EM atomic structures and five sets of X-ray atomic structures, including one derived from X-ray data with better than 1.5 Å resolution. Cryo-EM data sets contain structures released by December 2016 and those released between 2017 and 2019, derived from resolution ranges 0–4 Å and 4–6 Å respectively. Results: The distribution of HBOS values in five sets of X-ray structures show that HBOS is sensitive distinguishing …
Psu At Clef-2020 Arqmath Track: Unsupervised Re-Ranking Using Pretraining, Shaurya Rohatgi, Jian Wu, C. Lee Giles
Psu At Clef-2020 Arqmath Track: Unsupervised Re-Ranking Using Pretraining, Shaurya Rohatgi, Jian Wu, C. Lee Giles
Computer Science Faculty Publications
This paper elaborates on our submission to the ARQMath track at CLEF 2020. Our primary run for the main Task-1: Question Answering uses a two-stage retrieval technique in which the first stage is a fusion of traditional BM25 scoring and tf-idf with cosine similarity-based retrieval while the second stage is a finer re-ranking technique using contextualized embeddings. For the re-ranking we use a pre-trained robertabase model (110 million parameters) to make the language model more math-aware. Our approach achieves a higher NDCG0 score than the baseline, while our MAP and P@10 scores are competitive, performing better than the best submission …
Remark On Lehnert’S Revised Quantum Electrodynamics (Rqed) As An Alternative To Francesco Celani’S Et Al. Maxwell-Clifford Equations: With An Outline Of Chiral Cosmology Model And Its Role To Cmns, Florentin Smarandache, Victor Christianto, Yunita Umniyati
Remark On Lehnert’S Revised Quantum Electrodynamics (Rqed) As An Alternative To Francesco Celani’S Et Al. Maxwell-Clifford Equations: With An Outline Of Chiral Cosmology Model And Its Role To Cmns, Florentin Smarandache, Victor Christianto, Yunita Umniyati
Branch Mathematics and Statistics Faculty and Staff Publications
In a recent paper published in JCMNS in 2017, Francesco Celani, Di Tommaso & Vassalo argued that Maxwell equations rewritten in Clifford algebra are sufficient to describe the electron and also ultra-dense deuterium reaction process proposed by Homlid et al. Apparently, Celani et al. believed that their Maxwell-Clifford equations are an excellent candidate to surpass both Classical Electromagnetic and Zitterbewegung QM. Meanwhile, in a series of papers, Bo Lehnert proposed a novel and revised version of Quantum Electrodynamics (RQED) based on Proca equations. Therefore, in this paper, we gave an outline of Lehnert’s RQED, as an alternative framework to Celani …
New Challenges In Neutrosophic Theory And Applications, Florentin Smarandache, Stefan Vladutescu, Miihaela Colhon, Wadei Al-Omeri, Saeid Jafari, Muhammad Zahir Khan, Muhammad Farid Khan, Muhammad Aslam, Abdur Razzaque Mughal
New Challenges In Neutrosophic Theory And Applications, Florentin Smarandache, Stefan Vladutescu, Miihaela Colhon, Wadei Al-Omeri, Saeid Jafari, Muhammad Zahir Khan, Muhammad Farid Khan, Muhammad Aslam, Abdur Razzaque Mughal
Branch Mathematics and Statistics Faculty and Staff Publications
Neutrosophic theory has representatives on all continents and, therefore, it can be said to be a universal theory. On the other hand, according to the three volumes of “The Encyclopedia of Neutrosophic Researchers” (2016, 2018, 2019), plus numerous others not yet included in Encyclopedia book series, about 1200 researchers from 73 countries have applied both the neutrosophic theory and method. Neutrosophic theory was founded by Professor Florentin Smarandache in 1998; it constitutes further generalization of fuzzy and intuitionistic fuzzy theories. The key distinction between the neutrosophic set/logic and other types of sets/logics lies in the introduction of the degree of …
N-Refined Neutrosophic Rings, Florentin Smarandache, Mohammad Abobala
N-Refined Neutrosophic Rings, Florentin Smarandache, Mohammad Abobala
Branch Mathematics and Statistics Faculty and Staff Publications
The aim of this paper is to introduce the concept of n-refined neutrosophic ring as a generalization of refined neutrosophic ring. Also, we present concept of n-refined polynomial ring. We study some basic concepts related to these rings such as AH-subrings, AH-ideals, AH-factors, and AH-homomorphisms.
A Review On Superluminal Physics And Superluminal Communication In Light Of The Neutrosophic Logic Perspective, Victor Christianto, Florentin Smarandache
A Review On Superluminal Physics And Superluminal Communication In Light Of The Neutrosophic Logic Perspective, Victor Christianto, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
In a recent paper, we describe a model of quantum communication based on combining consciousness experiment and entanglement, which can serve as impetus to stop 5G-network-caused diseases. Therefore, in this paper we consider superluminal physics and superluminal communication as a bridge or intermediate way between subluminal physics and action-at-a-distance (AAAD) physics, especially from neutrosophic logic perspective. Although several ways have been proposed to bring such a superluminal communication into reality, such as Telluric wave or Telepathy analog of Horejev and Baburin, here we also review two possibilities: quaternion communication and also quantum communication based on quantum noise. Further research is …
Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao
Lattice-Reduction Aided Multiple-Symbol Differential Detection In Two-Way Relay Transmission, Chanfei Wang, Minghua Cao
Turkish Journal of Electrical Engineering and Computer Sciences
Multiple-symbol differential detection (MSDD) algorithms are proposed in two-way relay transmission (TWRT). Firstly, generalized likelihood ratio test based MSDD (GLRT-MSDD) is proposed in TWRT. Unfortunately, as the number of observation windows increases, the computational complexity of GLRT-MSDD increases exponentially. Hence, this detection in TWRT constitutes a challenging problem. Moreover, we find a way to reformulate the GLRTMSDD model and additionally propose a lattice-reduction aided MSDD (LR-MSDD) model. Performance analysis and simulations show that the proposed LR-MSDD provides bit-error rate performance close to that of GLRT-MSDD with lower complexity in TWRT.
A Population Based Simulated Annealing Algorithm For Capacitated Vehicle Routing Problem, İlhan İlhan
A Population Based Simulated Annealing Algorithm For Capacitated Vehicle Routing Problem, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The Vehicle Routing Problem (VRP) is one of the most discussed and researched topics nowadays. The VRP is briefly defined as the problem of identifying the best route to reduce distribution costs and improve the quality of service provided to customers. The Capacitated VRP (CVRP) is one of the most commonly researched among the VRP types. Therefore, the CVRP was studied in this paper and a new population based simulated annealing algorithm was proposed. In the algorithm, three different route development operators were used, which are exchange, insertion and reversion operators. It was tested on 63 well-known benchmark instances in …
Design Of A Spurious-Free Rf Frequency Synthesizer For Fast-Settling Receivers, Hi̇lmi̇ Kayhan Yilmaz, Serkan Topaloğlu
Design Of A Spurious-Free Rf Frequency Synthesizer For Fast-Settling Receivers, Hi̇lmi̇ Kayhan Yilmaz, Serkan Topaloğlu
Turkish Journal of Electrical Engineering and Computer Sciences
A tunable reference clock frequency topology is presented as a spur reduction application for frequency synthesizers of fast frequency hopping spread spectrum systems. The method was verified by measurements on a designed hardware operating at L-band frequencies. This spur reduction method is based on optimizing the reference clock frequency of synthesizers to mitigate spurs. By using the spur reduction method, the power of spurious signals was reduced up to 57 dB. The performance of the spur reduction method was also analyzed at different loop-filter configurations. Smaller lock time was obtained by enlarging the bandwidth of the loop filter up to …
Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D
Emulation Of Burst-Based Adaptive Link Rates In Netfpga Towards Green Networking, Shahul Hamead H, Mirnalinee Tt, Kavi Priya D
Turkish Journal of Electrical Engineering and Computer Sciences
In recent times, energy consumption in communication media has been increasing drastically. In the literature, energy-saving techniques that enable network devices to enter sleep state or limit the data rate have been proposed to reduce energy costs. In our earlier work, we proposed an energy-saving technique called burst-based adaptive link rate (BBALR), the simulation of which assures increased energy savings. In this paper, we have emulated the hardware implementation of BBALR and compared its performance with the outputs of other prominent energy-saving policies based on dynamic link rate adaption. The energy savings are mapped from the measured sleep time and …
Adjustable Testing Setup For A Single-Loop Optoelectronic Oscillator With Anelectrical Bandpass Filter, Mehmet Alp Ilgaz, Andrej Lavric, Temitope Odedeyi, Izzat Darwazeh, Bostjan Batagelj
Adjustable Testing Setup For A Single-Loop Optoelectronic Oscillator With Anelectrical Bandpass Filter, Mehmet Alp Ilgaz, Andrej Lavric, Temitope Odedeyi, Izzat Darwazeh, Bostjan Batagelj
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper we present a novel method to measure the free spectral range (FSR) and side-mode suppression ratio (SMSR) of an optoelectronic oscillator (OEO) by adjusting the optical fiber length using an optical path selector and signal source analyzer. We have designed a setup for a single-loop OEO operating around 5 GHz and 10 GHz that features electrical bandpass filters for side-mode suppression. The proposed approach makes it possible to evaluate the FSR and SMSR of OEOs with different optical fiber paths without requiring the changing of fiber spools or optical connectors. This approach could be useful for testbeds …
Combined Analytic Hierarchy Process And Binary Particle Swarm Optimization Formultiobjective Plug-In Electric Vehicles Charging Coordination With Time-Of-Usetariff, Junaid Bin Fakhrul Islam, Mir Toufikur Rahman, Hazlie Mokhlis, Mohamadariff Othman, Tengku Fiaz Tengku Mohmed Noor Izam, Hasmaini Mohamad
Combined Analytic Hierarchy Process And Binary Particle Swarm Optimization Formultiobjective Plug-In Electric Vehicles Charging Coordination With Time-Of-Usetariff, Junaid Bin Fakhrul Islam, Mir Toufikur Rahman, Hazlie Mokhlis, Mohamadariff Othman, Tengku Fiaz Tengku Mohmed Noor Izam, Hasmaini Mohamad
Turkish Journal of Electrical Engineering and Computer Sciences
Plug-in electric vehicles (PEVs) are gaining popularity as an alternative vehicle in the past few years. The charging activities of PEVs impose extra electrical load on residential distribution system as well as increasing operational cost. There are multiple conflicting requirements and constraints during the charging activities. Therefore, this paper presents multiobjective PEV charging coordination based on weighted sum technique to provide simultaneous benefits to the power utilities and PEV users. The optimization problem of the proposed coordination is solved using binary particle swam optimization. The objectives of the coordination are to (i) minimize daily power loss, (ii) maximize power delivery …
A Fully Batteryless Multiinput Single Inductor Single Output Energy Harvesting Architecture, Ridvan Umaz
A Fully Batteryless Multiinput Single Inductor Single Output Energy Harvesting Architecture, Ridvan Umaz
Turkish Journal of Electrical Engineering and Computer Sciences
Conventional energy architectures that utilize multiple ambient energy sources are initiated either by an external power supply or through the addition of an extra power source (e.g., battery) to the architecture. However, these interventions compromise the goal of a self-sustainable energy harvesting system. Moreover, conventional architectures are not effective in situations where space is limited (e.g., an artificial heart) or when access to this space is difficult (e.g., human implantable devices), due to their large battery size. Thus, conventional energy combiner circuits that use multiple energy sources are not well suited for supplying power to most applications. This paper presents …
An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil, Can Bariş Top
An Arbitrary Waveform Magnetic Nanoparticle Relaxometer With An Asymmetricalthree-Section Gradiometric Receive Coil, Can Bariş Top
Turkish Journal of Electrical Engineering and Computer Sciences
Magnetic nanoparticles (MNPs) have a wide range of clinical applications for imaging, therapy, and biosensing. Superparamagnetic MNPs can be directly visualized with high spatiotemporal resolution using the magnetic particle imaging (MPI) modality. The image resolution of MPI depends on the relaxation properties of the MNPs. Therefore, characterization of MNP response under alternating magnetic field excitation is necessary to predict MPI imaging performance and develop optimized MNPs. Biosensing applications also make use of the change in the relaxation response of MNPs after binding to a target agent. As MNP relaxation properties change with temperature and viscosity, noninvasive probing of these microenvironmental …
Low Harmonic 12-Pulse Rectifier With A Circulating Current Shaping Circuit, Jingfang Wang, Xuliang Yao, Qi Guan, Changji Deng, Shiyan Yang
Low Harmonic 12-Pulse Rectifier With A Circulating Current Shaping Circuit, Jingfang Wang, Xuliang Yao, Qi Guan, Changji Deng, Shiyan Yang
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a four-star 12-pulse diode rectifier with a circulating current shaping circuit (CCSC) on the DC side to decrease the input current harmonics effectively. The type of circulating current that can eliminate the input current harmonics is analysed and its waveform parameters are derived. The effects of triangular circulating current on the harmonics of the input current are analysed, and the harmonic suppression mechanism of the triangular circulating current is revealed. This scheme has excellent harmonic suppression capability, and the capacity of CCSC is only 2.35% of output power of the 12-pulse rectifier. Thus, this scheme is cost …
Deep Temporal Motion Descriptor (Dtmd) For Human Action Recognition, Nudrat Nida, Muhammad Haroon Yousaf, Aun Irtaza, Sergio A. Velastin
Deep Temporal Motion Descriptor (Dtmd) For Human Action Recognition, Nudrat Nida, Muhammad Haroon Yousaf, Aun Irtaza, Sergio A. Velastin
Turkish Journal of Electrical Engineering and Computer Sciences
Spatiotemporal features have significant importance in human action recognition, as they provide the actor's shape and motion characteristics specific to each action class. This paper presents a new deep spatiotemporal human action representation, the deep temporal motion descriptor (DTMD), which shares the attributes of holistic and deep learned features. To generate the DTMD descriptor, the actor?s silhouettes are gathered into single motion templates by applying motion history images. These motion templates capture the spatiotemporal movements of the actor and compactly represent the human actions using a single 2D template. Then deep convolutional neural networks are used to compute discriminative deep …
Deep Neural Network Based M-Learning Model For Predicting Mobile Learners'performance, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq, Arsalan Ali
Deep Neural Network Based M-Learning Model For Predicting Mobile Learners'performance, Muhammad Adnan, Asad Habib, Jawad Ashraf, Shafaq Mussadiq, Arsalan Ali
Turkish Journal of Electrical Engineering and Computer Sciences
The use of deep learning (DL) techniques for mobile learning is an emerging field aimed at developing methods for finding mobile learners' learning behavior and exploring important learning features. The learning features (learning time, learning location, repetition rate, content types, learning performance, learning time duration, and so on) act as fuel to DL algorithms based on which DL algorithms can classify mobile learners into different learning groups. In this study, a powerful and efficient m-learning model is proposed based on DL techniques to model the learning process of m-learners. The proposed m-learning model determines the impact of independent learning features …
Feature Points-Based Image Registration Between Satellite Imagery And Aerialimages Of Agricultural Land, Mohsin Abbas, Sajid Saleem, Fazli Subhan, Abdul Bais
Feature Points-Based Image Registration Between Satellite Imagery And Aerialimages Of Agricultural Land, Mohsin Abbas, Sajid Saleem, Fazli Subhan, Abdul Bais
Turkish Journal of Electrical Engineering and Computer Sciences
Rapid advancement in remote sensing sensors has resulted in an enormous increase in the use of satellite imagery (SI) and images taken from unmanned aerial vehicles (UAVs) in a wide range of remote sensing applications. These applications include urban planning, environment monitoring, map updating, change detection, and precision agriculture. This paper focuses on an agricultural application of SI and UAV images. SI-UAV images possess high temporal, textural, and intensity differences due to rapid changes in agricultural crops with the passage of time. Feature points such as scale invariant feature transform (SIFT), oriented FAST and rotated BRIEF (ORB), and speeded-up robust …
Implicit Relation-Based Question Answering To Answer Simple Questions Overdbpedia, Maryam Jamehshourani, Afsaneh Fatemi, Mohammadali Nematbakhsh
Implicit Relation-Based Question Answering To Answer Simple Questions Overdbpedia, Maryam Jamehshourani, Afsaneh Fatemi, Mohammadali Nematbakhsh
Turkish Journal of Electrical Engineering and Computer Sciences
RDF-based question answering systems give users the capability of natural language querying over RDF data. In order to respond to natural language questions, it is necessary that the main concept of the question be interpreted correctly, and then it is mapped to RDF data. A natural language question includes entities, classes, and implicit and explicit relationships. In this article, by focusing on identification and mapping of implicit relationships in the question (in addition to the explicit relationships), the mapping step has been improved. In the proposed solution (IRQA), entities and implicit/explicit relationships are identified by means of the provided rules …
Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin
Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin
Electrical & Computer Engineering Faculty Publications
We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through five passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level rf system configured such that a cavity fault triggers waveform recordings of 17 rf signals for each of the eight cavities in the cryomodule. Subject matter experts are able to analyze the collected time-series data and identify which of the …
Fault Identification Of Catenary Dropper Based On Improved Capsnet, Jianpeng Bian, Jiaxing Hao, Shuai Zhao, Weijing Hua, Shichuang Gao
Fault Identification Of Catenary Dropper Based On Improved Capsnet, Jianpeng Bian, Jiaxing Hao, Shuai Zhao, Weijing Hua, Shichuang Gao
Turkish Journal of Electrical Engineering and Computer Sciences
Traditional fault identification algorithms applied to catenary dropper suffer from various problems due to its small contact area. These problems include misidentification and lower recognition rate of the faulty dropper. Compared with the traditional convolutional neural network, the vector is utilized as the input of the capsule network (CapsNet) for the first time, which can well retain the feature information such as the direction and angle of the target, and is more suitable for identifying the dropper under complex background. Therefore, this paper proposes a dropper fault identification algorithm based on improved capsule network. The convolutional layer of traditional 9×9 …
A Fabrication-Oriented Remeshing Method For Auxetic Pattern Extraction, Levend Mehmet Mert, Ulaş Yaman, Yusuf Sahi̇lli̇oğlu
A Fabrication-Oriented Remeshing Method For Auxetic Pattern Extraction, Levend Mehmet Mert, Ulaş Yaman, Yusuf Sahi̇lli̇oğlu
Turkish Journal of Electrical Engineering and Computer Sciences
We propose a method for extracting auxetic patterns from meshes for fabrication by modifying the existing mesh primitives directly and fully automatically. This direct approach is novel in the sense that most of the fabricationoriented surface tiling methods introduce additional primitives, such as curve networks in an interactive semiautomatic framework. Our method is based on a remeshing procedure that converts a given quad mesh with arbitrary topology into our desired structure that is ready to be fabricated. The main advantages of establishing auxetic patterns on meshes are the achieved flexibility using cheap inflexible materials as well as less material usage …
User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç
User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an earlier method proposed by the authors to make smart recommendations utilizing artificial intelligence and the latest technologies developed for the television area is expanded further using controlled clustering with genetic algorithms (CCGA). For this purpose, genetic algorithms (GAs), artificial neural networks (ANNs), and hybrid broadcast broadband television (HbbTV) are combined to get the users' television viewing habits and to create profiles. Then television programs are recommended to the users based on that profiling. The data gathered by the developed HbbTV application for previous studies are reused in this study. These data are employed to cluster users. …