Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (977)
- Artificial Intelligence and Robotics (965)
- Computer Engineering (689)
- Databases and Information Systems (448)
- Numerical Analysis and Scientific Computing (405)
-
- Operations Research, Systems Engineering and Industrial Engineering (337)
- Information Security (335)
- Electrical and Computer Engineering (297)
- Systems Science (287)
- Social and Behavioral Sciences (262)
- Software Engineering (257)
- Graphics and Human Computer Interfaces (187)
- Mathematics (177)
- Business (167)
- Medicine and Health Sciences (159)
- Data Science (141)
- Other Computer Sciences (138)
- Theory and Algorithms (123)
- Life Sciences (114)
- Education (106)
- Physics (91)
- OS and Networks (74)
- Arts and Humanities (70)
- Public Affairs, Public Policy and Public Administration (68)
- Programming Languages and Compilers (62)
- Law (60)
- Chemistry (59)
- Biology (54)
- Institution
-
- Singapore Management University (577)
- China Simulation Federation (281)
- TÜBİTAK (166)
- Old Dominion University (151)
- University of Texas at El Paso (144)
-
- Kennesaw State University (137)
- MBZUAI (134)
- Chulalongkorn University (108)
- Zayed University (103)
- Missouri University of Science and Technology (73)
- Technological University Dublin (70)
- Air Force Institute of Technology (63)
- City University of New York (CUNY) (61)
- University of Nebraska - Lincoln (54)
- Karbala International Journal of Modern Science (49)
- Walden University (48)
- San Jose State University (42)
- University of Central Florida (41)
- University of Arkansas, Fayetteville (40)
- Boise State University (35)
- Loyola University Chicago (33)
- University of South Carolina (33)
- Embry-Riddle Aeronautical University (32)
- Wright State University (31)
- University of South Florida (30)
- University of Texas at Arlington (28)
- Portland State University (27)
- University of Texas Rio Grande Valley (26)
- Chapman University (25)
- Edith Cowan University (24)
- Keyword
-
- Machine learning (177)
- Deep learning (157)
- Technical Reports (129)
- UTEP Computer Science Department (129)
- Artificial intelligence (98)
-
- Machine Learning (85)
- Cybersecurity (62)
- Deep Learning (52)
- Computer Science (48)
- Security (46)
- COVID-19 (44)
- Computer vision (44)
- Blockchain (43)
- Natural language processing (33)
- Artificial Intelligence (32)
- Privacy (32)
- Neural networks (31)
- Optimization (31)
- AI (28)
- Classification (23)
- Internet of Things (23)
- Reinforcement learning (22)
- Department of Computer Science and Engineering (21)
- IoT (21)
- Virtual reality (21)
- Anomaly detection (20)
- Simulation (20)
- Feature extraction (19)
- Object detection (19)
- Semantics (19)
- Publication
-
- Research Collection School Of Computing and Information Systems (540)
- Journal of System Simulation (281)
- Turkish Journal of Electrical Engineering and Computer Sciences (166)
- Departmental Technical Reports (CS) (129)
- Theses and Dissertations (121)
-
- Chulalongkorn University Theses and Dissertations (Chula ETD) (108)
- All Works (103)
- C-Day Computing Showcase (90)
- Machine Learning Faculty Publications (67)
- Computer Science Faculty Research & Creative Works (58)
- Computer Science Faculty Publications (55)
- Articles (49)
- Karbala International Journal of Modern Science (49)
- Computer Vision Faculty Publications (48)
- Walden Dissertations and Doctoral Studies (48)
- Master's Projects (33)
- Faculty Publications (31)
- Cybersecurity Undergraduate Research Showcase (30)
- Electronic Theses and Dissertations, 2020-2023 (30)
- Computer Science Faculty Publications and Presentations (29)
- Dissertations (29)
- School of Computing: Faculty Publications (29)
- Publications and Research (28)
- Electronic Theses and Dissertations (26)
- Computer Science: Faculty Publications and Other Works (25)
- USF Tampa Graduate Theses and Dissertations (25)
- Browse all Theses and Dissertations (21)
- Graduate Theses and Dissertations (21)
- Research outputs 2022 to 2026 (21)
- Tanzania Journal of Engineering and Technology (TJET) (21)
- Publication Type
- File Type
Articles 2491 - 2520 of 3613
Full-Text Articles in Computer Sciences
Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry
Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry
Theses and Dissertations
The software verification in this thesis concentrates on verifying a particle filter for use in tracking and estimation, a key application area for the Air Force. The development and verification process described in this thesis is a demonstration of the power, limitation, and compromises involved in applying automated software verification tools to critical embedded software applications.
Independent Closed Loop Control Of Di/Dt And Dv/Dt For High Power Igbts, Osman Tanriverdi̇, Deni̇z Yildirim
Independent Closed Loop Control Of Di/Dt And Dv/Dt For High Power Igbts, Osman Tanriverdi̇, Deni̇z Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
As the insulated gate bipolar transistor (IGBT) modules have their own specific characteristic switching forms, their turn-on and turn-off times are changed according to practical applications. For the conventional gate drives, gate resistors are used to adjust the turn-on and turn-off times which change switching losses that have a significant amount in total losses. Collector current rate of change, $di_{C}/ dt$ and collector-emitter rate of change, $dv_{CE}/ dt$ are dependent on each other and they affect operating parameters in high power converters. Relations between current and voltages during the switching transitions are given and effects of the changes in electrical …
Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu
Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Centroid based clustering approaches, such as k-means, are relatively fast but inaccurate for arbitrary shape clusters. Fuzzy c-means with Mahalanobis distance can accurately identify clusters if data set can be modelled by a mixture of Gaussian distributions. However, they require number of clusters apriori and a bad initialization can cause poor results. Density based clustering methods, such as DBSCAN, overcome these disadvantages. However, they may perform poorly when the dataset is imbalanced. This paper proposes a clustering method, named clustering with density initialization and Bhattacharyya based merging based on the fuzzy clustering. The initialization is carried out by density estimation …
Photonic Integrated Circuit-Assisted Optical Time-Domainreflectometer System, Mehmet Cengi̇z Onbaşli
Photonic Integrated Circuit-Assisted Optical Time-Domainreflectometer System, Mehmet Cengi̇z Onbaşli
Turkish Journal of Electrical Engineering and Computer Sciences
Optical time-domain reflectometers (OTDR) are photonic systems that consist of an interrogator, a receiver and a fiber optical cable and have applications in telecommunications, security, environmental monitoring, distributed temperature and strain sensing. Since OTDR systems are bulk optical setups that consume multiple Watts of power, have large mass and volume footprint and are vulnerable to thermal drift, deployment of OTDR systems in the field is expensive, complicated and may not necessarily yield accurate sensing results. Thus, a compact, low-power, inexpensive and thermal drift-free OTDR system needs to be developed for improving the accuracy and the viability of OTDR in the …
Calculating Influence Based On The Fusion Of Interest Similarity And Informationdissemination Ability, Shulin Cheng, Ziming Wang, Meng Qian, Shan Yang, Xin Zheng
Calculating Influence Based On The Fusion Of Interest Similarity And Informationdissemination Ability, Shulin Cheng, Ziming Wang, Meng Qian, Shan Yang, Xin Zheng
Turkish Journal of Electrical Engineering and Computer Sciences
With the popularization, in-depth development and application of the Internet, microblogs have become a mainstream social network platform. Several studies on social networks have conducted researches, and user influence evaluation is an important research hotspot. Most of the existing studies calculate user influence by improving PageRank and have achieved certain results. However, these studies ignored the fusion of users' interest theme similarity and information dissemination ability, and the analysis of interaction behaviors among users is not comprehensive. To address these issues, we propose a new microblog user influence algorithm called microblog user influence based on interest similarity and information dissemination …
Performance Analysis And Feature Selection For Network-Based Intrusion Detectionwith Deep Learning, Serhat Caner, Nesli̇ Erdoğmuş, Yusuf Murat Erten
Performance Analysis And Feature Selection For Network-Based Intrusion Detectionwith Deep Learning, Serhat Caner, Nesli̇ Erdoğmuş, Yusuf Murat Erten
Turkish Journal of Electrical Engineering and Computer Sciences
An intrusion detection system is an automated monitoring tool that analyzes network traffic and detects malicious activities by looking out either for known patterns of attacks or for an anomaly. In this study, intrusion detection and classification performances of different deep learning based systems are examined. For this purpose, 24 deep neural networks with four different architectures are trained and evaluated on CICIDS2017 dataset. Furthermore, the best performing model is utilized to inspect raw network traffic features and rank them with respect to their contributions to success rates. By selecting features with respect to their ranks, sets of varying size …
Modeling And Evaluation Of Soc-Based Coordinated Ev Charging For Powermanagement In A Distribution System, Murat Akil, Emrah Dokur, Ramazan Bayindir
Modeling And Evaluation Of Soc-Based Coordinated Ev Charging For Powermanagement In A Distribution System, Murat Akil, Emrah Dokur, Ramazan Bayindir
Turkish Journal of Electrical Engineering and Computer Sciences
The importance of using clean energy in electrical energy generation and transportation network planning has recently increased due to carbon footprint rising. In this direction, the use of electric vehicles (EV), known as ultra-low carbon emission vehicles, has become widespread in addition to renewable energy sources (RES) such as wind and photovoltaic (PV) power generations. The trend of EVs to be preferred the primary means of transport has revealed the effects of charging an additional load on the grid. There is a need to create coordinated charging methods by considering the approaches for real-time charging models of EVs. In this …
Improving Utilization Rate Of Semi-Parallel Successive Cancellation Architecture For Polar Codes Using 2-Bit Decoding, Dinesh Kumar Devadoss, Shantha Selva Kumari Rama Packiam
Improving Utilization Rate Of Semi-Parallel Successive Cancellation Architecture For Polar Codes Using 2-Bit Decoding, Dinesh Kumar Devadoss, Shantha Selva Kumari Rama Packiam
Turkish Journal of Electrical Engineering and Computer Sciences
Polar codes are the capacity-achieving error-correcting code proved to be a significant invention in coding theory. It can achieve channel capacity at infinite code length N due to its explicit code construction. However, the processing complexity along with the higher latency due to successive cancellation (SC) decoding is being a major design issue, which reduces the utilization rate in the decoder architectures. This paper presents a modified semi-parallel architecture for decoding polar code with a better decoding latency. Precomputation and look-ahead techniques are used to generate two bits in the final stage. Pipelined partial-sum unit with a less critical path …
Predictive Optimization Of Sliding Mode Control Using Recurrent Neural Paradigmfor Nonlinear Dfig-Wpgs During Distorted Voltage, Omar Busati, Xiangjie Liu
Predictive Optimization Of Sliding Mode Control Using Recurrent Neural Paradigmfor Nonlinear Dfig-Wpgs During Distorted Voltage, Omar Busati, Xiangjie Liu
Turkish Journal of Electrical Engineering and Computer Sciences
Dynamic characteristics of the doubly-fed induction generator (DFIG)-based wind power generation (WPGS) are fully nonlinear. Therefore, issues such as stability and achieving high efficiency, especially under harmonics behavior, are challenges that assess the control strategy reliability to find the perfect dynamic solution. This discussion offers a control strategy for the separated stator-port power using a predictive sliding mode strategy with a resonant function (PSMC-R) based on a deep recurrent neural network (DRNN). DRNN is formed as a low-order Taylor series formula. PSMC-R predicts the perfect switching surface path and regulates the distorted nonlinear DFIG with several dynamic aims. This approach …
Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz
Forecasting Tv Ratings Of Turkish Television Series Using A Two-Level Machinelearning Framework, Büşranur Akgül, Tayfun Küçükyilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
TV rating is a numeric estimate of the popularity of television programs. Forecasting TV ratings is considered an important asset for investment planning of media due to its potential of reducing the risks of future ventures. The aim of this study is to develop a machine learning model capable of efficiently forecasting the TV ratings of Turkish TV series in a practical manner. To this end, two prediction models were proposed for forecasting the TV ratings of television series, facilitating an extensive set of features. A contribution of this study is the inclusion of social media-based features using search trends …
Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş
Design And Aerodynamic Analysis Of A Vtol Tilt-Wing Uav, Hasan Çakir, Di̇lek Funda Kurtuluş
Turkish Journal of Electrical Engineering and Computer Sciences
The aerodynamic design and analysis of an Unmanned Air Vehicle, capable of vertical take-off and landing by employing fixed four rotors on the tilt-wing and two rotors on the tilt-tail, will be presented in this study. Both main wing and the horizontal tail can be tilted 90°. During VTOL, transition and forward flight, aerodynamic and thrust forces have been employed. Different flight conditions, including the effects of angle of attack, side slip, wing tilt angle and control surfaces deflection angle changes, have been studied with CFD analysis. For a Tilt-Wing UAV, there are challenges like high non-linearity, vulnerability to disturbances …
Reactive Power Sharing And Voltage Restoration In Islanded Ac Microgrids, Khurram Hashmi, Rizwan Ali, Muhammad Hanan, Waseem Aslam, Abubakar Siddique, Muhammad Mansoor Khan
Reactive Power Sharing And Voltage Restoration In Islanded Ac Microgrids, Khurram Hashmi, Rizwan Ali, Muhammad Hanan, Waseem Aslam, Abubakar Siddique, Muhammad Mansoor Khan
Turkish Journal of Electrical Engineering and Computer Sciences
Microgrids (MG) are a new and innovative concept in modern distribution networks. Several challenges are associated with the operation and control of MG networks. Active and reactive power sharing among energy resources interfaced through power electronic conversion stages is a major challenge. Although active power sharing can be achieved under varying scenarios, sharing of reactive power between distributed generation units is difficult to achieve. This paper presents a novel and innovative control scheme to ensure sharing of reactive power between Distributed generation units within an autonomous, islanded AC microgrid. A framework composed of novel multiagent moving average estimators is proposed …
Robust Position/Force Control Of Nonholonomic Mobile Manipulator Forconstrained Motion On Surface In Task Space, Güli̇n Eli̇bol Seçi̇l, Serhat Obuz, Osman Parlaktuna
Robust Position/Force Control Of Nonholonomic Mobile Manipulator Forconstrained Motion On Surface In Task Space, Güli̇n Eli̇bol Seçi̇l, Serhat Obuz, Osman Parlaktuna
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a robust controller is developed for a mobile manipulator (MM) to track reference position/force trajectories. Nonholonomic and holonomic constraints are considered for the mobile platform and manipulator, respectively. Additionally, the control design considers the uncertainties in parameters of the dynamics of the mobile manipulator with a bounded time varying additive disturbance (unmodelled effects, external disturbances). A Lyapunov-based stability analysis is used to prove semiglobal uniform ultimate boundedness of the tracking error signals and the position/force of the system track to an arbitrarily small neighborhood of the reference trajectories. Numerical results for a mobile manipulator, which is formed …
Design And Manufacture Of Electromagnetic Absorber Composed Of Boricacid-Incorporated Wastepaper Composites, Ali̇ İhsan Kaya, Ahmet Çi̇fci̇, Fi̇li̇z Kirdioğullari, Mesud Kahri̇man, Osman Çerezci̇
Design And Manufacture Of Electromagnetic Absorber Composed Of Boricacid-Incorporated Wastepaper Composites, Ali̇ İhsan Kaya, Ahmet Çi̇fci̇, Fi̇li̇z Kirdioğullari, Mesud Kahri̇man, Osman Çerezci̇
Turkish Journal of Electrical Engineering and Computer Sciences
With the effect of technological advances, the use of electrical and electronic devices has increased dramatically in recent years. Wireless technologies and related applications are mostly preferred for the communication of these devices with each other. Thus, people are easily exposed to electromagnetic waves in daily life. The extensive global use of these devices raises the question of their possible biological effects on human health. Also, electromagnetic waves influence the functioning of a nearby device. In this study, an electromagnetic absorber based on boric acid (5, 10, 20, and 30 wt%) added wastepaper was developed. Copper (Cu) and aluminum (Al) …
A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇
A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇
Turkish Journal of Electrical Engineering and Computer Sciences
Recommender systems provide their users an efficient way to handle information overload problem by offering personalized suggestions. Traditional recommender systems are based on two-dimensional user-item preference matrix constructed depending on the users' overall evaluations over items. However, they have begun to present their preferences under various circumstances. Thus, traditional recommendation techniques fail to process multicriteria ratings during the recommendation process. Multicriteria recommender systems are an extension of traditional recommender systems that utilize multicriteria-based user preferences. Multicriteria recommender systems provide more personalized and accurate predictions compared to traditional recommender systems. However, the increased amount of data dimension causes sparsity to be …
Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft
Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft
Turkish Journal of Electrical Engineering and Computer Sciences
The massive use of social media causes rapid information dissemination that amplifies harmful messages such as fake news. Fake-news is misleading information presented as factual news that is generally used to manipulate public opinion. In particular, fake news related to COVID-19 is defined as 'infodemic' by World Health Organization. An infodemic is a misleading information that causes confusion which may harm health. There is a high volume of misinformation about COVID-19 that causes panic and high stress. Therefore, the importance of development of COVID-19 related fake news identification model is clear and it is particularly important for Turkish language from …
Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan
Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan
Turkish Journal of Electrical Engineering and Computer Sciences
Electric vehicles (EVs) exhibit several benefits over combustion engine vehicles, making them an attractive mode of mobility for the future. However, supplying the electrical energy required to recharge their batteries could adversely affect the power system infrastructure. The most severe impact of EV integration is expected to be on the distribution transformers, which are among the costliest equipment in the distribution network. Sustained overloads on the transformer could lead to accelerated aging and early retirement. As the rate of EV deployment rises, so does the probability of transformer overloads and the subsequent loss of life. There is a need for …
A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani
A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani
Turkish Journal of Electrical Engineering and Computer Sciences
A new design of current mode instrumentation amplifier (CMIA) with tunable gain and low voltage operation capability is proposed in this paper, which is suitable for biomedical signals processing, especially in electrocardiogram (ECG). It consists of a new design of current differencing transconductance amplifier (CDTA) and dual z copy CDTA (DZC-CDTA). The gain of the proposed CMIA is controlled by a MOS-based tunable resistor. The main advantage of the proposed CMIA is its high gain that can be tuned over a significant range with the help of two resistances. The performance of the proposed instrumentation amplifier is evaluated through simulation …
A Bi-Level Charging Management Approach For Electric Truck Charging Stationconsidering Power Losses, Tayfur Gökçek, Mehmet Tan Turan, Yavuz Ateş, Ahmet Yi̇ği̇t Arabul
A Bi-Level Charging Management Approach For Electric Truck Charging Stationconsidering Power Losses, Tayfur Gökçek, Mehmet Tan Turan, Yavuz Ateş, Ahmet Yi̇ği̇t Arabul
Turkish Journal of Electrical Engineering and Computer Sciences
This article presents an optimized heavy duty electric truck charging station (ETCS) design based on bi-level mixed integer linear programming. Electric truck parameters are integrated with the grid model and charging sequences are firstly formulated to optimize charging stages. As the second level of the optimization stage, line losses are aimed to be minimized for the charging station. ETCS model is obtained from actual parameters of the Istanbul Muratbey Customs zone which is one of the busiest customs zone in Europe and an ideal location for ETCS application in the future. The ETCS is equipped with roof type photovoltaic (PV) …
Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah
Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning (DL) models are currently not widely deployed for critical tasks such as in health. This is attributable to the "black box", making it difficult to gain the trust of practitioners. This paper proposes the use of visualizations to enhance performance verification, improve monitoring, ensure understandability, and improve interpretability needed to gain practitioners' confidence. These are demonstrated through the development of a CapsNet model for the recognition of gastrointestinal tract infection. The gastrointestinal tract comprises several organs joined in a long tube from the mouth to the anus. It is susceptive to diseases that are difficult for medics to …
45-Nm Cds Qds Photoluminescent Filter For Photovoltaic Conversionefficiency Recovery, Victor Juárez-Luna, Daniel Sauceda-Carvajal, Ivett Zavala-Guillen, Enrique Rodarte-Guajardo, Francisco Carranza-Chávez, Carlos Villa Angulo
45-Nm Cds Qds Photoluminescent Filter For Photovoltaic Conversionefficiency Recovery, Victor Juárez-Luna, Daniel Sauceda-Carvajal, Ivett Zavala-Guillen, Enrique Rodarte-Guajardo, Francisco Carranza-Chávez, Carlos Villa Angulo
Turkish Journal of Electrical Engineering and Computer Sciences
Different energy loss mechanisms have restricted the breakthroughs in concentrated photovoltaic/thermal (CPVT) hybrid solar systems that use photoluminescent filters. Re?ected and transmitted light, emission spectrum, nonideal absorption, Stokes shift (proportional to $f_1 f_2$), overlapping absorption, and scattering of light are mechanisms in photoluminescent filters that restrict optical efficiency to below theoretical limits. In addition, increases in temperature by light concentration affect the operation of photovoltaic cells and photoluminescent filters because of an increase in molecular motion and collisions that consequently lead to energy loss. Meanwhile, nanocrystals or quantum dots (QDs) from groups II VI hold electrical, optical, chemical, and physical …
Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao
Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao
Turkish Journal of Electrical Engineering and Computer Sciences
This paper is devoted to revealing some properties of the probabilistic optimal power flow (POPF) problem. In conjunction with Hermite polynomial model, Nataf transformation is introduced to map POPF problem to the independent standard normal space. Firstly, a multivariate polynomial model is employed to represent the function relationship between POPF inputs and outputs. Then, moment matching equations are derived to characterize the uncertainty effects of POPF inputs on outputs; three cubature rules are derived to calculate statistical moments of POPF outputs. Finally, along with Monte Carlo simulation method, the proposed methods are tested on IEEE 57-bus system and IEEE 118-bus …
Event-Related Microblog Retrieval In Turkish, Çağri Toraman
Event-Related Microblog Retrieval In Turkish, Çağri Toraman
Turkish Journal of Electrical Engineering and Computer Sciences
Microblogs, such as tweets, are short messages in which users are able to share any opinion and information. Microblogs are mostly related to real-life events reported in news articles. Finding event-related microblogs is important to analyze online social networks and understand public opinion on events. However, finding such microblogs is a challenging task due to the dynamic nature of microblogs and their limited length. In this study, assuming that news articles are given as queries and microblogs as documents, we find event-related microblogs in Turkish. In order to represent news articles and microblogs, we examine encoding methods, namely traditional bag-of-words …
Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu
Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Determining identity is a crucial task especially in the cases of mass disasters such as tsunamis, earthquakes, fires, epidemics, and in forensics. Although there are various studies in the literature on biometric identification from radiographic dental images, more research is still required. In this study, a panoramic dental radiographic (PDR) imagebased human identification system was developed using a customized deep convolutional neural network model in a few-shot learning scheme. The proposed model (PDR-net) was trained on 600 PDR images obtained from a total of 300 patients. As the PDR images of the patients were very different in terms of pose …
Identification Of Gain And Phase Margins Based Robust Stability Regions For Atime-Delayed Micro-Grid System Including Fractional-Order Controller In Presenceof Renewable Power Generation, Hakan Gündüz, Şahi̇n Sönmez, Saffet Ayasun
Identification Of Gain And Phase Margins Based Robust Stability Regions For Atime-Delayed Micro-Grid System Including Fractional-Order Controller In Presenceof Renewable Power Generation, Hakan Gündüz, Şahi̇n Sönmez, Saffet Ayasun
Turkish Journal of Electrical Engineering and Computer Sciences
This study examines the gain and phase margins (GPMs) based robust stability margins in the parameter space of fractional order proportional-integral (FOPI) controller for a micro-grid (MG) system with communication time delays. Fluctuations in renewable energy sources (RESs), uncertainties in parameters of system components and communication delays could adversely affect the dynamical analysis and frequency stability of the MG system. Such a MG system has an interval characteristic due to the parametric variations and the interval transfer functions defined by Kharitonov's theorem, which presents a solution for checking of robust stability. Therefore, this study addresses the robust stability regions containing …
Classifying Dead Code In Software Development, Arman Alavizadeh
Classifying Dead Code In Software Development, Arman Alavizadeh
University Honors Theses
Dead code pervades as an issue in the world of software development as a source of many famous software disasters such as the ARIANE 5 rocket failure and chemical bank withdrawal error. Defining dead code on narrow levels of granularity has not been fully explored, yet is crucial to better our understanding of dead code. Here we will be starting a discussion on how to approach classifying dead code via comparing dead code research specific to an industry segment. Research will be compared primarily by methodology and limitations. Dead code subtype classifications are gleaned from research comparisons and can serve …
The 10th Annual Computer Science Workshop, Submissions, Abstract Template, Computer Science Department
The 10th Annual Computer Science Workshop, Submissions, Abstract Template, Computer Science Department
Computer Science Faculty Proceedings & Presentations
This is the abstract template for the 10th Annual Computer Science Graduate Research Workshop (2022). To learn more about this workshop, please visit: https://digitalcommons.unomaha.edu/csworkshop/2022/.
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Articles
Healthcare systems are under siege globally regarding technology adoption; the recent pandemic has only magnified the issues. Providers and patients alike look to new enabling technologies to establish real-time connectivity and capability for a growing range of remote telehealth solutions. The migration to new technology is not as seamless as clinicians and patients would like since the new workflows pose new responsibilities and barriers to adoption across the telehealth ecosystem. Technology-mediated workflows (integrated software and personal medical devices) are increasingly important in patient-centered healthcare; software-intense systems will become integral in prescribed treatment plans [1]. My research explored the path to …
Deep Learning Model With Adaptive Regularization For Eeg-Based Emotion Recognition Using Temporal And Frequency Features, Alireza Samavat, Ebrahim Khalili, Bentolhoda Ayati, Marzieh Ayati
Deep Learning Model With Adaptive Regularization For Eeg-Based Emotion Recognition Using Temporal And Frequency Features, Alireza Samavat, Ebrahim Khalili, Bentolhoda Ayati, Marzieh Ayati
Computer Science Faculty Publications
Since EEG signal acquisition is non-invasive and portable, it is convenient to be used for different applications. Recognizing emotions based on Brain-Computer Interface (BCI) is an important active BCI paradigm for recognizing the inner state of persons. There are extensive studies about emotion recognition, most of which heavily rely on staged complex handcrafted EEG feature extraction and classifier design. In this paper, we propose a hybrid multi-input deep model with convolution neural networks (CNNs) and bidirectional Long Short-term Memory (Bi-LSTM). CNNs extract time-invariant features from raw EEG data, and Bi-LSTM allows long-range lateral interactions between features. First, we propose a …
Faster Multidimensional Data Queries On Infrastructure Monitoring Systems, Yinghua Qin, Gheorghi Guzun
Faster Multidimensional Data Queries On Infrastructure Monitoring Systems, Yinghua Qin, Gheorghi Guzun
Faculty Research, Scholarly, and Creative Activity
The analytics in online performance monitoring systems have often been limited due to the query performance of large scale multidimensional data. In this paper, we introduce a faster query approach using the bit-sliced index (BSI). Our study covers multidimensional grouping and preference top-k queries with the BSI, algorithms design, time complexity evaluation, and the query time comparison on a real-time production performance monitoring system. Our research work extended the BSI algorithms to cover attributes filtering and multidimensional grouping. We evaluated the query time with the single attribute, multiple attributes, feature filtering, and multidimensional grouping. To compare with the existing prior …