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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Influence Of Defects On In-Plane Dynamic Properties Of Hexagonal Ligament Chiral Structures, Ning An, Xunwen Su, Dongmei Zhu, Mileta M. Tomovic
Influence Of Defects On In-Plane Dynamic Properties Of Hexagonal Ligament Chiral Structures, Ning An, Xunwen Su, Dongmei Zhu, Mileta M. Tomovic
Engineering Technology Faculty Publications
Although the six-ligament chiral structure has many unique properties, due to its special structure, the stress concentration is prone to defects. In addition, additive manufacturing is also prone to defects. This paper studies the effect of defects, which is helpful for the better application of the six-ligament chiral structure. Several new six-ligament chiral structures with random and concentrated defects were designed to explore the effects of the defects on the in-plane dynamic properties. The structures were studied with the finite element ANSYS/LSDYNA numerical simulation and experimental methods. According to the defect-free six-ligament chiral structures exhibiting different deformation modes at different …
Security Concerns On Machine Learning Solutions For 6g Networks In Mmwave Beam Prediction, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Devrim Unal
Security Concerns On Machine Learning Solutions For 6g Networks In Mmwave Beam Prediction, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Devrim Unal
Engineering Technology Faculty Publications
6G – sixth generation – is the latest cellular technology currently under development for wireless communication systems. In recent years, machine learning (ML) algorithms have been applied widely in various fields, such as healthcare, transportation, energy, autonomous cars, and many more. Those algorithms have also been used in communication technologies to improve the system performance in terms of frequency spectrum usage, latency, and security. With the rapid developments of ML techniques, especially deep learning (DL), it is critical to consider the security concern when applying the algorithms. While ML algorithms offer significant advantages for 6G networks, security concerns on artificial …
A Pilot Course As A Step Towards New Academic Programs In Renewable Energies, Otilia Popescu, Orlando Ayala, Isaac Flory, Jose Fernandez, Vukica Jovanović
A Pilot Course As A Step Towards New Academic Programs In Renewable Energies, Otilia Popescu, Orlando Ayala, Isaac Flory, Jose Fernandez, Vukica Jovanović
Engineering Technology Faculty Publications
The challenges arising from climate change have never before in human history been more pressing for solutions. Addressing pollution and the transition to clean energies are essential problems to solve in the upcoming decades. The process of transitioning to renewable energies has started already, with some states leading the process. As the development of industries sees a fast growth, the supply of qualified engineers and technicians to support these industries needs to keep up. At the community college level, some efforts have already started to introduce courses on renewable energies as well as boot camps or certifications to prepare the …
Augmented Reality Integrated Welder Training For Mechanical Engineering Technology, Aditya Akundi, Hamid Eisazadeh, Mona Torabizadeh
Augmented Reality Integrated Welder Training For Mechanical Engineering Technology, Aditya Akundi, Hamid Eisazadeh, Mona Torabizadeh
Engineering Technology Faculty Publications
The shortage of welders is well documented and projected to become more severe for various industries such as shipbuilding in coming years. It is mainly because welding training is a critical and often costly endeavor. This study examines the training potential using augmented reality technology as a critical part of welder training for mechanical engineering technology students. This study assessed the performance of two groups of MET students trained with two different methods. One group received training with the traditional method in three sessions. The second group acquired training initially with an augmented reality welding system for three sessions. Then, …
Development Of Experiential Learning Experiences For K-12 Students Focusing On Smart Cities, Murat Kuzlu, Vukica Jovanovic, Nathan Puryear, Patrick J. Martin, Sherif Abdelwahed, Özgür Güler
Development Of Experiential Learning Experiences For K-12 Students Focusing On Smart Cities, Murat Kuzlu, Vukica Jovanovic, Nathan Puryear, Patrick J. Martin, Sherif Abdelwahed, Özgür Güler
Engineering Technology Faculty Publications
The main objective of this paper is to describe a project focused on the development of experiential learning experiences for undergraduate and graduate students focusing on smart cities. The future workforce needs students with various data analytics skills, service reliability, and sustainability. The team of researchers from Old Dominion University and Virginia Commonwealth University is developing a virtual smart city lab environment at both universities and collaborating on multiple research projects. The main purpose of this virtual labs is to provide a testbed that can be used for students who are interested in careers related to cyber-physical systems (CPS). These …
Defensive Distillation-Based Adversarial Attack Mitigation Method For Channel Estimation Using Deep Learning Models In Next-Generation Wireless Networks, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Ozgur Guler
Defensive Distillation-Based Adversarial Attack Mitigation Method For Channel Estimation Using Deep Learning Models In Next-Generation Wireless Networks, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Umit Cali, Ozgur Guler
Engineering Technology Faculty Publications
Future wireless networks (5G and beyond), also known as Next Generation or NextG, are the vision of forthcoming cellular systems, connecting billions of devices and people together. In the last decades, cellular networks have dramatically grown with advanced telecommunication technologies for high-speed data transmission, high cell capacity, and low latency. The main goal of those technologies is to support a wide range of new applications, such as virtual reality, metaverse, telehealth, online education, autonomous and flying vehicles, smart cities, smart grids, advanced manufacturing, and many more. The key motivation of NextG networks is to meet the high demand for those …
Bfv-Based Homomorphic Encryption For Privacy-Preserving Cnn Models, Febrianti Wibawa, Ferhat Ozgur Catak, Salih Sarp, Murat Kuzlu
Bfv-Based Homomorphic Encryption For Privacy-Preserving Cnn Models, Febrianti Wibawa, Ferhat Ozgur Catak, Salih Sarp, Murat Kuzlu
Engineering Technology Faculty Publications
Medical data is frequently quite sensitive in terms of data privacy and security. Federated learning has been used to increase the privacy and security of medical data, which is a sort of machine learning technique. The training data is disseminated across numerous machines in federated learning, and the learning process is collaborative. There are numerous privacy attacks on deep learning (DL) models that attackers can use to obtain sensitive information. As a result, the DL model should be safeguarded from adversarial attacks, particularly in medical data applications. Homomorphic encryption-based model security from the adversarial collaborator is one of the answers …
Security Hardening Of Intelligent Reflecting Surfaces Against Adversarial Machine Learning Attacks, Ferhat Ozgur Catak, Murat Kuzlu, Haolin Tang, Evren Catak, Yanxiao Zhao
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 …
A Comparison Of Deep Learning Algorithms On Image Data For Detecting Floodwater On Roadways, Sarp Salih, Kuzlu Murat, Zhao Yanxiao, Cetin Mecit
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 …