Engineering Commons^™

Network Intrusion Detection System Using Deep Learning, Lirim Ashiku, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The widespread use of interconnectivity and interoperability of computing systems have become an indispensable necessity to enhance our daily activities. Simultaneously, it opens a path to exploitable vulnerabilities that go well beyond human control capability. The vulnerabilities deem cyber-security mechanisms essential to assume communication exchange. Secure communication requires security measures to combat the threats and needs advancements to security measures that counter evolving security threats. This paper proposes the use of deep learning architectures to develop an adaptive and resilient network intrusion detection system (IDS) to detect and classify network attacks. The emphasis is how deep learning or deep neural …

Sensor Data Based Adaptive Models For Assembly Worker Training In Cyber Manufacturing, Md. Al-Amin

Doctoral Dissertations

“Production innovations are occurring faster than ever leading conventional production systems towards cyber manufacturing. Manufacturing workers thus need to frequently learn new methods and skills. In fast-changing, largely uncertain production systems, manufacturers with the ability to comprehend workers’ behavior and assess their operational performance in near real-time will achieve better performance than peers. Recognizing worker actions in near real-time while performing the assembly can serve this purpose. However, reliably recognizing the assembly actions performed by the workers is challenging, because the actions for assembly are complex and workers are not only heterogeneous but sensitive to the variation of the work …

Computational Intelligent Impact Force Modeling And Monitoring In Hislo Conditions For Maximizing Surface Mining Efficiency, Safety, And Health, Danish Ali

Doctoral Dissertations

"Shovel-truck systems are the most widely employed excavation and material handling systems for surface mining operations. During this process, a high-impact shovel loading operation (HISLO) produces large forces that cause extreme whole body vibrations (WBV) that can severely affect the safety and health of haul truck operators. Previously developed solutions have failed to produce satisfactory results as the vibrations at the truck operator seat still exceed the “Extremely Uncomfortable Limits”. This study was a novel effort in developing deep learning-based solution to the HISLO problem.

This research study developed a rigorous mathematical model and a 3D virtual simulation model to …

Variational Inference For Morphological Modification To 3d Geometry : An Application To The Support Generation For Metal Additive Manufacturing, Mugdha Swanand Joshi

Masters Theses

"A key issue in metal additive manufacturing (AM) processes is the optimization of support geometry. Correct selection of support strategy can reduce build time, improve surface finish, reduce support removal time, and maximize build success. Strategies used to design support structure are time consuming and need skilled personnel. In this research we have deployed a deep generative model capable of making morphological modifications to the part. However, it is not similar to topology optimization where the aim is to reduce or eliminate support structure. The proposed model can make necessary changes to the part in order to transform it into …