Engineering Commons^™

Towards Multi-Modal Interpretable Video Understanding, Quang Sang Truong

Graduate Theses and Dissertations

This thesis introduces an innovative approach to video comprehension, which simulates human perceptual mechanisms and establishes a comprehensible and coherent narrative representation of video content. At the core of this approach lies the creation of a Visual-Linguistic (VL) feature for an interpretable video portrayal and an adaptive attention mechanism (AAM) aimed at concentrating solely on principal actors or pertinent objects while modeling their interconnections. Taking cues from the way humans disassemble scenes into visual and non-visual constituents, the proposed VL feature characterizes a scene via three distinct modalities: (i) a global visual environment, providing a broad contextual comprehension of the …

Maximising Captured Power And Battery Management For Heaving Wave Energy Converters, Omsalama Mubarak Mohamed

Dissertations

Sea waves are considered the most potent energy carriers among all sources of renewable energy. This research work is concerned with developingtechnologies to enhance performance and improve power capturing and conversion capabilities of a single heaving wave energy converter (WEC) actuated by a PMLG (Permanent Magnet Linear Generator). The objective of this dissertation is achieved by three techniques. The first one considers maximizing conversion between the mechanical and electrical powers. It is implemented by designing intrinsic resistance using a rapid procedure involving the mechanical and electrical models of the converter and considering its operating constraints. A robust PID (proportional – …

A Framework Of Flow Models For The Development And Testing Of Cardiovascular Devices, Megan Laughlin

Graduate Theses and Dissertations

Cardiovascular disease (CVD) is the leading cause of death worldwide and its treatment continues to improve due to the advancement of innovative cardiovascular medical devices. In vitro and in silico models serve to replicate the in vivo environment for the development and testing of these devices prior to using animals for testing, and eventually humans in clinical trials. However, limitations related to these models exist in multiple areas including general, cardiac, and venous applications. Specifically, current gaps have been identified with customizable, tissue-mimicking phantoms (general), 2D Blood Speckle Imaging (BSI) (cardiac) and a bioprosthetic venous valve (venous). This dissertation focuses …

Evaluating Differences In Optical Properties Of Indolent And Aggressive Murine Breast Tumors Using Quantitative Diffuse Reflectance Spectroscopy, Joel Rodriguez Troncoso, Umme Marium Mim, Jesse D. Ivers, Santosh K. Paidi, Mason G. Harper, Khue G. Nguyen, Sruthi Ravindranathan, Lisa Rebello, David E. Lee, David A. Zaharoff, Ishan Barman, Narasimhan Rajaram

Biomedical Engineering Faculty Publications and Presentations

We used diffuse reflectance spectroscopy to quantify tissue absorption and scattering-based parameters in similarly sized tumors derived from a panel of four isogenic murine breast cancer cell lines (4T1, 4T07, 168FARN, 67NR) that are each capable of accomplishing different steps of the invasion-metastasis cascade. We found lower tissue scattering, increased hemoglobin concentration, and lower vascular oxygenation in indolent 67NR tumors incapable of metastasis compared with aggressive 4T1 tumors capable of metastasis. Supervised learning statistical approaches were able to accurately differentiate between tumor groups and classify tumors according to their ability to accomplish each step of the invasion-metastasis cascade. We investigated …

Thermal Atomization On Superhydrophobic Surfaces Of Varying Temperature Jump Length, Eric D. Lee, Daniel Maynes, Julie Crockett, Brian D. Iverson

Faculty Publications

This paper presents an experimental study of drop impingement and thermal atomization on hydrophobic and superhydrophobic (SH) surfaces. Superhydrophobic surfaces having both microscale and nanoscale geometry are considered. Microscale SH surfaces are coated with a hydrophobic coating and exhibit micropillars and cavities which are classified using the surface solid fraction and center to center pitch. The solid fraction and pitch values explored in this study range from 0.05-1.0 and 8-60 μm respectively. Nanoscale textured surfaces are created by applying a blanket layer of carbon nanotubes. Both types of surfaces are further classified by a temperature jump length (λ …

An Improved Genetic Algorithm Based Fractional Open Circuit Voltage Mppt For Solar Pv Systems, Aakash Hassan, Octavian Bass, Mohammad A. S. Masoum

Research outputs 2022 to 2026

To extract the maximum power from solar PV, maximum power point tracking (MPPT) controllers are needed to operate the PV arrays at their maximum power point under varying environmental conditions. Fractional Open Circuit Voltage (FOCV) is a simple, cost-effective, and easy to implement MPPT technique. However, it suffers from the discontinuous power supply and low tracking efficiency. To overcome these drawbacks, a new hybrid MPPT technique based on the Genetic Algorithm (GA) and FOCV is proposed. The proposed technique is based on a single decision variable, reducing the complexity and convergence time of the algorithm. MATLAB/Simulink is used to test …

On The Effect Of Emotion Identification From Limited Translated Text Samples Using Computational Intelligence, Madiha Tahir, Zahid Halim, Muhmmad Waqas, Shanshan Tu

Research outputs 2022 to 2026

Emotion identification from text data has recently gained focus of the research community. This has multiple utilities in an assortment of domains. Many times, the original text is written in a different language and the end-user translates it to her native language using online utilities. Therefore, this paper presents a framework to detect emotions on translated text data in four different languages. The source language is English, whereas the four target languages include Chinese, French, German, and Spanish. Computational intelligence (CI) techniques are applied to extract features, dimensionality reduction, and classification of data into five basic classes of emotions. Results …

Residual Trapping Of Co2, N2, And A Co2-N2 Mixture In Indiana Limestone Using Robust Nmr Coreflooding: Implications For Co2 Geological Storage, Amer Alanazi, Auby Baban, Muhammad Ali, Alireza Keshavarz, Stefan Iglauer, Hussein Hoteit

Research outputs 2022 to 2026

Carbon capture and sequestration (CCS) in geological formations is a prominent solution for reducing anthropogenic carbon emissions and mitigating climate change. The capillary trapping of CO2 is a primary trapping mechanism governed by the pressure difference between the wetting and nonwetting phases in a porous rock, making the latter a key input parameter for dynamic simulation models. During the CCS operational process, however, the CO2 is prone to contamination by impurities from various sources such as surfaces (e.g., pipelines and tanks) and the subsurface (e.g., existing natural gas). Such contamination can strongly influence the overall CO2 wettability, storage capacity, and …

Fatigue Behaviour Of Load-Bearing Polymeric Bone Scaffolds: A Review, Hamed Bakhtiari, Alireza Nouri, Mehrdad Khakbiz, Majid Tolouei-Rad

Research outputs 2022 to 2026

Bone scaffolds play a crucial role in bone tissue engineering by providing mechanical support for the growth of new tissue while enduring static and fatigue loads. Although polymers possess favourable characteristics such as adjustable degradation rate, tissue-compatible stiffness, ease of fabrication, and low toxicity, their relatively low mechanical strength has limited their use in load-bearing applications. While numerous studies have focused on assessing the static strength of polymeric scaffolds, little research has been conducted on their fatigue properties. The current review presents a comprehensive study on the fatigue behaviour of polymeric bone scaffolds. The fatigue failure in polymeric scaffolds is …

Numerical Investigation Of Lead Free Cs2tibr6 Based Perovskite Solar Cell With Optimal Selection Of Electron And Hole Transport Layer Through Scaps-1d Simulation, Hironmoy Karmaker, Ayesha Siddique, Barun K. Das

Research outputs 2022 to 2026

Halide-based perovskite has several advantages, including high efficiency, ease of manufacture, and low cost. In general, hazardous lead (Pb) is used in perovskite solar cells as an absorber layer, while polymer, which is unstable in nature used as the electron/hole transport layer. Despite its appealing characteristics, the device uses of lead and degradable components must be addressed. Lead-free titanium-based inorganic perovskite solar cells (PSCs) have drawn strong scientific interest in recent years in order to reduce the possibly detrimental effects of lead on the environment. Titanium is non-toxic, robust, inexpensive, and widely available when compared to other elements. The performance …

Thermo-Hydraulic Performance Evaluation Of A Naca 63-015 Heat Exchanger With Shark Denticles As Surface Textures, Aakash S. Hurry, Kevin Hayward, Ferdinando Guzzomi, Kanishk Rauthan, Ana Vafadar

Research outputs 2022 to 2026

In this study, the effect of using bio-inspired surface texturing as a technique to further enhance the efficiency of a single Plate Fin Heat Exchanger (PFHX) was investigated experimentally. By using biomimicry across disciplines, the denticle, which is a body adaptation from shark skin for enhanced hydrodynamics, was identified as a surface texture to be used on the fin of a PFHX. A smooth NACA 63-015 PFHX (HX0) was used as baseline for thermo-hydraulic performance comparisons. Initially, three PFHXs (HX1, HX2 and HX3), consisting of arrays of denticles upscaled to different scale factors, were designed and printed in ABS plastic …

Time Reduction For Slm Ofdm Papr Based On Adaptive Genetic Algorithm In 5g Iot Networks, Esam A. A. Hagras, Sameh F. Desouky, Saad Aldosary, Haitham Khaled, Tarek M. Hassan

Research outputs 2022 to 2026

In this paper, a new peak average power and time reduction (PAPTR) based on the adaptive genetic algorithm (AGA) strategy is used in order to improve both the time reduction and PAPR value reduction for the SLM OFDM and the conventional genetic algorithm (GA) SLM-OFDM. The simulation results demonstrate that the recommended AGA technique reduces PAPR by about 3.87 dB in comparison to SLM-OFDM. Comparing the suggested AGA SLM-OFDM to the traditional GA SLM-OFDM using the same settings, a significant learning time reduction of roughly 95.56% is achieved. The PAPR of the proposed AGA SLM-OFDM is enhanced by around 3.87 …

Wastewater Treatment Plants: The Missing Link In Global One-Health Surveillance And Management Of Antibiotic Resistance, Abdolmajid Gholizadeh, Mehdi Khiadani, Maryam Foroughi, Hadi Alizade Siuki, Hadi Mehrfar

Research outputs 2022 to 2026

Introduction: As a global public health crisis, antibiotic resistance (AR) should be monitored and managed under the One-Health concept according to the World Health Organization (WHO), considering the interconnection between humans, animals, and the environment. But this approach often remains focused on human health and rarely on the environment and its compartments, especially wastewater as the main AR receptor. Wastewater treatment plants (WWTPs) not only are not designed for reliving AR but also provide appropriate conditions for enhancing AR through different mechanisms. Methods: By reviewing the research-based statistics on the inclusion of WWTPs in the One-Health/AR program crisis, this paper …

A New Approach To Predicting Vertical Permeability For Carbonate Rocks In The Southern Mesopotamian Basin, Emad A. Al-Khdheeawi, Raed H. Allawi, Wisam I. Al-Rubaye, Stefan Iglauer

Research outputs 2022 to 2026

Reservoir performance depends on many factors, and the most important one is permeability anisotropy. In addition, with high heterogeneity, it is essential to find unique relationships to predict permeability. Therefore, this study aims to predict vertical permeability based on horizontal permeability and porosity and to find new equations for carbonate reservoirs. This work relied on the 398 measured points of cores data collected from several wells in carbonate reservoirs. A new correlation for predicting vertical permeability for the whole data (369 samples) as a function of horizontal permeability and porosity has been developed. The results indicate that this new correlation …

Capillary-Sealing Efficiency Of Mica-Proxy Caprock For Co2/H2 Geologic Storage In The Presence Of Organic Acids And Nanofluids, Amer Alanazi, Muhammad Ali, Mahmoud Mowafi, Saleh Bawazeer, Ziyad K K. Kaidar, Hussein Hoteit

Research outputs 2022 to 2026

Toward a diversified low-carbon future, the geological storage of carbon dioxide (CO2) and hydrogen (H2) is regarded as a key enabler for an industrial-scale implementation. However, many geological formations, such as depleted oil and gas reservoirs, can contain inherent traces of organic molecules that dramatically affect their storage capacities and caprock sealing efficiency. Hence, using the right analysis to accurately determine the caprock sealing efficiency and storage capacity in the presence of organics is crucial for a secure and safe storage process. This study analyzed the sealing potential of a proxy caprock (mica) by calculating the capillary entry pressure and …

Small Scale Desalination Technologies: A Comprehensive Review, Hamed Kariman, Abdellah Shafieian, Mehdi Khiadani

Research outputs 2022 to 2026

In recent decades, problems related to fresh water has become a very important issue for humans. Small-scale desalination (SSD) systems, besides large-scale desalination (LSD) systems, fulfil an important role in meeting freshwater demand by eliminating the cost of transmission and have the advantage of treating water on-site. In this study, for the first time, a comprehensive review of previous studies has been carried out on SSD systems (less than 25 m3/d water production). These systems are powered using renewable, non-renewable or hybrid sources of energy, incorporating different treatment technologies such as: reverse osmosis (RO); electro dialysis (ED); capacitive deionization (CDI); …

Metal Organic Frameworks With Carbon Black For The Enhanced Electrochemical Detection Of 2,4,6-Trinitrotoluene, Shaghraf Javaid, Muhammad R. Azhar, Xinyu Li, Juliette I. Phillips, Tanveer Hussain, Hussein Abid, Jun Chen, Xiaobo Ji, Debbie S. Silvester

Research outputs 2022 to 2026

The sensing of explosives such as 2,4,6-trinitrotoluene (TNT) directly at an explosion site requires a fast, simple and sensitive detection method, to which electrochemical techniques are well suited. Herein, we report an electrochemical sensor material for TNT based on an ammonium hydroxide (NH4OH) sensitized zinc-1,4–benzenedicarboxylate Zn(BDC) metal organic framework (MOF) mixed with carbon black on a glassy carbon electrode. In the solvent modulation mechanism, by merely changing the concentration of NH4OH during synthesis, two Zn(BDC) MOFs with novel morphologies were fabricated via a hydrothermal approach. The as-prepared MOFs were characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Fourier …

Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu

Journal of System Simulation

Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …

Knowing Just Enough To Be Dangerous: The Sociological Effects Of Censoring Public Ai, David Hopkins

Cybersecurity Undergraduate Research Showcase

This paper will present the capabilities and security concerns of public AI, also called generative AI, and look at the societal and sociological effects of implementing regulations of this technology.

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Characterizing Intervertebral Disc Strain Under Dynamic Loading Conditions Using Ultrasound Texture Analysis, Radhika Kulkarni

Discovery Undergraduate Interdisciplinary Research Internship

Herniated discs in the spine are a significant patient burden, with potential links to lower back and leg discomfort and a considerable impact on daily life. These discs, located between spinal vertebrae, are comprised of the annulus fibrosus (AF) and the nucleus pulposus (NP). Herniations happen when the NP protrudes through a full-thickness annular tear, possibly compressing spinal nerves. The mechanical factors underlying herniated discs are poorly understood, necessitating research into these mechanisms and accessible diagnostic techniques. Our study employs high-resolution ultrasound and texture correlation to quantify strain patterns in intervertebral discs during dynamic loading.

A motion segment from the …

A Comparative Study Of Yolo Models And A Transformer-Based Yolov5 Model For Mass Detection In Mammograms, Damla Coşkun, Dervi̇ş Karaboğa, Alper Baştürk, Bahri̇ye Akay, Özkan Ufuk Nalbantoğlu, Serap Doğan, İshak Paçal, Meryem Altin Karagöz

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is a prevalent form of cancer across the globe, and if it is not diagnosed at an early stage it can be life-threatening. In order to aid in its diagnosis, detection, and classification, computer-aided detection (CAD) systems are employed. You Only Look Once (YOLO)-based CAD algorithms have become very popular owing to their highly accurate results for object detection tasks in recent years. Therefore, the most popular YOLO models are implemented to compare the performance in mass detection with various experiments on the INbreast dataset. In addition, a YOLO model with an integrated Swin Transformer in its backbone …

Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang

Journal of System Simulation

Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …

Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma

Journal of System Simulation

Abstract: In order to solve the intercell scheduling problem of dynamic arrival of machining tasks and realize adaptive scheduling in the complex and changeable environment of the intelligent factory, a scheduling method based on a deep Q network is proposed. A complex network with cells as nodes and workpiece intercell machining path as directed edges is constructed, and the degree value is introduced to define the state space with intercell scheduling characteristics. A compound scheduling rule composed of a workpiece layer, unit layer, and machine layer is designed, and hierarchical optimization makes the scheduling scheme more global. Since double deep …

Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao

Journal of System Simulation

Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …

Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao

Journal of System Simulation

Abstract: Under the background of high-speed maneuvering target interception, an optimal guidance law generation method for head-on interception independent of target acceleration estimation is proposed based on deep reinforcement learning. In addition, its effectiveness is verified through simulation experiments. As the simulation results suggest, the proposed method successfully achieves head-on interception of high-speed maneuvering targets in 3D space and largely reduces the requirement for target estimation with strong uncertainty, and it is more applicable than the optimal control method.

Study On Effect Of 3d Printing Parameters On Surface Roughness And Tensile Strength Using Analysis Of Variance, Faqih Fadillah, Heru Suryanto, Suprayitno Suprayitno

Journal of Mechanical Engineering Science and Technology (JMEST)

Fused deposition modeling of 3D printing is the process of making workpieces or parts by adding filaments to each layer. Some indicators of a high-quality product of 3D printing are the precisions dimensions, the surface roughness, and tensile strength. This research aims to find the parameters most affecting surface roughness and tensile strength. The research design used an experimental method with input parameters: (1) print speed (15-35 mm/s), (2) print temperature (200-210C), (3) layer height (0.1 – 0.3 mm), (4) infill line directions (0-90), and dependent variables were surface roughness and tensile strength. The data distribution used the L9 orthogonal …

Mechanical Characterization Of Naoh-Treated Agel Fiber-Cotton Composites, I Gusti Ngurah Nitya Santhiarsa, I Gusti Bagus Wijaya Kusuma, I Gede Artha Negara

Journal of Mechanical Engineering Science and Technology (JMEST)

Composites comprising two or more distinct materials are fabricated to enhance the mechanical properties of the constituent materials. A common approach for generating composites is vacuum infusion. This technique enables the infusion of two materials utilizing a vacuum. In the field of composite science, textile composites have emerged as an important new development. Agel rope, derived from twisting agel fibers, exhibits inferior bending strength and elongation compared to ropes fabricated from synthetic fibers. Moreover, agel rope is susceptible to bacterial decay. This study aims to characterize the mechanical properties of textile composites comprising woven agel rope subjected to NaOH treatment. …

A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty

Turkish Journal of Electrical Engineering and Computer Sciences

Nephrons are the basic filtering units of the kidneys. Progression of chronic kidney disease (CKD) destroys nephrons permanently. Although there are many computing schemes suggested in recent years to identify CKD stages, no computing method has been suggested for identifying the nephron loss within kidney regions during CKD progression. In this paper, a novel pattern matching-based computation scheme is proposed to detect nephron loss in the kidney regions during CKD progression. We consider image registration (IR) with different transforms and a structural similarity index algorithm (SSIM) to match patterns of ultrasound images of kidney regions to identify the nephron loss. …

Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a design to detect and prevent IP spoofing-based distributed denial of service (DDoS) attacks on software-defined networks (SDNs). DDoS attacks are still one of the significant problems for internet service providers (ISPs) and individual users. These attacks can disrupt customer services by targeting the availability of the system, and in some cases, they can completely shut down the target infrastructure. Protecting the system against DDoS attacks is therefore crucial for ensuring the reliability and availability of internet services. To address this problem, we propose a lightweight source address validation (LSAV) framework that leverages the flexibility …