Engineering Commons^™

Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is the most prevalent and crucial cancer type that should be diagnosed early to reduce mortality. Therefore, mammography is essential for early diagnosis owing to high-resolution imaging and appropriate visualization. However, the major problem of mammography screening is the high false positive recall rate for breast cancer diagnosis. High false positive recall rates psychologically affect patients, leading to anxiety, depression, and stress. Moreover, false positive recalls increase costs and create an unnecessary expert workload. Thus, this study proposes a deep learning based breast cancer diagnosis model to reduce false positive and false negative rates. The proposed model has …

Structural Fiber Mesh Reinforcement Of A Polymeric Heart Valve: Improving Valve Durability And Leaflet Closure Effectiveness, Peter J. Choi, Hugo Zazueta, John A. Acevedo, Philip Park

Civil Engineering Faculty Publications

Objective: Bioprosthetic valves using either porcine or bovine pericardium have been widely used for transcatheter heart valve replacements. However, producing bioprosthetic valves is not a sustainable solution. Acquiring animal tissue is often not readily available and costly and requires time-consuming modifications. Moreover, its primary tissue failure requires reoperation after roughly 15 years. The suggested replacement of porcine and bovine leaflets with biocompatible polymers appears to be an attractive alternative to bioprosthetic valves. In this study, engineered fiber-reinforced polymers were developed, which are less degenerative and offer greater hemocompatibility in relation to mechanical valves.
Methods: Polydimethylsiloxane (PDMS) polymer reduces calcification significantly …

05.20.2024 Orsp Connect, Liz Williamson

ORED Newsletter

NIH RPPR Update (Research Performance Progress Report)

Ri2ap: Robust And Interpretable 2d Anomaly Prediction In Assembly Pipelines, Chathurangi Shyalika, Kaushik Roy, Renjith Prasad, Fadi El Kalach, Yuxin Zi, Priya Mittal, Vignesh Narayanan, Ramy Harik, Amit Sheth

Publications

Predicting anomalies in manufacturing assembly lines is crucial for reducing time and labor costs and improving processes. For instance, in rocket assembly, premature part failures can lead to significant financial losses and labor inefficiencies. With the abundance of sensor data in the Industry 4.0 era, machine learning (ML) offers potential for early anomaly detection. However, current ML methods for anomaly prediction have limitations, with F1 measure scores of only 50% and 66% for prediction and detection, respectively. This is due to challenges like the rarity of anomalous events, scarcity of high-fidelity simulation data (actual data are expensive), and the complex …

Comparative Analysis Of Water-Induced Response In 3d-Printed Scf/Abs Composites Under Controlled Diffusion, Samiul Alam, Md Tareq Hassan, Joshua Merrell, Juhyeong Lee

Mechanical and Aerospace Engineering Faculty Publications

Additive manufacturing (AM) or 3D printing of fiber-reinforced composites (FRCs) has garnered significant interests for its versatility in creating intricate parts and rapid prototyping due to cost-effectiveness. Although short fiber-reinforced thermoplastic composites are challenging to manufacture, their mechanical properties are enhanced. However, void formation during printing is a key issue, impacting mechanical properties and facilitating water ingress, affecting long-term durability. This work studies water diffusion characteristics and the associated hydro-aging of 3Dprinted short carbon fiber (SCF)/acrylonitrile butadiene styrene (ABS) composites with controlled water diffusion. Effects of material type (ABS and SCF/ABS), 3D printing path (horizontal and vertical filament orientation), and …

Signer-Independent Sign Language Recognition With Feature Disentanglement, İnci̇ Meli̇ha Baytaş, İpek Erdoğan

Turkish Journal of Electrical Engineering and Computer Sciences

Learning a robust and invariant representation of various unwanted factors in sign language recognition (SLR) applications is essential. One of the factors that might degrade the sign recognition performance is the lack of signer diversity in the training datasets, causing a dependence on the singer’s identity during representation learning. Consequently, capturing signer-specific features hinders the generalizability of SLR systems. This study proposes a feature disentanglement framework comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network based on adversarial training to learn a signer-independent sign language representation that might enhance the recognition of signs. We aim to …

Estimation Of Useful-Stage Energy Returns On Investment For Fossil Fuels And Implications For Renewable Energy Systems, Emmanuel Aramendia, Paul E. Brockway, Peter G. Taylor, Jonathan B. Norman, Matthew K. Heun, Zeke Marshal;

University Faculty Publications and Creative Works

The net energy implications of the energy transition have so far been analysed at best at the final energy stage. Here we argue that expanding the analysis to the useful stage is crucial. We estimate fossil fuelsʼ useful-stage energy returns on investment (EROIs) over the period 1971–2020, globally and nationally, and disaggregate EROIs by end use. We find that fossil fuelsʼ useful-stage EROIs (~3.5:1) are considerably lower than at the final stage (~8.5:1), due to low final-to-useful efficiencies. Further, we estimate the final-stage EROI for which electricity-yielding renewable energy would deliver the same net useful energy as fossil fuels (EROI …

Nanozyme: Combining Power Of Natural Enzymes And Artificial Catalysis, Peng Du, Lizeng Gao, Jian Jiao, Kelong Fan, Xiyun Yan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Nanozymes represent a novel class of artificial enzymes and biocatalysts, possessing both the physical and chemical properties of nanomaterials along with unique enzyme-like catalytic activities, which breaks the boundary between inorganic materials and organic life. Unlike natural enzymes, traditional enzyme mimics and chemical catalysts, nanozymes exhibit catalytic activity that can be regulated by their nanoscale physical and chemical properties. They are characterized by good stability, high- and lowtemperature resistance, acid and alkali resistance, adjustable activity, and multifunctionality. As a result, nanozymes have garnered widespread attention in the fields of biomedicine, environment treatment, green agriculture, new energy resources, and have begun …

New Frontier In Race For Deep Space Exploration: Lunar Water Resources, Yong Wei, Honglei Lin, Fei He, Hui Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep space exploration has become the commanding heights of science and technology competition. Since the beginning of the 21st century, China has successfully completed the lunar exploration missions of “orbiting, landing, and returning” in just twenty years, and upgraded to a new roadmap of “survey, construction, and utilization”. Meanwhile, lunar exploration worldwide has shown a trend towards normalization and commercialization. The research on lunar water resources has sparked widespread interest and intense competition among countries and space agencies, marking a new focus in human’s deep space exploration. The exploration of lunar water can help reveal crucial processes in the formation …

Winning Battle For Key And Core Technologies In Emerging Fields—Inspiration Based On 863 Program Related Projects, Guangzu Bai, Li Li, Hongfei Meng, Qiang Wang, Xiaoyang Cao, Anrong Liu, Bo Cheng, Mimi Zhan, Jing Li, Leiei Cui, Xiangwan Du

Bulletin of Chinese Academy of Sciences (Chinese Version)

Emerging technology fields have become the main battleground for strategic competition among major powers today, with key and core technologies serving as crucial approach in shaping a nation’s international competitive advantage. This study, from the perspective of national strategy, profoundly understands the significant importance of winning the key and core technology battle in emerging fields. Based on this understanding, it starts with a comparison between the implementation background of the 863 Program and the current reality. It systematically summarizes valuable experiences from projects aimed at advancing key and core technologies in emerging fields, and puts forward reflections and suggestions for …

Flexible Biosensors For Food Pathogen Detection, Sonatan Biswas, Md Shariful Islam, Fei Jia, Yunteng Cao, Yanbin Li, Changyong Cao

Biological and Agricultural Engineering Faculty Publications and Presentations

Food contamination poses a significant threat to public health, the economy, and human health worldwide, occurring at any stage of the food supply chain, from farm to fork. Efficient and effective real-time monitoring methods for the early identification and rapid detection of pathogen contamination are critical to preventing possible food safety issues. In the past decade, flexible electrochemical biosensors have rapidly expanded in the detection of foodborne pathogens, owing to their ability to function well at biological interfaces that may be soft, intrinsically curvy, irregular, or deformable. The most important features of flexible sensors are their flexibility, multifunctionality, low cost, …

Adsorption-Type Aluminium-Based Direct Lithium Extraction: The Effect Of Heat, Salinity And Lithium Content, Yasaman Boroumand, Amir Razmjou

Research outputs 2022 to 2026

Conventional lithium production through solar evaporation is considered a time-consuming procedure, taking a substantial 12 to 18 months with significant environmental impacts such as aquifer depletion and damaging the basin's complex hydrological system. Direct Lithium Extraction (DLE) has emerged as a promising alternative for lithium extraction from brines, offering reduced environmental impact. Although adsorption-type DLE with aluminium-based adsorbents is the sole commercial technology of DLE, a debate persists concerning its Technology Readiness Level (TRL), which challenges the prevailing notion that adsorption-type DLE undeniably reaches a TRL of 9. Within this narrative, we propose that adsorption is capable of attaining its …

An Integrated Resource Planning Proposal For Tucson Electric Power, Valeria Bernal

Master's Projects and Capstones

An integrated resource plan (IRP) is crucial for utilities to determine the most cost-efficient energy resources while considering system reliability, environmental impact, and regulatory requirements. VitalsparK developed an IRP for Tucson Electric Power (TEP) to transition its current 70% thermal and 30% renewable energy portfolio, emitting 740 grams of CO2 per kWh, toward carbon neutrality by 2050. The proposed plan involves retiring existing infrastructure, adding 8 GW of renewable and storage capacity, and incorporating 2.5 GW of net-zero natural gas power plants. VitalsparK presented two scenarios: the Reference (REF) Case, which focuses on the least-cost portfolio to meet demand through …

Extreme Image Transformations Improve Latent Representations In Machines, Girik Malik, Ennio Mingolla

MODVIS Workshop

Shuffling pixels in an image helps machines to learn a more robust object representation. To probe the strategies used by humans and machines for object recognition, we introduce Extreme Image Transformations (EITs). Machines rely heavily on exploiting low-level features like color and texture, so their performance degrades on out-of-distribution and adversarial inputs. Humans depend on high-level features like shapes and contours, making them relatively robust to image distortions. EITs systematically shuffle the pixels in an image, parameterized by the size of grids, probability of shuffle and binary block movement, distorting the structure of objects at both local and global levels. …

The Academic System Influence On Instructional Change: A Conceptual Systems Dynamics Model Of Faculty Motivation To Adopt Research-Based Instructional Strategies (Rbis), Juan M. Cruz Bohorquez, Stephanie G. Adams, Flor Angela Bravo

Henry M. Rowan College of Engineering Departmental Research

Many universities have implemented initiatives to drive instructional change, yet their success has often been limited due to a lack of recognition of academia as a complex dynamic system. This paper explores how the interconnected and dynamic nature of academic systems influences faculty motivation to adopt instructional innovations, such as project-based learning (PBL) and small group collaborations (SGCs). We present a Conceptual Systems Dynamics Model (CSDM) that illustrates these interconnections, demonstrating how systemic factors create feedback loops that either reinforce or hinder faculty motivation, as well as other related factors. These loops, represented as Causal Loop Diagrams (CLDs), were derived …

Can Smart Supply Chain Bring Agility And Resilience For Enhanced Sustainable Business Performance?, Mahak Sharma, Rose Antony, Ashu Sharma, Tugrul Daim

Engineering and Technology Management Faculty Publications and Presentations

Purpose

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

Design/methodology/approach

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices …

Residential Ders In Service-Oriented Load Participation: Enhancing Grid Flexibility, Zhongkai Zeng

Dissertations and Theses

Amidst concerns about power consumption during peak periods and potential grid instability, the role of Distributed Energy Resource (DER) aggregation comes into consideration. Smart electric water heaters with remote capabilities and energy storage offer load reduction capabilities that can help maintain grid stability and manage residential energy consumption. DERs address challenges posed by stochastic renewable energy generation and fossil fuel power plant emissions, playing a contributing role in load shifting and enhancing grid flexibility by participating in energy management programs.

However, high unenrollment rates in demand response programs, notably programs that use direct load control, persist due to customer dissatisfaction. …

Learning Proximal Operators With Gaussian Process And Adaptive Quantization In Distributed Optimization, Aldo Duarte Vera Tudela

LSU Doctoral Dissertations

In networks consisting of agents communicating with a central coordinator and working together to solve a global optimization problem in a distributed manner, the agents are often required to solve private proximal minimization subproblems. Such a setting often requires a further decomposition method to solve the global distributed problem, resulting in extensive communication overhead. In networks where communication is expensive, it is crucial to reduce the communication overhead of the distributed optimization scheme. Integrating Gaussian processes (GP) as a learning component to the Alternating Direction Method of Multipliers (ADMM) has proven effective in learning each agent's local proximal operator to …

Facilitation In Pattern Motion Perception Of Self-Operated Stimuli Explained By Adaptive Contrast Normalization, Fulvio Missoni, Francesca Peveri, Andrea Canessa, Giulia Sedda, Vittorio Sanguineti, Silvio P. Sabatini

MODVIS Workshop

Movement can affect the way we make sense of complex visual information. To investigate this issue, we designed an experiment to assess changes of plaid motion perception threshold after a period of sensorimotor contingency experience. We found that movement training facilitates combination of elementary motion cues into a global motion percept. No changes in perceptual thresholds are observed in a passive visual condition. A Bayesian model suggested a reduction, after training, of the cross-talk between two gratings with unbalanced contrasts in corresponding sensory channels. To test plausible neural mechanisms for active reduction of cross-talk in cortical representation of complex visual …

Redeveloping System Noise Temperature Test Capabilities For Dss-17 Using The Moon As A Noise Source, Emily R. Walter

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science and Engineering at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Emily R. Walter on May 16, 2024.

Design Of An Integrated System For The Protection Of Patient Health Information In Medical Images, Manikandan V

Theses and Dissertations

Electronic clinical data such as Patient Health Information (PHI) is stored by adapting the Digital Imaging and Communications in Medicine (DICOM) standard to build an integrated healthcare system where medical images from various sources can be interlinked. The healthcare industry poses a threat from hackers, and the information fetched by hackers provides more money than the other information stolen. This thesis deals with designing and analysing encryption algorithms, key generation mechanisms, and information-hiding schemes for protecting PHI.

Sensitive multimedia information of all forms is encrypted, with a key, before storage and transmission to protect it from illegal use and manipulation …

Investigating Small Drinking Water System Technical Capacity To Treat For Pfas, Chloe J. Yoder, Kaycie Lane

Department of Civil and Environmental Engineering: Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) presents technical challenges in small systems where advanced drinking water treatment implementation is difficult. Publicly available data were used to examine technical treatment capacity for PFAS in the US, using Nebraska as a pilot. Of 1312 PWSs in Nebraska, 441 have technologies capable of removing PFAS from drinking water. Reverse osmosis was the most common treatment technology in Nebraska with 277 total systems using this technology with, 194 PWSs with RO serving populations of <= 100 people. Fifty-two PWSs had granular activated carbon, 47 had ion exchange and 62 had ultraviolet, with UV being primarily used for disinfection. We found PWSs had different technology deployment methods, several systems had “significant deficiencies” reported in management and operation evaluations, and age and previous water quality violations were not correlated to treatment evaluations. The developed methodology models utilizing publicly available data for contaminants across the US.

Band Gap Tuning Of Perovskite Solar Cells For Enhancing The Efficiency And Stability: Issues And Prospects, Md Helal Miah, Mayeen Uddin Khandaker, Md Bulu Rahman, Mohammad Nur-E-Alam, Mohammad Aminul Islam

Research outputs 2022 to 2026

The intriguing optoelectronic properties, diverse applications, and facile fabrication techniques of perovskite materials have garnered substantial research interest worldwide. Their outstanding performance in solar cell applications and excellent efficiency at the lab scale have already been proven. However, owing to their low stability, the widespread manufacturing of perovskite solar cells (PSCs) for commercialization is still far off. Several instability factors of PSCs, including the intrinsic and extrinsic instability of perovskite materials, have already been identified, and a variety of approaches have been adopted to improve the material quality, stability, and efficiency of PSCs. In this review, we have comprehensively presented …

Barriers To Mental Health Treatment Among U.S. Army Aviation Personnel, Aric James Raus

Doctoral Dissertations and Projects

Safe and effective Army aviation operations require a clear focus from all involved. Yet, after more than two decades of U.S. combat aviation operations, little is known about the barriers experienced by aviators when considering mental health evaluation and treatment. An extensive literature review found no published studies examining mental health treatment hesitance among Army Aviation personnel or the perceived acceptability of self-help treatment options. This study identifies the relationships between age, gender, and aviation career specialty on the self-disclosed instrumental, attitudinal, and stigma-based barriers to care among U.S. Army aviation personnel. Additionally, the research determines relationships between the population’s …

Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar

Biology and Medicine Through Mathematics Conference

No abstract provided.

Enhancing Electrical Network Vulnerability Assessment With Machine Learning And Deep Learning Techniques, M Mishkatur Rahman, Ayman Sajjad Akash, Harun Pirim, Chau Le, Trung Le, Om Prakash Yadav

Northeast Journal of Complex Systems (NEJCS)

This research utilizes advanced machine learning techniques to evaluate node vul-
nerability in power grid networks. Utilizing the SciGRID and GridKit datasets, con-
sisting of 479, 16,167 nodes and 765, 20,539 edges respectively, the study employs
K-nearest neighbor and median imputation methods to address missing data. Cen-
trality metrics are integrated into a single comprehensive score for assessing node
criticality, categorizing nodes into four centrality levels informative of vulnerability.
This categorization informs the use of traditional machine learning (including XG-
Boost, SVM, Multilayer Perceptron) and Graph Neural Networks in the analysis.
The study not only benchmarks the capabilities of these …

Explaining The Staircase Gelb Illusion, Simultaneous Contrast, And Perceptual Fading Of Stabilized Images With A Neural Model Driven By Fixational Eye Movements, Michael E. Rudd

MODVIS Workshop

A neural model of lightness computation driven by fixational eye movements is described and used to simulate various lightness phenomenon, including the Staircase Gelb illusion and its variants, simultaneous contrast, the Chevreul illusion, and perceptual fading of stabilized images. The model provides a precise account of the lightness matches from several experiments, with an overall error of only 1.5%. In the model, spatial maps of transient ON and OFF cell activations—produced as the eyes traverse the visual scene—are sorted by eye movement direction in visual cortex. At a subsequent processing stage, the activations within these maps are summed across space …

Effects Of A Wi-Fi Link On The Performance Of A Path Following Autonomous Ground Vehicle, Anthony Iwejuo, Austin Cagle, Billy Kihei, Ph.D.

Symposium of Student Scholars

As vehicles become more automated and connected, the future of safe and efficient travel will be dependent on efficient wireless networks. Artificial intelligence (AI) demands high power resources and computing resources that can be resource-intensive for mobile robotic systems. A new paradigm involving the remote computing of A.I. can enable robotics that are built lighter and more power efficient. In this study, we compare a locally run artificial intelligence algorithm for autonomous ground vehicle navigation against remote computation through various wireless links to highlight the need for low-latency access to remote computing resources over Wi-Fi network calls. Our findings show …

A Robust Decision-Making Model For Medical Supplies Via Selecting Appropriate Unmanned Aerial Vehicle, Amira Salam, Mai Mohamed, Rui Yong, Jun Ye

Neutrosophic Systems with Applications

Recently, Unmanned Aerial Vehicles (UAVs) have been used in many fields, including the field of health care, especially in delivering the necessary medical equipment and supplies, due to the many advantages they have compared to other traditional methods and the presence of different types of UAVs, to improve healthcare and provide it with the medical supplies and equipment necessary to save the lives of patients. Choosing the appropriate UAV for a specific situation represents a problem facing decision-makers, which is considered a multi-criteria decision-making problem. Since the decision-making process is cumbersome and complex, and deals with uncertainty and ambiguity. In …

An Innovative Approach On Yao’S Three-Way Decision Model Using Intuitionistic Fuzzy Sets For Medical Diagnosis, Wajid Ali, Tanzeela Shaheen, Iftikhar Ul Haq, Florentin Smarandache, Hamza Ghazanfar Toor, Faiza Asif

Neutrosophic Systems with Applications

In the realm of medical diagnosis, intuitionistic fuzzy data serves as a valuable tool for representing information that is uncertain and imprecise. Nevertheless, decision-making based on this kind of knowledge can be quite challenging due to the inherent vagueness of the data. To address this issue, we employ power aggregation operators, which prove effective in combining several sources of data, such as expert thoughts and patient information. This allows for a more correct diagnosis; a particularly crucial aspect of medical practice where precise and timely diagnoses can significantly impact medication policy and patient results. In our research, we introduce a …