Digital Commons Network^™

Multi-View Brain Tumor Segmentation (Mvbts): An Ensemble Of Planar And Triplanar Attention Unets, Snehal Rajput, Rupal Kapdi, Mehul Raval, Mohendra Roy

Turkish Journal of Electrical Engineering and Computer Sciences

3D UNet has achieved high brain tumor segmentation performance but requires high computation, large memory, abundant training data, and has limited interpretability. As an alternative, the paper explores using 2D triplanar (2.5D) processing, which allows images to be examined individually along axial, sagittal, and coronal planes or together. The individual plane captures spatial relationships, and combined planes capture contextual (depth) information. The paper proposes and analyzes an ensemble of uniplanar and triplanar UNets combined with channel and spatial attention for brain tumor segmentation. It investigates the significance of each plane and analyzes the impact of uniplanar and triplanar ensembles with …

A Unique Hybrid Domain Hand-Crafted Feature To Classify Colorectal Tissue Histopathological Images Using Multiheaded Cnn, Anurodh Kumar, Amit Vishwakarma, Varun Bajaj

Turkish Journal of Electrical Engineering and Computer Sciences

Early diagnosis of colorectal cancer lengthens human life and is helpful in efforts to cure the illness. Histopathological inspection is a routinely utilized technique to diagnose it. Visual assessment of histopathological images takes more investigation time, and the decision is based on the individual perceptions of clinicians. The existing methods for colorectal cancer classification use only spatial information. However, studies on the spectral domains of information are lacking in the literature. Therefore, the performance of the existing techniques is moderate. To improve the performance of colorectal cancer classification, this work proposes a unique hybrid domain hand-crafted feature formulated using scale-invariant …

Hybrid Machine Learning Model To Predict Chronic Kidney Diseases Using Handcrafted Features For Early Health Rehabilitation, Amjad Rehman, Tanzila Saba, Haider Ali, Narmine Elhakim, Noor Ayesha

Turkish Journal of Electrical Engineering and Computer Sciences

Chronic kidney diseases proliferate due to hypertension, diabetes, anemia, obesity, smoking etc. Patients with such conditions are sometimes unaware of first symptoms, complicating disease diagnosis. This paper presents chronic kidney disease (CKD) prediction model to classify CKD patients from NCKD (Non-CKD). The proposed study has two main stages. First, we found the odds ratio through logistic regression and comparison test to identify early risk factors from kidneys? MRI and differentiate CKD from NCKD subjects. In stage 2, LR, LDA, MLP classifiers were applied to predict CKD and NCKD by extracting features from MRI. The odds ratio of blood glucose random …

Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson

Turkish Journal of Electrical Engineering and Computer Sciences

Millions of people throughout the world suffer from the complicated and crippling condition of chronic pain. It can be brought on by several underlying disorders or injuries and is defined by chronic pain that lasts for a period exceeding three months. To better understand the brain processes behind pain and create prediction models for pain-related outcomes, machine learning is a potent technology that may be applied in Functional magnetic resonance imaging (fMRI) chronic pain research. Data (fMRI and T1-weighted images) from 76 participants has been included (30 chronic pain and 46 healthy controls). The raw data were preprocessed using fMRIprep …

Deep Feature Extraction, Dimensionality Reduction, And Classification Of Medical Images Using Combined Deep Learning Architectures, Autoencoder, And Multiple Machine Learning Models, Ahmet Hi̇dayet Ki̇raz, Fatime Oumar Djibrillah, Mehmet Emi̇n Yüksel

Turkish Journal of Electrical Engineering and Computer Sciences

Accurate analysis and classification of medical images are essential factors in clinical decision-making and patient care. A novel comparative approach for medical image classification is proposed in this study. This new approach involves several steps: deep feature extraction, which extracts the informative features from medical images; concatenation, which concatenates the extracted deep features to form a robust feature vector; dimensionality reduction with autoencoder, which reduces the dimensionality of the feature vector by transforming it into a different feature space with a lower dimension; and finally, these features obtained from all these steps were fed into multiple machine learning classifiers (SVM, …

Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima

Turkish Journal of Electrical Engineering and Computer Sciences

The conventional approach to creating 3D surfaces from 2D medical images is the marching cube algorithm, but it often results in rough surfaces. On the other hand, B-spline curves and nonuniform rational B-splines (NURBSs) offer a smoother alternative for 3D surface reconstruction. However, NURBSs use control points (CTPs) to define the object shape and corners play an important role in defining the boundary shape as well. Thus, in order to fill the research gap in applying corner detection (CD) methods to generate the most favorable CTPs, in this paper corner points are identified to predict organ shape. However, CTPs must …

Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur

Turkish Journal of Electrical Engineering and Computer Sciences

Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray (CXR) images, which have a vital role in the detection of various pulmonary diseases. Precise identification of lung regions is the basic prerequisite for disease diagnosis and treatment planning. However, achieving precise lung segmentation poses significant challenges due to factors such as variations in anatomical shape and size, the presence of strong edges at the rib cage and clavicle, and overlapping anatomical structures resulting from diverse diseases. Although commonly considered as the de-facto standard in medical image segmentation, the convolutional UNet architecture and its variants …

Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi

Turkish Journal of Electrical Engineering and Computer Sciences

Explainable AI (XAI) improved by a deep neural network (DNN) of a residual neural network (ResNet) and long short-term memory networks (LSTMs), termed XAIRL, is proposed for segmenting foot infrared imaging datasets. First, an infrared sensor imaging dataset is acquired by a foot infrared sensor imaging device and preprocessed. The infrared sensor image features are then defined and extracted with XAIRL being applied to segment the dataset. This paper compares and discusses our results with XAIRL. Evaluation indices are applied to perform various measurements for foot infrared image segmentation including accuracy, precision, recall, F1 score, intersection over union (IoU), Dice …

Facial Motion Augmented Identity Verification With Deep Neural Networks, Zheng Sun

Theses and Dissertations

Identity verification is ubiquitous in our daily life. By verifying the user's identity, the authorization process grants the privilege to access resources or facilities or perform certain tasks. The traditional and most prevalent authentication method is the personal identification number (PIN) or password. While these knowledge-based credentials could be lost or stolen, human biometric-based verification technologies have become popular alternatives in recent years. Nowadays, more people are used to unlocking their smartphones using their fingerprint or face instead of the conventional passcode. However, these biometric approaches have their weaknesses. For example, fingerprints could be easily fabricated, and a photo or …

I-Guide Climbers: A Model For Multidisciplinary Academic Labs For Early Career Development, Iman Haqiqi, Wei Hu, Ramya Kumaran, Pin-Ching Li, Nicholas Manning, Alex Michels, Ayman Nassar, Jinwoo Park, Jimeng Shi, Adam Tonks, Zhaonan Wang

I-GUIDE Forum

In this paper, we propose a new form of multidisciplinary academic collaboration that goes beyond the traditional modes of knowledge exchange. We argue that most research collaboration today is based on interactions between closely related disciplines, in which researchers share data, methods, and insights within a common framework or problem. However, such collaboration may not foster the development of the communication and management skills essential to a multi-disciplinary research career. Therefore, we suggest establishing a network of researchers from divergent, yet complementary, disciplines who are interested in improving these skills through regular interactions and feedback. The main goal of this …

Seasonally Optimized Calibrations Improve Low-Cost Sensor Performance: Long-Term Field Evaluation Of Purpleair Sensors In Urban And Rural India, Mark Joseph Campmier, Jonathan D. Gingrich, Saumya Singh, Nisar Baig, Shahzad Gani, Adithi Upadhya, Pratyush Agrawal, Meenakshi Kushwaha, Harsh Raj Mishra, Ajay Pillarisetti, Sreekanth Vakacherla, Ravi Kant Pathak, Joshua S. Apte

Faculty Work Comprehensive List

Lower-cost air pollution sensors can fill critical air quality data gaps in India, which experiences very high fine particulate matter (PM2.5) air pollution but has sparse regulatory air monitoring. Challenges for low-cost PM2.5 sensors in India include high-aerosol mass concentrations and pronounced regional and seasonal gradients in aerosol composition. Here, we report on a detailed long-time performance evaluation of a popular sensor, the Purple Air PA-II, at multiple sites in India. We established three distinct sites in India across land use categories and population density extremes (in urban Delhi and rural Hamirpur in north India and urban Bengaluru in south …

Smart Sounding Table Using Adaptive Neuro-Fuzzy Inference System, Osman Ünal, Nuri Akkaş

Journal of Marine Science and Technology–Taiwan

Marine engineers measure the liquid level (sounding depth) to calculate the volumetric content of a ship's tank. The sounding depth is determined using an ullage pipe located at specific points on the tanks. To estimate the accurate volume of liquid, considering the ship's trim and heel conditions, engineers use a tank table (sounding table) consisting of hundreds of pages. However, this method is time-consuming and lacks intermediate values for sounding depth, trim, and heel. Ship designers recommend to use linear interpolation for intermediate values, yet this process is also time-consuming. This paper proposes the implementation of an Adaptive Neuro-Fuzzy Inference …

Case Study Of Coastal Erosion And Measures At Kezailiao Coast, Taiwan, Tai-Wen Hsu, Yi-Tse Tu, Jen-Yi Chang

Journal of Marine Science and Technology–Taiwan

This paper examines major factors of coastal erosion and measures against beach erosion at Kezailiao Coast, Taiwan. Typical examples of coastal erosion due to natural or man-made factors are reviewed. Case studies of countermeasure for beach erosion are addressed. We further analyze and discuss historical shoreline and coastal cliff recession as a result of the attack of storm surges and waves. The coastline mainly made up of cliffs (2-3m high), made of soft, easily eroded boulder sand and clay. In total, 3km of land have been lost since 1951, including villages and farm buildings. The most important impacts of beach …

Wearable Sensor-Based Walkability Assessment At Ferry Terminal Using Machine Learning: A Case Study Of Mokpo, Korea, Jungyeon Choi, Hwayoung Kim

Journal of Marine Science and Technology–Taiwan

Walkability assessments are becoming more popular, as walking offers numerous health, environmental, and economic benefits to communities. However, previous studies on ferry terminal walkability assessment have been inadequate. This study aimed to develop a wearable sensor system to automatically assess walkability at ferry terminals without conducting surveys. We applied seven machine learning (ML) classifiers to detect different walking environments, including flat ground (FG), downhill slope (DS), uphill slope (US), and uneven surface (UE). The ML models were evaluated across different combinations of classes: 2-class (FG vs. UE), 3-class (U) (FG vs. US vs. UE), 3-class (D) (FG vs. DS vs. …

Application Of Blockchain Technology In Aquaculture Management, Yu-Jen Pan, Hsin-Pei Shieh

Journal of Marine Science and Technology–Taiwan

In recent years, food safety has become a growing concern in Taiwanese society. To ensure efficient management of the supply chain within the L Aquatic Products company, it is imperative to employ reliable technical support in establishing an effective traceability management system. The traceability of products can provide managers with valuable insight into the intricacies of the supply chain. By establishing a dependable food traceability system, brand trust can be strengthened, and consumers can inquire about the movement of aquatic products within the supply chain. Blockchain technology offers features such as traceability, accountability, transparency, reliability, trust, privacy, and security, making …

Production Of Ground Granulated Blast-Furnace Slag Cement: Energy And Carbon Reduction Efficiency Of Cement-Grinding System, Kuan-Hung Lin, Chung-Chia Yang

Journal of Marine Science and Technology–Taiwan

This study used clinker, ground granulated blast-furnace slag (GGBS), and gypsum in a cement-grinding system to produce GGBS cement (GCE). Gypsum was used as the alkaline activator to modify the surface area of GCE and increase its compressive strength. The results revealed that the use of the gypsum activator and the modification of the surface area of GCE effectively increased the formerly inadequate compressive strength of GCE (GGBS > 60%) in the early stage. In addition, energy consumption data were obtained during the production of GCE and Portland cement (PCE) by the cement-grinding system. The calculations concerning the production proportions indicated …

Multi-Factor Optimization Of Bio-Methanol Production Through Gasification Process Via Statistical Methodology Coupled With Genetic Algorithm, Amin Hedayati Moghaddam, Morteza Esfandyari, Dariush Jafari, Hossein Sakhaeinia

Department of Civil and Environmental Engineering: Faculty Publications

This work innovatively explores the bio-methanol production process, conducts comprehensive analyses, develops statistical models, and optimizes operational conditions, contributing valuable insights to the field of sustainable energy production from biomass. Accordingly, bio-methanol production from biomass through gasification route was investigated and simulated using Aspen Plus software. The effects of operational parameters on energy duty of gasification reactor and the methanol production rate in syngas to methanol reactor were investigated. The parameters affecting the process performance including temperature, pressure, and steam/feed ratio were examined using the response surface methodology (RSM) by central composite design (CCD) technique. Analysis of variance (ANOVA) was …

Multi-Factor Optimization Of Bio-Methanol Production Through Gasification Process Via Statistical Methodology Coupled With Genetic Algorithm, Amin Hedayati Moghaddam, Morteza Esfandyari, Dariush Jafari, Hossein Sakhaeinia

Department of Civil and Environmental Engineering: Faculty Publications

This work innovatively explores the bio-methanol production process, conducts comprehensive analyses, develops statistical models, and optimizes operational conditions, contributing valuable insights to the field of sustainable energy production from biomass. Accordingly, bio-methanol production from biomass through gasification route was investigated and simulated using Aspen Plus software. The effects of operational parameters on energy duty of gasification reactor and the methanol production rate in syngas to methanol reactor were investigated. The parameters affecting the process performance including temperature, pressure, and steam/feed ratio were examined using the response surface methodology (RSM) by central composite design (CCD) technique. Analysis of variance (ANOVA) was …

The Development Of A One-Shot Learning Machine Learning For Industrial Use With Predictive Maintenance, Conor O Brien

Theses

With the advent of Industry 4.0, Manufacturing operations have become more connected and automated. Modern industrial monitoring technology can monitor the performance of both the sensor utilised and the material under monitoring. This has led to a trend where legacy machines without this technology are being removed from production and/or not included in new reconfigurations of production lines, well before their productive lifespan had ended. A key driver for this is the difficulty in retrofitting Predictive Maintenance (PdM) systems to legacy machines, in part due to the machine-to-machine variation present in older machines. Accounting for this variation in PdM systems …

Chacahoula 2023, Tram Phan, Mallory Kaul, Alayna Pellegrin

Chacahoula

WE GROW, WE DEVELOP, WE THRIVE:

The 2023 issue of Chacahoula includes December 2022 and May 2023 graduating classes, as well as stunning photography of Week of Welcome, Homecoming, Mardi Gras, and Spring Fever. With features covering notable students, faculty, and staff, this year's time capsule beautifully preserves an academic year in the life of the University of Louisiana at Monroe.

Using Noninvasive Calibrated Cuff Plethysmography To Observe The Effects Of Cold-Water Immersion On Arterial Compliance, Rita M. Grigorian

Master's Theses

As the prevalence of cardiovascular diseases continues to exponentially grow in populations across the globe, the necessity of determining underlying factors, effective methods of diagnoses, and universally available preventive measures also grows. Early detection of endothelial dysfunction, a proven precursor of cardiovascular diseases, can be extremely impactful in encouraging preventative measures and early intervention before medical conditions become chronic. In recent years, ice plunging, a form of cryotherapy involving full body immersion in cold water, has gained popularity within circles of fitness and health practitioners, gaining the interest of people of all backgrounds. Certain parallels observed between the human physiological …

Engineering News, Fall 2023, School Of Engineering

Engineering News

No abstract provided.

Precision Spraying Using Variable Time Delays And Vision-Based Velocity Estimation, Paolo Rommel Sanchez, Hong Zhang

Henry M. Rowan College of Engineering Departmental Research

Traditionally, precision farm equipment often relies on real-time kinematics and global positioning systems (RTK-GPS) for accurate position and velocity estimates. This approach proved effective and widely adopted in developed regions where RTK-GPS satellite and base station availability and visibility are not limited. However, RTK-GPS signal can be limited in farm areas due to topographic and economic constraints. Thus, this study developed a precision sprayer that estimated the travel velocity locally by tracking the relative motion of plants using a deep-learning-based machine vision system. Sprayer valves were then controlled by variable time delay (VTD) queuing and dynamic filtering. The proposed velocity …

Impulse, Fall 2023, Jill Fier, Micayla Standish, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

2 | Students Thank Sung Shin
4 | Norma Nusz Chandler Never Says Never
6 | Gary Anderson Retires
8 | Three New Endowed Positions
9 | Muthu Endowed Department Head
10 | New Faculty and Staff
14 | Concrete Industry Management Program Online
16 | College Hosts Engineering Conference
17 | Viaflex Supports Research
18 | Lunar Exhibit at Children’s Museum
20 | Break the Ice Challenges
22 | Quarter-Scale Tractor Champions
24 | Nasa Contest Success
26 | Student Compete at Nationals
28 | Culver A Model of Consistency
30 | Engineering Gridders Honored
32 | Liam Murray …

Soil Adsorption Of Heavy Metals To Protect Groundwater Near Refinery Wastewater Discharge Points, Hamid A. Al-Falahi, Ferdous A. Jabir, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

This study presents a strategy to manage the discharge of wastewater, which is either partially treated or untreated, to safeguard the groundwater reserves in the region. a case study involving Ad Diwaniyah refinery wastewater disposal into an adjacent desert was utilized to evaluate the influence of soil adsorption on the attenuation of Pb, Cu, and Cd ion concentrations. Investigation of competitive adsorption of heavy metal ions (Pb2+, Cu2+, and Cd2+) in Dolomite-Limestone soil was conducted through batch and column methods. the adsorption behavior of the bivalent metal cations was observed to be pH dependent. However, the competitive extraction of the …

Cellulose Materials For Drug Delivery Applications, Reham Mohamed

Mechanical Engineering Theses

Non-healing wounds are a growing global public health concern due to inadequate or ineffective therapeutic products available. Cellulose-based biopolymers are attractive wound dressing materials due to their biocompatibility, biodegradability, non-toxicity, and cost-effectiveness. This study aims to design and fabricate solid dosage formulations using carboxymethyl cellulose (CMC) and ethyl cellulose (EC) to facilitate multi-stage releases of phenytoin (PHT) and tetracycline hydrochloride (TCH) from plain carriers, fibers/films composites, and layer-by-layer fiber composites. Results from in vitro drug release assays demonstrated a time-dependent release up to 8 hours from PHT-loaded EC fibers, while TCH-loaded CMC films exhibited a rapid release within 5 minutes. …

Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Thursday, October 26, 2023, Wright State University

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Abstract Books

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Celebration of Student Research, Scholarship & Creative Activities on October 26, 2023.

Mems 411: Dialysqueeze, Ranch Kimball, Maeve Lomax, Tyler Carlson

Mechanical Engineering Design Project Class

Design a device to reduce occupational fatigue injuries suffered by nurses who must manually clamp and unclamp tubing for dialysis machines. This device was designed for MEMS 411 Senior Design.

Mems 411: Medical Clamp, Edis Skampo, Rodery Gonzalez, Sokcheatra Samrith, Sean Lucas

Mechanical Engineering Design Project Class

The goal of the team was to design a plier that would be able to clamp down a medical clamp used for a dialysis machine. Ideally the plier should be able to clamp down 3 medical clamps on three separate dialysis tubes in less than 5 seconds, reduce the force required to clamp those clamps by 4 times, and weigh less than 113 grams. The product design was broken down into 3 separate concepts, with four options for each component. The most preferable option of each component was chosen and several risk factors were taken in consideration so that the …

Additive Manufacturing For Medical Education, Michael Noon

College of Engineering Summer Undergraduate Research Program

A growing body of evidence is suggesting that anatomical knowledge, the keystone of many medical specialties, is suffering among new graduates. While a host of reasons are provided, one common thread that many point to is the decline of cadaver dissections in the classroom. Many virtual audio-visual tools are used to address this gap, yet evidence has shown their ineffectiveness. Given this gap, the high degree of flexibility found in additive manufacturing (AM), and the many uses AM has already found in the medical field, we propose its use to fill this gap, allowing for students to learn with touch …