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Academic Procrastination In Engineering Students, Pascal Wilhelm, Jarick Nijman Oct 2023

Academic Procrastination In Engineering Students, Pascal Wilhelm, Jarick Nijman

Research Papers

Procrastination is a common phenomenon in students in higher education. To voluntarily delay an intended course of action despite expecting to be worse off for the delay can affect academic performance, cause study delay, but also lead to frustration and stress. This study set out to explore students’ beliefs about what causes procrastination, the extent to which online education and the use of digital devices affects their level of procrastination, and their coping mechanisms and ideas about the kind of support a study program can offer to mitigate the effects of procrastination. Focus group interviews were conducted with first-, second- …


A Portable And Reliable Tool For On-Site Physical Reaction Time (Rt) Measurement, Brent Harper, Michael Shiraishi, Rahul Soangra Oct 2023

A Portable And Reliable Tool For On-Site Physical Reaction Time (Rt) Measurement, Brent Harper, Michael Shiraishi, Rahul Soangra

Physical Therapy Faculty Articles and Research

The drop-stick test system (DTS) invention has the capability to measure reaction accurately for sideline mild traumatic brain injury (mTBI) assessment. The reaction time (RT) measurements showed moderate to good inter-instrument reliability with an overall ICC of 0.82 (95 % CI 0.78–0.85). RT is a useful biomarker of mTBI or concussion, but existing technologies in controlled laboratory environments are not feasible for assessments in the field. With wearable technologies and wireless connection with smartphones, it is now easier to conduct RT assessments on the field. The purpose was to develop a portable DTS involving wearable inertial sensors translatable from the …


10.09.2023 Orsp Connect, Liz Williamson Oct 2023

10.09.2023 Orsp Connect, Liz Williamson

ORED Newsletter

No abstract provided.


Metabolomic Insights Into Tuberculosis: Machine Learning Approaches For Biomarker Identification, Miftahul Khair Akbar, Arief Aulia Rahman Oct 2023

Metabolomic Insights Into Tuberculosis: Machine Learning Approaches For Biomarker Identification, Miftahul Khair Akbar, Arief Aulia Rahman

Indonesian Journal of Medical Chemistry and Bioinformatics

The lung parenchyma is largely impacted by the infectious condition known as pulmonary tuberculosis (pulmonary TB) when the immune system creates a wall around the germs in the lungs, a tiny, hard bulge known as a tubercle develops, earning the disease the name tuberculosis. Although the majority of TB germs target the lungs, they can also harm other bodily organs. The identification of TB biomarkers, which are crucial for diagnosis, treatment monitoring, risk analysis, and prognosis, has been the subject of extensive research. Differences in metabolites between normal cells and tuberculosis are considered to be able to support the diagnosis …


Strategic Optimization Of The Flushing Operations In Lubricant Manufacturing And Packaging Facilities, Swapana Jerpoth, Robert Hesketh, C. Stewart Slater, Mariano Savelski, Kirti Maheshkumar Yenkie Oct 2023

Strategic Optimization Of The Flushing Operations In Lubricant Manufacturing And Packaging Facilities, Swapana Jerpoth, Robert Hesketh, C. Stewart Slater, Mariano Savelski, Kirti Maheshkumar Yenkie

Henry M. Rowan College of Engineering Departmental Research

Commercial lubricant industries use a complex pipeline network for the sequential processing of thousands of unique products annually. Flushing is conducted between changeovers to ensure the integrity of each production batch. An upcoming product is used for cleaning the residues of the previous batch, resulting in the formation of a commingled/mixed oil that does not match the specifications of either of the two batches. The existing operations are based on the operator’s experience and trial and error. After a selected flush time, the samples are tested for their viscosity to determine the success of a flush. The approach results in …


Multi-View Brain Tumor Segmentation (Mvbts): An Ensemble Of Planar And Triplanar Attention Unets, Snehal Rajput, Rupal Kapdi, Mehul Raval, Mohendra Roy Oct 2023

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 Oct 2023

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 Oct 2023

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 Oct 2023

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 Oct 2023

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, …


Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur Oct 2023

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 Oct 2023

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 …


Eeg Functional Connectivity In Infants At Elevated Familial Likelihood For Autism Spectrum Disorder, Christian O'Reilly, Scott Huberty, Stefon Van Noordt, James Desjardins, Nicky Wright, Julie Scorah, Sara Jane Webb, Mayada Elsabbagh, Basis Team Oct 2023

Eeg Functional Connectivity In Infants At Elevated Familial Likelihood For Autism Spectrum Disorder, Christian O'Reilly, Scott Huberty, Stefon Van Noordt, James Desjardins, Nicky Wright, Julie Scorah, Sara Jane Webb, Mayada Elsabbagh, Basis Team

Publications

Background

Many studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, we know relatively little about the development of these differences in infancy.

Methods

We used a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6 and 12 months of age in infants at typical (N = 92) or elevated likelihood for ASD (N = 90), determined by the presence of an older sibling with ASD. We computed the functional connectivity between …


Streamlined Hpc Environments With Cvmfs And Cybergis-Compute, Alexander C. Michels, Mit Kotak, Anand Padmanabhan, Shaowen Wang Oct 2023

Streamlined Hpc Environments With Cvmfs And Cybergis-Compute, Alexander C. Michels, Mit Kotak, Anand Padmanabhan, Shaowen Wang

I-GUIDE Forum

High-Performance Computing (HPC) resources provide the potential for complex, large-scale modeling and analysis, fueling scientific progress over the last few decades, but these advances are not equally distributed across disciplines. Those in computational disciplines are often trained to have the necessary technical skills to utilize HPC (e.g. familiarity with the terminal), but many disciplines face technical hurdles when trying to apply HPC resources to their work. This unequal familiarity with HPC is increasingly a problem as cross-discipline teams work to tackle critical interdisciplinary issues like climate change and sustainability. CyberGIS-Compute is middle-ware designed to democratize to HPC services with the …


Covid-19 Detection Using Machine Learning, Amira M. Dawaba, Hanan M. Amer, Ahmed I. Saleh, M.A. Abo-Elsoud Oct 2023

Covid-19 Detection Using Machine Learning, Amira M. Dawaba, Hanan M. Amer, Ahmed I. Saleh, M.A. Abo-Elsoud

Mansoura Engineering Journal

At the end of the year 2019, the world was hit by a drastic pandemic known as COVID-19. The lack of treatment has prompted research in all sectors to address it. Contributions in Computer Science mainly include the development of methods for the diagnostic testing, recognition, and assessment of COVID-19 cases. The most widely used techniques in this field are data science and machine learning (ML). This paper provides a new framework for Computer Aided Diagnosis System for Covid-19 (CADS-Covid-19) using the collected blood test data from patients. CADS consists of two main stages, which are: (I) the features selection …


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 Oct 2023

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 …


Feasibility And Outcomes Of Supplemental Gait Training By Robotic And Conventional Means In Acute Stroke Rehabilitation, Mukul Talaty, Alberto Esquenazi Oct 2023

Feasibility And Outcomes Of Supplemental Gait Training By Robotic And Conventional Means In Acute Stroke Rehabilitation, Mukul Talaty, Alberto Esquenazi

Moss-Magee Rehabilitation Papers

INTRODUCTION: Practicality of implementation and dosing of supplemental gait training in an acute stroke inpatient rehabilitation setting are not well studied but can have positive impact on outcomes.

OBJECTIVES: To determine the feasibility of early, intense supplemental gait training in inpatient stroke rehabilitation, compare functional outcomes and the specific mode of delivery.

DESIGN AND SETTING: Assessor blinded, randomized controlled trial in a tertiary Inpatient Rehabilitation Facility.

PARTICIPANTS: Thirty acute post-stroke patients with unilateral hemiparesis (≥ 18 years of age with a lower limb MAS ≤ 3).

INTERVENTION: Lokomat® or conventional gait training (CGT) in addition to standard mandated therapy time. …


Wearable Sensor-Based Walkability Assessment At Ferry Terminal Using Machine Learning: A Case Study Of Mokpo, Korea, Jungyeon Choi, Hwayoung Kim Oct 2023

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 Oct 2023

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 …


Overview Of Various Components Of Lateral Flow Immunochromatography Assay For The Detection Of Mycotoxins And Limit Of Detection In Food Samples: A Systematic Review, Vinayak Sharma, Thasmin Shahjahan, Bilal Javed, Furong Tian Oct 2023

Overview Of Various Components Of Lateral Flow Immunochromatography Assay For The Detection Of Mycotoxins And Limit Of Detection In Food Samples: A Systematic Review, Vinayak Sharma, Thasmin Shahjahan, Bilal Javed, Furong Tian

Articles

The detection of aflatoxins is essential for the food industry to ensure the safety and quality of food products before their release to the market. The lateral-flow immunochromatography assay (LFIA) is a simple technique that allows the rapid on-site detection of aflatoxins. The purpose of this review is to evaluate and compare the limits of detection reported in the most recent research articles, published between the years of 2015 and 2023. The limits of detection (LODs) were compared against the particle type and particle size, as well as other variables, to identify trends and correlations among the parameters. A growing …


10.02.2023 Orsp Connect, Liz Williamson Oct 2023

10.02.2023 Orsp Connect, Liz Williamson

ORED Newsletter

No abstract provided.


The Development Of A One-Shot Learning Machine Learning For Industrial Use With Predictive Maintenance, Conor O Brien Oct 2023

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 …


Tricritical Point As A Crossover Between Type-Is And Type-Iis Bifurcations, Prabakaran Rajamanickam, Joel Daou Oct 2023

Tricritical Point As A Crossover Between Type-Is And Type-Iis Bifurcations, Prabakaran Rajamanickam, Joel Daou

Progress in Scale Modeling, an International Journal

A tricritical point as a crossover between (stationary finite-wavelength) type-Is and (stationary longwave) type-IIs bifurcations is identified in the study of diffusive-thermal (Turing) instability of flames propagating in a Hele-Shaw channel in a direction transverse to a shear flow. Three regimes exhibiting different scaling laws are identified in the neighbourhood of the tricritical point. For these three regimes, sixth-order partial differential equations are obtained governing the weakly nonlinear evolution of unstable solutions near the onset of instability. These sixth-order PDES may be regarded as the substitute for the classical fourth-order Kuramoto­­­­­­–­­Sivashinsky equation which is not applicable near the …


Chacahoula 2023, Tram Phan, Mallory Kaul, Alayna Pellegrin Oct 2023

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 Oct 2023

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 Oct 2023

Engineering News, Fall 2023, School Of Engineering

Engineering News

No abstract provided.


Characterization Of Influenza-Specific Antibodies, Xinping Ran Oct 2023

Characterization Of Influenza-Specific Antibodies, Xinping Ran

ENGS 86 Independent Projects (AB Students)

Influenza viruses cause respiratory illness that affects 8% of the U.S. population annually. However, current influenza vaccines have a limited efficacy of only 40-60%. This highlights the need for a universal vaccine design that can generate broadly neutralizing antibodies against influenza surface protein hemagglutinin (HA). Previous work by our group identified HA-specific monoclonal antibodies (mAbs) from serum samples through high-throughput antibody profiling. In this study, three of the identified mAbs were generated using mammalian cell expression and their binding affinity against three HA antigens was characterized via Enzyme-Linked Immuno-Sorbent Assay (ELISA). The ELISA results demonstrated specific binding affinity towards B/Yamagata/18/1998 …


Virus Control Aboard A Commuter Bus, Hamid Rahai, Jeremy Bonifacio Oct 2023

Virus Control Aboard A Commuter Bus, Hamid Rahai, Jeremy Bonifacio

Mineta Transportation Institute

A major health concern for public transit users is exposure to viruses from other passengers. This numerical study examines virus containment aboard a public bus with changes to the bus ventilation system. The virus was modeled as a 2.5 µm round solid particle released from the mouth of the infectious passenger at a rate of 21 particles per second at a mouth velocity of 0.278 m/sec. The air delivery to the cabin was two linear ceiling slots spanning the length of the bus delivering 59.38 m3/min (2,097 CFM) of air at a mean velocity of 1 m/sec. Two different axial …


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

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 …


Construction Aspects And Seismic Analysis Of Typical Buildings In Dolpo, Lhakpa Tsering Oct 2023

Construction Aspects And Seismic Analysis Of Typical Buildings In Dolpo, Lhakpa Tsering

Independent Study Project (ISP) Collection

This study delves into the construction aspects and seismic analysis of typical buildings in the challenging terrain of Dolpo, situated within the Himalayan mountain range. Dolpo's unique geological and geographical characteristics, combined with its susceptibility to seismic activity, make it crucial to investigate and understand the dynamics of construction in this remote region. The research explores traditional and contemporary building practices, aiming to elucidate the interplay between construction methodologies and seismic resilience. Through a comprehensive examination of the geological context, structural design, and seismic vulnerability, this study contributes valuable insights to inform the development of robust and earthquake-resistant building strategies …