Digital Commons Network^™

Economic, Environmental, And Social Characteristics Of E-Scooters On Lsu Campus, Mostafa Elseifi, Md Afif Rahman Chowdhury

Data

This study provides a comprehensive evaluation of e-scooter technology, with a focus on its environmental, economic, and social impacts, particularly within university settings at the Louisiana State University (LSU) campus. A life-cycle assessment (LCA) was conducted to assess the environmental sustainability of e-scooters, encompassing all stages from raw materials acquisition to end-of-life. The analysis determined that the total CO₂ emissions for an e-scooter over a five-year lifespan were approximately 389 kg, with significant reductions possible by improving the lifespan of e-scooters, integrating recycled materials, and utilizing renewable energy sources for charging batteries. The study also compared the environmental and …

Dynamics Of Cell Membrane Lesions And Adaptive Conductance Under The Electrical Stress, Mantas Silkunas, Olga N. Pakhomova, Giedre Silkuniene, Andrei G. Pakhomov

Bioelectrics Publications

Exceeding physiological limits of the cell membrane potential compromises structural integrity, enabling the passage of normally impermeant solutes and disrupting cell function. Electropermeabilization has been studied extensively at the cellular scale, but not at the individual membrane lesion level. We employed fast total internal reflection fluorescence (TIRF) imaging of Ca(2+) entry transients to discern individual lesions in a hyperpolarized cell membrane and characterize their focality, thresholds, electrical conductance, and the lifecycle. A diffuse and momentary membrane permeabilization without a distinct pore formation was observed already at a -100 mV threshold. Polarizing down to -200 mV created focal pores with a …

Evaluation Of Physicochemical Properties Of Chicken Sausages Containing Whey Protein Isolate And Guar Gum, Nur Hamizah Hamid, Namasivayam Navaranjan

ASEAN Journal on Science and Technology for Development

The present work aims to evaluate the physicochemical properties and proximate composition of adding whey protein isolate (WPI) and guar gum (GG) as emulsion gels in chicken sausages formulated with different fat percentages. The fat reduction resulted in products having lower moisture content (p

Preliminary Study On The Effects Of Vinegar As Pre- Treatment For The Oven-Drying Of Pacific Yellowtail Emperor (Lethrinus Atkinsoni) Fillets, Nurisa A. Suhaili, Rafael S. Jamih, Normina A. Abubakar, Jaro O. Ajik, Merilyn Q. Amlani

ASEAN Journal on Science and Technology for Development

This study aimed to assess the impact of various vinegar compositions used as pre-treatment for Pacific Yellowtail Emperor (PYE) fillets during the oven-drying process, with a focus on moisture content and optimal drying conditions. Two types of commercially available vinegar, Superior Vinegar and Datu Puti Vinegar, were compared, and different drying temperatures were evaluated. The investigation revealed that the drying temperature significantly influenced the moisture content of the dried PYE fillets. Among the tested temperatures (40°C, 60°C, and 80°C), the most favorable outcome in terms of moisture content was achieved when fillets were dried at 80°C for a duration of …

Application Of Three Of Selected Medicinal Plant Extracts In Brunei Darussalam To Improve Shelf Life Of Poultry Product, Hazirah Abd Hamid, Namasivayam Navaranjan, Zohrah Sulaiman, Aida Maryam Binti Hj Basri

ASEAN Journal on Science and Technology for Development

Abstract. Bioactive compounds from plant derived in food application become increasingly in demand due to natural and nutritionally safe products. Due to some issues concerning food safety on the excessive use of synthetic preservatives; the present study aims to investigate the natural alternatives to synthetic antimicrobial food additives. The chicken meat’s shelf life was studied by adopting bio-based antimicrobial agents using three of selected native medicinal plants; P. betle, A. catechu, and A. tricolor, against common foodborne pathogens; E. coli, P. aeruginosa, S. aureus, and Salmonella spp. The overall results revealed that, all study extracts possessed antioxidant properties by DPPH …

Byproducts Of Tropical Marine Processing As A Candidate For Industrial Food Ingredients: An Appraisal On Macro And Micronutrients, Abdul Aziz Jaziri, Hajariah Hasanuddin, Rossita Shapawi, Ruzaidi Azli Mohd Mokhtar, Wan Norhana Md. Noordin, Masmunira Rambli, Nurul Huda

ASEAN Journal on Science and Technology for Development

Tropical marine fish is a main raw material for surimi processing plants, including golden threadfin bream (Nemipterus virgatus Houttuyn, 1782) and swallowtail dwarf monocle bream (Parascolopsis eriomma Jordan & Richardson, 1909). After processing, more than 60% of fish are considered as byproducts (i.e., head, viscera, skin, bones, fins and scale), and tend to discard due to poor-utilization. Hence, this paper aims to evaluate macro- and micro-nutrients derived from golden threadfin bream (GTB) and swallowtail dwarf monocle bream (SDMB). The higher content of protein (25.31 ± 0.81%) was observed in the skin part of GTB, followed by the flesh (21.26 ± …

Release Behavior Of Butterfly Pea Anthocyanins From Sago Starch Micro-Composite Films Under Food Stimulants, Afiqah Nabihah Ahmad, Eng Tong Phuah, Namasivayam Navaranjan, Syazana Abdullah Lim

ASEAN Journal on Science and Technology for Development

This study investigates the release behaviour of Butterfly Pea (BP) anthocyanins from Sago starch micro-composite (SMC) films in the presence of food stimulants. To comprehensively describe the release profiles of BP from SMC, six well-established kinetic release models were employed which includes Korsmeyer-Peppas, zero-order, first-order, second-order, Higuchi, and Hixson-Crowell models. These models played a crucial role in examining how the release fraction changes over time, facilitating a comprehensive understanding of the release kinetics of BP anthocyanins. Our data analysis revealed a strong conformity with the Korsmeyer-Peppas model, suggesting its applicability in describing the release of BP anthocyanins from SMC. The …

Emotion Detection Using Ensemble Learning, Priya Harika Yerapothu

Master's Projects

Emotion detection is gaining exponential necessity in today’s technological age. This research seeks to delve into ways conversational AI could be enhanced by integrating emotional intelligence using an ensemble learning approach. Traditional machine learning along with advanced neural network architectures are implemented to improve the understanding and intricacies of emotion detection from textual data. The dataset we use is GoEmotions dataset, annotated with 27 emotional labels, to conduct a detailed analysis of emotion recognition. Various machine learning models, such as HistGradientBoosting, LightGBM, CatBoost, and MLP, will be evaluated side by side with advanced models of Bidirectional Long Short-Term Memory (BiLSTM) …

Regional Sea Level Rise Prediction In Monterey Bay With Lstms And Vertical Land Motion, Branden Lopez

Master's Projects

Earth system data is vast in volume and variety, and is used to forecast weather,

hurricanes, floods, and sea level. Sea Level Rise (SLR) impacts various sectors, espe- cially ecosystems, food production, industry, population, health, and the availability of

clean water. Because of its broad impact, describing the behavior and forecasting SLR is an important topic. Traditional Machine Learning (ML) models vary in use, but many are not capable of capturing all the non-linear spatial and temporal properties of SLR factors. Deep learning models efficaciously handle complex time series data, noise, and high dimensional spaces, making them a focus of …

Skin Cancer Detection Using Reinforcement Learning, Vikas Chercadu

Master's Projects

Advances in medical diagnostics have increasingly harnessed the power of artificial

intelligence, offering substantial improvements in early and accurate disease identifi- cation. This paper elaborates on a novel integration of Multi-Agent Reinforcement

Learning (MARL) with Deep Learning for the early detection of skin cancer, one of the most prevalent and lethal forms of cancer when left unchecked. Our project capitalizes on the sophisticated VGG16 Network for the extraction of detailed features from the widely-utilized HAM10000 dermatoscopic dataset, enhancing these features with additional color, texture, and shape analysis. Utilizing a custom-designed MARL environment, we facilitate a collaboration among multiple intelligent agents, …

Mitigating Learning Bias In Healthcare Datasets, Samyak Jagdish Kumbhalwar

Master's Projects

CVDs have been a major cause of deaths worldwide with WHO reporting 17.9 million deaths annually. Although there are advancements in the treatment of these diseases, most of the fatalities are a result of untimely diagnosis. Active research is going on to collect data points and risk factors related to these diseases, which can enable early diagnosis. Of the datasets available, many researchers have employed different ML models to predict/detect the prevalence of heart diseases. Many employed Tree based, regression models [3, 6]. Few also tried ensemble approaches [1, 2, 4]. These healthcare datasets are generally found to be imbalanced. …

Hindi Image Captioning Using Indictrans2 And Encoder-Decoder Architecture, Anahita Vayalombrone Dinesh

Master's Projects

One of the most prominent tasks that lie on the conjunction of Natural Language Processing (NLP) and computer vision, is image captioning. Image captioning is the generative task of achieving textual descriptions from images. Its application finds use in many real-world scenarios like aiding the visually impaired, editing applications, recommendation systems, and medical imaging. This research focus lies in Hindi image captioning, the official language of India, as it has not been explored as far as its need. Several challenges such as the lack of substantial Hindi text data for training models, the need for human annotators to verify the …

Multimodal Emotion Detection In Conversations And Dialogues: A Fusion Model Approach, Abhinay Jatoth

Master's Projects

Emotion recognition is gaining traction due to its wide range of potential applications across different fields. With the rise of social media, chat platforms, and voice assistants, there is a vast increase in data through which humans implicitly and explicitly carry emotional cues. With new algorithms being developed for understanding the nuances of human language and emotion, businesses can tailor more personalized and empathetic service. Sentiment analysis, expresses a positive, negative, or neutral viewpoint laid the foundation of Emotion classification. Emotion classification in conversations represents the most advanced stage of classification. It is also challenging due to the existence and …

Load Balancing For Cloud-Based Applications, Nitish Ranjan

Master's Projects

Effective load balancing is critical in ensuring optimal resource utilization, reducing latency, and improving the overall performance of distributed systems. This report commences with a comprehensive literature review on existing load-balancing algorithms, examining their methodologies, strengths, and limitations within various computing environments, including cloud computing, data centers, and network traffic management. Despite significant advancements in this field, the dynamic nature of distributed systems, coupled with the ever-increasing demand for efficient data processing, poses ongoing challenges. In response, this study proposes a novel load-balancing algorithm to address these contemporary challenges. The approach leverages dynamic and hybrid load balancing, distinguishing it from …

Exploring The Use And Misuse Of Large Language Models (Llms), Hezekiah Paul D. Valdez

Master's Projects

Large Language Models (LLMs) have quickly gone from simple rule-based systems to complex knowledge bases capable of tackling many different tasks across a variety of fields. What began as an exercise in human-computer interaction has become the basis for artificial intelligence in a variety of mediums. When attached to larger systems, LLMs become generative assistants that can perform highly on human proficiency assessments and other benchmark skill assessments. This increase in proficiency has led these systems to be deployed in fields such as cybersecurity, business, and programming to help improve productivity and efficiency. However, such a wide availability has allowed …

Enhancing Qwen2.5-Coder: A Deep Dive Into Fine-Tuning Using Peft For Superior Code Outputs, Lohith Nagaraja

Master's Projects

The main objective of this research is to improve the quality of software code that is produced by the Qwen2.5-Coder model specifically in terms of maintainability, complexity, and reliability. Our approach is going to be a more specific one that will involve the Parameter-Efficient Fine Tuning (PEFT) framework combined with quantization through Low-Rank Adaption (LoRA). This approach involves fine-tuning only some of the parameters of a model to make it suitable for software programming with the general structure of the model largely intact. In this paper, SonarQube is used as a tool to help quantify the improvements made to the …

Integrated Building Assessment To Enable Retrofit Design, Fabrication And Verification: A Drone-Based Approach, Paul Crovella

SyracuseCoE

Buildings account for approximately 40% of annual greenhouse gas emissions in the United States. In New York State, approximately 80% of residential and commercial buildings were constructed before the emerging energy codes in the 1970s [1]. Therefore, there is a significant need for affordable and scalable building retrofit solutions with low embodied emissions to meet the targets in the NYS Climate Leadership and Community Protection Act of 2019. A building energy audit is the initial step to quantify a building's energy performance and reveal its energy-saving potential. However, performing a high-level energy audit requires detailed field analysis and is often …

The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña

Social Science - All Scholarship

This work formulates the hazard prediction problem while addressing the research question: Can machine learning create a model to automatically recognize patterns that correspond to hazard state conditions during a mission-critical operation? Supervised learning models were trained and tested on data observed from mission simulators, which allowed for safe observation of dynamic system states and undesirable casualty events. The prediction task was formulated as a binary classification problem, producing the probability of being in a hazard state at time t and providing situational awareness of a possible imminent loss. Several modeling architectures were investigated: neural networks, logistic regression, a support …

Towards Algorithmic Justice: Human Centered Approaches To Artificial Intelligence Design To Support Fairness And Mitigate Bias In The Financial Services Sector, Jihyun Kim

CMC Senior Theses

Artificial Intelligence (AI) has positively transformed the Financial services sector but also introduced AI biases against protected groups, amplifying existing prejudices against marginalized communities. The financial decisions made by biased algorithms could cause life-changing ramifications in applications such as lending and credit scoring. Human Centered AI (HCAI) is an emerging concept where AI systems seek to augment, not replace human abilities while preserving human control to ensure transparency, equity and privacy. The evolving field of HCAI shares a common ground with and can be enhanced by the Human Centered Design principles in that they both put humans, the user, at …

Photoluminescence Switching In Quantum Dots Connected With Fluorinated And Hydrogenated Photochromic Molecules, Ephraiem S. Sarabamoun, Jonathan M. Bietsch, Pramod Aryal, Amelia G. Reid, Maurice Curran, Grayson Johnson, Esther H. R. Tsai, Charles W. Machan, Guijun Wang, Joshua J. Choi

Chemistry & Biochemistry Faculty Publications

We investigate switching of photoluminescence (PL) from PbS quantum dots (QDs) crosslinked with two different types of photochromic diarylethene molecules, 4,4'-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (1H) and 4,4'-(1-perfluorocyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (2F). Our results show that the QDs crosslinked with the hydrogenated molecule (1H) exhibit a greater amount of switching in photoluminescence intensity compared to QDs crosslinked with the fluorinated molecule (2F). With a combination of differential pulse voltammetry and density functional theory, we attribute the different amount of PL switching to the different energy levels between 1H and 2F molecules which result in different potential barrier …

Hardness Removal By A Continuous Flow Electrochemical Reactor From Different Types Of Water, Shahad Fadhil Alrubaye, Naseer A. Al Haboubi, Hussein A. Al-Amili, Aiman H. Al-Allaq, Dhuha Ahmed Mohammed

Mechanical & Aerospace Engineering Faculty Publications

The present study focuses on the technique of hardness removal by using a novel reactor performing an electrocoagulation (EC) process. The variation of alkalinity is also recorded. Continuous flow experiments were conducted for Total Hardness (TH) removal using a transparent plastic reactor using aluminum plate electrodes that have holes so that the water flows through the plates in a zigzag way. The influence of various operating parameters such as the number of plates (two and four), flow rate (600, 1000 L/h), and water type (Tigris River & rejected water from Reverse Osmosis system RO) was investigated. The results showed that …

Development Of A Two-Finger Haptic Robotic Hand With Novel Stiffness Detection And Impedance Control, Vahid Mohammadi, Ramin Shahbad, Mojtaba Hosseini, Mohammad Hossein Gholampour, Saeed Shiry Ghidary, Farshid Najafi, Ahad Behboodi

Mechanical & Aerospace Engineering Faculty Publications

Haptic hands and grippers, designed to enable skillful object manipulation, are pivotal for high-precision interaction with environments. These technologies are particularly vital in fields such as minimally invasive surgery, where they enhance surgical accuracy and tactile feedback: in the development of advanced prosthetic limbs, offering users improved functionality and a more natural sense of touch, and within industrial automation and manufacturing, they contribute to more efficient, safe, and flexible production processes. This paper presents the development of a two-finger robotic hand that employs simple yet precise strategies to manipulate objects without damaging or dropping them. Our innovative approach fused force-sensitive …

Factors Affecting Electrocoagulation Process For Different Water Types: A Review, Shahad Fadhil Abed Al-Rubaye, Naseer A. Alhaboubi, Aiman H. Al-Allaq

Mechanical & Aerospace Engineering Faculty Publications

Raw water must meet specific physical, chemical, and biological requirements to be suitable for drinking. There are various techniques available for treating wastewater, and aside from conventional methods that involve chemicals, electrocoagulation is an efficient and advanced approach. Electrocoagulation has proven effective in treating many pollutants, including bacteria, viruses, iron, fluoride, sulfate, boron, hardness, and turbidity. Total suspended solids, organic and inorganic materials, chemical oxygen demand COD, biochemical oxygen demand BOD, and color. It finds extensive application in treating different types of water and wastewater due to its exceptional ability to remove diverse contaminants. Recently, electrocoagulation has garnered significant attention …

Prediction Of Chlorophyll-A As An Index Of Harmful Algal Blooms Using Machine Learning Models, Ibrahim Busari, Debrabata Sahoo, R. Daren Harmel, Brian E. Haggard

Biological and Agricultural Engineering Faculty Publications and Presentations

The complex dynamics of freshwater harmful algal blooms (HABs) necessitate proactive monitoring approaches to mitigate their impacts. The rapid breakthrough in computing prowess and statistical advances is triggering the development of data-driven techniques such as machine learning (ML) models, which have been shown in different fields to be instrumental in finding patterns for explaining relationships in observed data. This study assesses the ability of ML models for HABs monitoring in a lake using chlorophyll-a concentration as the index. The selected models for this study were regression tree, random forest (RF), multilayer perceptron (MLP), support vector regression (SVR), long short-term memory …

Stormwater Alters The Resistome Of Urban Surface Water, An Impact That Can Be Mitigated By Green Stormwater Infrastructure, Kassidy N. O'Malley, Walter M. Mcdonald, Patrick J. Mcnamara

Civil and Environmental Engineering Faculty Research and Publications

Antibiotic resistance poses an escalating threat to global health, with environmental reservoirs being pivotal areas of concern, as well as opportunities for potential mitigation. Stormwater systems are an important type of environmental reservoir in the urban water cycle with a dearth of research related to impacts on antibiotic resistance. In particular, there has been limited research exploring the impact of diverse antibiotic resistance genes (ARGs) carried by stormwater from various land uses on surface water, nor has there been an examination of the role played by green stormwater infrastructure (GSI) in mitigating this impact. Therefore, this study sought to elucidate …

An Efficient And Trusted Deep Learning Framework For Real-Time Ppe Detection In Secure Iomt Environment, Anusha Verma

Browse all Theses and Dissertations

Occupationally-acquired infections impact thousands of healthcare workers (HCWs) in the U.S., with many cases preventable through proper use of personal protective equipment (PPE). This study seeks to develop a robust system to enhance PPE compliance and reduce infection risks among HCWs. The objectives of this thesis are twofold: (1) to create a hybrid machine learning model that combines object detection and keypoint detection to ensure correct donning and doffing of PPE, and (2) to design a real-time feedback system using LED indicators and a display interface to offer actionable guidance to HCWs during PPE usage. The goal is to optimize …

A Systematic Study Of Freezing Behavior In Earthworms In Response To Auditory And Vibratory Stimuli, Navjot Singh, A. Burton, Dragana Ivkovich Claflin

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

This study examined the parameters needed to reliably induce a freezing fear response to a predator-like auditory stimulus in the earthworm species Eisenia Fetida. Previous work from our lab found that a grunting noise was more reliable in causing freezing compared to a mole sound, i.e. artificial versus natural predators of E. Fetida (Worthen et al., 2024). In the present study, 8 amplitude levels of grunting sound were presented in either serial or random order. The speaker location was varied so that it either did or did not touch the apparatus, thus producing a mechanical vibration in addition to the …

Probiotics-Encapsulated Hydrogel Beadsfor Functional Food Applications, Korlid Thinkohkaew

Chulalongkorn University Theses and Dissertations (Chula ETD)

The growing application of probiotics in functional food products has highlighted the need to preserve their viability and stability throughout gastrointestinal transit and storage. This study aims to address these issues by developing and optimizing biopolymer-based hydrogel beads using a vibrational nozzle-assisted ionic gelation method. Initially, probiotics were encapsulated in chitosan-coated alginate/gellan gum microcapsules using a vibrational nozzle-assisted ionic gelation method. The encapsulation process was optimized via response surface methodology, achieving high encapsulation efficiency (97.35%) under optimal conditions (0.6% gellan gum, 1.61% CaCl2, and a flow rate of 9.84 mL/min). The optimized microcapsules demonstrated strong tolerance to simulated gastric fluid …

Spatio-Heterogeneity Risk Assessment From Microplastic Contaminations In Water And Sediment Of The Inner Gulf Of Thailand, Sarayut Suanluang

Chulalongkorn University Theses and Dissertations (Chula ETD)

The inner Gulf of Thailand, a shallow semi-enclosed marine basin, plays a vital economic and ecological role for Thailand, yet faces increasing threats from microplastic (MP) pollution driven by urbanization, industrial and agriculture developments, and riverine discharges. This study aimed to assess the spatial and vertical distributions, polymer characteristics, and ecological risks associated with MP contamination in water columns and surface sediments throughout the inner Gulf. Sampling was conducted at 13 stations, with water collected from surface, mid-depth, and bottom layers, and sediment samples taken from corresponding surface sediments. MPs were analyzed for abundance, size, shape, color, and polymer composition …

การประเมินอายุความล้าของตะไบทางทันตกรรมแบบหมุนโดยวิธีทดสอบชิ้นงานร่วมกับระเบียบวิธีไฟไนต์เอลิเมนต์, กิตติพงษ์ สุดจินดา

Chulalongkorn University Theses and Dissertations (Chula ETD)

ตะไบทันตกรรมเป็นเครื่องมือที่ใช้ในการรักษาคลองรากฟันเพื่อคงสภาพฟันไว้โดยไม่ต้องถอนออก ระหว่างการรักษา ตะไบเหล่านี้จะรับภาระแบบวัฏจักร ระหว่างภาระดึงและภาระอัด การใช้งานตะไบเกินกว่าขีดจำกัดความล้าของวัสดุ อาจทำให้เกิดการแตกหักจากความล้า โดยไม่มีสัญญาณให้เห็นล่วงหน้า ซึ่งอาจนำไปสู่ความล้มเหลวของการรักษา วิทยานิพนธ์ฉบับนี้มีวัตถุประสงค์เพื่อสร้างเส้นโค้งความเค้น-อายุการใช้งาน และแบบความเครียด-อายุการใช้งาน เพื่อใช้ในการทำนายอายุความล้าของตะไบภายใต้สภาพความโค้งของคลองรากฟันที่แตกต่างกัน โดยไม่ต้องทราบคุณสมบัติความล้าของวัสดุตะไบ และเพื่อเปรียบเทียบความแม่นยำของเส้นโค้งทั้งสอง ในการดำเนินการ ได้ใช้ระเบียบวิธีไฟไนต์เอลิเมนต์ เพื่อจำลองพฤติกรรมทางกลของตะไบ และประเมินค่าแอมพลิจูดความเค้นและความเครียดจากตะไบในคลองรากฟันอย่างง่าย 8 ลักษณะความโค้ง จากนั้นทำการทดสอบความล้าดัดในคลองรากฟันแบบเดียวกันเพื่อเก็บข้อมูลอายุความล้า ข้อมูลที่ได้ถูกนำไปหาเส้นโค้งตัวแทนของข้อมูลด้วยสมการของ Basquin และ Coffin-Manson เพื่อสร้างเส้นโค้งความเค้น-อายุความล้า และความเครียด-อายุความล้า นอกจากนี้ยังได้ตรวจสอบความแม่นยำและความสอดคล้องของเส้นโค้งที่พัฒนาขึ้น โดยใช้ข้อมูลจากการทดสอบตะไบในคลองรากฟันที่มีลักษณะความโค้งแบบตัวเอส จำนวน 6 ลักษณะ ที่มีระดับแอมพลิจูดความเค้นและความเครียดต่างจากข้อมูลก่อนหน้า ผลการศึกษาแสดงให้เห็นว่าเส้นโค้งความเครียด-อายุการใช้งาน สามารถพยากรณ์อายุความล้าได้แม่นยำกว่า และสอดคล้องกับพฤติกรรมความล้าของตะไบมากกว่าเส้นโค้งความเค้น-อายุการใช้งาน) อย่างไรก็ตาม เส้นโค้งดังกล่าว สามารถใช้พยากรณ์ได้อย่างเหมาะสมเฉพาะในช่วงอายุความล้าที่ต่ำกว่า 2,500 รอบ ซึ่งแสดงถึงความจำเป็นในการศึกษาพฤติกรรมความล้าในรอบสูงเพิ่มเติมในอนาคต