Engineering Commons^™

Cognitive Eeg Differentiation With Hypnosis-Based Noise Reduction And K-Harmonic Means For Personalized Brainwave Modeling, Ahmad Azhari, Dimas Chaerul Ekty Saputra

Knowledge Engineering and Data Science

This study investigates the integration of hypnosis-based noise reduction and K-Harmonic Means (KHM) clustering for personalized brainwave modeling using Electroencephalography (EEG) data. EEG signals were collected from 100 participants using a Neurosky Mindset sensor at the FP1 (prefrontal) location, with each subject performing nine standardized cognitive tasks such as breathing, memory recall, and mathematical problem-solving. Hypnosis was applied not as a filtering method but as a behavioral protocol to standardize subject conditions and minimize physiological and environmental noise. The EEG signals were sampled at 128 Hz and analyzed using KHM clustering with K=4K = 4K=4, resulting in a Silhouette Score …

Ahp–Python Framework For Multicriteria Modeling Of Rice Production In Asean, Mayang Anglingsari Putri, Risqy Siwi Pradini, Anuraga Jayanegara, Alexander Dimas Yonanta Putra

Knowledge Engineering and Data Science

Rice production is a key indicator of food security and agricultural stability in Southeast Asia, especially among Association of Southeast Asian Nations (ASEAN) countries. Despite shared regional goals, disparities in rice production remain, and previous studies mainly rely on descriptive statistics, lacking structured multicriteria decision-making frameworks and computational tools for cross-country comparisons. This study addresses these gaps by proposing an integrated Analytic Hierarchy Process (AHP)–Python framework to evaluate and rank ASEAN rice production from 2013 to 2022. Three criteria are used: Total Production Volume (K1), Production Growth Trend (K2), and Recent Year Performance (K3), capturing both long-term consistency and short-term …

Stable Numerical Solution Of An Elliptic Pde Inverse Problem Subject To Incomplete Boundary Conditions, Qasim Abd Ali Tayyeh

Knowledge Engineering and Data Science

This study addresses the challenging problem of solving inverse elliptic Partial Differential Equations (PDE) with incomplete boundary data, data available only on a part of the domain boundary. The aim is to develop a robust, effective numerical framework that consistently recovers parameters and/or sources from incomplete, ill-posed data. In the case of a variational problem discretized by the Finite Element Method (FEM) and solved by an adjoint-based optimization strategy, the framework uses Tikhonov regularization. Morozov's Discrepancy Principle is used to determine regularization parameters that achieve the best balance between accuracy and stability. Even with 5% noise in the measurement data, …

Assessing Deep Learning Models And Hyperparameter Optimization For Stable Time-Series Electricity Load Forecasting, Sukma Patrya, Aji Prasetya Wibawa, Aripriharta Aripriharta

Knowledge Engineering and Data Science

Long-term electricity load forecasting plays an important role in ensuring system reliability, optimizing energy management, and making operational plans in face of continuously rising electricity demands. This study suggests a complete deep learning method for univariate forecasting of future electricity loads based on climatology and electricity consumption data for the period between 2019 and 2023. The initial dataset was cleaned, normalized, and partitioned chronologically into train/test datasets. Four train/test split cases (20/80, 40/60, 60/40, 80/20) were considered to explore the impact of different levels of historical data availability on the performance of the suggested framework from data-poor to data-rich situations. …

Computation-Efficient Deep Learning Models For Computer Vision And Multimodal Vision-Language Tasks Via Network Pruning, Abir Mohammad Hadi

Electronic Theses and Dissertations

With the rapid evolution of deep neural networks over the past decade, the demand for efficient, generalizable, and task-adaptable models, especially in computer vision, has increased significantly. To address the computational and deployment challenges posed by overparameterized models, the research community has extensively explored model compression techniques such as pruning, quantization, and distillation. These approaches aim to enhance model efficiency without compromising performance, particularly when adapting to domain-specific tasks under limited resources. This dissertation investigates several underexplored yet critical aspects of task-aware deep learning model compression, spanning both convolutional and vision-language architectures. In the early part of this work, we …

Video Comprehension Score (Vcs): A Metric For Long-Form Video Description Evaluation, Harsh Dubey

Electronic Theses and Dissertations

Existing video description evaluation metrics fail to capture the long-range chronology and semantic alignment essential for long-form descriptions. An effective evaluation metric for long-form descriptions must (i) assess global thematic alignment, (ii) measure local semantic alignment, and (iii) evaluate chronological alignment while detecting corrupted content. We introduce Video Comprehension Score (VCS), a reference-based metric, which directly addresses these evaluation requirements through three components: Global Alignment Score for thematic alignment, Local Alignment Score for local semantic alignment, and Narrative Alignment Score for chronological alignment with adjustable tolerance. We evaluate VCS on two large-scale synthetic datasets designed to test corruption detection and …

Effects Of Peel Angle And Strain Rate On The Bond Between Frcm Composite And Concrete Substrate, Lucas Robert Gervais

Electronic Theses and Dissertations

Fiber-reinforced cementitious matrix (FRCM) composites have gained increasing attention for the rehabilitation and strengthening of concrete and masonry structures due to their favorable mechanical properties, compatibility with existing substrates, and ease of application. The effectiveness of any strengthening procedure depends on the quality of the bond between the external reinforcement and the substrate, ensuring efficient stress transfer and enabling the system to reach its ultimate capacity without premature debonding. While research has focused on the bond performance of FRCM systems under pure shear loading and quasi-static, low strain rate conditions, the effects of mixed-mode loading and high strain rates representative …

Molecular Dynamics Simulation Of Thermal Properties Of Single Walled Carbon Nanotubes, Shiv Nath Jha

Electronic Theses and Dissertations

Molecular dynamics (MD) simulations are a powerful tool for investigating the thermal behavior of carbon nanotubes (CNTs), which are renowned for their exceptional thermal conductivity and potential in nanoscale thermal management applications. This study employs the open-source software LAMMPS, in conjunction with VMD for model generation, to explore the thermal transport properties of (10,10) single-walled carbon nanotubes (SWCNTs) using non-equilibrium molecular dynamics (NEMD). The thermal conductivity of SWCNTs was evaluated across four tube lengths (5 nm, 10 nm, 20 nm, and 40 nm) and at temperatures ranging from 300 K to 600 K under two distinct boundary conditions: free boundary …

Generalized Reference Targeting For Spacecraft, David Geller, David Woffinden, Collin York

Space Dynamics Laboratory Publications

For spaceflight programs to achieve some of the aggressive exploration initiatives such as visiting and landing on other celestial bodies, rendezvousing with other orbiting vehicles, and ultimately returning crew safely to Earth, an assortment of targeting algorithms to compute the necessary burns to strategically maneuver a spacecraft to a variety of destinations are required. Numerous examples exist, but rather than creating and implementing multiple targeting solutions, is it possible to have a general targeting model that can accommodate a variety of applications? Originally motivated for mission design and analysis purposes, this paper outlines a generalized reference targeting algorithm for spaceflight …

Engineering Geological And Groundwater Mapping Of Negara Brunei Darussalam For Urban Planning, Nur Thaqifah Junaidi, Siti Lieyana Azffri, Afiq Aiman Jaya, Muhammad Asri Akmal Suhip, Stefan Herwig Gödeke

ASEAN Journal on Science and Technology for Development

Engineering geology and Hydrogeology play a crucial role in the development of urban areas. Without a thorough geological and hydrogeological understanding, urban development can be risky and prone to numerous challenges. In this study, we aim to conduct engineering geological and groundwater mapping of Brunei utilizing data from 614 sacrificial investigative boreholes drilled over the course of 40 years for geotechnical investigation and housing development. Borehole parameters such as soil data, SPT N-values, depth to groundwater and surface elevation were gathered and evaluated. Soil investigation in the study area revealed predominantly clayey sediments with SPT N-values ranging from 0 to …

A First Model Foundation Design Of Wood Pillar In Banjarmasin Swampland, Nursyarif Agusniansyah, Gusti Novi Sarbini, Akbar Rahman, Muhammad Tharziansyah

ASEAN Journal on Science and Technology for Development

Banjarmasin's swampland presents distinct characteristics that make it suitable for constructing homes, but it also requires special attention, especially concerning the foundation. The soil in this area often has extremely low carrying capacity, which poses a significant challenge for construction. Mistakes in choosing construction materials, coupled with mismatched building loads and inadequate foundation functions, often result in foundation failures—a common cause of building collapses. As the complexity and functionality of buildings increase, the need for more thoughtful house design becomes more crucial. The commonly used wooden pile foundation, while popular, has limited load-bearing capacity, necessitating modifications to enhance its strength. …

Kadysnet: A Novel Approach To Dyslexia Prediction In Children: Combining Handwritten Text Recognition With A Hybrid Cnn-Bilstm-Ctc Model And Personalized Learning Strategies, Shailesh Prabhakar Patil, Ravindra Sadashivrao Apare, Ravindra Honaji Borhade, Parikshit Narendra Mahalle

ASEAN Journal on Science and Technology for Development

This study introduces a novel approach for early dyslexia detection in children through automated handwriting analysis, integrating a hybrid CNN-BiLSTM-CTC architecture with personalized learning strategies. Our method combines a custom CNN-BiLSTM-CTC model with tailored educational interventions to support dyslexic learners. We analyzed children's handwritten text images in English, collected from specially designed tests involving word rewriting, sentence reconstruction, and paragraph composition, particularly challenging tasks for dyslexic individuals. Notably, our CNN-BiLSTM-CTC model achieved the best result with an accuracy of 97.67%, outperforming other architectures. Compared to pre-trained models like EfficientNetB7, DenseNet121, and MobileNetV2, our custom CNN-BiLSTM-CTC model demonstrated superior performance. Key …

Unwritten Rules And Oral Transmission In Architectural Proportion Systems: Case Study Of Bubungan Tinggi House, Huzairin. Muhammad Deddy, Dila Nadya Andini, Rudi Hartono, Anna Oktaviana, Dahliani Dahliani

ASEAN Journal on Science and Technology for Development

The proportional systems in vernacular architecture often exist without formal written codification, raising questions about their transmission across generations. Bubungan Tinggi House which is a replica of the Banjar Kingdom palace was built by Banjarese merchants and aristocrats from the 16th to the 19th centuries, showing a uniform aesthetic quality, which indicates a regularity in the proportions of its form. However, no historical written manuals detailing these proportions are known to exist. To prove the existence of regularity in the Bubungan Tinggi House proportion system, research was conducted by taking 7 Bubungan Tinggi House samples spread across South Kalimantan province, …

Leveraging Strategic Information Systems For Competitive Advantage: A Case Study Of Veolia As A Multinational Enterprise, Sohail Nawaz Sabir

ASEAN Journal on Science and Technology for Development

Instead of examining several components that link planning and strategy implementation, researchers have focused on the alignment of IT and business, as well as the Strategic Information Systems Planning (SISP) process. The goal of this study is to examine several approaches that can close the gap between IT project planning and execution. Therefore, the primary objective of the proposed study is to examine SISP implementation strategies that can be theorized in the context of Veolia, a global multinational corporation (MNC). The primary aspects influencing the SISP for this study are the frequency of planning, the function of IT/business managers, assessment …

Numerical And Experimental Investigation Of Mechanical Performance, Interface Pressure Distribution, And Structural Safety Of Glass Fiber-Reinforced Below-Knee Prosthetic Sockets, Saif M. Abbas, Kadhim K. Resan, Mohammed Ali Abdulrehman, Ali M. Flayyih

ASEAN Journal on Science and Technology for Development

In this study, below-knee prosthetic sockets reinforced with glass-fiber composites were investigated experimentally and numerically. In compliance with the ASTM guidelines, two lay-up configurations were constructed and tested for tensile and fatigue strengths. During the gait trials, the F-socket system was used to measure the interface pressure distribution. Stress, deformation, and safety factor responses under physiological loading conditions were simulated using complementary finite element analysis (FEA). With the yield strength, ultimate tensile strength, and fatigue life significantly improved in the reinforced group, the results demonstrated that the 10-layer laminate displayed superior mechanical performance relative to the 8-layer laminate; however, this …

Performance Evaluation And Economic Analysis Of Lithium Iron Phosphate (Lfp) And Nickel Manganese Cobalt (Nmc) Batteries In Electric Vehicles In Indonesia, Yasa Sanusi, Fatwa Tresna Radityan, Farrah Anis Fazliatul Adnan, Jong Soo Rhee, Dianta Ginting

ASEAN Journal on Science and Technology for Development

The transfer to electric vehicles (EVs) in more and more countries is a response to the increasing problems of climate change and air pollution. Electric cars solve this issue as they have zero emissions. EVs can significantly reduce carbon and air pollution, depending on the charging energy mix. In Indonesia, lithium ferro phosphate and nickel manganese cobalt are among the two most preferred types of batteries for EVs, and both have their advantages. This study evaluates the performance of these batteries in terms of power, range, charging speed, and thermal properties, using a range of battery capacities from 26.7 kWh …

Analysis Of The Sustainability Management Of Coral Reef Ecosystem In The Marine Protected Area Of Wediombo, Gunungkidul, Nabilah L. Rohmah, Rika Harini, Sudrajat Sudrajat

ASEAN Journal on Science and Technology for Development

The Wediombo Coastal Area is a Marine Protected Area (MPA) with highly potential in coral reef ecosystems. According to the Millennium Ecosystem Assessment (MEA), coral reefs play a vital role in supporting human life by providing provisioning, supporting, regulating, and cultural services. However, the utilization of this area as a tourist destination and suboptimal management practices have led to the degradation of its coral reef ecosystems. Efective management strategies for the sustainability of coral reefs can have positive impacts across ecological, economic, social, technological, and institutional dimensions. Therefore, this study aims to analyze the sustainability management of coral reef ecosystem …

Potential Of Green Synthesis Of Silver And Gold Nanoparticles For The Management Of Metabolic Associated Steatotic Liver Disease: A Mini Review, Atiqah Suhaili, Ya Chee Lim, Mei Ann Lim, Lee Hoon Lim, Mohammad Mansoob Khan, Monowarul Mobin Siddique

ASEAN Journal on Science and Technology for Development

Metabolic-associated steatotic liver disease is a metabolic disorder with limited pharmacological treatment options and only one approved medication to date. MASLD can be asymptomatic in its earlier stage and hence, prevention of this disease progression is the most effective approach. Recently, green-synthesized nanoparticles, particularly silver (AgNPs) and gold nanoparticles (AuNPs), have gained interest due to their eco-friendly production, biocompatibility, and bioactive properties. This review highlights the biosynthesis of AgNPs and AuNPs using medicinal plant extracts and their reported biological effects relevant to MASLD management including anti-hyperlipidemic, anti-diabetic, antioxidant and anti-inflammatory activities. While findings are promising, further mechanistic studies and preclinical …

Artificial Intelligence To Transform Lifelong Learning And Workforce Development In Southeast Asia: A Call To Action, Shyh Poh Teo, Khadizah H. Abdul-Mumin

ASEAN Journal on Science and Technology for Development

No abstract for this article type.

Classification Of Indonesian Sign Language (Sibi) Using Data Mining Algorithms K-Nearest Neighbor And Random Forest, Muhammad Zaki Wirawan, Achmad Afif, Anik Nur Handayani, Imanuel Hitipeuw, Osamu Fukuda

Knowledge Engineering and Data Science

This study aims to address the communication hallenges faced by the Indonesian deaf community by developing an automatic classification model for Sistem Bahasa Isyarat Indonesia (SIBI) using data mining techniques. The main objective is to identify a practical algorithm for recognizing SIBI hand gestures to enhance accessibility and inclusiveness in digital communication. A comprehensive dataset consisting of 32,850 gesture samples representing SIBI alphabet signs was collected and processed through feature extraction, data cleaning, and normalization using Z-Transform and Min-Max methods. Two classification algorithms, K-Nearest Neighbor (KNN) and Random Forest, were implemented and evaluated using metrics such as accuracy, precision, recall, …

Autonomous Vehicle Platooning, Tony Abelson

McNair Summer Research Program

This research investigates the construction and performance optimization of two autonomous vehicles with using "Platooning," a strategy aimed at reducing fuel consumption and enhancing transportation efficiency. Platooning allows one vehicle to follow another closely, minimizing aerodynamic drag and improving fuel economy. This study addresses the growing need for sustainable transportation solutions in the context of increasing urbanization and environmental concerns, emphasizing the importance of efficient autonomous vehicle operation. The primary objectives of this research are to assemble autonomous vehicles from scratch and to optimize their performance in both individual and platoon operations. The methodology involves using Traxxas Slash chassis and …

Application-Driven Materials Development Of Solid-State Conductive Composites Of Ultra-High Molecular Weight Polyethylene, Peder Solberg

Dartmouth College Ph.D Dissertations

Ultra-high molecular weight polyethylene (UHMWPE) is a linear long chain homopolymer valued for its toughness, wear resistance, and chemical inertness. In the medical field, these properties make it the material of choice for bearing surfaces despite recognized tradeoffs between wear resistance, toughness, and oxidation resistance. Electrically conductive composites of UHMWPE show promise to enable new types of smart and active load-bearing implants in a future of personalized medicine, if beneficial properties can be maintained with the addition of solid-state additives.

Clinical need-finding conducted through Dartmouth’s Training Program in Surgical Innovation revealed several potential applications for conductive, load-bearing polymers. These include: …

Improving The Figure Of Merit In Iron-Vanadium-Aluminium Thermoelectric Alloy System Guided By Computational Modeling, Tao Fang

Dartmouth College Ph.D Dissertations

Thermoelectric materials can convert a thermal gradient to electricity. Currently, commercialized Bi₂Te₃ is brittle and expensive, which restricts the usage of this material. Compared to other thermoelectric materials, Fe₂VAl is cost-effective, stable and more robust mechanically. However, the figure of merit (zT) had been much lower than Bi₂Te₃. In this thesis, our main goal is to improve the figure of merit in Fe₂VAl system guided by computational modeling. We will start the discussion by presenting the Ge doped Fe₂VAl sample with record thermoelectric figure of merit value. …

Exploring The Benefits, Barriers, And Sustainability Of Community Stem Partnerships: A Qualitative Case Study On Stem Collaboration In Elementary Education, Katherine M. Blagden

Open Access Dissertations

In an era of increasing emphasis on science, technology, engineering, and mathematics (STEM) education, elementary schools often face significant challenges in implementing high-quality, integrated STEM instruction. These challenges include limited resources, inconsistent professional development, and a lack of access to real-world, community-based learning experiences (Dorph et al., 2018; National Science Board, 2024). This dissertation explores how collaborative partnerships among elementary schools, community organizations, and industry professionals can overcome these barriers and foster meaningful, sustainable STEM learning opportunities for young students. Drawing on the Asset-Based Community Development (ABCD) model (Kretzmann & McKnight, 1993) and informed by a constructivist theoretical framework (Vygotsky, …

Democratizing Deep-Sea Technology Development Using Rapid Prototyping Techniques, Breanna Motsenbocker

Open Access Dissertations

Deep-sea research and exploration have consistently been inaccessible to a broader oceanographic community due to the lack of affordable technology and resources that are required for this type of work. Traditionally, to investigate the deep sea, large research vessels are required to operate the expensive and massive equipment that can withstand the intense pressure and harsh environment beyond 200 meters of water. Not only does this lessen the capacity for exploring the deep sea but it also introduces an extreme inequity for who can participate and lead these efforts. With a growing demand for the global Blue Economy and a …

Development And Characterization Of Polysaccharide-Based Controlled Drug Delivery Platforms, Amanda Pepler

Open Access Dissertations

Drug delivery research focuses on overcoming challenges in patient treatment. Most therapeutics are delivered systemically through oral or intravenous routes. However, these administration methods are often inefficient due to therapeutic hydrophobicity, poor bioavailability, and liver metabolic clearance, necessitating frequent dosing. When treatment plans require frequent dosing, patients experience significant fluctuations in therapeutic concentration in the bloodstream, which can increase adverse side effects. These factors contribute to low patient compliance. Therefore, the core focus of drug delivery research is to develop new administration routes for therapeutics. Drug delivery systems (DDS) that can target therapeutics to a localized region offer advantages over …

Comparison Of Dynamic Mode Decomposition With Other Data-Driven Models For Lung Cancer Incidence Rate Prediction, L. Raymond Guo, Jifu Tan, M. Courtney Hughes

Faculty Articles, Papers, and Other Scholarship

Introduction: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and time factors. Machine learning offers powerful tools but can be computationally expensive and require specialized knowledge. Dynamic mode decomposition (DMD) is an alternative that offers efficient analysis with fewer resources. This study explores applying DMD in public health using lung cancer data and compares it with other machine learning models.

Methods: We analyzed lung cancer incidence data (2000–2021) from 1,013 US counties. Machine learning models (random forest, gradient boosting machine, support vector machine) …

Predicting Biomechanical Risk Factors For Division - I Women’S Basketball Athletes, Aayushi Shah, Vanaja Agarwal, Dhairya Shah, Harman Jani, Sristi Sharma, Kaya Tolga, Christopher Taber, Mehul Raval

School of Computer Science & Engineering Faculty Publications

Collegiate basketball is characterized by high-impact movements such as jump landings, making athletes more susceptible to injuries. Critical biomechanical factors like knee flexion, lateral trunk flexion, and foot landing asymmetry are strongly associated with injury risk. This study aims to predict six biomechanical risk factors in the landing error scoring system (LESS). The dataset comprises 8600 video frames of counter-movement jumps (CMJs) from 17 NCAA Division I female basketball athletes, recorded from frontal and lateral perspectives and annotated using a customized error annotation algorithm. The study uses the You Only Look Once (YOLOv5nu) model to analyze the basketball athletes’ CMJ …

Lunar Refueling: Legal Issues And Suggested Solutions, Francesca Giannoni-Crystal

Journal of Law and Mobility

The establishment of settlements and economic activities on the Moon is expected to occur in the near future, positioning the Moon as a critical hub for continued exploration of the Solar System. Central to this development is the creation of a lunar refueling industry, which will play a pivotal role in supporting lunar activities and fostering further exploration.

Lunar refueling, which includes extracting local resources like lunar ice water to obtain hydrogen, offers key benefits, such as reducing the need for resupply missions from Earth, lowering launch costs, extending mission capabilities, and enabling launches from the Moon, which are more …

Development Of A Spss-Based Prediction Model To Evaluate ‎Volatile Organic Compounds During Trenchless Cured-In-Place Pipe Method, Salar Bavili Nezhad

Civil Engineering Dissertations - Archive

The Cured-in-Place Pipe (CIPP) method is a widely implemented trenchless technology for the rehabilitation of deteriorated pipelines, offering benefits such as cost-effectiveness and reduced surface disruption. However, the CIPP installation process, particularly during curing, raises concerns over the emission of Volatile Organic Compounds (VOCs), which can adversely impact worker safety, public health, and environmental standards. This dissertation aims to address these concerns by evaluating VOC emissions during CIPP installations and developing a predictive model to guide emission management practices.

A comprehensive field study was conducted, collecting air samples from 15 pipeline rehabilitation sites that utilized different site-specific conditions using non-Styrene …