Engineering Commons^™

Automation To Autonomy: Temporal Dynamics Of Trust And Visual Attention Allocation Did Not Evolve, Tetsuya Sato, Eric Chancey, Yusuke Yamani

Psychology Faculty Publications

Emerging work environments are expected to implement autonomy that performs various functions without human input. Previous works has shown that trust in automation is negatively correlated with visual attention allocation, indicating that trust is a dynamic construct. Moreover, trust in automation and trust in autonomy appears to evolve in similar ways. However, recent work has demonstrated differences between trust in automation and trust in autonomy within Kaber’s (2018) theoretical framework (Sato et al., 2023b). Yet, it is uncertain whether the development of trust and visual attention allocation differs between automation and autonomy. The present study examined the temporal dynamics of …

The Interacting Roles Of Attention Allocation And Trust In Highly Automated Aam Environments, Yusuke Yamani

Psychology Faculty Publications

[First slide]

Mechanisms of attentive visual processing

• Attention control
• Visual search
• Eye movement
• Aging and individual differences

Limits of human performance in applied environment

• Complex displays
• Machine operation
• Surface transportation
• Advanced air mobility
• Nuclear operation

Methods to ameliorate human cognitive performance

• Human-machine interface
• Human autonomy/AI teaming
• Human-systems integration
• Training

Generalizing Classification Of Pilot Workload: Transfer Learning Versus A Jepa-Inspired Transformer Architecture, Naim Barnett, Shivani Nagrecha, Morgan Glover, Clayton Harper, Justin Wilson, James Maher, Eric C. Larson

International Journal of Aviation, Aeronautics, and Aerospace

Within the context of learning, there poses difficulty when objectively measuring human performance. In this work, we investigate the evaluation of human performance via its relation to the individual's mental capacity by classification of cognitive load within the domain of aviation. By utilizing a mixed virtual and physical flight simulation environment in conjunction with biometric sensing, we create and evaluate the predictive capabilities of a Joint-Embedding Predictive Architecture (JEPA) and compare the architecture and results to traditional methods for transfer learning and domain adaptation. We find that our JEPA inspired architecture can achieve more than 70% accuracy of cognitive workload, …

Advances In Ocean Mapping And Nautical Cartography, Giuseppe Masetti, Ian Church, Anand Hiroji, Ove Andersen

Center for Coastal and Ocean Mapping

The Special Issue of Geomatics on "Advances in Ocean Mapping and Nautical Cartography" addresses emerging methodologies, technologies, and applications in ocean mapping. This collection includes studies on the development of high-resolution seabed mapping techniques, innovative data processing for marine cartography, and advancements in hydrographic surveying. It highlights the importance of integrating geospatial data from sources such as remote sensing, autonomous underwater vehicles, and satellite-based observations. Additionally, articles discuss challenges and strategies for ensuring data accuracy and accessibility, reflecting a growing interest in sustainable marine resource management and navigation safety enhancements.

Afit Generative Ai Teaching Guidebook, Afit Faculty Learning Community, Mark G. Bateman, Brett J. Borghetti, Allen W. Dukes, Nicholas C. Francis, Mike Frick, Bobbie Oh, Kevin Patterson, Hiren J. Patel, Mark G. Reith, Erick S. Tyndall, Teresa M. Walton, Torrey J. Wagner, Timothy S. Wolfe, Jonathan Zemmer

AFIT Documents

AFIT is proud to highlight the Generative AI Teaching Guidebook, a resource designed to provide military educators with practical insights, strategies, and use cases for integrating Generative AI (Gen AI) into their teaching practices. Developed through a collaborative effort involving AFIT faculty across various departments within the Graduate School of Engineering and Management and the School of Systems and Logistics, this digital resource serves as a starting point for educators exploring how to leverage Gen AI in their classrooms. It offers accessible examples and best practices, ensuring utility for instructors of all technical backgrounds. The guidebook provides a comprehensive overview …

Afit Generative Ai Teaching Guidebook Synopsis, Afit Faculty Learning Community, Mark G. Bateman, Brett J. Borghetti, Allen W. Dukes, Nicholas C. Francis, Mike Frick, Bobbie Oh, Kevin Patterson, Hiren J. Patel, Mark G. Reith, Erick S. Tyndall, Teresa M. Walton, Torrey J. Wagner, Timothy S. Wolfe, Jonathan Zemmer

AFIT Documents

The main objective of this work was to bring together various perspectives on how to envision incorporating Gen AI capabilities into the learning environment and identify some best practices for their implementation. Any instructor who is interested in these capabilities but does not necessarily have a technical background can find pragmatic use of the examples provided. While the examples have a wide range of applicability, they are meant to serve as a starting point for educators to explore what would be beneficial to their educational environment, from traditional classroom settings to online continuing education courses.

A Comprehensive Exploration Of 6g Wireless Communication Technologies, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md. Shahriar Uzzal, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory toward 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, we unravel the evolution from the existing 5G infrastructure to the nascent 6G framework, setting the stage for transformative advancements anticipated in the 2030s. Our discourse navigates through the intricate architecture of 6G, highlighting the paradigm shifts toward superconvergence, non-IP-based networking protocols, and information-centric networks, all underpinned by a robust 360-degree cybersecurity and privacy-by-engineering design. Delving into …

Optimizing Ai Language Models: A Study Of Chatgpt-4 Vs. Chatgpt-4o, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Fayaz Bin Hossen, Muhammad Rezaur Rahman, Md. Shahadat Jaman

Electrical & Computer Engineering Faculty Publications

This paper presents a comparative analysis of OpenAI's GPT-4 and its optimized variant, GPT-4o, focusing on their architectural differences, performance, and real-world applications. GPT-4, built upon the Transformer architecture, has set new standards in natural language processing (NLP) with its capacity to generate coherent and contextually relevant text across a wide range of tasks. However, its computational demands, requiring substantial hardware resources, make it less accessible for smaller organizations and real-time applications. In contrast, GPT-4o addresses these challenges by incorporating optimizations such as model compression, parameter pruning, and memory-efficient computation, allowing it to deliver similar performance with significantly lower computational …

A Potentially Fruitful Path Toward A Cleaner And Safer Environment: Mxenes Uses In Environmental Remediation, Ali Mohammad Amani, Milad Abbasi, Atena Najdian, Farzaneh Mohamadpour, Seyed Reza Kasaee, Hesam Kamyab, Shreeshivadasan Chelliapan, Hanieh Ardeshiri, Lobat Tayebi, Ehsan Vafa, Sarah Mosleh-Shirazi, Alireza Jahanbin, Saravanan Rajendran, Daniel Simancas-Racines

Electrical & Computer Engineering Faculty Publications

The rapid industrialization of the world has resulted in severe environmental pollution, necessitating the development of new materials such as pollution remediation. Two-dimensional (2D) MXenes have emerged as a promising family of materials due to their unique physicochemical properties, making them ideal for environmental remediation. The article sheds light on the new opportunities of MXenes in the removal of organic and inorganic contaminants, including organic dyes, pharmaceuticals, heavy metals, radionuclides, and gas pollutants. MXenes also show excellent performance in photocatalytic degradation, adsorption, and microbial inactivation with environmental safety. Moreover, their application in recovering valuable elements from waste streams is also …

Energy-Aware Sensor Fusion Architecture For Autonomous Channel Robot Navigation In Constrained Environments, Mohamed Shili, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

Navigating autonomous robots in confined channels is inherently challenging due to limited space, dynamic obstacles, and energy constraints. Existing sensor fusion strategies often consume excessive power because all sensors remain active regardless of environmental conditions. This paper presents an energy-aware adaptive sensor fusion framework for channel robots that deploys RGB cameras, laser range finders, and IMU sensors according to environmental complexity. Sensor data are fused using an adaptive Extended Kalman Filter (EKF), which selectively integrates multi-sensor information to maintain high navigation accuracy while minimizing energy consumption. An energy management module dynamically adjusts sensor activation and computational load, enabling significant reductions …

Groundwater Pumping Impacts On Stream Depletion In Humboldt County, Ca: Integrating Analytical Models And Field Data, Andy Hans Heise

Cal Poly Humboldt theses and projects

This study addresses the significant concern of stream depletion from groundwater pumping in Humboldt County, CA. The objective of this study is to develop an analytical model for estimating stream depletion and integrating field data into model parameters.

The methodology involved conducting a field study near three operating wells by a stream, installing stream gages upstream and downstream of the wells, and recording pumping rates and schedules for two of the wells. The third well’s pumping data was synthetically generated, for privacy concerns of the well owner. The StreamDepletR package was used for estimating depletion rates in a stream in …

An Optimized Generalized Multi-Color Point Implicit Solver For Intel Gpus Using Oneapi Esimd, Joseph Wassell, Mohammad Zubair, Aaron Walden, Gabriel Nastac, Eric Nielsen, Timothée Ewart

Computer Science Faculty Publications

This paper presents an efficient implementation of a linear-solver kernel relevant to FUN3D, a suite of computational fluid dynamics software developed at NASA’s Langley Research Center. The linear solver is optimized for a range of block sizes commonly used in FUN3D. The implementation targets Aurora, the Argonne Leadership Computing Facility’s (ALCF) exascale machine featuring Intel Data Center Max 1550 GPUs. The linear solver’s performance is memory bandwidth-bound due to its low arithmetic intensity. The primary performance challenges stem from variable matrix row lengths and indirect memory access patterns inherent in unstructured-grid applications. Variable block sizes introduce additional complexity through differing …

Impact Of Color, Shape, And Typeface On Visual Attention: An Eye Tracking Study On Brand Logo, Suzayana Rosidah, Fransiskus Xaverius Ivan, Suatmi Murnani, Hafzatin Nurlatifa, Kristian Adi Nugraha, Sunu Wibirama

ASEAN Journal on Science and Technology for Development

In numerous cases, companies undertake logo redesigns to enhance brand perception. However, little attention has been paid to the impact of each element of the redesigned logo on visual attention and brand perception. To address this research gap, we collected data from eye tracking and self-report questionnaires of 30 participants during exposure to the old and new logos of a prominent bookstore in Indonesia. The results of the questionnaires revealed a significant relationship between the responses concerning color, shape, typeface, and those pertaining to visual attention (p < 0.05). Most participants were able to grasp the value of creativity, flexibility, progress, change, and strength in the new logo shape. The results of eye tracking show that color was the most influential factor that attracted visual attention in old (F(1.5, 43.4) = 14.905, p < 0.05) and new logos (F(1.7, 50) = 34.757, p < 0.05). This study suggests that companies should selectively choose a color scheme of a logo that better attracts the attention of consumers. In addition, our finding is promising as a practical guide for similar research, as well as a case study on how logo redesign affects brand perception and visual attention.

Minimizing Cpu Utilization For Job Scheduling Problems By The Advanced Round Robin Method: A Pragmatic Perspective, Haribhau R Bhapkar, Pankaj R Chandre, Parikshit Mahalle

ASEAN Journal on Science and Technology for Development

CPU scheduling issues include minimizing waiting time for processes, ensuring fairness in resource allocation, and optimizing throughput. Balancing these objectives can be challenging, as improving one aspect may negatively impact another, making it essential to design efficient scheduling algorithms. This work presents an innovative approach to enhance CPU utilization through the development of a Result-Based Round Robin Scheduling Algorithm. Traditional Round Robin Scheduling methods often face challenges in efficiently allocating CPU time, leading to suboptimal system performance. In response to these limitations, the proposed method introduces a result-oriented strategy that dynamically adjusts time quantum allocations based on the execution progress …

Regulation Of Haemodynamic Variables By Laguerre Polynomials Based Model Predictive Control., Sai Sandeep Boda, Hiren Kumar G. Patel, Khyati D. Mistry

ASEAN Journal on Science and Technology for Development

Purpose: Cardiac output (CO) and Mean Arterial Pressure (MAP) are two haemodynamic variables that need regulation in clinical situations, particularly in post-cardiac surgery patients. As it is difficult for clinical personnel to monitor continuously, automatic drug infusion to regulate MAP and CO is recommended and essential in the medical environment. Methods: Two input and two output patient model was used in this work to study the variation of haemodynamic variables in response to the infusion of Dopamine (DP) and Sodium Nitroprusside (SNP) drugs. Model predictive control (MPC) algorithm was exercised here as it was a well-established technique to regulate output …

From Theory To Practice: Simulating Zero Trust Architecture With Python For Cybersecurity, Pankaj R. Chandre, Bhagyashree D. Shendkar, Sulochana Sagar Madachane, Nikita Kulkarni, Sayalee Deshmukh

ASEAN Journal on Science and Technology for Development

The increasing complexity and frequency of cyber threats have necessitated the adoption of advanced security models, such as Zero Trust Architecture (ZTA). ZTA runs on the tenet that no entity whether inside or outside the network should be trusted by default, in contrast to conventional perimeter-based security solutions. This paper describes a thorough method for simulating and implementing Zero Trust Architecture in Python. We examine the essential elements and procedures of ZTA, such as identity verification, access control, and continuous monitoring, through a thorough analysis and step-by-step manual. The simulation shows how ZTA works to ensure strong network security and …

Solid Waste Management Strategies In Coastal Areas Affected By Seawater Flood Disaster, Adib Khoirul Anas, Maryono Maryono, Hartuti Purnaweni

ASEAN Journal on Science and Technology for Development

Solid waste in areas affected by seawater floods must be handled specifically because people often dispose of solid waste on flooded land. This research aims to identify the performance of the community to manage solid waste and solid waste management strategy, solid waste measurement using SNI method 19-3964-1994. Analysis of land affected by seawater floods shows that 12 villages are flooded. Communities in coastal areas are not optimal in managing solid waste because the government has never given directions to manage solid waste in a good way, the facilities and marketing are inadequate so that solid waste is often not …

Exploring Dynamics And Effective Strategies For Tidal Flood Risk Reduction In Indonesia's Coastal Cities, Satria Yudha Adhitama, Diana Puspitasari, Lucia Sandra Budiman, Azis Musthofa

ASEAN Journal on Science and Technology for Development

Indonesia’s coastal regions have distinct charateristics. However, nearly all of these coastal regions are vulnerable to tidal floods. The purpose of this study is to determine the features of coastal regions in Indonesia that have been damaged by tidal floods, as well as the actions implemented to mitigate disaster risk. Thus study takes a qualitiative method with explanatory analysis. The Island Spatial Planning is used to classify Indonesia’s archipelagic regions.An urban area vulnerable to tidal flood was selected from each archipelagic region. The characteristics of coastal regions affected by tidal flood were identified by the tidal flood characteristics, coastal physiography. …

Wind Speed Forecasting: A Comparative Study Of Decomposition Techniques, Manisha Galphade, V.B. Nikam, Nilkamal More, Biplab Banerjee, Arvind W. Kiwelekar, Priyanka Sharma

ASEAN Journal on Science and Technology for Development

Renewable energy is sourced from natural resources that are continually available. Wind energy is a main category of renewable energy, which largely depends on wind speed. Accurate wind speed forecasting is essential for incorporating renewable energy into the electrical grid. Moreover, it is crucial to ensure the safety of wind turbines by anticipating extreme weather conditions and implementing necessary precautions. Predicting wind speed presents several challenges because of dynamic and complex nature of atmospheric conditions. Traditional methods for wind speed forecasting, such as statistical models and basic physical approaches, often face limitations in accuracy, flexibility, and handling of complex data …

Snake Optimization Algorithm For Fractional Order Controller In Three-Area Load Frequency Regulation, Shubra Goel, Omveer Singh

ASEAN Journal on Science and Technology for Development

The transition toward renewable energy-dominated power systems have accentuated the intricacies of frequency control, necessitating advanced regulatory mechanisms. This investigation articulates a tri-zonal frequency stabilization approach, employing a hybridized controller that synergizes Fuzzy Fractional-Order PI and Tilt-Integral-Derivative methodologies. The uniqueness of this approach is further amplified by the deployment of the Snake Optimization algorithm for precise parameter tuning. Set within a conventional grid topology integrated with assorted renewable energy sources, the study evaluates the controller’s adaptability and resilience through a series of comprehensive scenario-based analyses.

Quality And Safety Analysis Of Integrated Bus Services And Feeder Transport In Surabaya, Indonesia, Desrina Yusi Irawati, Agrienta Bellanov, Armadeo Ruben Canariesa

ASEAN Journal on Science and Technology for Development

The Surabaya city government has developed public transportation through integrated bus services and feeder transport. These transportation systems include Trans Semanggi, Suroboyo Bus, and Wira Wiri Surabaya. The challenge facing these transportation programs is the low level of public participation in using public transportation. This research aims to provide a comprehensive investigation of the perceived service quality of integrated public transportation in Surabaya by combining the RESCA and SERVQUAL frameworks. The study contributes by highlighting service quality gaps across five customized dimensions and offering practical insights to improve user satisfaction and increase public transport usage. Each RESCA dimension incorporates RATER …

Manure Handling In Circular Farming: An In Vitro Study Of Fermented Poultry Manure As Unconventional Feed For Ruminants, Dimas Hand Vidya Paradhipta, De Lavida Padma Terrakota, Ali Agus, Andriyani Astuti, Viagian Pastawan, Kharisma Taufiqa Hidayah

ASEAN Journal on Science and Technology for Development

The development of the poultry industry must consider the principle of circular economy. Therefore, this study aims to develop a method of fermenting poultry manure as a new, unconventional feed, which can support the model of circular farming. Poultry manure obtained from laying hens was mixed with cassava solid waste at a ratio of 7:3 to maintain proper moisture content. The mixed manure fermented for 14 days into a 30 kg silo in triplicate using different additives, namely Lactiplantibacillus plantarum FNCC 0020 at 1 x 10⁵ cfu/g (LP), Bacillus cereus LS2B as proteolytic bacteria at 1 x …

Numerical Modeling Of Performance And Phenomena In A Single Proton Exchange Membrane Fuel Cell, Doan Nguyen Cong, Hiep Nguyen Ha

ASEAN Journal on Science and Technology for Development

One of the methods to protect our environment is to convert the fuel's chemical energy directly into electricity, bypassing the fuel's combustion process. This method is implemented in devices called fuel cells. Among them, the proton exchange membrane fuel cell (PEMFC) is widely used in practice because it has outstanding advantages such as high power density and efficiency, low operating temperature and noise, compactness, fast start-up, and, most importantly, only releases water, entirely safe for the environment. The paper presents a method for selecting materials for manufacturing PEMFC components, making a single PEMFC model based on the materials chosen, then …

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 …

Simulating Positive Ion Distribution In The Protodune Single Phase Detector, Vishnu Pfeiffer

Electronic Theses and Dissertations

This work covers the validation and implementation of a model to solve for argon ion (Ar+) distribution in the ProtoDUNE-SP liquid argon time projection chamber (LArTPC). ProtoDUNE-SP undergoes a constant flux of cosmic ray muons due to surface operation. The performance of the ProtoDUNE-SP provided valuable insights into single-phase technology, membrane cryostat technology, and calibration of cryogenic instrumentation. Still, challenges in achieving precise measurements persist due to the space charge effect—the distortion of the electric field within the detector due to the accumulation of positive argon ions generated from constant cosmic muon flux. The overarching goal of this thesis is …

Hydrogen-Enriched Lng As A Mid-Term Solution To Mitigate Greenhouse Gas Emissions From Shipping, Kang-Ki Lee

World Maritime University Ph.D. Dissertations

In light of the International Maritime Organization’s (IMO) ambitious Initial GHG Strategy, the rise in international shipping’s carbon dioxide emissions by 2 percent in 2022 compared to 2019 poses a formidable challenge. This increase underscores the pressing need to address the limited availability of green hydrogen, prompting the exploration of mid-term solutions to bridge this critical gap. The IMO’s 2023 Strategy on Reduction of GHG Emissions from Ships attempted to tackle this challenge head-on, recognizing the urgency of reducing the industry’s substantial carbon footprint. While hydrogen offers a simple solution as a zero-carbon fuel, LNG remains the most widespread alternative …

Modeling Neighborhoods As Fuel For Wildfire, Bryce Alan Young

Graduate Student Theses, Dissertations, & Professional Papers

Wildfire models drive billions of dollars in risk mitigation efforts. However, the modeling community currently lacks a representative fuelscape on which to base simulations of fire spread in the built environment and the wildland-urban interface (WUI) where vegetation and structures act together as fuel for wildfire. This thesis advances wildfire risk modeling by addressing the underdeveloped representation of the built environment in existing frameworks. By identifying inconsistencies in how structure and defensible space features are defined and used across empirical studies, predictive indices, and fire spread models, this research lays the groundwork for standardized modeling approaches and feature selection (Chapter …

Sensitivity Analysis Of The 197 Mhz Prototype Crab Cavity For Eic, Subashini De Silva, Jean R. Delayen, B. Xiao, E. Drachuk, I. H. Senevirathne, A. Castilla, N. Huque, Z. Li

Physics Faculty Publications

The Electron-Ion Collider at BNL requires several crabbing systems that will be operating at 197 MHz and 394 MHz to compensate for the loss of luminosity due to the large crossing angle of the colliding beams. Two 197 MHz crab cavity cryomodules containing two cavities each will be installed in the Hadron Storage Ring (HSR) at the IP6 interaction region. Due to its large size compared to previously developed crabbing cavities, the 197 MHz crabbing cavity system was identified as one of the critical rf systems in the EIC. Therefore, a cavity has been designed including the ancillaries, and is …

Effect Of Activation Temperature On Quantum Efficiency And Lifetime Of Nea Truncated Nanocone Array Gaas Photocathode, Md. Aziz Arroyo Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali

Physics Faculty Publications

This study investigates the quantum efficiency (QE) and operational lifetime of a negative electron affinity GaAs truncated nanocone array (TNCA) photocathode benchmarked against a conventional flat GaAs photocathode under varying activation temperatures. The TNCA structure demonstrated a QE of up to 13.6% at 590 nm with room temperature (RT) activation—approximately 1.5 times higher than its flat counterpart. This enhancement is due to Mie resonance effects within the nanostructure, as confirmed by finite-difference time-domain simulations. Moreover, the TNCA photocathode exhibits significantly extended charge lifetime, with enhancement factors of ∼6.1 and ∼19.8 under RT and 50 °C activations, respectively. These gains are …

Modeling Strain And Quantum Confinement In Gaas/GaXIn1-XP Superlattices For Spin-Polarized Electron Sources, A. Kachwala, G. Blume, S. Marsillac, J. Grames, M. Grau

Physics Faculty Publications

In this study, we systematically design and simulate a series of GaAs-based superlattice configurations aimed at enhancing heavy-hole–light-hole band splitting while simultaneously optimizing band alignment to reduce the conduction band barrier, thereby facilitating efficient electron transport. These combined effects are crucial for achieving high electron spin polarization and high quantum efficiency, the two key performance metrics of next-generation spin-polarized electron sources. We investigated three types of superlattice architectures: (1) compressively strained GaAs wells on GaInP barriers, yielding a maximum band splitting of 140 meV, (2) lattice-matched GaAs/GaInP structures, resulting in the maximum band splitting of 75 meV, and (3) tensile …