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Articles 1681 - 1710 of 13783

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

3d Point Cloud Sensing And Analytics With Applications In Process Mining And Quality Control Of Additive Manufacturing, Zehao Ye Jan 2024

3d Point Cloud Sensing And Analytics With Applications In Process Mining And Quality Control Of Additive Manufacturing, Zehao Ye

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

The rapid advancement in Additive Manufacturing (AM) technologies has developed significant innovations in various sectors, including medical, aerospace, and automotive industries. Despite these benefits, the adoption of AM is often hindered by quality inconsistencies related to the surface defects and geometrical inaccuracies in the fabricated products. These defects can significantly undermine the mechanical properties of the products, leading to material waste and potential safety issues. This dissertation addresses the critical challenges in quality control of AM processes through the integration of 3D point cloud data and machine learning techniques, aiming to enhance the reliability and efficiency of AM systems. The …

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Development Of Dynamic Mass-Energy-Thermodynamics Constrained Hybrid Neural Network Models For Process Systems Applications, Angan Mukherjee Jan 2024

Development Of Dynamic Mass-Energy-Thermodynamics Constrained Hybrid Neural Network Models For Process Systems Applications, Angan Mukherjee

Graduate Theses, Dissertations, and Problem Reports (ETD)

First-principles models can provide very good predictions even for cases when there are no data at all, or data are limited in certain range of operating conditions, or for cases where data collection is infeasible. However, the development of accurate first-principles models for complex nonlinear dynamic systems can be time consuming, computationally expensive, and may be infeasible for certain systems due to lack of sufficient knowledge (information). It is also challenging to adapt first-principles models for time-varying systems. Furthermore, it can be difficult, if not impossible, to develop accurate models for some complex phenomena that are poorly understood. On the …

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Enhancing Robotic Exploration Through Semantically-Guided Sampling Strategies, Christopher Alexander Arend Tatsch Jan 2024

Enhancing Robotic Exploration Through Semantically-Guided Sampling Strategies, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports (ETD)

From space and deep-sea exploration to disaster response and environmental monitoring, autonomous robots are essential for advancing science, improving safety, and addressing critical challenges. This dissertation introduces a novel open-source strategy for autonomous robotic exploration: the Semantically-Guided Exploration (SGE) framework. Designed for ground vehicles, SGE integrates semantic understanding into the autonomous exploration process, improving decision-making in complex environments. Specifically, the proposed sampling-based approach uses the information from the semantic segmentation of RGB images and depth images to guide the robot's selection of exploration goals. This method enables the robot to steer away from potential dangers such as large rocks and …

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User-Interaction With A Web-Served Global Ground Motion Relational Database, T. E. Buckreis, C. C. Nweke, P. Wang, S. J. Brandenberg, R. Shams, M. E. Ramos-Sepulveda, R. Pretell, S. Mazzoni Jan 2024

User-Interaction With A Web-Served Global Ground Motion Relational Database, T. E. Buckreis, C. C. Nweke, P. Wang, S. J. Brandenberg, R. Shams, M. E. Ramos-Sepulveda, R. Pretell, S. Mazzoni

Civil & Environmental Engineering Faculty Publications

We present an application programming interface (API) which facilitates public access to a global relational database of earthquake ground motion intensity measures, associated metadata, and time-series data. Next Generation Attenuation (NGA)-East and NGA-West2 project spreadsheets have been adapted into a relational database format composed of multiple tables through a series of primary and foreign keys. The combined dataset has been expanded to include contributions from earthquakes, generally with magnitudes greater than M3.9, that have occurred since the conclusion of the data synthesis component of both projects in 2011. Currently the database includes 62,449 ground motions recorded at 9,092 stations for …

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‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody Jan 2024

‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody

Publications and Research

Most timetabling problems have a given objective function to measure the quality of a solution. However, users may have a “I know it when I see it” recognition of a quality schedule, without specifying the complete basis for their judgment. In this situation, the objective function cannot be exclusively used as a solution quality measurement. This work presents an AI based approach to aid in categorizing the solution’s quality when the users have not explicitly defined all factors used in their criteria.

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An Impedance Tube Technique For Estimating The Insertion Loss Of Earplugs, K. Carillo, O. Doutres, F. Sgard Jan 2024

An Impedance Tube Technique For Estimating The Insertion Loss Of Earplugs, K. Carillo, O. Doutres, F. Sgard

Études primaires

This paper proposes a quick and straightforward technique for estimating the insertion loss (IL) of earplugs measured on an acoustical test fixture (ATF) using a commercial impedance tube. In this method, the earplug's acoustic properties (i.e., its transmission loss and the reflection coefficient of its medial surface) are determined from its transfer matrix measured using the three-microphones impedance tube method modified here for the current application. The IL is then estimated using a one-dimensional analytical model of open and occluded earcanals based on the wavefield decomposition theory. The method is evaluated numerically and experimentally from 50 Hz to 6.5 kHz. …

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Methods That Support The Validation Of Agent-Based Models: An Overview And Discussion, Andrew Collins, Matthew Koehler, Christopher Lynch Jan 2024

Methods That Support The Validation Of Agent-Based Models: An Overview And Discussion, Andrew Collins, Matthew Koehler, Christopher Lynch

Engineering Management & Systems Engineering Faculty Publications

Validation is the process of determining if a model adequately represents the system under study for the model’s intended purpose. Validation is a critical component in building the credibility of a simulation model with its end-users. Effectively conducting validation can be a daunting task for both novice and experienced simulation developers. Further compounding the difficult task of conducting validation is that there is no universally accepted approach for assessing a simulation. These challenges are particularly relevant to the paradigm of Agent-Based Modeling and Simulation (ABMS) because of the complexity found in these models’ mechanisms and in the real-world situations they …

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Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan Jan 2024

Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan

Engineering Management & Systems Engineering Faculty Publications

Integrating human behavior into agent-based models has been challenging due to its diversity. An example is strategic coalition formation, which occurs when an individual decides to collaborate with others because it strategically benefits them, thereby increasing the expected utility of the situation. An algorithm called ABMSCORE was developed to help model strategic coalition formation in agent-based models. The ABMSCORE algorithm employs hedonic games from cooperative game theory and has been applied to various situations, including refugee egress and smallholder farming cooperatives. This paper discusses ABMSCORE, including its mechanism, requirements, limitations, and application. To demonstrate the potential of ABMSCORE, a new …

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Yankee Manufacturing Multi-Assembly Pvc-Gasket Assembly Mechanism, Lily Coss, Jessica Kun, Dana Chapin, Jenan Hasan Jan 2024

Yankee Manufacturing Multi-Assembly Pvc-Gasket Assembly Mechanism, Lily Coss, Jessica Kun, Dana Chapin, Jenan Hasan

Williams Honors College, Honors Research Projects

This project focuses on designing and implementing an efficient mechanism to connect PVC and gasket pieces in the door assembly process at Yankee Manufacturing. The aim is to improve process efficiency and productivity by increasing the assembly rate from 130 to 195 assemblies per hour, a 38% improvement. The project involved research, design iterations, performance evaluations, and adherence to engineering codes and standards, particularly focused on safety, ergonomics, and sustainability. The design process includes addressing challenges from a previous attempt, redefining project scope, and incorporating new elements such as transitioning to the packaging process seamlessly. Ethical considerations include promoting operator …

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Letac-Mpc: Learning Model Predictive Control For Tactile-Reactive Grasping, Zhengtong Xu, Yu She Jan 2024

Letac-Mpc: Learning Model Predictive Control For Tactile-Reactive Grasping, Zhengtong Xu, Yu She

School of Industrial Engineering Faculty Publications

Grasping is a crucial task in robotics, necessitating tactile feedback and reactive grasping adjustments for robust grasping of objects under various conditions and with differing physical properties. In this article, we introduce LeTac-MPC, a learning-based model predictive control (MPC) for tactile-reactive grasping. Our approach enables the gripper to grasp objects with different physical properties on dynamic and force-interactive tasks. We utilize a vision-based tactile sensor, GelSight (Yuan et al. 2017), which is capable of perceiving high-resolution tactile feedback that contains information on the physical properties and states of the grasped object. LeTac-MPC incorporates a differentiable MPC layer designed to model …

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Leto: Learning Constrained Visuomotor Policy With Differentiable Trajectory Optimization, Zhengtong Xu, Yu She Jan 2024

Leto: Learning Constrained Visuomotor Policy With Differentiable Trajectory Optimization, Zhengtong Xu, Yu She

School of Industrial Engineering Faculty Publications

This paper introduces LeTO, a method for learning constrained visuomotor policy with differentiable trajectory optimization. Our approach integrates a differentiable optimization layer into the neural network. By formulating the optimization layer as a trajectory optimization problem, we enable the model to end-to-end generate actions in a safe and constraint-controlled fashion without extra modules. Our method allows for the introduction of constraint information during the training process, thereby balancing the training objectives of satisfying constraints, smoothing the trajectories, and minimizing errors with demonstrations. This “gray box” method marries optimization-based safety and interpretability with powerful representational abilities of neural networks. We quantitatively …

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Yankee Feedstock Project, Nathan Mcanany, Richard Gualtiere Jan 2024

Yankee Feedstock Project, Nathan Mcanany, Richard Gualtiere

Williams Honors College, Honors Research Projects

This report details the design process, application, considerations, costs, and functionality of an automated tape “feedstock” machine. Yankee Insulation Products will use this project to create rolls of Aluminum foil tape that are included in their Therma-Dome assembly kit. The goal of this design will aid in the streamlining and effectiveness of the current process. When designing the automated process, the current process was evaluated for areas of improvement. Design parameters were also given to the project by the sponsoring company that were to be considered and incorporated.

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Conflict Profiles And Team Outcomes In Cross-Disciplinary Teams: An Integrated Latent Profile Analysis And Natural Language Processing Approach, Francisco Cima, Pilar Pazos Jan 2024

Conflict Profiles And Team Outcomes In Cross-Disciplinary Teams: An Integrated Latent Profile Analysis And Natural Language Processing Approach, Francisco Cima, Pilar Pazos

Engineering Management & Systems Engineering Faculty Publications

Team conflict is a naturally emerging phenomenon resulting from individuals' interactions during project execution. Cross-disciplinary teams can experience higher levels of conflict than single-discipline teams because of the increased diversity of knowledge and perspectives. Research has shown that team conflict can emerge from different types of disagreements (cognitive and interpersonal), which have different implications for team functioning. Past empirical research has focused on the impact of both conflict types independent from each other while overlooking their combined effects. This work examines the conflict profiles resulting from the combined levels of interpersonal and cognitive disagreements and their association with team outcomes. …

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Collaborative Robotic Finishing Platform For Metal Part Processing Towards Industry 5.0, Seyedhossein Hajargarbashi, Gabriel Côté, Jonathan Boisvert, Ramy Meziane, Chen Xu, Corentin Hubert, Sabrina Jocelyn, Clément Gosselin Jan 2024

Collaborative Robotic Finishing Platform For Metal Part Processing Towards Industry 5.0, Seyedhossein Hajargarbashi, Gabriel Côté, Jonathan Boisvert, Ramy Meziane, Chen Xu, Corentin Hubert, Sabrina Jocelyn, Clément Gosselin

Articles dans des actes de congrès

Manual finishing operations in aerospace and ground transportation industries are often associated with health-and-safety-related issues such as musculoskeletal disorders, productivity loss, and challenges in workforce renewal. This work presents an innovative automated solution to address these challenges, prioritizing the ease of implementation and affordability for small and midsize enterprises (SMEs). Our proposed solution is a collaborative robotic (cobotic) finishing platform designed to eliminate labor-intensive work while keeping human operators in the loop to manage unforeseen situations. This platform aims to eliminate health risks, enhance repeatability, improve product quality, and increase productivity. This paper describes the mechanical design of the platform, …

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Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis Jan 2024

Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis

Theses and Dissertations

This dissertation explores how to better manage resources in mobile networks, especially for enhancing the performance of Unmanned Aerial Vehicles (UAV)-supported IoT networks. We explored ways to set up a flexible communication architecture that can handle large IoT deployments by making good use of mobile core network resources like bearers and data paths. We developed strategies that meet the needs of IoT networks and enhance network performance. We also developed and tested a system that combines traffic from several mobile devices that use the same user identity and network resources within the core mobile network. We used everyday smartphones, SIM …

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The Impact Of Social Media On Charitable Giving For Nonprofit Organization, Namchul Shin Jan 2024

The Impact Of Social Media On Charitable Giving For Nonprofit Organization, Namchul Shin

Journal of International Technology and Information Management

Research has extensively studied nonprofit organizations’ use of social media for communications and interactions with supporters. However, there has been limited research examining the impact of social media on charitable giving. This research attempts to address the gap by empirically examining the relationship between the use of social media and charitable giving for nonprofit organizations. We employ a data set of the Nonprofit Times’ top 100 nonprofits ranked by total revenue for the empirical analysis. As measures for social media traction, i.e., how extensively nonprofits draw supporters on their social media sites, we use Facebook Likes, Twitter Followers, and Instagram …

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How Does Digitalisation Transform Business Models In Ropax Ports? A Multi-Site Study Of Port Authorities, Yiran Chen, Anastasia Tsvetkova, Kristel Edelman, Irina Wahlström, Marikka Heikkila, Magnus Hellström Jan 2024

How Does Digitalisation Transform Business Models In Ropax Ports? A Multi-Site Study Of Port Authorities, Yiran Chen, Anastasia Tsvetkova, Kristel Edelman, Irina Wahlström, Marikka Heikkila, Magnus Hellström

Journal of International Technology and Information Management

This article investigates the relationship between digitalisation and business model changes in RoPax ports. The study is based on six RoPax ports in Northern Europe, examining their digitalisation efforts and the resulting changes in their business models, leading to further digital transformation. The paper offers insights by reviewing relevant literature on digitalisation’s role in business model innovation and its application in ports. The findings reveal that digitalisation supports relevant business model changes concerning port operation integration within logistics chains, communication, documentation flow, and cargo flow optimisation. However, exploring digitalisation’s potential for diversifying value propositions is still limited. Most digitalisation efforts …

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Key Issues Of Predictive Analytics Implementation: A Sociotechnical Perspective, Leida Chen, Ravi Nath, Nevina Rocco Jan 2024

Key Issues Of Predictive Analytics Implementation: A Sociotechnical Perspective, Leida Chen, Ravi Nath, Nevina Rocco

Journal of International Technology and Information Management

Developing an effective business analytics function within a company has become a crucial component to an organization’s competitive advantage today. Predictive analytics enables an organization to make proactive, data-driven decisions. While companies are increasing their investments in data and analytics technologies, little research effort has been devoted to understanding how to best convert analytics assets into positive business performance. This issue can be best studied from the socio-technical perspective to gain a holistic understanding of the key factors relevant to implementing predictive analytics. Based upon information from structured interviews with information technology and analytics executives of 11 organizations across the …

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Activities Tailoring Within Agile Scrum Roles: A Case Of Nigerian Healthcare Information Systems Development, Yazidu Salihu, Julian Bass, Gloria Iyawa Jan 2024

Activities Tailoring Within Agile Scrum Roles: A Case Of Nigerian Healthcare Information Systems Development, Yazidu Salihu, Julian Bass, Gloria Iyawa

Journal of International Technology and Information Management

Developing quality agile healthcare information systems requires understanding regulatory compliance and evolving healthcare needs through activities tailored within agile scrum roles. Agile scrum, a widely adopted philosophy, offers significant advantages in managing software development processes. This research explores how activities within the agile scrum roles are tailored to agile healthcare information systems development within the Nigerian context. This study adopted a qualitative case study methodology and interviewed 12 agile practitioners developing healthcare information systems within Nigeria using semi-structured open-ended interview guide questions. The practitioners were selected based on a snowballing process, a sunset of purposive sampling techniques from our network …

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Advancing Household Robotics: Deep Interactive Reinforcement Learning For Efficient Training And Enhanced Performance, Arpita Soni, Sujatha Alla, Suresh Dodda, Hemanth Volikatla Jan 2024

Advancing Household Robotics: Deep Interactive Reinforcement Learning For Efficient Training And Enhanced Performance, Arpita Soni, Sujatha Alla, Suresh Dodda, Hemanth Volikatla

Engineering Management & Systems Engineering Faculty Publications

The market for domestic robots—made to perform household chore, is growing as these robots relieve people of everyday responsibilities. Domestic robots are generally welcomed for their role in easing human labour, in contrast to industrial robots, which are frequently criticised for displacing human workers. But before these robots can carry out domestic chores, they need to become proficient in a number of minor activities, such as recognizing their surroundings, making decisions, and picking up on human behaviours. Reinforcement learning, or RL, has emerged as a key robotics technology that enables robots to interact with their environment and learn how to …

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Navigating Innovation Within A Contractor's Business Model: A System Dynamics Approach, Mariam Elazhary, Cihan Dagli, Islam H. El-Adaway Jan 2024

Navigating Innovation Within A Contractor's Business Model: A System Dynamics Approach, Mariam Elazhary, Cihan Dagli, Islam H. El-Adaway

Engineering Management and Systems Engineering Faculty Research & Creative Works

Innovation is essential in the construction industry, but current practices often focus narrowly on specific aspects rather than taking a comprehensive approach. To address this, systematic innovation through business model innovation (BMI) is proposed to enhance overall performance. Despite increasing interest in BMI research, it remains in its early stages, lacking quantitative analysis of its impact on business model components. This paper develops a framework using system dynamics to assess changes to a construction company's BM when faced with a variety of innovations across various projects. This shall be accomplished by (1) establishing factors and their relationships that define a …

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Large Retail Logistics Warehouse Execution System, Michael Broughton Jan 2024

Large Retail Logistics Warehouse Execution System, Michael Broughton

Graduate Research Theses & Dissertations

In this study, integrated technical solutions designed for large retail logistics (LRL) material handling equipment (MHE) were integrated with advanced technical industry trends to create a warehouse execution/warehouse control system (WES/WCS) distribution center (DC) model. This model was executed using a distributor profitability framework. The resulting process metrics, financial elements, and forecasted financial drivers within the new model were tested against a standard warehouse management system (WMS) DC model without WES or integrated WCS technical solutions. The hypothesis was that using the WES/WCS DC model in automating store functionality would result in superior cost-effective solutions for the P&L/EBITDA lines of …

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Data-Driven Approaches For Achieving Carbon Neutrality: Predictive Models For Reducing Co2 Emissions And Enhancing Industrial Sustainability, Farzana Islam Jan 2024

Data-Driven Approaches For Achieving Carbon Neutrality: Predictive Models For Reducing Co2 Emissions And Enhancing Industrial Sustainability, Farzana Islam

Graduate Theses, Dissertations, and Problem Reports (ETD)

In response to the escalating challenges posed by climate change and industrial inefficiency, this thesis presents a comprehensive investigation aimed at advancing the predictive modeling of global CO2 emissions and enhancing operational efficiency in steel manufacturing through Electric Arc Furnace (EAF) temperature optimization. Leveraging a rich dataset sourced from the World Development Indicators database alongside a meticulously curated dataset specific to EAF operations, our study applies an innovative blend of econometric and machine learning techniques, including Pooled Ordinary Least Squares (Pooled OLS), Random Effects (RE), Fixed Effects (FE), and Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) models. The …

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A Mixed Methods Approach To Evaluation And Modeling Of Ergonomic Stressors Due To Mass Decedent Handling, Vaishakhi Suresh Jan 2024

A Mixed Methods Approach To Evaluation And Modeling Of Ergonomic Stressors Due To Mass Decedent Handling, Vaishakhi Suresh

Graduate Theses, Dissertations, and Problem Reports (ETD)

Work-related injuries, illnesses, and musculoskeletal disorders (MSDs) significantly impact the U.S. healthcare industry, leading to lost working days, high medical costs, and increased turnover rates among healthcare workers (HCWs). Increased physical and mental health risks due to the handling of deceased during COVID-19 pandemic has exacerbated these issues. While the ergonomic risks of patient handling are well-studied, limited research exists on the ergonomic risks of manual handling of the deceased. Therefore, the primary objective of this study was to explore the challenges associated with decedent handling so that effective safety interventions to reduce the risk of injury and mental distress …

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Investigating The Influence Of Container Design And A Bulge Reduction Technique In Corrugated Fiberboard Containers Under Static Compression, Jay Singh, Koushik Saha Jan 2024

Investigating The Influence Of Container Design And A Bulge Reduction Technique In Corrugated Fiberboard Containers Under Static Compression, Jay Singh, Koushik Saha

Industrial Technology and Packaging

This study explored the bulge effect in corrugated fiberboard boxes caused by excessive weight, leading to compromised stacking strength and potential product damage. It investigated how container design, specifically the height variations of regular slotted containers (RSCs), affects bulging under compression and its vulnerability to environmental conditions. Testing met ASTM standards, with samples conditioned according to ASTM and TAPPI protocols, revealing that changes in box height influence bulge displacement. Subsequent research examined the impact of top-to-bottom static compression loads on bulging in tape-reinforced RSC designs, evaluating bulge reduction and compression strength across various tape placements and environments. Notably, previous studies …

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Co-Evolving Multi-Agent Transfer Reinforcement Learning Via Scenario Independent Representation, Ayesha Siddiqua Jan 2024

Co-Evolving Multi-Agent Transfer Reinforcement Learning Via Scenario Independent Representation, Ayesha Siddiqua

Graduate Theses/Dissertations

Multi-Agent Reinforcement Learning (MARL) addresses complex tasks involving cooperation and competition among agents, training them to develop optimal policies for collective goals. However, facilitating simultaneous learning for multiple agents is challenging because the complexity increases rapidly with the number of agents. Current methods encompass a variety of centralized, decentralized, semi-centralized, and hybrid approaches to balance the trade-offs between computational efficiency, scalability, and coordination in MARL. In this study, I employed a centralized training with semi-centralized execution (CTSCE) framework, utilize both local observations from agents and abstracted global observations to effectively train agents in cooperative environments. Additionally, earning complex, domain-specific tasks …

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Automation Of Productive Machinery. Bases For An Innovative Business Model, Carlos Guillermo Hernández-Cenzano, Angel Contreras-Cruz, Eduardo Humada-Tello Jan 2024

Automation Of Productive Machinery. Bases For An Innovative Business Model, Carlos Guillermo Hernández-Cenzano, Angel Contreras-Cruz, Eduardo Humada-Tello

Engineering and Technology Management Faculty Publications and Presentations

Nowadays, some laboratories perform elastic properties tests for concrete or rock cores using equipment manufactured 50 years ago. The original data collection procedure uses analog and manual recordings, which can cause inaccuracies in the measurements taken during these trials The process is tedious and updated since each trial's measurement data is recorded manually. In this context, this study systematizes the process and proposes an automated data acquisition and recording system for this type of equipment, followed by a case study presenting a rock compression test.

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Mouralherwaqh Coastal Wetland Road Crossing Da'luk, Romel Robinson Ii Jan 2024

Mouralherwaqh Coastal Wetland Road Crossing Da'luk, Romel Robinson Ii

Cal Poly Humboldt theses and projects

The integration of Indigenous and Western science plays an essential role in Tribally led collaborations for land management. This process of woven sciences is rooted in reciprocal relations and partnerships guided by Tribal Nations. Our cohort was invited by Wiyot Tribal Representatives to investigate a culvert located within the wetlands of Mouralherwaqh— a parcel of land reacquired by the Wiyot Tribe in 2022. This document seeks to share our experience and analysis as part of the Wiyot Tribe’s broader journey in navigating ecocultural restoration projects within Mouralherwaqh. The four community interests we investigated for the wetland crossing included a resized …

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What Can We Learn From A Co-Creation Journey For A Quick Scan Digital Transformation Maturity Assessment Tool For Development Ngos?, Anand Sheombar Jan 2024

What Can We Learn From A Co-Creation Journey For A Quick Scan Digital Transformation Maturity Assessment Tool For Development Ngos?, Anand Sheombar

Journal of International Technology and Information Management

This paper describes the approach and lessons learned from a co-creation process with Dutch development NGOs to create a practical and easy-to-use assessment tool for practitioners to assess the organisation's maturity level of digital transformation. For this study, we applied a design science research methodology, specifically a six-step co-creation approach suitable for developing maturity models. The digital maturity assessment tool (quick scan) created is a domain- specific digital transformation maturity tool for development NGOs rather than a generally applicable tool. This artefact was evaluated using an eight-point Requirements framework for the development of digital maturity assessment tools. By developing a …

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Prediction Of Anomalous Events With Data Augmentation And Hybrid Deep Learning Approach, Ahmed Shoyeb Raihan Jan 2024

Prediction Of Anomalous Events With Data Augmentation And Hybrid Deep Learning Approach, Ahmed Shoyeb Raihan

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this study, we propose a novel anomaly detection framework designed specifically for Multivariate Time Series (MTS) data, addressing the prevalent challenges in analyzing such complex datasets. The detection of anomalies within MTS data is notably difficult due to the complex interplay of numerous variables, temporal dependencies, and the common issue of class imbalance, where one category significantly outnumbers another. Traditional deep learning (DL) approaches often fall short in simultaneously tackling these issues. Our framework is designed to address these challenges through a two-phased approach. Phase I employs Conditional Tabular Generative Adversarial Networks (CTGAN) to create strategic synthetic data, setting …

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