Product Specification: Distributed Trust Model System (Doe-Psu-0000922-4), 2024 Portland State University
Product Specification: Distributed Trust Model System (Doe-Psu-0000922-4), Narmada Sonali Fernando, Abdullah Barghouti, Robert B. Bass, John M. Acken
Electrical and Computer Engineering Faculty Publications and Presentations
A Distributed Trust Model (DTM) System is a supervisory component within an energy grid of things. The role of a DTM System is to implement the trust aspects of an energy services interface. The DTM System augments existing security measures by monitoring the communication between the various EGoT System actors and quantifying metrics of trust of each actor.
Product Specification: Distributed Control Module (Doe-Psu-0000922-5), 2024 Portland State University
Product Specification: Distributed Control Module (Doe-Psu-0000922-5), Nicole Henderson, Kai Zeng, Robert B. Bass
Electrical and Computer Engineering Faculty Publications and Presentations
This product specification describes the architecture, implementation, and hardware descriptions of a Distributed Control Module (DCM) prototype. A DCM is an enabling technology for distributed energy resources (DER). DERs are grid-enabled generation, storage, and load devices that are owned by utility customers. DCMs enable information exchange between a distributed energy resource management system (DERMS) and DERs for the purpose of networking large numbers of DERs. The DCM prototype described within this document enables DER participation in a service-oriented aggregation system. A DERMS server provides IEEE 2030.5 smart energy resource services to DCM clients using a request/response information exchange process. DCMs …
Energy Services Interface (Doe-Psu-0000922-1), 2024 Portland State University
Energy Services Interface (Doe-Psu-0000922-1), Robert B. Bass
Electrical and Computer Engineering Faculty Publications and Presentations
This document defines a set of rules known as the Energy Services Interface (ESI), which “establish a bi-directional, service-oriented, logical interface to support secure, trustworthy information exchange between an aggregator and distributed energy resources (DERs). These exchanges facilitate energy interactions between the DERs and the aggregator, thereby allowing the aggregator to provide grid services through dispatch of the DERs.” The ESI serves as an umbrella, ensuring the information exchange between an aggregator and DER owners conforms to expectations: protect privacy, provide security, develop trustworthiness, and ensure interoperability. DERMS developers use the ESI to ensure that information exchange meets these expectations.
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, 2024 University of Kentucky
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi
Theses and Dissertations--Electrical and Computer Engineering
The long-standing technological pillars for computing systems evolution, namely Moore's law and Von Neumann architecture, are breaking down under the pressure of meeting the capacity and energy efficiency demands of computing and communication architectures that are designed to process modern data-centric applications related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In response, both industry and academia have turned to 'more-than-Moore' technologies for realizing hardware architectures for communication and computing. Fortunately, Silicon Photonics (SiPh) has emerged as one highly promising ‘more-than-Moore’ technology. Recent progress has enabled SiPh-based interconnects to outperform traditional electrical interconnects, offering advantages like high bandwidth density, …
Tutorial: Knowledge-Infused Artificial Intelligence For Mental Healthcare, 2024 University of South Carolina - Columbia
Tutorial: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy
Publications
Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …
Nonuniform Sampling-Based Breast Cancer Classification, 2024 University of Kentucky
Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso
Theses and Dissertations--Electrical and Computer Engineering
The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …
Disaggregating Longer-Term Trends From Seasonal Variations In Measured Pv System Performance, 2024 Technological University Dublin
Disaggregating Longer-Term Trends From Seasonal Variations In Measured Pv System Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon
Articles
Photovoltaic (PV) systems are widely adopted for renewable energy generation, but their performance is influenced by complex interactions between longer-term trends and seasonal variations. This study aims to remove these factors and provide valuable insights for optimising PV system operation. We employ comprehensive datasets of measured PV system performance over five years, focusing on identifying the distinct contributions of longer-term trends and seasonal effects. To achieve this, we develop a novel analytical framework that combines time series and statistical analytical techniques. By applying this framework to the extensive performance data, we successfully break down the overall PV system output into …
Enhancing Grid Reliability With Coordination And Control Of Distributed Energy Resources, 2024 University of Vermont
Enhancing Grid Reliability With Coordination And Control Of Distributed Energy Resources, Hani Mavalizadeh
Graduate College Dissertations and Theses
The growing utilization of renewable energy resources (RES) within power systems has brought about new challenges due to the inherent uncertainty associated with RES, which makes it challenging to accurately forecast available generation. Further- more, the replacement of synchronous machines with inverter-based RES results in a reduction of power system inertia, complicating the task of maintaining a balance between generation and consumption. In this dissertation, coordinating Distributed Energy Resources (DER) is presented as a viable solution to these challenges.DERs have the potential to offer different ancillary services such as fast frequency response (FFR) when efficiently coordinated. However, the practical implementation …
A Survey On Few-Shot Class-Incremental Learning, 2024 University of Chinese Academy of Sciences
A Survey On Few-Shot Class-Incremental Learning, Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Xin Ning, Prayag Tiwari
Computer Science Faculty Publications
Large deep learning models are impressive, but they struggle when real-time data is not available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for deep neural networks to learn new tasks from just a few labeled samples without forgetting the previously learned ones. This setup can easily leads to catastrophic forgetting and overfitting problems, severely affecting model performance. Studying FSCIL helps overcome deep learning model limitations on data volume and acquisition time, while improving practicality and adaptability of machine learning models. This paper provides a comprehensive survey on FSCIL. Unlike previous surveys, we aim to synthesize few-shot learning and incremental …
Structured Invariant Subspace And Decomposition Of Systems With Time Delays And Uncertainties, 2024 Southern Illinois University Edwardsville
Structured Invariant Subspace And Decomposition Of Systems With Time Delays And Uncertainties, Huan Phan-Van, Keqin Gu
SIUE Faculty Research, Scholarship, and Creative Activity
This article discusses invariant subspaces of a matrix with a given partition structure. The existence of a nontrivial structured invariant subspace is equivalent to the possibility of decomposing the associated system with multiple feedback blocks such that the feedback operators are subject to a given constraint. The formulation is especially useful in the stability analysis of time-delay systems using the Lyapunov-Krasovskii functional approach where computational efficiency is essential in order to achieve accuracy for large scale systems. The set of all structured invariant subspaces are obtained (thus all possible decompositions are obtained as a result) for the coupled differential-difference equations …
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, 2024 Virginia Commonwealth University
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber
Theses and Dissertations
As cyber-physical systems (CPS) become more integrated into everyday life, the security of these systems must also be considered during their development due to their ever-increasing importance. With the growth of physical components in the system, more autonomous control requirements, and increased dependence on proper functionality, verifying system safety and correct operation becomes increasingly difficult. CPS have become more complex through the combination of additional hardware and the resulting interconnected software in many layers, each requiring unique security solutions. One example of such a safety-critical CPS embedded system is the Flight Control System (FCS) of an Unmanned Aerial System (UAS). …
Moisture-Controlled Triboelectrification During Coffee Grinding, 2024 Portland State University
Moisture-Controlled Triboelectrification During Coffee Grinding, Joshua Méndez Harper, Yong-Hyun Kim, Robin E. Bumbaugh, Connor S. Mcdonald, Christopher H. Hendon, Elana J. Cope, Leif E. Lindberg, Justin Pham, Multiple Additional Authors
Electrical and Computer Engineering Faculty Publications and Presentations
Triboelectrification is the physical process where materials acquire surface charge from frictional interactions at their interfaces.The magnitude of charge depends on the interfacial material composition and can be harnessed in emergent technologies for energy generation.
The mechanism of electrostatic accumulation is complex and is further obscured in granular materials where collisions are sufficiently energetic to cause fracturing. In this “fractoelectric” regime, crack initiation and propagation are thought to charge particles through transfer of electrons and/or ions at the hot crack interface.
Whether a material’s charging is dominated by tribo- or fractoelectrification, fracture-generated granular flows often comprise particles whose surface charge …
Psu Esi Review (Doe-Psu-0000922-6), 2024 Pacific Northwest National Laboratory
Psu Esi Review (Doe-Psu-0000922-6), Tylor Slay, Jaime Kolln, Robert B. Bass
Electrical and Computer Engineering Faculty Publications and Presentations
A guide to developing an Energy Service Interface (ESI) was created as part of the Grid Modernization Laboratory Consortium 2.5.2 ESI project. The approach applies device-agnostic and service-oriented ESI principles and leverages documents such as the Interoperability Maturity Model and Common Grid Service Definitions to provide a methodology to review, develop, and update standards and profiles to engage distributed energy resources to provide grid services. This document evaluates the ESI developed by Portland State University’s Power Engineering Group under the Electric Grid of Things project funded by the U.S. Department of Energy. The evaluation explores the compliance of this specific …
Modeling And Analysis Methods For Esd And Emi Problems, 2024 Missouri University of Science and Technology
Modeling And Analysis Methods For Esd And Emi Problems, Xin Yan
Doctoral Dissertations
"Electrostatic discharge (ESD) failures and Electromagnetic interference (EMI) problems are becoming more critical in electronic devices and large systems. In this work, four studies are presented to model and analyze ESD and EMI problems.
First, a simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed. While based on physics, the number of parameters and components is minimized. Results show that the proposed model captures the most important behaviors of the TVS response using a limited number of parameters, allowing the model to be tuned relatively easily using data obtained only from package-level transient and quasi-static measurements. Second, a …
Control And Optimization Of Energy Storage System In Power Distribution System, 2024 Missouri University of Science and Technology
Control And Optimization Of Energy Storage System In Power Distribution System, Waqas Ur Rehman
Doctoral Dissertations
"The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, …
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, 2024 Edith Cowan University
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia
Research outputs 2022 to 2026
Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …
An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, 2024 Air Force Institute of Technology
An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, Jeffrey Choate, Derek Worth, Scott Nykl, Clark N. Taylor, Brett J. Borghetti, Christine M. Schubert Kabban
Faculty Publications
Achieving precise 6 degrees of freedom (6D) pose estimation of rigid objects from color images is a critical challenge with wide-ranging applications in robotics and close-contact aircraft operations. This study investigates key techniques in the application of YOLOv5 object detection convolutional neural network (CNN) for 6D pose localization of aircraft using only color imagery. Traditional object detection labeling methods suffer from inaccuracies due to perspective geometry and being limited to visible key points. This research demonstrates that with precise labeling, a CNN can predict object features with near-pixel accuracy, effectively learning the distinct appearance of the object due to perspective …
Designing High-Performance Identity-Based Quantum Signature Protocol With Strong Security, 2024 Central University of Himachal Pradesh
Designing High-Performance Identity-Based Quantum Signature Protocol With Strong Security, Sunil Prajapat, Pankaj Kumar, Sandeep Kumar, Ashok Kumar Das, Sachin Shetty, M. Shamim Hossain
VMASC Publications
Due to the rapid advancement of quantum computers, there has been a furious race for quantum technologies in academia and industry. Quantum cryptography is an important tool for achieving security services during quantum communication. Designated verifier signature, a variant of quantum cryptography, is very useful in applications like the Internet of Things (IoT) and auctions. An identity-based quantum-designated verifier signature (QDVS) scheme is suggested in this work. Our protocol features security attributes like eavesdropping, non-repudiation, designated verification, and hiding sources attacks. Additionally, it is protected from attacks on forgery, inter-resending, and impersonation. The proposed scheme benefits from the traditional designated …
K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, 2024 University of South Carolina - Columbia
K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur
Publications
Personalizing conversational agents can enhance the quality of conversations and increase user engagement. However, they often lack external knowledge to tend to a user’s persona appropriately. This is particularly crucial for practical applications like mental health support, nutrition planning, culturally sensitive conversations, or reducing toxic behavior in conversational agents. To enhance the relevance and comprehensiveness of personalized responses, we propose using a two-step approach that involves (1) selectively integrating user personas and (2) contextualizing the response with supplementing information from a background knowledge source. We develop K-PERM (Knowledge-guided PErsonalization with Reward Modulation), a dynamic conversational agent that combines these elements. …
Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, 2024 University of South Carolina - Columbia
Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth
Publications
Despite their wide applications to language understanding tasks, large language models (LLMs) still face challenges such as hallucinations - the occasional fabrication of information, and alignment issues - the lack of associations with human-curated world models (e.g., intuitive physics or common-sense knowledge). Additionally, the black-box nature of LLMs makes it highly challenging to train them meaningfully in order to achieve a desired behavior. Specifically, the attempt to adjust LLMs’ concept embedding spaces can be highly intractable, which involves analyzing the implicit impact on LLMs’ numerous parameters and the resulting inductive biases. This paper proposes a novel architecture that wraps powerful …