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Product Specification: Distributed Trust Model System (Doe-Psu-0000922-4), Narmada Sonali Fernando, Abdullah Barghouti, Robert B. Bass, John M. Acken 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.


Implementation Profile: Modeling Environment (Doe-Psu-0000922-3), Sean Keene, Midrar Adham, Robert B. Bass 2024 Portland State University

Implementation Profile: Modeling Environment (Doe-Psu-0000922-3), Sean Keene, Midrar Adham, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

This implementation profile provides the scope, background, and requirements necessary to implement a Modeling Environment (ME) to test a Distributed Energy Resource (DER) Management System (DERMS). A DERMS is used by an aggregator to dispatch large numbers of DERs in order to provide grid services to a Grid Operator. The ME addresses scalability issues inherent to Hardware-in-the-Loop DERMS simulation; a large number of assets are needed in order to observe effects on the grid from deployment and dispatch of DERs.


Product Specification: Distributed Control Module (Doe-Psu-0000922-5), Nicole Henderson, Kai Zeng, Robert B. Bass 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 …


Psu Derms Operating Manual And Egot System Reference (Doe-Psu-0000922-7), Tylor Slay, Robert B. Bass 2024 Pacific Northwest National Laboratory

Psu Derms Operating Manual And Egot System Reference (Doe-Psu-0000922-7), Tylor Slay, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

This document guides the user of the Portland State University Distributed Energy Resource Management System in configuration and normal operation. For direct access to the underlying code and its usage see the accompanying PSU EGoT System Reference. The system reference outlines all classes and methods used through the Energy Grid of Things system including applications, models, interfaces and the entity component system.


External Direct Sum Invariant Subspace And Decomposition Of Coupled Differential-Difference Equations, Keqin Gu, Huan Phan-Van 2024 Southern Illinois University Edwardsville

External Direct Sum Invariant Subspace And Decomposition Of Coupled Differential-Difference Equations, Keqin Gu, Huan Phan-Van

SIUE Faculty Research, Scholarship, and Creative Activity

This article discusses the invariant subspaces that are restricted to be external direct sums. Some existence conditions are presented that facilitate finding such invariant subspaces. This problem is related to the decomposition of coupled differential-difference equations, leading to the possibility of lowering the dimensions of coupled differential-difference equations. As has been well documented, lowering the dimension of coupled differential-difference equations can drastically reduce the computational time needed in stability analysis when a complete quadratic Lyapunov-Krasovskii functional is used. Most known ad hoc methods of reducing the order are special cases of this formulation.


Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi 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, …


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 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 …


Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso 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 …


Ultra-Fast Annealing Improves Snr And Long-Term Stability Of A Highly Multiplexed Line-By-Line Fbg Array Inscribed By Femtosecond Laser In A Coreless Fiber For Extreme-Temperature Applications, Farhan Mumtaz, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang 2024 Missouri University of Science and Technology

Ultra-Fast Annealing Improves Snr And Long-Term Stability Of A Highly Multiplexed Line-By-Line Fbg Array Inscribed By Femtosecond Laser In A Coreless Fiber For Extreme-Temperature Applications, Farhan Mumtaz, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This study reports the fabrication of an 4th-order line-by-line Fiber Bragg Gratings (FBG) array using femtosecond laser inscription within a highly multimode coreless optical fiber, with a particular focus on achieving substantial multiplexing capabilities. An ultra-fast annealing procedure is employed, resulting in an impressive enhancement of the FBG sensor's fringe visibility by approximately 13 dB, signifying a notable improvement of approximately ~4 dB. This substantial enhancement contributes to the long-term stability and performance of the multiplexed FBG array in extreme temperature conditions. The systematic fabrication approach employed for the multiplexed FBG array guarantees a high signal-to-noise ratio (SNR) for each …


Disaggregating Longer-Term Trends From Seasonal Variations In Measured Pv System Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon 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, Hani Mavalizadeh 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, Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Xin Ning, Prayag Tiwari 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 …


Photoluminescence Switching In Quantum Dots Connected With Fluorinated And Hydrogenated Photochromic Molecules, Ephraiem S. Sarabamoun, Jonathan M. Bietsch, Pramod Aryal, Amelia G. Reid, Maurice Curran, Grayson Johnson, Esther H. R. Tsai, Charles W. Machan, Guijun Wang, Joshua J. Choi 2024 University of Virginia

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

Chemistry & Biochemistry Faculty Publications

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


Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber 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). …


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 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 …


Tutorial: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy 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, …


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 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, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth 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 …


Causal Event Graph-Guided Language-Based Spatiotemporal Question Answering, Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit Sheth 2024 University of South Carolina - Columbia

Causal Event Graph-Guided Language-Based Spatiotemporal Question Answering, Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit Sheth

Publications

Large Language Models have excelled at encoding and leveraging language patterns in large text-based corpora for various tasks, including spatiotemporal event-based question answering (QA). However, due to encoding a text-based projection of the world, they have also been shown to lack a fullbodied understanding of such events, e.g., a sense of intuitive physics, and cause-and-effect relationships among events. In this work, we propose using causal event graphs (CEGs) to enhance language understanding of spatiotemporal events in language models, using a novel approach that also provides proofs for the model’s capture of the CEGs. A CEG consists of events denoted by …


A Wavegan Approach For Mmwave-Based Fanet Topology Optimization, Enas Odat, Hakim Ghazzai, Ahmad Alsharoa 2024 Missouri University of Science and Technology

A Wavegan Approach For Mmwave-Based Fanet Topology Optimization, Enas Odat, Hakim Ghazzai, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

The integration of dynamic Flying Ad hoc Networks (FANETs) and millimeter Wave (mmWave) technology can offer a promising solution for numerous data-intensive applications, as it enables the establishment of a robust flying infrastructure with significant data transmission capabilities. However, to enable effective mmWave communication within this dynamic network, it is essential to precisely align the steerable antennas mounted on Unmanned Aerial Vehicles (UAVs) with their corresponding peer units. Therefore, it is important to design a novel approach that can quickly determine an optimized alignment and network topology. In this paper, we propose a Generative Adversarial Network (GAN)-based approach, called WaveGAN, …


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