Article
Energy & Fuels
Li He, Yuanzhi Liu, Jie Zhang
Summary: This study introduces a peer-to-peer energy trading framework where interactions among the EP, prosumers, and consumers are optimized to achieve mutual benefits. Through a hierarchical approach, the framework allows for efficient management of energy sharing markets to balance supply and demand.
Article
Energy & Fuels
Mohammad Kazem Salehi, Mohammad Rastegar
Summary: This paper proposes an optimal energy management model in a transactive energy framework based on a distributed optimization mechanism. The proposed model utilizes cloud energy storage technology to support residential consumers in energy trading, reducing costs and energy demand. Simulation results demonstrate the effectiveness of the model, highlighting its importance in applications for residential users, cloud energy storage, and the grid.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Computer Science, Information Systems
Arkan Hammoodi Hasan Kabla, Mohammed Anbar, Selvakumar Manickam, Alwan Ahmed Abdulrahman Alwan, Shankar Karuppayah
Summary: The paper provides an overview of P2P botnets, explores existing monitoring approaches, and categorizes them into passive, active, and hybrid monitoring. It also discusses the functional and non-functional requirements of advanced monitoring and identifies the challenges in monitoring P2P botnets, proposing future avenues for improvement.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Engineering, Electrical & Electronic
Wei Zhou, Yuying Wang, Feixiang Peng, Ying Liu, Hui Sun, Yu Cong
Summary: In the deregulated energy market environment, small-scale peer-to-peer (P2P) energy trading can increase distributed photovoltaic power generation consumption and promote local energy balance. However, it also raises the risk of security constraints violations during the utility grid operation. To address physical network congestion caused by distributed P2P energy trading, a method based on a continuous double auction mechanism is proposed, along with a two-tier market coordination mechanism to utilize user flexibility.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Ambar Tenorio-Fornes, Samer Hassan, Juan Pavon
Summary: This paper presents guidelines for designing decentralized systems, illustrated through the design of a decentralized questions and answers system, providing a framework for creating decentralized services and applications using IPFS and Blockchain technologies.
APPLIED SCIENCES-BASEL
(2021)
Article
Automation & Control Systems
Md Habib Ullah, Jae-Do Park
Summary: This article presents a novel two-tier peer-to-peer market paradigm for energy sharing between multiregional proactive prosumers. The proposed approach uses distributed market-clearing methods to protect prosumers' privacy and significantly increase their economic benefits. The effectiveness of the approach is validated through software simulations.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Energy & Fuels
Mirza Jabbar Aziz Baig, M. Tariq Iqbal, Mohsin Jamil, Jahangir Khan
Summary: This paper presents a low-cost, open-source peer-to-peer energy trading system designed for a remote community to utilize distributed energy resources. The system utilizes a Raspberry Pi main server, an Ethereum blockchain server, and IoT microcontrollers for trading and data monitoring. Multiple security measures are implemented to ensure system and information security.
Article
Engineering, Electrical & Electronic
Mohsen Khorasany, Ali Dorri, Reza Razzaghi, Raja Jurdak
Summary: P2P energy trading in smart grids presents challenges in decentralized management, market settlement, and grid constraints. This paper proposes a blockchain-enabled framework for energy trading among agents, considering reputation factors and electrical distance.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Alberto Morato, Stefano Vitturi, Federico Tramarin, Angelo Cenedese
Summary: The industrial Internet of Things (IIoT) provides opportunities for new generation measurement applications but requires solutions for interoperability between communication systems and sensors. The open platform communications (OPC) unified architecture (UA) protocol is considered a suitable solution, but its performance needs to be evaluated.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Economics
Berno Buechel, Philemon Krahenmann
Summary: This article introduces online platforms for peer-to-peer exchange and their fixed prices, analyzes the inherent inefficiency of fixed prices and voluntary trade, discusses the potential advantages of price restrictions, and verifies theoretical insights through empirical examples.
JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION
(2022)
Article
Chemistry, Multidisciplinary
Qinglong Dai, Jin Qian, Guangjun Qin, Jianwu Li, Jun Zhao
Summary: This paper investigates the resource management issue in the tactile internet and proposes an offloading solution. The superiority of the proposed method is demonstrated through numerical simulations.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Haoran Ji, Jie Jian, Hao Yu, Jie Ji, Mingjiang Wei, Xinmin Zhang, Peng Li, Jinyue Yan, Chengshan Wang
Summary: This article proposes a DLT-based P2P electricity trading method based on intelligent SOP regulation, which allows multiple regions interconnected by soft open points to flexibly exchange power to alleviate power imbalance. Smart contracts and distributed ledger technology ensure the credibility of transactions.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Homa Rashidizadeh-Kermani, Mostafa Vahedipour-Dahraie, Miadreza Shafie-khah, Pierluigi Siano
Summary: This paper presents a risk-averse stochastic framework for managing the participation of virtual associations (VAs) in the day-ahead electricity market, with the main goal of optimizing VA decision-making to maximize VA profit and minimize total energy costs for prosumers, while also considering the impacts of P2P trading.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Automation & Control Systems
Mingming Mao, Junjun Xu, Zaijun Wu, Qinran Hu, Xiaobo Dou
Summary: This article proposes a novel multiarea architecture to address the increasing computational tasks in state estimation (SE) method for large-scale distribution networks. The proposed method introduces an innovative multiarea state estimation (MASE) model that combines microphasor measurement units (mu PMU) and conventional supervisory control and data acquisition (SCADA) systems, considering both coordinate tensions and synchronization issues. The hybrid state estimation (HSE) model is solved in a distributed way, with minimal data exchanges among neighbor subareas. Case studies demonstrate the accuracy and efficiency improvements of the proposed MASE method compared to existing ones.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Jing Li, Yujian Ye, Dimitrios Papadaskalopoulos, Goran Strbac
Summary: This article proposes two computationally efficient mechanisms to construct a stable grand coalition of prosumers participating in P2P energy trading. Through numerous case studies using real-world data, the proposed mechanisms exhibit superior computational performance and incentivize prosumers to remain in the grand coalition.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Ghane Zandi, Hoda Roodaki, Shervin Shirmohammadi
Summary: This paper proposes a method for fast disparity estimation in multiview/3D video, which reduces computational complexity and achieves better performance in terms of bitrate and quality.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Review
Computer Science, Information Systems
Mohammad Kazemi, Mohammad Ghanbari, Shervin Shirmohammadi
Summary: This article reviews temporal video error concealment methods developed over the past 30 years, categorizing them into 8 groups with detailed discussions on their strengths and weaknesses. Suggestions for future work and open areas for research are also provided.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Shervin Shirmohammadi, Luca Mari, Dario Petri
Summary: The majority of search results on accuracy and precision use misleading visuals, with correct ones appearing lower down the rankings. Incorrect visuals are often found in non-peer-reviewed documents, warning against blindly trusting everything found on the internet.
IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE
(2021)
Editorial Material
Engineering, Electrical & Electronic
Shervin Shirmohammadi
IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE
(2021)
Article
Engineering, Electrical & Electronic
Shervin Shirmohammadi, Hussein Al Osman
Summary: Instrumentation and Measurement (I&M) and Machine Learning (ML) are two fields that are currently experiencing the impact of the rise of Applied AI. While terminology used in both fields may sound or look similar, it is important to understand the differences in order to fully grasp the influence of ML in an I&M system. Additionally, the importance of measurement uncertainty is well-known in I&M, but has been under-studied in the context of ML.
IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE
(2021)
Article
Computer Science, Information Systems
Boon-Yaik Ooi, Woan-Lin Beh, Xin-Yi Kh'ng, Soung-Yue Liew, Shervin Shirmohammadi
Summary: This paper proposes the construction of a low-cost wireless vibration sensor using a 3-axis accelerometer and Wi-Fi microchip, and solves the inaccuracy issue of the direct-read-and-send method through compressive sampling technique, enabling the sensor to continuously and efficiently measure vibration data in an IoT environment.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Majid Ghosian Moghaddam, Ali Asghar Nazari Shirehjini, Shervin Shirmohammadi
Summary: In this article, a novel method combining channel state information (CSI) and received signal strength indicator (RSSI) signals is proposed to improve the performance of device-free fine-grained human activity recognition (HAR) using WiFi data. The method is evaluated using a dataset of 12 human-to-human fine-grained interactions and various classification methods. The results show that the method achieves high accuracy, precision, recall, F1-score, k-score, and area under the curve (AUC) in the recognition of seven human-to-human interactions using random forest (RF).
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Liansheng Liu, Zhuo Zhi, Yufei Yang, Shervin Shirmohammadi, Datong Liu
Summary: The condition of the harmonic reducer is important for the availability of industrial robots. A fault detection method utilizing the acoustic emission (AE) signal is proposed, consisting of two unique algorithms. This method effectively reduces noise and achieves fault detection through feature extraction and signal optimization.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Hardware & Architecture
Xinjue Hu, Chenchen Wang, Lin Zhang, Guo Chen, Shervin Shirmohammadi
Summary: The Light field (LF) is a technique that describes the light rays emitted at each point in a scene, and it can be used for six-degrees-of-freedom (6DOF) immersive media. Similar to multiview video, LF is captured by an array of cameras, resulting in a large data volume that needs to be streamed to users. Rendering virtual viewpoints in real-time from the directly captured viewpoints places high demands on computing and caching capabilities. Edge computing (EC) brings computation resources closer to users and can enable real-time LF viewpoint rendering.
Article
Computer Science, Information Systems
Xinjue Hu, Yuxuan Pan, Yumei Wang, Lin Zhang, Shervin Shirmohammadi
Summary: This paper proposes a dynamic adaptive LF video transmission scheme that achieves high compression and near-distortion-free LF video under stable network conditions. It also introduces a description scheduling algorithm for unstable network conditions, which can decode the LF video with the highest quality even with partial and/or delayed data. Experimental results show that the scheduling algorithm improves decoding quality by 3% to 15%. Compared with similar schemes, our system greatly improves the reliability of the video streaming system against packet loss/error and supports heterogeneous receivers.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Computer Science, Information Systems
Sa'di Altamimi, Basel Altamimi, David Cote, Shervin Shirmohammadi
Summary: Today's Network Operation Centres (NOC) are responsible for monitoring and maintaining the health of networks. As networks become larger and more complex, it has become necessary to automate some or all NOC tasks for efficiency. This article investigates the possibility of achieving superintelligence in an autonomous NOC using reinforcement learning, showing that it can outperform human-designed expert rules and improve network recovery.
Article
Engineering, Electrical & Electronic
Jana Rusrus, Shervin Shirmohammadi, Martin Bouchard
Summary: This article evaluates the performance of a deep learning classification system for localizing moving sound sources and investigates the impact of key parameters in feature extraction and model training. The results show that window size has a significant effect on the performance of moving sources but not static sources, sequence length affects the performance of recurrent architectures, and a temporal convolutional neural network outperforms recurrent and feedforward networks for moving sound sources.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Information Systems
Sanaz Nami, Farhad Pakdaman, Mahmoud Reza Hashemi, Shervin Shirmohammadi
Summary: This paper proposes a Block-Level Just Noticeable Distortion-based Perceptual (BL-JUNIPER) framework for video coding, which combines different perceptual information to improve prediction accuracy. By adjusting the quantization parameter based on JND levels and visual importance, better compression performance can be achieved.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Engineering, Electrical & Electronic
Hossein Ebrahimi Dinaki, Shervin Shirmohammadi, Emil Janulewicz, David Cote
Summary: This research proposes a method for predicting QoE for networked video service providers using deep learning technique BiLSTM-CNN. The method aims to proactively address service delivery issues by accurately forecasting user experience quality (QoE).
IEEE OPEN JOURNAL OF SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Ayse Rumeysa Mohammed, Shady A. Mohammed, David Cote, Shervin Shirmohammadi
Summary: The article proposes a machine learning method for automatically detecting network status and localizing faults, achieving accuracies of up to 99% on a dataset collected through an emulated network. This method outperforms existing works in classifying network status between normal, congestion, and network fault.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)