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2024 IEEE URUCON, URUCON 2024

作者： Barragán, Diana Estefanía Chérrez Acurio, Byron Alejandro Acuña López, Juan Morais, Hugo Guzman, Cindy P. Silva, Luiz Universidade Estadual de Campinas School of Electrical Engineering SP Campinas Brazil Eemcs University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Enschede Netherlands Instituto Superior Técnico-IST Universidade de Lisboa INESC-ID Department of Electrical and Computer Engineering Lisboa Portugal

ISBN: (纸本)9798350355383

Forecasting algorithms for photovoltaic (PV) power generation play an important role in energy management systems. Nevertheless, the precision of machine learning models is significantly compromised when historical data is limited. This situation is challenging for new plants for which a long history of measurements is not yet available. The unpredictable nature of the weather gives the perception that a competitive forecast requires a substantial amount of data and a very complicated algorithm. However, in this manuscript, it was found that using five historical days for the inverse quantification of uncertainty, can implicitly describe complex non-linear relationships between last five-day records and day-ahead PV power generation. The proposed approach learns the emerging patterns across various seasons throughout the year without relying on exogenous data such as air temperature, wind speed, pressure, cloud cover, and relative humidity. Results using real-world data collected at the microgrid of the University of Campinas (UNICAMP) confirm that our proposed model outperforms previous state-of-the-art deep learning models as Long short-term memory (LSTM), Gated Recurrent Unit (GRU) and traditional Autoregressive Integrated Moving Average (ARIMA) statistical model, using limited data. The proposed approach is flexible and can be easily adapted to other PV power generation systems with limited data. The source code is available at https://***/byronacunia/***. © 2024 IEEE.

关键词： Adaptive learning forecasting photovoltaic statistical approach

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Digital Investigation Forensic Model with P2P Timestamp Blockchain for Monitoring and Analysis

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Journal of electrical Systems 2024年第1期20卷 9-17页

作者： Almahadeen, Layth Pecho, Renzon Daniel Cosme Raj, Murugananth Gopal Rajesh, Nichenametla Imneef, Zainab Mohammed Yelpale, Sayali Karmode Department of Financial and Administrative Sciences Al- Balqa' Applied University Jordan Department of Biochemistry Universidad San Ignacio de Loyola Lima Peru Department of Electrical and Electronics Engineering Ahalia School of Engineering and Technology Kerala India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh India Department of Dentistry Al-Zahrawi University College Karbala Iraq Department of Information Technology MGM College of Engineering Maharashtra India

Forensic analysis of Blockchain data is a new field in police work. It's now one of the largest problems facing law enforcement. The paper discussed the worldwide need for digital forensics in law enforcement and Blockchain forensics to counteract crimes committed using Blockchain technology. It's been said that we've entered a new age of technology that's heavily dependent on the principles of Blockchain. The research produced a set of guidelines for Digital Investigators. on addition, a theoretical framework grounded on the concept of regular activity has been developed, and a legislative framework has been proposed to ensure that its illegal purpose will always be punished severely. © JES 2024 on-line: ***

关键词： Digital forensics

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Semantic and spatial‐spectral feature fusion transformer network for the classification of hyperspectral image

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1308-1322页

作者： Erxin Xie Na Chen Jiangtao Peng Weiwei Sun Qian Du Xinge You Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhanChina Department of Geography and Spatial Information Techniques Ningbo UniversityNingboChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhanChina

Recently,transformer‐based networks have been introduced for the classification of hyperspectral image(HSI).Although transformer‐based methods can well capture spectral sequence information,their ability to fuse different types of information contained in HSI is still *** exploit rich spectral,spatial and semantic information in HSI,a novel semantic and spatial‐spectral feature fusion transformer(S3FFT)network is proposed in this *** the proposed S3FFT method,spatial attention and efficient channel attention(ECA)modules are employed for the extraction of shallow spatialspectral ***,a transformer‐based module is designed to extract advanced fused features and to produce the pseudo‐label and class probability of each pixel for semantic feature ***,the semantic,spatial and spectral features are combined by the transformer for *** with traditional deep learning methods and recently transformer‐based methods,the proposed S3FFT shows relatively better results on three HSI datasets.

关键词： image classification machine learning

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Development of Character Recognition Model Inspired by Visual Explanations

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第3期5卷 1362-1372页

作者： Ralekar, Chetan Choudhary, Shubham Gandhi, Tapan Kumar Chaudhury, Santanu Department of Brain and Cognitive Sciences Massachusetts Institute of Technology CambridgeMA02139 United States Harvard John A. Paulson School of Engineering and Applied Sciences CambridgeMA02138 United States Department of Electrical Engineering Indian Institute of Technology New Delhi110016 India Department of Computer Science and Engineering Indian Institute of Technology Jodhpur342030 India

Deep neural networks (DNNs) currently constitute the best-performing artificial vision systems. However, humans are still better at recognizing many characters, especially distorted, ornamental, or calligraphic characters compared with the highly sophisticated recognitionmodels. Understanding themechanism of character recognition by humans may give some cues for building better recognition models. However, the appropriate methodological approach to using these cues has not been much explored for developing character recognition models. Therefore, this paper tries to understand the process of character recognition by humans and DNNs by generating visual explanations for their respective decisions. We have used eye tracking to assay the spatial distribution of information hotspots for humans via fixation maps. We have proposed a gradient-based method for visualizing the reasoning behind the model's decision through visualization maps and have proved that our method is better than the other class activation mapping methods. Qualitative comparison between visualization maps and fixation maps reveals that both model and humans focus on similar regions in character in the case of correctly classified characters. However, when the focused regions are different for humans and model, the characters are typically misclassified by the latter. Hence, we propose to use the fixation maps as a supervisory input to train the model that ultimately results in improved recognition performance and better generalization. As the proposedmodel gives some insights about the reasoning behind its decision, it can find applications in fields, such as surveillance and medical applications, where explainability helps to determine system fidelity. Impact Statement-Humans and DNNs rely on selective information uptake while classifying a character. This information selection strategy can be understood by visualizing the important, informative character regions that ultimately govern the decision o

关键词： Visualization

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Performance Analysis of Model-Free Control and PID Control on a Class of Nonlinear MIMO Systems 57

Performance Analysis of Model-Free Control and PID Control o...

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57th Annual Conference on Information Sciences and Systems, CISS 2023

作者： Peng, James Cheng Spall, James C. Virginia Tech Bradley Department of Electrical and Computer Engineering ArlingtonVA United States Johns Hopkins University Department of Applied Mathematics and Statistics Applied Physics Laboratory LaurelMD United States

ISBN: (纸本)9781665451819

Modern dynamical systems are generally non-linear, which make traditional linear controllers infeasible in some cases. To cope with the need for controlling such modern systems, researchers have developed robust nonlinear controllers that leverage function approximators such as neural networks and polynomials. In this work, we investigate one successful nonlinear controller, the SPSA (si-multaneous perturbation stochastic approximation)-based model-free control. We shall make a rigorous performance analysis on a class of nonlinear MIMO systems. As a benchmark, we compare it with PID, one of the most-widely used control technique. © 2023 IEEE.

关键词： Stochastic systems

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Development of ANFIS Controller for Trajectory Tracking Control Using ROBO2L MATLAB Toolbox for KUKA Industrial Robot via RSI 21

Development of ANFIS Controller for Trajectory Tracking Cont...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Mousa, Mohamed Al-Mahasneh, Ahmad Baniyounis, Mohammed Biesenbach, Rolf Falkenhain, Jan Philadelphia University Mechatronics Engineering Department Amman Jordan Institute for Automation and Industry 4.0 Bochum University of Applied Sciences Bochum Germany Bochum University of Applied Sciences Electrical Engineering and Computer Science Department Bochum Germany

ISBN: (纸本)9798350374131

A new control scheme is proposed in the MATLAB/Simulink environment based on ANFIS technology using ROBO2L MATLAB toolbox with RSI to control the motion of the real KUKA robot. In detail, the control system has two subsystems designed for trajectory tracking error regulation in closed-loop control. One is a fuzzy logic controller, and the other is an ANFIS controller. These two controllers were used to control the velocity of the KUKA robot located inside the Hochschule Bochum laboratory. The testing process for these controllers was done by switching between FLC and ANFIS controllers and then studying each response separately. The results were compared with a linear controller produced in Hochschule Bochum experiments. The ROBO2L MATLAB toolbox provides many functions, such as sending and receiving positions and rotation for the end effector via UDP/IP communication, which RSI established to provide remote control for the robot using a PC. This work mainly emphasizes the ability to track the trajectories supported by the robotics toolbox in smooth motion. After observing the simulation results, the comparison between the linear, FLC, and ANFIS controllers is confirmed. The performance of the proposed approach is efficient for trajectory tracking control for the manipulator. © 2024 IEEE.

关键词： Controllers

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Advanced SMS Spam Detection using Deep Complex Models and Sine-Cosine Algorithm 14

Advanced SMS Spam Detection using Deep Complex Models and Si...

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14th International Conference on Information and Knowledge Technology, IKT 2023

作者： Rezaei, Sepehr Shams, Mohammadreza Meybodi, Mohsen Alambardar University of Isfahan Faculty of Mathematics and Statistics Department of Applied Mathematics and Computer Science Isfahan Iran University of Isfahan Shahreza Campus Department of Computer Engineering Isfahan Iran

ISBN: (纸本)9798350349412

With the increasing use of mobile phones and messaging services, SMS spam has become a significant issue for users. In this paper, we propose a novel approach1 to tackle this problem by using Sine-Cosine Algorithm (SCA) and Complex Multi-Layer Perceptron (C-MLP). Specifically, we apply the SCA method to reduce the dimensionality of the feature space and CMLP to improve the performance of spam detection. Also, in this paper, we investigate the effectiveness of different classification algorithms, including Support Vector Machines, Random Forests, K-nearest neighbors, Naive Bayes, bagging, and voting approaches. Our experimental results show that the proposed approach achieves high accuracy and outperforms existing methods in terms of both accuracy and F-measure. The proposed approach can be helpful in designing effective SMS spam filters and improving the overall user experience.1All the code used in this research is publicly available on the first author's GitHub repository: https://***/seper-sw/*** © 2023 IEEE.

关键词： Support vector machines

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Optimal Operation of Integrated Multi-energy Systems during Emergency Conditions 59

Optimal Operation of Integrated Multi-energy Systems during ...

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59th IEEE/IAS Industrial and Commercial Power Systems Technical Conference, I and CPS 2023

作者： Alnakhli, Ahmad Dehghanian, Payman Alhazmi, Mohannad George Washington University Department of Electrical and Computer Engineering WashingtonDC20052 United States College of Applied Engineering King Saud University Department of Electrical Engineering Riyadh11421 Saudi Arabia

ISBN: (纸本)9798350396515

The rapid growth of interconnections between different energy systems has seen emerging developments in recent years. Electric Power System (EPS), Water System (WS) and Natural Gas System (NGS) have been traditionally operated independently. However, a multi-sectoral approach is needed to enhance the resilience of critical infrastructure systems and reap the economic benefits. This becomes crucial as natural disasters with massive power outages have increased in both frequency and magnitude. To address these challenges, this paper proposes a cooperative co-optimization framework for the operation of the Power, Water, and Gas Networks (PWGNs) during emergency operating conditions. The proposed formulation takes into account the nonlinear nature of both the hydraulic constraints in WS and the gas flow in the NGS. Linearization techniques are employed to convert the nonlinear model into a MixedInteger Linear Programming (MILP) formulation. Case studies with different contingency scenarios are analyzed in the IEEE 24-bus reliability test system, which is jointly operated with a 12-node NGS and a 15-node commercial-scale WS. Numerical results demonstrate that the proposed model effectively enhances the resilience of the interconnected energy systems and reduces the overall operational costs during emergency conditions. © 2023 IEEE.

关键词： Flow of gases

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Improving Information Freshness in Edge-Assisted Smart Grids: An AoI-Aware Routing Strategy for Neighborhood Area Networks 22

Improving Information Freshness in Edge-Assisted Smart Grids...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Farag, Hossam Kotb, Mostafa Stefanović, Čedomir Gidlund, Mikael Department of Electronic Systems Aalborg University Denmark Department of Informatics Universität Hamburg Germany Department of Electrical Engineering Aswan University Egypt Mathematics Department Aswan University Egypt Department of Computer and Electrical Engineering Mid Sweden University Sweden

ISBN: (纸本)9798331527471

The integration of edge controllers into smart grid infrastructures facilitates advanced functionalities and high responsiveness, thereby bolstering the overall efficiency of the energy grid. The freshness of the sensing information received at the edge controller, captured by the Age of Information (AoI) metric, is vital to maintain system stability, where outdated information may lead to incorrect responses to grid conditions, potentially causing inefficiencies or system disruptions. However, the timeliness of the transmitted updates is mainly compromised by the delay and congestion within the routing links in the Neighborhood Area Network (NAN). In this work, we develop an intelligent routing strategy to improve the AoI of the Routing Protocol for Low-power and lossy networks (RPL), which is the common routing protocol for smart grids. Our proposed method is based on an AoI-aware parent selection mechanism, by which a node becomes attached to the parent with the highest probability of delivering a packet within a predefined AoI threshold. The prediction is made based on a supervised machine learning model, trained using the collection of heterogeneous routing metrics. The performance of the proposed method is evaluated via extensive discrete-event simulations and the results show its potency to improve the peak AoI and the AoI violation probability compared to the standard RPL. © 2024 IEEE.

关键词： Edge computing

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OTFS - Predictability in the Delay-Doppler Domain and Its Value to Communication and Radar Sensing

IEEE BITS the Information Theory Magazine

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IEEE BITS the Information Theory Magazine 2023年第2期3卷 7-31页

作者： Mohammed, Saif Khan Hadani, Ronny Chockalingam, Ananthanarayanan Calderbank, Robert Indian Institute of Technology Delhi Department of Electrical Engineering New Delhi110016 India University of Texas at Austin Department of Mathematics AustinTX78712 United States Indian Institute of Science Bangalore Department of Electrical Communication Engineering Bangalore560012 India Duke University Department of Electrical Computer Engineering DurhamNC27708 United States

In our first paper (Mohammed et al., IEEE BITS Inf. Theory Mag., vol. 2, no. 2, pp. 36-55, Nov. 2022.), we explained why the Zak-OTFS input-output (I/O) relation is predictable and nonfading when the delay and Doppler periods are greater than the effective channel delay and Doppler spreads, a condition which we refer to as the crystallization condition. We argued that a communication system should operate within the crystalline regime. It is well known that it is possible to identify a linear time varying (LTV) channel if and only if it is underspread. The crystallization condition is more restrictive than the underspread condition, so identification is always possible. In the crystalline regime, we show that Zak-OTFS pilot sequences minimize the complexity of identifying the effective delay-Doppler (DD) domain channel filter. We demonstrate that the filter taps can simply be read off from the response to a single Zak-OTFS pilot. In general, we provide an explicit formula for reconstructing the Zak-OTFS I/O relation from a finite number of received pilot symbols in the DD domain. This reconstruction formula makes it possible to study predictability of the Zak-OTFS I/O relation for a sampled system that operates under finite duration and bandwidth constraints. We analyze reconstruction accuracy for different choices of the delay and Doppler periods, and of the pulse shaping filter. Reconstruction accuracy is high when the crystallization condition is satisfied, implying that it is possible to learn directly the I/O relation without needing to estimate the underlying channel. This opens up the possibility of a model-free mode of operation, which is especially useful when a traditional model-dependent mode of operation (reliant on estimation of the underlying physical channel) is out of reach (for example, when the channel comprises of unresolvable paths, or exhibits a continuous DD profile such as in presence of acceleration). Our study clarifies the fundamental origi

关键词： Bandwidth

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