Multilayer cyberattacks identification and classification using machine learning in internet of blockchain (IoBC)-based energy networks

Data in Brief, Journal Year: 2024, Volume and Issue: 54, P. 110461 - 110461

Published: May 3, 2024

The world's need for energy is rising due to factors like population growth, economic expansion, and technological breakthroughs. However, there are major consequences when gas coal burnt meet this surge in needs. Although these fossil fuels still essential meeting demands, their combustion releases a large amount of carbon dioxide other pollutants into the atmosphere. This significantly jeopardizes community health addition exacerbating climate change, thus it move swiftly incorporate renewable sources by employing advanced information communication technologies. change brings up several security issues emphasizing innovative cyber threats detection prevention solutions. Consequently, study presents bigdata sets obtained from solar wind powered distributed systems through blockchain-based networks smart grid (SG). A hybrid machine learning (HML) model that combines both Deep Learning (DL) Long-Short-Term-Memory (LSTM) models characteristics developed applied identify unique patterns Denial Service (DoS) Distributed (DDoS) cyberattacks power generation, transmission, distribution processes. presented big datasets helps identifying classifying cyberattacks, leading predicting accurate behavior SG.

Language: Английский

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Design and optimization of energy-efficient wireless sensor networks for industrial automation

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

In order to improve the overall performance of edge-integrated edge IoT networks, this research introduces a combined technique based on profound learning for booking assets. If an network wants finish task quickly and effectively, it has get greatest resources from layer. Thorough asset is crucial identification transfer optimal The integration networks with applications reduction data transmission latency were previously addressed using algorithms. we want make Internet Things application more feasible provide better service overall, should think about other metrics like reaction time, waiting bandwidth needs. Combining convolutional neural gated repeating unit in certain manner achieves enhanced performance. suggested model considers features requirements assets select most suitable ones pool allocate them networks. Here, give comprehensive analysis method-data combination.

Language: Английский

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An Easily Scalable Multilayer Rotary Electret Generator Based on Bipolar Electrets

Energy Technology, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Electret generators, which harvest ambient mechanical energy to power electronic devices, have emerged as a potential sustainable solution for supply and attracted widespread interest. However, the realization of high electrical outputs well simplification machining processes structural designs remain challenges. Herein, an easily scalable multilayer rotary electret generator (REG) based on bipolar electrets is proposed provide above problems. The films are utilized preparation REG, eliminating need conventional patterned charging process. output performance REG under different parameters investigated optimized. Results show that increases linearly with number rotor layers. Compared single‐layer one side, ten‐layer both sides voltage current by ≈18 times. achieves maximum average 58.7 mW at 360 rpm. As demonstration, over 500 blue light emitting diodes in series lit using REG.

Language: Английский

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Leveraging industry 4.0 and circular open innovation for digital sustainability: The role of circular ambidexterity

Journal of Open Innovation Technology Market and Complexity, Journal Year: 2025, Volume and Issue: 11(2), P. 100545 - 100545

Published: May 2, 2025

Language: Английский

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Internet of Things in Energy-Sensitive Processes: Application in a Refrigerated Warehouse

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 76257 - 76276

Published: Jan. 1, 2024

This article aims to address an existing research gap in the study of most widely used mathematical procedures field automatic control energy-sensitive industrial processes. In these types processes, as is case cold storage food sector or pharmaceutical industry, applying energy efficiency measures very risky. because margin variation temperature processes small, since product be manufactured preserved sensitive. where developments Internet Things showcase their usefulness they allow measurements taken with great accuracy and verify effectiveness proposals. Nevertheless, there are few studies on automation energetically sensitive industries. that present work shed light on, proposing a method for optimizing process revision refrigerated warehouse. Said prominently employs charts, relatively easy set up require minimal intervention but can revised manually if so desired. The analysis also includes auxiliary variable impact variations system. Improvements provided variables, which commonly methods industry maintain good results Finally, best selection charts chosen variables then discussed justified.

Language: Английский

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Critical review on resource scheduling in IaaS clouds: Taxonomy, issues, challenges, and future directions

The Journal of Engineering, Journal Year: 2024, Volume and Issue: 2024(8)

Published: Aug. 1, 2024

Abstract In a cloud computing environment, the primary goal of resource scheduling is to reduce economic expenditures for users and grow fiscal achievement providers. this article, study numerous forms algorithms presented that has been applied in IaaS clouds. The selected research articles are classified into six categories, according nature algorithm used. Further, authors pointed out several issues challenges with help algorithms, comparative performance metrics, simulation tools used validate algorithms. enhancement illustrates better concerns decreasing cost time while improving competence utilization resources These executed real environments similar CloudSim, SimGrid, MATLAB, test‐bed (practical implementation). This critical review classification will serve as foundation further clouds Internet Things (IoT) environments.

Language: Английский

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Using Neural Network-Based Time Series Analysis in Wireless Sensor Networks

Published: March 15, 2024

Neural community-primarily based time series analysis (NNTSA) is an effective technique for research records collected from wireless sensor networks (WSNs). NNTSA uses models stimulated by means of biological neural to capture complicated time-various statistics. It requires minimum training the enter facts and offers a high degree modelling accuracy. This method has turned out be increasingly famous WSN evaluation when you consider that it miles appropriate streaming statistics seizing patterns might not effortlessly detected with aid other techniques. fashions are commonly carried use supervised gaining knowledge processes, together lower back-propagation, wherein education styles fed network at same as its parameters adjusted fixed desired output values, average temperature over some time. After c section complete, new can evaluated trained model analyze their temporal conduct. techniques have been applied in diverse areas, inclusive fitness monitoring, site visitors management, weather tracking, suitable result.

Language: Английский

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Exploring the Use of Applied Cryptography Algorithms for Preventing Data Leakage

Published: March 15, 2024

This study explores the usage of encryption algorithms to prevent facts leakage. In particular, we have a look at effectiveness such alongside different assault vectors that may result in statistics We check out modern-day available tools addition proposed solutions for cryptography strategies counter assaults. Lastly, speak about results expanding techniques save you information breaches numerous organizations. The aim take is provide insights on how leverage carried beautify security and

Language: Английский

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Examining Dynamic Time Warping Algorithms for Hyper Spectral Image Data

Published: March 15, 2024

Dynamic Time Warping (DTW) algorithms have currently been implemented to provide efficient and accurate time series analysis in a selection of programs. This paper examines the performance numerous DTW within context hyperspectral image records. Specifically, focal point research is determine most suitable technique for mapping producing effective initialized fashions use imaging segmentation feature extraction responsibilities. The software those verified by utilizing exclusive styles imagery appearing example-precise experiments every one algorithms. GLCM texture function set used look at modifications statistics with respect distinct alterations. overall evaluation metrics evaluate diverse techniques are time, accuracy, inter-pixel as opposed intra-pixel dependencies. Results show that SOGA-DTW appropriate alternative interpreting information sets phrases its ability version relationships. changed additionally like greater stability robustness over varying ameliorations. Finally, create customized specific instance highlighted precious while thinking about analysis.

Language: Английский

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An Empirical Study of Medical Diagnosis Using Deep Learning

Published: March 15, 2024

this paper provides an empirical have a look at investigating the effectiveness of deep mastering (DL) for medical prognosis. The authors completed scientific on two one-of-a-kind issues: blood cellular and breast cancer analysis. For every trouble, explored performance 3 distinctive DL models, particularly convolutional neural networks (CNNs), notion (DBNs), recurrent (RNNs). Furthermore, examine accuracy fashions to baseline non-DL technique. Experiments benchmark dataset show that models reap higher quicker convergence than method, accordingly supplying sturdy indication use is powerful diagnosis. inspect additionally exclusive combinations with specific feature choice strategies, as well hyperparameter tuning techniques enhance pace Moreover, steadiness inside presence noisy information. results study exhibit tool clinical prognosis ought be similarly explored.

Language: Английский

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