Pub Date : 2024-07-23DOI: 10.3390/electronics13152909
O. Oyerinde, Adam Flizikowski, Tomasz Marciniak, Dmitry Zelenchuk, T. Ngatched
This paper investigates single-user uplink and two-user downlink channel estimation in reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) wireless communication systems. Because of the difficulty associated with the estimation of channels in RIS-aided wireless communication systems, channel state information (CSI) is assumed to be known at the receiver in some previous works in the literature. By assuming that prior knowledge of the line-of-sight (LoS) channel between the RIS and the base station (BS) is known, two compressive sensing-based channel estimation schemes that are based on simultaneous orthogonal matching pursuit and structured matching pursuit (StrMP) algorithms are proposed for estimation of uplink channel between RIS and user equipment (UE), and joint estimations of downlink channels between BS and a UE, and between RIS and another UE, respectively. The proposed channel estimation schemes exploit the inherent common sparsity shared by the angular domain mmWave channels at different subcarriers. The superiority of one of the proposed channel estimation techniques, the StrMP-based channel estimation technique, with negligibly higher computational complexity cost compared with other channel estimators, is documented through extensive computer simulation. Specifically, with a reduced pilot overhead, the proposed StrMP-based channel estimation scheme exhibits better performance than other channel estimation schemes considered in this paper for signal-to-noise ratio (SNR) between 0 dB and 5 dB upward at different instances for both uplink and downlink scenarios, respectively. However, below these values of SNR the proposed StrMP-based channel estimation scheme will require higher pilot overhead to perform optimally.
{"title":"Compressive Sensing-Based Channel Estimation for Uplink and Downlink Reconfigurable Intelligent Surface-Aided Millimeter Wave Massive MIMO Systems","authors":"O. Oyerinde, Adam Flizikowski, Tomasz Marciniak, Dmitry Zelenchuk, T. Ngatched","doi":"10.3390/electronics13152909","DOIUrl":"https://doi.org/10.3390/electronics13152909","url":null,"abstract":"This paper investigates single-user uplink and two-user downlink channel estimation in reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) wireless communication systems. Because of the difficulty associated with the estimation of channels in RIS-aided wireless communication systems, channel state information (CSI) is assumed to be known at the receiver in some previous works in the literature. By assuming that prior knowledge of the line-of-sight (LoS) channel between the RIS and the base station (BS) is known, two compressive sensing-based channel estimation schemes that are based on simultaneous orthogonal matching pursuit and structured matching pursuit (StrMP) algorithms are proposed for estimation of uplink channel between RIS and user equipment (UE), and joint estimations of downlink channels between BS and a UE, and between RIS and another UE, respectively. The proposed channel estimation schemes exploit the inherent common sparsity shared by the angular domain mmWave channels at different subcarriers. The superiority of one of the proposed channel estimation techniques, the StrMP-based channel estimation technique, with negligibly higher computational complexity cost compared with other channel estimators, is documented through extensive computer simulation. Specifically, with a reduced pilot overhead, the proposed StrMP-based channel estimation scheme exhibits better performance than other channel estimation schemes considered in this paper for signal-to-noise ratio (SNR) between 0 dB and 5 dB upward at different instances for both uplink and downlink scenarios, respectively. However, below these values of SNR the proposed StrMP-based channel estimation scheme will require higher pilot overhead to perform optimally.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152906
Jayanthi Ramamoorthy, Khushi Gupta, Ram C. Kafle, N. Shashidhar, C. Varol
The proliferation of Internet of Things (IoT) devices on Linux platforms has heightened concerns regarding vulnerability to malware attacks. This paper introduces a novel approach to investigating the behavior of Linux IoT malware by examining syscalls and library syscall wrappers extracted through static analysis of binaries, as opposed to the conventional method of using dynamic analysis for syscall extraction. We rank and categorize Linux system calls based on their security significance, focusing on understanding malware intent without execution. Feature analysis of the assigned syscall categories and risk ranking is conducted with statistical tests to validate their effectiveness and reliability in differentiating between malware and benign binaries. Our findings demonstrate that potential threats can be reliably identified with an F1 score of 96.86%, solely by analyzing syscalls and library syscall wrappers. This method can augment traditional static analysis, providing an effective preemptive measure to enhance Linux malware analysis. This research highlights the importance of static analysis in strengthening IoT systems against emerging malware threats.
Linux 平台上物联网 (IoT) 设备的激增加剧了人们对恶意软件攻击脆弱性的担忧。本文介绍了一种研究 Linux 物联网恶意软件行为的新方法，即通过静态分析二进制文件来检查系统调用和库系统调用包装器，而不是使用动态分析来提取系统调用的传统方法。我们根据安全重要性对 Linux 系统调用进行排序和分类，重点是在不执行的情况下了解恶意软件的意图。我们通过统计测试对分配的系统调用类别和风险排名进行了特征分析，以验证它们在区分恶意软件和良性二进制文件方面的有效性和可靠性。我们的研究结果表明，仅通过分析系统调用和库系统调用封装，就能可靠地识别潜在威胁，F1 得分为 96.86%。这种方法可以增强传统的静态分析，为加强 Linux 恶意软件分析提供有效的先发制人的措施。这项研究强调了静态分析在加强物联网系统应对新兴恶意软件威胁方面的重要性。
{"title":"A Novel Static Analysis Approach Using System Calls for Linux IoT Malware Detection","authors":"Jayanthi Ramamoorthy, Khushi Gupta, Ram C. Kafle, N. Shashidhar, C. Varol","doi":"10.3390/electronics13152906","DOIUrl":"https://doi.org/10.3390/electronics13152906","url":null,"abstract":"The proliferation of Internet of Things (IoT) devices on Linux platforms has heightened concerns regarding vulnerability to malware attacks. This paper introduces a novel approach to investigating the behavior of Linux IoT malware by examining syscalls and library syscall wrappers extracted through static analysis of binaries, as opposed to the conventional method of using dynamic analysis for syscall extraction. We rank and categorize Linux system calls based on their security significance, focusing on understanding malware intent without execution. Feature analysis of the assigned syscall categories and risk ranking is conducted with statistical tests to validate their effectiveness and reliability in differentiating between malware and benign binaries. Our findings demonstrate that potential threats can be reliably identified with an F1 score of 96.86%, solely by analyzing syscalls and library syscall wrappers. This method can augment traditional static analysis, providing an effective preemptive measure to enhance Linux malware analysis. This research highlights the importance of static analysis in strengthening IoT systems against emerging malware threats.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152891
Yuehua Liu, Xiaoyu Li, Jifei Fang
Radar radiation source recognition technology is vital in electronic countermeasures, electromagnetic control, and air traffic management. Its primary function is to identify radar signals in real time by computing and inferring the parameters of intercepted signals. With the rapid advancement of AI technology, deep learning algorithms have shown promising results in addressing the challenges of radar radiation source recognition. However, significant obstacles remain: the radar radiation source data often exhibit large-scale, unbalanced sample distribution and incomplete sample labeling, resulting in limited training data resources. Additionally, in practical applications, models must be deployed on outdoor edge computing terminals, where the storage and computing capabilities of lightweight embedded systems are limited. This paper focuses on overcoming the constraints posed by data resources and edge computing capabilities to design and deploy large-scale radar radiation source recognition algorithms. Initially, it addresses the issues related to large-scale radar radiation source samples through data analysis, preprocessing, and feature selection, extracting and forming prior knowledge information. Subsequently, a model named RIR-DA (Radar ID Recognition based on Deep Learning Autoencoder) is developed, integrating this prior knowledge. The RIR-DA model successfully identified 96 radar radiation source targets with an accuracy exceeding 95% in a dataset characterized by a highly imbalanced sample distribution. To tackle the challenges of poor migration effects and low computational efficiency on lightweight edge computing platforms, a parallel acceleration scheme based on the embedded microprocessor T4240 is designed. This approach achieved a nearly eightfold increase in computational speed while maintaining the original training performance. Furthermore, an integrated solution for a radar radiation source intelligent detection system combining PC devices and edge devices is preliminarily designed. Experimental results demonstrate that, compared to existing radar radiation source target recognition algorithms, the proposed method offers superior model performance and greater practical extensibility. This research provides an innovative exploratory solution for the industrial application of deep learning models in radar radiation source recognition.
雷达辐射源识别技术对电子对抗、电磁控制和空中交通管理至关重要。其主要功能是通过计算和推断截获信号的参数来实时识别雷达信号。随着人工智能技术的飞速发展，深度学习算法在应对雷达辐射源识别挑战方面取得了可喜的成果。然而，巨大的障碍依然存在：雷达辐射源数据往往呈现大规模、不均衡的样本分布，且样本标记不完整，导致训练数据资源有限。此外，在实际应用中，模型必须部署在户外边缘计算终端上，而轻量级嵌入式系统的存储和计算能力有限。本文的重点是克服数据资源和边缘计算能力带来的限制，设计和部署大规模雷达辐射源识别算法。首先，本文通过数据分析、预处理和特征选择，提取并形成先验知识信息，解决了大规模雷达辐射源样本的相关问题。随后，结合这些先验知识，开发了一个名为 RIR-DA（基于深度学习自动编码器的雷达 ID 识别）的模型。在样本分布高度不平衡的数据集中，RIR-DA 模型成功识别了 96 个雷达辐射源目标，准确率超过 95%。为解决轻量级边缘计算平台迁移效果差和计算效率低的难题，设计了一种基于嵌入式微处理器 T4240 的并行加速方案。这种方法在保持原有训练性能的同时，将计算速度提高了近八倍。此外，还初步设计了一种结合 PC 设备和边缘设备的雷达辐射源智能检测系统的集成解决方案。实验结果表明，与现有的雷达辐射源目标识别算法相比，所提出的方法具有更优越的模型性能和更大的实用扩展性。该研究为深度学习模型在雷达辐射源识别中的工业应用提供了一种创新的探索性解决方案。
{"title":"Deep-Autoencoder-Based Radar Source Recognition: Addressing Large-Scale Imbalanced Data and Edge Computing Constraints","authors":"Yuehua Liu, Xiaoyu Li, Jifei Fang","doi":"10.3390/electronics13152891","DOIUrl":"https://doi.org/10.3390/electronics13152891","url":null,"abstract":"Radar radiation source recognition technology is vital in electronic countermeasures, electromagnetic control, and air traffic management. Its primary function is to identify radar signals in real time by computing and inferring the parameters of intercepted signals. With the rapid advancement of AI technology, deep learning algorithms have shown promising results in addressing the challenges of radar radiation source recognition. However, significant obstacles remain: the radar radiation source data often exhibit large-scale, unbalanced sample distribution and incomplete sample labeling, resulting in limited training data resources. Additionally, in practical applications, models must be deployed on outdoor edge computing terminals, where the storage and computing capabilities of lightweight embedded systems are limited. This paper focuses on overcoming the constraints posed by data resources and edge computing capabilities to design and deploy large-scale radar radiation source recognition algorithms. Initially, it addresses the issues related to large-scale radar radiation source samples through data analysis, preprocessing, and feature selection, extracting and forming prior knowledge information. Subsequently, a model named RIR-DA (Radar ID Recognition based on Deep Learning Autoencoder) is developed, integrating this prior knowledge. The RIR-DA model successfully identified 96 radar radiation source targets with an accuracy exceeding 95% in a dataset characterized by a highly imbalanced sample distribution. To tackle the challenges of poor migration effects and low computational efficiency on lightweight edge computing platforms, a parallel acceleration scheme based on the embedded microprocessor T4240 is designed. This approach achieved a nearly eightfold increase in computational speed while maintaining the original training performance. Furthermore, an integrated solution for a radar radiation source intelligent detection system combining PC devices and edge devices is preliminarily designed. Experimental results demonstrate that, compared to existing radar radiation source target recognition algorithms, the proposed method offers superior model performance and greater practical extensibility. This research provides an innovative exploratory solution for the industrial application of deep learning models in radar radiation source recognition.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152903
Lin Li, Zhenchuan Wang, Jinqi Zhu, Shizhao Ma
Earthquake disasters are usually very destructive and pose a great threat to human life and property. Based on the relatively mature technology of unmanned aerial vehicles (UAVs) and their high flexibility, these devices are widely used for information collection and processing in post-disaster relief operations. However, UAVs are limited by their battery capacity, which makes it hard for them to perform both large-scale information gathering and data processing at the same time. Nowadays, smartphones (SPs), which have become portable devices for people, have the characteristics of strong computing power, rich communication means and wide distribution. Therefore, in this study, we developed SPs to assist UAVs in computation incentive-based task execution. To balance the cost of UAVs and the execution utility of SPs during the task execution process, a multi-objective optimization problem was established, and the Multi-Objective Mutation-Immune Bat (MOMIB) algorithm was developed to optimize the proposed problem. Additionally, considering the diversity of tasks in real-world scenarios, Quality of Service (QoS) coefficients were introduced to ensure the performance requirements of different types of tasks. A large number of simulation experiments show that the task-offloading scheme that we propose is effective.
{"title":"Smartphone-Based Task Scheduling in UAV Networks for Disaster Relief","authors":"Lin Li, Zhenchuan Wang, Jinqi Zhu, Shizhao Ma","doi":"10.3390/electronics13152903","DOIUrl":"https://doi.org/10.3390/electronics13152903","url":null,"abstract":"Earthquake disasters are usually very destructive and pose a great threat to human life and property. Based on the relatively mature technology of unmanned aerial vehicles (UAVs) and their high flexibility, these devices are widely used for information collection and processing in post-disaster relief operations. However, UAVs are limited by their battery capacity, which makes it hard for them to perform both large-scale information gathering and data processing at the same time. Nowadays, smartphones (SPs), which have become portable devices for people, have the characteristics of strong computing power, rich communication means and wide distribution. Therefore, in this study, we developed SPs to assist UAVs in computation incentive-based task execution. To balance the cost of UAVs and the execution utility of SPs during the task execution process, a multi-objective optimization problem was established, and the Multi-Objective Mutation-Immune Bat (MOMIB) algorithm was developed to optimize the proposed problem. Additionally, considering the diversity of tasks in real-world scenarios, Quality of Service (QoS) coefficients were introduced to ensure the performance requirements of different types of tasks. A large number of simulation experiments show that the task-offloading scheme that we propose is effective.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152904
Thanh-Dat Nguyen, Minh-Son Le, Thi-Nhan Pham, Ik-Joon Chang
Some applications, such as satellites, require ultralow power and high-radiation resilience. We developed a12Tsoft error-resilient SRAM cell, TA-Quatro, to deliver in-memory computing (IMC) for those applications. Based on our TA-Quatro cell, we implemented an IMC circuit to support binary weights and ternary activations in a single SRAM cell. Our simulation under 28 nm FD-SOI technology demonstrates that the TA-Quatro IMC circuit maintains good IMC stability at a scaled supply of 0.7Vand achieves ternary activation without needing analog-to-digital converters. These advancements significantly enhance the power efficiency of the proposed IMC circuit compared to state-of-the-art works.
{"title":"TA-Quatro: Soft Error-Resilient and Power-Efficient SRAM Cell for ADC-Less Binary Weight and Ternary Activation In-Memory Computing","authors":"Thanh-Dat Nguyen, Minh-Son Le, Thi-Nhan Pham, Ik-Joon Chang","doi":"10.3390/electronics13152904","DOIUrl":"https://doi.org/10.3390/electronics13152904","url":null,"abstract":"Some applications, such as satellites, require ultralow power and high-radiation resilience. We developed a12Tsoft error-resilient SRAM cell, TA-Quatro, to deliver in-memory computing (IMC) for those applications. Based on our TA-Quatro cell, we implemented an IMC circuit to support binary weights and ternary activations in a single SRAM cell. Our simulation under 28 nm FD-SOI technology demonstrates that the TA-Quatro IMC circuit maintains good IMC stability at a scaled supply of 0.7Vand achieves ternary activation without needing analog-to-digital converters. These advancements significantly enhance the power efficiency of the proposed IMC circuit compared to state-of-the-art works.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152894
Samantha Leigh Williams, S. Reising
This work addresses the design of sub-terahertz narrow-band resonators for high performance and low-cost manufacturability. The intended application for these resonators is to realize narrow-band filters for passive millimeter-wave sounding of upper atmospheric humidity using the 380 GHz water vapor absorption line. Various narrow-band resonator designs and manufacturing processes were considered for this application. A design based on a waveguide split-ring resonator topology was selected to be developed and manufactured using laser machining. Experimental results are presented and compared with results from simulations for ten narrow-band resonators fabricated with a design center frequency in the WR-2.2 (325–500 GHz) waveguide band.
{"title":"Waveguide-Based Split-Ring Resonators for Narrow-Band Filters Near 380 GHz","authors":"Samantha Leigh Williams, S. Reising","doi":"10.3390/electronics13152894","DOIUrl":"https://doi.org/10.3390/electronics13152894","url":null,"abstract":"This work addresses the design of sub-terahertz narrow-band resonators for high performance and low-cost manufacturability. The intended application for these resonators is to realize narrow-band filters for passive millimeter-wave sounding of upper atmospheric humidity using the 380 GHz water vapor absorption line. Various narrow-band resonator designs and manufacturing processes were considered for this application. A design based on a waveguide split-ring resonator topology was selected to be developed and manufactured using laser machining. Experimental results are presented and compared with results from simulations for ten narrow-band resonators fabricated with a design center frequency in the WR-2.2 (325–500 GHz) waveguide band.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152900
Imanol Martín Toral, I. Calvo, Eneko Villar, J. M. Gil-García, O. Barambones
Designing smart building IoT applications is a complex task. It requires efficiently integrating a broad number of heterogeneous, low-resource devices that adopt lightweight strategies. IoT frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 standard, promotes the use of free open source (FOS) technologies and has been identified for use in smart buildings. However, smart building systems may present vulnerabilities, which can put their integrity at risk. Adopting state-of-the-art security mechanisms in this domain is critical but not trivial. It complicates the design and operation of the applications, increasing the cost of the deployed systems. In addition, difficulties may arise in finding qualified cybersecurity personnel. OpenFog identifies the security requirements of the applications, although it does not describe clearly how to implement them. This article presents a scalable architecture, based on the OpenFog reference architecture, to provide security by design in buildings of different sizes. It adopts FOS technologies over low-cost IoT devices. Moreover, it presents guidelines to help developers create secure applications, even if they are not security experts. It also proposes a selection of technologies in different layers to achieve the security dimensions defined in the X.805 ITU-T recommendation. A proof-of-concept Indoor Environment Quality (IEQ) system, based on low-cost smart nodes, was deployed in the Faculty of Engineering of Vitoria-Gasteiz to illustrate the implementation of the presented approach. The operation of the IEQ system was analyzed using software tools frequently used to find vulnerabilities in IoT applications. The use of state-of-the-art security mechanisms such as encryption, certificates, protocol selection and network partitioning/configuration in the OpenFog-based architecture improves smart building security.
{"title":"Introducing Security Mechanisms in OpenFog-Compliant Smart Buildings","authors":"Imanol Martín Toral, I. Calvo, Eneko Villar, J. M. Gil-García, O. Barambones","doi":"10.3390/electronics13152900","DOIUrl":"https://doi.org/10.3390/electronics13152900","url":null,"abstract":"Designing smart building IoT applications is a complex task. It requires efficiently integrating a broad number of heterogeneous, low-resource devices that adopt lightweight strategies. IoT frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 standard, promotes the use of free open source (FOS) technologies and has been identified for use in smart buildings. However, smart building systems may present vulnerabilities, which can put their integrity at risk. Adopting state-of-the-art security mechanisms in this domain is critical but not trivial. It complicates the design and operation of the applications, increasing the cost of the deployed systems. In addition, difficulties may arise in finding qualified cybersecurity personnel. OpenFog identifies the security requirements of the applications, although it does not describe clearly how to implement them. This article presents a scalable architecture, based on the OpenFog reference architecture, to provide security by design in buildings of different sizes. It adopts FOS technologies over low-cost IoT devices. Moreover, it presents guidelines to help developers create secure applications, even if they are not security experts. It also proposes a selection of technologies in different layers to achieve the security dimensions defined in the X.805 ITU-T recommendation. A proof-of-concept Indoor Environment Quality (IEQ) system, based on low-cost smart nodes, was deployed in the Faculty of Engineering of Vitoria-Gasteiz to illustrate the implementation of the presented approach. The operation of the IEQ system was analyzed using software tools frequently used to find vulnerabilities in IoT applications. The use of state-of-the-art security mechanisms such as encryption, certificates, protocol selection and network partitioning/configuration in the OpenFog-based architecture improves smart building security.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152889
Youxiang Zhu, Dong Li, Shenyang Xiao, Xuekong Liu, Shi Bu, Lijun Wang, Kai Ma, Piming Ma
This study aims to minimize the overall cost of wind power, photovoltaic power, energy storage, and demand response in the distribution network. It aims to solve the source-grid-load-storage coordination planning problem by considering demand response. Additionally, the study includes a deep analysis of the relationship between demand response, energy storage configuration, and system cost. A two-level planning model is established for wind power and photovoltaic power grid connection, including demand response, wind power, photovoltaic power, and energy storage. The model minimizes the sum of the differences between the total load and the total new energy generation after demand response in each time period as the bottom-level objective and minimizes the overall cost of the distribution network as the top-level objective, achieving the coordinated configuration of wind power, photovoltaic power, and energy storage. The simplex method is used to solve the model, and the improved IEEE33 node system is used as an example for verification. The simulation results fully prove the model’s correctness and the algorithm’s effectiveness, supporting the coordinated planning of distribution networks.
{"title":"Coordinated Control Strategy of Source-Grid-Load-Storage in Distribution Network Considering Demand Response","authors":"Youxiang Zhu, Dong Li, Shenyang Xiao, Xuekong Liu, Shi Bu, Lijun Wang, Kai Ma, Piming Ma","doi":"10.3390/electronics13152889","DOIUrl":"https://doi.org/10.3390/electronics13152889","url":null,"abstract":"This study aims to minimize the overall cost of wind power, photovoltaic power, energy storage, and demand response in the distribution network. It aims to solve the source-grid-load-storage coordination planning problem by considering demand response. Additionally, the study includes a deep analysis of the relationship between demand response, energy storage configuration, and system cost. A two-level planning model is established for wind power and photovoltaic power grid connection, including demand response, wind power, photovoltaic power, and energy storage. The model minimizes the sum of the differences between the total load and the total new energy generation after demand response in each time period as the bottom-level objective and minimizes the overall cost of the distribution network as the top-level objective, achieving the coordinated configuration of wind power, photovoltaic power, and energy storage. The simplex method is used to solve the model, and the improved IEEE33 node system is used as an example for verification. The simulation results fully prove the model’s correctness and the algorithm’s effectiveness, supporting the coordinated planning of distribution networks.","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.3390/electronics13152902
Anshi Xiong, Tao Wu, Jingtao Jia
Cerebral palsy is a disorder of central motor and postural development, resulting in limited mobility. Cerebral palsy is often accompanied by cognitive impairment and abnormal behavior, significantly impacting individuals and society. Time, energy, and economic investment in the rehabilitation process is substantial, yet the rehabilitation outcomes often remain unsatisfactory. Additionally, some patients have limited sensory perception during rehabilitation training, making it challenging to effectively regulate exercise intensity. Traditional evaluation methods are mostly based on recovery performance, lack guidance at the neurophysiological level, and have an unequal distribution of medical rehabilitation resources, which pose great challenges to the rehabilitation of patients. Based on the issues mentioned above, this paper proposes a real-time cerebral signal monitoring system based on wearable devices. This system can monitor and store blood oxygen, heart rate, myoelectric, and EEG signals during cerebral palsy rehabilitation, and it can track and monitor signals during the rehabilitation treatment process. The system includes two parts: hardware design and software design. The hardware design includes a data signal acquisition module, a main control chip (ESP32), a muscle electrical sensor module, a brain electrical sensor module, a blood/heart rate acquisition module, etc. It is primarily for real-time signal data acquisition, processing, and uploading to the cloud server. The software design includes functions such as data receiving, data processing, data storage, network configuration, and remote communication and enables the visual monitoring of data signals. The system can achieve real-time monitoring of electromyography, electroencephalography, and blood oxygen levels, as well as the heart rate of patients with cerebral palsy, and adjust rehabilitation training in real-time during the rehabilitation process. At the same time, based on the real-time storage of the original electromyography and electroencephalography data, it can provide auxiliary guidance for later rehabilitation evaluation and effective data support for the entire rehabilitation treatment process.
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Pub Date : 2024-07-23DOI: 10.3390/electronics13152887
Tomasz Rak, Dariusz Rzońca
The digital era has significantly transformed the dissemination of information and business operations, creating an intricate web of interconnected systems [...]
数字时代极大地改变了信息传播和商业运作，形成了一个错综复杂的互联系统网络 [...] 。
{"title":"Security and Privacy in Networks and Multimedia","authors":"Tomasz Rak, Dariusz Rzońca","doi":"10.3390/electronics13152887","DOIUrl":"https://doi.org/10.3390/electronics13152887","url":null,"abstract":"The digital era has significantly transformed the dissemination of information and business operations, creating an intricate web of interconnected systems [...]","PeriodicalId":504598,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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