IEEE Access最新文献

{"title":"Automatic Recognition of Illegal Substations by Employing Logit-Boost Algorithm and LSTM With the Help of Different Landsat-8 OLI Image Spectral Band Parameters: A Case Study in Sason, Turkey","authors":"Emrullah Acar;Enes Bakiş;Musa Yilmaz","doi":"10.1109/ACCESS.2023.3323694","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323694","url":null,"abstract":"Automatic recognition of illegal substations is of great importance, since most of the leakage electricity in Turkey is due to the use of these substations in agricultural fields. One of the most effective ways to detect illegal substations is to employ remote sensing images and machine learning techniques together. Because, thanks to remote sensing images, it is possible to analyze illegal substations on huge agricultural lands in a short time. In this study, illegal substations on the agricultural fields in the southeast Anatolian region, which is one of the regions where leakage electricity are most common, have been detected with the aid of Landsat-8 OLI images and machine learning algorithm. The proposed study has been carried out in several stages, respectively. In the first stage, the locations of 42 substations and 21 non-substation objects on the pilot area have been recorded with the help of GPS and these coordinates have been later transferred to the Landsat-8 OLI image dated on 14 June 2019. In the second stage, an image analysis has been performed by calculating the spectral band parameters from the Landsat-8 OLI images. In the next stage, relationships among illegal substations and non-substation objects have been set by utilizing the statistical metrics of obtained spectral band parameters. In the last stage, by utilizing LSTM (Long Short-Term Memory) method, which is a recurrent neural network model that has gained popularity in both remote sensing and various scientific disciplines in recent years and the Logit-Boost method, which is one of the popular boosting machine learning algorithms, automatic recognition of substations has been performed with an average accuracy of 88.89% for Logit-Boost method and 84.21% for LSTM method. It is notable from this study that the Logit-Boost Algorithm yields more proficient results than the LSTM model.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"112293-112306"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278420.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50362825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Head Attention-Based Hybrid Deep Neural Network for Aeroengine Risk Assessment","authors":"Jian-Hang Li;Xin-Yue Gao;Xiang Lu;Guo-Dong Liu","doi":"10.1109/ACCESS.2023.3323843","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323843","url":null,"abstract":"Existing deep-learning models have limited applicability to aeroengine risk assessment owing to insufficient feature extraction capabilities and low robustness. This paper presents a hybrid deep neural network based on a Time2Vec time-embedding layer and multi-head attention mechanism for the proactive risk assessment of aeroengines. The proposed model uses quick access recorder data as input to identify risks associated with different types of failures and outputs two sets of labels: risk level and risk cause. The base of the proposed model combines a convolutional neural network and bidirectional long short-term memory, which are used to automatically extract temporal and spatial features from the input data to represent the system state and capturing irregular temporal trends. The Time2Vec layer facilitates automated processing of sequential data to make it easier for these deep-learning models to recognize patterns in the dataset. The multi-head attention mechanism further enhances the ability of the proposed model to capture and allocate information weights effectively. In comparative experiments, five benchmark models were compared with the proposed model, which demonstrated the best classification accuracy and computational efficiency as well as the most robustness against imbalanced data samples.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"113376-113389"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278395.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50311009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Realtime Malicious Traffic Detection Targeted for TCP Out-of-Order Packets Based on FPGA","authors":"Zhenguo Hu;Hirokazu Hasegawa;Yukiko Yamaguchi;Hajime Shimada","doi":"10.1109/ACCESS.2023.3323853","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323853","url":null,"abstract":"Currently, with the increasing popularity of high-speed network, in order to protect the network environment, more and more companies start to explore how to efficiently detect malicious traffic. On the software side, traditional detection systems are usually based on CPU which will consume multi-core processing ability to handle huge network traffic. On the hardware side, current researches focus on using specific hardware to offload some functions such as string matching in malicious traffic detection. However, they cannot detect attack behaviors hidden in TCP out-of-order (OOO) packets well, which are very common in modern complex network environments. To deal with this problem, we present an FPGA-based realtime malicious traffic detection method especially to inspect TCP OOO packets. It employs two core function designs for efficient malicious traffic inspection: TCP OOO reassembly and hierarchical packet match. First, the TCP OOO packets are reassembled to in-order packets to prevent the omission check of malicious traffic. Second, we adapt a hierarchical packet match design which can not only detect the packet header and filter the matching traffic, but also has the ability to inspect the carried payload to further determine whether the traffic is benign or malicious. We use Xilinx Alveo U50 accelerator card as the implementation platform to achieve high speed detection. This paper aims to provide a full detection path and implement all the reassembly and inspection process within an FPGA board. We adapt Cisco TRex as the traffic generator to evaluate the system from detection throughput, resource utilization and power consumption. Compared with the CPU-based approaches, the experiment results show that our system has 485% detection throughput increase and 68% average power decrease.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"112212-112222"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278400.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50362820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparison of PCA and LBF Based Multireceiver SAS Imaging Algorithms","authors":"Meng Wang;Pan Huang","doi":"10.1109/ACCESS.2023.3323593","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323593","url":null,"abstract":"Multireceiver synthetic aperture sonar (SAS) is a useful tool to provide high-resolution images. The most important step lies in developments of multireceiver synthetic aperture image formation processors, which uses the sonar echoed signal as the input. The system transfer function is crucial in the development of signal processors. In order to use traditional imaging algorithms, the monostatic conversion transferring multireceiver SAS signal to monostatic SAS data is often conducted. A review and evaluation of imaging methods based on monostatic conversion is conducted in this article. The relationship of Phase center approximation (PCA) method and Loffeld’s bistatic formula (LBF) is firstly reformulated in theory. Considering facts that PCA and LBF methods are the approximation of exact system transfer function, the approximation error of both methods are firstly compared and evaluated by using the numerical system transfer function, which is considered to be the precise system transfer function. Since more approximations of PCA and LBF should be carried out to develop fast imaging algorithms, the actual phase error of both methods is compared and evaluated based on numerical system transfer function. Then, the imaging performance of both methods based on range migration algorithm (RMA) is further evaluated. At last, the relationships of both patent methods are comprehensively described.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"113272-113283"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278398.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50362854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Mixed Capacity of Extended Reality and Mobile Broadband Services in 5G-Advanced Networks","authors":"Pouria Paymard;Abolfazl Amiri;Troels E. Kolding;Klaus I. Pedersen","doi":"10.1109/ACCESS.2023.3323815","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323815","url":null,"abstract":"Extended reality (XR) is an emerging technology that has gained significant attention in the context of fifth-generation (5G) and 5G-Advanced cellular networks and beyond. One of the less explored areas for practical XR service deployments is the study of its interaction with the existing traffic such as enhanced mobile broadband (eMBB). This study explores the performance of having both XR and eMBB users simultaneously in a multi-cell network for two different indoor and outdoor deployment scenarios. We show that the main limitation to maximizing XR capacity in the mixed scenario is inter-cell interference (ICI) generated by eMBB users. ICI from eMBB results in a loss of about 80% in XR capacity when an XR source data rate of 45 Mbps and a strict packet delay budget (PDB) of 10 ms is enforced. To mitigate this, we propose new radio resource management enhancements that apply restrictions on eMBB radio resource usage to balance between eMBB and XR simultaneous capacity. With the proposed enhancements, maximum XR capacity can be maintained for the case with an XR source data rate of 45 Mbps and a PDB of 20 ms while restricting eMBB throughput by about 50%. The impact on eMBB throughput performance from adding XR users depends on the XR PDB, deployment environment, and the eMBB radio resource usage restriction. The results demonstrate that the eMBB throughput declines with a factor of 1 to 4 of the XR sum rate.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"113324-113338"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278399.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50362857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"International Student Profiling Framework","authors":"Renugah Rengasamy;Suraya Binti Hamid;Abdullah Bin Gani","doi":"10.1109/ACCESS.2023.3323416","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323416","url":null,"abstract":"The current conventional way of screening international students, solely based on prior admission and self-reported documents, is inadequate. Given the drastic increase in the number of incoming students, this inadequacy calls for better security surveillance. Therefore, this study investigates how personality traits can influence one’s online prosocial behavior, as an alternative screening mechanism for international students. To assess the association between Big Five and Dark Triad personality traits and online prosocial behavior via the mediation of self-esteem, cross-sectional survey data was collected from 218 international postgraduate students and analyzed using partial least squares structural equation modeling. The significant outcome of this study is the establishment of the International Student Profiling Framework, which serves as the basis for understanding the influence of personality traits and self-esteem on international students’ online prosocial behavior.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"114117-114127"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278432.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50363740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparative Perspective on Technologies of Big Data Value Chain","authors":"Ahmet Arif Aydin","doi":"10.1109/ACCESS.2023.3323160","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323160","url":null,"abstract":"Data is one of the most valuable assets in the digital era because it may conceal hidden valuable insights. Diverse organizations in diverse domains overcome the challenges of the big data value chain by employing a wide range of technologies to meet their needs and achieve a variety of goals to support their decision-making. Due to the significance of data-oriented technologies, this paper presents a model of the big data value chain based on technologies used in the acquisition, storage, and analysis of data. The following are the paper’s contributions: First, a model of the big data value chain is developed to illustrate a comprehensive representation of the big data value chain that depicts the relationships between the characteristics of big data and the technologies associated with each category. Second, in contrast to previous research, this paper presents an overview of technologies for each category of the big data value chain. The third contribution of this paper is to assist researchers and developers of data-intensive systems in selecting the appropriate technology for their specific application development use cases by providing examples of applications and use cases from prominent papers in a variety of fields and by describing the capabilities and stages of the technologies being presented so that the right technology is used at the right time in the big data collection, processing, storage, and analytics tasks.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"112133-112146"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10281364.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50215683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Generalized Two-Dimensional FFT Precoded Filter Bank Scheme With Low Complexity Equalizers in Time-Frequency Domain","authors":"Rogério Pereira Junior;Carlos Aurélio Faria Da Rocha;Bruno S. Chang;Didier Le Ruyet","doi":"10.1109/ACCESS.2023.3323928","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323928","url":null,"abstract":"Recently, the two-dimensional (2D) fast Fourier transform (2D-FFT) filter bank (FB) technique was proposed as an alternative to new wireless communication technologies covering several application scenarios. This technique presents similar characteristics to orthogonal time-frequency space modulation (OTFS), such as lower PAPR and robustness in high mobility scenarios; in addition, thanks to the use of filter bank modulation, the technique has a good spectral localization. In this work, we present the generalization of the 2D-FFT FB system by making changes in the waveform structure to obtain advantages in the symbol detection process. The proposed idea allows the use of low-complexity equalizers in the time-frequency (TF) domain, bringing a good performance/complexity trade-off and obtaining bit error rate (BER) results of the same order than delay-Doppler domain receivers for OTFS. Theoretical and simulation results show that it is possible to obtain a good error performance in high mobility scenarios even using simple equalizers in the TF domain combined with waveform structure adjustments.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"112414-112428"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278409.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50233735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-Efficient Transmission Strategy for Delay Tolerable Services in NOMA-Based Downlink With Two Users","authors":"Mengmeng Bai;Rui Zhu;Jianxin Guo;Feng Wang;Liping Wang;Hangjie Zhu;Lei Huang;Yushuai Zhang","doi":"10.1109/ACCESS.2023.3323930","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323930","url":null,"abstract":"With the continuous development of the communication industry, there is a shift in real-time services from 4G networks to Delay Tolerable (DT) services in the context of 5G/B5G networks. Additionally, energy consumption control poses significant challenges in the current communication industry. Therefore, we study algorithms and schemes to improve the Energy Efficiency (EE) of DT services in the context of Non-Orthogonal Multiple Access (NOMA) downlink two-user communication system.First, we transformed the EE enhancement problem into a convex optimization problem based on transmission power by derivation. Secondly, we propose to use Approximate Statistical Dynamic Programming (ASDP) algorithm, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO) to solve the problem that convex optimization cannot be decided in real time. Finally, we perform an interpretability analysis on whether the decision schemes of the agents trained by the DDPG algorithm and the PPO algorithm are reasonable. The simulation results show that the decisions made by the agent trained by the DDPG algorithm perform better compared to the ASDP algorithm and the PPO algorithm.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"113227-113243"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10278391.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50362853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Organized Wireless Sensor Network (SOWSN) for Dense Jungle Applications","authors":"Galang P. N. Hakim;Mohamed Hadi Habaebi;MD. Rafiqul Islam;Abdullah Alghaihab;Siti Hajar Binti Yusoff;Erry Yulian T. Adesta","doi":"10.1109/ACCESS.2023.3323035","DOIUrl":"https://doi.org/10.1109/ACCESS.2023.3323035","url":null,"abstract":"To facilitate wireless sensor networks deployment in dense jungle environments, the challenges of unreliable wireless communication links used for routing data between nodes and the gateway, and the limited battery energy available from the nodes must be overcome. In this paper, we introduce the Self-Organized Wireless Sensor Network (SOWSN) to overcome these challenges. To develop the traits needed for such SOWSN nodes, three types of computational intelligence mechanisms have been featured in the design. The first feature is the introduction of Multi Criteria Decision Making (MCDM) algorithm with simple Additive Weight (SAW) function for clustering the SOWSN nodes. The second feature is the introduction of the fuzzy logic ANFIS-optimized Near Ground Propagation Model to predict the wireless transmission link quality and power transfer between transmitters. The third feature is the introduction of the (Levenberg Marquardt artificial neural network (LM-ANN) for Adaptive and Dynamic Power Control to further optimize the transmitter power levels, radio modulation, Spreading Factor configurations, and settings of the employed SOWSN LoRaWAN nodes based on predicted wireless transmission link quality parameters. The introduced features were extensively evaluated and analyzed using simulation and empirical measurements. Using clustering, near-ground propagation, and adaptive transmission power control features, a robust wireless data transmission system was built while simultaneously providing power conservation in SOWSN operation. The payload loss can be improved using SAW clustering from 1275-bytes to 5100-bytes. The result of power conservation can be seen from the reduction of transmission power in SOWSN nodes with the increase of transmission time (TOA) as its side effect. With the original power transmission at 20-dBm, original TOA time at 96.832-milliseconds for all nodes, and SNR 3 as input, transmission power was reduced to 12.76-dBm and the TOA increased to 346.78-milliseconds for all nodes.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"11 ","pages":"112940-112952"},"PeriodicalIF":3.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/6287639/10005208/10281366.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50212136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}