Pub Date : 2024-11-13DOI: 10.1109/JSEN.2024.3467055
Qian Sun;Jialong Pang;Xiaoyi Wang;Zhiyao Zhao;Jing Li
Given the intrinsic low energy and high consumption characteristics of sensor nodes, it is imperative to explore strategies for achieving energy-efficient routing within wireless sensor networks (WSNs). A significant body of existing research on clustered routing algorithms for WSNs has concentrated on employing heuristic optimization algorithms to facilitate the selection of routing paths. However, once the number of sensor nodes or the deployment environment changes, the algorithm’s performance can fluctuate significantly, potentially requiring redesign and retuning. In this article, we propose the clustered routing algorithm based on forwarding mechanism optimization (CRFMO), which defines separate routing rules for intracluster and intercluster communication, providing suitable communication paths for nodes. The algorithm eschews the complex procedure of parameter tuning during the routing path selection process and contributes to expediting WSN deployment and balancing node load pressure, ultimately extending the network’s operational lifespan. Simulation outcomes reveal that, in comparison to LEACH-IACA and IMP-LEACH, the CRFMO algorithm markedly enhances energy distribution balance, equalizes the burden among nodes, sustains high network coverage over an extended period, which enhances the quality of network monitoring, and significantly extends the lifetime of the network.
{"title":"A Clustered Routing Algorithm Based on Forwarding Mechanism Optimization","authors":"Qian Sun;Jialong Pang;Xiaoyi Wang;Zhiyao Zhao;Jing Li","doi":"10.1109/JSEN.2024.3467055","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3467055","url":null,"abstract":"Given the intrinsic low energy and high consumption characteristics of sensor nodes, it is imperative to explore strategies for achieving energy-efficient routing within wireless sensor networks (WSNs). A significant body of existing research on clustered routing algorithms for WSNs has concentrated on employing heuristic optimization algorithms to facilitate the selection of routing paths. However, once the number of sensor nodes or the deployment environment changes, the algorithm’s performance can fluctuate significantly, potentially requiring redesign and retuning. In this article, we propose the clustered routing algorithm based on forwarding mechanism optimization (CRFMO), which defines separate routing rules for intracluster and intercluster communication, providing suitable communication paths for nodes. The algorithm eschews the complex procedure of parameter tuning during the routing path selection process and contributes to expediting WSN deployment and balancing node load pressure, ultimately extending the network’s operational lifespan. Simulation outcomes reveal that, in comparison to LEACH-IACA and IMP-LEACH, the CRFMO algorithm markedly enhances energy distribution balance, equalizes the burden among nodes, sustains high network coverage over an extended period, which enhances the quality of network monitoring, and significantly extends the lifetime of the network.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"24 22","pages":"38071-38081"},"PeriodicalIF":4.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-12DOI: 10.1109/TPS.2024.3486956
{"title":"Blank Page","authors":"","doi":"10.1109/TPS.2024.3486956","DOIUrl":"https://doi.org/10.1109/TPS.2024.3486956","url":null,"abstract":"","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":"52 8","pages":"C4-C4"},"PeriodicalIF":1.3,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10750911","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-04DOI: 10.1109/JPHOTOV.2024.3489253
{"title":"2024 Index IEEE Journal of Photovoltaics Vol. 14","authors":"","doi":"10.1109/JPHOTOV.2024.3489253","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3489253","url":null,"abstract":"","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"14 6","pages":"977-1002"},"PeriodicalIF":2.5,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10741899","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1109/OJNANO.2024.3488787
Anmol Garg;Sajal Agarwal;Deepak Punetha
This paper reports the comparative analysis of different piezoelectric materials through a MEMS-based piezoelectric actuator model, emphasizing their potential for sensing applications. The polarization and electrostrictive strain tensor capabilities have been extensively studied for different piezoelectric materials such as PZT, LiNbO 3 , PVDF, etc. The simulation results obtained at varying voltages and mechanical stress demonstrate that LiNbO 3 exhibits superior performance among the tested materials, with a polarization value of 0.5163 C/m 2 at 800 volts and an electrostrictive strain tensor of 0.01 at an applied mechanical stress of 25 MPa. These findings will assist scientists in selecting the most suitable piezoelectric materials for sensing applications in biomedical fields.
{"title":"Polarization and Strain in Piezoelectric Nanomaterials: Advancing Sensing Applications in Biomedical Technology","authors":"Anmol Garg;Sajal Agarwal;Deepak Punetha","doi":"10.1109/OJNANO.2024.3488787","DOIUrl":"https://doi.org/10.1109/OJNANO.2024.3488787","url":null,"abstract":"This paper reports the comparative analysis of different piezoelectric materials through a MEMS-based piezoelectric actuator model, emphasizing their potential for sensing applications. The polarization and electrostrictive strain tensor capabilities have been extensively studied for different piezoelectric materials such as PZT, LiNbO\u0000<sub>3</sub>\u0000, PVDF, etc. The simulation results obtained at varying voltages and mechanical stress demonstrate that LiNbO\u0000<sub>3</sub>\u0000 exhibits superior performance among the tested materials, with a polarization value of 0.5163 C/m\u0000<sup>2</sup>\u0000 at 800 volts and an electrostrictive strain tensor of 0.01 at an applied mechanical stress of 25 MPa. These findings will assist scientists in selecting the most suitable piezoelectric materials for sensing applications in biomedical fields.","PeriodicalId":446,"journal":{"name":"IEEE Open Journal of Nanotechnology","volume":"5 ","pages":"89-97"},"PeriodicalIF":1.8,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10739969","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1109/TNANO.2024.3487223
Nandit Kaushik;B. Srinivasu
In-Memory-Computing (IMC) through memristive architectures has recently gained traction owing to their capacity to perform logic operations within a crossbar, optimizing both area and speed constraints. This paper introduces two approximate serial IMPLY-based subtractor designs, denoted as Serial IMPLY-based Approximate Subtractor Design-1 (SIASD-1), Serial IMPLY-based Approximate Subtractor Design-2 (SIASD-2), with potential applications in image processing and deep neural networks. The proposed designs are implemented in MAGIC topology for comparison, named as Serial MAGIC-based Approximate Subtractor Design-1 (SMASD-1) and Serial MAGIC-based Approximate Subtractor Design-2 (SMASD-2). Moreover, these proposed subtractor designs are extended to design magnitude comparators. IMPLY-based approximate designs improve the overall latency up to 1.67× with energy savings in the range of 17.4% to 40.3% while occupying the same number of memristors for SIASD-1 and an increase of 3 to 5 memristors for SIASD-2, compared to the best existing exact 8-bit serial IMPLY subtractor. SMASD-1 and SMASD-2 improve the latency up to 1.43×, and energy efficiency are up by 77.6% compared to other MAGIC-based exact designs. Additionally, as comparators, the SIASD-1 and SIASD-2 are up to 4.93× faster with energy reduction up to 79.7% compared to their IMPLY-based equivalents. Similarly, the SMASD-1 and SMASD-2 reduce the latency up to 62% with area savings of 77%, compared to MAGIC-based equivalent designs. Furthermore, the proposed subtractor designs undergo analysis in an image processing application called Motion Detection, while the comparators are evaluated in Max Pooling operations. With Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) serving as assessment metrics, the proposed designs consistently demonstrate acceptable PSNR and SSIM values, affirming their suitability for these applications.
{"title":"High-Speed and Area-Efficient Serial IMPLY-Based Approximate Subtractor and Comparator for Image Processing and Neural Networks","authors":"Nandit Kaushik;B. Srinivasu","doi":"10.1109/TNANO.2024.3487223","DOIUrl":"https://doi.org/10.1109/TNANO.2024.3487223","url":null,"abstract":"In-Memory-Computing (IMC) through memristive architectures has recently gained traction owing to their capacity to perform logic operations within a crossbar, optimizing both area and speed constraints. This paper introduces two approximate serial IMPLY-based subtractor designs, denoted as Serial IMPLY-based Approximate Subtractor Design-1 (SIASD-1), Serial IMPLY-based Approximate Subtractor Design-2 (SIASD-2), with potential applications in image processing and deep neural networks. The proposed designs are implemented in MAGIC topology for comparison, named as Serial MAGIC-based Approximate Subtractor Design-1 (SMASD-1) and Serial MAGIC-based Approximate Subtractor Design-2 (SMASD-2). Moreover, these proposed subtractor designs are extended to design magnitude comparators. IMPLY-based approximate designs improve the overall latency up to 1.67× with energy savings in the range of 17.4% to 40.3% while occupying the same number of memristors for SIASD-1 and an increase of 3 to 5 memristors for SIASD-2, compared to the best existing exact 8-bit serial IMPLY subtractor. SMASD-1 and SMASD-2 improve the latency up to 1.43×, and energy efficiency are up by 77.6% compared to other MAGIC-based exact designs. Additionally, as comparators, the SIASD-1 and SIASD-2 are up to 4.93× faster with energy reduction up to 79.7% compared to their IMPLY-based equivalents. Similarly, the SMASD-1 and SMASD-2 reduce the latency up to 62% with area savings of 77%, compared to MAGIC-based equivalent designs. Furthermore, the proposed subtractor designs undergo analysis in an image processing application called Motion Detection, while the comparators are evaluated in Max Pooling operations. With Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) serving as assessment metrics, the proposed designs consistently demonstrate acceptable PSNR and SSIM values, affirming their suitability for these applications.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":"23 ","pages":"748-757"},"PeriodicalIF":2.1,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1109/JPHOTOV.2024.3438451
Navid Tavakoli;Pascal Koelblin;Michael Saliba
Photovoltaic (PV) module performance is primarily characterized by their current-voltage ( I-V ) measurements. However, the data obtained mostly contains errors. Commercial I-V curve tracking units are generally expensive, hard to transport, slow to respond, and limited at low irradiations. This article proposes a novel I-V tracer (SEPIV) based on an optimized single-ended primary inductance converter. The SEPIV comprises a linear variable dc load connected to the solar panel's output. In this study, the experimental performance of the SEPIV was compared with the outcomes of commercial and lab devices, which are PVPM 1000 C 40 (PVPM) and WAVELABS SINUS-3000 PRO, respectively. SEPIV's accuracy matched lab units and surpassed PVPM's. As a highlight of this study, the introduced setup can capture the I-V curves of PV modules up to 650 W, a maximum V OC of 60 V, and a maximum I SC of 20 A. In contrast to commercial units, the SEPIV measurement does not depend on irradiation level. Moreover, it has the Internet of Things capability through a Wi-Fi connection for remote measurement.
{"title":"Design and Development of a New Smart Portable I-V Tracer","authors":"Navid Tavakoli;Pascal Koelblin;Michael Saliba","doi":"10.1109/JPHOTOV.2024.3438451","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3438451","url":null,"abstract":"Photovoltaic (PV) module performance is primarily characterized by their current-voltage (\u0000<italic>I-V</i>\u0000) measurements. However, the data obtained mostly contains errors. Commercial \u0000<italic>I-V</i>\u0000 curve tracking units are generally expensive, hard to transport, slow to respond, and limited at low irradiations. This article proposes a novel \u0000<italic>I-V</i>\u0000 tracer (SEPIV) based on an optimized single-ended primary inductance converter. The SEPIV comprises a linear variable dc load connected to the solar panel's output. In this study, the experimental performance of the SEPIV was compared with the outcomes of commercial and lab devices, which are PVPM 1000 C 40 (PVPM) and WAVELABS SINUS-3000 PRO, respectively. SEPIV's accuracy matched lab units and surpassed PVPM's. As a highlight of this study, the introduced setup can capture the \u0000<italic>I-V</i>\u0000 curves of PV modules up to 650 W, a maximum \u0000<italic>V</i>\u0000<sub>OC</sub>\u0000 of 60 V, and a maximum \u0000<italic>I</i>\u0000<sub>SC</sub>\u0000 of 20 A. In contrast to commercial units, the SEPIV measurement does not depend on irradiation level. Moreover, it has the Internet of Things capability through a Wi-Fi connection for remote measurement.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"14 6","pages":"951-959"},"PeriodicalIF":2.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524163","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 : 2024-10-25DOI: 10.1109/TPS.2024.3412532
Edl Schamiloglu
{"title":"Editorial Editor-in-Chief Transition","authors":"Edl Schamiloglu","doi":"10.1109/TPS.2024.3412532","DOIUrl":"https://doi.org/10.1109/TPS.2024.3412532","url":null,"abstract":"","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":"52 7","pages":"2652-2652"},"PeriodicalIF":1.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10736389","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-25DOI: 10.1109/JPHOTOV.2024.3480752
{"title":"IEEE Open Access Publishing","authors":"","doi":"10.1109/JPHOTOV.2024.3480752","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2024.3480752","url":null,"abstract":"","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":"14 6","pages":"975-975"},"PeriodicalIF":2.5,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10736228","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142518125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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