{"title":"Compact Coradiator MIMO Antenna for Super Wideband Applications","authors":"K. Srividhya;P. Jothilakshmi","doi":"10.1109/ICJECE.2023.3312590","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3312590","url":null,"abstract":"This article presents a compact planar circular monopole antenna with a shared radiator for super wideband (SWB) applications compatible with multiple-input multiple-output (MIMO) configurations. The novelty lies in the coradiator being a simple circular structure enhanced with stepped impedance feed. The antenna uses a partial ground with a stepped system designed over an RO3003 substrate, with an overall dimension of 29 \u0000<inline-formula> <tex-math>$times $ </tex-math></inline-formula>\u0000 29 \u0000<inline-formula> <tex-math>$times $ </tex-math></inline-formula>\u0000 0.8 mm3. The antenna operates over a wideband from 4 to 50 GHz and beyond. The system works in dual polarization with a shared radiator and offers a peak gain value of 7.15 dBi with a high efficiency of 80%–97%. The proposed antenna provides stunning isolation between the dual orthogonal ports of the shared radiator. The diversity performance of the antenna in terms of envelope correlation coefficient (ECC < 0.002), multiplexing efficiency (ME = −3.111 dB), diversity gain (DG > 9.995 dB), and mean effective gain (MEG = −3.01 dB) are also studied and analyzed. The designed structure is fabricated, and antenna parameters are measured. The proposed design meets the desired values, and measured parameters agree with the simulated ones, rendering the antenna a suitable candidate for SWB-MIMO applications. Combining the two standards would help breakthrough in wireless communication. With its wide bandwidth, the proposed design finds scope in Internet of Things (IoT), future 5G, and emerging 6G technologies.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"348-357"},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138550319","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}
{"title":"Efficient Edge Computing Device for Traffic Monitoring Using Deep Learning Detectors","authors":"Yixin Huangfu;Masoumeh Ahrabi;Rondon Tahal;Junbo Huang;Arta Mohammad-Alikhani;Steffen Reymann;Babak Nahid-Mobarakeh;Shahram Shirani;Saeid Habibi","doi":"10.1109/ICJECE.2023.3305323","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3305323","url":null,"abstract":"This article presents a smart camera device for traffic monitoring at intersections. The device is based on the Nvidia Jetson Nano, a small form factor, efficient artificial intelligence (AI) computational device that is capable of deep learning inference. The state-of-the-art deep learning detection models were investigated, and the full YOLOv4 was selected for deployment on the edge device. The deployed model and analytics achieved an average frame rate of 7.8 frames/s (fps). A fisheye lens and camera were selected and integrated with the Jetson processing unit. The original YOLOv4 performed less optimally on fisheye-distorted images. Therefore, we applied transfer learning to the YOLOv4 model using data collected from a local intersection. The final models were evaluated in three different use cases detecting different types of road objects, achieving 100% precision and around 90% accuracy when detecting road vehicles in real time. This article demonstrates the feasibility of running large deep learning models for traffic monitoring services, even on resource-restrained AI edge devices.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"371-379"},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138550247","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}
A. F. M. Shahen Shah;Muhammet Ali Karabulut;Haci Ilhan;Ufuk Tureli
{"title":"Influence of Channel Fading and Capture for Performance Evaluation in Vehicular Communications","authors":"A. F. M. Shahen Shah;Muhammet Ali Karabulut;Haci Ilhan;Ufuk Tureli","doi":"10.1109/ICJECE.2023.3308478","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3308478","url":null,"abstract":"Autonomy and intelligent transportation systems (ITSs) have recently received increased interest for vehicular ad hoc networks (VANETs). In addition, the impending 5G and 6G technologies will result in substantial advancements for VANETs. The IEEE 802.11p summarizes specifications of physical (PHY) and medium access control (MAC) layers for VANETs. Although IEEE 802.11p MAC performance has been investigated, analytical methods need improvement. Bit error and channel capture influence the performance of vehicular communications in real-world transmission. These effects are investigated separately in previous works. In this article, an extensive study is provided that integrates these two major factors. In VANETs, the influence of channel fading and capture on IEEE 802.11p is investigated analytically using a Markov chain model. For Nakagami-m, Rayleigh, and Rician fading channels, performance-impacting factors are considered, and the relationships between parameters as well as performance metrics are derived. The probability of unsuccessful and successful transmission, outage probability, probability of frame capture, throughput, bit error rate (BER), and delay terms are attained. Moreover, simulation results are provided, which verify analytical studies.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"322-332"},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138491028","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}
{"title":"Detecting Wireless Signal Noise in Mobile Radio Communications Using Spatiotemporal AnoGAN-Based Approaches","authors":"Tae-Young Kim;Eunil Park","doi":"10.1109/ICJECE.2023.3320958","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3320958","url":null,"abstract":"With the development of radio modulation technologies for communication and wireless applications, several studies have been conducted to reduce and eliminate noise during signal transmission. Although the influence of noise can be effectively addressed, it has become a popular research topic in mobile communications. Moreover, in recent telecommunication systems, owing to their complexity and comprehensive protocols, which require a large number of mathematical and engineering approaches, predicting and classifying noise is difficult. Thus, to effectively address these challenges, we propose a spatiotemporal AnoGAN to detect the noise that can occur during radio modulation. In our approach, we assemble a set of AnoGANs based on convolutional neural networks (CNNs) and long short-term memory (LSTM) to enable the system to learn the time-series features of the radio modulation signal and shape expressed in complex planes. The proposed spatiotemporal AnoGAN can discriminate the interference caused by noise without any annotation of anomalies using a generator and discriminator. The proposed spatiotemporal AnoGAN achieves a 91.4% recall in digitally modulated signals that were previously difficult to identify. Through an empirical analysis of the proposed method, we observed that the spatiotemporal AnoGAN accurately identified abnormal interference signals.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"310-321"},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138491037","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}
Hariharan Ramamoorthy;Mohan Ramasundaram;Raja Soosaimarian Peter Raj;Krunal Randive
{"title":"TransAttU-Net Deep Neural Network for Brain Tumor Segmentation in Magnetic Resonance Imaging","authors":"Hariharan Ramamoorthy;Mohan Ramasundaram;Raja Soosaimarian Peter Raj;Krunal Randive","doi":"10.1109/ICJECE.2023.3289609","DOIUrl":"10.1109/ICJECE.2023.3289609","url":null,"abstract":"A brain tumor is a deformity in the tissue where cells divide promptly and uncontrollably. As a consequence, the tumor expands. It is hypothesized that a neural network can successfully identify and predict brain tumors, two of the most challenging medical problems now facing doctors. The abundance of information enhances the diagnostic potential of magnetic resonance imaging (MRI) which provides the anatomical features of brain tumors. To improve the efficiency of the semantic segmentation architecture, we introduce a novel transformer-based attention U-shaped network called TransAttU-Net, in which the multilevel guided attention and multiscale skip connection operate simultaneously and which is also used to extract the pixel on the tumor area. Initially, the input image data are altered and undergo further processing using various preprocessing techniques. Methods such as these can be used to resize or rescale features, data augmentation, reverse or flip data, and alter the orientation of data. These procedures are required before sending data to the TransAttU-Net deep learning (DL) model. The algorithm attained a degree of accuracy on the BraTS 2019, i.e., the dataset provided in multimodal brain tumor image segmentation challenge and BraTS 2020 dataset, indicating great performance on BraTS 2020 dataset. The performance metrics of the models are evaluated using and results are discussed in this article.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"298-309"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134891010","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}
{"title":"A New Adaptive POL Converter Controller Design to Improve Bus Voltage Stability for DC Microgrid Application","authors":"Rohit Kumar Rastogi;Manoj Tripathy","doi":"10.1109/ICJECE.2023.3288928","DOIUrl":"10.1109/ICJECE.2023.3288928","url":null,"abstract":"This article describes an adaptive resonance frequency extraction-based dc–dc converter controller to stabilize the dc microgrid (dc MG). The dc MG becomes prone to instability due to the excessive application of constant power loads (CPLs) and their variations. Under such conditions, the source-side control techniques for the stabilization of dc MG systems fail. Therefore, to stabilize dc MG systems, the load-side control methods are alternate approaches to improve the stability of dc MG. In this article, a new feed-forward control technique is proposed to improve the stability of the dc MG. In the proposed method, the input impedance of the load-side dc–dc converter is modified by the phase compensation method without realizing a total magnitude separation \u0000<inline-formula> <tex-math>$(Z_{text {os}}$ </tex-math></inline-formula>\u0000 and \u0000<inline-formula> <tex-math>$y_{text {iL}}=1/Z_{text {iL}}) $ </tex-math></inline-formula>\u0000 to stabilize the dc MG system. The investigation analyzes the possibility of instability across the operational frequency spectrum. Based on that, a new feed-forward loop compensator is derived, which is a function of the center frequency to make it adaptive to load variations. After that, the derived compensator is realized for voltage mode control of the buck converter. It reduces the dc MG bus voltage oscillations without increasing system complexity and dissipation. The results of the MATLAB® simulation are compared with suggested and existing control methods. Moreover, it was discovered that the ripple in bus voltage decreased from 5.28% to 0.7%. And the settling durations of dc bus voltage and current were lowered from 0.5 and 0.25 s to 0.25 and 0.16 s, respectively.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"288-297"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134891016","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}
{"title":"Near-Infrared Handheld Probe and Imaging System for Breast Tumor Localization","authors":"Shadi Momtahen;Majid Shokoufi;Ramani Ramaseshan;Farid Golnaraghi","doi":"10.1109/ICJECE.2023.3259239","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3259239","url":null,"abstract":"Diffuse optical tomography (DOT) is a breast imaging modality that measures the functional characteristics of breast lesions using near-infrared (NIR) light to calculate the optical properties (scattering and absorption coefficients) of breast tissues. In this study, we have developed a NIR diffuse optical breast scanning (DOB-Scan) probe and evaluated a new imaging method based on a modified diffusion equation (MDE) for breast tumor localization. The probe is applied to breast phantoms to collect reflectance or the intensity of backscattered light. To measure the optical properties of the phantoms, we also calculated the reflectance theoretically, where we initially utilized the original diffusion equation (DE) to arrive at the theoretical reflectance. However, the DE algorithm has several limitations, which require modification of the DE formula to match the experimental results before obtaining the optical properties. Finally, the imaging algorithm is used to map the optical properties to cross-sectional images, which can localize the abnormalities in the breast phantoms. These findings suggest the DOB-Scan probe has valuable potential for breast cancer detection and diagnosis.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"246-255"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903511","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}
{"title":"Disk Forensics of VxWorks File Systems for Aircraft Security Analyse","authors":"Stephen McKeon;Vincent Roberge","doi":"10.1109/ICJECE.2023.3298846","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3298846","url":null,"abstract":"Modern avionics systems exhibit numerous networked electronic components ranging from sensors and actuators to dedicated subsystems, resulting in aircraft capable of processing and responding to information accurately, reliably, and in a timely fashion. Assuring the cyber security of these systems is a continual challenge and an active area of research; in the case where an aircraft has been compromised by a malicious actor, digital forensics can be utilized to investigate what and how the incident occurred. This research answers a simple, yet fundamental question on the security of aircraft: whether useful digital forensic artifacts be obtained from embedded real-time systems on aircraft. The highly reliable file system (HRFS) utilized by VxWorks was analyzed and described to align with the generalized descriptions of file system formats accepted in academia. The Sleuth Kit (TSK), an open-source forensic toolkit, was analyzed and extended to include functionality to support this file system, and a proof-of-concept implementation to obtain digital forensic artifacts from real-time operating systems on aircraft was developed. This research finds that the proposed implementation can perform file analysis and recovery from a VxWorks generated HRFS-formatted file system and can be generalized to show that embedded real-time systems can provide useful digital forensic artifacts.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"278-287"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903515","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}
Kumar Reddy Cheepati;E. Parimalasundar;K. Suresh;Ch. Rami Reddy;Mohammed M. Alqahtani;Muhammad Khalid
{"title":"Design of Triple Tuned Passive Harmonic Power Filter—A Novel Approach","authors":"Kumar Reddy Cheepati;E. Parimalasundar;K. Suresh;Ch. Rami Reddy;Mohammed M. Alqahtani;Muhammad Khalid","doi":"10.1109/ICJECE.2023.3296826","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3296826","url":null,"abstract":"Nowadays, there is a race between active and passive harmonic filters and still ambiguity persists. It is a proven fact that active harmonic filters (AHFs) are costly solutions though have proved better than passive harmonic filters. Except sizing and resonance problems, tuned passive harmonic filters (TPHFs) are proved to give economical solutions with little compromise on their performance. The accurate design of TPHFs gives a greater impact on its performance. The triple-TPHF (TTPHF) is essential to alleviate first three dominant ac side current harmonics simultaneously at the high voltage direct current (HVdc) converters and it is proved better than the single and double TPHFs. Existing equivalent methods of TTPHF design failed to give satisfactory performance under dynamic conditions. Hence, this article introduces a novel parametric method-based design of TTPHF, which will give better performance under static and dynamic loading conditions. The results also reveal that the proposed TTPHF design method will perform better than the existing methods.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"270-277"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903514","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}
{"title":"Estimation of Random Channel Gain for SISO Visible Light Communications System","authors":"Maysa Yaseen;Ayse E. Canbilen;Salama Ikki","doi":"10.1109/ICJECE.2023.3293031","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3293031","url":null,"abstract":"In this article, the estimation of random channel gain is studied for a single-input single-output (SISO) visible light communication (VLC) system. Five different estimators, namely maximum likelihood (ML), least square (LS), maximum posteriori probability (MAP), linear minimum mean square error (LMMSE), and minimum mean square error (MMSE), are proposed. The performances of these estimators are compared with the derived Bayesian Cramér–Rao lower bound (BCRLB), which can be used as a benchmark to evaluate the efficiency of the unbiased estimators. The presented analytical results, corroborated with Monte Carlo simulations, indicate that the MMSE estimator provides the best results. Additionally, the increasing number of pilot symbols as well as the ascending transmitted power improve the system performance. On the other hand, the noise variance has a negative effect on the channel estimation in terms of mean square error (MSE), and thus, it can dramatically reduce the performance of the estimators.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"262-269"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903513","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}