Grant-free random access (RA) utilizing massive multiple-input multiple-output (MIMO) technology has attracted considerable attention in recent years due to its potential to enhance spectral efficiency. This paper introduces an innovative and advanced approach for the joint detection of users and estimation of channels in grant-free RA. The approach incorporates two distinct preamble structures: the single orthogonal preamble (SOP) and the concatenated orthogonal preamble (COP). The proposed algorithms make full use of the inherent quasiorthogonal characteristic of massive MIMO, thereby enabling the accurate estimation of user channels while effectively avoiding collisions in the preambles. As a result, these algorithms generate highly precise estimations of user channels. To substantiate the effectiveness of the proposed algorithms, this paper provides an extensive theoretical analysis and presents a comprehensive set of experimental results. These findings offer robust evidence for the efficacy of the algorithms in substantially bolstering the performance of grant-free RA. Additionally, we have conducted further research and analysis, which has led to additional insights and refinements in our proposed approach. Moreover, the experimental results validate the statistical significance and reliability of the performance enhancements achieved by these algorithms. Moreover, the proposed approach exhibits robustness in scenarios with different levels of user density and varying channel conditions. Through a thorough analysis of these scenarios, we showcase the versatility and applicability of our algorithms in real-world environments.
近年来，利用大规模多输入多输出（MIMO）技术的免授权随机接入（RA）因其提高频谱效率的潜力而备受关注。本文介绍了一种创新的先进方法，用于在无补助随机接入中联合检测用户和估计信道。该方法包含两种不同的前导码结构：单正交前导码（SOP）和并集正交前导码（COP）。所提出的算法充分利用了大规模多输入多输出（MIMO）固有的准正交特性，从而实现了对用户信道的精确估计，同时有效避免了前置信号中的碰撞。因此，这些算法能产生高度精确的用户信道估计。为了证实所提算法的有效性，本文进行了广泛的理论分析，并给出了一组全面的实验结果。这些研究结果提供了有力的证据，证明了这些算法在大幅提高免授权 RA 性能方面的功效。此外，我们还进行了进一步的研究和分析，从而对我们提出的方法有了更多的了解和改进。此外，实验结果也验证了这些算法在提高性能方面的统计意义和可靠性。此外，所提出的方法在不同用户密度和不同信道条件的情况下都表现出稳健性。通过对这些场景的深入分析，我们展示了算法在现实环境中的多功能性和适用性。
{"title":"Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems","authors":"Yang Yang, Guang Song, Hui Liu","doi":"10.1155/2023/1672421","DOIUrl":"https://doi.org/10.1155/2023/1672421","url":null,"abstract":"Grant-free random access (RA) utilizing massive multiple-input multiple-output (MIMO) technology has attracted considerable attention in recent years due to its potential to enhance spectral efficiency. This paper introduces an innovative and advanced approach for the joint detection of users and estimation of channels in grant-free RA. The approach incorporates two distinct preamble structures: the single orthogonal preamble (SOP) and the concatenated orthogonal preamble (COP). The proposed algorithms make full use of the inherent quasiorthogonal characteristic of massive MIMO, thereby enabling the accurate estimation of user channels while effectively avoiding collisions in the preambles. As a result, these algorithms generate highly precise estimations of user channels. To substantiate the effectiveness of the proposed algorithms, this paper provides an extensive theoretical analysis and presents a comprehensive set of experimental results. These findings offer robust evidence for the efficacy of the algorithms in substantially bolstering the performance of grant-free RA. Additionally, we have conducted further research and analysis, which has led to additional insights and refinements in our proposed approach. Moreover, the experimental results validate the statistical significance and reliability of the performance enhancements achieved by these algorithms. Moreover, the proposed approach exhibits robustness in scenarios with different levels of user density and varying channel conditions. Through a thorough analysis of these scenarios, we showcase the versatility and applicability of our algorithms in real-world environments.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"48 5","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139004476","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}
Achmad Rizal, S. Hadiyoso, S. Aulia, I. Wijayanto, Triwiyanto, Ziani Said
The electroencephalogram (EEG) examination provides information on the brain’s electricity, especially in cases of epilepsy. Since the characteristics of EEG signals are nonlinear and nonstationary, visual inspection becomes very difficult. To overcome this problem, digital EEG signal processing was developed. Automatic epileptic EEG recognition is an area of interest on which much research focuses. The complexity approach to EEG signal analysis is interesting to be used as feature extraction, referring to the nonlinear characteristics of the signal. This study proposed an automatic epileptic EEG classification method based on the multiscale Hjorth descriptor measurement. EEG signals consisting of normal, interictal, and seizure (ictal) were simulated. The signal is scaled into new signals using the coarse-grained procedure on a scale of 1–20. Then, the Hjorth parameter which consists of activity, mobility, and complexity is calculated on the new signal. This process produces a feature vector that is used in the classification stage. Support vector machine (SVM) is used to evaluate the proposed feature extraction method. Simulation results showed that the Hjorth parameter on a scale of 1–15 yields 99.5% accuracy. The proposed method is expected to be applied to digital EEG for seizure detection and prediction.
{"title":"Multiscale Hjorth Descriptor on Epileptic EEG Classification","authors":"Achmad Rizal, S. Hadiyoso, S. Aulia, I. Wijayanto, Triwiyanto, Ziani Said","doi":"10.1155/2023/4961637","DOIUrl":"https://doi.org/10.1155/2023/4961637","url":null,"abstract":"The electroencephalogram (EEG) examination provides information on the brain’s electricity, especially in cases of epilepsy. Since the characteristics of EEG signals are nonlinear and nonstationary, visual inspection becomes very difficult. To overcome this problem, digital EEG signal processing was developed. Automatic epileptic EEG recognition is an area of interest on which much research focuses. The complexity approach to EEG signal analysis is interesting to be used as feature extraction, referring to the nonlinear characteristics of the signal. This study proposed an automatic epileptic EEG classification method based on the multiscale Hjorth descriptor measurement. EEG signals consisting of normal, interictal, and seizure (ictal) were simulated. The signal is scaled into new signals using the coarse-grained procedure on a scale of 1–20. Then, the Hjorth parameter which consists of activity, mobility, and complexity is calculated on the new signal. This process produces a feature vector that is used in the classification stage. Support vector machine (SVM) is used to evaluate the proposed feature extraction method. Simulation results showed that the Hjorth parameter on a scale of 1–15 yields 99.5% accuracy. The proposed method is expected to be applied to digital EEG for seizure detection and prediction.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"7 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139008094","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}
Di Hu, Zhong Chen, Wei Yang, Taiyun Zhu, Y. Ke, Kaiyang Yin
Different types of partial discharge (PD) cause different damages to gas-insulated substation (GIS), so it is very important to correctly identify the type of PD for evaluating the GIS insulation condition. The traditional PD pattern recognition algorithm has the limitations of low recognition accuracy and slow recognition speed in engineering applications. To effectively diagnose the GIS PD type and safeguard the safe and reliable operation of the distribution network, a GIS PD method based on improved CBAM-ResNet was proposed in this paper. And the improved CBAM-ResNet takes advantage of the residual neural network and attention mechanism. In particular, the channel attention module and the spatial attention module are connected in parallel in the improved CBAM. The experimental results showed that the GIS PD pattern recognition method proposed herein has a recognition rate of 93.58%, 95.00%, 93.55%, and 93.88% against the four PD types. Compared with the traditional PD pattern recognition algorithm, the algorithm has the advantages of a lightweight model and more accurate recognition results, which carry better engineering application values.
{"title":"A GIS Partial Discharge Pattern Recognition Method Based on Improved CBAM-ResNet","authors":"Di Hu, Zhong Chen, Wei Yang, Taiyun Zhu, Y. Ke, Kaiyang Yin","doi":"10.1155/2023/9948438","DOIUrl":"https://doi.org/10.1155/2023/9948438","url":null,"abstract":"Different types of partial discharge (PD) cause different damages to gas-insulated substation (GIS), so it is very important to correctly identify the type of PD for evaluating the GIS insulation condition. The traditional PD pattern recognition algorithm has the limitations of low recognition accuracy and slow recognition speed in engineering applications. To effectively diagnose the GIS PD type and safeguard the safe and reliable operation of the distribution network, a GIS PD method based on improved CBAM-ResNet was proposed in this paper. And the improved CBAM-ResNet takes advantage of the residual neural network and attention mechanism. In particular, the channel attention module and the spatial attention module are connected in parallel in the improved CBAM. The experimental results showed that the GIS PD pattern recognition method proposed herein has a recognition rate of 93.58%, 95.00%, 93.55%, and 93.88% against the four PD types. Compared with the traditional PD pattern recognition algorithm, the algorithm has the advantages of a lightweight model and more accurate recognition results, which carry better engineering application values.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"18 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139009491","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}
Aqib Raqeeb, Fahim Shah, Zaheer Alam, Subhashree Choudhury, Bilal Khan, R. Palanisamy
Bearings are critical components in modern manufacturing, yet they are prone to failures in induction machines. Detecting these faults early can reduce repair costs. To achieve efficient and accurate fault detection, we explore vibration-based analysis. Traditional methods rely on manual feature extraction, which is time-consuming. In contrast, our work leverages deep learning, particularly convolutional neural networks, to automatically extract fault features from raw data. We investigate various image sizes (16 × 16, 32 × 32, 64 × 64, 128 × 128, 256 × 256) and their performance in bearing fault diagnosis. Our convolutional neural networks-based approach is compared to traditional methods such as support vector machine, nearest neighbors, and artificial neural networks. Results demonstrate the superior performance of our data-driven fault diagnosis using convolutional neural networks.
{"title":"Data-Driven Bearing Fault Diagnosis for Induction Motor","authors":"Aqib Raqeeb, Fahim Shah, Zaheer Alam, Subhashree Choudhury, Bilal Khan, R. Palanisamy","doi":"10.1155/2023/7173989","DOIUrl":"https://doi.org/10.1155/2023/7173989","url":null,"abstract":"Bearings are critical components in modern manufacturing, yet they are prone to failures in induction machines. Detecting these faults early can reduce repair costs. To achieve efficient and accurate fault detection, we explore vibration-based analysis. Traditional methods rely on manual feature extraction, which is time-consuming. In contrast, our work leverages deep learning, particularly convolutional neural networks, to automatically extract fault features from raw data. We investigate various image sizes (16 × 16, 32 × 32, 64 × 64, 128 × 128, 256 × 256) and their performance in bearing fault diagnosis. Our convolutional neural networks-based approach is compared to traditional methods such as support vector machine, nearest neighbors, and artificial neural networks. Results demonstrate the superior performance of our data-driven fault diagnosis using convolutional neural networks.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"9 28","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139237243","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}
R. Al-Nima, Marwa Mawfaq Mohamedsheet Al-Hatab, Maysaloon Abed Qasim
Deoxyribonucleic acid (DNA) can be considered as one of the most useful biometrics. It has effectively been used for recognizing persons. However, it seems that there is still a need to propose a new approach for verifying humans, especially after the recent big wars, where too many people lost and die. This approach should have the capability to provide high personal verification performance. In this paper, a personal recognition approach based on artificial intelligence is proposed. This approach is called the artificial DNA algorithm for recognition (ADAR). It utilizes a unique identity for each person acquired from DNA nucleotides, and it can verify individuals efficiently with high performance. The ADAR has been designed and applied to multiple datasets, namely, the DNA classification (DC), sample DNA sequence (SDS), human DNA sequences (HDS), and DNA sequences (DS). For all datasets, a low value of 0% is achieved for each of the false acceptance rate (FAR) and false rejection rate (FRR).
脱氧核糖核酸（DNA）可以说是最有用的生物识别技术之一。它已被有效地用于识别人的身份。然而，似乎仍有必要提出一种新的方法来验证人类，特别是在最近的大战之后，有太多的人失去了生命。这种方法应该能够提供较高的个人验证性能。本文提出了一种基于人工智能的个人识别方法。这种方法被称为人工 DNA 识别算法（ADAR）。它利用从 DNA 核苷酸中获取的每个人的唯一身份，可以高效、高性能地验证个人。ADAR 已被设计并应用于多个数据集，即 DNA 分类（DC）、样本 DNA 序列（SDS）、人类 DNA 序列（HDS）和 DNA 序列（DS）。在所有数据集中，错误接受率（FAR）和错误拒绝率（FRR）均达到了 0% 的低值。
{"title":"An Artificial Intelligence Approach for Verifying Persons by Employing the Deoxyribonucleic Acid (DNA) Nucleotides","authors":"R. Al-Nima, Marwa Mawfaq Mohamedsheet Al-Hatab, Maysaloon Abed Qasim","doi":"10.1155/2023/6678837","DOIUrl":"https://doi.org/10.1155/2023/6678837","url":null,"abstract":"Deoxyribonucleic acid (DNA) can be considered as one of the most useful biometrics. It has effectively been used for recognizing persons. However, it seems that there is still a need to propose a new approach for verifying humans, especially after the recent big wars, where too many people lost and die. This approach should have the capability to provide high personal verification performance. In this paper, a personal recognition approach based on artificial intelligence is proposed. This approach is called the artificial DNA algorithm for recognition (ADAR). It utilizes a unique identity for each person acquired from DNA nucleotides, and it can verify individuals efficiently with high performance. The ADAR has been designed and applied to multiple datasets, namely, the DNA classification (DC), sample DNA sequence (SDS), human DNA sequences (HDS), and DNA sequences (DS). For all datasets, a low value of 0% is achieved for each of the false acceptance rate (FAR) and false rejection rate (FRR).","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"55 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139263429","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}
The fundamental challenge in video generation is not only generating high-quality image sequences but also generating consistent frames with no abrupt shifts. With the development of generative adversarial networks (GANs), great progress has been made in image generation tasks which can be used for facial expression synthesis. Most previous works focused on synthesizing frontal and near frontal faces and manual annotation. However, considering only the frontal and near frontal area is not sufficient for many real-world applications, and manual annotation fails when the video is incomplete. AffineGAN, a recent study, uses affine transformation in latent space to automatically infer the expression intensity value; however, this work requires extraction of the feature of the target ground truth image, and the generated sequence of images is also not sufficient. To address these issues, this study is proposed to infer the expression of intensity value automatically without the need to extract the feature of the ground truth images. The local dataset is prepared with frontal and with two different face positions (the left and right sides). Average content distance metrics of the proposed solution along with different experiments have been measured, and the proposed solution has shown improvements. The proposed method has improved the ACD-I of affine GAN from 1.606 ± 0.018 to 1.584 ± 0.00, ACD-C of affine GAN from 1.452 ± 0.008 to 1.430 ± 0.009, and ACD-G of affine GAN from 1.769 ± 0.007 to 1.744 ± 0.01, which is far better than AffineGAN. This work concludes that integrating self-attention into the generator network improves a quality of the generated images sequences. In addition, evenly distributing values based on frame size to assign expression intensity value improves the consistency of image sequences being generated. It also enables the generator to generate different frame size videos while remaining within the range [0, 1].
{"title":"Attention-Based Image-to-Video Translation for Synthesizing Facial Expression Using GAN","authors":"Kidist Alemayehu, Worku Jifara, Demissie Jobir","doi":"10.1155/2023/6645356","DOIUrl":"https://doi.org/10.1155/2023/6645356","url":null,"abstract":"The fundamental challenge in video generation is not only generating high-quality image sequences but also generating consistent frames with no abrupt shifts. With the development of generative adversarial networks (GANs), great progress has been made in image generation tasks which can be used for facial expression synthesis. Most previous works focused on synthesizing frontal and near frontal faces and manual annotation. However, considering only the frontal and near frontal area is not sufficient for many real-world applications, and manual annotation fails when the video is incomplete. AffineGAN, a recent study, uses affine transformation in latent space to automatically infer the expression intensity value; however, this work requires extraction of the feature of the target ground truth image, and the generated sequence of images is also not sufficient. To address these issues, this study is proposed to infer the expression of intensity value automatically without the need to extract the feature of the ground truth images. The local dataset is prepared with frontal and with two different face positions (the left and right sides). Average content distance metrics of the proposed solution along with different experiments have been measured, and the proposed solution has shown improvements. The proposed method has improved the ACD-I of affine GAN from 1.606 ± 0.018 to 1.584 ± 0.00, ACD-C of affine GAN from 1.452 ± 0.008 to 1.430 ± 0.009, and ACD-G of affine GAN from 1.769 ± 0.007 to 1.744 ± 0.01, which is far better than AffineGAN. This work concludes that integrating self-attention into the generator network improves a quality of the generated images sequences. In addition, evenly distributing values based on frame size to assign expression intensity value improves the consistency of image sequences being generated. It also enables the generator to generate different frame size videos while remaining within the range [0, 1].","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"13 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134957588","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}
As global energy consumption continues to increase, increased utilization and adaptation of renewable energy resources have tremendously increased over the last decades. Unfortunately, despite the many benefits of renewable energy resources, the intermittent nature of generation and the far distance of large installations from demand centers have tremendous effects on the connecting grid’s stability. In this study, high-voltage direct current (HVDC) systems are proposed as a solution for stable and reliable grid operation in the presence of large renewable energy installations. This research investigates the deployment of an HVDC system into an entire network rather than studying it as an isolated radial system. Various power system analysis functions for both static and dynamic conditions are used to study the effect of integrating an HVDC system on the overall network’s stability. To verify the proposed approach, Jordan’s national electric grid was modeled and used as a case study. The results show when deploying HVDC transmission, losses are reduced by 70% from the baseline case, in addition to better handling of contingency events and enhanced grid’s stability when examining the generator’s rotor angle and speed. Rigorous modeling and simulations of the proposed system structure show the feasibility and prove the advantages of modern HVDC systems over HVAC counterparts.
{"title":"Power System Analysis of Moving from HVAC to HVDC in the Presence of Renewable Energy Resources","authors":"Osama Saadeh, Baher Abu Sba, Zakariya Dalala","doi":"10.1155/2023/8527308","DOIUrl":"https://doi.org/10.1155/2023/8527308","url":null,"abstract":"As global energy consumption continues to increase, increased utilization and adaptation of renewable energy resources have tremendously increased over the last decades. Unfortunately, despite the many benefits of renewable energy resources, the intermittent nature of generation and the far distance of large installations from demand centers have tremendous effects on the connecting grid’s stability. In this study, high-voltage direct current (HVDC) systems are proposed as a solution for stable and reliable grid operation in the presence of large renewable energy installations. This research investigates the deployment of an HVDC system into an entire network rather than studying it as an isolated radial system. Various power system analysis functions for both static and dynamic conditions are used to study the effect of integrating an HVDC system on the overall network’s stability. To verify the proposed approach, Jordan’s national electric grid was modeled and used as a case study. The results show when deploying HVDC transmission, losses are reduced by 70% from the baseline case, in addition to better handling of contingency events and enhanced grid’s stability when examining the generator’s rotor angle and speed. Rigorous modeling and simulations of the proposed system structure show the feasibility and prove the advantages of modern HVDC systems over HVAC counterparts.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"4 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391523","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}
Underwater wireless sensor nodes comprise hundreds to thousands of battery-operated sensor nodes with limited bandwidth. These networks are employed to transmit the data with enhanced quality of service (QoS). However, efficient data routing is the most challenging obstacle in many underwater applications. To solve the issues in underwater sensor nodes, the hybridized cluster-based geographical opportunistic routing protocol with distance vector establishment has been proposed to transmit the data efficiently. Primarily, the proposed methodology finds out the shortest path with minimal hop count whereas the void node can be updated with infinite hop count. Thereafter, the sleep/wake scheduling and waiting mechanism and periodic beaconing algorithm are incorporated into the proposed model to attain a higher packet delivery ratio with minimal energy consumption. This proper scheduling and optimal cluster routing enhance the continuous data transmission in underwater applications. The simulation result reveals that the proposed method achieves better energy efficiency and higher network lifetime when compared with the existing clustering methods.
{"title":"A Novel Hybridized Cluster-Based Geographical Opportunistic Routing Protocol for Effective Data Routing in Underwater Wireless Sensor Networks","authors":"B. Ragavi, V. Baranidharan, K. Ramash Kumar","doi":"10.1155/2023/5567483","DOIUrl":"https://doi.org/10.1155/2023/5567483","url":null,"abstract":"Underwater wireless sensor nodes comprise hundreds to thousands of battery-operated sensor nodes with limited bandwidth. These networks are employed to transmit the data with enhanced quality of service (QoS). However, efficient data routing is the most challenging obstacle in many underwater applications. To solve the issues in underwater sensor nodes, the hybridized cluster-based geographical opportunistic routing protocol with distance vector establishment has been proposed to transmit the data efficiently. Primarily, the proposed methodology finds out the shortest path with minimal hop count whereas the void node can be updated with infinite hop count. Thereafter, the sleep/wake scheduling and waiting mechanism and periodic beaconing algorithm are incorporated into the proposed model to attain a higher packet delivery ratio with minimal energy consumption. This proper scheduling and optimal cluster routing enhance the continuous data transmission in underwater applications. The simulation result reveals that the proposed method achieves better energy efficiency and higher network lifetime when compared with the existing clustering methods.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"4 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135873890","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}
Joseph Amajama, Emmanuel N. Asagha, Ogri J. Ushie, Prince C. Iwuji, Julius U. Akwagiobe, Fina O. Faithpraise, Alexander I. Ikeuba, Donatus E. Bassey
This research investigated radio refractivity impact on signal strength of mobile communication. The mobile communication signal strengths of two popular networks in Nigeria, 9Mobile and MTN, were considered. In the 2100 MHz-3 G band, 9Mobile transmits in the downlink spectrum of 2130.00–2140.00 MHz, while MTN transmits in the downlink spectrum of 2110.00–2120.00 MHz. Also, 9Mobile transmits in the downlink spectrum of 791–821 MHz in the 800 MHz band and 1805–1880 MHz in the 1800 MHz, while MTN transmits in the downlink spectrums of 2620–2690 MHz in the 2600 MHz band; all in the 4 G band. Using the instrument of a mobile station in each station (location) in some selected cities in southern Nigeria, the signal strengths were measured. A cell signal monitor (version 5.1.1) mobile application installed in an Android (transceiver) device (having two SIM slots) constituted the mobile station. To achieve high accuracy, there was a restriction in measuring transmission from specific cells. Hourly measurement of signal strengths was carried out and instantaneously corresponding weather parameters were recorded. Weather parameters for this investigation; atmospheric temperature and pressure; and relative humidity were excerpted online from the Nigeria Meteorological Agency (NIMET) hourly weather report for the various cities where the stations were situated. The hourly radio refractivity was computed using the 2015 International Telecommunication Union–Radio-communication sector (ITU-R) recommended model. Overall, the results indicate that there was no established linear relationship between signal strength and radio refractivity since the overall average R value is 0.0123691 and the overall average standard deviation of R values is 0.1112165. The inconsistencies in the linear relationships obtained from different locations and cells could be due to variations in topography, antenna properties, seasonal variations, wind and position, and distance of the receiver from the transmitter.
{"title":"Radio Refractivity Impact on Signal Strength of Mobile Communication","authors":"Joseph Amajama, Emmanuel N. Asagha, Ogri J. Ushie, Prince C. Iwuji, Julius U. Akwagiobe, Fina O. Faithpraise, Alexander I. Ikeuba, Donatus E. Bassey","doi":"10.1155/2023/3052241","DOIUrl":"https://doi.org/10.1155/2023/3052241","url":null,"abstract":"This research investigated radio refractivity impact on signal strength of mobile communication. The mobile communication signal strengths of two popular networks in Nigeria, 9Mobile and MTN, were considered. In the 2100 MHz-3 G band, 9Mobile transmits in the downlink spectrum of 2130.00–2140.00 MHz, while MTN transmits in the downlink spectrum of 2110.00–2120.00 MHz. Also, 9Mobile transmits in the downlink spectrum of 791–821 MHz in the 800 MHz band and 1805–1880 MHz in the 1800 MHz, while MTN transmits in the downlink spectrums of 2620–2690 MHz in the 2600 MHz band; all in the 4 G band. Using the instrument of a mobile station in each station (location) in some selected cities in southern Nigeria, the signal strengths were measured. A cell signal monitor (version 5.1.1) mobile application installed in an Android (transceiver) device (having two SIM slots) constituted the mobile station. To achieve high accuracy, there was a restriction in measuring transmission from specific cells. Hourly measurement of signal strengths was carried out and instantaneously corresponding weather parameters were recorded. Weather parameters for this investigation; atmospheric temperature and pressure; and relative humidity were excerpted online from the Nigeria Meteorological Agency (NIMET) hourly weather report for the various cities where the stations were situated. The hourly radio refractivity was computed using the 2015 International Telecommunication Union–Radio-communication sector (ITU-R) recommended model. Overall, the results indicate that there was no established linear relationship between signal strength and radio refractivity since the overall average R value is 0.0123691 and the overall average standard deviation of R values is 0.1112165. The inconsistencies in the linear relationships obtained from different locations and cells could be due to variations in topography, antenna properties, seasonal variations, wind and position, and distance of the receiver from the transmitter.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"277 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135872704","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}
Failure of vulnerable lines in the power system often results in tidal shifts, and triggering chain failures and their corresponding transmission sections are concentrated manifestations of the weak links in the power system. It is very important to identify the vulnerable lines and search the transmission section to prevent the chain faults as well as to analyze the stability of the power system. Aiming at the problems of inaccurate search of vulnerable lines, difficulties adapting to the complex and changing power system as well as wrong selection and omission of transmission section search in the existing references, this paper proposes an algorithm for searching vulnerable lines and their key transmission sections based on the graph theory and PMU (phasor measurement unit) data. First, the method combines with the graph theory and PMU data to construct the grid topology map. Second, the comprehensive indicators for screening vulnerable lines are proposed by fully considering the network topology and line capacity, which combines with power exchange efficiency and energy fluctuation probability. Third, the distance matrix in the Floyd algorithm is transformed into a unit group that can store more elements, which reduces the traversal times of the algorithm and improves computational efficiency. The fast localization of transmission cross sections associated with vulnerable lines is realized. Finally, the critical transmission cross sections are screened according to the line outage distribution factor and line safety margin. The IEEE 39-bus system is selected for simulation experiments, and the simulation results show that the key transmission section search method proposed in this paper can better adapt to the variable power grid and is faster and more accurate than the other common method.
{"title":"Key Transmission Section Search Based on Graph Theory and PMU Data for Vulnerable Line Identification in Power System","authors":"Miao Yu, Shouzhi Zhang, Fang Shi, Jianqun Sun, Jingjing Wei, Yixiao Wu, Jingxuan Hu","doi":"10.1155/2023/8643537","DOIUrl":"https://doi.org/10.1155/2023/8643537","url":null,"abstract":"Failure of vulnerable lines in the power system often results in tidal shifts, and triggering chain failures and their corresponding transmission sections are concentrated manifestations of the weak links in the power system. It is very important to identify the vulnerable lines and search the transmission section to prevent the chain faults as well as to analyze the stability of the power system. Aiming at the problems of inaccurate search of vulnerable lines, difficulties adapting to the complex and changing power system as well as wrong selection and omission of transmission section search in the existing references, this paper proposes an algorithm for searching vulnerable lines and their key transmission sections based on the graph theory and PMU (phasor measurement unit) data. First, the method combines with the graph theory and PMU data to construct the grid topology map. Second, the comprehensive indicators for screening vulnerable lines are proposed by fully considering the network topology and line capacity, which combines with power exchange efficiency and energy fluctuation probability. Third, the distance matrix in the Floyd algorithm is transformed into a unit group that can store more elements, which reduces the traversal times of the algorithm and improves computational efficiency. The fast localization of transmission cross sections associated with vulnerable lines is realized. Finally, the critical transmission cross sections are screened according to the line outage distribution factor and line safety margin. The IEEE 39-bus system is selected for simulation experiments, and the simulation results show that the key transmission section search method proposed in this paper can better adapt to the variable power grid and is faster and more accurate than the other common method.","PeriodicalId":46573,"journal":{"name":"Journal of Electrical and Computer Engineering","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136019721","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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