A micro grid system with renewable source operation control is a complex part as each source operates at different parameters. This renewable micro grid with multiple sources like solar plants, wind farm, fuel cell, battery backup has to be operated in both grid connected and standalone condition. During grid connection the micro grid, inverter has to inject power to the grid and compensate load in synchronization to the grid voltages. And during standalone condition the inverter is controlled with droop control module which stabilizes the voltage and frequency of the system even during grid disconnection. The droop control module is further updated with new advanced controllers like fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS) replacing the traditional proportional integral derivative (PID) and proportional integral (PI) controllers improving the response rate and for achieving better stabilization. This paper has comparative analysis of the micro grid system with different droop controllers under various operating conditions. Parameters like voltage magnitude (Vmag), frequency (F), load and inverter powers (Pload and Pinv) of the test system are compared with different controllers. A numeric comparison table is given to determine the optimal controller for the inverter operation. The analysis is carried out in MATLAB/Simulink software with graphical and parametric validations.
{"title":"Comparative analysis and validation of advanced control modules for standalone renewable micro grid with droop controller","authors":"Savitri Swathi, Bhaskaruni Suresh Kumar, Jalla Upendar","doi":"10.11591/eei.v13i2.5849","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5849","url":null,"abstract":"A micro grid system with renewable source operation control is a complex part as each source operates at different parameters. This renewable micro grid with multiple sources like solar plants, wind farm, fuel cell, battery backup has to be operated in both grid connected and standalone condition. During grid connection the micro grid, inverter has to inject power to the grid and compensate load in synchronization to the grid voltages. And during standalone condition the inverter is controlled with droop control module which stabilizes the voltage and frequency of the system even during grid disconnection. The droop control module is further updated with new advanced controllers like fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS) replacing the traditional proportional integral derivative (PID) and proportional integral (PI) controllers improving the response rate and for achieving better stabilization. This paper has comparative analysis of the micro grid system with different droop controllers under various operating conditions. Parameters like voltage magnitude (Vmag), frequency (F), load and inverter powers (Pload and Pinv) of the test system are compared with different controllers. A numeric comparison table is given to determine the optimal controller for the inverter operation. The analysis is carried out in MATLAB/Simulink software with graphical and parametric validations.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"11 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353701","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}
Sri Yulianto Joko Prasetyo, B. H. Simanjuntak, Yeremia Alfa Susatyo, Wiwin Sulistyo
This study aims to build a computer model to detect built-up land in the identified tsunami hazard zone based on Sentinel 2A imagery using the normalized built up area index (NBI), urban index (UI), normalize difference build-up index (NDBI), a modified built-up index (MBI), index-based builtup index (IBI) algorithms, optimized with machine learning Random Forest (RF) and extreme gradient boosting (XGboost) algorithms and the spatial patterns are predicted using the ordinary kriging (OK) method. Testing of the accuracy of the classification and optimization results was performed using the Kohen Kappa and overall accuracy functions. The results of the study show that a built-up land consisting of open land and water, settlements, industry areas, and agriculture and tourism areas can be identified using the parameters of built-up indices. The accuracy testings that were performed using overall accuracy and Kohen Kappa methods show that classification and prediction are highly accurate using XGboost machine learning, namely 91%. This study produces a novelty of finding, namely a computer model to detect and predict the spatial distribution of built-up land in 4 scales, i.e., very low, low, high, and very high based on NBI, UI, NDBI, MBI, IBI data extracted from Sentinel 2A imagery.
{"title":"A machine learning-based computer model for the assessment of tsunami impact on built-up indices using 2A Sentinel imageries","authors":"Sri Yulianto Joko Prasetyo, B. H. Simanjuntak, Yeremia Alfa Susatyo, Wiwin Sulistyo","doi":"10.11591/eei.v13i2.5910","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5910","url":null,"abstract":"This study aims to build a computer model to detect built-up land in the identified tsunami hazard zone based on Sentinel 2A imagery using the normalized built up area index (NBI), urban index (UI), normalize difference build-up index (NDBI), a modified built-up index (MBI), index-based builtup index (IBI) algorithms, optimized with machine learning Random Forest (RF) and extreme gradient boosting (XGboost) algorithms and the spatial patterns are predicted using the ordinary kriging (OK) method. Testing of the accuracy of the classification and optimization results was performed using the Kohen Kappa and overall accuracy functions. The results of the study show that a built-up land consisting of open land and water, settlements, industry areas, and agriculture and tourism areas can be identified using the parameters of built-up indices. The accuracy testings that were performed using overall accuracy and Kohen Kappa methods show that classification and prediction are highly accurate using XGboost machine learning, namely 91%. This study produces a novelty of finding, namely a computer model to detect and predict the spatial distribution of built-up land in 4 scales, i.e., very low, low, high, and very high based on NBI, UI, NDBI, MBI, IBI data extracted from Sentinel 2A imagery.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140355111","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 field of smart agriculture is ranked among the top areas that uses the internet of things (IoT), whose goal is to increase the quantity and quality of agricultural productivity. The aim of this work is to realize a new device that will be cost-effective, reliable, and autonomous using a solar panel to provide electricity in large-scale agricultural fields, ESP32 to interconnect IoT sensors and the long range (LoRa) data transmission protocol to guarantee connectivity in places where there is no internet, whose objective is to monitor and irrigate agricultural fields only when there is a need for water. The data received by the sensors is sent to mobile app users via the Blynk cloud. The performance of our new approach is measured in terms of energy savings. This new model of irrigation and smart monitoring will improve the efficiency of farming techniques.
{"title":"Intelligent agriculture system using low energy and based on the use of the internet of things","authors":"Kamal Elhattab, Karim Abouelmehdi","doi":"10.11591/eei.v13i2.6346","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6346","url":null,"abstract":"The field of smart agriculture is ranked among the top areas that uses the internet of things (IoT), whose goal is to increase the quantity and quality of agricultural productivity. The aim of this work is to realize a new device that will be cost-effective, reliable, and autonomous using a solar panel to provide electricity in large-scale agricultural fields, ESP32 to interconnect IoT sensors and the long range (LoRa) data transmission protocol to guarantee connectivity in places where there is no internet, whose objective is to monitor and irrigate agricultural fields only when there is a need for water. The data received by the sensors is sent to mobile app users via the Blynk cloud. The performance of our new approach is measured in terms of energy savings. This new model of irrigation and smart monitoring will improve the efficiency of farming techniques.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"3 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140352766","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}
For over a decade, online job portals have been providing their services to both job seekers and employers in search of hiring opportunities. Because of the high demand for recruitment, it is insufficient to use conventional hiring methods to find a suitable candidate to fill the position. Validating resumes online is challenging due to the potential for manual errors, making the process inherently risky. The bidirectional method comprises named entity recognition (NER) for extracting the required resumes for recruiters. Cosine similarity shows the match percentage of resumes for the job requirements and vice versa. In an attempt to tackle an issue of unregistered words, a solution called decoder attention with pointer network (DA-PN) has been introduced. This method incorporates the use of coverage mechanism to prevent word repetition through generated text summary. DA-PN+Cover method with mixed learning objective (MLO) (DA-PN+Cover+MLO) is utilized for protecting grow of increasing faults in generated text summary. Performance of proposed method is estimated using evaluation indicator recall oriented understudy for gisting evaluation (ROUGE) and attains an average of 27.47 which is comparatively higher than existing methods.
{"title":"Bidirectional recommendation in HR analytics through text summarization","authors":"Channabasamma Arandi, Suresh Yeresime","doi":"10.11591/eei.v13i2.5650","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5650","url":null,"abstract":"For over a decade, online job portals have been providing their services to both job seekers and employers in search of hiring opportunities. Because of the high demand for recruitment, it is insufficient to use conventional hiring methods to find a suitable candidate to fill the position. Validating resumes online is challenging due to the potential for manual errors, making the process inherently risky. The bidirectional method comprises named entity recognition (NER) for extracting the required resumes for recruiters. Cosine similarity shows the match percentage of resumes for the job requirements and vice versa. In an attempt to tackle an issue of unregistered words, a solution called decoder attention with pointer network (DA-PN) has been introduced. This method incorporates the use of coverage mechanism to prevent word repetition through generated text summary. DA-PN+Cover method with mixed learning objective (MLO) (DA-PN+Cover+MLO) is utilized for protecting grow of increasing faults in generated text summary. Performance of proposed method is estimated using evaluation indicator recall oriented understudy for gisting evaluation (ROUGE) and attains an average of 27.47 which is comparatively higher than existing methods.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"11 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353424","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}
Nornazurah Nazir Ali, Hidayat Zainuddin, J. Abd Razak, Rahisham Abd-Rahman, N. F. Ambo
Silicone rubber (SiR) is known for its exceptional electrical insulation properties. The performance of SiR could be affected by many factors, including processing parameters, particularly mixing speed and time. While these parameters are crucial for ensuring the homogeneity of blended polymeric materials, their electrical impact remains relatively unexplored. This research investigates the effect of varying processing parameters on SiR samples during rapid aging under the incline plane tracking (IPT) test. The study unfolds in three phases, with the final IPT stage revealing the significant influence of different mixing speeds and times on the recorded leakage current (LC) values for each sample. Sample 2, subjected to 70 rpm mixing speed and 10 minutes of mixing time, exhibited great resistance to tracking and erosion. Fourier transform infrared spectroscopy (FTIR) was conducted on the samples before and after the IPT test to further analyze the impact of the varying processing parameters. Once again, sample 2 displayed notable resilience, demonstrating lower reductions in absorbance values for key functional groups. In conclusion, the specific processing parameters of 70 rpm and 10 minutes have been shown to positively influence the performance of SiR, enhancing their resistance to tracking and erosion during rapid aging.
{"title":"Effects of processing parameters on the leakage current of silicone rubber insulator","authors":"Nornazurah Nazir Ali, Hidayat Zainuddin, J. Abd Razak, Rahisham Abd-Rahman, N. F. Ambo","doi":"10.11591/eei.v13i2.6070","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6070","url":null,"abstract":"Silicone rubber (SiR) is known for its exceptional electrical insulation properties. The performance of SiR could be affected by many factors, including processing parameters, particularly mixing speed and time. While these parameters are crucial for ensuring the homogeneity of blended polymeric materials, their electrical impact remains relatively unexplored. This research investigates the effect of varying processing parameters on SiR samples during rapid aging under the incline plane tracking (IPT) test. The study unfolds in three phases, with the final IPT stage revealing the significant influence of different mixing speeds and times on the recorded leakage current (LC) values for each sample. Sample 2, subjected to 70 rpm mixing speed and 10 minutes of mixing time, exhibited great resistance to tracking and erosion. Fourier transform infrared spectroscopy (FTIR) was conducted on the samples before and after the IPT test to further analyze the impact of the varying processing parameters. Once again, sample 2 displayed notable resilience, demonstrating lower reductions in absorbance values for key functional groups. In conclusion, the specific processing parameters of 70 rpm and 10 minutes have been shown to positively influence the performance of SiR, enhancing their resistance to tracking and erosion during rapid aging.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"19 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140354497","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}
This paper proposes a compact decagon antenna for wireless applications based on inspired metamaterial (MTM) loaded with a modified complementary split ring resonator (CSRR). A MTM loaded with CSRR is used to achieve a size reduction of 50% when compared to a traditional antenna. The suggested decagon antenna's ground plane has been loaded with CSRR. The antenna was made on an FR4 substrate with a thickness of 1.6 mm and εr=4.4 and has a very small dimension of 0.288 λ_0x0.272 λ_0x0.013 λ_0 (where λ_0 represent center frequency at 2.4 GHz). The given antenna has a 90 MHz bandwidth (2.40-2.50 GHz) with a peak gain of 2.36 dB. The presented design is validated by showing simulated results of the S parameter, VSWR, gain, surface current, and radiation pattern. The proposed antenna is well suited for wireless applications.
{"title":"Miniaturization of antenna using metamaterial loaded with CSRR for wireless applications","authors":"S. Pande, Dipak P. Patil","doi":"10.11591/eei.v13i2.6362","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6362","url":null,"abstract":"This paper proposes a compact decagon antenna for wireless applications based on inspired metamaterial (MTM) loaded with a modified complementary split ring resonator (CSRR). A MTM loaded with CSRR is used to achieve a size reduction of 50% when compared to a traditional antenna. The suggested decagon antenna's ground plane has been loaded with CSRR. The antenna was made on an FR4 substrate with a thickness of 1.6 mm and εr=4.4 and has a very small dimension of 0.288 λ_0x0.272 λ_0x0.013 λ_0 (where λ_0 represent center frequency at 2.4 GHz). The given antenna has a 90 MHz bandwidth (2.40-2.50 GHz) with a peak gain of 2.36 dB. The presented design is validated by showing simulated results of the S parameter, VSWR, gain, surface current, and radiation pattern. The proposed antenna is well suited for wireless applications.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"1 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140355127","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}
N. Shairi, Zahriladha Zakaria, Imran Mohd Ibrahim, Anwar Faizd Osman
This paper proposes a microstrip antenna that was made of a microstrip fed slot with a complimentary stub on a single dielectric medium. This antenna was integrated with a reflector and air gap for the application of short range communication (SRC) in a 900 MHz band. Analyses were made on the dimension of the reflector and the height of the air gap towards the antenna performance. Besides, an antenna field test was done for the propagation distance of the proposed antenna. As a result, with the antenna size of 13,770 mm2 , the measured return loss was -10.79 dB and the directivity gain was 7.44 dBi. Besides, with the effective isotropic radiated power (EIRP) of 7.44 dBm, it was predicted that at 100 m, the received signal would be around 60 to 70 dBm. Therefore, a high gain was produced by using a reflector with air gap and a compact size was achieved if compared to conventional high gain antenna designs such as Yagi Uda. Thus, it is suitable for a communication device such as the SRC application.
{"title":"Microstrip antenna with reflector and air gap for short range communication in 900 MHz band","authors":"N. Shairi, Zahriladha Zakaria, Imran Mohd Ibrahim, Anwar Faizd Osman","doi":"10.11591/eei.v13i2.5515","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5515","url":null,"abstract":"This paper proposes a microstrip antenna that was made of a microstrip fed slot with a complimentary stub on a single dielectric medium. This antenna was integrated with a reflector and air gap for the application of short range communication (SRC) in a 900 MHz band. Analyses were made on the dimension of the reflector and the height of the air gap towards the antenna performance. Besides, an antenna field test was done for the propagation distance of the proposed antenna. As a result, with the antenna size of 13,770 mm2 , the measured return loss was -10.79 dB and the directivity gain was 7.44 dBi. Besides, with the effective isotropic radiated power (EIRP) of 7.44 dBm, it was predicted that at 100 m, the received signal would be around 60 to 70 dBm. Therefore, a high gain was produced by using a reflector with air gap and a compact size was achieved if compared to conventional high gain antenna designs such as Yagi Uda. Thus, it is suitable for a communication device such as the SRC application.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140355299","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}
Shahin Shoukat Makubhai, Ganesh R. Pathak, Pankaj R. Chandre
Lung cancer is a lethal disease that claims numerous lives annually, and early detection is essential for improving survival rates. Machine learning has shown promise in predicting lung cancer risk, but the lack of transparency and interpretability in black-box models impedes the understanding of factors that contribute to risk. Explainable artificial intelligence (XAI) can overcome this limitation by providing a clear and understandable approach to machine learning. In this study, we will use a large patient record dataset to train an XAI-based model that considers various patient information, including lifestyle factors, clinical data, and medical history, for predicting lung cancer risk. We will use different XAI techniques, including decision trees, partial dependence plots, and feature importance, to interpret the model’s predictions. These methods will provide healthcare professionals with a transparent and interpretable framework for screening and treatment decisions concerning lung cancer risk.
{"title":"Predicting lung cancer risk using explainable artificial intelligence","authors":"Shahin Shoukat Makubhai, Ganesh R. Pathak, Pankaj R. Chandre","doi":"10.11591/eei.v13i2.6280","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6280","url":null,"abstract":"Lung cancer is a lethal disease that claims numerous lives annually, and early detection is essential for improving survival rates. Machine learning has shown promise in predicting lung cancer risk, but the lack of transparency and interpretability in black-box models impedes the understanding of factors that contribute to risk. Explainable artificial intelligence (XAI) can overcome this limitation by providing a clear and understandable approach to machine learning. In this study, we will use a large patient record dataset to train an XAI-based model that considers various patient information, including lifestyle factors, clinical data, and medical history, for predicting lung cancer risk. We will use different XAI techniques, including decision trees, partial dependence plots, and feature importance, to interpret the model’s predictions. These methods will provide healthcare professionals with a transparent and interpretable framework for screening and treatment decisions concerning lung cancer risk.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"11 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353101","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}
Arief Kelik Nugroho, Retantyo Wardoyo, Moh Edi Wibowo, H. Soebono
Classifying skin lesions poses a significant challenge due to the distinctive characteristics and diverse shapes they can exhibit, particularly in identifying early-stage melanoma. To address the shortcomings of the prior method, a neural network-driven strategy was introduced to differentiate between two types of skin lesions based on dermoscopic images. This new approach comprises four key stages: i) initial image processing, ii) skin lesion segmentation, iii) feature extraction, and iv) classification using deep neural networks (DNNs). Computers can also provide more accurate diagnosis results. In the review process, the articles are analyzed and summarized to contribute to developing methods or application development in skin lesion diagnosis. The stages include defining the relevant theory, input data, methods used (architecture and modules), training process, and model evaluation. This review also explores information based on trends and users, emphasizing the skin lesion segmentation process, skin lesion classification process, and minimal datasets as recommendations for future research.
{"title":"Image dermoscopy skin lesion classification using deep learning method: systematic literature review","authors":"Arief Kelik Nugroho, Retantyo Wardoyo, Moh Edi Wibowo, H. Soebono","doi":"10.11591/eei.v13i2.6077","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6077","url":null,"abstract":"Classifying skin lesions poses a significant challenge due to the distinctive characteristics and diverse shapes they can exhibit, particularly in identifying early-stage melanoma. To address the shortcomings of the prior method, a neural network-driven strategy was introduced to differentiate between two types of skin lesions based on dermoscopic images. This new approach comprises four key stages: i) initial image processing, ii) skin lesion segmentation, iii) feature extraction, and iv) classification using deep neural networks (DNNs). Computers can also provide more accurate diagnosis results. In the review process, the articles are analyzed and summarized to contribute to developing methods or application development in skin lesion diagnosis. The stages include defining the relevant theory, input data, methods used (architecture and modules), training process, and model evaluation. This review also explores information based on trends and users, emphasizing the skin lesion segmentation process, skin lesion classification process, and minimal datasets as recommendations for future research.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"59 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140356886","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}
Communication systems at millimeter-wave (mm-wave) frequencies with high propagation losses use radio frequency (RF) budget analysis. RF system gains and losses ensure the receiver can recover the broadcast signal. Modern communication systems use compressive sensing (CS) and discrete wavelet transform (DWT). Hardware implementation is hard. Fieldprogrammable gate arrays (FPGA) adaptability, configurability, and processing speed make them popular. More mm-wave transceivers use FPGAs and advanced signal processing. FPGA-based mm-wave transceivers use compressed sensing and dual-tree complex wavelet transform (DTCWT). RF budget analysis recovers receiver signals. Energy and data efficiency transceivers have baseband processors, transmitters, and receivers. RF-to-mm-wave transmitter. Receiver demodulation and baseband conversion. CS and DTCWT processing modules boost baseband signal processing 5 Gbps Xilinx virtex-6 FPGAs. The system retrieves the signal while conserving power, according to simulations and testing. This study found that FPGA-based mm-wave transceivers can use advanced signal processing in future high-speed communication systems.
{"title":"FPGA implementation of DTCWT architecture's high-speed DA structure for OFDM-based transceiver with CS","authors":"Anuapam Sindgi, U. B. Mahadevaswamy","doi":"10.11591/eei.v13i2.6543","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6543","url":null,"abstract":"Communication systems at millimeter-wave (mm-wave) frequencies with high propagation losses use radio frequency (RF) budget analysis. RF system gains and losses ensure the receiver can recover the broadcast signal. Modern communication systems use compressive sensing (CS) and discrete wavelet transform (DWT). Hardware implementation is hard. Fieldprogrammable gate arrays (FPGA) adaptability, configurability, and processing speed make them popular. More mm-wave transceivers use FPGAs and advanced signal processing. FPGA-based mm-wave transceivers use compressed sensing and dual-tree complex wavelet transform (DTCWT). RF budget analysis recovers receiver signals. Energy and data efficiency transceivers have baseband processors, transmitters, and receivers. RF-to-mm-wave transmitter. Receiver demodulation and baseband conversion. CS and DTCWT processing modules boost baseband signal processing 5 Gbps Xilinx virtex-6 FPGAs. The system retrieves the signal while conserving power, according to simulations and testing. This study found that FPGA-based mm-wave transceivers can use advanced signal processing in future high-speed communication systems.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":"22 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140352565","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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