Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp5770-5781
Raghavendra Srinivasaiah, M. Meenakshi, Ravikumar Hodikehosalli Chennegowda, SantoshKumar Jankatti
The mainstay of the economy has always been agriculture, and the majority of tasks are still carried out without the use of modern technology. Currently, the ability of human intelligence to forecast seed quality is used. Because it lacks a validation method, the existing seed prediction analysis is ineffective. Here, we have tried to create a prediction model that uses machine learning algorithms to forecast seed quality, leading to high crop yield and high-quality harvests. For precise seed categorization, this model was created using convolutional neural networks and trained using the seed dataset. Using data that can be used to forecast the future, this model is used to learn about whether the seeds are of premium quality, standard quality, or regular quality. While testing data are employed in the algorithm’s predictive analytics, training data and validation data are used for categorization reasons. Thus, by examining the training accuracy of the convolution neural network (CNN) model and the prediction accuracy of the algorithm, the project’s primary goal is to develop the best method for the more accurate prediction of seed quality.
{"title":"Analysis and prediction of seed quality using machine learning","authors":"Raghavendra Srinivasaiah, M. Meenakshi, Ravikumar Hodikehosalli Chennegowda, SantoshKumar Jankatti","doi":"10.11591/ijece.v13i5.pp5770-5781","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5770-5781","url":null,"abstract":"The mainstay of the economy has always been agriculture, and the majority of tasks are still carried out without the use of modern technology. Currently, the ability of human intelligence to forecast seed quality is used. Because it lacks a validation method, the existing seed prediction analysis is ineffective. Here, we have tried to create a prediction model that uses machine learning algorithms to forecast seed quality, leading to high crop yield and high-quality harvests. For precise seed categorization, this model was created using convolutional neural networks and trained using the seed dataset. Using data that can be used to forecast the future, this model is used to learn about whether the seeds are of premium quality, standard quality, or regular quality. While testing data are employed in the algorithm’s predictive analytics, training data and validation data are used for categorization reasons. Thus, by examining the training accuracy of the convolution neural network (CNN) model and the prediction accuracy of the algorithm, the project’s primary goal is to develop the best method for the more accurate prediction of seed quality.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45133103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp5273-5281
Ritu Ratra, P. Gulia, N. S. Gill
Nowadays, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In perturbation, datasets are perturbed in order to preserve personal information. Both data accuracy and data privacy are addressed by it. This paper will explore and compare several hybrid perturbation strategies that may be used to protect data privacy. For this, two perturbation-based techniques named improved random projection perturbation (IRPP) and enhanced principal component analysis-based technique (EPCAT) were used. These methods are employed to assess the precision, run time, and accuracy of the experimental results. This paper provides the impacts of perturbation-based privacy preserving techniques. It is observed that hybrid approaches are more efficient than the traditional approach.
{"title":"Performance analysis of perturbation-based privacy preserving techniques: an experimental perspective","authors":"Ritu Ratra, P. Gulia, N. S. Gill","doi":"10.11591/ijece.v13i5.pp5273-5281","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5273-5281","url":null,"abstract":"Nowadays, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In perturbation, datasets are perturbed in order to preserve personal information. Both data accuracy and data privacy are addressed by it. This paper will explore and compare several hybrid perturbation strategies that may be used to protect data privacy. For this, two perturbation-based techniques named improved random projection perturbation (IRPP) and enhanced principal component analysis-based technique (EPCAT) were used. These methods are employed to assess the precision, run time, and accuracy of the experimental results. This paper provides the impacts of perturbation-based privacy preserving techniques. It is observed that hybrid approaches are more efficient than the traditional approach.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44824548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp5006-5025
K. Saleh, M. Sumner
The article is introducing a new control technique for the 7-phase permanent magnet synchronous motor (PMSM) drive to enhance its robustness against the failure of phases ‘a’ and ‘c’ in addition to the failure of the encoder occurring simultaneously. The article is firstly developing a new multi-dimension space vector pulse width modulation (SVPWM) technique as a part of the fault-tolerant control technique (FTC) to control the magnitudes and angles of the motor’s current after the failures of phases ‘a’ and ‘c’. Moreover, the paper is developing another FTC to obtain a sensorless operation of the 7-phase motor after the failure in the encoder while the phase ‘a’ and ‘c’ are faulted based on the tracking of the saturation saliency. Simulation results prove that the ripple in the speed post the three failures was maintained to be less than 10 rpm compared to 2 rpm when the 7-phase drive is running without faults. In addition to that, the results demonstrated that the motor responded to instant changes in speeds and loads with a dynamic response very close to that obtained when the 7-phase motor ran under healthy operating conditions.
{"title":"Control of 7-phase permanent magnet synchronous motor drive post three failures","authors":"K. Saleh, M. Sumner","doi":"10.11591/ijece.v13i5.pp5006-5025","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5006-5025","url":null,"abstract":"The article is introducing a new control technique for the 7-phase permanent magnet synchronous motor (PMSM) drive to enhance its robustness against the failure of phases ‘a’ and ‘c’ in addition to the failure of the encoder occurring simultaneously. The article is firstly developing a new multi-dimension space vector pulse width modulation (SVPWM) technique as a part of the fault-tolerant control technique (FTC) to control the magnitudes and angles of the motor’s current after the failures of phases ‘a’ and ‘c’. Moreover, the paper is developing another FTC to obtain a sensorless operation of the 7-phase motor after the failure in the encoder while the phase ‘a’ and ‘c’ are faulted based on the tracking of the saturation saliency. Simulation results prove that the ripple in the speed post the three failures was maintained to be less than 10 rpm compared to 2 rpm when the 7-phase drive is running without faults. In addition to that, the results demonstrated that the motor responded to instant changes in speeds and loads with a dynamic response very close to that obtained when the 7-phase motor ran under healthy operating conditions.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45158562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp5599-5606
Q. Batiha, Nazatul Aini Abd Majid, N. Sahari, N. M. Ali
Students often feel overwhelmed by object-oriented programming courses. They find it difficult and complex to learn, requiring a high cognitive load to use the concepts in coding. These issues lead to demotivation in learning programming. This research aims to identify and verify factors that contribute to learning object-oriented programming from two perspectives: interviews and surveys. A literature review was conducted to identify these factors, followed by interviews with five experts who have been teaching object-oriented programming for over ten years to confirm them. Based on the interview results, a questionnaire was developed and administered to 31 bachelor students and 19 lecturers with master’s or doctorate degrees in computer science. The responses indicated that the identified factors were acceptable, with scores ranging from 3.74 to 4.65. The outcomes of this study are a set of factors that should be considered in a programming environment to improve the teaching and learning of object-oriented programming and make it more accessible and engaging for students.
{"title":"Analysis of the learning object-oriented programming factors","authors":"Q. Batiha, Nazatul Aini Abd Majid, N. Sahari, N. M. Ali","doi":"10.11591/ijece.v13i5.pp5599-5606","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5599-5606","url":null,"abstract":"Students often feel overwhelmed by object-oriented programming courses. They find it difficult and complex to learn, requiring a high cognitive load to use the concepts in coding. These issues lead to demotivation in learning programming. This research aims to identify and verify factors that contribute to learning object-oriented programming from two perspectives: interviews and surveys. A literature review was conducted to identify these factors, followed by interviews with five experts who have been teaching object-oriented programming for over ten years to confirm them. Based on the interview results, a questionnaire was developed and administered to 31 bachelor students and 19 lecturers with master’s or doctorate degrees in computer science. The responses indicated that the identified factors were acceptable, with scores ranging from 3.74 to 4.65. The outcomes of this study are a set of factors that should be considered in a programming environment to improve the teaching and learning of object-oriented programming and make it more accessible and engaging for students.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46318397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp5026-5034
H. B. Marulasiddappa, V. Pushparajesh
Permanent magnet synchronous motors (PMSM) have the capability of delivering a high torque-to-current ratio, better efficiency and low noise. Because of the above-mentioned factors, PMSMs are commonly employed in variable speed drives, especially in electric vehicle (EV) applications. Without the usage of electromechanical devices, the conventional direct torque control (DTC) can control the speed and torque of PMSM. DTC is highly efficient, fast-tracking and provides smooth torque while limiting its ripple during transient periods. There are many benefits to using a DTC-controlled PMSM drive, including quick and reliable torque reaction, high-performance control speed, and enhanced performance. This research examines the use of the DTC approach to enhance the speed and torque behavior of PMSM. The jellyfish search optimizer (JSO) is used to adjust the DTC's responsiveness and tailor the controller's best gains. In order to train the adaptive neuro-fuzzy inference system (ANFIS) controller, JSO data are utilized. The simulation outcomes demonstrate that the proposed JSO-ANFIS controller achieves a minimal torque ripple of 0.26 Nm and preserves the speed with a harmonic error of 1.21% while contrasted to existing methods.
{"title":"Direct torque control of electric vehicle drives using hybrid techniques","authors":"H. B. Marulasiddappa, V. Pushparajesh","doi":"10.11591/ijece.v13i5.pp5026-5034","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5026-5034","url":null,"abstract":"Permanent magnet synchronous motors (PMSM) have the capability of delivering a high torque-to-current ratio, better efficiency and low noise. Because of the above-mentioned factors, PMSMs are commonly employed in variable speed drives, especially in electric vehicle (EV) applications. Without the usage of electromechanical devices, the conventional direct torque control (DTC) can control the speed and torque of PMSM. DTC is highly efficient, fast-tracking and provides smooth torque while limiting its ripple during transient periods. There are many benefits to using a DTC-controlled PMSM drive, including quick and reliable torque reaction, high-performance control speed, and enhanced performance. This research examines the use of the DTC approach to enhance the speed and torque behavior of PMSM. The jellyfish search optimizer (JSO) is used to adjust the DTC's responsiveness and tailor the controller's best gains. In order to train the adaptive neuro-fuzzy inference system (ANFIS) controller, JSO data are utilized. The simulation outcomes demonstrate that the proposed JSO-ANFIS controller achieves a minimal torque ripple of 0.26 Nm and preserves the speed with a harmonic error of 1.21% while contrasted to existing methods.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46449566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp5804-5812
Arif Rahman, E. Winarko, Khabis Mustofa
Convolutional neural networks (CNN) have proven to be highly effective in large-scale object detection and image classification, as well as in serving as feature extractors for content-based image retrieval. While CNN models are typically trained with category label supervision and softmax loss for product image retrieval, we propose a different approach for feature extraction using the squared-hinge loss, an alternative multiclass classification loss function. First, transfer learning is performed on a pre-trained model, followed by fine-tuning the model. Then, image features are extracted based on the fine-tuned model and indexed using the nearest-neighbor indexing technique. Experiments are conducted on VGG19, InceptionV3, MobileNetV2, and ResNet18 CNN models. The model training results indicate that training the models with squared-hinge loss reduces the loss values in each epoch and reaches stability in less epoch than softmax loss. Retrieval results show that using features from squared-hinge trained models improves the retrieval accuracy by up to 3.7% compared to features from softmax-trained models. Moreover, the squared-hinge trained MobileNetV2 features outperformed others, while the ResNet18 feature gives the advantage of having the lowest dimensionality with competitive accuracy.
{"title":"Content-based product image retrieval using squared-hinge loss trained convolutional neural networks","authors":"Arif Rahman, E. Winarko, Khabis Mustofa","doi":"10.11591/ijece.v13i5.pp5804-5812","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5804-5812","url":null,"abstract":"Convolutional neural networks (CNN) have proven to be highly effective in large-scale object detection and image classification, as well as in serving as feature extractors for content-based image retrieval. While CNN models are typically trained with category label supervision and softmax loss for product image retrieval, we propose a different approach for feature extraction using the squared-hinge loss, an alternative multiclass classification loss function. First, transfer learning is performed on a pre-trained model, followed by fine-tuning the model. Then, image features are extracted based on the fine-tuned model and indexed using the nearest-neighbor indexing technique. Experiments are conducted on VGG19, InceptionV3, MobileNetV2, and ResNet18 CNN models. The model training results indicate that training the models with squared-hinge loss reduces the loss values in each epoch and reaches stability in less epoch than softmax loss. Retrieval results show that using features from squared-hinge trained models improves the retrieval accuracy by up to 3.7% compared to features from softmax-trained models. Moreover, the squared-hinge trained MobileNetV2 features outperformed others, while the ResNet18 feature gives the advantage of having the lowest dimensionality with competitive accuracy.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47678100","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}
Replica server placement is one of the crucial concerns for a given geographic diversity associated with placement problems in content delivery network (CDN). After reviewing the existing literatures, it is noted that studies are more for solving placement problem in conventional CDN and not much over cloud-based CDN architectures, which some few studies are reported towards replica selection are much in its nascent stages of development. Moreover, such models are not benchmarked or practically assessed to prove its effectiveness. Hence, the proposed study introduces a novel design of computational framework associated with cloud-based CDN which can facilitate cost-effective replica server management for enhanced service delivery. Implemented using analytical research methodology, the simulated study outcome shows that proposed scheme offers reduced cost, reduced resource dependencies, reduced latency, and faster processing time in contrast to existing models of replica server placement.
{"title":"A novel cost-based replica server placement for optimal service quality in cloud-based content delivery network","authors":"Priyanka Dharmapal, Channakrishnaraju Channakrishnaraju, Chethan Bommalingaiahanapalya Krishnamur","doi":"10.11591/ijece.v13i5.pp5588-5598","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5588-5598","url":null,"abstract":"Replica server placement is one of the crucial concerns for a given geographic diversity associated with placement problems in content delivery network (CDN). After reviewing the existing literatures, it is noted that studies are more for solving placement problem in conventional CDN and not much over cloud-based CDN architectures, which some few studies are reported towards replica selection are much in its nascent stages of development. Moreover, such models are not benchmarked or practically assessed to prove its effectiveness. Hence, the proposed study introduces a novel design of computational framework associated with cloud-based CDN which can facilitate cost-effective replica server management for enhanced service delivery. Implemented using analytical research methodology, the simulated study outcome shows that proposed scheme offers reduced cost, reduced resource dependencies, reduced latency, and faster processing time in contrast to existing models of replica server placement.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42539108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp5662-5673
Rahmat Budiarsa, Retantyo Wardoyo, Aina Musdholifah
Face recognition technology has been used in many ways, such as in the authentication and identification process. The object raised is a piece of face image that does not have complete facial information (occluded face), it can be due to acquisition from a different point of view or shooting a face from a different angle. This object was raised because the object can affect the detection and identification performance of the face image as a whole. Deep leaning method can be used to solve face recognition problems. In previous research, more focused on face detection and recognition based on resolution, and detection of face. Mask region convolutional neural network (mask R-CNN) method still has deficiency in the segmentation section which results in a decrease in the accuracy of face identification with incomplete face information objects. The segmentation used in mask R-CNN is fully convolutional network (FCN). In this research, exploration and modification of many FCN parameters will be carried out using the CNN backbone pooling layer, and modification of mask R-CNN for face identification, besides that, modifications will be made to the bounding box regressor. it is expected that the modification results can provide the best recommendations based on accuracy.
{"title":"Face recognition for occluded face with mask region convolutional neural network and fully convolutional network: a literature review","authors":"Rahmat Budiarsa, Retantyo Wardoyo, Aina Musdholifah","doi":"10.11591/ijece.v13i5.pp5662-5673","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp5662-5673","url":null,"abstract":"Face recognition technology has been used in many ways, such as in the authentication and identification process. The object raised is a piece of face image that does not have complete facial information (occluded face), it can be due to acquisition from a different point of view or shooting a face from a different angle. This object was raised because the object can affect the detection and identification performance of the face image as a whole. Deep leaning method can be used to solve face recognition problems. In previous research, more focused on face detection and recognition based on resolution, and detection of face. Mask region convolutional neural network (mask R-CNN) method still has deficiency in the segmentation section which results in a decrease in the accuracy of face identification with incomplete face information objects. The segmentation used in mask R-CNN is fully convolutional network (FCN). In this research, exploration and modification of many FCN parameters will be carried out using the CNN backbone pooling layer, and modification of mask R-CNN for face identification, besides that, modifications will be made to the bounding box regressor. it is expected that the modification results can provide the best recommendations based on accuracy.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43938109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp4979-4986
A. Es-saqy, Maryam Abata, M. Fattah, S. Mazer, M. Mehdi, M. El Bekkali, C. Algani
This paper presents the design of a pseudomorphic high electron mobility transistor (pHEMT) self-oscillating mixer (SOM) for millimeter wave wireless communication systems. The 180° out-of-phase technique is chosen to both improve the desired lower sideband (LSB) signal and to achieve a satisfactory rejection of the unwanted signals (LO, USB and IF). This SOM is designed on the PH15 process of UMS foundry which is based on 0.15 µm GaAs pHEMT. The signal is up-converted from 2 GHz-IF frequency to 26 GHz-LSB frequency, using an autogenerated 28 GHz-LO signal. Simulations were performed using the advanced design system (ADS) workflow. They show 6.4 dB conversion gain and a signal rejection rate of 29.7 dB for the unwanted USB signal. the chip size is 3.6 mm2.
{"title":"High rejection self-oscillating up-conversion mixer for fifth-generation communications","authors":"A. Es-saqy, Maryam Abata, M. Fattah, S. Mazer, M. Mehdi, M. El Bekkali, C. Algani","doi":"10.11591/ijece.v13i5.pp4979-4986","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp4979-4986","url":null,"abstract":"This paper presents the design of a pseudomorphic high electron mobility transistor (pHEMT) self-oscillating mixer (SOM) for millimeter wave wireless communication systems. The 180° out-of-phase technique is chosen to both improve the desired lower sideband (LSB) signal and to achieve a satisfactory rejection of the unwanted signals (LO, USB and IF). This SOM is designed on the PH15 process of UMS foundry which is based on 0.15 µm GaAs pHEMT. The signal is up-converted from 2 GHz-IF frequency to 26 GHz-LSB frequency, using an autogenerated 28 GHz-LO signal. Simulations were performed using the advanced design system (ADS) workflow. They show 6.4 dB conversion gain and a signal rejection rate of 29.7 dB for the unwanted USB signal. the chip size is 3.6 mm2.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46963677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.11591/ijece.v13i5.pp4824-4834
J. Silva-Ortega, Jean Carlos Calvo Cervantes, Eliab de Jesus Rodriguez Acosta, Idi Amin Isaac Millán, Juan Rivera-Alvarado, Kelly Margarita Berdugo Sarmiento
Thermal power plants are the widely conventional generation unit technology used to produce electricity being controllable and dispatchable. The location of thermal power plants depends on the energy availability conditions of the areas and the capacity to fuels access. Their location and geographical distribution define a high level of concentration in areas defined as thermal districts and its location define reliability, security, availability, and flexibility indices to avoid critical scenario or support system from contingencies. However, in many cases the electrical configuration does not correspond to requirements. This paper links the concentration by political distribution in Colombia and the configuration used in the generating substations to guarantee requirements. The Hirschman-Herfindahl index as a market tool is used to evaluate energy concentration facing representative participation in certain departments of Colombia. Results evidenced configurations and concentration in a study case, results and analysis could be used for planner to promote participation, reliability and promote. The paper’s contribution and conclusions are linked to guide planners towards market and technical tool to evaluate installed capacities, avoid market concentration, and reduce risky scenarios.
{"title":"Technical and market evaluation of thermal generation power plants in the Colombia power system","authors":"J. Silva-Ortega, Jean Carlos Calvo Cervantes, Eliab de Jesus Rodriguez Acosta, Idi Amin Isaac Millán, Juan Rivera-Alvarado, Kelly Margarita Berdugo Sarmiento","doi":"10.11591/ijece.v13i5.pp4824-4834","DOIUrl":"https://doi.org/10.11591/ijece.v13i5.pp4824-4834","url":null,"abstract":"Thermal power plants are the widely conventional generation unit technology used to produce electricity being controllable and dispatchable. The location of thermal power plants depends on the energy availability conditions of the areas and the capacity to fuels access. Their location and geographical distribution define a high level of concentration in areas defined as thermal districts and its location define reliability, security, availability, and flexibility indices to avoid critical scenario or support system from contingencies. However, in many cases the electrical configuration does not correspond to requirements. This paper links the concentration by political distribution in Colombia and the configuration used in the generating substations to guarantee requirements. The Hirschman-Herfindahl index as a market tool is used to evaluate energy concentration facing representative participation in certain departments of Colombia. Results evidenced configurations and concentration in a study case, results and analysis could be used for planner to promote participation, reliability and promote. The paper’s contribution and conclusions are linked to guide planners towards market and technical tool to evaluate installed capacities, avoid market concentration, and reduce risky scenarios.","PeriodicalId":38060,"journal":{"name":"International Journal of Electrical and Computer Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41603425","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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