Pub Date : 2024-03-14DOI: 10.1109/TLA.2024.10472960
Javiera Vásquez-Salgado;Rosa L. Figueroa;Julio Sotelo;Manuel Villalobos-Cid
Biomedical engineering (BME) combines engineering, biology, and medicine to develop innovative healthcare solutions. There is an increasing demand for BME professionals following technological and scientific advances. In Chile, only three universities offer undergraduate BME programs: Universidad de Valparaiso, Universidad de Concepcion, and Universidad de Santiago de Chile. Each institution has defined its curriculum, professional profile, and research focus based on its perspective of the country's needs. However, the scope of their research contribution has not been studied. In this work, we perform a comprehensive bibliometric analysis using data from the SCOPUS database to evaluate publications by researchers affiliated with Chilean undergraduate BME programs from 2000 to 2022. The objective is to identify the research areas of BME in Chile, understand the similarities and differences between universities, analyse their research areas, explore collaboration relationships, and characterise the discipline's evolution. The main contributions of this work are (1) a quantitative and qualitative analysis of BME research in Chile, (2) the identification of BME research areas and their development over time, (3) the creation of a dashboard-style web tool, and (4) proposing a robust methodology for bibliometric analysis applicable to BME literature in Chile and similar contexts. This work represents the first collaboration involving authors from all universities with undergraduate Chilean BME programs.
{"title":"Biomedical engineering research in Chilean universities - A bibliometric analysis","authors":"Javiera Vásquez-Salgado;Rosa L. Figueroa;Julio Sotelo;Manuel Villalobos-Cid","doi":"10.1109/TLA.2024.10472960","DOIUrl":"https://doi.org/10.1109/TLA.2024.10472960","url":null,"abstract":"Biomedical engineering (BME) combines engineering, biology, and medicine to develop innovative healthcare solutions. There is an increasing demand for BME professionals following technological and scientific advances. In Chile, only three universities offer undergraduate BME programs: Universidad de Valparaiso, Universidad de Concepcion, and Universidad de Santiago de Chile. Each institution has defined its curriculum, professional profile, and research focus based on its perspective of the country's needs. However, the scope of their research contribution has not been studied. In this work, we perform a comprehensive bibliometric analysis using data from the SCOPUS database to evaluate publications by researchers affiliated with Chilean undergraduate BME programs from 2000 to 2022. The objective is to identify the research areas of BME in Chile, understand the similarities and differences between universities, analyse their research areas, explore collaboration relationships, and characterise the discipline's evolution. The main contributions of this work are (1) a quantitative and qualitative analysis of BME research in Chile, (2) the identification of BME research areas and their development over time, (3) the creation of a dashboard-style web tool, and (4) proposing a robust methodology for bibliometric analysis applicable to BME literature in Chile and similar contexts. This work represents the first collaboration involving authors from all universities with undergraduate Chilean BME programs.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10472960","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.1109/TLA.2024.10472961
Peiran Zhang;Guoxin Zhang;Kuihe Yang
Unmanned aerial vehicle (UAV) image object detection, in recent years, has been receiving increasing attention for its wide application in military and civil fields. Current object detection methods perform well in generic scenarios, while vast small objects and extremely dense distribution in UAV images make it difficult to capture them, resulting in sub-optimal performance. In this paper, we propose a UAV image object detection framework APNet, which addresses the issue mentioned above by fine-grain deformable convolution (DC) and effective feature fusion. First, we design an accurate positioning deformable convolution (APDC), which changes the kernel shape dynamically to enforce refined features, especially in regions where objects gather densely. Specifically, a positional information enhancement attention (PEA) is designed to generate more accurate convolutional position offsets depending on the object position. Therefore, APDC alleviates inflexible deformation in vanilla DC and exhibits better adaptability to the shapes of different objects, which discriminates multi-objects in densely distributed areas in a fine-grain way. Second, we propose an effective cross-layer feature fusion (ECF) to integrate multi-scale features effectively and aggregate attentive features dynamically. Extensive experiments conducted on VisDrone and UAVDT demonstrate the universality and effectiveness of our APNet, achieving 29.8 and 48.7 in mAP and mAP50, respectively. Compared to the state-of-the-art (SOTA) method, our APNet achieves an improvement of 2.2 and 3.5 in mAP and mAP50, respectively.
{"title":"APNet: Accurate Positioning Deformable Convolution for UAV Image Object Detection","authors":"Peiran Zhang;Guoxin Zhang;Kuihe Yang","doi":"10.1109/TLA.2024.10472961","DOIUrl":"https://doi.org/10.1109/TLA.2024.10472961","url":null,"abstract":"Unmanned aerial vehicle (UAV) image object detection, in recent years, has been receiving increasing attention for its wide application in military and civil fields. Current object detection methods perform well in generic scenarios, while vast small objects and extremely dense distribution in UAV images make it difficult to capture them, resulting in sub-optimal performance. In this paper, we propose a UAV image object detection framework APNet, which addresses the issue mentioned above by fine-grain deformable convolution (DC) and effective feature fusion. First, we design an accurate positioning deformable convolution (APDC), which changes the kernel shape dynamically to enforce refined features, especially in regions where objects gather densely. Specifically, a positional information enhancement attention (PEA) is designed to generate more accurate convolutional position offsets depending on the object position. Therefore, APDC alleviates inflexible deformation in vanilla DC and exhibits better adaptability to the shapes of different objects, which discriminates multi-objects in densely distributed areas in a fine-grain way. Second, we propose an effective cross-layer feature fusion (ECF) to integrate multi-scale features effectively and aggregate attentive features dynamically. Extensive experiments conducted on VisDrone and UAVDT demonstrate the universality and effectiveness of our APNet, achieving 29.8 and 48.7 in mAP and mAP50, respectively. Compared to the state-of-the-art (SOTA) method, our APNet achieves an improvement of 2.2 and 3.5 in mAP and mAP50, respectively.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10472961","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.1109/TLA.2024.10472958
Ricardo Afonso;João Rosas
In a digital society, the truth portrayed by information is crucial in promoting education, security, and evolution. However, fake news raises a significant concern in that regard. Although there has been a continuous effort in the fight against fake news, it is still a multifaceted challenge in constant change as the menace renovates itself. Thus, in our approach, several machine learning and deep learning models were developed to obtain models that can detect fake content that appears online. The models can then be interfaced with users devices, namely in the form of browser extensions and smartphone applications. The classification models run on a cloud server and are accessible via web services. These models can detect fake news in English and European Portuguese, with a stronger focus on the latter, given the reduced number of projects in this specific field and language. Besides developing the first public dataset for fake news detection in European Portuguese through web scraping, the models achieved better performance than previous work while being trained with a significantly higher amount of data from a wider variety of sources.
{"title":"Development of a Smartphone Application and Chrome Extension to Detect Fake News in English and European Portuguese","authors":"Ricardo Afonso;João Rosas","doi":"10.1109/TLA.2024.10472958","DOIUrl":"https://doi.org/10.1109/TLA.2024.10472958","url":null,"abstract":"In a digital society, the truth portrayed by information is crucial in promoting education, security, and evolution. However, fake news raises a significant concern in that regard. Although there has been a continuous effort in the fight against fake news, it is still a multifaceted challenge in constant change as the menace renovates itself. Thus, in our approach, several machine learning and deep learning models were developed to obtain models that can detect fake content that appears online. The models can then be interfaced with users devices, namely in the form of browser extensions and smartphone applications. The classification models run on a cloud server and are accessible via web services. These models can detect fake news in English and European Portuguese, with a stronger focus on the latter, given the reduced number of projects in this specific field and language. Besides developing the first public dataset for fake news detection in European Portuguese through web scraping, the models achieved better performance than previous work while being trained with a significantly higher amount of data from a wider variety of sources.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10472958","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.1109/TLA.2024.10473002
Grisel Miranda-Piña;Roberto Alejo;Eréndira Rendón-Lara;Vicente García
In Latin American and Caribbean States the verbal violence against women on social networks, such as Twitter, is a serious threat that has been addressed through the implementation of social norms, public policies, and social movements. Nevertheless, a challenge is the effective and automatic real-time detection of violent tweets. In this sense, traditional machine learning algorithms have been proposed to tackle social issues where the training process is performed in a static manner. However, considering that Twitter is a dynamic environment where a vast of tweets are generated each second, it requires powerful machine learning algorithms that could exploit this pool of unlabeled data to be incorporated into the model through continuous updates. This paper explores an active learning method based on uncertainty sampling, which identifies the most confusing tweets to be labeled by an expert in real-time. This focused selection prioritizes which data can be used to train a multilayer perceptron that can achieve a better performance with fewer training samples. Experimental results show that including new samples yields promising results, increasing the AUC from 0.8712 to 0.8833.
{"title":"Detection of violent speech against women in Mexican tweets using an active learning approach","authors":"Grisel Miranda-Piña;Roberto Alejo;Eréndira Rendón-Lara;Vicente García","doi":"10.1109/TLA.2024.10473002","DOIUrl":"https://doi.org/10.1109/TLA.2024.10473002","url":null,"abstract":"In Latin American and Caribbean States the verbal violence against women on social networks, such as Twitter, is a serious threat that has been addressed through the implementation of social norms, public policies, and social movements. Nevertheless, a challenge is the effective and automatic real-time detection of violent tweets. In this sense, traditional machine learning algorithms have been proposed to tackle social issues where the training process is performed in a static manner. However, considering that Twitter is a dynamic environment where a vast of tweets are generated each second, it requires powerful machine learning algorithms that could exploit this pool of unlabeled data to be incorporated into the model through continuous updates. This paper explores an active learning method based on uncertainty sampling, which identifies the most confusing tweets to be labeled by an expert in real-time. This focused selection prioritizes which data can be used to train a multilayer perceptron that can achieve a better performance with fewer training samples. Experimental results show that including new samples yields promising results, increasing the AUC from 0.8712 to 0.8833.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10473002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.1109/TLA.2024.10473000
Xu Lu;Kejie Zhong;Zhiwei Guan;Jun Liu
WiFi fingerprint positioning is a common method for indoor location determination. Existing methods are susceptible to fluctuations in WiFi signal strength during the offline phase, leading to unevenly received signals. Additionally, during online positioning, there is a lack of integration with historical trajectory information. These problems can result in errors in both offline fingerprint acquisition and online location positioning. To address these problems, we propose a method that combines normality detection in the offline phase and Location Weighted K-nearest Neighbor positioning in the online phase. In the offline phase, initial Received Signal Strength Indication samples undergo preprocessing based on skewness and kurtosis for normality detection. If the samples conform to a normal distribution model, the probability density is estimated using the normal distribution function. If not, estimation occurs using the kernel density function model. Subsequently, values are averaged after Kalman filtering to establish a high-precision fingerprint database. During the online positioning phase, the LWKNN algorithm is employed. Initially, the Weighted K-nearest Neighbor method estimates the position, and this information is utilized as features to construct a Longterm and Shortterm Memory network model. The optimal path is determined through the least square method. Finally, the obtained outputs are integrated with historical data from the fingerprint positioning trajectory to enhance target positioning accuracy. Experimental results demonstrate that our indoor localization method significantly improves WiFi fingerprint localization accuracy compared to traditional localization methods.
WiFi 指纹定位是确定室内位置的常用方法。现有方法在离线阶段容易受到 WiFi 信号强度波动的影响，导致接收到的信号不均匀。此外，在在线定位期间，缺乏与历史轨迹信息的整合。这些问题都会导致离线指纹采集和在线定位出现错误。为了解决这些问题，我们提出了一种方法，将离线阶段的常态检测和在线阶段的位置加权 K 近邻定位结合起来。在离线阶段，初始接收信号强度指示样本会经过基于偏度和峰度的预处理，以进行正态性检测。如果样本符合正态分布模型，则使用正态分布函数估算概率密度。如果不符合，则使用核密度函数模型进行估计。随后，在卡尔曼滤波后对数值进行平均，以建立高精度指纹数据库。在线定位阶段采用 LWKNN 算法。最初，加权 K 近邻法估计位置，并利用这些信息作为特征来构建长期和短期记忆网络模型。通过最小平方法确定最佳路径。最后，将获得的输出结果与指纹定位轨迹的历史数据相结合，以提高目标定位的准确性。实验结果表明，与传统定位方法相比，我们的室内定位方法显著提高了 WiFi 指纹定位精度。
{"title":"A fingerprint location framework for uneven WiFi signals based on machine learning","authors":"Xu Lu;Kejie Zhong;Zhiwei Guan;Jun Liu","doi":"10.1109/TLA.2024.10473000","DOIUrl":"https://doi.org/10.1109/TLA.2024.10473000","url":null,"abstract":"WiFi fingerprint positioning is a common method for indoor location determination. Existing methods are susceptible to fluctuations in WiFi signal strength during the offline phase, leading to unevenly received signals. Additionally, during online positioning, there is a lack of integration with historical trajectory information. These problems can result in errors in both offline fingerprint acquisition and online location positioning. To address these problems, we propose a method that combines normality detection in the offline phase and Location Weighted K-nearest Neighbor positioning in the online phase. In the offline phase, initial Received Signal Strength Indication samples undergo preprocessing based on skewness and kurtosis for normality detection. If the samples conform to a normal distribution model, the probability density is estimated using the normal distribution function. If not, estimation occurs using the kernel density function model. Subsequently, values are averaged after Kalman filtering to establish a high-precision fingerprint database. During the online positioning phase, the LWKNN algorithm is employed. Initially, the Weighted K-nearest Neighbor method estimates the position, and this information is utilized as features to construct a Longterm and Shortterm Memory network model. The optimal path is determined through the least square method. Finally, the obtained outputs are integrated with historical data from the fingerprint positioning trajectory to enhance target positioning accuracy. Experimental results demonstrate that our indoor localization method significantly improves WiFi fingerprint localization accuracy compared to traditional localization methods.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10473000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.1109/TLA.2024.10473001
{"title":"Table of Contents April 2024","authors":"","doi":"10.1109/TLA.2024.10473001","DOIUrl":"https://doi.org/10.1109/TLA.2024.10473001","url":null,"abstract":"","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10473001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-14DOI: 10.1109/TLA.2024.10472962
Pooja Sahoo;Pramod K. Singhal;Karuna Markam
The paper objective is to designed circular polarized microstrip patch antenna and enhancing axial ratio bandwidth with improved impedance bandwidth. An antenna is designed using stacking method. The design of the antenna is achieved using two slots on the main radiating patch and one cross slot on the near field resonating parasitic patch (NFRP). The NFRP patch is positioned below the main radiating patch at some height. The structure is called modified Hilbert shaped antenna. A slots methodology on patches is used for the attainment of wider bandwidth. Improvement of the axial ratio bandwidth of an antenna is achieved by the introduction of NFRP patch. The antenna that has been designed is resonated at frequencies 900 MHz and 1890 MHz, covering two bands i.e. (725-990) MHz & (1800-1920) MHz with a return loss of -25 dB. Impedance bandwidths are obtained 265 MHz and 120 MHz at these frequencies. Furthermore, bands are covered by a 3-dB axial ratio of (800950) MHz and (1720-1920) MHz. The percentage axial ratio bandwidths are obtained 17.14% and 10.98% over the operating bands. An average gain and radiation efficiency is reported 6.7 dBi and 84% for the antenna. The size of the antenna is calculated 0.3600.420 0.0420. In summery the antenna is described as a dual-band, circular polarized with a stable gain and wider axial ratio bandwidth, deemed suitable for GSM (Global System for Mobile Communication) applications.
{"title":"Enhancing Axial Ratio Bandwidth of Dual Band Microstrip Patch Antenna for GSM Application","authors":"Pooja Sahoo;Pramod K. Singhal;Karuna Markam","doi":"10.1109/TLA.2024.10472962","DOIUrl":"https://doi.org/10.1109/TLA.2024.10472962","url":null,"abstract":"The paper objective is to designed circular polarized microstrip patch antenna and enhancing axial ratio bandwidth with improved impedance bandwidth. An antenna is designed using stacking method. The design of the antenna is achieved using two slots on the main radiating patch and one cross slot on the near field resonating parasitic patch (NFRP). The NFRP patch is positioned below the main radiating patch at some height. The structure is called modified Hilbert shaped antenna. A slots methodology on patches is used for the attainment of wider bandwidth. Improvement of the axial ratio bandwidth of an antenna is achieved by the introduction of NFRP patch. The antenna that has been designed is resonated at frequencies 900 MHz and 1890 MHz, covering two bands i.e. (725-990) MHz & (1800-1920) MHz with a return loss of -25 dB. Impedance bandwidths are obtained 265 MHz and 120 MHz at these frequencies. Furthermore, bands are covered by a 3-dB axial ratio of (800950) MHz and (1720-1920) MHz. The percentage axial ratio bandwidths are obtained 17.14% and 10.98% over the operating bands. An average gain and radiation efficiency is reported 6.7 dBi and 84% for the antenna. The size of the antenna is calculated 0.3600.420 0.0420. In summery the antenna is described as a dual-band, circular polarized with a stable gain and wider axial ratio bandwidth, deemed suitable for GSM (Global System for Mobile Communication) applications.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10472962","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops a dynamic optimization methodology based on direct numerical methods, for the bioethanol fed-batch production from glucose and fructose as a substrate. The mathematical model that governs the process consists of six differential equations and is highly nonlinear. The proposed strategy uses the Fourier trigonometric basis and normalized orthogonal polynomials for substrate feeding rate parameterization. Then, evolutionary algorithms and gradient methods are combined to search parameters that generate the best control action. This parameterization methodology requires a minimum number of parameters to optimize. Also, the continuous and differentiable nature of the optimal profile enables its direct implementation in the physical process, eliminating the necessity for filtering or smoothing it. In addition, they are ideal for bioprocesses, in which it is preferable to avoid abrupt changes in the operating modes of the process to promote cell growth. As a result, using only 3 parameters, a 3.5% increase in ethanol production was achieved, while the reference uses at least 10 parameters and provides a stepped feed profile. The simulations have yielded promising results, making this proposal an alternative with excellent potential for process optimization.
{"title":"Bioethanol production optimization by direct numerical methods and evolutionary algorithms","authors":"Cecilia Fernández;Nadia Pantano;Carla Groff;Rocío Gil;Gustavo Scaglia","doi":"10.1109/TLA.2024.10431425","DOIUrl":"https://doi.org/10.1109/TLA.2024.10431425","url":null,"abstract":"This paper develops a dynamic optimization methodology based on direct numerical methods, for the bioethanol fed-batch production from glucose and fructose as a substrate. The mathematical model that governs the process consists of six differential equations and is highly nonlinear. The proposed strategy uses the Fourier trigonometric basis and normalized orthogonal polynomials for substrate feeding rate parameterization. Then, evolutionary algorithms and gradient methods are combined to search parameters that generate the best control action. This parameterization methodology requires a minimum number of parameters to optimize. Also, the continuous and differentiable nature of the optimal profile enables its direct implementation in the physical process, eliminating the necessity for filtering or smoothing it. In addition, they are ideal for bioprocesses, in which it is preferable to avoid abrupt changes in the operating modes of the process to promote cell growth. As a result, using only 3 parameters, a 3.5% increase in ethanol production was achieved, while the reference uses at least 10 parameters and provides a stepped feed profile. The simulations have yielded promising results, making this proposal an alternative with excellent potential for process optimization.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10431425","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139715211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-09DOI: 10.1109/TLA.2024.10431418
Venkata Subba Reddy Chagam;Swati Devabhaktuni
A modified hysteresis torque controller is introduced into the direct torque control scheme of a 5-phase open-end winding induction motor, aimed at enhancing steady-state performance by minimizing torque, flux ripple, and current total harmonic distortion (%THD) with the dual 5-leg inverter configuration. The proposed Direct Torque Control (DTC) strategy utilizes a common DC source for both converters without the need for a bulky isolation transformer, accomplished by nullifying common mode voltage in the dual inverter open-end winding configuration. This proposed technique employs 30 virtual voltage vectors (VVVs) generated from the dual inverter configuration, strategically categorized as small, large, and medium voltage vectors. These 30 VVVs are instrumental in forming a 7-level torque controller and a 3-level torque controller in the proposed DTC scheme. In contrast to the existing DTC method, which uses 20 virtual voltage vectors from a dual 5-leg inverter configuration and grapples with challenges like high current harmonic distortion, torque ripple, and flux ripple, the proposed control scheme introduces a new 7-level torque hysteresis controller. The outcome is reduced torque and flux ripple, along with minimized harmonic content across various speeds and loading conditions without disturbing the dynamics. Experimental hardware results are scrutinized, comparing the classical DTC with the proposed DTC schemes in open-end winding induction motors, aiming to know the superior qualities of the proposed control approach.
{"title":"An Isolation Transformer-less Single DC Source fed Dual 5-leg Inverter Controlled 5-Phase Induction Motor with Modified Direct Torque Control","authors":"Venkata Subba Reddy Chagam;Swati Devabhaktuni","doi":"10.1109/TLA.2024.10431418","DOIUrl":"https://doi.org/10.1109/TLA.2024.10431418","url":null,"abstract":"A modified hysteresis torque controller is introduced into the direct torque control scheme of a 5-phase open-end winding induction motor, aimed at enhancing steady-state performance by minimizing torque, flux ripple, and current total harmonic distortion (%THD) with the dual 5-leg inverter configuration. The proposed Direct Torque Control (DTC) strategy utilizes a common DC source for both converters without the need for a bulky isolation transformer, accomplished by nullifying common mode voltage in the dual inverter open-end winding configuration. This proposed technique employs 30 virtual voltage vectors (VVVs) generated from the dual inverter configuration, strategically categorized as small, large, and medium voltage vectors. These 30 VVVs are instrumental in forming a 7-level torque controller and a 3-level torque controller in the proposed DTC scheme. In contrast to the existing DTC method, which uses 20 virtual voltage vectors from a dual 5-leg inverter configuration and grapples with challenges like high current harmonic distortion, torque ripple, and flux ripple, the proposed control scheme introduces a new 7-level torque hysteresis controller. The outcome is reduced torque and flux ripple, along with minimized harmonic content across various speeds and loading conditions without disturbing the dynamics. Experimental hardware results are scrutinized, comparing the classical DTC with the proposed DTC schemes in open-end winding induction motors, aiming to know the superior qualities of the proposed control approach.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10431418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139715136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-09DOI: 10.1109/TLA.2024.10431419
Juan Gerardo Parada-Salado;Luis M. Martinez-Patiño;Francisco J. Pérez-Pinal;Allan G. Soriano-Sánchez;Alejandro I. Barranco-Gutiérrez;Carina Zarate-Orduño
The theoretical application of fractional equations in controller development is not a new topic. The first efforts on this topic were reported in the late 1970s. However, in the last four years, a greater number of papers related to fractional control have been published than the one accumulated in previous years. Motivated by the above, this paper reports the step-by-step development of this type of control in a bidirectional converter. Furthermore, the discrete-time equivalent of the developed fractional control is implemented on Texas Instruments F280042C digital signal processor. The experimental results of the discrete fractional compensator are compared with the experimental results of a conventional proportional integral derivative (PID) controller. The results show a notable improvement in the response of the bidirectional converter with the fractional control; specifically, faster responses and less overshoot in most of the experiments carried out. Also, the existing challenges facing the widespread application of this control technique are notorious and are extensively addressed in this article.
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