Pub Date : 2021-10-12DOI: 10.1109/ETCM53643.2021.9590699
Renato Ortega, M. Cerrada, D. Cabrera, Réne-Vinicio Sánchez
In this paper, the constant load torque of a three-phase induction motor is estimated by means of the steady-state electrical torque signal and the motor torque due to the friction loss. In this case study, the load is connected to the motor's output shaft through an electromagnetic brake generating constant load at three magnitudes. Validation of load torque estimation is performed by identifying electrical and mechanical parameters and simulating its mathematical model to compare estimated and simulated constant load signals. Then this methodology can be used to estimate constant load torques on induction motors.
{"title":"A Method for the Estimation of the Constant Load Torque by Using the Steady-State Electrical Torque Signal","authors":"Renato Ortega, M. Cerrada, D. Cabrera, Réne-Vinicio Sánchez","doi":"10.1109/ETCM53643.2021.9590699","DOIUrl":"https://doi.org/10.1109/ETCM53643.2021.9590699","url":null,"abstract":"In this paper, the constant load torque of a three-phase induction motor is estimated by means of the steady-state electrical torque signal and the motor torque due to the friction loss. In this case study, the load is connected to the motor's output shaft through an electromagnetic brake generating constant load at three magnitudes. Validation of load torque estimation is performed by identifying electrical and mechanical parameters and simulating its mathematical model to compare estimated and simulated constant load signals. Then this methodology can be used to estimate constant load torques on induction motors.","PeriodicalId":438567,"journal":{"name":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131898123","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 : 2021-10-12DOI: 10.1109/ETCM53643.2021.9590811
Jonathan A. Zea, Marco E. Benalcázar, Lorena Isabel Barona López, Ángel Leonardo Valdivieso Caraguay
Due to lack of standardization in the data acquisition process, Hand Gesture Recognition literature has produced a high number of different but incompatible datasets. This paper presents a system for data acquisition of EMG signals and its manual segmentation. The system can be connected with the two most affordable wearable EMG armbands: Myo Armband and gForce Pro. The system allows to record a given number of samples per gesture during a given number of seconds. Twelve gestures were selected for being natural and the most reported in the literature. The system includes several features that enhance the quality of the dataset such as: strategies to maintain the volunteer attention, and the capability to resume recording in case of interruption. The system was evaluated using the Computer System Usability Questionnaire (CSUQ) over 10 data collectors. This questionnaire allowed to obtain System quality (85.5 %), Information quality (84.5 %) and Interface quality (89.5%) perceptions with an overall usability of 85.9%. These results show that the system is greatly designed, intuitive and of ease of use. The software is publicly available and was developed in Matlab.
{"title":"An Open-Source Data Acquisition and Manual Segmentation System for Hand Gesture Recognition based on EMG","authors":"Jonathan A. Zea, Marco E. Benalcázar, Lorena Isabel Barona López, Ángel Leonardo Valdivieso Caraguay","doi":"10.1109/ETCM53643.2021.9590811","DOIUrl":"https://doi.org/10.1109/ETCM53643.2021.9590811","url":null,"abstract":"Due to lack of standardization in the data acquisition process, Hand Gesture Recognition literature has produced a high number of different but incompatible datasets. This paper presents a system for data acquisition of EMG signals and its manual segmentation. The system can be connected with the two most affordable wearable EMG armbands: Myo Armband and gForce Pro. The system allows to record a given number of samples per gesture during a given number of seconds. Twelve gestures were selected for being natural and the most reported in the literature. The system includes several features that enhance the quality of the dataset such as: strategies to maintain the volunteer attention, and the capability to resume recording in case of interruption. The system was evaluated using the Computer System Usability Questionnaire (CSUQ) over 10 data collectors. This questionnaire allowed to obtain System quality (85.5 %), Information quality (84.5 %) and Interface quality (89.5%) perceptions with an overall usability of 85.9%. These results show that the system is greatly designed, intuitive and of ease of use. The software is publicly available and was developed in Matlab.","PeriodicalId":438567,"journal":{"name":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114962477","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 : 2021-10-12DOI: 10.1109/ETCM53643.2021.9590764
Carlos Velasquez, M. A. Castro, F. Rodrı́guez, F. Espín, Nathaly Falconi
Public lighting systems base their efficiency on the correct measurement of the photometric properties of lamps and luminaires. Metrological traceability, given by external calibrations, is essential to guarantee confidence in the test results. Maintaining traceability implies periodically calibrating the measuring equipment. This work presents a proposal for optimizing the calibration intervals of the equipment used in the measurement of total luminous flux according to IES LM 78 and IES LM 51 for HID and IES LM 79 for SSL lamps. The theory of first-order gray models is applied to estimate the time intervals in which the equipment will go out of tolerance. A methodology is presented to use historical calibration certificates in non-symmetric intervals and calculate points of symmetric intervals to represent the equipment behavior. Additionally, an experimental scheme for a whole system is presented, by weighing each piece of equipment and its relevance in the test of HID and SSL lamps. Finally, the methodology is applied in the lighting laboratory of IIGE with its calibration certificates and the results and advantages are discussed.
{"title":"Optimization of the Calibration Interval of a Luminous Flux Measurement System in HID and SSL Lamps Using a Gray Model Approximation","authors":"Carlos Velasquez, M. A. Castro, F. Rodrı́guez, F. Espín, Nathaly Falconi","doi":"10.1109/ETCM53643.2021.9590764","DOIUrl":"https://doi.org/10.1109/ETCM53643.2021.9590764","url":null,"abstract":"Public lighting systems base their efficiency on the correct measurement of the photometric properties of lamps and luminaires. Metrological traceability, given by external calibrations, is essential to guarantee confidence in the test results. Maintaining traceability implies periodically calibrating the measuring equipment. This work presents a proposal for optimizing the calibration intervals of the equipment used in the measurement of total luminous flux according to IES LM 78 and IES LM 51 for HID and IES LM 79 for SSL lamps. The theory of first-order gray models is applied to estimate the time intervals in which the equipment will go out of tolerance. A methodology is presented to use historical calibration certificates in non-symmetric intervals and calculate points of symmetric intervals to represent the equipment behavior. Additionally, an experimental scheme for a whole system is presented, by weighing each piece of equipment and its relevance in the test of HID and SSL lamps. Finally, the methodology is applied in the lighting laboratory of IIGE with its calibration certificates and the results and advantages are discussed.","PeriodicalId":438567,"journal":{"name":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134119723","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 : 2021-10-12DOI: 10.1109/ETCM53643.2021.9590779
J. Castillo-Velazquez, Itzel-Iliana Rosas-Suarez, Diaan-Laura Fernandez-Tinoco
GEANT and AFRICACONNECT are the advanced networks for Europe and Africa respectively, offering advanced Internet backbone infrastructure to 72 countries, interconnecting the national research and education networks in, 43 countries in Europe and 29 countries in Africa. Europe and Africa are closely related, having three communication links among them that, are evolving in time, developing a better infrastructure with increasing bandwidth and backbone equipment capabilities. In this work, management emulation was developed for a network resulting from joining of the GEANT and AFRICACONNECT backbones topologies for 2020 under IPv6 communications protocols. The results show the capabilities of the GNS3 emulator when running these kinds of topologies in a limited computer resources environment and are useful for analysis by ISP companies.
{"title":"Management of the Continental Advanced Networks GEANT and AFRICACONNECT Joint as Two Autonomous Systems by BGP-4 Under IPv6: Using Limited Resources.","authors":"J. Castillo-Velazquez, Itzel-Iliana Rosas-Suarez, Diaan-Laura Fernandez-Tinoco","doi":"10.1109/ETCM53643.2021.9590779","DOIUrl":"https://doi.org/10.1109/ETCM53643.2021.9590779","url":null,"abstract":"GEANT and AFRICACONNECT are the advanced networks for Europe and Africa respectively, offering advanced Internet backbone infrastructure to 72 countries, interconnecting the national research and education networks in, 43 countries in Europe and 29 countries in Africa. Europe and Africa are closely related, having three communication links among them that, are evolving in time, developing a better infrastructure with increasing bandwidth and backbone equipment capabilities. In this work, management emulation was developed for a network resulting from joining of the GEANT and AFRICACONNECT backbones topologies for 2020 under IPv6 communications protocols. The results show the capabilities of the GNS3 emulator when running these kinds of topologies in a limited computer resources environment and are useful for analysis by ISP companies.","PeriodicalId":438567,"journal":{"name":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114793410","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 : 2021-10-12DOI: 10.1109/ETCM53643.2021.9590823
E. Severeyn, A. La Cruz, M. Huerta
The obesity epidemic has reached a high prevalence in adults, adolescents, and children. Overweight and obesity, together with a sedentary lifestyle and family history of cardiovascular disease, anticipate a high prevalence of metabolic diseases such as metabolic syndrome (MS), insulin resistance (IR), atherosclerosis, and glucose intolerance, increasing the risk of type 2 diabetes and cardiovascular disease (CVD). Although waist circumference (WC) is one of the best predictors of CVD, IR, and MS, this measure has limits because diagnostic cut-off points vary by ethnicity and race background. The waist to height ratio (WHtR) and waist to hip ratio (WHR) are suggested as better predictors because they are universal indexes that only varied because of gender. Some studies have used machine learning techniques, such as Support vector machine (SVM), clustering techniques, and random forest, in anthropometric measures such as waist circumference, hip circumference, BMI, WHtR, and WHR to evaluate the diagnosis of metabolic dysfunctions, like obesity, insulin resistance, among others. This work aims to classified impaired WHtR and WHR subjects using anthropometric parameters and the SVM technique as a classifier. This study used a database of 1978 subjects with 26 anthropometrics variables. Results showed that the SVM performed as an acceptable classification of subjects with abnormal WHtR values and abnormal WHR values using anthropometric measurements of skinfolds and circumferences.
{"title":"Classification of Impaired Waist to Height Ratio and Waist to Hip Ratio Using Support Vector Machine","authors":"E. Severeyn, A. La Cruz, M. Huerta","doi":"10.1109/ETCM53643.2021.9590823","DOIUrl":"https://doi.org/10.1109/ETCM53643.2021.9590823","url":null,"abstract":"The obesity epidemic has reached a high prevalence in adults, adolescents, and children. Overweight and obesity, together with a sedentary lifestyle and family history of cardiovascular disease, anticipate a high prevalence of metabolic diseases such as metabolic syndrome (MS), insulin resistance (IR), atherosclerosis, and glucose intolerance, increasing the risk of type 2 diabetes and cardiovascular disease (CVD). Although waist circumference (WC) is one of the best predictors of CVD, IR, and MS, this measure has limits because diagnostic cut-off points vary by ethnicity and race background. The waist to height ratio (WHtR) and waist to hip ratio (WHR) are suggested as better predictors because they are universal indexes that only varied because of gender. Some studies have used machine learning techniques, such as Support vector machine (SVM), clustering techniques, and random forest, in anthropometric measures such as waist circumference, hip circumference, BMI, WHtR, and WHR to evaluate the diagnosis of metabolic dysfunctions, like obesity, insulin resistance, among others. This work aims to classified impaired WHtR and WHR subjects using anthropometric parameters and the SVM technique as a classifier. This study used a database of 1978 subjects with 26 anthropometrics variables. Results showed that the SVM performed as an acceptable classification of subjects with abnormal WHtR values and abnormal WHR values using anthropometric measurements of skinfolds and circumferences.","PeriodicalId":438567,"journal":{"name":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125732046","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 : 2021-10-12DOI: 10.1109/ETCM53643.2021.9590777
Franklin Parrales-Bravo, Joel Torres-Urresto, Dayannara Avila-Maldonado, Julio Barzola-Monteses
Removing redundant features is one of the goals addressed by the feature subset selection techniques (FSS). According to some studies, the selection of non-redundant features is not guaranteed when using only a filter or a wrapper FSS approach. Thus, the aim of this research is to present a methodology to train intrusion detection models that considers a combination of filter and wrapper FSS techniques to guarantee the selection of non-redundant attributes in the data pre-processing phase. To test the effectiveness of the proposed technique, the accuracy of the trained models with the features selected by the proposed technique was evaluated on a set of malware detection data. The classifying algorithms selected for training the malware-detection models were: i) Random Forest, ii) C4.5, iii) Adaboost, iv) Gradient boosting. Based on the accuracy metric, the malware detection model that obtained the best results was the one trained with the RandomForest algorithm. This model achieved an average of 99.42% accuracy when using the proposed feature selection technique, improving by 0.10% the accuracy of the model trained with the same algorithm, but without the use of the proposed methodology. Therefore, we can conclude that the models trained with the proposed methodology provide similar results to the models that do not use it, having the advantage of removing all redundant features from the dataset.
去除冗余特征是特征子集选择技术(FSS)的目标之一。根据一些研究，当仅使用过滤器或包装器FSS方法时，不能保证非冗余特征的选择。因此，本研究的目的是提出一种训练入侵检测模型的方法，该方法考虑了过滤器和包装器FSS技术的组合，以保证在数据预处理阶段选择非冗余属性。为了验证所提技术的有效性，在一组恶意软件检测数据上对所提技术选择的特征训练模型的准确性进行了评估。用于训练恶意软件检测模型的分类算法为:i) Random Forest, ii) C4.5, iii) Adaboost, iv) Gradient boosting。基于精度度量，随机森林算法训练出的恶意软件检测模型效果最好。当使用本文提出的特征选择技术时，该模型的平均准确率达到99.42%，比使用相同算法训练的模型的准确率提高了0.10%，但没有使用本文提出的方法。因此，我们可以得出结论，使用所提出的方法训练的模型与不使用它的模型提供相似的结果，具有从数据集中删除所有冗余特征的优势。
{"title":"Relevant and Non-Redundant Feature Subset Selection Applied to the Detection of Malware in a Network","authors":"Franklin Parrales-Bravo, Joel Torres-Urresto, Dayannara Avila-Maldonado, Julio Barzola-Monteses","doi":"10.1109/ETCM53643.2021.9590777","DOIUrl":"https://doi.org/10.1109/ETCM53643.2021.9590777","url":null,"abstract":"Removing redundant features is one of the goals addressed by the feature subset selection techniques (FSS). According to some studies, the selection of non-redundant features is not guaranteed when using only a filter or a wrapper FSS approach. Thus, the aim of this research is to present a methodology to train intrusion detection models that considers a combination of filter and wrapper FSS techniques to guarantee the selection of non-redundant attributes in the data pre-processing phase. To test the effectiveness of the proposed technique, the accuracy of the trained models with the features selected by the proposed technique was evaluated on a set of malware detection data. The classifying algorithms selected for training the malware-detection models were: i) Random Forest, ii) C4.5, iii) Adaboost, iv) Gradient boosting. Based on the accuracy metric, the malware detection model that obtained the best results was the one trained with the RandomForest algorithm. This model achieved an average of 99.42% accuracy when using the proposed feature selection technique, improving by 0.10% the accuracy of the model trained with the same algorithm, but without the use of the proposed methodology. Therefore, we can conclude that the models trained with the proposed methodology provide similar results to the models that do not use it, having the advantage of removing all redundant features from the dataset.","PeriodicalId":438567,"journal":{"name":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","volume":"180 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114004745","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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