2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)最新文献_第7页

A Method for the Estimation of the Constant Load Torque by Using the Steady-State Electrical Torque Signal 一种利用稳态转矩信号估计恒载转矩的方法

2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM) Pub Date : 2021-10-12 DOI: 10.1109/ETCM53643.2021.9590699

Renato Ortega, M. Cerrada, D. Cabrera, Réne-Vinicio Sánchez

引用次数: 0

An Open-Source Data Acquisition and Manual Segmentation System for Hand Gesture Recognition based on EMG 基于肌电图的开源手势识别数据采集与人工分割系统

2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM) Pub Date : 2021-10-12 DOI: 10.1109/ETCM53643.2021.9590811

Jonathan A. Zea, Marco E. Benalcázar, Lorena Isabel Barona López, Ángel Leonardo Valdivieso Caraguay

{"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}

引用次数: 3

Optimization of the Calibration Interval of a Luminous Flux Measurement System in HID and SSL Lamps Using a Gray Model Approximation 利用灰色模型逼近优化HID和SSL灯光通量测量系统的校准间隔

2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM) Pub Date : 2021-10-12 DOI: 10.1109/ETCM53643.2021.9590764

Carlos Velasquez, M. A. Castro, F. Rodrı́guez, F. Espín, Nathaly Falconi

{"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}

引用次数: 0

Management of the Continental Advanced Networks GEANT and AFRICACONNECT Joint as Two Autonomous Systems by BGP-4 Under IPv6: Using Limited Resources. IPv6下BGP-4对大陆先进网络GEANT和AFRICACONNECT联合自治系统的管理:利用有限资源

2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM) Pub Date : 2021-10-12 DOI: 10.1109/ETCM53643.2021.9590779

J. Castillo-Velazquez, Itzel-Iliana Rosas-Suarez, Diaan-Laura Fernandez-Tinoco

引用次数: 0

Classification of Impaired Waist to Height Ratio and Waist to Hip Ratio Using Support Vector Machine 残障腰高比和腰臀比的支持向量机分类

2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM) Pub Date : 2021-10-12 DOI: 10.1109/ETCM53643.2021.9590823

E. Severeyn, A. La Cruz, M. Huerta

{"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}

引用次数: 0

Relevant and Non-Redundant Feature Subset Selection Applied to the Detection of Malware in a Network 相关和非冗余特征子集选择在网络恶意软件检测中的应用

2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM) Pub Date : 2021-10-12 DOI: 10.1109/ETCM53643.2021.9590777

Franklin Parrales-Bravo, Joel Torres-Urresto, Dayannara Avila-Maldonado, Julio Barzola-Monteses

{"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}

引用次数: 2