2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )最新文献
Pub Date : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9073365
R. Tolentino, Pinky Mae F. Guinto, Dorothy Ysabelle B. Maypa
This study aim to recognize gestures that may serve as an indication for an emergency situation. Different gesture that indicates an emergency condition has been observe and studied that will be used as comparison and recognition for recognition. In this study emergency situation are classified into three category namely medical, life threating condition and disaster. The acquisition of gestures was done using the latest camera technology of today which is the MS Kinect sensor. The researchers used the skeletal tracking capability of the sensor to acquire data that will represent the movement or gesture of the person. The recognition of this gesture with respect to an actual medical emergency will be done using Decision tree algorithm.
{"title":"Recognition of Different Emergency Situation through Body Gesture Using Microsoft Kinect Sensor","authors":"R. Tolentino, Pinky Mae F. Guinto, Dorothy Ysabelle B. Maypa","doi":"10.1109/HNICEM48295.2019.9073365","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073365","url":null,"abstract":"This study aim to recognize gestures that may serve as an indication for an emergency situation. Different gesture that indicates an emergency condition has been observe and studied that will be used as comparison and recognition for recognition. In this study emergency situation are classified into three category namely medical, life threating condition and disaster. The acquisition of gestures was done using the latest camera technology of today which is the MS Kinect sensor. The researchers used the skeletal tracking capability of the sensor to acquire data that will represent the movement or gesture of the person. The recognition of this gesture with respect to an actual medical emergency will be done using Decision tree algorithm.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"15 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74117875","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9073522
Xyrex A. Calang, Al John S. Timogan, O. J. Gerasta, Najie M. Pandian, V. J. Ylaya
This paper presents the development of a low costpassive high frequency tag antenna that is utilized for an inventory management radio frequency identification (rfid) system. The main material used in the study is the Magnetic Copper Wire. There are four types of antenna that has been designed namely the multilayer circular, multilayer rectangular, single layer circular and single layer rectangular tag antenna. Each type of antenna has some dimension and parameter combinations that is varied in order to determine the most optimized design. The designs had undergone simulation using the Computer Simulations Technology (CS T) StudioSuite 2018. The chosen fabricated designs were tested using RFID Reader and a Digital Oscilloscope. Analysis and comparison of actual results were done between the chosen fabricated antennas in order to determine the most optimized designs of tag antenna.
{"title":"Low Cost High Frequency Tag Antenna for an Inventory Management RFID System","authors":"Xyrex A. Calang, Al John S. Timogan, O. J. Gerasta, Najie M. Pandian, V. J. Ylaya","doi":"10.1109/HNICEM48295.2019.9073522","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073522","url":null,"abstract":"This paper presents the development of a low costpassive high frequency tag antenna that is utilized for an inventory management radio frequency identification (rfid) system. The main material used in the study is the Magnetic Copper Wire. There are four types of antenna that has been designed namely the multilayer circular, multilayer rectangular, single layer circular and single layer rectangular tag antenna. Each type of antenna has some dimension and parameter combinations that is varied in order to determine the most optimized design. The designs had undergone simulation using the Computer Simulations Technology (CS T) StudioSuite 2018. The chosen fabricated designs were tested using RFID Reader and a Digital Oscilloscope. Analysis and comparison of actual results were done between the chosen fabricated antennas in order to determine the most optimized designs of tag antenna.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"45 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73255498","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9073372
Aaron U. Aquino, Dustin G. Baylon, Francis Paul B. Dela Cruz, Ma. Armae Hazel Joy M. Medina, Girlie A. Reyes, Jascha Mae L. Tulauan, Timothy M. Amado, J. M. Ramos, L. K. Tolentino, E. Fernandez
Vermicomposting is a low-cost technology that naturally converts organic wastes into organic fertilizers, commonly called vermicompost, through the combined action of earthworms and mesophilic microorganisms. Vital parameters, such as moisture and temperature, must be considered in the vermicompost production to achieve optimum yield. However, manual monitoring and correction of these said parameters do not give guaranteed results. Also, the traditional process of harvesting vermicompost consumes longer time and requires more human intervention. As a solution, the proponents introduced the development of a system which monitors and corrects these vital parameters, determines the readiness of vermicompost for harvest using digital image processing, and automatically sieves the vermicompost. The system uses Raspberry Pi microcontroller, sensors, and an android phone for monitoring. To measure the system’s reliability and efficiency, the proponents conducted two setups of vermicomposting system – one controlled and the other uncontrolled. From the data gathered, the automated system surpassed the latter in terms of production time, yield quality and quantity.
{"title":"Development of a Solar-Powered Closed-Loop Vermicomposting System with Automatic Monitoring and Correction via IoT and Raspberry Pi Module","authors":"Aaron U. Aquino, Dustin G. Baylon, Francis Paul B. Dela Cruz, Ma. Armae Hazel Joy M. Medina, Girlie A. Reyes, Jascha Mae L. Tulauan, Timothy M. Amado, J. M. Ramos, L. K. Tolentino, E. Fernandez","doi":"10.1109/HNICEM48295.2019.9073372","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073372","url":null,"abstract":"Vermicomposting is a low-cost technology that naturally converts organic wastes into organic fertilizers, commonly called vermicompost, through the combined action of earthworms and mesophilic microorganisms. Vital parameters, such as moisture and temperature, must be considered in the vermicompost production to achieve optimum yield. However, manual monitoring and correction of these said parameters do not give guaranteed results. Also, the traditional process of harvesting vermicompost consumes longer time and requires more human intervention. As a solution, the proponents introduced the development of a system which monitors and corrects these vital parameters, determines the readiness of vermicompost for harvest using digital image processing, and automatically sieves the vermicompost. The system uses Raspberry Pi microcontroller, sensors, and an android phone for monitoring. To measure the system’s reliability and efficiency, the proponents conducted two setups of vermicomposting system – one controlled and the other uncontrolled. From the data gathered, the automated system surpassed the latter in terms of production time, yield quality and quantity.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"18 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75243729","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9073559
Dailyne D. Macasaet, A. Bandala, Ana Antoniette C. Illahi, E. Dadios, Sandy C. Lauguico
This paper intends to explore bomb detection technology by employing fuzzy logic in classifying Toluene, Carbon dioxide and Methane which are commonly used gases in bombs and other flammables. This research uses Matlab Fuzzy Logic toolbox in classifying gases into three hazard classifications- Safe, Hazardous, and Deadly based on gas concentration and exposure time. Provided in this paper are the standard gas levels which are considered safe to human with respect to exposure time. The output of the classification will help develop a more improved and accurate bomb detection system which is of great importance in today’s world.
{"title":"Hazard Classification of Toluene, Methane and Carbon Dioxide for Bomb Detection Using Fuzzy Logic","authors":"Dailyne D. Macasaet, A. Bandala, Ana Antoniette C. Illahi, E. Dadios, Sandy C. Lauguico","doi":"10.1109/HNICEM48295.2019.9073559","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073559","url":null,"abstract":"This paper intends to explore bomb detection technology by employing fuzzy logic in classifying Toluene, Carbon dioxide and Methane which are commonly used gases in bombs and other flammables. This research uses Matlab Fuzzy Logic toolbox in classifying gases into three hazard classifications- Safe, Hazardous, and Deadly based on gas concentration and exposure time. Provided in this paper are the standard gas levels which are considered safe to human with respect to exposure time. The output of the classification will help develop a more improved and accurate bomb detection system which is of great importance in today’s world.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"89 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78395794","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9072726
Anne Louise M. Cuenca, Ysabelle Rey C. Dizon, H. A. Espinosa, Ellizer Mernard L. Mendoza, Fhaym C. Sarrondo, Angelo R. dela Cruz, Edison A. Roxas, C. Suarez, Kanny Krizzy D. Serrano
Diabetic foot ulceration (DFU) which affects approximately 15% of diabetic patients has the highest prevalence of occurring in the presence of Diabetic Peripheral Neuropathy (DPN). Plantar pressure modelling is the chosen method of the group in classifying a person with and without DPN since existing studies only consider classification of data collected from the F-Scan System by Tekscan. To further explore the understanding of a person with and without DPN, an insole prototype was proposed using plantar pressure modelling with pressure-sensitive conductive sheet to analyze and to compare the data that was gathered from the plantar pressure sensors and F-scan System and to provide classification whether the patient is with or without DPN.
{"title":"Development of Plantar Pressure In-sole System for Diabetic Peripheral Neuropathy Analysis using Pressure Mapping Sensors","authors":"Anne Louise M. Cuenca, Ysabelle Rey C. Dizon, H. A. Espinosa, Ellizer Mernard L. Mendoza, Fhaym C. Sarrondo, Angelo R. dela Cruz, Edison A. Roxas, C. Suarez, Kanny Krizzy D. Serrano","doi":"10.1109/HNICEM48295.2019.9072726","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072726","url":null,"abstract":"Diabetic foot ulceration (DFU) which affects approximately 15% of diabetic patients has the highest prevalence of occurring in the presence of Diabetic Peripheral Neuropathy (DPN). Plantar pressure modelling is the chosen method of the group in classifying a person with and without DPN since existing studies only consider classification of data collected from the F-Scan System by Tekscan. To further explore the understanding of a person with and without DPN, an insole prototype was proposed using plantar pressure modelling with pressure-sensitive conductive sheet to analyze and to compare the data that was gathered from the plantar pressure sensors and F-scan System and to provide classification whether the patient is with or without DPN.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"12 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84497251","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9073419
Joshua A. Meneses, G. F. Apolinario, Jay-ar Maglente, Jayson G. Cordero
A typical transmission system uses high-voltage threephase alternating current as a transmission line. But as time pass by, the HVDC transmission system shows more flexibility that makes the system work more efficiently. This paper will focus on a design of HVDC transmission system that will showcase the advantages of the system in terms of the reliability, economical, and sustainability of transmission route, converter station design and the overall effect on the stability of the power system due to specific changes of the materials/equipment used in building the system. The parts/components of the said transmission system will be computed manually and simulated through the help of different software such as MATLAB Simulink and Paladin Database. The raw values such as load forecast and the location of the system will be provided through reliable data together with the needed standards using PEC, NEC, and more for a more realistic outcome.
{"title":"Design of HVDC Transmission System Connecting Boracay, Panay, and Negros Islands","authors":"Joshua A. Meneses, G. F. Apolinario, Jay-ar Maglente, Jayson G. Cordero","doi":"10.1109/HNICEM48295.2019.9073419","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073419","url":null,"abstract":"A typical transmission system uses high-voltage threephase alternating current as a transmission line. But as time pass by, the HVDC transmission system shows more flexibility that makes the system work more efficiently. This paper will focus on a design of HVDC transmission system that will showcase the advantages of the system in terms of the reliability, economical, and sustainability of transmission route, converter station design and the overall effect on the stability of the power system due to specific changes of the materials/equipment used in building the system. The parts/components of the said transmission system will be computed manually and simulated through the help of different software such as MATLAB Simulink and Paladin Database. The raw values such as load forecast and the location of the system will be provided through reliable data together with the needed standards using PEC, NEC, and more for a more realistic outcome.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"10 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85461854","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9072878
Maverick Rivera, J. R. D. del Rosario, A. Bandala
Development of Unmanned Aerial Vehicle (UAV) is now a popular field in research. In most of its applications, a pathfinding algorithm is needed in order to find the optimal path and avoid obstacles. In this paper, a genetic algorithm is implemented in order to determine the optimal path for a UAV that will avoid obstacles along the way. The genetic algorithm implemented uses variable-length chromosomes to solve the problem. The results of the simulation of the system yield an average of 29 generations and avoided 53, 500 collisions to find the best path.
{"title":"Genetic Algorithm Based 3D Motion Planning for Unmanned Aerial Vehicle","authors":"Maverick Rivera, J. R. D. del Rosario, A. Bandala","doi":"10.1109/HNICEM48295.2019.9072878","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072878","url":null,"abstract":"Development of Unmanned Aerial Vehicle (UAV) is now a popular field in research. In most of its applications, a pathfinding algorithm is needed in order to find the optimal path and avoid obstacles. In this paper, a genetic algorithm is implemented in order to determine the optimal path for a UAV that will avoid obstacles along the way. The genetic algorithm implemented uses variable-length chromosomes to solve the problem. The results of the simulation of the system yield an average of 29 generations and avoided 53, 500 collisions to find the best path.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"11 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85646046","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9072862
Paul Adrian E. Divino, Michelle P. Prunes, Kevin O. Maglinte
A Single-Inductor Multiple-Output (SIMO) Boost DC-DC Converter that operates for Ultra-Low Power (ULP) Applications is designed in 65nm TSMC technology. The converter boosts and regulates three output voltages using Ripple-Based Control of Pulse Frequency Modulation (PFM) while operating in Discontinuous Conduction Mode (DCM). To control the regulation of the output voltages, its control system follows an algorithm that is converted into digital logic circuits and helps in synchronizing the power MOS switching in the power stage. Aside from using Ripple- Based Control and DCM operation, the designed converter also uses a Strong-Arm comparator, which has no power consumption during its idle state to help ensure good power conversion efficiency of the system, making it suitable for the target application. This converter is suitable for indoor applications, for its input voltage could vary from 0.4V, for low light intensity situation, to 0.6V. With output voltages of 1.2V for analog core and two 1 V for digital cores, the converter shows excellent overall transient response and a peak power efficiency of 86% at 1mA load current.
{"title":"Single-Inductor Multiple-Output (SIMO) Boost DC-DC Converter using Ripple-Based Control for Ultra-Low Power Indoor Light Energy Harvesting Applications","authors":"Paul Adrian E. Divino, Michelle P. Prunes, Kevin O. Maglinte","doi":"10.1109/HNICEM48295.2019.9072862","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072862","url":null,"abstract":"A Single-Inductor Multiple-Output (SIMO) Boost DC-DC Converter that operates for Ultra-Low Power (ULP) Applications is designed in 65nm TSMC technology. The converter boosts and regulates three output voltages using Ripple-Based Control of Pulse Frequency Modulation (PFM) while operating in Discontinuous Conduction Mode (DCM). To control the regulation of the output voltages, its control system follows an algorithm that is converted into digital logic circuits and helps in synchronizing the power MOS switching in the power stage. Aside from using Ripple- Based Control and DCM operation, the designed converter also uses a Strong-Arm comparator, which has no power consumption during its idle state to help ensure good power conversion efficiency of the system, making it suitable for the target application. This converter is suitable for indoor applications, for its input voltage could vary from 0.4V, for low light intensity situation, to 0.6V. With output voltages of 1.2V for analog core and two 1 V for digital cores, the converter shows excellent overall transient response and a peak power efficiency of 86% at 1mA load current.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"97 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80938075","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9072907
Timothy M. Amado, Ma. Rica Bunuan, Relamae F. Chicote, Sheila May C. Espenida, Honeyleth L. Masangcay, Camille H. Ventura, L. K. Tolentino, M. V. Padilla, G. A. Madrigal, Lejan Alfred C. Enriquez
One of the necessities of human to survive is food and meat is one of mainly consumed food by humans. Thus, a level of quality of food is a must to be safely consumed. There have been some cases of adulteration of meats, which can cause harm to consumers. Adulteration can lead to bacteria contamination which are difficult to determine the presence of bacteria without an instrument or food laboratory tests. Nowadays, the idea of applying machine learning in the field of food microbiology is becoming a trend. And one of these applications is on detection and classification of bacteria in food products. Hence, this study aims to apply machine learning algorithms to construct predictive models to detect the presence of bacteria such as Escherichia Coli and Staphylococcus Aureus in raw meat and determine which model is best through accuracy and cross-validation. In this study, five machine learning algorithms are used which are K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Random Forest (RF), Naïve-Bayes Classifier (NB), and Artificial Neural Network (ANN). All models are implemented effectively each having an accuracy of 94.97%, 91.84%, 97.57%, 61.46%, and 66.84% respectively. A web application is created using the shiny package in R to attain a standalone application used to show the detected bacteria.
{"title":"Development of Predictive Models using Machine Learning Algorithms for Food Adulterants Bacteria Detection","authors":"Timothy M. Amado, Ma. Rica Bunuan, Relamae F. Chicote, Sheila May C. Espenida, Honeyleth L. Masangcay, Camille H. Ventura, L. K. Tolentino, M. V. Padilla, G. A. Madrigal, Lejan Alfred C. Enriquez","doi":"10.1109/HNICEM48295.2019.9072907","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072907","url":null,"abstract":"One of the necessities of human to survive is food and meat is one of mainly consumed food by humans. Thus, a level of quality of food is a must to be safely consumed. There have been some cases of adulteration of meats, which can cause harm to consumers. Adulteration can lead to bacteria contamination which are difficult to determine the presence of bacteria without an instrument or food laboratory tests. Nowadays, the idea of applying machine learning in the field of food microbiology is becoming a trend. And one of these applications is on detection and classification of bacteria in food products. Hence, this study aims to apply machine learning algorithms to construct predictive models to detect the presence of bacteria such as Escherichia Coli and Staphylococcus Aureus in raw meat and determine which model is best through accuracy and cross-validation. In this study, five machine learning algorithms are used which are K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Random Forest (RF), Naïve-Bayes Classifier (NB), and Artificial Neural Network (ANN). All models are implemented effectively each having an accuracy of 94.97%, 91.84%, 97.57%, 61.46%, and 66.84% respectively. A web application is created using the shiny package in R to attain a standalone application used to show the detected bacteria.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"39 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78563589","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 : 2019-11-01DOI: 10.1109/HNICEM48295.2019.9072846
Ma. Ian P. Delos Trinos, Jozar H. Rios, Keith Gabriel O. Portades, Paulo Rae O. Portades, Renielle Miguel P. Langreo, Mideth B. Abisado
Student attendance in classroom-based learning usually becomes a pain stake for teachers in terms of monitoring and records keeping. The study provides a solution to this by using the technology of image processing applied in facial recognition. A software was developed to check the student attendance in real-time. The ISO 9126 gauges for functional stability, usability, reliability, portability, efficiency, and maintainability. The functionalities and user acceptance were measured within the bounds of software engineering and measured acceptable to a mean very acceptable rating of 3.74.
{"title":"Real-time Class Attendance Monitoring using Smart Face Recognition","authors":"Ma. Ian P. Delos Trinos, Jozar H. Rios, Keith Gabriel O. Portades, Paulo Rae O. Portades, Renielle Miguel P. Langreo, Mideth B. Abisado","doi":"10.1109/HNICEM48295.2019.9072846","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072846","url":null,"abstract":"Student attendance in classroom-based learning usually becomes a pain stake for teachers in terms of monitoring and records keeping. The study provides a solution to this by using the technology of image processing applied in facial recognition. A software was developed to check the student attendance in real-time. The ISO 9126 gauges for functional stability, usability, reliability, portability, efficiency, and maintainability. The functionalities and user acceptance were measured within the bounds of software engineering and measured acceptable to a mean very acceptable rating of 3.74.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"25 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77122847","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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