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/HNICEM48295.2019.9072830
Myla B. Cabanada, Jesus M. Martinez, Eryl Nico Morales, Flordeliza L. Valiente, Oliver Mallari
The research aims to implement a 450Watts synchronous DC-DC boost converter with an adjustable output current operation. A unit was built and tested. The power supply unit (PSU) was designed for battery charging applications and designed to perform in continuous conduction mode and to operate at two modes: constant-voltage (CV) and constant-current (CC). Initially the PSU was operating at CV Mode. Once the PSU reached the current limit, power supply operates at constant current mode, the power supply acts as a current source with varying output voltage depending on the value of the load resistance. The PSU uses the inherent fault protections of main controller such as cycle-by-cycle current limiting, inrush current limiting, hiccup mode short circuit/overload protection, and the researchers implement over-voltage protection (OVP), over-temperature protection (OTP), and reverse polarity protection (RPP) by using additional comparator circuitry. The results presented in this study show that the design is has a regulated output voltage of 53.9V with maximum of 236mV peak-to-peak voltage ripple and 120mA peak-to-peak current ripple which was measured at full load condition. Through the constant voltage test, the unit can maintain a constant output current from 2A up to 8A by adjusting the potentiometer. The 96% efficiency was achieved at 3A load from an input voltage range of 11.34V to 13.86V.
{"title":"Performance Evaluation of a Synchronous DC-DC Boost Converter with Adjustable Output Current","authors":"Myla B. Cabanada, Jesus M. Martinez, Eryl Nico Morales, Flordeliza L. Valiente, Oliver Mallari","doi":"10.1109/HNICEM48295.2019.9072830","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072830","url":null,"abstract":"The research aims to implement a 450Watts synchronous DC-DC boost converter with an adjustable output current operation. A unit was built and tested. The power supply unit (PSU) was designed for battery charging applications and designed to perform in continuous conduction mode and to operate at two modes: constant-voltage (CV) and constant-current (CC). Initially the PSU was operating at CV Mode. Once the PSU reached the current limit, power supply operates at constant current mode, the power supply acts as a current source with varying output voltage depending on the value of the load resistance. The PSU uses the inherent fault protections of main controller such as cycle-by-cycle current limiting, inrush current limiting, hiccup mode short circuit/overload protection, and the researchers implement over-voltage protection (OVP), over-temperature protection (OTP), and reverse polarity protection (RPP) by using additional comparator circuitry. The results presented in this study show that the design is has a regulated output voltage of 53.9V with maximum of 236mV peak-to-peak voltage ripple and 120mA peak-to-peak current ripple which was measured at full load condition. Through the constant voltage test, the unit can maintain a constant output current from 2A up to 8A by adjusting the potentiometer. The 96% efficiency was achieved at 3A load from an input voltage range of 11.34V to 13.86V.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"87 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":"73200492","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/HNICEM48295.2019.9073361
Leonardro A. Venancio, Armyn C. Sy, R. Bedruz, E. Dadios
This paper presents a charge level monitoring system for lead acid battery bank in Solar Panel setup. The research implements the approximate linear relationship between the charge level and the current-voltage for lead acid batteries. Prediction method utilizes is the objective fuzzy logic approach. Both the interphase of the instrument and the fuzzy system together with the fuzzy rule system were created using LabView. Dataset used is based on an actual 12-hour data gathering of charging cycle and current-voltage readings. Simulation results show that the developed system generated correctly the charge level of the battery using only the instantaneous voltage and current readings from the sensors.
{"title":"Development of Charge Level Monitoring of Lead-Acid Battery Bank for PV System using Fuzzy Logic in LabView","authors":"Leonardro A. Venancio, Armyn C. Sy, R. Bedruz, E. Dadios","doi":"10.1109/HNICEM48295.2019.9073361","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073361","url":null,"abstract":"This paper presents a charge level monitoring system for lead acid battery bank in Solar Panel setup. The research implements the approximate linear relationship between the charge level and the current-voltage for lead acid batteries. Prediction method utilizes is the objective fuzzy logic approach. Both the interphase of the instrument and the fuzzy system together with the fuzzy rule system were created using LabView. Dataset used is based on an actual 12-hour data gathering of charging cycle and current-voltage readings. Simulation results show that the developed system generated correctly the charge level of the battery using only the instantaneous voltage and current readings from the sensors.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"115 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":"73364425","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/HNICEM48295.2019.9073599
Reagan L. Galvez, E. Dadios, A. Bandala, R. R. Vicerra
Manual detection of threat objects in an X-ray machine is a tedious task for the baggage inspectors in airports, train stations, and establishments. Objects inside the baggage seen by the X-ray machine are commonly occluded and difficult to recognize when rotated. Because of this, there is a high chance of missed detection, particularly during rush hour. As a solution, this paper presents a You Only Look Once (YOLO)based object detector for the automated detection of threat objects in an X-ray image. The study compared the performance between using transfer learning and training from scratch in an IEDXray dataset which composed of scanned Xray images of improvised explosive device (IED) replicas. The results of this research indicate that training YOLO from scratch beats transfer learning in quick detection of threat objects. Training from scratch achieved a mean average precision (mAP) of 45.89% in 416×416 image, 51.48% in 608×608 image, and 52.40% in a multi-scale image. On the other hand, using transfer learning achieved only an mAP of 29.54% while 29.17% mAP in a multi-scale image.
对于机场、火车站和其他场所的行李检查人员来说，用x光机手动检测威胁物体是一项乏味的任务。x光机看到的行李内的物体通常是闭塞的，旋转时难以识别。正因为如此，漏检的几率很高，尤其是在高峰时段。作为解决方案，本文提出了一种基于YOLO (You Only Look Once)的目标检测器，用于自动检测x射线图像中的威胁目标。该研究比较了在iedx射线数据集中使用迁移学习和从头开始训练的性能，该数据集由简易爆炸装置(IED)复制品的扫描x射线图像组成。研究结果表明，在快速检测威胁目标方面，从头开始训练YOLO优于迁移学习。从头开始训练的平均精度(mAP)在416×416图像上达到45.89%，在608×608图像上达到51.48%，在多尺度图像上达到52.40%。另一方面，使用迁移学习的mAP仅为29.54%，而多尺度图像的mAP为29.17%。
{"title":"YOLO-based Threat Object Detection in X-ray Images","authors":"Reagan L. Galvez, E. Dadios, A. Bandala, R. R. Vicerra","doi":"10.1109/HNICEM48295.2019.9073599","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073599","url":null,"abstract":"Manual detection of threat objects in an X-ray machine is a tedious task for the baggage inspectors in airports, train stations, and establishments. Objects inside the baggage seen by the X-ray machine are commonly occluded and difficult to recognize when rotated. Because of this, there is a high chance of missed detection, particularly during rush hour. As a solution, this paper presents a You Only Look Once (YOLO)based object detector for the automated detection of threat objects in an X-ray image. The study compared the performance between using transfer learning and training from scratch in an IEDXray dataset which composed of scanned Xray images of improvised explosive device (IED) replicas. The results of this research indicate that training YOLO from scratch beats transfer learning in quick detection of threat objects. Training from scratch achieved a mean average precision (mAP) of 45.89% in 416×416 image, 51.48% in 608×608 image, and 52.40% in a multi-scale image. On the other hand, using transfer learning achieved only an mAP of 29.54% while 29.17% mAP in a multi-scale image.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"62 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":"73830770","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/HNICEM48295.2019.9072791
John Daniel M. Valencia, Al Joseph T. Laure, Niño Mark R. Centino, Bernie S. Fabito, Joseph Marvin Imperial, Ramon L. Rodriguez, Angelica De La Cruz, Manolito V. Octaviano, Marilou N. Jamis
Social Media holds a substantial amount of text data that can help organizations better understand their clients. For students of National University (NU) – Manila, Facebook serves as a medium to express their opinions and create topics for discussion that may generally speak about the University. Through Topic Modeling using Latent Dirichlet Allocation (LDA), various experiments were conducted to identify the topics discussed by the students based on the highest coherence score value obtained. From these experiments, a total of twenty (20) topics with Alpha and Beta values set to one (1) revealed the highest coherence. The topics were labeled and revealed interesting insights. Personal relationships and school-related concerns were the common topics posted on the two Facebook pages. To further improve the study, a chronological approach for topic modeling is recommended.
{"title":"Understanding Anonymous Social Media Posts using Topic Modeling","authors":"John Daniel M. Valencia, Al Joseph T. Laure, Niño Mark R. Centino, Bernie S. Fabito, Joseph Marvin Imperial, Ramon L. Rodriguez, Angelica De La Cruz, Manolito V. Octaviano, Marilou N. Jamis","doi":"10.1109/HNICEM48295.2019.9072791","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072791","url":null,"abstract":"Social Media holds a substantial amount of text data that can help organizations better understand their clients. For students of National University (NU) – Manila, Facebook serves as a medium to express their opinions and create topics for discussion that may generally speak about the University. Through Topic Modeling using Latent Dirichlet Allocation (LDA), various experiments were conducted to identify the topics discussed by the students based on the highest coherence score value obtained. From these experiments, a total of twenty (20) topics with Alpha and Beta values set to one (1) revealed the highest coherence. The topics were labeled and revealed interesting insights. Personal relationships and school-related concerns were the common topics posted on the two Facebook pages. To further improve the study, a chronological approach for topic modeling is recommended.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"17 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":"81868771","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/HNICEM48295.2019.9073407
Adrian Jose D. Antoja, Patrick Amiel O. Lafamia, Clarizza Allen B. Yang, G. Magwili, R. Santiago
The accuracy of the electricity demand forecast is important in the operations of a power system. The objective of this paper is to generate an automated forecast model with better accuracy than its predecessors. The Automated ShortTerm Load Forecasting Using Modified Stochastic Hour Ahead Proportion (SHAP) Analysis is generated using the C# program. The constructed application would then use an excel spreadsheet to input data. Therefore, the data would be used as a basis for the construction of the forecast model. The output would then display the equation and the graph of the constructed forecast model. Based on the output of the program, the generated forecast model has a MAPE and SDE value of 0.941725 and 1.149855 respectively. The MAPE and SDE value of the generated forecast model is significantly lower than the MAPE and SDE values of the SHAP, WMA, SHAP-WMA which are 3.765681 and 2.822254, 5.610123 and 10.312887, 3.278946 and 3.055406 respectively. This comparison shows that the Modified SHAP Analysis is statistically better than its predecessors.
{"title":"Automated Short-Term Load Forecasting Using Modified Stochastic Hour Ahead Proportion (SHAP) Analysis","authors":"Adrian Jose D. Antoja, Patrick Amiel O. Lafamia, Clarizza Allen B. Yang, G. Magwili, R. Santiago","doi":"10.1109/HNICEM48295.2019.9073407","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073407","url":null,"abstract":"The accuracy of the electricity demand forecast is important in the operations of a power system. The objective of this paper is to generate an automated forecast model with better accuracy than its predecessors. The Automated ShortTerm Load Forecasting Using Modified Stochastic Hour Ahead Proportion (SHAP) Analysis is generated using the C# program. The constructed application would then use an excel spreadsheet to input data. Therefore, the data would be used as a basis for the construction of the forecast model. The output would then display the equation and the graph of the constructed forecast model. Based on the output of the program, the generated forecast model has a MAPE and SDE value of 0.941725 and 1.149855 respectively. The MAPE and SDE value of the generated forecast model is significantly lower than the MAPE and SDE values of the SHAP, WMA, SHAP-WMA which are 3.765681 and 2.822254, 5.610123 and 10.312887, 3.278946 and 3.055406 respectively. This comparison shows that the Modified SHAP Analysis is statistically better than its predecessors.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"19 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":"82103252","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/HNICEM48295.2019.9072836
L. Ambata, Isabel Angela P. del Castillo, Jeremiah Rod H. Jacinto, Cellix Mark T. Santos
Traffic congestion in the Philippines is diverse consisting public and private vehicles. One approach of this is to design a system that can count, detect, recognize, and classify public and private vehicles from a surveillance video. This research introduces the development of the said system, to be used as a statistical data for implementing traffic rules. The dataset the researchers used consists of 13,600 images: 10,880 images for training and 2,720 images for testing. These were obtained from a gas station video source, for the vehicles frequently passing though in a gas station. The researchers used an algorithm called Convolutional Neural Network for the detecting and classifying vehicles.
{"title":"Public and Private Vehicle Quantification and Classification using Vehicle Detection and Recognition","authors":"L. Ambata, Isabel Angela P. del Castillo, Jeremiah Rod H. Jacinto, Cellix Mark T. Santos","doi":"10.1109/HNICEM48295.2019.9072836","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072836","url":null,"abstract":"Traffic congestion in the Philippines is diverse consisting public and private vehicles. One approach of this is to design a system that can count, detect, recognize, and classify public and private vehicles from a surveillance video. This research introduces the development of the said system, to be used as a statistical data for implementing traffic rules. The dataset the researchers used consists of 13,600 images: 10,880 images for training and 2,720 images for testing. These were obtained from a gas station video source, for the vehicles frequently passing though in a gas station. The researchers used an algorithm called Convolutional Neural Network for the detecting and classifying vehicles.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"15 5 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":"79845508","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/HNICEM48295.2019.9072756
Jo-Ann V. Magsumbol, Vincent Jan D. Almero, Marife A. Rosales, A. Bandala, E. Dadios
Smart aquaculture is making a name these days due to an ever-increasing demand for an alternative source of protein, fatty acids, vitamins, minerals and essential nutrients, which make it superior over animal meat. To address the rising demand for healthy source of meat, aqua farmers adapt methods wherein they can increase the fish supply all year round. This paper makes use of the fuzzy logic system to identify the current growth stage of carp fish in the pond. The output of the system will be used as an actuator for the feeder system in the aquafarm. Results show that the system successfully identified the current status of the fish in the study.
{"title":"A Fuzzy Logic Approach for Fish Growth Assessment","authors":"Jo-Ann V. Magsumbol, Vincent Jan D. Almero, Marife A. Rosales, A. Bandala, E. Dadios","doi":"10.1109/HNICEM48295.2019.9072756","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072756","url":null,"abstract":"Smart aquaculture is making a name these days due to an ever-increasing demand for an alternative source of protein, fatty acids, vitamins, minerals and essential nutrients, which make it superior over animal meat. To address the rising demand for healthy source of meat, aqua farmers adapt methods wherein they can increase the fish supply all year round. This paper makes use of the fuzzy logic system to identify the current growth stage of carp fish in the pond. The output of the system will be used as an actuator for the feeder system in the aquafarm. Results show that the system successfully identified the current status of the fish in the study.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"19 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":"84506149","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/HNICEM48295.2019.9072730
A. Culaba, J. Juan, P. M. Ching, A. Mayol, E. Sybingco, A. Ubando
Biomass derived from microalgae is an emerging technology and attractive alternative source for biofuels. However, its exclusive production cannot be feasibly commercialized because of economic and environmental sustainability issues. The biorefinery concept allows microalgae to be efficiently converted into biofuels and other high-valued products, such as cosmetics, nutraceuticals, and pharmaceuticals. Nonetheless, this venture would require large capital investments that must be strategically scheduled across the lives of the investments, while keeping a reliable forecast of market growth. A multi-period multi-objective mixed integer non-linear programming (MINLP) model is proposed in this study to determine optimal investment schedule and operational decisions that would simultaneously maximize the net present value (NPV) and minimize the greenhouse gas (GHG) emissions of an algal biorefinery. An illustrative case study and scenario analyses demonstrate the validity and the capabilities of the proposed model.
{"title":"Optimal Synthesis of Algal Biorefineries for Biofuel Production Based on Techno-Economic and Environmental Efficiency","authors":"A. Culaba, J. Juan, P. M. Ching, A. Mayol, E. Sybingco, A. Ubando","doi":"10.1109/HNICEM48295.2019.9072730","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072730","url":null,"abstract":"Biomass derived from microalgae is an emerging technology and attractive alternative source for biofuels. However, its exclusive production cannot be feasibly commercialized because of economic and environmental sustainability issues. The biorefinery concept allows microalgae to be efficiently converted into biofuels and other high-valued products, such as cosmetics, nutraceuticals, and pharmaceuticals. Nonetheless, this venture would require large capital investments that must be strategically scheduled across the lives of the investments, while keeping a reliable forecast of market growth. A multi-period multi-objective mixed integer non-linear programming (MINLP) model is proposed in this study to determine optimal investment schedule and operational decisions that would simultaneously maximize the net present value (NPV) and minimize the greenhouse gas (GHG) emissions of an algal biorefinery. An illustrative case study and scenario analyses demonstrate the validity and the capabilities of the proposed model.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"4 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":"81753277","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/HNICEM48295.2019.9072839
Wilfredo A. Claur, Jessa Cristie Montaño, Ezyl Sarita, Andrew Gumawa, Joevan Guilleran, K. Caceres, Adrian Langcoy, Krizia Marie Monotillia, Karce Ortiz, Mark Rioffer, Jinky Damas, Jerson Mag-aso, Ahenor Almaquer
Nature has a lot to offer to people. Source of food and income are just few. Waste from natural sources of food is abundant in coastal areas where the source of living is fishing. The study is focused on utilizing food waste from Cerastoderma edule commonly known in the Philippines as Litob and river sand as additives in making recycled (high density polyethylene) HDPE composite plastic tiles. The researchers prepared the materials according to the set conditions. Composite plastic tiles made of remoulded HDPE plastic, river sand and Cerastoderma edule shells were fabricated in five different proportions. It was found out that the composite plastic tile with 40:30:30 ratio by mass inhibits the best characteristics in terms of average density, thermal resistance, and impact strength. The study shows that we can be able to make useful building materials such composite plastic tile from shells, river sand and HDPE plastic.
{"title":"Utilization of Food Waste as Materials for Composite Plastic Tile","authors":"Wilfredo A. Claur, Jessa Cristie Montaño, Ezyl Sarita, Andrew Gumawa, Joevan Guilleran, K. Caceres, Adrian Langcoy, Krizia Marie Monotillia, Karce Ortiz, Mark Rioffer, Jinky Damas, Jerson Mag-aso, Ahenor Almaquer","doi":"10.1109/HNICEM48295.2019.9072839","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072839","url":null,"abstract":"Nature has a lot to offer to people. Source of food and income are just few. Waste from natural sources of food is abundant in coastal areas where the source of living is fishing. The study is focused on utilizing food waste from Cerastoderma edule commonly known in the Philippines as Litob and river sand as additives in making recycled (high density polyethylene) HDPE composite plastic tiles. The researchers prepared the materials according to the set conditions. Composite plastic tiles made of remoulded HDPE plastic, river sand and Cerastoderma edule shells were fabricated in five different proportions. It was found out that the composite plastic tile with 40:30:30 ratio by mass inhibits the best characteristics in terms of average density, thermal resistance, and impact strength. The study shows that we can be able to make useful building materials such composite plastic tile from shells, river sand and HDPE plastic.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"1 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":"83041756","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/HNICEM48295.2019.9072778
D. G. Evangelista, Dr. Ryan Rhay Vicerra, Dr. Argel A. Bandala
Detonation velocity or rate of energy release is an important property to consider when rating an explosive. It is a critical parameter used for estimating explosive performance as it can indicate the intensity of detonation. The purpose of this research study is to propose an artificial neural network model that would aid in the estimation of detonation velocities of a high explosive specifically, tetranitromethane-nitrobenzene (TNM/NB) mixture, with varying parameters
{"title":"Use of Artificial Neural Network in the Estimation of Detonation Velocity for Tetranitromethane-Nitrobenzene Mixture","authors":"D. G. Evangelista, Dr. Ryan Rhay Vicerra, Dr. Argel A. Bandala","doi":"10.1109/HNICEM48295.2019.9072778","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072778","url":null,"abstract":"Detonation velocity or rate of energy release is an important property to consider when rating an explosive. It is a critical parameter used for estimating explosive performance as it can indicate the intensity of detonation. The purpose of this research study is to propose an artificial neural network model that would aid in the estimation of detonation velocities of a high explosive specifically, tetranitromethane-nitrobenzene (TNM/NB) mixture, with varying parameters","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"60 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":"81025193","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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