2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )最新文献
Jessie R. Balbin, Leonardo D. Valiente, Kim Martin P. Monsale, Emmanuel D. Olorvida, Gerard Glenn V. Salazar, Lyzza Marie L. Soto
{"title":"Determination of Calorie Content in Different Type of Foods using Image Processing","authors":"Jessie R. Balbin, Leonardo D. Valiente, Kim Martin P. Monsale, Emmanuel D. Olorvida, Gerard Glenn V. Salazar, Lyzza Marie L. Soto","doi":"10.1109/HNICEM48295.2019.9073397","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073397","url":null,"abstract":"This paper discusses a system that estimates the weight and calorie content of a food specifically chicken and fish based single image by using a fixed-placed camera in a hardware system. Convolutional Neural Network (CNN) was the integrated algorithm to recognize food on an image. Graph Cut image segmentation was used to analyze to determine the regions of the food in the image. Volume estimation based its measurement on the area of the segmented food image and the height of the food measured by fixed-placed ultrasonic sensor. The system was tested by each part of the chicken and fish for 10 trials each as well as if it is fried or grilled which resulted to a food detection accuracy of 91.82%, a mean accuracy of 88.18% for the calorie estimation.","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":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76380657","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}
Pablo Q. Acuin, Jonathan Q. Puerto, Rodnel O. Tamayo, Geoffrey L. Abulencia, Rolando F. Ibuig
{"title":"Development of a Functionally-Tested Hybrid Electric Train","authors":"Pablo Q. Acuin, Jonathan Q. Puerto, Rodnel O. Tamayo, Geoffrey L. Abulencia, Rolando F. Ibuig","doi":"10.1109/HNICEM48295.2019.9072793","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072793","url":null,"abstract":"This paper presents the development of a local train set aiming to augment the number of fleets presently the Philippine National Railways (PNR) provides. While importation has been the normal practice to supplement trains in the country’s railway lines, this outsourcing is becoming more and more impractical as localization provides compelling advantages of cheaper cost and easier troubleshooting and maintenance. The train is composed of five (5) coaches which is powered by either generator set and/or batteries setting up the hybrid system. The coach assembly was designed using Solidworks and underwent stress analysis to verify its compactness and credibility. The addition of load sharing and regenerative braking technology furthers energy efficiency. To establish interaction with minimal wirings among systems making up the train set, a control system utilizing Programmable Logic Controller (PLC) and Human-Machine Interface (HMI) with CC-Link Central System was installed. Performance testing and Reliability-Availability- Maintainability-Safety (RAMS) validation wrapped up the development securing the train set functionality and commercial viability.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"59 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":"73859959","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}
Cyrus Lawrence C. Bual, Rachel D. Cunanan, R. Bedruz, A. Bandala, R. R. Vicerra, E. Dadios
{"title":"Design of Controller and PWM-enabled DC Motor Simulation using Proteus 8 for Flipper Track Robot","authors":"Cyrus Lawrence C. Bual, Rachel D. Cunanan, R. Bedruz, A. Bandala, R. R. Vicerra, E. Dadios","doi":"10.1109/HNICEM48295.2019.9072736","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072736","url":null,"abstract":"The developed tracked mobile robot such as flipper track robot increases its ability and capability in overcoming more challenges in urban environment context and rough terrains. In addition, flippers are its support in dealing with this circumstances. The configuration of flipper tracked robots came from the extended version of conventional two-tracked mobile robot such as two and four-tracked robots. Then, the study aims to create a dedicated controller for the modified flipper track robot. Correspondingly, the target instruments, display and analog control are identified for adept monitoring of the robot status while doing its intended function. Afterwards, using Proteus 8 Professional simulation software, the Arduino UNO controller as main MCU, 16x2 LCD, analog joysticks in terms of analog resistors, and virtual terminal for serial print monitoring are attached and wired accurately. The nine speed level is established and paralleled to the required PWM output for the fine movement of flipper track robot and also the map function of Arduino IDE for degree manipulation of servo motor of two flipper arms. Finally, the results are shown in LCD which matches the established logical conditions of nine speed level as well as the status movement of the flipper track robot. The functionality and feasibility of the controller is verified and exhibited.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"73 8","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":"91473863","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}
Richard Josiah C. Tan Ai, Dino Dominic F. Ligutan, Allysa Kate M. Brillantes, Jason L. Española, E. Dadios
{"title":"Visual Odometry in Dynamic Environments using Light Weight Semantic Segmentation","authors":"Richard Josiah C. Tan Ai, Dino Dominic F. Ligutan, Allysa Kate M. Brillantes, Jason L. Española, E. Dadios","doi":"10.1109/HNICEM48295.2019.9073562","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073562","url":null,"abstract":"Visual odometry is the method in which a robot tracks its position and orientation using a sequence of images. Feature based visual odometry matches feature between frames and estimates the pose of the robot according to the matched features. These methods typically assume a static environment and relies on statistical methods such as RANSAC to remove outliers such as moving objects. But in highly dynamic environment where majority of the scene is composed of moving objects these methods fail. This paper proposes to use the feature based visual odometry part of ORB-SLAM2 RGB-D and improve it using DeepLabv3-MobileNetV2 semantic segmentation. The semantic segmentation algorithm is used to segment the image, then extracted feature points that are on pixels of dynamic objects (people) are not tracked. The method is tested on TUM-RGBD dataset. Evaluation shows that the proposed algorithm performs significantly better in dynamic scenes compared to the base algorithm, with reduction in Absolute Trajectory Error (ATE) greater than 92.90% compared to the base algorithm in fr3w_xyz, fr3w_rpy and fr3_half sequences. Additionally, when comparing the algorithm that used DeepLabv3-MobileNetV2 to the computationally intensive DeepLabv3-Xception65, the largest increase in ATE was 27%, while the computation time is 3 times faster.","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":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81195448","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}
Jan Carlo G. Maghirang, Roger Luis Uy, Kaizen Vinz A. Borja, Joven L. Pernez
{"title":"QCKer-FPGA: An FPGA Implementation of Q- gram Counting Filter for DNA Sequence Alignment","authors":"Jan Carlo G. Maghirang, Roger Luis Uy, Kaizen Vinz A. Borja, Joven L. Pernez","doi":"10.1109/HNICEM48295.2019.9072768","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072768","url":null,"abstract":"Read mapping is a process in which DNA reads are mapped to a reference genome through filtering and verification using a predefined metric. Filtering is done by quickly eliminating incorrect regions when a DNA read is compared to the reference genome. Verification on the other hand is responsible for verifying these candidate regions which require mathematical and theoretical approaches. Due to large amounts of data produced by Next Generation Sequencing (NGS) platforms, a filter is needed to reduce various computational challenges introduced by the verification process. FPGAs are special purpose processors that are designed to handle compute-intensive applications, having a highly customizable fabric. In this paper, the q-gram counting filter is implemented that takes advantage of the flexibility and capabilities of FPGAs in parallel applications using the ZedBoard development board. The paper discusses the results of the filter with varying sizes of q, number of reads with various lengths, and different reference sequences. The results show an average of 34.02% lesser clock cycles with a q-gram length of 4 and 53.58% for q-gram of 8 when compared to an implementation in C.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"27 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":"77951133","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}
G. C. Bartolome, Bhejay E. Piojo, Allan Paul L. Palugod, Rustom L. Patata
{"title":"Design and Performance of a Single-Chamber Membraneless Sediment Microbial Fuel Cell for Bioenergy Generation","authors":"G. C. Bartolome, Bhejay E. Piojo, Allan Paul L. Palugod, Rustom L. Patata","doi":"10.1109/HNICEM48295.2019.9072767","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072767","url":null,"abstract":"This study investigated the potential for bioenergy generation of a single-chamber, membrane-less SMFCs which used different types of electrode materials and sediment-rich brackish water as substrate. A multi-factor experiment was laid out in a completely randomized design (CRD). Stainless steel, aluminum, and titanium mesh were used as electrodes. On a fed-batch mode, the chambers were loaded with different amounts of sediment 25, 50, and 75 percent per volume of the chamber. Constant external loads of 100Ω, 200Ω, 300Ω were also applied. Each treatment was observed for 24 hours in duplicates. Significant findings showed that the performance of the SMFCs varied. Titanium electrode worked best in terms of open and close circuit voltage, current, power density, and bioenergy generation potential at various external resistance loadings and composition of the substrates. The SMFC yield a more stable OCV at 4452.6 mV, peak closed circuit voltage of 62.12 mV, current of 0.285 mA, power density of 0.340±0.04 mAcm-2, and bioenergy generation potential 1193.7 kJ.","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":"84425180","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}
{"title":"Rainfall Predictive Approach for La Trinidad, Benguet using Machine Learning Classification","authors":"Rose Ellen N. Macabiog, J. D. dela Cruz","doi":"10.1109/HNICEM48295.2019.9072761","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072761","url":null,"abstract":"Use of rain as a source of irrigation water presents an effective use of natural water resources. Predicting the occurrence of rainfall plays a major role especially in an agricultural area with untimely rainfall like La Trinidad, Benguet. For a more efficient irrigation scheduling, a reliable method for rainfall prediction is needed. This entails the adaptation and utilization of suitable prediction approaches and techniques. Various analytical approaches and methods are made available to develop new techniques to predict future possibilities. This study aimed to propose an approach in predicting the occurrence and non-occurrence of rainfall in La Trinidad, Benguet based on various historical weather parameters. Five machine learning classification algorithms were used to build the predictive models for the weather dataset namely: Fine Decision Tree, Linear Discriminant, Course K-Nearest Neighbors, Gaussian Support Vector Machines, and Neural Network. A poor choice of model cannot further improve the predictions. To choose between models, focus must be put on the appropriate evaluation metrics. Among the 5 models, results suggest that Course K-Nearest Neighbor gives the highest performance in all the evaluation metrics. Course KNN, with a good accuracy of 81.1% proves to be the best model to use in predicting rainfall in La Trinidad, Benguet. Course KNN model evaluation reveals that Machine Learning Classification can be adopted to predict the occurrence and non-occurrence of rainfall.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"29 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":"84517279","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}
{"title":"Performance Comparison of Beat Frequency Extraction Algorithm and Cross Correlation Algorithm for FMCW Radar Signal Processing Implemented on LabVIEW and USRP","authors":"Jesrey Martin S. Macasero, Olga Joy L. Gerasta","doi":"10.1109/HNICEM48295.2019.9073501","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073501","url":null,"abstract":"There are two prominent ways of implementing signal processing of FMCW radar in SDRs, namely i) the Beat Frequency Extraction Algorithm and ii) Cross Correlation Algorithm. The former is done by numerical mixing of the reference signal and the received signal first and then performing an FFT to detect the beat frequency that is then processed to output range information. Moreover, the latter is done by using cross correlation on the reference signal and the received signal. The aim of this paper is to scrutinize these two algorithms when they are implemented on the NI-USRP SDR platform and determine which is best for FMCW radar target detection accuracy. This paper gives guidance on the pros and cons of choosing such algorithm when being implemented on the USRP platform with LabVIEW as the development environment. The implementation of the two systems are based on these conditions: i) Carrier signal is 2Ghz, ii) Loopback cable is RG58 with lengths= 6m, 8m, 14m, 22m, and iii) Output RF Power of device is 70mW. Given the performance criteria of this paper, the Beat Frequency algorithm performed best compared to the Cross-Correlation algorithm.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"61 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":"83179730","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}
Johnathan Richard A. Barrios, M. I. P. D. Trinos, Mideth B. Abisado
{"title":"Knowledge-Based and Crowdsourcing Fault Analysis Toolkit for Unexpected Vehicle Malfunction","authors":"Johnathan Richard A. Barrios, M. I. P. D. Trinos, Mideth B. Abisado","doi":"10.1109/HNICEM48295.2019.9073400","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9073400","url":null,"abstract":"Mobile gadgets such as phones and tablets are used not only to communicate but also handy and a need to access applications that improves daily people’s lives. Considering not all drivers have enough knowledge of what car mishaps they will encounter on the road or even idea on where is the location of the nearest mechanic shop plus what numbers to call for help like towing services. The research suggests solutions to unexpected vehicle malfunction by implementing a mobile application that has access to an updated knowledge base for basic car mishaps and available services. Providing the best functionality, the mobile application undergoes a variety of functional test procedures that satisfies the required parameters needed. The tests were successfully conducted, proving that the project is functional.","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":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83514790","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}
N. Concha, Arnold Nicole Cana, Rissa Mae Suzara, Ulysses Fallarcuna
{"title":"An Artificial Neural System to Predict Building Demolition Cost","authors":"N. Concha, Arnold Nicole Cana, Rissa Mae Suzara, Ulysses Fallarcuna","doi":"10.1109/HNICEM48295.2019.9072750","DOIUrl":"https://doi.org/10.1109/HNICEM48295.2019.9072750","url":null,"abstract":"Cost estimation of building demolition, like any engineering project, requires ample amount of time and experience to accomplish since it involves calculations of complex relationships between its influencing factors. Since artificial neural networks (ANNs) are known to be effective in the cost-forecasting domain with complex parameters involve, the study aims to develop an ANN that can predict building demolition cost in Quezon City. One-hundred demolition projects from the Department of Building Official in Quezon City were gathered, evaluated and divided randomly into two sets: 90% for training, validation and internal testing and 10% for external application. Nine demolition cost-influencing factors were identified, namely: building condition, materials and classification, number of floors, total floor area, site accessibility, location, demolition methods used and debris removal options. The training was applied with feedforward backpropagation algorithm. The resulting architecture for the selected ANN model consists of 12 hidden nodes. The model tested and was successful in predicting demolition cost in Quezon City with an average accuracy rating of 90.21%.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"27 3 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":"83996503","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}