Tangtisanon, Pikulkaew
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Preferred name
Tangtisanon, Pikulkaew
Alternative Name
Tangtisanon, P.
Main Affiliation
Email
pikulkaew.ta@kmitl.ac.th
22 results
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Item type:Publication, Capactive double layers uniformly distributed RC line and its applications to active filters(2000-12-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Real time human emotion monitoring based on bio-signals(2018-12-10)Nowadays, medical technologies are rapidly improved leading to an increasing of life expectancy that caused ageing society problems. The most vital issue for elders is a health problem in both physical and mental aspect. This paper focuses on emotional monitoring and warning system using human Bio-signals in real time. The signals come from galvanic skin response and heart rate sensor that attached with a wristband wearing by the elders. The two signals are sent to a server as inputs, calculated using Fuzzy set variable model then return emotion and health status of the elder as outputs stored in the server. The proposed system is run based on ubiquitous computing so caretakers can monitor for the elder’s emotion in real time anywhere, any time. Moreover, the caretakers also get automatically alerts from the system in a case that the system returns an irregular health status of the elders. Experimental results show that the proposed system was run with a high accuracy rate. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The design of an active band pass filter using uniformly distributed RC line(2002-01-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Generational Cohort Comparison of Icon Selection Accuracy under Varying Conditions of Icon Entropy and Concreteness(2023-01-01); —The objective of this research was to compare icon selection accuracy under varying icon entropy and concreteness conditions between different generational cohorts (Millennial, Generation X, and Baby Boomers). These generational cohorts have different levels of experience with technology, with younger generations often being framed as “digital natives” and holding stronger technological experience and competence in comparison to older groups. Generational groups also have variations in physiological factors including visual acuity and reaction time. Despite these differences between user groups, many user interaction systems and processes are designed for a single user, rather than considering differences in user processing between different groups. Therefore, this study compares generational cohorts in their icon selection accuracy under varying icon conditions, to help identify what generational differences can be observed in this task. The study selected a sample of 150 participants (n = 50 for each generational cohort). The experiment was a 2☓2☓3 design (entropy (high/low) ☓ abstractness (abstract/concrete) ☓ time (9/6/3 seconds), with each participant completing 60 trials (five questions per entropy/abstractness pair over three timed runs). Results showed that there were significant differences in mean accuracy per trial under all of the time conditions and icon entropy and concreteness conditions. Mean differences showed that under most conditions, Millennial and Generation X participants did not have a significant mean difference, but Baby Boomers were significantly slower under almost all conditions. The implication of this finding is that Baby Boomers are more sensitive to icon abstractness and entropy conditions than other age groups tested. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Portable Electronic Nose for Real-time Monitoring of Food Spoilage Using Multiple Machine Learning Models(2025-01-01); Grodniyomchai, BoonyaweeIn this study, we present the design and development of a portable electronic nose (E-nose) system for detecting and classifying spoiled household food through the application of machine learning (ML) techniques. The targeted odors include fungi from bread, spoiled rice, spoiled milk, yoghurt, rotten egg, rotten boiled egg, rotten pork, and rotten beef, totaling eight odor classes. A total of 1800 samples were collected using three gas sensors and one temperature sensor. After outlier removal with Isolation Forest, 1000 samples remained. Multiple ML models were trained and evaluated over ten iterations, comparing classification accuracy and processing time. Among all the models, the k-nearest neighbor (KNN) achieved the highest performance, with an average accuracy of 99.889% and an average processing time of 0.167477 s. The decision tree (DT) model followed closely with an accuracy of 99.843% and required a significantly less processing time of 0.012080 s. Although DT has a slightly lower accuracy than KNN, its processing time is 13.86 times faster. For our scenario that requires real-time results, DT is a better choice than KNN. The proposed portable E-nose demonstrates strong potential for realworld applications such as food spoilage detection, environmental monitoring, and health diagnostics. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Android-based surveillance car(2015-01-26)Nowadays, mobile phone technologies have been developed in many aspects both software and hardware. In this era, a mobile phone contains many smart functions that perform with higher speed but lower price than before. A smart phone attracts people and almost everyone already possess. This paper illustrates a method to build a surveillance car that is controlled by a smart phone with an android operating system. The advantage of the surveillance car over the surveillance camera is that the car can move around the area freely, so a user can get any point of view in video format from a camera that is attached to the car. Moreover, with temperature sensor, the user can monitor and prevent a house fire. In the present study, the system was composed of two smart phones. The first one held by a user received video content from the second one attached to the car. The user could control the direction of the car by sliding fingers on a touch screen or tilting a smart phone. At this stage, the signal was sent to the second one which passed it to the microcontroller board controlling the movement of the car. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Android-based gardening robot with fuzzy variable set model(2017-11-03)The aim of this paper is to build android-based gardening robot that can be controlled by Android-based smartphone via long distance. Moreover, the robot can be used to check humidity of the soil and sending the information to a cloud server. The information from the server will be used in the fuzzy algorithm to determine plan of the planting for the user. In the present study, two Android based smartphone are required. One smartphone was attached to the robot and acted as a robot's eyes and brain. Another was held by the user to monitor a video content sending from the robot's eyes. The user can control a movement of the robot by sliding fingers on a touch screen or tilting the smartphone. If he sees weeds along the way, he can send the command to the robot to immediately cut it. Furthermore, the user also can ask the robot to measure a soil humidity and view the result online in real-time. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The design of an active band pass filter using uniformly distributed RC line(2003-07-14); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automatic labeling for thai news articles based on vector representation of documents(2018-08-13)