Pub Date : 2018-10-01DOI: 10.1109/TENCON.2018.8650535
Arvin Escultero, C. Odulio
An LCC resonant converter when operating at a certain frequency performs as a current source that is independent of the load resistance. This frequency is dependent only on the values of the capacitors and inductor of the tank. Unfortunately, the values for these components are usually specified within a certain precision by manufacturers. Furthermore, factors such as temperature affects these values. This paper proposes a control scheme for setting the frequency of an LCC resonant converter at the unloaded natural resonant frequency. This allows the system to lock on to the load independent frequency despite the issue of component value precision. Analysis of the system, which aims to be used as an LED driver in smart farm applications, is discussed. A 64w LCC converter is designed and simulated to test the control scheme.
{"title":"Constant Current Frequency Tracking in LCC Converters","authors":"Arvin Escultero, C. Odulio","doi":"10.1109/TENCON.2018.8650535","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650535","url":null,"abstract":"An LCC resonant converter when operating at a certain frequency performs as a current source that is independent of the load resistance. This frequency is dependent only on the values of the capacitors and inductor of the tank. Unfortunately, the values for these components are usually specified within a certain precision by manufacturers. Furthermore, factors such as temperature affects these values. This paper proposes a control scheme for setting the frequency of an LCC resonant converter at the unloaded natural resonant frequency. This allows the system to lock on to the load independent frequency despite the issue of component value precision. Analysis of the system, which aims to be used as an LED driver in smart farm applications, is discussed. A 64w LCC converter is designed and simulated to test the control scheme.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115481975","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650360
Lee Sze Foo, H. Lin, Wen Hao Png, C. Pua, F. Rahman
In this paper, the feasibility of cross-time-frequency spectrum based leak location of gas pipeline using fiber taper sensor is tested. The cross-Wigner distribution of the two signals collected on either side of the leakage point is used to extract the time difference of arrival between the two signals and the corresponding frequency. This information is then used to estimate the leak location. The distance between the leak and Sensor 1 tested was 0.79 m. The percentage error obtained from the estimation was as low as 5.29 percent.
{"title":"Feasibility of Cross-Time-Frequency Spectrum Based Leakage Location in Gas Pipeline Using Fiber Taper Sensor","authors":"Lee Sze Foo, H. Lin, Wen Hao Png, C. Pua, F. Rahman","doi":"10.1109/TENCON.2018.8650360","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650360","url":null,"abstract":"In this paper, the feasibility of cross-time-frequency spectrum based leak location of gas pipeline using fiber taper sensor is tested. The cross-Wigner distribution of the two signals collected on either side of the leakage point is used to extract the time difference of arrival between the two signals and the corresponding frequency. This information is then used to estimate the leak location. The distance between the leak and Sensor 1 tested was 0.79 m. The percentage error obtained from the estimation was as low as 5.29 percent.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115540394","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650541
J. Co, F. Tiausas, Prince Aldrin Domer, M. L. Guico, J. C. Monje, C. Oppus
This paper presents the design and development of the hardware and software components of a soil monitoring Wireless Sensor Network (WSN) for medium-scale deployments. It is composed of multiple remote sensing and transmitting devices for autonomous monitoring of soil and several surrounding environmental conditions. Using commercially-available sensor probes, it can gather soil parameters such as air and soil temperature, sunlight, moisture, humidity, and soil pH. The proposed system, subdivided into three node classes, namely sensor, relay, and aggregator nodes, has wireless communication capabilities enabled by short-range packet radio, and long-range/low-power radio (LoRa) modules which can attend to telemetry-related challenges imposed by large area coverage, vegetation density, and location remoteness.
{"title":"Design of a Long-Short Range Soil Monitoring Wireless Sensor Network for Medium-Scale Deployment","authors":"J. Co, F. Tiausas, Prince Aldrin Domer, M. L. Guico, J. C. Monje, C. Oppus","doi":"10.1109/TENCON.2018.8650541","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650541","url":null,"abstract":"This paper presents the design and development of the hardware and software components of a soil monitoring Wireless Sensor Network (WSN) for medium-scale deployments. It is composed of multiple remote sensing and transmitting devices for autonomous monitoring of soil and several surrounding environmental conditions. Using commercially-available sensor probes, it can gather soil parameters such as air and soil temperature, sunlight, moisture, humidity, and soil pH. The proposed system, subdivided into three node classes, namely sensor, relay, and aggregator nodes, has wireless communication capabilities enabled by short-range packet radio, and long-range/low-power radio (LoRa) modules which can attend to telemetry-related challenges imposed by large area coverage, vegetation density, and location remoteness.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116565800","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650192
John Chris T. Kwong, Felan Carlo C. Garcia, P. Abu, R. Reyes
Emotion Recognition has been a prominent study even before computers had the same computing power as of today. Human’s emotions can be recognized through their body language, behavior and, most evidently, from the facial expression of the person. In facial image classification, each facial image can be represented through feature descriptors. Feature descriptors are simplified representations of the facial image that incorporates the essential key facial features. This study determines which feature descriptor will best fit a respective machine learning algorithm to classify facial expressions. Twelve possible combinations of Key Facial Detection, Saliency Mapping, Local Binary Pattern, and Histogram of Oriented Gradient are investigated together with six machine learning classification algorithms thus generating a total of seventy-two models. These will classify the following emotions: anger, disgust, fear, joy, neutral, sadness and surprise. A stratified ten-fold cross-validation is performed for verification on both the CK+ dataset and the locally gathered dataset for "in the wild" image testing. This study has determined that among the seventy-two models, the RBF SVM HOG+LBP model attained the highest average accuracy of 0.94 across the seven emotions with an F1 score of 0.93.
{"title":"Emotion Recognition via Facial Expression: Utilization of Numerous Feature Descriptors in Different Machine Learning Algorithms","authors":"John Chris T. Kwong, Felan Carlo C. Garcia, P. Abu, R. Reyes","doi":"10.1109/TENCON.2018.8650192","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650192","url":null,"abstract":"Emotion Recognition has been a prominent study even before computers had the same computing power as of today. Human’s emotions can be recognized through their body language, behavior and, most evidently, from the facial expression of the person. In facial image classification, each facial image can be represented through feature descriptors. Feature descriptors are simplified representations of the facial image that incorporates the essential key facial features. This study determines which feature descriptor will best fit a respective machine learning algorithm to classify facial expressions. Twelve possible combinations of Key Facial Detection, Saliency Mapping, Local Binary Pattern, and Histogram of Oriented Gradient are investigated together with six machine learning classification algorithms thus generating a total of seventy-two models. These will classify the following emotions: anger, disgust, fear, joy, neutral, sadness and surprise. A stratified ten-fold cross-validation is performed for verification on both the CK+ dataset and the locally gathered dataset for \"in the wild\" image testing. This study has determined that among the seventy-two models, the RBF SVM HOG+LBP model attained the highest average accuracy of 0.94 across the seven emotions with an F1 score of 0.93.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122436087","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650213
P. Silapachote, A. Srisuphab, Variya Sirilertworakul, Pakawat Anekwiroj
The issue of tree instability and failure, particularly during windstorms or wind gusts, is of great concern. Its extensive impact on public safety is becoming more widely acknowledged. When blowing at critically high speed, the kinetic energy carried by winds, loading onto trees, may forcefully exceed tree strength. This may cause the stem to break, the trunk to split, or the entire tree to be uprooted. Even if surviving bursts of strong wind, the structural elements of trees may have undergone irreversible plastic deformation. Permanently damaged trees have a greater risk of failure and they need to be properly trimmed, pruned, or removed. Realizing these dangerous wind effects, it follows that the assessment of dynamic wind loading on tree stress and stains is a key to preventing tree hazards. We have developed a small-scale inertial measurement sensor unit on a single-board microcontroller. Attached to a tree branch, it constantly measures a time series of oscillatory motion of the branch in response to natural wind forces. Decomposing this signal into its constituent spectral components, the tuned mass damping effects of tree sways can effectively be estimated. Our experiments verified and validated that the wind directions can be determined, relative dynamic wind loads can be approximated, types of trees can be categorized, and the signal energy of tree swaying accelerations can be analyzed. Affordability and ease of use of our device make it highly practical to monitor not only multiple trees at once but also many branches of a single tree. Resulting analysis benefits tree management teams and landscape architects, assisting them in assessing which trees to prune and when.
{"title":"Spectral Analysis of Dynamic Wind Loads on Trees","authors":"P. Silapachote, A. Srisuphab, Variya Sirilertworakul, Pakawat Anekwiroj","doi":"10.1109/TENCON.2018.8650213","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650213","url":null,"abstract":"The issue of tree instability and failure, particularly during windstorms or wind gusts, is of great concern. Its extensive impact on public safety is becoming more widely acknowledged. When blowing at critically high speed, the kinetic energy carried by winds, loading onto trees, may forcefully exceed tree strength. This may cause the stem to break, the trunk to split, or the entire tree to be uprooted. Even if surviving bursts of strong wind, the structural elements of trees may have undergone irreversible plastic deformation. Permanently damaged trees have a greater risk of failure and they need to be properly trimmed, pruned, or removed. Realizing these dangerous wind effects, it follows that the assessment of dynamic wind loading on tree stress and stains is a key to preventing tree hazards. We have developed a small-scale inertial measurement sensor unit on a single-board microcontroller. Attached to a tree branch, it constantly measures a time series of oscillatory motion of the branch in response to natural wind forces. Decomposing this signal into its constituent spectral components, the tuned mass damping effects of tree sways can effectively be estimated. Our experiments verified and validated that the wind directions can be determined, relative dynamic wind loads can be approximated, types of trees can be categorized, and the signal energy of tree swaying accelerations can be analyzed. Affordability and ease of use of our device make it highly practical to monitor not only multiple trees at once but also many branches of a single tree. Resulting analysis benefits tree management teams and landscape architects, assisting them in assessing which trees to prune and when.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122640010","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650523
Thunwa Sattrupai, Worapan Kusakunniran
The popular techniques of gait recognition rely on the appearance information, such as Gait Energy Image (GEI). However, they need the pre-processing stage of silhouette segmentation in a walking video. This may not be efficient when the complete silhouette could not be obtained under the cluttered walking environment. It is also sensitive to the changes of walking conditions. Thus, this paper comes up with a new solution using the dense trajectory. This technique is commonly used in the action recognition domain. In this paper, it is used to extract the gait information. The key points and their corresponding trajectories are detected. Then, HOG, HOF, MBHx, MBHy and dense trajectory are extracted from each key point as the point descriptor. In the training phase, the bag of word (BoW) are trained using the extracted point descriptors from the training gait videos. Finally, in the testing phase, the BoW is extracted for each gait video, as the gait feature. The experimental result based on the well-known CASIA gait database B shows the promising performance of the proposed method, under various views.
{"title":"Deep Trajectory Based Gait Recognition for Human Re-identification","authors":"Thunwa Sattrupai, Worapan Kusakunniran","doi":"10.1109/TENCON.2018.8650523","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650523","url":null,"abstract":"The popular techniques of gait recognition rely on the appearance information, such as Gait Energy Image (GEI). However, they need the pre-processing stage of silhouette segmentation in a walking video. This may not be efficient when the complete silhouette could not be obtained under the cluttered walking environment. It is also sensitive to the changes of walking conditions. Thus, this paper comes up with a new solution using the dense trajectory. This technique is commonly used in the action recognition domain. In this paper, it is used to extract the gait information. The key points and their corresponding trajectories are detected. Then, HOG, HOF, MBHx, MBHy and dense trajectory are extracted from each key point as the point descriptor. In the training phase, the bag of word (BoW) are trained using the extracted point descriptors from the training gait videos. Finally, in the testing phase, the BoW is extracted for each gait video, as the gait feature. The experimental result based on the well-known CASIA gait database B shows the promising performance of the proposed method, under various views.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122987234","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650346
P. V. Bhanu, P. Kulkarni, Sarthak Jain, J. Soumya, Linga Reddy Cenkeramaddi, Henning Idsøe
As the size of the chip is scaling down the density of Intellectual Property (IP) cores integrated on a chip has been increased rapidly. The communication between these IP cores on a chip is highly challenging. To overcome this issue, Network-on-Chip (NoC) has been proposed to provide an efficient and a scalable communication architecture. In the deep sub-micron level NoCs are prone to faults which can occur in any component of NoC. To build a reliable and robust systems, it is necessary to apply efficient fault-tolerant techniques. In this paper, we present a flexible spare core placement in Mesh-of-Tree (MoT) topology using Particle Swarm Optimization (PSO) by considering IP core failures in NoC. We have experimented by considering several application benchmarks reported in the literature. Comparisons have been carried out, (i) by varying the percentage of faults in the MoT network with fixed network size and (ii) by considering the each core has been failed in the given application benchmark. The results show limited overhead in communication cost while providing fault-tolerance.
{"title":"Fault-Tolerant Network-on-Chip Design for Mesh-of-Tree Topology Using Particle Swarm Optimization","authors":"P. V. Bhanu, P. Kulkarni, Sarthak Jain, J. Soumya, Linga Reddy Cenkeramaddi, Henning Idsøe","doi":"10.1109/TENCON.2018.8650346","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650346","url":null,"abstract":"As the size of the chip is scaling down the density of Intellectual Property (IP) cores integrated on a chip has been increased rapidly. The communication between these IP cores on a chip is highly challenging. To overcome this issue, Network-on-Chip (NoC) has been proposed to provide an efficient and a scalable communication architecture. In the deep sub-micron level NoCs are prone to faults which can occur in any component of NoC. To build a reliable and robust systems, it is necessary to apply efficient fault-tolerant techniques. In this paper, we present a flexible spare core placement in Mesh-of-Tree (MoT) topology using Particle Swarm Optimization (PSO) by considering IP core failures in NoC. We have experimented by considering several application benchmarks reported in the literature. Comparisons have been carried out, (i) by varying the percentage of faults in the MoT network with fixed network size and (ii) by considering the each core has been failed in the given application benchmark. The results show limited overhead in communication cost while providing fault-tolerance.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122053284","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650462
B. Chan, K. Lim, Lenin Gopal, A. Gopalai, W.C. Chia, W. J. Chew
Stereo-vision technology has shown its advantages to overcome the occlusion and realistic information. However, marker-less human motion detection and tracking in the unconstrained environment were led to the difficulty of features extraction. In this paper, we proposed a hybrid technique of Gaussian and median filter to improve the shadow and sudden change of the illumination problems. The skeleton model of the detected human was constructed using the sequential mathematical morphology. Based on the results, the skeleton model produced was not affected by the shadow and the illumination issue. Proposed approach and the normalized filter approach produces up to 86% and 71% of the average accuracy tracking respectively in the real-time tracking. Hence, the proposed approach could improve the performance of the human detection in the unconstrained environment.
{"title":"Marker-less Stereo-Vision Human Motion Tracking Using Hybrid Filter in Unconstrained Environment","authors":"B. Chan, K. Lim, Lenin Gopal, A. Gopalai, W.C. Chia, W. J. Chew","doi":"10.1109/TENCON.2018.8650462","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650462","url":null,"abstract":"Stereo-vision technology has shown its advantages to overcome the occlusion and realistic information. However, marker-less human motion detection and tracking in the unconstrained environment were led to the difficulty of features extraction. In this paper, we proposed a hybrid technique of Gaussian and median filter to improve the shadow and sudden change of the illumination problems. The skeleton model of the detected human was constructed using the sequential mathematical morphology. Based on the results, the skeleton model produced was not affected by the shadow and the illumination issue. Proposed approach and the normalized filter approach produces up to 86% and 71% of the average accuracy tracking respectively in the real-time tracking. Hence, the proposed approach could improve the performance of the human detection in the unconstrained environment.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128631825","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650266
M. N. Mishuk, Saifur Rahman, Md. Anamul Hoque
Imaging technique with high-sensitivity and high-spatial-resolution at single molecular level is always a desired aspect to the researchers. In association with scanning probe microscopy and Surface-Enhanced Raman Spectroscopy (SERS), a new technology has shown the light of hope to achieve what was thought as unachievable earlier, named Tip-Enhanced Raman Spectroscopy (TERS). An essential tip is used in TERS to disseminate the information of the morphology of the target molecule by scanning probe technique and concurrently can magnify the Raman signal largely without any special sample preparation. Between this metal tip and surface, a ‘hot-spot’ is formed when the laser beam is applied. TERS has many applications in nanotechnology, biophotonics, and sensing etc. Generally, noble materials are used in the operation of TERS. Recently, 2D materials are showing great potential in parallel with the noble materials in producing sensors, measurement devices, conductive films, printed electronics and many more due to their extraordinary properties like strength, thermal conductivity, high electrical conductivity etc. In this paper, we will compare the enhancement factor of noble and 2D materials at the vicinity of the metallic tip of TERS. Finite-Difference Time-Domain (FDTD) simulation method has been opted to find out the enhancement factor. For this simulation, tip radius was varied from 5 nm to 30 nm with 5 nm interval and distance between tip and substrate was varied from 1 nm to 5 nm with 1 nm interval and incident wavelength was kept constant at visible wavelength (300nm–700nm).
{"title":"Comparative Analysis of FDTD Intensity Profile of 2D and Noble Materials for TERS Application","authors":"M. N. Mishuk, Saifur Rahman, Md. Anamul Hoque","doi":"10.1109/TENCON.2018.8650266","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650266","url":null,"abstract":"Imaging technique with high-sensitivity and high-spatial-resolution at single molecular level is always a desired aspect to the researchers. In association with scanning probe microscopy and Surface-Enhanced Raman Spectroscopy (SERS), a new technology has shown the light of hope to achieve what was thought as unachievable earlier, named Tip-Enhanced Raman Spectroscopy (TERS). An essential tip is used in TERS to disseminate the information of the morphology of the target molecule by scanning probe technique and concurrently can magnify the Raman signal largely without any special sample preparation. Between this metal tip and surface, a ‘hot-spot’ is formed when the laser beam is applied. TERS has many applications in nanotechnology, biophotonics, and sensing etc. Generally, noble materials are used in the operation of TERS. Recently, 2D materials are showing great potential in parallel with the noble materials in producing sensors, measurement devices, conductive films, printed electronics and many more due to their extraordinary properties like strength, thermal conductivity, high electrical conductivity etc. In this paper, we will compare the enhancement factor of noble and 2D materials at the vicinity of the metallic tip of TERS. Finite-Difference Time-Domain (FDTD) simulation method has been opted to find out the enhancement factor. For this simulation, tip radius was varied from 5 nm to 30 nm with 5 nm interval and distance between tip and substrate was varied from 1 nm to 5 nm with 1 nm interval and incident wavelength was kept constant at visible wavelength (300nm–700nm).","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128717543","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 : 2018-10-01DOI: 10.1109/TENCON.2018.8650277
Sara Zulfiqar, Hamza Nadeem, Zamen Tahir, Minnaam Mazhar, K. Hasan
This paper focuses on the development of a precise, user-adjustable breathing cycle for mechanical intervention in patients suffering from respiratory problems. Controlled breaths are provided using a closed loop system with feedback path from two self-calibrated sensors i.e. a pressure sensor and a flowrate sensor. User-input through a Graphical User Interface (GUI), displayed on touch screen module, will act as control signals. It is in response to these signals that the breathing cycle will adjust. Raw data from sensors is optically insulated and converted into variable duty PWM signals for precise, error free readings. The cycle is digitally controlled with a wide range of settings so that it is adjustable from patient to patient. DC piston air pump, with modified buck converter as speed controller, is PID tuned and is replaceable with similar pumps after tuning. Sensors are also replaceable by modeling their behavior to appropriate transfer functions. The result is the design and making of a low-cost, portable prototype that can be used in ambulances, small hospitals and during disaster management to provide volume and pressure-controlled air for mechanical ventilation.
{"title":"Portable, Low Cost, Closed-Loop Mechanical Ventilation Using Feedback from Optically Isolated Analog Sensors","authors":"Sara Zulfiqar, Hamza Nadeem, Zamen Tahir, Minnaam Mazhar, K. Hasan","doi":"10.1109/TENCON.2018.8650277","DOIUrl":"https://doi.org/10.1109/TENCON.2018.8650277","url":null,"abstract":"This paper focuses on the development of a precise, user-adjustable breathing cycle for mechanical intervention in patients suffering from respiratory problems. Controlled breaths are provided using a closed loop system with feedback path from two self-calibrated sensors i.e. a pressure sensor and a flowrate sensor. User-input through a Graphical User Interface (GUI), displayed on touch screen module, will act as control signals. It is in response to these signals that the breathing cycle will adjust. Raw data from sensors is optically insulated and converted into variable duty PWM signals for precise, error free readings. The cycle is digitally controlled with a wide range of settings so that it is adjustable from patient to patient. DC piston air pump, with modified buck converter as speed controller, is PID tuned and is replaceable with similar pumps after tuning. Sensors are also replaceable by modeling their behavior to appropriate transfer functions. The result is the design and making of a low-cost, portable prototype that can be used in ambulances, small hospitals and during disaster management to provide volume and pressure-controlled air for mechanical ventilation.","PeriodicalId":132900,"journal":{"name":"TENCON 2018 - 2018 IEEE Region 10 Conference","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124720886","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：