{"title":"Analysis of Power, Temperature, and Performance on Mobile Application Processor","authors":"D. Lee, Hyun Hak Cho, O. H. Jeong","doi":"10.1109/MoRSE48060.2019.8998679","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998679","url":null,"abstract":"Recent mobile devices have multiple cores and high operating frequencies. As a result, their performance has increased, along with their power consumption and temperature, which have become problems to solve. To understand how to operate a CPU efficiently while solving these problems, we study the relationship between power consumption, temperature, and performance as functions of the number of operating cores and operating frequency. We use CPU power consumption that we measured, use steady-state temperature of the CPU calculated by Therminator and use DMIPS that is an index of CPU performance measured by Dhrystone. The experimental results show that the performance increases and temperature decreases as the number of operating cores increases for the same power consumption. In addition, for the same performance, power consumption and temperature decrease as the number of operating cores increases. Consequentially, the quad-core shows a 75.54% performance improvement and 36.04% reductions in temperature compared to the single-core for the same power consumption. In addition, when at the same performance, the quad-core has decreased power consumption and temperature compared to the single-core, 49.42% and 53.94%, respectively. Therefore, operating by increasing the number of cores in the multi-core application processor will effectively increase the performance and lower the power consumption and temperature.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116774025","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}
Abdullah Faqih Al Mubarok, Ahmad Habbie Thias, A. Handayani, D. Danudirdjo, Tati Erawati Rajab
{"title":"Brain Tumor Classification with Fisher Vector and Linear Classifier for T1-Weighted Contrast-Enhanced MRI Images","authors":"Abdullah Faqih Al Mubarok, Ahmad Habbie Thias, A. Handayani, D. Danudirdjo, Tati Erawati Rajab","doi":"10.1109/MoRSE48060.2019.8998672","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998672","url":null,"abstract":"This paper presents the development of a computational method for classifying three types of brain tumors - i.e. meningioma, glioma and pituitary - from T1-weighted contrast-enhanced MRI images. The proposed method performs feature extraction on a specified set of tumor pixel intensity and uses the extracted information to determine the corresponding type of brain tumor. In feature extraction, the specified tumor area was first augmented to incorporate the sample of the surrounding tissue, prior to intensity extraction with dense local patches. Afterwards, the extracted intensity from each patch was fitted to a Gaussian Mixture Model (GMM) and processed into Fisher Vector representation. Furthermore, we applied four linear classifiers to the Fisher Vector representation and evaluated their classification performance. Our experiments showed that the logistic regression gave the best performance with average accuracy, sensitivity and specificity of 89.9%, 95.2%, and 89.0% respectively.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122201187","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}
C. Huynh, J. Lee, J. Bae, D. Lee, M. Hsiao, C. Nguyen
{"title":"A Millimeter-Wave Phased Array for Communication and Sensing Systems","authors":"C. Huynh, J. Lee, J. Bae, D. Lee, M. Hsiao, C. Nguyen","doi":"10.1109/MoRSE48060.2019.8998712","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998712","url":null,"abstract":"A 94-GHz 4×4 phased array frontend capable of two-dimensional scanning with orthogonal polarizations for wireless communication and radar systems has been designed. The phased array frontend resolves the RF signal leakage and isolation dilemma encountered in typical systems employing a single antenna for both transmission and reception, effectively maximizing the system's dynamic range and linearity operation as well as minimizing the noise figure. Simulations at 94 GHz show high performance for the phased array frontend. In the receive (RX) mode, it has noise figure of 8.5/8.4dB at the radiating element, RMS phase error of 2.38/2.36° and gain error of 1.22/1.27dB, and total array gain of 17/22.3dB for H/V polarization, respectively, and ultra-high isolations from TX-Antenna (−200/−190dB), TX-RX (−106/−180dB) and V-H antenna ports (66/69dB). In the Transmit (TX) mode at 94 GHz, it achieves a radiated power of 7.8 dBm at the element antenna and RMS gain and phase errors of 1.28 dB and 2.19° at 94 GHz, respectively.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129031969","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":"Development of On-Demand Controller for Continuous Positive Airways Pressure","authors":"Yusuf A. Amrulloh, Brian A Hisif, D. A. R. Wati","doi":"10.1109/MoRSE48060.2019.8998698","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998698","url":null,"abstract":"Continuous Positive Airway Pressure (CPAP) is one of the primary treatments for sleep apnea. In a conventional CPAP, the device produces a constant air pressure to maintain the opening of the respiratory tract. The common problem found in the conventional CPAP is discomfort due to long term air pressure during sleep. Further, in subjects who undergo training to strengthen upper airways muscles, the application of high air pressure during non-apnea period may reduce the muscular strength. In this work, we propose to develop an on-demand CPAP controller that follows the normal respiratory pressure during non-apnea event and produce a pre-set positive air pressure during the sleep apnea event. Not only improve the comfortability of the subjects, our method also useful for patients who plan to discontinue using CPAP in the future. Our proposed model was developed using LabView software. We simulated breathing signal to represent normal breathing and apnea condition. Then a proportional and integral control system was developed for regulating the air pressure. The results show that in 60 trials with several setting points, our model achieved the average rise time 0.75s, overshoot 3.79%, and settling time 1.72s. The total accuracy of the method was 100% in detection of sleep apnea events. Our method can be developed into a low-cost device for sleep apnea treatment in Indonesia.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126416710","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":"Designing a Testbed to Assess Secure Control of Cyber-Physical Systems","authors":"E. Park, K. C. Chan","doi":"10.1109/MoRSE48060.2019.8998684","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998684","url":null,"abstract":"The world today increasingly relies upon the usage of smart devices which have the capability to communicate with other systems and the cloud. Cyber-Physical Systems (CPS) are one such application of smart devices making use of network mediums for augmented communication capabilities. Problems and risks arise when the messages being sent via the network are not secure, as this would allow adversaries to manipulate and ultimately compromise the entire system. In the past, implementing security to these system have been more reactive than proactive. This paper illustrates the design of a CPS testbed in which different security implementation methods can be tested upon and analysed. The abstraction of the CPS testbed and an adversary model that shows where attacks may occur are then discussed.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134180420","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":"Adaptive Control for Jib Crane System with Rope Hoisting and Uncertain Parameters","authors":"S. Ishikura, Gan Chen, I. Takami","doi":"10.1109/MoRSE48060.2019.8998649","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998649","url":null,"abstract":"This paper proposes a robust control system which consists of a robust controller and Model Reference Adaptive Control law for an uncertain jib crane system with rope hoisting. In this study, decentralized control comprised of two independent controllers is utilized to control the jib crane. To suppress the influences of system uncertainties e.g., variations of the rope length, nonlinear friction and so on, we design the control system composed of a linear robust controller and an adaptive law for the positioning system of the trolley. We apply the linear robust controller for the variation of system characteristics caused by hoisting the rope. On the other hand, the adaptive law is designed to estimate nonlinear friction. The characteristic of this study is to cope with nonlinear friction by using the robust controller with the adaptive law. The adaptive law is utilized for the estimation and compensation of nonlinear friction. Besides, we approximate nonlinear friction by a nonlinear function in the adaptive law. We show the exponential stability for the system with the proposed method by using Linear Matrix Inequality. Finally, we verify the effectiveness of the adaptive law by contrasting the proposed method with the only robust controller in the simulation of load transferring.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131776238","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}
Dita Chasanah Dewi Suwarno, T. Wijayanto, F. Trapsilawati
{"title":"Cybersickness Evaluation While using Driving Simulator in a Head-Mounted Display Environment","authors":"Dita Chasanah Dewi Suwarno, T. Wijayanto, F. Trapsilawati","doi":"10.1109/MoRSE48060.2019.8998692","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998692","url":null,"abstract":"This study aims to investigate the cybersickness severity in a driving simulator presented with two different displays: A head-mounted display and a three-monitor display. Twenty students participated in this study. They performed a set of driving task on a driving simulator. Half participants performed the task using the head-mounted display (HMD group), and the other half performed using the monitor display screen (MD group). Here, we found that using a head-mounted display to display the virtual environment of the driving simulator will cause cybersickness more severe than using the monitor display. Participants in the HMD group reported higher nausea, oculomotor, and disorientation problem after performing the driving simulation task. Of the three symptoms, the disorientation was reported to be the most severe symptom contribute to cybersickness occurrence when using head-mounted display.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125870178","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}
Kiem Nguyen Tien, Duyen Ha Thi Kim, T. Manh, C. Manh, Ngoc Pham Van Bach, Hiep Do Quang
{"title":"Adaptive Dynamic Surface Control for Car Driving Simulator based on Artificial Neural Network","authors":"Kiem Nguyen Tien, Duyen Ha Thi Kim, T. Manh, C. Manh, Ngoc Pham Van Bach, Hiep Do Quang","doi":"10.1109/MoRSE48060.2019.8998749","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998749","url":null,"abstract":"This paper presents an adaptive controller for a four degrees of freedom car driving simulator. The actual model of the simulator is often deficient in the system's parameters or has the nonlinear uncertainties. Therefore an adaptive dynamic surface control based on radial basis function neural network is proposed to approximate the uncertain elements and ensure the stability of the system at the same time. The stability of the system is proved based on Lyapunov theorem. Simulation results verify the effectiveness and accuracy of the proposed algorithm and the comparison between using neural network and not using this element indicates the superiority of the proposed controller.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127145784","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":"Comparison of Neural Biomarker Assessment Methods for Early Detection of Alzheimer's Disease","authors":"Dalin Yang, K. Hong","doi":"10.1109/MoRSE48060.2019.8998674","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998674","url":null,"abstract":"With growing age, the cognitive ability degrades gradually as an aging factor. For a portion of people, the cognitive capability diminishes to a great extent, which will eventually result in Alzheimer's disease (AD). Mild cognitive impairment (MCI) is considered as an intermediate stage of AD. Diagnosis of AD patients at an early stage can reduce the chance of developing into a severe condition for cognition. This study aims to investigate the MCI assessment methods (statistical analysis and individual classification) for distinguishing the healthy control (HC) and MCI patients via functional near-infrared spectroscopy (fNIRS). This study evaluated ten digital biomarkers from three brain regions and three mental tasks ($N$-back, Stroop, and verbal fluency task). Among these three tasks, the $N$-back task achieved the best accuracy (76.67 %) with biomarker 2 (HbO mean from 5 to 25 sec) and 7 (HbO slope from 0 to peak value) in the middle prefrontal cortex by linear discriminant analysis (LDA). Additionally, the statistical analysis results also indicated that a significant difference ($p$-value < 0.05) existed between MCI and HC. However, the biomarkers, which achieved an individual classification accuracy more than 70%, could not be consistent with the biomarkers with $p$-value < 0.05. It reveals that statistical analysis technique still should be improved for diagnosing MCI individuals. Machine learning (LDA) can contribute as a tool by early prediction of AD via analyzing digital biomarkers using a non-invasive technique.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"49 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114124667","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}
Ahmad Habbie Thias, Abdullah Faqih Al Mubarok, A. Handayani, D. Danudirdjo, Tati Erawati Rajab
{"title":"Brain Tumor Semi-automatic Segmentation on MRI T1-weighted Images using Active Contour Models","authors":"Ahmad Habbie Thias, Abdullah Faqih Al Mubarok, A. Handayani, D. Danudirdjo, Tati Erawati Rajab","doi":"10.1109/MoRSE48060.2019.8998651","DOIUrl":"https://doi.org/10.1109/MoRSE48060.2019.8998651","url":null,"abstract":"Brain tumor is a collection of abnormal growth in brain tissue. One of the methods to diagnose brain tumor is using magnetic resonance imaging (MRI) to produce images of brain tissue, on which the radiologist will perform manual segmentation of the tumor boundary. Manual segmentation poses a challenge in a large number of images. A Computer Aided Diagnosis (CAD) system can be designed to perform an automated segmentation of tumor boundary, thus providing more efficient and objective results. In this work, we compared and analyze the performance of snake active contour (SAC), morphological active contour without edge (MACWE), and morphological geodesic active contour (MGAC) segmentation algorithms on 3049 brain MRI T1-weighted images containing glioma, meningioma, or pituitary tumor. The performance of these algorithms quantified using the Jaccard Similarity Index (JSI) and the Hausdorff Distance (HD). The best segmentation results were obtained by the MGAC with the average JSI and HD of 71.18% and 4.04 pixels, respectively. The JSI of MGAC segmentation was highest for meningioma (77.94%) and lowest for glioma (66.31%) while a random shift in contour initialization affected the glioma and pituitary tumors more than the meningiomas, as shown by the respective post-shift JSI of 76.42%, 76.84%, and 85.98% accuracy for glioma, pituitary, and meningioma.","PeriodicalId":111606,"journal":{"name":"2019 International Conference on Mechatronics, Robotics and Systems Engineering (MoRSE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131354355","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}