{"title":"Probabilistic model of nanometer MIFGMOSFET","authors":"R. Banchuin, R. Chaisricharoen","doi":"10.1109/ECTICON.2017.8096355","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096355","url":null,"abstract":"The probabilistic model of the random variation in drain current of the nanometer multiple input floating-gate MOSFET (MIFGMOSFET) has been proposed in this research. The modeling process has taken the major physical level causes of random variations e.g. random dopant fluctuation and line edge roughness etc., into account. The proposed model have been found to be very accurate since it can fit the probabilistic distributions of normalized random drain current variations of the candidate MIFGMOSFET obtained by using the 90 nm SPICE BSIM4 based Monte-Carlo simulation with 99% confidence.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132098861","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":"Optimum lowest input energy for first-order circuits in transient state","authors":"Radit Smunyahirun, E. L. Tan","doi":"10.1109/ECTICON.2017.8096193","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096193","url":null,"abstract":"This paper presents optimum lowest input energy for first-order circuits in transient state. A resistors network with a capacitor is chosen for derivation. The derivation is based on calculus of variations theory or more specifically, the Euler-Lagrange's differential equation. Essential parameters are introduced and the most energy-efficient input source function is obtained. The lowest input energy of a capacitive circuit and an inductive circuit are derived and stated as corollaries. Using the corollaries with a circuit of a supercapacitor is illustrated. Speed and energy trade-off is shown that it is not always held by inspecting the corollaries. Finally, optimum transient duration is determined as well as optimum lowest input energy.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134244375","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":"Forward kinematic-like neural network for solving the 3D reaching inverse kinematics problems","authors":"Pannawit Srisuk, A. Sento, Y. Kitjaidure","doi":"10.1109/ECTICON.2017.8096211","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096211","url":null,"abstract":"This paper presents the inverse kinematic solutions based on neural networks. General neural network approaches use data of the end-effector positions as an input and angle joints as an output to train the neural network for mapping the input to the output. However, the proposed method creates the custom networks from forward kinematic equations. This special structure makes the network like a position finder with ability to automatically adjust angle joints until the end-effector reaches the desired position by backpropagation with variable learning rate algorithm. Then, the solutions of angles can be found from the final weights and bias values. Moreover, the proposed network use less number of neurons and amount of the solution space is not depend on the training data. Finally, to evaluate the performance algorithm, the MATLAB Program is used to demonstrate a 4-DOF robotic arm movement in 3-dimensional. As a result, the proposed algorithm can help a robotic arm move to the desired position (3D reaching) quickly and correctly.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134450792","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":"Optical fiber sensor system design utilizing the field programmable gate array","authors":"Y. Ong, I. Grout, E. Lewis, W. Mohammed","doi":"10.1109/ECTICON.2017.8096181","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096181","url":null,"abstract":"This paper presents the design of a system that is aimed to provide a flexible, portable and low cost solution for optical fiber based sensor systems. The field programmable gate array (FPGA) provides the digital logic to implement the system and ability to reconfigure the system operation. It aims to support different optical fiber sensing requirements by the ability to reconfigure the digital circuitry used. It is therefore a hardware configured alternative to a software programmed processor based approach. The work discussed in this paper focuses on the architecture of the FPGA based system with additional circuitry to implement the light source using a light emitting diode (LED), sensor signal sampling using a photodiode and the digital functions implemented using the Xilinx Artix-7 FPGA. The system also includes serial communications to an external computer that allows the system to be used as part of a larger sensor network. In this paper, system control and sensor data visualization on a personal computer (PC) is undertaken using the Python open source programming language.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133388205","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":"Applications of DSTATCOM to regulate voltage on a distribution network","authors":"P. Shafaghi","doi":"10.1109/ECTICON.2017.8096376","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096376","url":null,"abstract":"The distribution static compensator (DSTATCOM) is the FACTS device used for regulate voltage in power distribution network. In this paper, the particular application of a DST-ATCOM in voltage control mode is investigated in a power distribution system. Simulated performance of DSTATCOM is presented at varying conditions. At the end, the result of simulation with Matlab Simulink software has been presented.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132960513","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":"A logarithmic level-crossing ADC","authors":"S. Sirimasakul, A. Thanachayanont","doi":"10.1109/ECTICON.2017.8096303","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096303","url":null,"abstract":"A 3-bit logarithmic level-crossing analog-to-digital converter (LC-ADC) for biomedical applications is presented. Based on the feedback LC-ADC structure, the proposed circuit is realized by using logarithmic charge-scaling digital-to-analog converters. The circuit is designed and simulated with process parameters from a 0.35-μm CMOS technology and a 1.5-V power supply voltage. Process corner simulation results showed that the INL and DNL errors are within the range of +0.14/−0.09LSB and +0.14/−0.21LSB, respectively.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128010396","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":"Brain tumor segmentation and classification using cascaded random decision forests","authors":"N. Shah, Sheikh Ziauddin, A. R. Shahid","doi":"10.1109/ECTICON.2017.8096339","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096339","url":null,"abstract":"Automated segmentation and classification of brain tumor is important to avoid misdiagnosis and to improve chances of patients' survival. In this paper, we present a fully automated technique for segmentation and classification of brain tumor into three different regions namely Complete Tumor, Tumor Core and Enhancing Tumor. We use a cascaded Random Decision Forest (RDF) model for classification. In our experiments, we use BRATS 2013 3D MR images dataset which contains T1, T1c, T2 and Flair MRI sequences. These sequences are standard in clinical acquisition. Using 10-fold cross validation for evaluation, we achieve promising Dice scores of 0.90, 0.79 and 0.84 for Complete Tumor, Tumor Core and Enhancing Tumor, respectively.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128503009","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}
Saif Nalband, C. Valliappan, Raag Gupta A. Amalin Prince, Anita Agrawal
{"title":"Feature extraction and classification of knee joint disorders using Hilbert Huang transform","authors":"Saif Nalband, C. Valliappan, Raag Gupta A. Amalin Prince, Anita Agrawal","doi":"10.1109/ECTICON.2017.8096224","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096224","url":null,"abstract":"Non-invasive investigation methods along with computer based exploration of vibroarthrography (VAG) signals can contribute compiling indication of human knee-joint deformity. The VAG signals are characterized as non-stationary and aperiodic in nature. As a result, feature extraction technique is challenging for researchers. This paper proposes analysis of VAG signal using Hilbert-Huang transform (HHT). The ensemble empirical mode decomposition (EEMD) decomposes raw VAG signal individual characteristic scales known as intrinsic mode function (IMF). The analytical signal representation of IMFs is attained by implementing Hilbert transform on IMFs. In the z-plane, the fundamental analytic IMFs are plotted which are circular in geometry. Area of these circular curves in the z-plane are computed using the central tendency measure (CTM) and chosen as feature in differentiating between healthy and unhealthy VAG signals. A pattern analysis is carried out using least square support vector machine (LS-SVM) which gives a classification accuracy of 83.12% and area under receiver operating characteristic of 0.6708 were obtained.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"57 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115887478","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":"EEG power spectra during stroop color word task training in obese patients","authors":"Pawana Khemapathumak, Suraphong Lookhanumanchao, Phakkharawat Sittiprapaporn","doi":"10.1109/ECTICON.2017.8096165","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096165","url":null,"abstract":"This study aimed to evaluate the modifications of electroencephalographic (EEG) power spectra in overweight and obese patients. EEG was recorded while performing the Stroop Color Word Test. Stroop Color Word Test was performed and EEG activity was also monitored during the experiment. Paired t-test and independent t-test were used to show statistical difference between baseline and Stroop Color Word Test. Compared to baseline, patients showed an increase of theta, alpha, and gamma frequency bands. Our results show that overweight and obese patients had similar neurophysiological correlates of other forms of substance-related and addictive disorders suggesting similar psychopathological mechanisms.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116111716","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":"Lung volume monitoring using flow-oriented incentive spirometer with video processing","authors":"Athtayu Yuthong, Kanadit Chetpattananondh, Rakkrit Duangsoithong","doi":"10.1109/ECTICON.2017.8096293","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096293","url":null,"abstract":"Lung rehabilitation can be done by using different measuring and monitoring tools to recover patient from lung collapse. However, the patients can feel uncomfortable or get infected from using these tools. This paper present lung volume monitoring using flow-oriented incentive spirometer with video processing. According to the result, the proposed method can be used for lung rehabilitation monitoring and measuring with more comfortable, low cost and easy to use.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116890762","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}