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MagneFi: Multiuser, Multi-Building and Multi-Floor Geomagnetic Field Dataset for Indoor Positioning

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Computers, Materials & Continua 2022年第10期73卷 1747-1768页

作者： Imran Ashraf Muhammad Usman Ali Soojung Hur Gunzung Kim yongwan park Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea Department of Computer Science University of GujratGujrat50700Pakistan

Indoor positioning and localization have emerged as a potential research area during the last few years owing to the wide proliferation of smartphones and the inception of location-attached services for the consumer *** to the importance of precise location information,several positioning technologies are adopted such as Wi-Fi,ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,*** Wi-Fi and magnetic field-based positioning are more attractive concerning the deployment of Wi-Fi access points and ubiquity of magnetic field data,the latter is preferred as it does not require any additional infrastructure as other approaches *** the advantages of magnetic field positioning,comparing the performance of positioning and localization algorithms is very difficult due to the lack of good public datasets that cover various aspects of the magnetic field *** datasets do not provide the data to analyze the impact of device heterogeneity,user heights,and time-specific magnetic field ***,multi-floor and multibuilding data are available for the evaluation of state-of-the-art *** overcome the above-mentioned issues,this study presents multi-user,multidevice,multi-building magnetic field data which is collected over a longer *** dataset contains the data from five different smartphones including Samsung Galaxy S8,S9,A8,LG G6,and LG G7 for three geographically separated *** users including one female and two males collected the data for various path geometry and data collection ***,the data contains the magnetic field samples collected on stairs to test multifloor *** the magnetic field data,the data from inertial measurement unit sensors like the accelerometer,motion sensors,and barometer is provided as well.

关键词： Magnetic field dataset magnetic-field based positioning smartphone sensors benchmark analysis indoor positioning and localization

Ensembling Neural Networks for User’s Indoor Localization Using Magnetic Field Data from Smartphones

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Computers, Materials & Continua 2021年第8期68卷 2597-2620页

作者： Imran Ashraf Soojung Hur Yousaf Bin Zikria yongwan park Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors:Smartphone heterogeneity and smaller data *** use of multifarioussmartphones cripples the performance of such approaches owing to the variability of the magnetic field *** the same vein,smaller lengths of magnetic field data decrease the localization accuracy *** current study proposes the use of multiple neural networks like deep neural network(DNN),long short term memory network(LSTM),and gated recurrent unit network(GRN)to perform indoor localization based on the embedded magnetic sensor of the smartphone.A voting scheme is introduced that takes predictions from neural networks into consideration to estimate the current location of the *** to conventional magnetic field-based localization approaches that rely on the magnetic field data intensity,this study utilizes the normalized magnetic field data for this *** of neural networks is carried out using Galaxy S8 data while the testing is performed with three devices,i.e.,LG G7,Galaxy S8,and LG *** are performed during different times of the day to analyze the impact of time *** indicate that the proposed approach minimizes the impact of smartphone variability and elevates the localization *** comparison with three approaches reveals that the proposed approach outperforms them in mean,50%,and 75%error even using a lesser amount of magnetic field data than those of other approaches.

关键词： Indoor localization magnetic field data long short term memory network data normalization gated recurrent unit network deep learning

Heart valve closure timing intervals in response to left ventricular blood pressure

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Journal of Biomedical Science and Engineering 2013年第1期6卷 65-75页

作者： Hong Tang Jiao Gao yongwan park Department of Biomedical Engineering Dalian University of Technology Dalian China Department of Information and Communication Engineering Yeungnam University Seoul South Korea

This article investigates the relationships between heart valve closure timing intervals and left ventricular systolic blood pressure (LVSBP). For this investigation, the cardiopulmonary system is modeled as an analog circuit, including heart chambers, the distal and proximal aorta, distal and proximal systemic arteries/veins, systemic capillaries, the vena cava, the distal and proximal pulmonary artery, distal and proximal pulmonary arteries/veins, pulmonary capillaries and physiological control of heart rate and cardiac contractibility. In this model, the ventricles, atria and arteries were modeled as advanced pressur-volume relationships. A vagal-sympathetic mechanism was adopted to simulate transient systemic and pulmonary blood pressure. Four intervals, i.e., the timing interval between mitral and aortic valve closure (TIMA), the timing interval between aortic and mitral valve closure (TIAM), the timing interval be- tween aortic and pulmonary valve closure (TIAP) and the timing interval between mitral and tricuspid valve closure (TIMT), are further defined in a heart cycle to illustrate their relationships to LVSBP. Simula- tions showed that the TIMA, TIAM and TIAP have strong negative correlations with LVSBP;meanwhile, the TIMT has a slightly negative relationship with LVSBP. To further validate the relationships, 6 healthy male subjects were experimentally evaluated. The intervals were extracted from non-invasively sampled heart sound signals taken from the surface of the thorax. The experiments showed relationships consistent with those obtained by simulations. These relationships may have potential applications for noninvasively accessing LVSBP in real-time with a high time resolution of one heartbeat.

关键词： Cardiopulmonary Modeling Systemic Hemodynamic Pulmonary Hemodynamic Timing of Heart Valve Closure Heart Sounds

Magnetic properties of M-type strontium ferrites with different heat treatment conditions

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Rare Metals 2020年第1期39卷 84-88页

作者： Namji Oh Seungyeon park yongwan Kim Hyukmin Kwon Sangsub Kim Kyoungmook Lim Korea Institute of Industrial Technology Incheon21999Republic of Korea Ugimag Korea Cheongju27655Republic of Korea Department of Materials Science and Engineering Inha UniversityIncheon22212Republic of Korea

The effects of heat treatment conditions on the magnetic properties and microstructure of M-type strontium ferrite according to calcination temperature were *** ferrite Sr0.06Ca0.52La0.52Fe11.68Co0.22O19magnetic powder was prepared by a standard ceramic *** experiments,the calcination temperature was varied from 1180 to 1260℃,and sintering temperature was *** the M-phase(SrFe12O19)existed with hematite(Fe2 O3)in the powder calcined at below 1220℃,the pure M-phase was observed in the powder calcined at over1240℃.With an increase in the calcination temperature,the magnetization of the calcined powder increases,meanwhile,the coercivity *** magnetization is improved by decreasing the lattice constant c and activating the Fe3+-OFe3+superexchange interaction,and the coercivity decreases by the large particle sizes due to the grain growth.

关键词： M-type ferrites Standard ceramic process Phase analysis Superexchange Permanent magnet