Showing 121–132 of 141 results
Chaotic Synchronization of Pulse Waves and RespirationOpen Access
Abstract: Thus far, attention has been paid to phenomena wherein the cardiovascular system and
respiratory movement system have worked in coordination with one another, which has been studied. On the other hands, the earlier studies have hinted at the importance of considering mental and physical health from a holistic perspective, while taking into consideration the principles that prescribe the chaotic behavior of living organisms. In other words, this raises the issue: The validity of hypothesizing chaos dynamics as a universal principle for living systems that prescribes the chaotic nature of pulse waves and respiration. Therefore, the purpose of this study is to focus on pulse waves and respiration in order to examine the relationship in the chaotic nature between the two. Consequently, the issue presented above was supported. What this implies is that quantitatively assessing synchronous phenomena for the LLE for pulse waves and respiration used in this study is a more highly valid approach for determining people’s mental and physical conditions in the fields of clinical medicine and ergonomics, and therefore it could potentially be applied as a means of substantially supporting the promotion of health.
Keywords: Pulse Waves; Respiration; Chaos; Synchronization
The 3-Dimensional Medical Image Recognition of Right and Left Kidneys by Deep GMDH-type Neural NetworkOpen Access
Abstract: In this study, the deep multi-layered Group Method of Data Handling (GMDH)-type neural
network algorithm using principal component-regression analysis is applied to recognition problems of the right and left kidney regions. The deep multi-layered GMDH-type neural network algorithm can automatically organize the deep neural network architectures which have many hidden layers and these deep neural networks can identify the characteristics of very complex nonlinear systems. The architecture of the deep neural network with many hidden layers is automatically organized using the heuristic self-organization method, so as to minimize the prediction error criterion defined as Akaike’s information criterion (AIC) or Prediction Sum of Squares (PSS). The heuristic self-organization method is a type of the evolutionary computation. In this deep GMDH-type neural network, principal component-regression analysis is used as the learning algorithm of the weights in the deep GMDHtype neural network, and multi-colinearity does not occur and stable and accurate prediction values are obtained. This new algorithm is applied to the medical image recognitions of the right and left kidney regions. The optimum neural network architectures, which fit the complexity of the right and left kidney regions, are automatically organized and the right and left kidney regions are automatically recognized and extracted by the organized deep GMDH-type neural networks. The recognition results are compared with the conventional sigmoid function neural network trained using the back propagation method and it is shown that this deep GMDH-type neural networks are useful for the medical image recognition problems of the right and left kidney regions.
Keywords: Deep neural network, GMDH, medical image recognition, evolutionary computation,
Impacts of Radio Frequency Interference on Human Brain Waves and Neuropsychological ChangesOpen Access
Abstract: This study investigates the neuro-psychological impacts of radio frequency interference
(RFI) by correlating the brain waves under RFI exposure. In our experiments, twelve participants were tested under controlled RF exposure at 1.8 GHz in an anechoic chamber under one-blind condition. The electroencephalograph (EEG) were recorded for each 5-minute time trial before, during and after RF exposure with an intensity of 10% of the ICNIRP Guideline exposure limits. The psychological responses of the participants are inquired with psychometric scales before and after the experiment to analyze the correlationship between RFI and the emotional reaction of humans. Statistical tests indicate that theta and alpha waves were able to be characterized, and the significant differences were observed in both alpha waves and theta waves between the data before and after exposure from the consequence of paired t-tests. This initial study indicated that short term exposure to RFI may cause impacts on brain waves, but may not lead to any direct emotional changes by the participants.
Keywords: EEG, Radio frequency interference, RF exposure, Brain waves, Neuro-psychological
Chaotic Synchronization of Respiration and Center of Gravity SwayOpen Access
Abstract: Thus far, attention has been paid to phenomena wherein respiratory movement and physical movement systems have worked in coordination with one another, which has been studied. On the other hand, the earlier studies have hinted at the importance of considering mental and physical health from a holistic perspective, while taking into consideration the principles that prescribe the chaotic behavior of living organisms. In other words, this raises the issue: The validity of hypothesizing chaos dynamics as a universal principle for living systems that prescribes the chaotic nature of center of gravity sway and respiration. Therefore, the purpose of this study is to focus on center of gravity sway and respiration in order to examine the relationship in the chaotic nature between the two. Consequently, the issue presented above was supported. What this implies is that quantitatively assessing synchronous phenomena for the LLE for center of gravity sway and respiration used in this study is a more highly valid approach for determining people’s mental and physical conditions in the field of clinical medicine, and therefore it could potentially be applied as a means of substantially supporting the promotion of health.
Keywords: Respiration; Center of Gravity Sway; Chaos; Synchronization
JACAR Vol. 3 Issue 2Open Access
Publication Date: 18th April. 2017, ISSN 2186-9154, Total Pages: 4
Design and Application of the Electronic Lock for BicycleOpen Access
Abstract: A new type of the anti-theft electronic lock with the lock bolt structure is designed, which can realize the function of locking and unlocking of the bicycle safely. The hardware system includes the STC-12C5A microcontroller, RFID card, data read/write module and mechanical lock structure. The system combined the non-contact RFID card reader and the lock structure. And the static mechanical property is analyzed to meet various situations. A number of actual test results showed that the electronic lock system is safe and reliable.
Keywords: Electronic lock, Lock bolt, Control center, RFID card
JACAR Vol. 2 Issue 2Open Access
Publication Date: 10th Aug. 2016, ISSN 2186-9154, Total Pages: 6
Hardware Detection and Parameter Tuning Method for Speed Control System of PMSMOpen Access
Abstract: In this paper, the development of permanent magnet synchronous motor AC speed control system is taken as an example, aiming to expound the principle and parameter setting method of the system hardware, and puts forward the method of using software or hardware to eliminate the problem.
Keywords: PMSM; Parameter tuning; Closed Control
JACAR Vol. 1 Issue 1Open Access
Publication Date: 25th Dec. 2015, ISSN 2186-9154, Total Pages: 63
Rut Detection using Lasers and In-Vehicle Stereo CameraOpen Access
Abstract: This paper reports a new method of detecting ruts using lasers and in-vehicle stereo camera. We process laser lines reflected in image data to obtain feature values of rut. And we determine whether it is rut or not from shapes of the laser lines. The proposed algorithm ensures processing time and cost reduction in comparison with conventional methods.
Keywords: Rut detection ; Computer vision ; Inspection vehicle
Determining a Mobile Device’s Indoor and Outdoor Location considering Actual UseOpen Access
Abstract: To obtain a person’s location information with high accuracy using mobile devices, it is
necessary for a mobile device to switch its localization method depending on whether the user is
indoors or outdoors. We propose a method to determine indoor and outdoor location using only the
sensors on a mobile device. To obtain a decision with high accuracy for many devices, the method
must consider individual differences between devices. We confirmed that using a majority decision
method reduces the influence of individual device difference. Moreover, for highly accurate decisions in various environments, it is necessary to consider the differences in environments, such as large cities surrounded by high-rise buildings versus suburban areas. We measured classification features in different environments; the accuracy of the classifier constructed using these features was 99.6%.
Keywords: GPS, Wi-Fi, Localization, Mobile Device
Localization for Autonomous Vehicle on Urban RoadsOpen Access
Abstract: Autonomous driving is an emerging technology in which a car performs recognition,
decision making, and control in place of a human driver. Localization is one of the core issues for
autonomous driving. In particular, driving on urban roads requires highly dependable localization
techniques, because the traffic environment is more complicated than that of an expressway. In this paper, we propose a localization algorithm for an autonomous vehicle, which estimates the vehicle’s position by means of template matching. The results show that this algorithm is better suited to make estimations in various environments than the Global Navigation Satellite System and Inertial Measurement Unit (GNSS/IMU) system. Specifically, the method used in this study enables autonomous operation the vehicle up to 13km on public roads, while the GNSS/IMU system cannot achieve this.
Keywords: autonomous vehicle; localization; LIDAR; infrared reflectivity; template matching