Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Interventional Pulmonology
The kernel estimator especially the univariate type often needs one smoothing parameter as against more smoothing parameters demanded by greater dimensional estimators though it all depends on kind of smoothing parameterizations employed. The smoothing parameter(s) of kernels with higher dimension may be called smoothing matrices. Kernels of higher dimensions have three kinds of parameterizations as estimators viz: constant, diagonal and full parameterizations. Unlike the full parameterization, the diagonal parameterization exhibits some levels of restrictions. This study investigates the efficiency of kernel estimators to which smoothing parameterizations are applied. The asymptotic mean-integrated squared error is employed as a criterion function with emphasis on bivariate case only. With real data, the results show that full smoothing parameterization outperformed the constant and diagonal parameterizations in respect of the asymptotic mean-integrated squared error’s value and the kernel estimate’s ability to retain the true characteristics of the affected distribution
Power consumption is an essential challenge in medical application devices using WSN, where the patient who carries a battery power system. Thus, an energy-efficient monitoring system that can independently measure the vital signs of the patient is necessary. This study presents an energy-efficient wearable patient monitoring system (WPMS) to monitor the temperature, heart rate, and oxygen level in the blood (SpO2). A low power consumption ZigBee wireless protocol was interfaced with Arduino Pro Mini microcontroller based on Atmega 328P to alert caregivers in real-time during emergency cases when risks are observed in the patient's biomedical signs. A sleep/wake algorithm has been proposed and implemented inside the microcontroller to improve the power consumption of this wearable device. Results show that the power saving of 92.39% was achieved based on sleep/wake algorithm relative to the traditional wearable device (i.e., without sleep/wake algorithm). In addition, the battery life was extended to approximately 15 days relative to the traditional one-day operation. Comparison results disclosed that the WPMS outperform the power consumption of other studies in medical applications. Where the average current consumption of 6.13 mA is obtained based on the sleep/wake scheme. We can be concluded that the proposed system is energy-efficient, real-time monitoring, cost-effective, none-complex, comfortable due to it is dispense of wire connection, and easily implemented
