T. Viveka^1,*, C. Christopher Columbus², N. Senthil Velmurugan³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 535-547, 2022, DOI:10.32604/iasc.2022.022976

Abstract Because of the increasing workload, people are having several clinical examinations to determine their health status, resulting in limited time. Here, we present a healthful consuming device based on rule mining that can modify your parameter dependency and recommend the varieties of meals that will boost your fitness and assist you to avoid the types of meals that increase your risk for sicknesses. Using the meals database, the data mining technique is useful for gathering meal energy from breakfast, after breakfast, lunch, after lunch, dinner, after dinner, and bedtime for ninety days. The purpose of this study is to determine… More >

Hongqiao Wang^1,*, Yanning Cai²

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 187-203, 2022, DOI:10.32604/cmes.2022.018000

Abstract Inertial system platforms are a kind of important precision devices, which have the characteristics of difficult acquisition for state data and small sample scale. Focusing on the model optimization for data-driven fault state prediction and quantitative degree measurement, a fast small-sample supersphere one-class SVM modeling method using support vectors pre-selection is systematically studied in this paper. By theorem-proving the irrelevance between the model's learning result and the non-support vectors (NSVs), the distribution characters of the support vectors are analyzed. On this basis, a modeling method with selected samples having specific geometry character from the training sets is also proposed. The… More >

Yanxue Li^1,*, Weijun Gao^1,2, Xiaoyi Zhang², Wenya Xu¹, Yingjun Ruan³, Yinzhong Wang⁴

Energy Engineering, Vol.119, No.1, pp. 63-81, 2022, DOI:10.32604/EE.2022.016209

Abstract The building sector contributes a large ratio of final energy consumption, and improving building energy efficiency is expected to play a significant role in mitigating its carbon dioxide emission. Herein, we collected the on-site measurement data to investigate the techno-economic performances of different heat pump types that exist in building space heating projects in Qingdao, China. An in-depth analysis revealed the temperature variations of measured low-grade heat sources over the whole heating supply period, and urban sewage water shows high stable heat energy quality compared with seawater and geothermal heat resources. Operational behaviors including cycling inlet and outlet temperature of… More >

Chih-Ta Yen^1,*, Cheng-Hong Liao²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679

Abstract In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of PPG signals and how to… More >

Lihua Zhu¹, Qifan Yun¹, Zhiqiang Wu^1,*, Cheire Cheng²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1489-1501, 2022, DOI:10.32604/cmc.2022.022091

Abstract Thanks to its light weight, low power consumption, and low price, the inertial measurement units (IMUs) have been widely used in civil and military applications such as autopilot, robotics, and tactical weapons. The calibration is an essential procedure before the IMU is put in use, which is generally used to estimate the error parameters such as the bias, installation error, scale factor of the IMU. Currently, the manual one-by-one calibration is still the mostly used manner, which is low in efficiency, time-consuming, and easy to introduce mis-operation. Aiming at this issue, this paper designs an automatic batch calibration method for… More >

Tao Yang¹, Chengyu Wang¹, Tongqing Zhou¹, Zhiping Cai^1,*, Kui Wu², Bingnan Hou¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5179-5198, 2022, DOI:10.32604/cmc.2022.021626

Abstract Malicious attacks can be launched by misusing the network address translation technique as a camouflage. To mitigate such threats, network address translation identification is investigated to identify network address translation devices and detect abnormal behaviors. However, existing methods in this field are mainly developed for relatively small-scale networks and work in an offline manner, which cannot adapt to the real-time inference requirements in high-speed network scenarios. In this paper, we propose a flexible and efficient network address translation identification scheme based on actively measuring the distance of a round trip to a target with decremental time-to-live values. The basic intuition… More >

Syed Ali Raza^*, Ahsan Ullah, Shuang He, Yifeng Wang, Jiangtao Li

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 829-847, 2021, DOI:10.32604/cmes.2021.017360

Abstract The distribution transformer is the mainstay of the power system. Its internal temperature study is desirable for its safe operation in the power system. The purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading conditions. To achieve this goal, the temperature distribution in the oil, core, and windings are studied at each loading. An experimental study is performed with a 10/0.38 kV, 10 kVA oil–immersed transformer equipped with forty–two PT100 sensors (PTs) for temperature measurement installed inside during its manufacturing process. All possible locations for the hottest spot temperature (HST)… More >

Komeil Raisian¹, Jamaiah Yahaya^2,*, Aziz Deraman³

Computer Systems Science and Engineering, Vol.41, No.1, pp. 271-288, 2022, DOI:10.32604/csse.2022.020496

Abstract Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently,… More >

Chih-Ta Yen^1,*, Sheng-Nan Chang², Liao Jia-Xian³, Yi-Kai Huang³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2937-2952, 2022, DOI:10.32604/cmc.2022.020493

Abstract This study proposed a measurement platform for continuous blood pressure estimation based on dual photoplethysmography (PPG) sensors and a deep learning (DL) that can be used for continuous and rapid measurement of blood pressure and analysis of cardiovascular-related indicators. The proposed platform measured the signal changes in PPG and converted them into physiological indicators, such as pulse transit time (PTT), pulse wave velocity (PWV), perfusion index (PI) and heart rate (HR); these indicators were then fed into the DL to calculate blood pressure. The hardware of the experiment comprised 2 PPG components (i.e., Raspberry Pi 3 Model B and analog-to-digital… More >

Yuji Saito^*, Keigo Yamada, Naoki Kanda, Kumi Nakai, Takayuki Nagata, Taku Nonomura, Keisuke Asai

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 1-30, 2021, DOI:10.32604/cmes.2021.016603

Abstract A vector-measurement-sensor-selection problem in the undersampled and oversampled cases is considered by extending the previous novel approaches: a greedy method based on D-optimality and a noise-robust greedy method in this paper. Extensions of the vector-measurement-sensor selection of the greedy algorithms are proposed and applied to randomly generated systems and practical datasets of flowfields around the airfoil and global climates to reconstruct the full state given by the vector-sensor measurement. More >