Zhong Huang¹, Jian Su², Guangjun Wen¹, Wenxian Zheng³, Chu Chu¹, Yijun Zhang^4,*, Yibo Zhang⁵

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 399-408, 2019, DOI:10.32604/cmc.2019.05876

Abstract A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems. The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA (DFSA) and to adjust access probability in random access protocols. Conventional researches estimate the number of tags in MAC layer based on statistics of empty slots, collided slots and successful slots. Usually, a collision detection algorithm is employed to determine types of time slots. Only three types are distinguished because of lack of ability to detect the number of tags in single time slot. In this… More >

Yang Yu¹, Zeyu Xiong^1,*, Yueshan Xiong¹, Weizi Li²

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 103-118, 2019, DOI:10.32604/cmc.2019.05154

Abstract Logistic regression is often used to solve linear binary classification problems such as machine vision, speech recognition, and handwriting recognition. However, it usually fails to solve certain nonlinear multi-classification problem, such as problem with non-equilibrium samples. Many scholars have proposed some methods, such as neural network, least square support vector machine, AdaBoost meta-algorithm, etc. These methods essentially belong to machine learning categories. In this work, based on the probability theory and statistical principle, we propose an improved logistic regression algorithm based on kernel density estimation for solving nonlinear multi-classification. We have compared our approach with other methods using non-equilibrium samples,… More >

Kamaljit Kaur^{1, *}, Kuljit Kaur²

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 913-946, 2019, DOI:10.32604/cmc.2019.07675

Abstract Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the gradual change/deterioration of HDDs; they… More >

Yao Hsu¹, Chih-Yen Su², Wen-Fang Wu^3,4

CMC-Computers, Materials & Continua, Vol.36, No.2, pp. 155-176, 2013, DOI:10.3970/cmc.2013.036.155

Abstract To study the fatigue reliability of a flip-chip chip scale package (FCCSP) subject to thermal cyclic loading, a Monte Carlo simulation-based parametric study is carried out in the present study. A refined procedure as compared with the recently released Probabilistic Design System (PDS) of ANSYS is proposed and employed in particular. The thermal-cyclic fatigue life of the package is discussed in detail since it is related directly to the reliability of the package. In consideration of the analytical procedure as well as real manufacturing processes, a few geometric dimensions and material properties of the package are assumed random. The empirical… More >

C.J. Huang¹, T.Y. Hung¹, K.N. Chiang²

CMC-Computers, Materials & Continua, Vol.36, No.2, pp. 99-133, 2013, DOI:10.3970/cmc.2013.036.099

Abstract The development in the field of nanotechnology has prompted numerous researchers to develop various simulation methods for determining the material properties of nanoscale structures. However, these methods are restricted by the speed limitation of the central processing unit (CPU), which cannot estimate larger-scale nanoscale models within an acceptable time. Thus, decreasing the CPU processing time and retaining the estimation accuracy of physical properties of nanoscale structures have become critical issues. Accordingly, this study aims to decrease the CPU processing time and complexity of large nanoscale models by utilizing, atomistic-continuum mechanics (ACM) to build an equivalent model of carbon nanotubes (CNTs).… More >

J.M. Zhu¹, X.C. Wang¹, D. Wei², Y.H. Liu², B.Y. Xu²

CMC-Computers, Materials & Continua, Vol.22, No.3, pp. 261-274, 2011, DOI:10.3970/cmc.2011.022.261

Abstract The residual stiffness of concrete member after fire is a very important parameter of the load-bearing ability and seismic performance of fire-damaged concrete structures. It is also one of the most important criteria for repairing and reinforcing the fire-damaged concrete structures. Based on the equivalent elastic modulus method, improved segment model method and parameter inversion method developed in this paper, the residual stiffness of concrete members exposed to standard fire is calculated and the effects of fire duration, steel ratio and section size on the stiffness are also presented in detail. The results show that these three methods can easily… More >

H. T. Chen¹,K. H. Hsu¹, S. K. Lee¹, L. Y. Haung¹

CMC-Computers, Materials & Continua, Vol.22, No.3, pp. 239-260, 2011, DOI:10.3970/cmc.2011.022.239

Abstract The inverse scheme of the finite difference method in conjunction with the least-squares scheme and experimental measured temperatures is proposed to solve a two-dimensional steady-state inverse heat conduction problem in order to estimate the natural-convection heat transfer coefficient under the isothermal situation [`h] iso from three vertical fins mounted on a vertical plate and fin efficiency hf for various values of the fin spacing and fin height. The measured fin temperatures and ambient air temperature are measured from the present experimental apparatus conducted in a small wind tunnel. The heat transfer coefficient on the middle fin of three vertical fins… More >