okirya, martin du plessis, ja
Understanding rainfall variability and trends is crucial for effective water resource management and disaster preparedness, particularly in tropical regions like Uganda. This study analyzes the trends and variability of the Annual Maximum Series (AMS) and seasonal rainfall data across four rainfall stations in Uganda, comparing observed data with v...
lupu (blaj), adina elena vlad, adriana
One technique, especially in chaos-based cryptographic applications, is to include the message in the evolution of the dynamical system. This paper aims to find out if and to what extent the statistical behavior of the chaotic system is affected by the message inclusion in its dynamic evolution. The study is illustrated by the dynamical system desc...
jiang-tao, fu xia-song, hu xi-lai, li zhao, ji-mei xing, guang-yan liu, chang-yi
The shear strength (particularly soil cohesion) of rooted soil is an important parameter that reflects the true erodibility of meadows, particularly in meadows experiencing different degrees of degradation, ranging from undegraded (UD) through to lightly degraded (LD) and from moderately degraded (MD) to heavily degraded (HD). The cohesion of roote...
cui, xiaotong zhang, hongxin jun, xu fang, xing ning, wenxu wang, yuanzhen hosen, sabbir
The leaked signals, including electromagnetic, power, timing, and temperature generated during the operation of cryptographic devices, contain highly correlated key value information, leading to security vulnerabilities. In practical operations, due to information collection conditions and time limitations, attackers can only obtain limited valid d...
nguyen, duc-thuan nguyen, tuan-khai ahmad, zahoor kim, jong-myon
This paper proposes a novel and reliable leak-detection method for pipeline systems based on acoustic emission (AE) signals. The proposed method analyzes signals from two AE sensors installed on the pipeline to detect leaks located between these two sensors. Firstly, the raw AE signals are preprocessed using empirical mode decomposition. The time d...
londhe, digambar s. katpatal, yashwant b. bokde, neeraj dhanraj
Hydrological modeling relies on the inputs provided by General Circulation Model (GCM) data, as this allows researchers to investigate the effects of climate change on water resources. But there is high uncertainty in the climate projections with various ensembles and variables. Therefore, it is very important to carry out bias correction in order ...
ibrahim, mohamad najib
Estimates of extreme precipitation are commonly associated with different sources of uncertainty. One of the primary sources of uncertainty in the statistical modeling of precipitation extremes comes from extreme data series (i.e., sampling uncertainty). Therefore, this research aimed to quantify the sampling uncertainty in terms of confidence inte...
Heuchenne, Cédric Mordant, Gilles
peer reviewed / This paper proposes new tests to compare two multivariate probability distributions. Since basic ranks do not canonically exist in Rd, it is impossible to have a natural multivariate generalisation of rank-based tests such as the two-sample Kolmogorov–Smirnov test. We thus rely on recent measure transportation theory to transform th...
merchant, naveed hart, jeffrey d.
A new nonparametric test of equality of two densities is investigated. The test statistic is an average of log-Bayes factors, each of which is constructed from a kernel density estimate. Prior densities for the bandwidths of the kernel estimates are required, and it is shown how to choose priors so that the log-Bayes factors can be calculated exact...
zou, yajie ding, lusa zhang, hao zhu, ting lingtao, wu
Driving behavior is one of the most critical factors in traffic accidents. Accurate vehicle acceleration prediction approaches can promote the development of Advanced Driving Assistance Systems (ADAS) and improve traffic safety. However, few prediction models consider the characteristics of individual drivers, which may overlook the potential heter...
