Changing Trends in Modeling Mobility by Aarti Munjal, Tracy Camp, Nils Aschenbruck

“…A phenomenal increase in the number of wireless devices has led to the evolution of several interesting and challenging research problems in opportunistic networks. For example, the random waypoint mobility model, an early, popular effort to model mobility, involves generating random movement patterns. …”
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Effect of Luminance and Contrast Variation on Stereoacuity Measurements Using Smartphone Technology by Lu Liu, Lingxian Xu, Junyue Wang, Huang Wu

“…Similarly, no significant difference was found between contour-based and random-dot-based patterns under different contrasts of above 35%. …”
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Compressed Sensing Based Apple Image Measurement Matrix Selection by Ying Xiao, Wanlin Gao, Ganghong Zhang, Han Zhang

“…This paper firstly chooses sym5 wavelet base as apple image sparse transformation base, and then it uses Gaussian random matrices, Bernoulli random matrices, Partial Orthogonal random matrices, Partial Hadamard matrices, and Toeplitz matrices to measure apple images, respectively. …”
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RELIABILITY SENSITIVITY ANALYSIS OF TRACKED VEHICLE GEAR TRANSMISSION BOX WITH MULTIPLE FAILURE MODES by YAN SiHong, TAO FengHe, JIA ChangZhi

“…In order to solve the problem of reliability sensitivity analysis of tracked vehicle transmission gears in the presence of different failure modes, the random perturbation theory, the fourth moment method and Edgeworth series are employed to calculate the statistical correlation and reliability index of each performance function of the failure modes, and the reliability of the failure modes of the mechanical component with the arbitrary random distribution parameters. …”
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Zero-effort projection for sensory data reconstruction in wireless sensor networks by Xiancun Zhou, Haibo Ling

“…Our scheme can efficiently resolve two types of sensor networks’ data gathering problems: recover missing sensory data and extend monitoring field using incomplete random sampling. Extensive experimental results show that our proposed random sampling zero-encoding data gathering model has good performance for reconstructing the sensory data in wireless sensor networks.…”
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Based on the CT Image Rebuilding the Micromechanics Hierarchical Model of Concrete by Lei Guangyu, Han Jichang

“…The random aggregate model and the interface model of random aggregate were established. …”
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Interacting Urns Processes for Clustering of Large-Scale Networks of Tiny Artifacts by Pierre Leone, Elad M. Schiller

“…Neighboring urns interact by repeatedly adding the same colored ball based on previous random choices. We discover that the process rapidly converges to a definitive random ratio between the colors in every urn. …”
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Probability Density Evolution Algorithm for Stochastic Dynamical Systems Based on Fractional Calculus by Yang Yan, Xiaohong Yu

“…It is the direct probability integration method, which is extended and applied to the random vibration reliability analysis of dynamical systems. …”
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The Effect of Intermittent Signal on the Performance of Code Tracking Loop in GNSS Receivers by Chung-Liang Chang

“…The blanking effect is usually caused by buildings that obscure the signal in either a periodic or random manner. In some cases, ideal blanking is used to remove random or periodic interference. …”
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CS-based data collection method for airborne clustering WSN by HOUWei Z, INGBo J, UANGYi-feng H, IAOXiao-xuan J, UJia-xing H, IANGWei L

“…A data acquisition scheme which was suitable for airborne clustering WSN was proposed.On the one hand,this scheme adopts the random compressive sampling could reduce the amount of sampling data of the cluster nodes ef-fectively,and greatly reducing the hardware requirements of the cluster nodes; on the other hand,put forward a MP re-construction method based on composite chaotic-genetic algorithm expressly,which combined the excellent local searching characteristics of chaos theory with the powerful global search ability of genetic algorithm,could improve the signal reconstruction performance of the cluster head or Sink effectively.The experimental results show that,by dimin-ishing the sampling frequency to 1/8 of the original sampling frequency,this random compressive sensing scheme can dramatically reduce the sampling quantity,and the reconstruction precision can reach 10^-7magnitude.This random com-pressive sensing scheme provides a useful idea for practical WSN.…”
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A Geometric Derivation of the Irwin-Hall Distribution by James E. Marengo, David L. Farnsworth, Lucas Stefanic

“…In certain special cases, the derivation can be extended to linear combinations of independent uniform random variables on other intervals of finite length. …”
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Machine Learning-Based Quantification of Lateral Flow Assay Using Smartphone-Captured Images by Anne M. Davis, Asahi Tomitaka

“…Contrarily, CNN models outperformed random forest models in classifying noisy images.…”
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Application of Big Data Technology to Assessments of Female Ovarian Reserve Dysfunction by Xia Ji'An, Ma YunFei, Wu YiYun, Zhao YouLin, Ni HaoRang, Liu XinYan

“…The random forest algorithm had the least time overhead for datasets smaller than 50 MB; for datasets exceeding 50 MB, the support vector machine algorithm had the least time overhead, followed by the random forest and neural network algorithms. …”
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Vibration Analysis of Driving-Point System with Uncertainties Using Polynomial Chaos Expansion by Bin Xiao, Yu-long Zhou, Chao Gao, Shuang-Xia Shi, Ze-Xi Sun, Zong-biao Song

“…This proposed approach is valid and feasible, but since broad-band spectrum analysis loses some important information about the random vibration, both the aforementioned processes need to simultaneously be applied to analyze the random vibration transmission of low-medium frequency systems.…”
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FORECASTING DEFERRED TAXES IN INTERNATIONAL ACCOUNTING WITH MACHINE LEARNING by Osman Bayri, Ahmet Çağdaş Seçkin, Feden Koç

“…Within the context of the study, the deferred tax output parameters, which companies will present in their annual financial reports in 2020, have been estimated using the following methods: the DTA value using the random forest method with an accuracy rate of 0,823, the net DTA value using the artificial neural networks method with an accuracy rate of 0,790, the DTL value using the random forest method with an accuracy rate of 0,823 and the net DTL value using the random forest method with an accuracy rate of 0,887. …”
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Self-adaptive fuzzing optimization method based on distribution divergence by XU Hang, JI Jiangan, MA Zheyu, ZHANG Chao

“…An interprocedural comparison flow graph was first constructed based on the interprocedural control flow graph to characterize the spatial random field corresponding to the branch condition variables of the program under test, and the distribution features of the random field generated by a fuzzing mutation strategy were extracted using the Monte Carlo method. …”
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Development and validation of a prediction model for coronary heart disease risk in depressed patients aged 20 years and older using machine learning algorithms by Yicheng Wang, Yicheng Wang, Yicheng Wang, Chuan-Yang Wu, Hui-Xian Fu, Jian-Cheng Zhang, Jian-Cheng Zhang, Jian-Cheng Zhang

“…Eight machine learning algorithms are applied to construct the models, among which the Random Forest model has the best performance, with an (Area Under Curve) AUC of 0.987 for the random forest model in the training set, and an AUC of 0.848 for the PR curve. …”
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Quantitative Fourth Moment Theorem of Functions on the Markov Triple and Orthogonal Polynomials by Yoon Tae Kim, Hyun Suk Park

“…In this paper, we consider a quantitative fourth moment theorem for functions (random variables) defined on the Markov triple E,μ,Γ, where μ is a probability measure and Γ is the carré du champ operator. …”
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A genetic algorithm based method of optimizing dispersion matrix for RDSM system by Peng ZHANG, Xiaoping JIN, Dongxiao CHEN

“…Rectangular differential spatial modulation (RDSM) is a multi-antenna incoherent modulation technology with high spectral efficiency, low power consumption, and zero-overhead for channel estimation.RDSM is especially suitable for 6G communication systems, such as fast-moving Internet of vehicles, Internet of things, cellular networks, etc.However, the construction of the sparse rectangular unitary space-time dispersion matrix (DM) at transmitter is a problem.The proposed Genetic algorithm (GA) will result in less computational complexity than the currently used random research.The fitness of GA was calculated by the rank and determinant criterion (RDC) method to avoid discussions in differential system.Due to characteristics of constellation symbols of RDSM, the proposed method reduced the computational complexity during each single iteration in GA.The simulation results show that the optimized DMS can significantly improve the bit error rate (BER) performance of the RDSM system.Compared with random search, the low-complexity GA effectively improves the DMS optimization efficiency of RDSM.The computational complexity required for optimizing DMS is about 0.1% of random search optimization method.…”
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Power Spectral Density Conversions and Nonlinear Dynamics by Mostafa Rassaian

“…This phenomenon, described by the stationary response of the Duffing oscillator to narrow-band Gaussian random excitation, requires an alternative approach for calculation of power spectral density acceleration response at a shock isolated payload under random vibration. …”
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