bluuebunny/crossref_metadata_2025 huggingface dataset:
Security‐reliability tradeoff analysis of joint relay‐user pair and friendly jammer selection for physical layer security against multiple eavesdroppers
Authors: Zhang Guangna , Gao Yuanyuan , Luo Huadong , Liu Xiaochen , Guo Mingxi , Sha Nan , Wang Shijie
Published: January 2021

This paper examines a wireless communication network comprised of a source and multiple relay‐user pairs in face of multiple malicious eavesdroppers. In order to improve the physical layer security of cooperative communication networks, a joint relay‐user pair and friendly jammer selection (JRUPaFJS) scheme is proposed. Apart from the impacts of friendly jammers on the eavesdroppers, that on the legitimate users is also taken into account due to the presence of channel state information estimation errors. The traditional round‐robin (TRR) scheme and traditional pure relay‐user pair selection (TPRUPS) scheme are considered as benchmark schemes. The exact closed‐form expressions of outage probability and intercept probability for the TRR and TPRUPS schemes as well as JRUPaFJS scheme over Rayleigh fading channels are derived. It is verified that the proposed JRUPaFJS scheme outperforms both the TRR and TPRUPS schemes in terms of their SRT, which demonstrates the wireless security and reliability benefits of exploiting JRUPaFJS scheme. Moreover, as the number of relay‐user pairs increases, the SRT of the TPRUPS and JRUPaFJS schemes improve notably, while as the number of eavesdroppers increases, the SRT of all the three schemes become worse.
A new fault tolerant control scheme for non‐linear systems by T‐S fuzzy model approach
Authors: Wu Yue , Wang Yang , Li Tieshan , Yang Zhixin
Published: January 2021

This paper is concerned with the problem of fault tolerant control for non‐linear systems with sensor faults based on the T‐S fuzzy model approach. First, a fault estimation (FE) observer with technique is designed to estimate the fault. Second, by using the fault estimation information, which are provided by the fault estimation observer, a novel fault tolerant control scheme with a fault compensation mechanism in the premise part of the fuzzy controller is presented to compensate the effect of the fault and stabilize the system. Different from the existing methods, where the fault compensation mechanism is only established in the consequent part of the controller, in the presented method, the fault compensation mechanism is established in the consequent part as well as the premise part of the fuzzy controller. Then, by using the fault compensation mechanism, the bound of the deviation between the normalized membership functions of the fuzzy model and those of the controller can be reduced such that the fault tolerant control design can be relaxed. In the end, an example is given to illustrate the validity of the developed fault tolerant control scheme.
A two‐stage method for bus passenger load prediction using automatic passenger counting data
Authors: Wang Pengfei , Chen Xuewu , Chen Jingxu , Hua Mingzhuang , Pu Ziyuan
Published: January 2021

In high‐frequency transit, providing real‐time crowding information (RTCI) is a potential way to promote passenger satisfaction and reduce negative crowding externalities, by assisting passengers in choosing less crowded vehicles. To make RTCI convincing and reliable, it is necessary to provide predictive RTCI, in which bus passenger load (BPL) prediction is the primary problem. This paper proposes a novel two‐stage BPL prediction method using automatic passenger counting (APC) data. The first stage is to predict short‐term passenger flows at stops based on an adaptive Kalman filter approach. Using the outputs from the first stage as well as other variables directly from APC data, the second stage is to predict BPL based on a support vector regression algorithm. Several methods from the existing literature are used as benchmarks to test the relative performance of the proposed method. An empirical study on bus line 1 in Suzhou, China shows that the proposed method outperforms all the benchmarks, and shows significant superiority over other methods for stops with sharp increases in BPL and for multi‐step ahead prediction. This study contributes to the limited literature on BPL prediction and lays the foundation for providing accurate and reliable predictive RTCI in the future.
Safety guaranteed longitudinal motion control for connected and autonomous vehicles in a lane‐changing scenario
Authors: Hu Zhanyi , Yang Zeyu , Huang Jin , Zhong Zhihua
Published: January 2021

This paper aims at utilising the ideology of controlling a constrained dynamical system to address the longitudinal motion control problem during lane‐changing process subject to time‐varying uncertainties. To this end, a robust controller is designed based on Udwadia–Kalaba (UK) approach and Lyapunov stability theory. Most of the studies on lane‐changing considered only the equality constraint, namely the desired inter‐vehicle distance. In a bilateral inequality constraint, the upper bound avoids unpredictable cut‐ins and the lower bound collisions. This research applies the constraint to guarantee a safe and efficient lane‐changing process. The original UK approach cannot handle bilateral inequalities. Therefore, a diffeomorphism method is proposed to transform the bounded state to an unbounded one. The latter enables the UK approach to deal with both equality and bilateral inequality constraints. The proposed controller can render each vehicle to adjust its distance with the predecessor without violating the prescribed bounds. Numerical experiments have been conducted to validate the effectiveness of the proposed controller under different traffic demands.
Incidence of Venous Thromboembolism in a Racially Diverse Population of Oklahoma County, Oklahoma
Authors: Wendelboe Aaron M. , Campbell Janis , Ding Kai , Bratzler Dale W. , Beckman Michele G. , Reyes Nimia L. , Raskob Gary E.
Published: January 2021

Background Contemporary incidence data for venous thromboembolism (VTE) from racially diverse populations are limited. The racial distribution of Oklahoma County closely mirrors that of the United States.

Objective To evaluate VTE incidence and mortality, including demographic and racial subgroups.

Design Population-based prospective study.

Setting We conducted VTE surveillance at all relevant tertiary care facilities and outpatient clinics in Oklahoma County, Oklahoma during 2012 to 2014, using both active and passive methods. Active surveillance involved reviewing all imaging reports used to diagnose VTE. Passive surveillance entailed identifying VTE events from hospital discharge data and death certificate records.

Measurements We used Poisson regression to calculate crude, age-stratified, and age-adjusted incidence and mortality rates per 1,000 population per year and 95% confidence intervals (CIs).

Results The incidence rate of all VTE was 3.02 (2.92–3.12) for those age ≥18 years and 0.05 (0.04–0.08) for those <18 years. The age-adjusted incidence rates of all VTE, deep vein thrombosis, and pulmonary embolism were 2.47 (95% CI: 2.39–2.55), 1.47 (1.41–1.54), and 0.99 (0.93–1.04), respectively. The age-adjusted VTE incidence and the 30-day mortality rates, respectively, were 0.63 and 0.121 for Asians/Pacific Islanders, 3.25 and 0.355 for blacks, 0.67 and 0.111 for Hispanics, 1.25 and 0.195 for Native Americans, and 2.71 and 0.396 for whites.

Conclusion The age-adjusted VTE incidence and mortality rates vary substantially by race. The incidence of three per 1,000 adults per year indicates an important disease burden, and is informative of the burden in the U.S. population.
Effect of the First Factor VIII Infusions on Immunological Biomarkers in Previously Untreated Patients with Hemophilia A from the HEMFIL Study
Authors: de Oliveira Larissa Maira Moura , Jardim Letícia Lemos , Santana Marcio Antônio Portugal , Cerqueira Mônica Hermida , Lorenzato Claudia Santos , Franco Vivian Karla Brognoli , Zuccherato Luciana Werneck , Rezende Suely Meireles , Chaves Daniel Gonçalves
Published: January 2021

Hemophilia A (HA) is an inherited bleeding disorder which requires continuous replacement with factor (F) VIII concentrate. The main complication of HA is the development of neutralizing alloantibodies which inhibit FVIII activity (inhibitors). The objective of this study was to investigate the effect of the first FVIII infusions on immunological biomarkers in previously untreated patients with HA. Plasma samples were collected at enrollment before any FVIII infusion (T0) and at inhibitor development (INB +/T1) or up to 35 exposure days without inhibitors (INB −/T1). Anti-FVIII antibodies (immunoglobulin M, immunoglobulin G [IgG] 1, IgG3, and IgG4), chemokines (CCL2, CCL5, CXCL8, CXCL9, and CXCL10), and cytokines (interleukin [IL]-2, IL-4, IL-6, IL-10, interferon-γ, tumor necrosis factor, and IL-17) were assessed. A total of 71 children with severe HA were included, of whom 28 (39.4%) developed inhibitors. Plasma levels of anti-FVIII IgG4, IL-6, and CXCL8 were higher at INB +/T1 when compared with INB −/T1. This group presented a mixed cytokine profile and higher plasma levels of CXCL9 and CXL10 when compared with INB +/T1. We conclude that exposure to FVIII triggers a proinflammatory response mediated by IL-6 and CXCL8 in patients with HA who developed inhibitors. Regardless of inhibitor status, the immune system of all HA patients is stimulated after infusions of FVIII.
Properties, preparation, and application of tungsten disulfide: a review
Authors: Ding Jinzi , Feng Ailing , Li Xiaodong , Ding Shijiu , Liu Liang , Ren Wei
Published: January 2021

Transition metal dichalcogenides (TMDs) attract research interest owing to their unique physical and chemical properties. Among the family of TMDs, tungsten disulfide (WS2) has a unique band structure due to its semiconductor characteristics; namely, its broadband spectral response characteristics, ultra-fast bleach recovery time and excellent saturable light absorption. This article is a review of the current application of WS2 in catalysts, lasers, batteries, photodetectors and lubricants. The review begins with a brief overview of the structure, properties and growth of WS2 and describes the existing preparation methods for this material. Finally, methods for improving the performance of WS2 in its current applications are presented. This review is limited to the most recent reports on this topic.
Hybrid model of radio-frequency low-pressure inductively coupled plasma discharge with self-consistent electron energy distribution and 2D electric field distribution
Authors: Yang Wei , Wang You-Nian
Published: January 2021

Low-pressure radio-frequency (RF) inductively coupled plasmas (ICPs) are extensively used for materials processing. In this work, we have developed a hybrid model consisting of two-dimensional (2D) Maxwell equations with an open boundary, zero-dimensional Boltzmann equation under linear and quasilinear approximations, and a power balance equation. The hybrid model is capable of achieving a self-consistent description of the electron heating mechanism and electron kinetics for the RF ICPs at low pressures. This work presents an investigation of the influence of operating conditions on 2D distributions of electric field and power density, normalized electron energy probability function (EEPF) (effective electron temperature), and plasma density in a low-pressure RF Ar ICP using the hybrid model. The results show that the RF frequency and absorption power significantly affect the 2D distributions and amplitudes of electric field and power density. The normalized EEPF is almost independent of RF frequency and weakly dependent on absorption power but significantly modulated by pressure at low RF frequency. The plasma density is also almost independent of RF frequency but increases with absorption power and pressure. In addition, we have validated the hybrid model against experimental data obtained in the driver region of a two-chamber RF Ar ICP source, where the RF frequency is 13.56 MHz, the power range is 200–1000 W and the pressure range is 0.1–1.0 Pa. The hybrid model qualitatively (and even quantitatively for some cases) reproduces the experimentally normalized EEPF and plasma density. The discrepancies in these plasma parameters could be attributed to the simplified collision processes taken into account in the hybrid model. The developed hybrid model can help us to better understand the effect of discharge conditions on electron kinetics and electron heating mechanism, and to ultimately optimize the parameters of RF ICP sources.
Synergy of coupled kink and tearing modes in fast ion transport
Authors: Yang J , Podestà M , Fredrickson E D
Published: January 2021

One aspect of the interaction between fast ions and magnetohydrodynamic (MHD) instabilities is the fast ion transport. Coupled kink and tearing MHD instabilities have also been reported to cause fast ion transport. Recently, the ‘kick’ model has been developed to compute the evolution of the fast ion distribution from neutral beam injection using instabilities as phase-space resonance sources. The goal of this paper is to utilize the kick model to understand the physics of fast ion transport caused by the coupled kink and tearing modes. Soft x-ray diagnostics are used to identify the mode parameters in the National Spherical Torus Experiment. The comparison of neutron rates measured and computed from time-dependent TRANSP simulation with the kick model shows that the coupling of kink and tearing mode is important in determination of the fast ion transport. The numerical scan of the mode parameters shows that the relative phase of the kink and tearing modes and the overlapping of kink and tearing mode resonances in the phase space can affect the fast ion transport, suggesting that the synergy of the coupled modes may be causing the fast ion transport.
Ultralight dark matter detection with mechanical quantum sensors
Authors: Carney Daniel , Hook Anson , Liu Zhen , Taylor Jacob M , Zhao Yue
Published: January 2021

We consider the use of quantum-limited mechanical force sensors to detect ultralight (sub-meV) dark matter (DM) candidates which are weakly coupled to the standard model. We show that mechanical sensors with masses around or below the milligram scale, operating around the standard quantum limit, would enable novel searches for DM with natural frequencies around the kHz scale. This would complement existing strategies based on torsion balances, atom interferometers, and atomic clock systems.
On rapid oscillations driving biological processes at disparate timescales
Authors: Lunz Davin
Published: January 2021

We consider a generic biological process described by a dynamical system, subject to an input signal with a high-frequency periodic component. The rapid oscillations of the input signal induce inherently multiscale dynamics, motivating order-reduction techniques. It is intuitive that the system behaviour is well approximated by its response to the averaged input signal. However, changes to the high-frequency component that preserve the average signal are beyond the reach of such intuitive reasoning. In this study, we explore system response under the influence of such an input signal by exploiting the timescale separation between high-frequency input variations and system response time. Employing the asymptotic method of multiple scales, we establish that, in some circumstances, the intuitive approach is simply the leading-order asymptotic contribution. We focus on higher-order corrections that capture the response to the details of the high-frequency component beyond its average. This approach achieves a reduction in system complexity while providing valuable insight into the structure of the response to the oscillations. We develop the general theory for nonlinear systems, while highlighting the important case of systems affine in the state and the input signal, presenting examples of both discrete and continuum state spaces. Importantly, this class of systems encompasses biochemical reaction networks described by the chemical master equation and its continuum approximations. Finally, we apply the framework to a nonlinear system describing mRNA translation and protein expression previously studied in the literature. The analysis shines new light on several aspects of the system quantification and both extends and simplifies results previously obtained.
Efficient carpet invisibility cloaking with dielectric resonant metasurfaces in terahertz region
Authors: Lu Tian , Feng Dantian , Fang Bo , Zhou Pengwei , Yao Dong , Jing Xufeng , Li Chenxia , Gan Haiyong , He Yingwei , Cai Jinhui , Hong Zhi
Published: January 2021

The application of metasurface in invisibility technology is mainly based on its phase control function, which provides a new choice for the design of ultra-thin carpet cloaking devices with arbitrary shape. At present, most of the carpet cloaking devices mainly focus on metal structure metasurfaces. The Ohmic loss of metallic materials seriously affects the efficiency of cloaking devices. To reduce Ohmic loss and improve reflection efficiency, a dielectric resonance cylindrical harmonic oscillator is proposed to construct the metasurface layer. Based on the analysis of the principle of carpet reflection cloaking, a dielectric metasurface layer is optimized to cover a triangular scatterer, making it invisible. The near field and far field scattering characteristics of dielectric metasurface carpet cloaking device are numerically simulated to confirm its cloaking effect.
Dispersive analysis of low energy γN→πN process and studies on the N*(890) resonance *
Authors: Ma Yao , Niu Wen-Qi , Yao De-Liang , Zheng Han-Qing
Published: January 2021

We present a dispersive representation of the

partial-wave amplitude based on unitarity and analyticity. In this representation, the right-hand-cut contribution responsible for

final-state-interaction effects is taken into account via an Omnés formalism with elastic

phase shifts as inputs, while the left-hand-cut contribution is estimated by invoking chiral perturbation theory. Numerical fits are performed to pin down the involved subtraction constants. Good fit quality can be achieved with only one free parameter, and the experimental data regarding the multipole amplitude

in the energy region below the

are well described. Furthermore, we extend the

partial-wave amplitude to the second Riemann sheet to extract the couplings of the

. The modulus of the residue of the multipole amplitude

(S

) is

, and the partial width of

at the pole is approximately

, which is almost the same as that of the

resonance, indicating that

strongly couples to the

system.
The microglia response to electrical overstimulation of the retina imaged under a transparent stimulus electrode
Authors: Yohannes Alula R , Jung Christopher Y , Shea Katherine I , Wong Wai T , Beylin Alexander , Cohen Ethan D
Published: January 2021

Objective. We investigated using the morphological response of retinal microglia as indicators of tissue damage from electrical overstimulation by imaging them through an optically transparent stimulus electrode. Approach. To track the microglia, we used a transgenic mouse where the microglia expressed a water soluble green fluorescent protein. The clear stimulus electrode was placed epiretinally on the inner limiting membrane and the microglia layers were imaged using time-lapse confocal microscopy. We examined how the microglia responded both temporally and spatially to local overstimulation of the retinal tissue. Using confocal microscope vertical image stacks, the microglia under the electrode were imaged at 2.5 min intervals. The retina was overstimulated for a 5 min period using 1 ms 749 μC cm−2 ph−1 biphasic current pulses and changes in the microglia morphology were followed for 1 h post stimulation. After the imaging period, a label for cellular damage was applied to the retina. Main results. The microglia response to overstimulation depended on their spatial location relative to the electrode lumen and could result in three different morphological responses. Some microglia were severely injured and became a series of immotile ball-like fluorescent processes. Other microglia survived, and reacted rapidly to the injury by extending filopodia oriented toward the damage zone. This response was seen in inner retinal microglia outside the stimulus electrode edge. A third effect, seen with the deeper outer microglia under the electrode, was a fading of their fluorescent image which appeared to be due to optical scatter caused by overstimulation-induced retinal edema. Significance. The microglial morphological responses to electrical overstimulation injury occur rapidly and can show both direct and indirect effects of the stimulus electrode injury. The microglia injury pattern closely follows models of the electric field distribution under thinly insulated disc electrodes.
A study on CNN image classification of EEG signals represented in 2D and 3D
Authors: Bird Jordan J , Faria Diego R , Manso Luis J , Ayrosa Pedro P S , Ekárt Anikó
Published: January 2021

Objective. The novelty of this study consists of the exploration of multiple new approaches of data pre-processing of brainwave signals, wherein statistical features are extracted and then formatted as visual images based on the order in which dimensionality reduction algorithms select them. This data is then treated as visual input for 2D and 3D convolutional neural networks (CNNs) which then further extract ‘features of features’. Approach. Statistical features derived from three electroencephalography (EEG) datasets are presented in visual space and processed in 2D and 3D space as pixels and voxels respectively. Three datasets are benchmarked, mental attention states and emotional valences from the four TP9, AF7, AF8 and TP10 10–20 electrodes and an eye state data from 64 electrodes. Seven hundred twenty-nine features are selected through three methods of selection in order to form 27 × 27 images and 9 × 9 × 9 cubes from the same datasets. CNNs engineered for the 2D and 3D preprocessing representations learn to convolve useful graphical features from the data. Main results. A 70/30 split method shows that the strongest methods for classification accuracy of feature selection are One Rule for attention state and Relative Entropy for emotional state both in 2D. In the eye state dataset 3D space is best, selected by Symmetrical Uncertainty. Finally, 10-fold cross validation is used to train best topologies. Final best 10-fold results are 97.03% for attention state (2D CNN), 98.4% for Emotional State (3D CNN), and 97.96% for Eye State (3D CNN). Significance. The findings of the framework presented by this work show that CNNs can successfully convolve useful features from a set of pre-computed statistical temporal features from raw EEG waves. The high performance of K-fold validated algorithms argue that the features learnt by the CNNs hold useful knowledge for classification in addition to the pre-computed features.
A construction of MDS involutory matrices using MDS self-dual codes: a preliminary result
Authors: Irwansyah  , Alamsyah I. Muchtadi , Yuliawan F.
Published: January 2021

The Maximum Distance Separable (MDS) matrices have an important application in cryptography, for example see [1]. In order to reduce the implementation complexities, it is important to consider MDS matrices which are involutory. Some constructions of involutory MDS matrices can be found in [2, 3]. In this paper, we give some properties related to a construction of involutory MDS matrices using orthogonal matrices derived from Euclidean self-dual MDS codes. Then, we do a computer search to find involutory MDS matrices with small sizes using classical simulated annealing algorithm. The proposed construction is different compared to the ones in [2, 3].
Mathematical model of COVID-19 transmission in the presence of waning immunity
Authors: Inayaturohmat F , Zikkah R N , Supriatna A K , Anggriani N
Published: January 2021

We develop a new transmission model of COVID-19 in the presence of waning immunity with isolation and vaccination in humans. The spreading of the disease is determined by the basic reproduction number (ℜ0). Based on mathematical analysis, we found that the non-endemic equilibrium is locally asymptotically stable when ℜ0 < 1 whereas the endemic equilibrium is locally asymptotically stable when ℜ0 > 1. A numerical simulation is used to show the population dynamics. In conclusion, isolation, and vaccination (once it is available) are regarded as effective strategies for eliminating viruses, or at least to suppress the spread of the disease.
On the computational Bayesian survival spatial dengue hemorrhagic fever (DHF) modeling with double-exponential CAR frailty
Authors: Rantini D , Abdullah M N , Iriawan N , Irhamah  , Rusli M
Published: January 2021

In statistics, there are many types of data. Some data carry information about the location where observations occur, so that they can have a spatial effect. Dengue hemorrhagic fever (DHF) data which is easily transmitted, will be consequently has a spatial effect on its patient survival. In this study, we included DHF patient recovery time as a response variable, and several other variables as covariates considered to influence the patient’s recovery time. Our aim in this study is to model how these variables affect the recovery rate for DHF patients with the accompanying patient residence as the spatial effects. Survival analysis is the best method for modeling the recovery rate for DHF patients. A conditional autoregressive (CAR) model is given to explain the relationship between adjacent locations, which is not explained in the general survival analysis. Several researchers have used the Cox model coupled with the Normal CAR. In this study, we used the Cox model using Normal CAR and compared it with the Double-Exponential (DE) CAR. To estimate the regression parameters of the Cox model, we used the Stan software. The advantage of Stan compared to the other Bayesian software such as BUGS and JAGS is the creativity of the researcher in writing the distribution as user-defined, as well as writing the CAR model in the Stan. Based on the WAIC value, modeling the DHF data using the Cox model coupled with the DE CAR is better than coupled with the Normal CAR. Based on the best model, variables that affect the recovery rate of DHF patients are age, the high schools in last education, unemployed in the type of occupations, the stadium II in severity level, pulse, temperature, and leukocytes.
Analysis of factors associated with early stage Parkinson’s disease based on daily activities and sleeping behaviour disorder
Authors: Nastitie F , Abdulllah S , Nurrohmah S
Published: January 2021

Parkinson’s Disease (PD) is a disorder in human movement coordination system that is characterized by motoric and non-motoric symptoms. At the late stage of PD, clinical diagnosis is relatively easy to detect because the symptoms are clear-cut. However, when the symptoms are often incomplete or subtle, in the initial stage, diagnosis becomes difficult and sometimes the subject still remains undiagnosed or even misdiagnosed. This study was aimed at identifying risk factors in early stage PD based on patient daily activities and rapid eye movement behaviour disorder. Daily activities were measured using the Modified Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) part I and part II and sleep behaviour disorder was measured using Rapid eye movement sleeping Behaviour Disorder Screening Questionnaire (RBDSQ). Data analysis was conducted using classification trees with CART algorithm, to classify patients into early stage PD patients or healthy control patients. Missing values were handled using k-Nearest Neighbour (kNN) method. The results were satisfactory, with the classification accuracy of 86.5%, sensitivity 80%, specificity 91.57% and AUC 0.858. It is also found that tremor, dressing difficulty, speech difficulty, RBD questionnaire score, and age are important in differentiating early stage PD from healthy control.
Adjustable robust counterpart optimization model for internet shopping online problem
Authors: Chaerani D , Rusyaman E , Mahrudinda  , Marcia A , Fridayana A
Published: January 2021

In this paper, a discussion on deriving the Adjustable Robust Counterpart for Internet Shopping Online (ARC-ISO) is discussed. The problem on Internet Shopping Online is considered as an application of Robust Maximum Flow Problem (RMFP) with circular demand. The decision variables which considered as the adjustable variable is the maximum flow from a destination node in a flow network which back to the source node. In this paper, when the source nodes is multiple, then it is possible to add a dummy node as a single source node. For the multiple destinations, the same design is done. The main challenge is when and how we assume the data can be uncertain and assumed to be lies within a box, an ellipsoidal or polyhedral uncertainty set. In this paper, the uncertain delivering time is assumed to be lied in a polyhedral uncertainty set.
Quantile regression in varying coefficient model of upper respiratory tract infections in Bandung City
Authors: Tantular B , Andriyana Y , Ruchjana B N
Published: January 2021

Varying coefficient models are commonly used to obtain effects of covariates that vary over other variables. A special case of varying coefficient model is applied to longitudinal data where the covariates may vary over time. When the function is not easy to specify parametrically, we then need to work on a non-parametric regression technique. In this case, we approximate the function by B-splines. B-splines smoothing tends to overfit with increasing knots, then a penalty is added to the quantile objective function. This estimation procedure is called P-splines. As the objective function, we propose to use quantile loss function. The technique will be implemented to the upper respiratory tract infection data in Bandung City which was measured repeatedly from 30 sub district in Bandung City and hence we have a longitudinal data structure.
Stationary distribution Markov chain for Covid-19 pandemic
Authors: Achmad A L H , Mahrudinda  , Ruchjana B N
Published: January 2021

Coronavirus disease (Covid-19) is a new disease found in the late 2019. The first case was reported on December 31, 2019 in Wuhan, China and spreading all over the countries. The disease was quickly spread to all over the countries. There are 206,900 cases confirmed by March 18, 2020 causing 8,272 death. It was predicted that the number of confirmed cases will continue to increase. On January 30, 2020, World Health Organization (WHO) declared this as Public Health Emergency of International Concern (PHEIC). There are a lot of researchers which discuss pandemic spreading caused by virus with mathematical modelling. In this paper, we discuss a long-term prediction over the Covid-19 spreading using stationary distribution Markov chain. The aim of this paper is to analyze the prediction of infected people in long-term by analyzing the Covid-19 daily cases in an observation interval. By analyzing the daily cases of Covid-19 worldwide from December 31, 2019 until April 16, 2020, result shows that 61.43% of probability that the Covid-19 daily case will incline in long-term, 32.14% of chance will decline, and 6.43% of chance will stagnant.
Factors affecting the number of dengue fever cases in West Sumatra province using the Multivariate Adaptive Regression Splines (MARS) approach
Authors: Sriningsih R , Otok B W , Sutikno
Published: January 2021

The Multivariate Adaptive Regression Splines (MARS) approach is a multivariate nonparametric regression analysis that assumes the form of a functional relationship between response variable and predictors whose patterns are unknown. MARS is a combination of Recursive Partitioning Regression (RPR) and the Spline method which is able to process high-dimensional data (data that has many predictor variables 3 ≤ p ≤ 20), and large data samples (50 ≤ n ≤ 1000). The MARS model is obtained from a combination of Basis Function values (BF), Maximum Interaction (MI), and Minimum Observation (MO) by trial and error. In this study, we describe the use of MARS to analyze the factors that influence the number of dengue cases in West Sumatra Province. The response variable (Y) used was the number of dengue fever cases in West Sumatra Province with several predictor variables, namely the number of health workers (X1), the number of health facilities (X2), the height of an area (X3), and the density of settlements (X4). The data used is secondary data from the Central Statistics Agency (BPS) in 2019. Based on the calculation, the best model for this problem is the model with a combination of BF = 16, MI = 3, and MO = 2 with GCV value = 279.1654. The results showed that all predictor variables had an effect on the number of dengue fever cases according to the order of importance: the number of health workers (X1), the number of health facilities (X2), the density of settlements (X4) and finally the height of an area (X3).
Application of Internet Communications in Agricultural Electromechanical Drainage and Irrigation Pumping Station
Authors: Li Yanman , Huang Kun , Zhu Xingye , Lu Keji
Published: January 2021

With the gradual advancement of electric energy substitution, the power consumption of agricultural electromechanical drainage and irrigation pumping station increases rapidly. It is urgent to update and transform the pumping station. Aiming at the substitution scenario of electric energy for agricultural irrigation and drainage, the technology of internet communications are combined in the application. It focuses on the design of two systems: monitoring and warning of operation conditions, and charging management of pumping stations. An electrical control cabinet integrated with power supply and control is designed by using PLC control system. This control cabinet is installed in the pump house of irrigation and drainage area. Some control terminals can be connected to it, and each terminal can be connected with a load that can work or shut down independently. These two systems store and analyse the operation conditions and electricity charge information. They also establish database and exchange data with external power supply companies and water resources management bureaus through internet communications. They are used to realize intelligent control and management. It is of great significance to establish a perfect integrated power supply control system for agricultural irrigation and drainage.
Advanced Production Plan System of Military Manufacturing Enterprises Based on Linear Programming Model
Authors: Wang Tao , Zhao Yaojun , Zhu Xi
Published: January 2021

The problem encountered by military manufacturing enterprises in the preparation of production plans is mainly attributable to the failure to optimize supply and demand resources in the supply chain. The article innovatively employs the advanced planning system based on linear programming model to solve the problem. The problem is first of all described mathematically; then its linear programming model is constructed, and the latter’s APS system designed; at last, the model is solved and checked. Upon the verification, the model is proven helpful for enterprises to work out production plans quickly and efficiently, and carry out what-if analysis. While winning the time advantage for military manufacturing enterprises in the market competition, it also enhances their operating management efficiency.
Design for Spatiotemporal Information Cloud Platform of Smart City Based on OSGi
Authors: Zhao Tianpu , Yu Zhibo , Han Jiale , Zhang Min , Wang Jingyang
Published: January 2021

In 2009, IBM put forward the development policy of building “smart city” before building “smart earth”. In response to this policy, the National Bureau of Surveying and Mapping issued “The Notification on the Development of Smart City Spatiotemporal Information Cloud Platform”, which formally took the construction spatiotemporal information cloud platform of smart city as a pilot project. In this paper, the OSGi (Open Service Gateway Initiative) technology is used as the framework. Developing component on demand is realized by the SOA architecture and OSGi technology, which improves the efficiency of developing software, shortens the cycle of developing software and saves labor costs. Resource access is achieved through RESTful services, and distributed coordination services are implemented through Zookeeper.
Improving the Performance of Target Tracker by Deepening Neural Network
Authors: Zhao Yifeng , Lang Weimin , Peng Xiangyu , Li Bin
Published: January 2021

Visual target tracking is an important topic in the field of vision research. Its main task is to automatically process and analyze the input video information by computer, so as to obtain the position and key motion information of the target in the input video sequence, and to facilitate the subsequent research and analysis of the track and behavior of the tracking target. At present, researchers in the field of visual target tracking have proposed a series of excellent algorithms and frameworks. However, in view of the problems of deformation, occlusion, illumination change and random motion in the process of target tracking, it is still a great challenge to ensure the real-time, accuracy and robustness of tracking algorithms. In recent years, with the excellent performance of depth neural network in many tasks, the fusion of depth features based on relevant filtering algorithms to achieve target tracking tasks has become a hot research topic. In this paper, an improved target tracking algorithm is proposed based on the framework of classical target tracking methods: (1) Integrating deeper ResNet-101 deep convolution neural network model to detect target features more accurately. (2) Improve the model training method to save the network training cost. Finally, the performance of the proposed tracking algorithm is tested on the OTB target tracking standard dataset, and compared with other mainstream algorithms. The results show that the improved method proposed in this paper can effectively improve the tracking effectiveness and robustness.
Construction of Hierarchical Detail Model of Energy Environment Based on the Integration of Automatic Information Association Technology in Virtual Reality
Authors: Zhang Zhiliang , Bing Liu
Published: January 2021

In this paper, the defects of the existing models in virtual reality, such as the excessively long pretreatment time, time consuming in update operations and so on, when dealing with the large-scale automatic information association technology are analyzed. And a kind of construction method for the hierarchical detail model of energy environment (hereinafter referred to as CHDM for short) based on the integration of automatic information association technology is put forward. In this method, the information is aggregated in virtual reality to establish the hierarchical detail model of energy environment. Then the geometric parameters and form features are integrated to calculate the hierarchical details of each volume element. The topology connection relationship of the hierarchical detail model of energy environment is used to form a “Hierarchical detail model of energy environment”, which is merged and simplified in virtual reality. The experimental results show that for the automatic association of information with a patch complexity of about 10M can improve the average rate of model establishment about 3 times on the premise of guaranteeing certain construction quality on the ordinary PC. And the pretreatment time is controlled within 7min.
Visual inspection method for inner wall of small hole based on internal reflection principle
Authors: Chen Xinyang , Chen Xin , Wei Jiasi , Cai Xiaoyu , Li Yuan
Published: January 2021

This paper introduces a new image acquisition scheme based on the principle of internal reflection for the inner wall of the small hole, and visually inspects small hole workpieces with an inner diameter of 2-10mm. The customized reflector is inserted into the small hole, and the internal wall image is displayed in the CCD industrial camera through the reflection of light, and then the subsequent image processing is performed. The feasibility of the scheme is verified by theoretical calculations, and the obtained inner wall image resolution can reach 10 μm, which has high practical value.
Optimization and improvement of software and theory comprehensive training
Authors: Yu Wenjun , Huang Yu , Hu Bin , Gao Junxiang
Published: January 2021

The rapid development of information science and the transformation of modern teaching concepts have made the teaching work more inclined to the cultivation of students’ practical ability. Comprehensive training is a teaching activity for the better application of students’ computer theory knowledge. The research and practice of practical teaching system, practical teaching content and practical teaching methods are particularly important in the teaching work of colleges and universities. Based on this, we have built and improved the core layer of the practical teaching system, namely the comprehensive training of software and theory.
Study on night transportation organization of high-speed rail express products
Authors: Ma Mingyao , Zhao Peng , Qiao Ke
Published: January 2021

Along with the rapid development of high-speed railway, high-speed railway express products gradually mature, the electronic commerce industry of high-speed rise in demand for goods, the implementation of the high-speed rail freight trains is imperative, but freight trains operation organization faces new challenges at night. In this paper, we study the freight trains, different types of high-speed rail transportation express product process, the purpose is to effectively reduce skylight influence on train operation organization and freight trains for passenger train interference, and improve transportation efficiency, increase freight trains, operation specification, create a good environment for the emu operation. Based on the characteristics of different types of high-speed rail express products, this paper puts forward suggestions on rationalizing the transport process of freight emu, so as to give full play to the transport capacity advantages of freight emu, which is conducive to the high-quality development of freight emu.
Dynamic Evaluation of Discrete Zoning over Time Using Spatial Big Data
Authors: Liu Chenyu , Liao Zhouxing
Published: January 2021

Zoning is widely used in land-use control and the criteria for a ‘good’ zoning scheme varies dramatically for different purposes of zoning. Studies during the past decades have presented many theoretical frameworks for the design and evaluation of zoning schemes designed for dynamic urban processes especially the housing market, but challenges remain. Therefore, this paper attempts to explore the robust zoning over time help derive boundaries that better fit with changing housing market. It starts with the preliminary introduction of the zoning and a review of spatial big data and existing studies on evaluating the suitability of zoning schemes over time. Three indicators are adopted to evaluate the current zoning framework. A new index called RHD that can evaluate zoning changing dynamics over time is proposed, followed by the discussion of the empirical findings of the impacts of the zoning on land supply and house prices in the territory. The proposed framework for evaluating zoning can benefit future studies of zoning regarding dynamic housing market in the world.
Hyperspectral anomaly detection method based on linear background removal
Authors: Du Huiting , Fan Yanguo , Xu Mingming
Published: January 2021

In view of the fact that the existing hyperspectral image anomaly detection algorithms only pay attention to distinguish between target and background by using spectral differences and ignore the correlation between pixels, and that local RX algorithm is easy to detect global non-anomalies as anomalies when the background is relatively complex, a hyperspectral anomaly detection method based on linear background removal is proposed. In this method, the edge information of hyperspectral image is obtained first, then the line part of edge image is extracted by Hough transform, and finally the local anomaly detection is carried out based on the linear background removal. By comparing the ROC curve and AUC value of this algorithm with RX algorithm and local RX algorithm, it shows that the algorithm of this paper can effectively reduce the false alarm rate of detection and has a better detection effect.
Automatic Text Summarization for Marine Natural Products Literature
Authors: Zhang Xukai , Liu Sue
Published: January 2021

Based on the Encoder-Decoder framework, an automatic summarization model MNPAS for marine natural products literature is proposed. Instead of directly using the structure of the common encoder in the past, a certain degree of innovation has been made to make Gru model complete the coding work. This advantage is that data information is not so easy to lose. In decoder, attention mechanism is integrated to improve the quality of predicted output word sequence. Compared with the traditional methods, the method proposed in this paper can complete the automatic generation of marine natural product literature abstracts better.
Design and implementation of partition Operating System based on ARINC653 standard
Authors: Tao Yongchao , Song Qilong , Piao Songhao
Published: January 2021

The ARINC series of standards are mainly used to define how to use the computing resources of avionics. The ARINC 653 standard applies to the service interface of the spacecraft’s integrated electronic operating system to the upper-layer application software. It isolates the application software from the underlying processor architecture and meets the requirements of the on-board real-time system with good scalability. This article will follow the ARINC 653 standard, design and implement a partition operating system, providing basic system static configuration capabilities, space partition capabilities, time sharing capabilities, inter-zone communication capabilities, and security monitoring capabilities
Design and Simulation of information processing system based on digital PCR
Authors: Shi Weizhan , Wang Junbo
Published: January 2021

In order to meet the demand of real-time data acquisition and analysis in the process of digital PCR detection, this paper proposes a high-speed data acquisition system and design scheme based on FPGA. The system uses FPGA as the signal acquisition platform, USB interface as the data transmission module, develops a set of real-time acquisition and processing software, and proposes a peak extraction algorithm based on Chebyshev inequality. The algorithm improves the peak detection accuracy, shortens the peak extraction time, and reduces the requirements for software and hardware. The system can monitor and analyze the data signal. It provides a reliable basis for the later data processing, and has strong engineering practice.
Research on Hybrid Real-Time System Scheduling Algorithm for Multiprocessor Environment
Authors: Cai Ren Pu Cuo , Hong JianChao
Published: January 2021

Firstly, the mixed key system task model of compatible with periodic tasks and sporadic tasks is studied. Based on the model compatible with these two tasks, a semi-divided real-time task scheduling mechanism is proposed. This process also considers the aggressive handling of Low critical task to improve resource utilization. Finally, the relevant program code is designed and developed, and the performance of the proposed algorithm is evaluated by means of simulation and simulation. The correctness of the model and theory is verified, and the theory and protocol design are further improved.