Establishing dynamic thresholds for potato nitrogen status diagnosis with the SPAD chlorophyll meter

The hand-held soil plant analysis development （SPAD） chlorophyll meter nitrogen status of the potato and guiding fertilization recommendations N recommendation, it is critical to establish the threshold SPAD value has proved to be a promising tool in evaluating the n the process of N evaluation of potato plants and （SPAD reading）, below which nitrogen supplement is required. And taking convenient using into account, the threshold needs to be dynamic throughout the potato growing season so that the users can test their potato plants and make fertilization decision at any growing time of potato. To complete this goal, field experiments with different nitrogen supply levels were conducted in different sites in northern China from 2009 to 2011. The results showed that threshold SPAD values decrease as the growing season progresses for all cultivars and planting sites. By statistical analysis, the threshold regression models were established respectively as： y=-0.003χ2-0.0507χ＋58.213 （y, threshold SPAD value; χ, days after emergence） for the potato cultivar Kexin 1, and y=-0.003χ2＋0.017χ＋52.489 （y, threshold SPAD value; χ, days after emergence） for the cultivar Shepody, from which, the threshold SPAD value at any day after emergence can be calculated.

Dynamic threshold for SPWVD parameter estimation based on Otsu algorithm

Time-frequency-based methods are proven to be effective for parameter estimation of linear frequency modulation （LFM） signals. The smoothed pseudo Winger-Ville distribution （SPWVD） is used for the parameter estimation of multi-LFM signals, and a method of the SPWVD binarization by a dynamic threshold based on the Otsu algorithm is proposed. The proposed method is effective in the demand for the estimation of different parameters and the unknown signal-to-noise ratio （SNR） circumstance. The performance of this method is confirmed by numerical simulation.

An Improved Artificial Immune Algorithm with a Dynamic Threshold

An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antibody＇s fitness and setting the dynamic threshold value. Numerical experiments show that compared with the genetic algorithm and the originally real-valued coding artificial immune algorithm, the improved algorithm possesses high speed of convergence and good performance for preventing premature convergence.

Dynamic Threshold-Based Approach to Detect Low-Rate DDoS Attacks on Software-Defined Networking Controller

The emergence of a new network architecture,known as Software Defined Networking(SDN),in the last two decades has overcome some drawbacks of traditional networks in terms of performance,scalability,reliability,security,and network management.However,the SDN is vulnerable to security threats that target its controller,such as low-rate Distributed Denial of Service(DDoS)attacks,The low-rate DDoS attack is one of the most prevalent attacks that poses a severe threat to SDN network security because the controller is a vital architecture component.Therefore,there is an urgent need to propose a detection approach for this type of attack with a high detection rate and low false-positive rates.Thus,this paper proposes an approach to detect low-rate DDoS attacks on the SDN controller by adapting a dynamic threshold.The proposed approach has been evaluated using four simulation scenarios covering a combination of low-rate DDoS attacks against the SDN controller involving(i)a single host attack targeting a single victim;(ii)a single host attack targeting multiple victims;(iii)multiple hosts attack targeting a single victim;and(iv)multiple hosts attack targeting multiple victims.The proposed approach’s average detection rates are 96.65%,91.83%,96.17%,and 95.33%for the above scenarios,respectively;and its average false-positive rates are 3.33%,8.17%,3.83%,and 4.67%for similar scenarios,respectively.The comparison between the proposed approach and two existing approaches showed that it outperformed them in both categories.

Efficient Dynamic Threshold Group Signature Scheme Based on Elliptic Curve Cryptosystem

The short secret key characteristic of elliptic curve cryptosystem （ECC） are integrated with the （ t, n ） threshold method to create a practical threshold group signature scheme characterized by simultaneous signing. The scheme not only meets the requirements of anonymity and traceability of group signature but also can withstand Tseng and Wang＇s conspiracy attack. It allows the group manager to add new members and delete old members according to actual application, while the system parameters have a little change. Cryptanalysis result shows that the scheme is efficient and secure.

A dynamic condition-based maintenance optimization model for mission-oriented system based on inverse Gaussian degradation process

An effective maintenance policy optimization model can reduce maintenance cost and system operation risk. For mission-oriented systems, the degradation process changes dynamically and is monotonous and irreversible. Meanwhile, the risk of early failure is high. Therefore, this paper proposes a dynamic condition-based maintenance(CBM) optimization model for mission-oriented system based on inverse Gaussian(IG) degradation process. Firstly, the IG process with random drift coefficient is used to describe the degradation process and the relevant probability distributions are obtained. Secondly, the dynamic preventive maintenance threshold(DPMT) function is used to control the early failure risk of the mission-oriented system, and the influence of imperfect preventive maintenance(PM)on the degradation amount and degradation rate is analysed comprehensively. Thirdly, according to the mission availability requirement, the probability formulas of different types of renewal policies are obtained, and the CBM optimization model is constructed. Finally, a numerical example is presented to verify the proposed model. The comparison with the fixed PM threshold model and the sensitivity analysis show the effectiveness and application value of the optimization model.

Central Force Optimization with Gravity <0, Elitism, and Dynamic Threshold Optimization: An Antenna Application, 6-Element Yagi-Uda Arrays

This paper investigates the effect of adding three extensions to Central Force Optimization when it is used as the Global Search and Optimization method for the design and optimization of 6-elementYagi-Uda arrays. Those extensions are Negative Gravity, Elitism, and Dynamic Threshold Optimization. The basic CFO heuristic does not include any of these, but adding them substantially improves the algorithm’s performance. This paper extends the work reported in a previous paper that considered only negative gravity and which showed a significant performance improvement over a range of optimized arrays. Still better results are obtained by adding to the mix Elitism and DTO. An overall improvement in best fitness of 19.16% is achieved by doing so. While the work reported here was limited to the design/optimization of 6- element Yagis, the reasonable inference based on these data is that any antenna design/optimization problem, indeed any Global Search and Optimization problem, antenna or not, utilizing Central Force Optimization as the Global Search and Optimization engine will benefit by including all three extensions, probably substantially.

Fast Iterative Closest Point-Simultaneous Localization and Mapping(ICP-SLAM)with Rough Alignment and Narrowing-Scale Nearby Searching

Two deficiencies in traditional iterative closest pointsimultaneous localization and mapping( ICP-SLAM) usually result in poor real-time performance. On one hand, relative position between current scan frame and global map cannot be previously known. As a result, ICP algorithm will take much amount of iterations to reach convergence. On the other hand,establishment of correspondence is done by global searching, which requires enormous computational time. To overcome the two problems,a fast ICP-SLAM with rough alignment and narrowing-scale nearby searching is proposed. As for the decrease of iterative times,rough alignment based on initial pose matrix is proposed. In detail,initial pose matrix is obtained by micro-electro-mechanical system( MEMS) magnetometer and global landmarks. Then rough alignment will be applied between current scan frame and global map at the beginning of ICP algorithm with initial pose matrix. As for accelerating the establishment of correspondence, narrowingscale nearby searching with dynamic threshold is proposed,where match-points are found within a progressively constrictive range.Compared to traditional ICP-SLAM,the experimental results show that the amount of iteration for ICP algorithm to reach convergence reduces to 92. 34% and ICP algorithm runtime reduces to 98. 86% on average. In addition,computational cost is kept in a stable level due to the eliminating of the accumulation of computational consumption. Moreover,great improvement can also been achieved in SLAM quality and robustness.

Optimization of threshold for local spectrum sensing with energy detector

Spectrum sensing is the first step of cognitive radio （CR）. In this area, previous researches mostly consider distributed local nodes which are under identical channel conditions, hence uniform and fixed detection threshold is set with energy detector. However, the distributions of nodes in real environments are not quite the same. In this paper, the optimal threshold to minimize the total detection error over add＇itive white Gaussion noise （AWGN） channel is derived firstly. Then the dynamic threshold scheme is proposed to reduce the average total detection error. Simulations have shown that, with this scheme, sensing performance is improved.

High-emitter identification for heavy-duty vehicles by temporal optimization LSTM and an adaptive dynamic threshold

Heavy-duty diesel vehicles are important sources of urban nitrogen oxides(NOx)in actual applications for environmental compliance,emitting more than 80%of NOx and more than 90%of particulate matter(PM)in total vehicle emissions.The detection and control of heavy-duty diesel emissions are critical for protecting public health.Currently,vehicles on the road must be regularly tested,every six months or once a year,to filter out high-emission mobile sources at vehicle inspection stations.However,it is difficult to effectively screen high-emission vehicles in time with a long interval between annual inspections,and the fixed threshold cannot adapt to the dynamic changes of vehicle driving conditions.An on-board diagnostic device(OBD)is installed inside the vehicle and can record the vehicle’s emission data in real time.In this paper,we propose a temporal optimization long short-term memory(LSTM)and adaptive dynamic threshold approach to identify heavy-duty high-emitters by using OBD data,which can continuously track and record the emission status in real time.First,a temporal optimization LSTM emission prediction model is established to solve the attention bias discrepancy problem on time steps that is caused by the large number of OBD data streams in practice.Then,the concentration prediction error sequence is detected and distinguished from the anomalous emission contexts using flexible criteria,calculated by an adaptive dynamic threshold with changing driving conditions.Finally,a similarity metric strategy for the time series is introduced to correct some pseudo anomalous results.Experiments on three real OBD time-series emission datasets demonstrate that our method can achieve high accuracy anomalous emission identification.

Threshold dynamics of a cooperation-diffusion-advection model in open advective environments

This paper is concerned with a Lotka-Volterra cooperation-reaction-diffusion-advection model in open advective environments.It is found that there are two critical advection rates,which classify the dynamic behavior of this system into three different scenarios,namely,(i)both species go extinct;(ii)one species survives in the long run,the other goes extinct and(ii)both species can persistently survive.The theoretical results provide some interesting highlights in ecological protection in streams and rivers.

An Adaptive Threshold Dynamics Method for Three-Dimensional Wetting on Rough Surfaces

We propose an adaptive threshold dynamics method for wetting problems in three space dimensions.The method is based on solving a linear heat equation and a thresholding step in each iteration.The heat equation is discretized by a cell-centered finite volume method on an adaptively refined mesh.An efficient technique for volume conservation is developed on the nonuniform meshes based on a quick-sorting operation.By this method,we compute some interesting wetting problems on complicated surfaces.Numerical results verify some recent theory for the apparent contact angle on rough and chemically patterned surfaces.

Qualitative analysis of a reaction-diffusion SIRS epidemic model with nonlinear incidence rate and partial immunity

In this paper,a reaction-diffusion SIRS epidemic model with nonlinear incidence rate and partial immunity in a spatially heterogeneous environment is proposed.The well-posedness of the solution is firstly established.Then the basic reproduction number R0 is defined and a threshold dynamics is obtained.That is,when R_(0)<1,the disease-free steady state is locally stable,which implies that the disease is extinct,when R_(0)>1,the disease is permanent,and there exists at least one positive steady state solution.Finally,the asymptotic profiles of the positive steady state solution as individuals disperse at small and large rates are investigated.Furthermore,as an application of theoretical analysis,a numerical example involving the spread of influenza is discussed.Based on the numerical simulations,we find that the increase of transmission rate and spatial heterogeneity can enhance the risk of influenza propagation,and the increase of diffusion rate,saturation incidence for susceptible and recovery rate can reduce the risk of influenza propagation.Therefore,we propose to reduce the flow of people to lower the effect of spatial hetero-geneity,increase the transfer of infected individuals to hospitals in surrounding areas to increase the diffusion rate,and increase the construction of public medical resources to increase the recovery rate for controlling influenza propagation.

Climate policy uncertainty and corporate investment:evidence from the Chinese energy industry

In recent years,with the increasing attention paid to climate risks,the changes in climate policies are also more full of uncertainties,which have brought tremendous impact to economic entities,including companies.Using the dynamic threshold model,this study investigates the nonlinear and the asymmetric effect of climate policy uncertainty on Chinese firm investment decisions with panel data of 128 Chinese energy-related companies from 2007 to 2019.The empirical findings indicate that the influence of climate policy uncertainty on firm investment is significantly nonlinear.Overall,climate policy uncertainty is not apparently related to corporate investments in the high-level range,while it negatively affects the investments in the low-level range.In addition,to be more specific,the negative impact of climate policy uncertainty on the mining industry is tremendous,while the influence on the production and supply of electricity,heat,gas,and water sector is remarkably positive.The results of this study could help the company managers and policymakers to arrange appropriate related strategies under different climate policy conditions.

A novel SOI-DTMOS structure from circuit performance considerations

The performance of a partially depleted silicon-on-insulator （PDSO1） dynamic threshold MOSFET （DT- MOS） is degraded by the large body capacitance and body resistance. Increasing silicon film thickness can reduce the body resistance greatly, but the body capacitance also increases significantly at the same time. To solve this problem, a novel SOl DTMOSFET structure （drain/source-on-local-insulator structure） is proposed. From ISE simulation, the improvement in delay, obtained by optimizing p-n junction depth and silicon film thickness, is very significant. At the same time, we find that the drive current increases significantly as the thickness of the silicon film increases. Furthermore, only one additional mask is needed to form the local SIMOX, and other fabrication processes are fully compatible with conventional CMOS/SOI technology.

PDSOI DTMOS for analog and RF application

Based on the platform of 0.35μm PDSOI CMOS process technology, the partially depleted siliconon-insulator dynamic threshold voltage （PDSOI DT） NMOS with an H-gate was implemented. The analog characteristics and RF characteristics of the gate-body contacted dynamic threshold voltage H-gate NMOS and con- ventional H-gate NMOS were performed and compared. Furthermore, the fundamental operation principle and physical mechanism of the PDSOI H-gate DTMOS compared with the conventional H-gate NMOS are analyzed in detail. The results indicate that the cutoff frequency can reach 40 GHz and the maximum oscillation frequency 29.43 GHz as Vgs = 0.7 V and Vas = 1 V.

Breeding versus survival:proximate causes of abrupt population decline under environmental change in a desert rodent,the midday gerbil(Meriones meridianus)

Studying abrupt ecological shifts under gradual environmental change caused,in particular,by human activi­ty is important for understanding the fundamental aspects and underlying mechanisms of ecological resilience.One of the rare well-documented examples of an abrupt ecological shift is the delayed step transition of the population of a desert rodent,the midday gerbil(Meriones meridianus),from high-abundance(1994-2002)to low-abundance(2003-2017)regimes.This was in response to landscape transformation from desert to steppe caused by the drastic reduction of livestock in the rangelands of southern Russia after the collapse of the USSR in the early 1990s.In this study,we tested whether demographic parameters were correlated with the observed abrupt downward population shift.We found that reproductive activity(the percentage of breeding females,the number of litters,fecundity and the number of young recruited per female)showed no trend over time and did not differ between periods of high and low abundance.In contrast,the adult sex ratio(SR=males:females)de­creased significantly with time and was as much as twice more female-biased for the low-abundance population regime.However,SR was not related to any reproductive parameter,including the percentage of breeding fe­males.We conclude that proximate reasons for an abrupt population decline in M.meridianus are not associat­ed with the changes in breeding patterns or mate limitation caused by the Allee effect but relate to the increased mortality as a result of the desert landscape being fragmented by steppezation.The mortality is expected to be higher for males as the mobile and dispersing sex.

A semi-empirical analytic model for threshold voltage instability in MOSFETs with high-k gate stacks

A semi-empirical analytic model for the threshold voltage instability of a MOSFET is derived from Shockley-Read-Hall （SRH） statistics to account for the transient charging effects in a MOSFET high-k gate stack. Starting from the single energy level and single trap assumption, an analytical expression for the filled trap density in terms of dynamic time is derived from SRH statistics. The semi-empirical analytic model for the threshold voltage instability is developed based on MOSFET device physics between the threshold voltage and the induced trap density. The obtained model is also verified by extensive experimental data of trapping and de-trapping stress from different high-k gate configurations.

The BER performance optimization of ultra wideband TH-PPM in a multi-path environment

This paper is focuses on the unbalanced bit error rate(BER)for different transmitted data symbols of ultra wideband(UWB)impulse radio time-hopping pulse-posi-tion-modulation(TH-PPM)in a deterministic multi-path environment for unreasonable parameter selection.Two solutions are presented here.The first is that the decision threshold of RAKE is dynamic for different channel environments;the other is that we can improve the tra-ditional TH-PPM modulation,which is,encoding the trans-mitted data symbol with balance code.It is shown by theoretical analysis and computer simulation that these two methods can solve the unbalanced BER of traditional TH-PPM.Compared with the dynamic threshold method,the balance encoding scheme can be implemented more easily,and is more robust to the channel time variant char-acteristics,the channel estimation of RAKE receiver and the combination techniques.