On Performance Characteristics of a Nonparametric Subset Selection Procedure with a Small Randomized Block Experimental Design

This article addresses the issue of computing the constant required to implement a specific nonparametric subset selection procedure based on ranks of data arising in a statistical randomized block experimental design. A model of three populations and two blocks is used to compute the probability distribution of the relevant statistic, the maximum of the population rank sums minus the rank sum of the “best” population. Calculations are done for populations following a normal distribution, and for populations following a bi-uniform distribution. The least favorable configuration in these cases is shown to arise when all three populations follow identical distributions. The bi-uniform distribution leads to an asymptotic counterexample to the conjecture that the least favorable configuration, i.e., that configuration minimizing the probability of a correct selection, occurs when all populations are identically distributed. These results are consistent with other large-scale simulation studies. All relevant computational R-codes are provided in appendices.

Comparison of Block Design Nonparametric Subset Selection Rules Based on Alternative Scoring Rules

This article compares the size of selected subsets using nonparametric subset selection rules with two different scoring rules for the observations. The scoring rules are based on the expected values of order statistics of the uniform distribution (yielding rank values) and of the normal distribution (yielding normal score values). The comparison is made using state motor vehicle traffic fatality rates, published in a 2016 article, with fifty-one states (including DC as a state) and over a nineteen-year period (1994 through 2012). The earlier study considered four block design selection rules—two for choosing a subset to contain the “best” population (i.e., state with lowest mean fatality rate) and two for the “worst” population (i.e., highest mean rate) with a probability of correct selection chosen to be 0.90. Two selection rules based on normal scores resulted in selected subset sizes substantially smaller than corresponding rules based on ranks (7 vs. 16 and 3 vs. 12). For two other selection rules, the subsets chosen were very close in size (within one). A comparison is also made using state homicide rates, published in a 2022 article, with fifty states and covering eight years. The results are qualitatively the same as those obtained with the motor vehicle traffic fatality rates.

Novel sensor selection strategy for LPI based on an improved IMMPF tracking method

Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent performance of the low probability of intercept（LPI）. In order to reduce the emission times of the radar, a novel sensor selection strategy based on an improved interacting multiple model particle filter（IMMPF） tracking method is presented. Firstly the IMMPF tracking method is improved by increasing the weight of the particle which is close to the system state and updating the model probability of every particle. Then a sensor selection approach for LPI takes use of both the target＇s maneuverability and the state＇s uncertainty to decide the radar＇s radiation time. The radar will work only when the target＇s maneuverability and the state＇s uncertainty exceed the control capability of the passive sensors. Tracking accuracy and LPI performance are demonstrated in the Monte Carlo simulations.

Performance Analysis of NOMA-Based Cooperative Networks with Relay Selection

Non-orthogonal multiple access(NOMA)technique is an expert on channel differences exploiting.In this paper,a dual-hop NOMA-based cooperative relaying network where a best relay is selected as an active node to accomplish the communication between a source and a destination is discussed.We assume that both decode-and-forward(DF)and amplify-and-forward(AF)protocols are applied to the selected relay.The metrics that ergodic sum-rate and outage probability are investigated,and the closed-form expressions of the latter for DF and AF protocols are derived.Numerical and simulation results are conducted to verify the validity of the theoretical analysis,in which we can see that the NOMA based DF relaying is better than the NOMA based AF relaying and other existing NOMA-based cooperative communication schemes.

Antenna Selection in Energy Harvesting Relaying Networks Using Q-Learning Algorithm

In this paper,a novel opportunistic scheduling(OS)scheme with antenna selection(AS)for the energy harvesting(EH)cooperative communication system where the relay can harvest energy from the source transmission is proposed.In this considered scheme,we take into both traditional mathematical analysis and reinforcement learning(RL)scenarios with the power splitting(PS)factor constraint.For the case of traditional mathematical analysis of a fixed-PS factor,we derive an exact closed-form expressions for the ergodic capacity and outage probability in general signal-to-noise ratio(SNR)regime.Then,we combine the optimal PS factor with performance metrics to achieve the optimal transmission performance.Subsequently,based on the optimized PS factor,a RL technique called as Q-learning(QL)algorithm is proposed to derive the optimal antenna selection strategy.To highlight the performance advantage of the proposed QL with training the received SNR at the destination,we also examine the scenario of QL scheme with training channel between the relay and the destination.The results illustrate that,the optimized scheme is always superior to the fixed-PS factor scheme.In addition,a better system parameter setting with QL significantly outperforms the traditional mathematical analysis scheme.

Adaptive Relay Selection Scheme for Minimization of the Transmission Time

As the installation of small cells increases,the use of relay also increases.The relay operates as a base station as well as just an amplifier.As the roles and types of relays become more diverse,appropriate relay selection technology is an effective way to improve communication performance.Many researches for relay selection have been studied to secure the reliability of relay communication.In this paper,the relay selection scheme is proposed for a cooperative system using decode-and-forward(DF)relaying scheme in the mobile communication system.To maintain the transmission rate,the proposed scheme classifies a candidate group considering the outage probability of multiple relays.For the applicable candidate group,the proposed scheme selects the relay considering the amount of data allocated to each user.Therefore,the proposed scheme defines the unit transmission time through each user’s data and relay capacity.Finally,the proposed scheme selects a relay that minimizes the total transmission time through the relay transmission time that calculates the unit transmission time for all users.With this adaptive relay selection scheme,an optimal relay can be assigned for each user.For the same transmission rate and the amount of data,the proposed scheme improves the performance of transmission time and reliability.Simulation results show that the proposed scheme reduces the total transmission time for the same amount of data and signal to noise ratio(SNR).

An Introduction to Transmit Antenna Selection in MIMO Wiretap Channels

This paper is a survey of transmit antenna selection-a low-complexity, energy-efficient method for improving physical layer security in multiple-input multiple-output wiretap channels. With this method, a single antenna out of multiple antennas is selected at the transmitter. We review a general analytical framework for analyzing exact and asymptotic secrecy of transmit antenna selection with receive maximal ratio combining, selection combining, or generalized selection combining. The analytical results prove that secrecy is significantly improved when the number of transmit antennas increases.

Transitions in a genotype selection model driven by coloured noises

This paper investigates a genotype selection model subjected to both a multiplicative coloured noise and an additive coloured noise with different correlation time τ1 and τ2 by means of the numerical technique. By directly simulating the Langevin Equation, the following results are obtained. （1） The multiplicative coloured noise dominates, however, the effect of the additive coloured noise is not neglected in the practical gene selection process. The selection rate μ decides that the selection is propitious to gene A haploid or gene B haploid. （2） The additive coloured noise intensity and the correlation time τ2 play opposite roles. It is noted that α and τ2 can not separate the single peak, while can make the peak disappear and ^-2 can make the peak be sharp. （3） The multiplicative coloured noise intensity D and the correlation time τ1 can induce phase transition, at the same time they play opposite roles and the reentrance phenomenon appears. In this case, it is easy to select one type haploid from the group with increasing D and decreasing τ1.

Performance Analysis of a Threshold-Based Relay Selection Algorithm in Wireless Networks

Relay selection is an effective method to realize the cooperative diversity gain in wireless networks. In this paper, we study a threshold-based single relay selection algorithm. A reasonable threshold value is set at each relay node, and the first relay with the instantaneous channel gain larger than the threshold will be se-lected to cooperate with the source. The exact and closed form expression for its outage probability is de-rived over independent, non-identically distributed (i. n. i. d) Rayleigh channels. The complexity of the algo-rithm is also analyzed in detail. Simulation results are presented to verify our theoretical analysis.

Performance of Nth Worst Full-Duplex Relay Selection over Nakagami-M Fading Channels

The performance analysis of Nth worst relay selection for the full-duplex (FD) mode over Nakagami-m fading channels is studied. We assume the relay employs the amplify-and-forward (AF) protocol. The closed-form expres-sions for the outage performance in terms of the received signal-to-noise ratio cumulative distribution function are derived. In the high signal-to-noise ratio regime, asymptotic outage probability is also investigated. Based on these expressions, the effect of several important network parameters, i.e., the number of relays and the order of selected relay, as well as the quality of the relay links, source-relay links, relay-destination links, are analytically characterized. Finally, numerical results are provided to verify and illustrate our mathematical analysis.

Analysis of State Homicide Rates Using Statistical Ranking and Selection Procedures

Nonparametric and parametric subset selection procedures are used in the analysis of state homicide rates (SHRs), for the year 2005 and years 2014-2020, to identify subsets of states that contain the “best” (lowest SHR) and “worst” (highest SHR) rates with a prescribed probability. A new Bayesian model is developed and applied to the SHR data and the results are contrasted with those obtained with the subset selection procedures. All analyses are applied within the context of a two-way block design.

A DISTRIBUTED METHOD FOR RELAY SELECTION IN COOPERATIVE COGNITIVE RADIO NETWORKS

We analyze the performance of a fully decentralized relay-selection method for the re-lay-assisted Cognitive Radio(CR) systems.The method requires no explicit communication among relay,assumes no prior knowledge of geometry.In particular,we assume that the frequencies chosen by the relay-assisted CR network overlapped with an active primary link.The proposed relay-selection scheme decreases the outage probability by considering both the channel scenario and the interference to the primary link compared with the non-cooperative transmission.Benefits of cooperative diversity are increased with the increased number of relays.

A Failure Sample Selection Method Based on Failure Pervasion Intensity

The complex and uncertain relationship among failures was always ignored in failure sample selection based on traditional testability demonstration experimental method. A failure pervasion model is founded based on fuzzy probability Petri net (FPPN) which can depict the propagation and pervasion relation among failures,then failure pervasion intensity is defined,the process of failure pervasion was depicted based on k-step fault pervasion algorithm and the pervasion intensity was expressed by a value. The method of sample selection based on failure pervasion intensity and failure rate is introduced into the process of sample selection. The practical application shows that the sample set selected based on failure pervasion intensity and failure rate can represent the failure set adequately.

Transmission Probability of an Ultracold Three-Level Atom Through a Micromaser Cavity

The transmission probability of an ultracold cascade three-level atom through a micromaser cavity is calculated and analyzed. It is shown that the micromaser cavity can be used as a velocity selector for ultracold three-level atoms, and the velocity selectivity is better for three-level atoms than for two-level atoms.

Two Probability Plots of the Three-Parameter Lognormal Distribution

The two-parameter lognormal distribution is a variant of the normal distribution and the three-parameter lognormal distribution is an extension of the two-parameter lognormal distribution by introducing a location parameter. The Q-Q plot of the three-parameter lognormal distribution is widely used. To obtain the Q-Q plot one needs to iteratively try different values of the shape parameter and subjectively judge the linearity of the Q-Q plot. In this paper,a mathematical method was proposed to determine the value of the shape parameter so as to simplify the generation of the Q-Q plot. Then a new probability plot was proposed,which was more easily obtained and provided more accurate parameter estimates than the Q-Q plot. These are illustrated by three realworld examples.

Selecting a Component with Longer Mean Life Time in Bivariate Pareto Models

In any parallel system, selecting a component with longer mean lifetime is of interest to the researchers. Hanagal (1997) [1] discussed selection procedures for a two-component system with bivariate exponential (BVE) models. In this paper, the problem of selecting a better component with reference to its mean life time under bivariate Pareto (BVP) models is considered. Three selection procedures based on sample proportions, sample means and maximum likelihood estimators (MLE) are proposed. The probability of correct selection for the proposed procedures is evaluated through Monte Carlo simulation using normal approximation. The asymptotic relative efficiency (ARE) of the proposed procedures is presented to facilitate the evaluation of the performance of procedures.

Outage Probability of Composite Microscopic and Macroscopic Diversity over Correlated Shadowed Fading Channels

The outage probability of a composite microscopic and macroscopic diversity system is evaluated over correlated shadowed fading channels.The correlations on both a microlevel and macrolevel are taken into account for the evaluations.The expression of the desired outage probability is explicitly presented,and two evaluation approaches,i.e.a compact Gaussian-Hermite quadrature method and an effective iterative algorithm,are proposed.The accuracy and efficiency of the proposed approaches are analysed,and a guideline is provided for their application.By employing the proposed evaluation approaches,results and demonstrations are presented,which display the implied effects of the corresponding parameters on the system outage performance,and reveal the potential to facilitate the design and analysis of such composite diversity systems.

Secrecy Outage Probability Analysis Based on Cognitive Decode-and-Forward Relaying

Wireless communications have to face to several different security issues in practice due to the nature of broadcast.The information theory is well known to provide efficient approaches to address security issues in wireless communications,which attracts much attention in both industry and academia in recent years.In this paper,inspired by information theory,we study the outage probability of the opportunistic relay selection based on cognitive decode-and-forward relaying with the secrecy consideration.Specifically,the closed-form expression of the outage probability is proposed.Moreover,the asymptotic performance evaluation on the basis of the analytical results is investigated.The simulation results show that the relay selection can reduce the outage probability in accordance with our theoretical analysis.

On the Probability of Erasure for MIMO-OFDM

Detecting the presence of a valid signal is an important task of a telecommunication receiver.When the receiver is unable to detect the presence of a valid signal,due to noise and fading,it is referred to as an erasure.This work deals with the probability of erasure computation for orthogonal frequency division multiplexed(OFDM)signals used by multiple input multiple output(MIMO)systems.The theoretical results are validated by computer simulations.OFDM is widely used in present day wireless communication systems due to its ability to mitigate intersymbol interference(ISI)caused by frequency selective fading channels.MIMO systems offer the advantage of spatial multiplexing,resulting in increased bit-rate,which is the main requirement of the recent wireless standards like 5G and beyond.

大豆杂交育种组合规模与品种选育概率及亲本选用研究

为指导当前与今后的大豆杂交育种工作,以黑龙江省农业科学院佳木斯分院1952-2013年间杂交育种选用的有效亲本和配制的杂交组合及选育的新品种为研究对象,对116个有效亲本和5610个杂交组合及110个品种进行深入系统地研究与分析。结果表明,杂交组合配制规模以每年150~200个为宜,选育品种概率为1.96%;亲本选择要依据育种理论、育种目标和遗传背景;亲本选用原则要坚持高起点、要考虑亲本血缘关系与遗传基础、亲本配合力(一般配合力和特殊配合力)及目标性状遗传特点;亲本使用要确定核心亲本(骨干亲本)与改良亲本,要采用梯级杂交、连续改造或回交转育、定向改良或一母多父,集中围攻或采用多亲本杂交聚合育种。