带有预验证机制的区块链动态共识算法

委员会共识和混合共识通过选举委员会来代替全网节点完成区块验证,可有效加快共识速度,提高吞吐量,但恶意攻击和收买易导致委员会发生腐败问题,严重时将影响共识结果甚至造成系统瘫痪.现有工作虽引入信誉机制降低委员会节点腐败的可能性,但开销大、可信度低且无法降低腐败问题对系统的影响.提出一种带有预验证机制的区块链动态共识算法(DBCP),通过预验证机制在较小开销的前提下对委员会进行可靠的信誉评估,及时淘汰委员会中的恶意节点.若腐败问题已影响到共识结果,DBCP会通过动态共识将区块验证权转移到全网节点,并淘汰给出错误意见的委员会节点,避免系统瘫痪.若委员会通过迭代达到高可信状态,则DBCP会将区块验证权交由委员会,全网节点将认同委员会的共识结果,并不再对区块进行验证,进而加快共识速度.经实验验证,DBCP的吞吐量与比特币相比提升了两个数量级,且与Byzcoin相近,可在一个出块周期内快速应对委员会腐败问题,安全性优于Byzcoin.

台湾预拌混凝土验证推动成效与大陆星级评定制度探讨

混凝土为营建工程最大宗材料之一,然因为预拌混凝土特殊的产制特性与环境,使得预拌混凝土质量管理方式与需求,不同于其他营建材料。台湾地区的预拌混凝土市场量已趋近饱和,在供需失衡之清况下,预半场竞争激烈,导致买卖双方在质量上及履约上之争议层出不穷。为建立市场秩序,促成建筑商优先采用高质量预拌混凝土厂之产品,台湾营建研究院经多年规划,推动自愿性之「优质预拌混凝土(GRMC)验证」,召集具混凝土与ISO 9000验证专长之专家学者群,以第三者验证之公正客观立场与专业能力,结合ISO9000质量验证与CNS标准对预拌混凝土产制过程之各项技术要求,以查验各预拌混凝土厂生产符合CNS规范产品之能力,并经由后续追查与抽验结果之统计分析,协助验证厂商改善产制及品管上之盲点,进而促使预拌混凝质量之提升,经过10年的努力,台湾已有一定成效。大陆与台湾地缘相近,混凝土产业发展历程相似,虽然混凝土年产量高居世界第一,但市场却极端无序竞争,因此台湾的预拌厂验证制度可作为大陆推动星级评定制度之借镜,藉由两岸合作模式,引导预拌混凝土企业提高核心竞争力,共创双赢局面。

BIM技术在模板数据验证中的应用

以斯里兰卡电视塔项目为例,针对数据调整精度和安装定位精度是可调圆弧模板工程的难点,利用模板和结构外筒的BIM模型,对模板进行数据验证、模拟预拼接,对深化设计和现场施工提供有效支持。BIM验证方案无论是在数据准确性,数据验证的效率,还是对施工的辅助性上,都有明显优越性。

高性能微处理器TLB的优化设计

虚拟存储是现代微处理器系统必不可少的存储模式。在虚存模式下,虚拟地址到物理地址的变换是流水线中最频繁的核心服务,容易处于决定处理器时钟周期的关键路径上。为加快虚存的访问,现代高性能微处理器实现了一种硬件地址映射结构:转换后援缓冲器(简称TLB);在分析TLB传统的地址映射机制的基础上,提出了基于虚区域和Cache块标记的预验证技术,结果表明该技术优化了TLB的设计,避免了TLB访问时延成为访存的瓶颈。

移动IPSec VPN实现中的性能改进方法研究

随着移动通信业务的发展和普及,对移动通信安全的需求也越来越高。移动IPSec VPN是一种很好的移动安全接入方案。针对目前手机终端资源受限和移动网络按流量计费的现状,提出了一个改进方案,在保证通信过程安全性的同时,能改进移动IPSec VPN在隧道建立和数据传输过程中的性能。

IPSec中密钥交换协议IKE的安全性研究及改进

IKE协议的高效实现是IPSec的关键,在分析了IKE协议的基础上针对主模式交换下预共享密钥验证算法的不足,提出了抵御两种攻击的改进方案。

Discovery and validation of prognostic markers in gastric cancer by genome-wide expression profiling

AIM: To develop a prognostic gene set that can predict patient overall survival status based on the whole genome expression analysis. METHODS: Using Illumina HumanWG-6 BeadChip followed by semi-supervised analysis, we analyzed the expression of 47 296 transcripts in two batches of gastric cancer patients who underwent surgical resection. Thirty-nine samples in the first batch were used as the training set to discover candidate markers correlated to overall survival, and thirty-three samples in the second batch were used for validation. RESULTS: A panel of ten genes were identified as prognostic marker in the first batch samples and classified patients into a lowand a high-risk group with significantly different survival times (P = 0.000047). This prognostic marker was then verified in an independent validation sample batch (P = 0.0009). By comparing with the traditional Tumor-node-metastasis (TNM) staging system, this ten-gene prognostic marker showed consistent prognosis results. It was the only independent prognostic value by multivariate Cox regression analysis (P = 0.007). Interestingly, six of these ten genes are ribosomal proteins, suggesting a possible association between the deregulation of ribosome related gene expression and the poor prognosis. CONCLUSION: A ten-gene marker correlated with overall prognosis, including 6 ribosomal proteins, was identified and verified, which may complement the predictive value of TNM staging system.

IKE协议的安全性分析及其改进

IKE(internet key exchange)密钥交换协议的复杂性使得它存在着一些安全缺陷,本文通过分析主模式交换下预共享密钥算法的不足,提出了该模式下抵御DOS攻击的方法。

Computational prediction and experimental validation of novel markers for detection of STEC O157:H7

AIM:To identify and assess the novel makers for detection of Shiga toxin producing Escherichia coli (STEC) O157:H7 with an integrated computational and experimental approach. METHODS:High-throughput NCBI blast (E-value cutoff e-5) was used to search homologous genes among all sequenced prokaryotic genomes of each gene encoded in each of the three strains of STEC O157:H7 with complete genomes,aiming to find unique genes in O157:H7 as its potential markers. To ensure that the identified markers from the three strains of STEC O157:H7 can serve as general markers for all the STEC O157:H7 strains,a genomic barcode approach was used to select the markers to minimize the possibility of choosing a marker gene as part of a transposable element. Effectiveness of the markers predicted was then validated by running polymerase chain reaction (PCR) on 18 strains of O157:H7 with 5 additional genomes used as negative controls. RESULTS:The blast search identified 20,16 and 20 genes,respectively,in the three sequenced strains of STEC O157:H7,which had no homologs in any of the other prokaryotic genomes. Three genes,wzy,Z0372 and Z0344,common to the three gene lists,were selected based on the genomic barcode approach. PCR showed an identification accuracy of 100% on the 18 tested strains and the 5 controls. CONCLUSION:The three identified novel markers,wzy,Z0372 and Z0344,are highly promising for the detection of STEC O157:H7,in complementary to the known markers.

Validation of a method to predict hammer speed from cable force

Purpose： The purpose of this study was to develop and validate a method that would facilitate immediate feedback on linear hammer speed during training. Methods： Three-dimensional hammer head positional data were measured and used to calculate linear speed （calculated speed） and cable force. These data were used to develop two linear regression models （shifted and non-shifted） that would allow prediction of hammer speed from measured cable force data （predicted speed）. The accuracy of the two models was assessed by comparing the predicted and calculated speeds. Averages of the coefficient of multiple correlation （CMC） and the root mean square （RMS） of the difference between the predicted and calculated speeds for each throw of each participant were used to assess the level of accuracy of the predicted speeds. Results： Both regression models had high CMC values （0.96 and 0.97） and relatively low RMS values （1.27 m/s and 1.05 m/s） for the non-shifted and shifted models, respectively. In addition, the average percentage differences between the predicted and calculated speeds were 6.6% and 4.7% for the non-shifted and shifted models, respectively. The RMS differences between release speeds attained via the two regression models and those attained via three-dimensional positional data were also computed. The RMS differences between the predicted and calculated release speeds were 0.69 m/s and 0.46 m/s for the non-shifted and shifted models, respectively. Conclusion： This study successfully derived and validated a method that allows prediction of linear hammer speed from directly measured cable force data. Two linear regression models were developed and it was found that either model would be capable of predicting accurate speeds. However, data predicted using the shifted regression model were more accurate.

Lifetime prediction for tantalum capacitors with multiple degradation measures and particle swarm optimization based grey model

A lifetime prediction method for high-reliability tantalum （Ta） capacitors was proposed, based on multiple degradation measures and grey model （GM）. For analyzing performance degradation data, a two-parameter model based on GM was developed. In order to improve the prediction accuracy of the two-parameter model, parameter selection based on particle swarm optimization （PSO） was used. Then, the new PSO-GM（1, 2, co） optimization model was constructed, which was validated experimentally by conducting an accelerated testing on the Ta capacitors. The experiments were conducted at three different stress levels of 85, 120, and 145℃. The results of two experiments were used in estimating the parameters. And the reliability of the Ta capacitors was estimated at the same stress conditions of the third experiment. The results indicate that the proposed method is valid and accurate.

IEC 62059 Standards' Application in Reliability Prediction and Verification of Smart Meters

This article introduces the current situation of the smart then describes the relationship of meter reliability characteristics meter＇s reliability and the failure mechanisms at first, and combined with its Bathtub Curve. It also introduces both the feasible failure tree model for meter lifecycle prediction based on actual experiences and meter reliability prediction methodology by SN 29500 norms based on this model. This article also brings forward that it is necessary that the ＂Learning Factor＂ shall be adopted in meter reliability prediction for new materials, new process, and customized parts by referring to GJB/Z299C. Thereafter, this article also tries to apply IEC 62059 and JB/T 50070 to introduce the feasible method for the lifecycle prediction result verification by accelerated lifecycle test. Furthermore, the article also explores ways to increase the firmware reliability in smart meter.

Characterization of Water Production and Its Implication to Forest Management

Nowadays, forests are being managed for multiple uses. The basic requirement of multiple use forestry is to identify and quantify forest values and to determine management objectives. The priorities of management objectives, however, must be decided. In this study, a model predicting water production for multi-objective forest management was developed. The model was based on data from permanent sample plots. The data were gathered from 132 sample plots. Approximately 80% of the observations were used for model development and 20% for validation. The model was designed for even-aged forests, as well as for forests with mixed and pure species composition. The explicatory variable in the model was number of trees. All parameter estimates were found highly significant （P 〈 0.001） in predicting water production. The model fit and validation tests were fairly good. The water production model presented in this study was considered to have an appropriate level of reliability. planning, but, it should be limited to the conditions for which the data It can be used in the overall multi-objective forest management were gathered.

Analysis of the Bovespa Futures and Spot Indexes With High Frequency Data

Data from the World Federation of Exchanges show that Brazil＇s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariate forecasting models based on intraday data from the futures and spot markets of the BOVESPA index. The interest is to verify if there exist arbitrage opportunities in Brazilian financial market. To this end, three econometric forecasting models were built： ARFIMA, vector autoregressive （VAR）, and vector error correction （VEC）. Furthermore, it presents the results of a Granger causality test for the aforementioned series. This type of study shows that it is important to identify arbitrage opportunities in financial markets and, in particular, in the application of these models on data of this nature. In terms of the forecasts made with these models, VEC showed better results. The causality test shows that futures BOVESPA index Granger causes spot BOVESPA index. This result may indicate arbitrage opportunities in Brazil.

A Public Verifiable Identity Based Signcryption in the Random Oracle Model

Since Libert and Quisquater's identity based signcryption scheme cannot provide public verifiability after research, the paper proposes a new identity based signcryption scheme. The scheme uses quadratic residue and pairings over elliptic curves to realize public verifiability. By analysis the scheme is proved to be more efficient than Libert and Quisquater's scheme. Moreover, a security proof of the original scheme is presented in the random oracle model.

Provably Secure Self-Certified Signature Schemes with Message Recovery

To solve the key escrow problem of the identity-based cryptosystem, Girault introduced the notion of a self-certified public key, which not only eliminates the need to authenticate a public key but also solves the key escrow problerrL This paper proposes a Self-Certified Signature （SCS） scheme with message recovery and two variants without using bilinear pairings： one is the authenticated encryption scheme in which only the designated re- ceiver can verify the signature, and the other is the authenticated encryption scheme with message linkage that deals with large messages. These three SCS schemes are provably secure in the random oracle model and are more efficient than previous schemes .

Mechanistic Model for Predicting NO_3-N Uptake by Plants and Its Verification

Some mechanistic models have been proposed to predict the No3- concentrations in the soil solution at root surface and the NO3-N uptake by plants, but all these relatively effective non-steady state models have not yet been verified by any soil culture experiment. In the present study, a mathematical model based on the nutrient transport to the roots, root length and root uptake kinetics as well as taking account of the inter-root competition was used for calculation, and soil culture experiments with rice, wheat and rape plants grown on alkali, neutral and acid soils in rhizoboxes with nylon screen as a isolator were carried out to evaluate the prediction ability of the model through comparing the measured NO3-concentrations at root surface and N uptake with the calculated values. Whether the inter-root competition for nutrients was accounted for in the model was of less importance to the calculated N uptake but could induce significant changes in the relative concentrations of NO3- at root surface. For the three soils and crops, the measured NO3-N uptake agreed well with the calculated one, and the calculated relative concentrations at root surface were approximate to the measured values. But an appropriate rectification for some conditions is necessary when the plant uptake parameter obtained in solution culture experiment is applied to soil culture. In contrast with the present non-steady state model, the predicted relative concentrations, which show an accumulation, by the Phillips' steady-state model were distinct from the measured values which show a depletion, indicating that the present model has a better prediction ability than the steady-state model.

Performance Analysis of a Woodchip Downdraft Gasifier： Numerical Prediction and Experimental Validation

The study deals with a multi-faceted theoretical approach, symbolic, analytical and numerical, based on the chemical equilibrium assumption, addressed at predicting the performance trends of downdrafi wood-gasification processes so to assess the optimal ranges of input parameters, in particular the equivalence ratios, suitable to achieving the highest cold gas efficiencies whilst keeping the more the possible tar-free the produced bio-syngas. The time-steady, zero-dimensional model has been developed within MATLAB （the computing language and interactive environment from Matrix Laboratory） and solved by enforcing the constraints posed by the equilibrium constants in relation to two reactions, gas-water shift and methanation. Particular care is devoted toward verifying the real attainment of the equilibrium condition, as attested by an actual presence of products from the equilibrium reactions together with a zero difference AE between the energy flows entering and exiting the system, an issue often overlooked. With respect to other similar theoretical approaches, the numerical model, assisted by the symbolic counterpart for better interpretation and intrinsic validation of results, shows a distinct advantage in predicting rather accurately the syngas composition for varying gasification temperatures, as attested by cross comparisons with experimental data directly taken on an instrumented, dedicated, small-scale downdraft gasifier operational at DIME/SCL （the Savona Combustion Laboratory of DIME, the Dept. of Mechanical, Energy, Management and Transportation Engineering of Genova University）. The behavior of cold gas efficiency clearly points out that, from an energy conversion point of view, the optimal gasification temperatures turn out comprised between 900 ℃ and 1,000 ℃： this range is indeed characterized by the highest concentrations in the energy-rich syngas components CO and H2. For higher temperatures, as induced by higher air-to-fuel ratios, the progressive oxidation of above components, together with increasing nitrogen levels, would decrease the bio-syngas heat values.

Climate Change Projections for Mediterranean Region with Focus over Alpine Region and Italy

Climate change projections over the Mediterranean region have been elaborated by using the outputs of ten ENSEMBLES regional climate simulations with an horizontal resolution of 25 km under the SRES A1B emission scenario. The analysis concerns some surface atmospheric variables： mean sea level pressure, temperature, precipitation and wind speed. At first, model validations have been performed by comparing model results with E-OBS and ERA-Interim data in reproducing the last decades over some Italian sub-areas and the Alpine region. In spite of the considerable spread in the models＇ performances to represent the reference climate, a multi-model reconstruction has been computed and some seasonal climate change projections have been elaborated. About the mean climate changes, the more significant signals expected by 2050 are a maximum warming （about 2 ~C） and maximum drying （about 20%） in the southern Europe in summer. Moreover, the results indicate an increasing risk for some severe weather conditions： more days of extremely high temperature in summer over the whole area, a greater occurrence of flooding and storms over coasts during spring and autumn seasons and a more serious wet-snow event over Alpine region in winter. No significant signals of wind changes have been detected.

今天的摩尔定律

摩尔定律属于IT产业。