Features of Estimation of the Main Key Performance Indicators of Work of Production of Technological Type. II. The Features of the Estimates of Quantitative Manufacture Indicators

The ways of plant’s product and energy flows measurement are discussed. The algorithms of computing cumulative flowrates within the specified time interval and error estimation formulae are included.This article continues consideration of features of estimates of the main KPI of work of production of technological type. In the previous article [1] features of estimates of qualitative indexes of production products were described. Features of estimates of quantitative indices of the products are given in this article.     

Artifacts and Process

This article deals with the comparison between building architecture and software architecture. In software, cost estimation is extremely immature, and more accurate estimates can be obtained only by each iteration.     

An approximation of the activity duration distribution in PERT

PERT is widely used as a tool for managing large-scale projects. The traditional PERT approach uses the beta distribution as the distribution of activity duration and estimates the mean and the variance of activity duration based on the “pessimistic”, “optimistic” and “most likely” time estimates. Several authors have modified the original three point PERT estimators to improve the accuracy of the estimates. This article proposes new approximations for the mean and the variance of activity based on “pessimistic”, “optimistic” and “most likely” time estimates. By numerical comparison with actual values, the proposal is shown as more accurate than the original PERT estimates and its modifications. Another advantage of the proposed approximation is that it requires no assumptions about the parameters of the beta distribution as in the case of existing ones.Scope and purposeThe traditional PERT model uses beta distribution as the distribution of activity duration and estimates the mean and the variance of activity duration using “pessimistic”, “optimistic” and “most likely” time estimates proposed by an expert. In the past several authors have modified the original PERT estimators to improve the accuracy. This article proposes new approximations for the mean and the variance of activity duration which are more accurate than the original PERT estimates and their modifications. Another advantage of the proposal is that it is not based on any assumptions about the parameters of the beta distribution as in the case of the existing ones.     

一种基于插件与联动技术的复合安全网关

针对中小型企业对网络安全防护需要网关功能多样化的需求，提出了一种复合型安全网关的设计方法。功能模块建立在安全网关管理平台之上，使用插件技术开发和添加所需功能模块，方便功能模块的改进、删除和增加，而功能模块之间的工作以模块内部的联动技术进行相互通信，提高了整体效率。文章给出了一种复合网关管理平台的实现模型和在Linux下的应用，指出了插件技术和联动技术在复合型网关中的重要作用，给出了这种技术在分布式复合网关中的应用前景。     

An integrated classification scheme for mapping estimates and errors of estimation from the American Community Survey

Demographic and socio-economic information provided by the American Community Survey (ACS) have been increasingly relied upon in many planning and decision making contexts due to its timely and current estimates. However, ACS estimates are well known to be subject to larger sampling errors with a much smaller sample size compared with the decennial census data. To support the assessment of the reliability of ACS estimates, the US Census Bureau publishes a margin of error at the 90% confidence level alongside each estimate. While data error or uncertainty in ACS estimates has been widely acknowledged, little has been done to devise methods accounting for such error or uncertainty. This article focuses on addressing ACS data uncertainty issues in choropleth mapping, one of the most widely used methods to visually explore spatial distributions of demographic and socio-economic data. A new classification method is developed to explicitly integrate errors of estimation in the assessment of within-class variation and the associated groupings. The proposed method is applied to mapping the 2009–2013 ACS estimates of median household income at various scales. Results are compared with those generated using existing classification methods to demonstrate the effectiveness of the new classification scheme.     

Consistent recursive parameter estimation of partial differential equation models

This article introduces a new residual-based recursive parameter estimation algorithm for linear partial differential equations. The main idea is to replace the unmeasurable noise variables by estimates of the noise and to compute recursively both the model parameters and the noise estimates. It is proven that under some mild assumptions the estimated parameters converge to the true values with probability one. Numerical examples that demonstrate the effectiveness of the proposed approach are also provided.     

Case Based Imprecision Estimates for Bayes Classifiers with the Bayesian Bootstrap

This article outlines a Bayesian bootstrap method for case based imprecision estimates in Bayes classification. We argue that this approach is an important complement to methods such as k-fold cross validation that are based on overall error rates. It is shown how case based imprecision estimates may be used to improve Bayes classifiers under asymmetrical loss functions. In addition, other approaches to making use of case based imprecision estimates are discussed and illustrated on two real world data sets. Contrary to the common assumption, Bayesian bootstrap simulations indicate that the uncertainty associated with the output of a Bayes classifier is often far from normally distributed.     

How to Avoid Selecting Bids Based on Overoptimistic Cost Estimates

This article documents important connections between cost overruns and bidding. It also recommends how clients should design their bidding process to avoid selecting bids based on overoptimistic cost estimates. The recommendations provided reduce the risk of initiating projects that have unrealistic plans, time overruns, low software quality, high maintenance costs, and inflexible providers. Although this article aims to improve the clients' bidding processes, the authos believes that it also has important implications for software providers. They could use the reported results to identify bidding rounds that they're likely to win only if they provide a bid based on strongly overoptimistic cost estimates. Software providers should consider carefully whether it's worthwhile to participate in bidding rounds in which this is the case.     

Eliciting reliable uncertainty estimates

Abstract: Knowledge engineers often find that experts' estimates of uncertainty change from one day to the next and therefore often seem unreliable. This article explores the unreliability of probability estimates. Forty undergraduates answered 31 questions concerning the probability of daily events at two separate times. Three answer modalities were available: probability, chances and percent of the time. This paper finds that reliability decreases when answer modalities change from one time to the next. It is hypothesized that problem-solving approaches changed along with the modalities. The subjects represented a wide range in reliability, with the most reliable subjects changing answer modalities less than the unreliable subjects. These results suggest that knowledge engineers should endeavor to have experts express their uncertainty estimates using consistent modalities.     

State fusion with unknown correlation: Ellipsoidal intersection

This article focuses on the problem of fusing two prior Gaussian estimates into a single estimate, when the correlation is unknown. Existing solutions either lead to a conservative fusion result, as the chosen parametrization focuses on the fusion formulas instead of correlations, or they are computationally expensive. The contribution of this article is a novel parametrization, in which the correlation is explicitly characterized a priori to deriving the fusion formulas. Then, maximizing the correlation ensures that the fusion result is based on independent parts of the prior estimates and, simultaneously, addresses the fact that the correlation is unknown. In addition, a guaranteed improvement of the accuracy after fusion is attained. An illustrative example demonstrates the benefits of the proposed method compared to an existing fusion method.     

On the estimation of sliding domains and stability regions of variable structure control systems with bounded controllers

This article examines the problem of the control of a class of multivariable linear time-invariant uncertain dynamic systems with bounded controllers using the variable structure control (VSC) approach and the second method of Lyapunov. A special coordinate transformation is utilized to facilitate the analysis. Sliding domains and estimates of the domain of attraction along with the regions of asymptotic stability (RAS) are obtained with the aid of Lyapunov-type arguments. Numerical examples are given to illustrate the approach developed in the article.Dedicated to the memory of Professor Janislaw M. Skowronski     

Spectral methods on triangles and other domains

This article shows how to obtain multidimensional spectral methods as a warped product of one-dimensional spectral methods, thus generalizing direct (tensor) products. This generalization includes the fast Fourier transform. Applications are given for spectral approximation on a disk and on a triangle. The use of the disk spectral method for simulating the Navier-Stokes equations in a periodic pipe is detailed. The use of the triangle method in a spectral element scheme is discussed. The degree of approximation of the triangle method is computed in a new way, which favorably compares with the classical approximation estimates.     

Project estimation: a simple use-case-based model

Software development estimates are inaccurate and overly optimistic estimates are major contributors to project failure, despite the fact that every completed project is a rich source of information about performance and estimation. Modern development processes promote risk management, the realization of architecture first, the decomposition of the project into iterations, and the assignment of requirements to these iterations. When a project adopts these forms of best practice, it achieves a high degree of technical control and easier management. One difficult project management task is to accurately determine the effort required to complete the project. This article discusses a use-case-based estimation model for determining project effort. This technique calls for looking at the relationship between estimated and actual data to improve future estimates. Using a simple set of metrics, it is possible to generate a credible model for project estimation. The model described here works best in an iterative development process, allowing comparisons between successive iterations.     

Stability and approximator convergence in nonparametric nonlinearadaptive control

This paper investigates nonparametric nonlinear adaptive control under passive learning conditions. Passive learning refers to the normal situation in control applications in which the system inputs cannot be selected freely by the learning system. This article also analyzes the stability of both the system state and approximator parameter estimates. Stability results are presented for both parametric (known model structure with unknown parameters) and nonparametric (unknown model structure resulting in epsilon-approximation error) adaptive control applications. Upper bounds on the tracking error are developed. The article also analyzes the persistence (PE) of excitation conditions required for parameter convergence. In addition, to a general PE analysis, the article presents a specific analysis pertinent to approximators that are composed of basis elements with local support. In particular, the analysis shows that as long as a reduced dimension subvector of the regressor vector is PE, then a specialized form of exponential convergence will be achieved. This condition is critical, since the general PE conditions are not practical in most control applications. In addition to the PE results, this article explicitly defines the regions over which the approximator converges when locally supported basis elements are used. The results are demonstrated throughout via examples.     

Practical guidelines for expert-judgment-based software effort estimation

This article presents seven guidelines for producing realistic software development effort estimates. The guidelines derive from industrial experience and empirical studies. While many other guidelines exist for software effort estimation, these guidelines differ from them in three ways: 1) They base estimates on expert judgments rather than models. 2) They are easy to implement. 3) They use the most recent findings regarding judgment-based effort estimation. Estimating effort on the basis of expert judgment is the most common approach today, and the decision to use such processes instead of formal estimation models shouldn't be surprising. Simple process changes such as reframing questions can lead to more realistic estimates of software development efforts.     

Simultaneous estimation of benthic fractional cover and shallow water bathymetry in coral reef areas from high-resolution satellite images

This article describes the development of a technique to estimate shallow water benthic cover and depth simultaneously from high-resolution satellite images of reef areas, specifically from the high-resolution sensor onboard IKONOS. The technique to derive the estimates of five bottom benthic cover types (sand, coral, seagrass, macroalgae and pavement) and depth from the four-band images uses a coupling of radiative transfer (RT) theory and spectral unmixing implemented in an iterative manner. To resolve the cover types for the unmixing, the method employed a combinatorial approach to select benthic cover composition. The estimation technique was applied to two reef areas around the coast of the Ishigaki in southern Ryukyus, namely, the Fukido River mouth area and the Shiraho Reef. The IKONOS images of Fukido River mouth area and Shiraho Reef were acquired in 2003 and 2002, respectively. The accuracy of the fractional cover and the depth estimates from the satellite images are then presented and compared with sea truth data and depth measurements. The results indicate good correspondence between estimated and measured depths, while the estimates for the benthic cover were at reasonable levels of accuracy.     

Measuring architectural vulnerability factors

The continuous exponential growth in transistors per chip as described by Moore's law has spurred tremendous progress in the functionality and performance of semiconductor devices, particularly microprocessors. At the same time, each succeeding technology generation has introduced new obstacles to maintaining this growth rate. Transient faults caused by single-event upsets have emerged as a key challenge likely to gain significantly more importance in the next few design generations. Techniques for dealing with these faults exist, but they come at a cost. Designers need accurate soft-error estimates early in the design cycle to weigh the benefits of error protection techniques against their costs. This article presents a method for generating these estimates.     

Transitory image sequences, asymptotic properties, and estimationof motion and structure

A transitory image sequence is one in which no scene element is visible through the entire sequence. This article deals with some major theoretical and algorithmic issues associated with the task of estimating structure and motion from transitory image sequences. It is shown that integration with a transitory sequence has properties that are very different from those with a nontransitory one. Two representations, world-centered (WC) and camera-centered (CC), behave very differently with a transitory sequence. The asymptotic error rates derived in this article indicate that one representation is significantly superior to the other, depending on whether one needs camera-centered or world-centered estimates. We introduce an efficient “cross-frame” estimation technique for the CC representation. For the WC representation, our analysis indicates that a good technique should be based on camera global pose instead of interframe motions. Rigorous experiments were conducted with real-image sequences taken by a fully calibrated camera system     

Use of lidar data to simulate forest net primary production

A method has been recently presented to predict the net primary production (NPP) of Mediterranean forests by integrating conventional and remote-sensing data. This method was based on the use of two models, C-Fix and BIOME-BGC, whose outputs are combined with estimates of stem volume and tree age to predict the NPP of the examined ecosystems. This article investigates the possibility of deriving these two forest attributes from airborne high-resolution lidar data. The research was carried out in the San Rossore pine forest, a test site in Central Italy where several investigations have been conducted. First, estimates of stand stem volume and tree age were obtained from lidar data by application of a simplified method based on existing literature and a few ground measurements. The accuracy of these stand attributes was assessed by comparison with the independent ground data derived from a recent forest inventory. Next, the stem volume and tree age estimates were used to drive the NPP modelling strategy, whose outputs were evaluated against the inventory measurements of current annual increment (CAI). The simplified lidar data processing method produces stand stem volume and tree age estimates having moderate accuracy, which are useful to feed the modelling strategy and predict CAI at a stand level. This method's success raises the possibility of integrating ecosystem modelling techniques and lidar data for the simulation of net forest carbon fluxes.