An integrated crop and hydrologic modeling system to estimate hydrologic impacts of crop irrigation demands

The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of the crop modeling system DSSAT. The irrigation demand from GriDSSAT is coupled to a regional hydrologic model (WaSSI). GriDSSAT and WaSSI are coupled through the USDA NASS CropScape data to provide crop acreages in each watershed. The crop model provides the dynamic irrigation demand which is a function of the weather. The hydrologic model responds to the weather and includes all other anthropogenic competing uses of water. Examples of the system include an analysis of the hydrologic impact of future expansion of irrigation and the real-time impact of short-term drought.     

不协调广义多尺度决策系统的局部最优尺度组合选择

针对不协调广义多尺度决策系统中每个对象事例的知识获取问题,文中提出局部最优尺度组合概念.首先,介绍广义多尺度决策系统中的尺度组合概念,给出在不同尺度组合下信息粒的表示及其相互关系.然后,在广义多尺度决策系统中,介绍不同尺度组合下集合的下近似与上近似概念及性质.最后,在不协调广义多尺度决策系统中定义7种局部最优尺度组合的概念,给出它们之间的相互关系,证明实际上只有5种不同的局部最优尺度组合概念.     

Comparison and evaluation of goal-oriented satisfaction analysis techniques

Goal-oriented requirements engineering (GORE) has been introduced as a means of modeling and understanding the motivations for system requirements. Using models to make goals explicit helps to avoid system failures due to implementing the wrong requirements or ignoring certain stakeholder needs. These models are unique when compared to other models used in system analysis in that their structure naturally lends itself to an analysis of goal satisfaction. Existing work claims that analysis using goal models can facilitate decision making over functional or design alternatives, using criteria in the model. Many different approaches to the analysis of goal-oriented requirements models have been proposed, including several procedures that analyze the satisfaction or denial of goals. These procedures make different choices in their interpretation of the goal model syntax, the methods to resolve conflicting or partial evidence, and in the way they represent satisfaction. This work uses three available tools implementing seven similar goal satisfaction analysis procedures to analyze three sample goal models. Results are reported and compared. The purpose of this comparison is to understand the ways in which procedural design choices affect analysis results, and how differences in analysis results could lead to different recommendations over alternatives in the model. Our comparison shows that different satisfaction analysis techniques for goal models can produce variable results, depending on the structure of the model. Comparison findings lead us to recommend the use of satisfaction analysis techniques for goal models as only heuristics for decision making. Our results emphasize investigation into the benefits of satisfaction analysis beyond decision making, namely improving model quality, increasing domain knowledge, and facilitating communication.     

Multi-product multi-market model for co-ordination of marketing and production decisions

A multi-product multi-market segment optimal control model for coordinating marketing and production decisions in a firm is presented. On the marketing side, the model considers pricing and the rate of advertising expenditure for each product for each market segment as decision (i.e. control) variables. On the production side, the production rate for an individual product is considered as a decision variable. The model assumes that demand for a product in each market segment is subject to seasonal and other exogenous effects. The model includes the following two special cases: (a) single-product multiple-market segments, (b) multiple products having purely exogenous, time-varying demand. The production planning subproblem in the model represents a class of partially singular optimal control problems. A solution procedure using Pontryagin's maximum principle is designed to solve the partially singular control problem. A hierarchical approach is then used in designing the solution procedure for the overall model.     

改进利益驱动神经网络在欺诈信息的应用研究

为了研究个体收益和代价实现总体净收益的最大化问题,提出了利益驱动的人工神经网络（ANN）分类方法。该方法引入了惩罚函数,根据实例不同的重要程度对不同实例的误分类给予可变惩罚,并在之后对净利益进行最大化处理。为了生成对个体的惩罚,参照每个实例的收益,通过改变函数值对误差平方和函数进行了修改,提出了七个不同版本的ANN模型。两个欺诈信息的实验结果表明,与原ANN、决策树和朴素贝叶斯分类器相比,所提模型的不同版本在净利润项上的性能优于其他方法,而且能够针对不同的数据集采用不同的权值生成方式。     

Centralized and distributed algorithms for on-line synthesis of maximal control policies under partial observation

This paper deals with the on-line control of partially observed discrete event systems (DES). The goal is to restrict the behavior of the system within a prefix-closed legal language while accounting for the presence ofuncontrollable andunobservable events. In the spirit of recent work on the on-line control of partially observed DES (Heymann and Lin 1994) and on variable lookahead control of fully observed DES (Ben Hadj-Alouane et al. 1994c), we propose an approach where, following each observable event, a control action is computed on-line using an algorithm oflinear worst-case complexity. This algorithm, calledVLP-PO, has the following additional properties: (i) the resulting behavior is guaranteed to be amaximal controllable and observable sublanguage of the legal language; (ii) different maximals may be generated by varying the priorities assigned to the controllable events, a parameter ofVLP-PO; (iii) a maximal containing the supremal controllable and normal sublanguage of the legal language can be generated by a proper selection of controllable event priorities; and (iv) no off-line calculations are necessary. We also present a parallel/distributed version of theVLP-PO algorithm calledDI-VLP-PO. This version uses several communicating agents that simultaneously run (on-line) identical versions of the algorithm but on possibly different parts of the system model and the legal language, according to the structural properties of the system and the specifications. While achieving the same behavior asVLO-PO, DI-VLP-PO runs at a total complexity (for computation and communication) that is significantly lower than its sequential counterpart.     

基于VPRS多变量决策树优化算法

噪声数据降低了多变量决策树的生成效率和模型质量,目前主要采用针对叶节点的剪枝策略来消除噪声数据的影响,而对决策树生成过程中的噪声干扰问题却没有给予关注。为改变这种状况,将基本粗糙集（rough set,RS）理论中相对核的概念推广到变精度粗糙集（variable precision roughset,VPRS）理论中,并利用其进行决策树初始变量选择;将两个等价关系相对泛化的概念推广为两个等价关系多数包含情况下的相对泛化,并利用其进行决策树初始属性检验;进而给出一种能够有效消除噪声数据干扰的多变量决策树构造算法。最后,采用实例验证了算法的有效性。     

Evaluating Optimized Decision Procedures for Propositional Modal K (m) Satisfiability

Heavily optimized decision procedures for propositional modal satisfiability are now becoming available. Two systems incorporating such procedures for modal K, DLP and KSATC, are tested on randomly generated CNF formulae with several sets of parameters, varying the maximum modal depth and ratio of propositional variable to modal subformulae. The results show some easy-hard-easy behavior, but there is as yet no sharp peak as in propositional satisfiability.     

Understanding the meaning of a shifted sky: a general framework on extending skyline query

Skyline queries are often used on data sets in multi-dimensional space for many decision-making applications. Traditionally, an object p is said to dominate another object q if, for all dimensions, it is no worse than q and is better on at least one dimension. Therefore, the skyline of a data set consists of all objects not dominated by any other object. To better cater to application requirements such as controlling the size of the skyline or handling data sets that are not well-structured, various works have been proposed to extend the definition of skyline based on variants of the dominance relationship. In view of the proliferation of variants, in this paper, a generalized framework is proposed to guide the extension of skyline query from conventional definition to different variants. Our framework explicitly and carefully examines the various properties that should be preserved in a variant of the dominance relationship so that: (1) maintaining original advantages, while extending adaptivity to application semantics, and (2) keeping computational complexity almost unaffected. We prove that traditional dominance is the only relationship satisfying all desirable properties, and present some new dominance relationships by relaxing some of the properties. These relationships are general enough for us to design new top-k skyline queries that return robust results of a controllable size. We analyze the existing skyline algorithms based on their minimum requirements on dominance properties. We also extend our analysis to data sets with missing values, and present extensive experimental results on the combinations of new dominance relationships and skyline algorithms.     

Regression and ratio estimators to integrate AVHRR and MSS data

Regression and ratio estimators are used to integrate AVHRR-GAC and Landsat MSS digital data to estimate forest area in the continental United States. Forestlands are enumerated for the 48 contiguous states using five different AVHRR-GAC data sets. The five GAC data sets tested, each with a spatial resolution of 4 km, were composed of different combinations of vegetation index and thermal data acquired over the nine month growing period in 1984. Twenty Landsat MSS scenes were selected countrywide and used to calibrate AVHRR forest estimates. Results indicated that the GAC and MSS forest estimates were not highly correlated; R² values ranged from 0.5 to 0.7. Although the ratio of means and linear regression corrections were, on the average, closer to national U.S. Forest Service forest area estimates, these correction procedures did not consistently improve GAC estimates of forest area. GAC forest area estimates tended to be high in densely forested regions such as the northeast and low in sparsely forested areas. This fact, and the low correlation coefficients, indicate that AVHRR data should be used for primary stratification (with MSS as the second stage) and not as an auxiliary variable in a regression correction procedure.     

Controllability of nonlinear time-varying systems: applications to spacecraft attitude control using magnetic actuation

Nonlinear controllability theory is applied to the time-varying attitude dynamics of a magnetically actuated spacecraft in a Keplerian orbit in the geomagnetic field. First, sufficient conditions for accessibility, strong accessibility and controllability of a general time-varying system are presented. These conditions involve application of Lie-algebraic rank conditions to the autonomous extended system obtained by augmenting the state of the original time-varying system by the time variable, and require the rank conditions to be checked only on the complement of a finite union of level sets of a finite number of smooth functions. At each point of each level set, it is sufficient to verify escape conditions involving Lie derivatives of the functions defining the level sets along linear combinations over smooth functions of vector fields in the accessibility algebra. These sufficient conditions are used to show that the attitude dynamics of a spacecraft actuated by three magnetic actuators and subjected to a general time-varying magnetic field are strongly accessible if the magnetic field and its time derivative are linearly independent at every instant. In addition, if the magnetic field is periodic in time, then the attitude dynamics of the spacecraft are controllable. These results are used to show that the attitude dynamics of a spacecraft actuated by three magnetic actuators in a closed Keplerian orbit in a nonrotating dipole approximation of the geomagnetic field are strongly accessible and controllable if the orbital plane does not coincide with the geomagnetic equatorial plane.     

A quantitative foundation for defining and manipulating deals to facilitate automated e-commerce

We propose a goal programming framework that aims at automating e-commerce transactions. This framework consists of three basic layers: deal definition—defining the deal’s parameters and associated constraints (e.g., item, price, delivery dates); deal manipulation—a collection of procedures for shaping deals to attain desired goals (e.g., earliest delivery and minimum price) and an applications layer that employs these procedures within some negotiations settings (e.g., an auction-related application presents a “better offer” while bidding on a contract). Our proposed foundation is rich enough to support a wide array of applications ranging from 1-1 and 1-n negotiations (auctions) to deal valuation and deal splitting. Whereas the techniques are appropriate to a multitude of settings, we shall mainly present them in the context of business-to-business (B2B) commerce where we see the greatest short term benefits. O. Shmueli’s work is partially supported by the Fund for the Promotion of Research at the Technion.     

Sensor control for multi-object state-space estimation using random finite sets

The problem addressed in this paper is information theoretic sensor control for recursive Bayesian multi-object state-space estimation using random finite sets. The proposed algorithm is formulated in the framework of partially observed Markov decision processes where the reward function associated with different sensor actions is computed via the Rényi or alpha divergence between the multi-object prior and the multi-object posterior densities. The proposed algorithm in implemented via the sequential Monte Carlo method. The paper then presents a case study where the problem is to localise an unknown number of sources using a controllable moving sensor which provides range-only detections. Four sensor control reward functions are compared in the study and the proposed scheme is found to perform the best.     

Resolution enhancement of integral‐imaging three‐dimensional display using directional elemental image projection

Abstract— A new approach to resolution enhancement of an integral‐imaging (II) three‐dimensional display using multi‐directional elemental images is proposed. The proposed method uses a special lens made up of nine pieces of a single Fresnel lens which are collected from different parts of the same lens. This composite lens is placed in front of the lens array such that it generates nine sets of directional elemental images to the lens array. These elemental images are overlapped on the lens array and produce nine point light sources per each elemental lens at different positions in the focal plane of the lens array. Nine sets of elemental images are projected by a high‐speed digital micromirror device and are tilted by a two‐dimensional scanning mirror system, maintaining the time‐multiplexing sequence for nine pieces of the composite lens. In this method, the concentration of the point light sources in the focal plane of the lens array is nine‐times higher, i.e., the distance between two adjacent point light sources is three times smaller than that for a conventional II display; hence, the resolution of three‐dimensional image is enhanced.     

On bilevel multi-follower decision making: General framework and solutions

Within the framework of any bilevel decision problem, a leader’s decision is influenced by the reaction of his or her follower. When multiple followers who may have had a share in decision variables, objectives and constraints are involved in a bilevel decision problem, the leader’s decision will be affected, not only by the reactions of these followers, but also by the relationships among these followers. This paper firstly identifies nine different kinds of relationships (S₁ to S₉) amongst followers by establishing a general framework for bilevel multi-follower decision problems. For each of the nine a corresponding bilevel multi-follower decision model is then developed. Also, this paper particularly proposes related theories focusing on an uncooperative decision problem (i.e., S₁ model), as this model is the most basic one for bilevel multi-follower decision problems over the nine kinds of relationships. Moreover, this paper extends the Kuhn-Tucker approach for driving an optimal solution from the uncooperative decision model. Finally, a real case study of a road network problem illustrates the application of the uncooperative bilevel decision model and the proposed extended Kuhn-Tucker approach.     

Rule induction for hierarchical attributes using a rough set for the selection of a green fleet

Rough set theory (RST) has been the subject of much study and numerous applications in many areas. However, most previous studies on rough sets have focused on finding rules where the decision attribute has a flat, rather than hierarchical structure. In practical applications, attributes are often organized hierarchically to represent general/specific meanings. This paper (1) determines the optimal decision attribute in a hierarchical level-search procedure, level by level, (2) merges the two stages, generating reducts and inducting decision rules, into a one-shot solution that reduces the need for memory space and the computational complexity and (3) uses a revised strength index to identify meaningful reducts and to improve their accuracy. The selection of a green fleet is used to validate the superiority of the proposed approach and its potential benefits to a decision-making process for transportation industry.     

A systematic evaluation of the concept of break-even analysis and risk: A computer based empirical study

It has been long understood that increasing profits are a justification for accepting increased risks. However, the development and presentation of the relationships between sales, variable expenses, fixed expenses and net income have received rather cursory and inadequate treatment in the finance literature in that the risk factor, although both readily available and measurable, is typically ignored. What the decision maker requires is not a series of observations concerning only a simple relationships, but a systematic development and exploration of the factors that affect these relations. The decision maker needs is a dynamic framework to examine the interrelationships of sales, variable costs, fixed costs and risk so that return (profits) can be maximized at an acceptable level of risk.

It has been shown that operating leverage is a good measure of operating risk. Specifically Lev (1) showed both at the analytical and empirical levels that as operating leverage increases (decreases), so does the overall and systematic volatility of the return on the firms stock. Using degree of operating leverage (DOL) as a surrogate for risk, this study sytematically explores and develops the impact the DOL on the break-even analysis and in turn evaluates the corollary role played by break-even analysis is influencing DOL.

The study establishes these relationships in a microcomputer and spreadsheet framework and develops a series of tabular and graphical tools for the decisions maker. The use of these tools clearly illustrates the effect of the risk factor on the break-even relationship and demonstrates that these relations are dramatically even though the investigation was simplified by assuming linear break-even analysis. The greatly increased sensitivity (in nonlinear terms) of profits to changes in the model clearly illustrate the necessity of including risk in an effort to optimize decisions. Although the decision maker may know intuitively that a business entity with increased operating leverage is far more vulnerable in learn years, the desire and/or necessity to increase profits through debt is always present. The model developed provides a framework that enables the decision maker to maximize profits at a given level of risk.

The study utilizes a series of numerical examples and illustrates results in both a tabular and graphical format. The analysis is performed within a spreadsheet format. A listing of the model is available.     

Evaluation of hyperspectral indices for LAI estimation and discrimination of potato crop under different irrigation treatments

In this study, various hyperspectral indices were evaluated for estimation of leaf area index (LAI) and crop discrimination under different irrigation treatments. The study was conducted for potato crop using the spectral reflectance values measured by a hand‐held spectro‐radiometer. Three categories of hyperspectral indices, such as ratio/difference indices, multivariate indices and derivative based indices were computed. It was found that, among various band combinations for NDVI (normalized difference vegetation index) and SAVI (soil adjusted vegetation index), the band combination of the 780～680, produced highest correlation coefficient with LAI. Among all the forms of LAI and VI empirical relationships, the power and exponential equations had highest R ² and F values. Analysis of variance showed that, hyperspectral indices were found to be more efficient than the LAI to detect the differences among crops under different irrigation treatments. The discriminant analysis produced a set of five most optimum bands to discriminate the crops under three irrigation treatments.     

Metalogical Frameworks II: Developing a Reflected Decision Procedure

Proving theorems is a creative act demanding new combinations of ideas and on occasion new methods of argument. For this reason, theorem proving systems need to be extensible. The provers should also remain correct under extension, so there must be a secure mechanism for doing this. The tactic-style provers pioneered by Edinburgh LCF provide a very effective way to achieve secure extensions, but in such systems, all new methods must be reduced to tactics. This is a drawback because there are other useful proof generating tools such as decision procedures; these include, for example, algorithms which reduce a deduction problem, such as arithmetic provability, to a computation on graphs.The Nuprl system pioneered the combination of fixed decision procedures with tactics, but the issue of securely adding new ones was not solved. In this paper we show how to safely include user- defined decision procedures in theorem provers. The idea is to prove properties of the procedure inside the prover's logic and then invoke a reflection rule to connect the procedure to the system. We also show that using a rich underlying logic permits an abstract account of the approach so that the results carry over to different implementations and other logics.