Abstract
The number of applications using machine vision and digital image processing techniques in the agricultural sector is increasing rapidly. These applications include land/aerial remote sensing of crops, detection and recognition of pathological stress conditions, shape and color characterization of fruits, among many other topics. In fact, quantification of the visual properties of horticultural products and plants can play an important role to improve and automate agricultural management tasks. In this paper, is described a plant leaf characterization system based on a personal computer. This system uses a digital scanner to acquire leaf images with a resolution of 150dpi. These images are afterwards processed in order to compute some leaf characteristic parameters, such as: leaf area and perimeter, existence of holes, width and length. With the implemented algorithms the errors between the measurements and the real values were typically less than +/-3% and +/-2.5% for the area and linear measurements, respectively. These tests and results were realized using sets of known size images and leaf images that were measured with the proposed system and with a commercial calibrated leaf area system LiCor from Delta-T Devices.

Abstract

Abstract
This paper presents some concepts related with the development of a "model generator" for simulating supply chain systems. Such concepts arise not only from the object point of view taken over this system, but also from our intention to synthesise the behaviour of such kind of systems in a more general form, in particular concerning the events and activities related with suppliers, factories, warehouses, retailers, and even the last customers, which in fact trigger the flow of materials and information on the chain. Unlike the static approaches usually used for strategic purposes, where parameters like the time of delivery or the average rate of material flow are held as inputs to the system, the ideas described here consider a dynamic representation of the supply chain in which those parameters are results of some detailed simulation process. what gives this approach the ability of modelling those systems starting from the less abstract point of view to a more abstract representation. The result is a more realistic picture of the dynamics involved. Due to this fact, this approach could be seen as being more directed to managers than to strategists. Nevertheless, the objective is also that the models can be used to simulate either short or long periods of time, revealing their usefulness also for strategic analysis. The basis of these ideas is to consider the flow of products, information and money between any elements in the chain as a general form of customer-supplier exchange activity, and also by treating each of those elements as inheriting from a single element which includes the basic behaviour (and resources) of a factory, warehouse and retailer. A description of such element will be made. explaining its structure and the associated fixed and variable costs of its various processes. As we will see, many parameters considered inputs to other modelling techniques will appear here as outputs. giving the analyst more interesting data with which it can measure the supply chain performance by means of any statistical methods.

Abstract

Abstract
In deregulated electrical systems, production schedule for power plants is the result of an auction process. In the Spanish case, this schedule includes two main concepts: energy production (to be actually produced) and secondary reserve (to maintain available). The generation company faces the problem of converting energy schedule into a power schedule, respecting the reserve schedule as well as technical constraints, and trying to accomplish different goals: to minimise the production costs, to obtain smooth shapes for the power schedules and to optimise eventual compensation in schedules. A weighted goal mixed integer programming model with a real-size application to deal with this problem is presented.

Abstract
Capacity analysis and planning plays a key role in the operational performance and levels of customer services of a company. Traditional capacity analysis and planning systems have become inadequate in the face of several emerging manufacturing paradigms. One such paradigm is the production in distributed enterprise networks, consisting of subsets of autonomous production units within supply chains working in a collaborative and coordinated way. In these distributed networks, capacity analysis and planning becomes a complex task, especially because it is performed in a heterogeneous environment where the performance of individual manufacturing sites and of the network as a whole should be simultaneously considered. Therefore, the use of information system solutions is desirable in order to support effective and efficient planning decisions. Nevertheless, it seems that there is a lack of a clear definition of the most important requirements that must be met by supporting solutions. This paper attempts to identify some general requirements of a decision support system to be used for capacity analysis and planning in enterprise networks. Adaptability of capacity models, computational efficiency, monitoring mechanisms, support for distributed order promising, and integration with other systems, are some important requirements identified.