The Spanish Guerrilla 1808-1814 as a model for people’s wars and resistance movements

Transforming the meaning of the term 'guerrilla' which had once meant feud or private warfare, and then irregular war conducted by special forces on behalf of a state or government, the Spanish Guerrilla (part of the Peninsular War) against Napoleon became the model to be emulated by insurgency movements across the world. Even though the term itself continued to be used, even in Spanish, for special operations, in henceforth became imbued with an ideological dimension, which is how it would be used especially in the 20th century.

Multi-agent simulation of sawmill yard operations

This paper reports the findings of using multi-agent based simulation model to evaluate the sawmill yard operations within a large privately owned sawmill in Sweden, Bergkvist Insjön AB in the current case. Conventional working routines within sawmill yard threaten the overall efficiency and thereby limit the profit margin of sawmill. Deploying dynamic work routines within the sawmill yard is not readily feasible in real time, so discrete event simulation model has been investigated to be able to report optimal work order depending on the situations. Preliminary investigations indicate that the results achieved by simulation model are promising. It is expected that the results achieved in the current case will support Bergkvist-Insjön AB in making optimal decisions by deploying efficient work order in sawmill yard.

Testing the gravity p-median model empirically

Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

A Model of Normative Power

A power describes the ability of an agent to act in some way. While this notion of power is critical in the context of organisational dynamics, and has been studied by others in this light, it must be constrained so as to be useful in any practical application. In particular, we are concerned with how power may be used by agents to govern the imposition and management of norms, and how agents may dynamically assign norms to other agents within a multi-agent system. We approach the problem by defining a syntax and semantics for powers governing the creation, deletion, or modification of norms within a system, which we refer to as normative powers. We then extend this basic model to accommodate more general powers that can modify other powers within the system, and describe how agents playing certain roles are able to apply powers, changing the system’s norms, and also the powers themselves. We examine how the powers found within a system may change as the status of norms change, and show how standard norm modification operations — such as the derogation, annulment and modification of norms— may be represented within our system.

Reservoir Management For Flood And Drought Protection Using Infinite Horizon Model Predictive Control

Model Predictive Control (MPC) is a control method that solves in real time an optimal control problem over a finite horizon. The finiteness of the horizon is both the reason of MPC's success and its main limitation. In operational water resources management, MPC has been in fact successfully employed for controlling systems with a relatively short memory, such as canals, where the horizon length is not an issue. For reservoirs, which have generally a longer memory, MPC applications are presently limited to short term management only. Short term reservoir management can be effectively used to deal with fast process, such as floods, but it is not capable of looking sufficiently ahead to handle long term issues, such as drought. To overcome this limitation, we propose an Infinite Horizon MPC (IH-MPC) solution that is particularly suitable for reservoir management. We propose to structure the input signal by use of orthogonal basis functions, therefore reducing the optimization argument to a finite number of variables, and making the control problem solvable in a reasonable time. We applied this solution for the management of the Manantali Reservoir. Manantali is a yearly reservoir located in Mali, on the Senegal river, affecting water systems of Mali, Senegal, and Mauritania. The long term horizon offered by IH-MPC is necessary to deal with the strongly seasonal climate of the region.

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.

Structuring a startup's operations in an emerging market

The present work analyzes the establishment of a startup’s operations and the structuring all of the processes required to start up the business, launch the platform and keep it working. The thesis’ main focus can therefore be described as designing and structuring a startup’s operations in an emerging market before and during its global launch. Such business project aims to provide a successful case regarding the creation of a business and its launch into an emerging market, by illustrating a practical example on how to structure the business’ operations within a limited time frame. Moreover, this work will also perform a complete economic analysis of Brazil, thorough analyses of the industries the company is related to, as well as a competitive analysis of the market the venture operates in. Furthermore, an assessment of the venture’s business model and of its first six-month performance will also be included. The thesis’ ultimate goal lies in evaluating the company’s potential of success in the next few years, by highlighting its strengths and criticalities. On top of providing the company’s management with brilliant findings and forecasts about its own business, the present work will represent a reference and a practical roadmap for any entrepreneur willing to establish his operations in Brazil.

Comparative analysis between a CAD model design and physical models obtained by manufacturing additive technologies using optical scan

This article presents a detailed study of the application of different additive manufacturing technologies (sintering process, three-dimensional printing, extrusion and stereolithographic process), in the design process of a complex geometry model and its moving parts. The fabrication sequence was evaluated in terms of pre-processing conditions (model generation and model STL SLI), generation strategy and physical model post-processing operations. Dimensional verification of the obtained models was undertook by projecting structured light (optical scan), a relatively new technology of main importance for metrology and reverse engineering. Studies were done in certain manufacturing time and production costs, which allowed the definition of an more comprehensive evaluation matrix of additive technologies.

Modeling and analysis of artificial neural networks applied in operations research

Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Knowledge-based integrated production management model

Purpose - This paper aims to propose a model of production management that integrates knowledge management, as a third dimension, to the production and work dimensions and to identify factors that promote a favorable context for knowledge sharing and results achievement in the production operations shop floor environment.Design/methodology/approach - The model proposed is built from opportunities identified in the literature review.Findings - The factors in the model integrate its three main components: knowledge management, production organization and work organization, providing a representation of the dynamics of the workplace and shop floor environment.Practical implications - The proposed model and its factors allow managers to better understand and to improve the organization activities, because it integrates knowledge management with the production organization and work organization components of traditional models.Originality/value - Literature acknowledges the role of knowledge as competitive advantage, but it is still dealt in an implicit way within the traditional models of production management. This paper proposes a model and factors that provide a favorable context for tacit knowledge sharing and results achievement in the production operations shop floor environment. The model explicitly integrates knowledge management with traditional models' components.

Knowledge-based integrated Production Management Model applied to automotive companies

This paper aims to examine the relevance of a production management model, in the shop-floor operations environment, that integrates the dimensions of production organisation (lean and mass production), work organisation (enriched and semi-autonomous groups) and knowledge management. A theoretical model has been applied to automotive companies to verify model adherence. Each of those dimensions has been described by factors. Shop-floor personnel interviews were conducted to confirm the factors relevance to that company. Results have shown that the model represented the reality of those companies concerning the researched dimensions. The factors allow managers to promote a favourable context for knowledge sharing. © 2010 Inderscience Enterprises Ltd.

Strategies to model scheduling decisions to plan the soft drink production process

In this paper we present a mixed integer model that integrates lot sizing and lot scheduling decisions for the production planning of a soft drink company. The main contribution of the paper is to present a model that differ from others in the literature for the constraints related to the scheduling decisions. The proposed strategy is compared to other strategies presented in the literature.

A model for analysing data portal performance: The biodiversity case

Currently, many museums, botanic gardens and herbariums keep data of biological collections and using computational tools researchers digitalize and provide access to their data using data portals. The replication of databases in portals can be accomplished through the use of protocols and data schema. However, the implementation of this solution demands a large amount of time, concerning both the transfer of fragments of data and processing data within the portal. With the growth of data digitalization in institutions, this scenario tends to be increasingly exacerbated, making it hard to maintain the records updated on the portals. As an original contribution, this research proposes analysing the data replication process to evaluate the performance of portals. The Inter-American Biodiversity Information Network (IABIN) biodiversity data portal of pollinators was used as a study case, which supports both situations: conventional data replication of records of specimen occurrences and interactions between them. With the results of this research, it is possible to simulate a situation before its implementation, thus predicting the performance of replication operations. Additionally, these results may contribute to future improvements to this process, in order to decrease the time required to make the data available in portals. © Rinton Press.

An Analytical Model for Virtual Topology Reconfiguration in Optical Networks and A Case Study

An analytical model for Virtual Topology Reconfiguration (VTR) in optical networks is developed. It aims at the optical networks with a circuit-based data plane and an IPlike control plane. By identifying and analyzing the important factors impacting the network performance due to VTR operations on both planes, we can compare the benefits and penalties of different VTR algorithms and policies. The best VTR scenario can be adaptively chosen from a set of such algorithms and policies according to the real-time network situations. For this purpose, a cost model integrating all these factors is created to provide a comparison criterion independent of any specific VTR algorithm and policy. A case study based on simulation experiments is conducted to illustrate the application of our models.

Spatio-Temporal Event Model for Cyber-Physical Systems

The emerging Cyber-Physical Systems (CPSs) are envisioned to integrate computation, communication and control with the physical world. Therefore, CPS requires close interactions between the cyber and physical worlds both in time and space. These interactions are usually governed by events, which occur in the physical world and should autonomously be reflected in the cyber-world, and actions, which are taken by the CPS as a result of detection of events and certain decision mechanisms. Both event detection and action decision operations should be performed accurately and timely to guarantee temporal and spatial correctness. This calls for a flexible architecture and task representation framework to analyze CP operations. In this paper, we explore the temporal and spatial properties of events, define a novel CPS architecture, and develop a layered spatiotemporal event model for CPS. The event is represented as a function of attribute-based, temporal, and spatial event conditions. Moreover, logical operators are used to combine different types of event conditions to capture composite events. To the best of our knowledge, this is the first event model that captures the heterogeneous characteristics of CPS for formal temporal and spatial analysis.