Application of Fuzzy Variables for Systems of Management Decision Support

The following article describes an approach covering the variety of opinions and uncertainties of estimates within the chosen technique of decision support. Mathematical operations used for assessment of options are traced to operations of working with functions that are used for assessment of possible options of decision-making. Approach proposed could be used within any technique of decision support based on elementary mathematical operations. In this article the above-mentioned approach is described under analytical hierarchy process.

Memorandum - Report on operations of 1st Division against St. Mihiel Salient, 1918

A memorandum describing the days leading up to the Battle of Saint-Mihiel. The document describes 1. Statement of Operation, 2. Character of Terrain, 3. Initial Dispositions, 4. Suitability of Formations, 5. How such formations were, or could have been, best adapted to meet the changing conditions of combat and terrain, 6. Employment of Infantry Weapons, 7. Artillery Support, 8. Passage of Obstacles, 9. Passage of Lines, 10. Destruction of Opposition, 11. Fighting in Intermediate Zone, 12. Organization of Ground, 13. Liaison, 14. General Observations.

International construction and Brazilian contractors’ operations

The international construction market is very complex, and requires strong structure and strategy for companies wanting to operate overseas. This article investigates characteristics of international construction. The international operation of Brazilian contractors is explored via results from a qualitative study which was carried out using case studies. The case studies comprised ten big Brazilian contractors, six of which operate abroad. The study identified the patterns of international operation, the competitive advantages of these contractors, as well as the difficulties faced by them in the international construction market. Four of the contractors studied operate only in the domestic market. The study of these cases revealed both obstacles and motivations for future international operations. The study revealed that despite the existing competitive advantages, Brazilian contractors' presence in the international market is limited. The main reason for that is probably their main competitive disadvantage: the lack of financial support from the government.

Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules

Infrared polarization and intensity imagery provide complementary and discriminative information in image understanding and interpretation. In this paper, a novel fusion method is proposed by effectively merging the information with various combination rules. It makes use of both low-frequency and highfrequency images components from support value transform (SVT), and applies fuzzy logic in the combination process. Images (both infrared polarization and intensity images) to be fused are firstly decomposed into low-frequency component images and support value image sequences by the SVT. Then the low-frequency component images are combined using a fuzzy combination rule blending three sub-combination methods of (1) region feature maximum, (2) region feature weighting average, and (3) pixel value maximum; and the support value image sequences are merged using a fuzzy combination rule fusing two sub-combination methods of (1) pixel energy maximum and (2) region feature weighting. With the variables of two newly defined features, i.e. the low-frequency difference feature for low-frequency component images and the support-value difference feature for support value image sequences, trapezoidal membership functions are proposed and developed in tuning the fuzzy fusion process. Finally the fused image is obtained by inverse SVT operations. Experimental results of visual inspection and quantitative evaluation both indicate the superiority of the proposed method to its counterparts in image fusion of infrared polarization and intensity images.

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.

From Smart Meters To Smart Decisions: Web-Based Support For The Water Efficient Household

Smart water metering technologies for residential buildings offer, in principle, great opportunities for sustainable urban water management. However, much of this potential is as yet unrealized. Despite that several ICT solutions have already been deployed aiming at optimum operations on the water utilities side (e.g. real time control for water networks, dynamic pump scheduling etc.), little work has been done to date on the consumer side. This paper presents a web-based platform targeting primarily the household end user. The platform enables consumers to monitor, on a real-time basis, the water demand of their household, providing feedback not only on the total water consumption and relevant costs but also on the efficiency (or otherwise) of specific indoor and outdoor uses. Targeting the reduction of consumption, the provided feedback is combined with notifications about possible leakages\bursts, and customised suggestions to improve the efficiency of existing household uses. It also enables various comparisons, with past consumption or even with that of similar households, aiming to motivate further the householder to become an active player in the water efficiency challenge. The issue of enhancing the platform’s functionality with energy timeseries is also discussed in view of recent advances in smart metering and the concept of “smart cities”. The paper presents a prototype of this web-based application and critically discusses first testing results and insights. It also presents the way in which the platform communicates with central databases, at the water utility level. It is suggested that such developments are closing the gap between technology availability and usefulness to end users and could help both the uptake of smart metering and awareness raising leading, potentially, to significant reductions of urban water consumption. The work has received funding from the European Union FP7 Programme through the iWIDGET Project, under grant agreement no318272.

Artificial immune systems for classification of petroleum well drilling operations

This paper presents two approaches of Artificial Immune System for Pattern Recognition (CLONALG and Parallel AIRS2) to classify automatically the well drilling operation stages. The classification is carried out through the analysis of some mud-logging parameters. In order to validate the performance of AIS techniques, the results were compared with others classification methods: neural network, support vector machine and lazy learning.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Alignment of operations strategy: Exploring the marketing interface

Purpose - The purpose of this paper is to identify factors that can help managers to overcome barriers to alignment of operations strategy at the interface with marketing. Design/methodology/approach - This objective required the application of a procedure based on strategic consensus and a deeper analysis, such that the delimitation of the study in a single case was mandatory. The strategic processes of interfacing involve managerial attributes that are subject to the influence of human aspects and, therefore, the research method used a qualitative approach. The protocol design included the following data sources: interviews, document reviews and researcher observations. The categorisation was made based on the theoretical references, the frequency of observations, common responses and information from documents. Findings - The balance between intra-functional trade-offs, joint research on the competitive context, reflections on the understanding of customer needs and operational performance, and understanding of inter-functional trade-offs were the main factors verified. They effectively support decisions associated with interface processes and promotes the integration of these processes. They can generate inputs that enable managers to achieve an appropriate balance among alternatives in light of various trade-offs. Practical implications - These factors make possible new connections between strategic processes in the context of operations and marketing functions. The formations of these strategies are aligned through a better understanding of both threats and opportunities by means of a joint analysis of the competitive context. The presented findings can be used to develop a clear definition of strategic objectives of operations and a more appropriate treatment of market needs. Originality/value - The findings from the research can be considered as new elements for promoting alignment in the formation process of the operations strategy. Little research to date has examined the operations-marketing strategic interface of companies in the context of strategic consensus. © Emerald Group Publishing Limited.

Research on policies and institutions to support small and medium scale enterprise in the Caribbean: Trinidad adn Tobago report

The Government of Trinidad and Tobago continues to provide support to SMEs in order to enhance their international competitiveness. The increasing effects of globalization and the reality of several trade agreements require that local businesses attain and maintain a level of competitiveness which ensures their continued survival and growth. This report examines in detail the policy environment within which these enterprises operate. It also examines the role of the key implementing agencies such as the BDC and NEDCO for government’s policy on the sector and also the role of the respective line ministries. These organizations strive to deliver value added technical, financial and export promotion services to its clients on a subsidised basis. The services offered reflect five key business areas such as financing, training, technical assistance, trade assistance, business re-engineering, project management and export promotion. In the case of the BDC its services target six sectors: food and beverage, metal processing, leisure marine, including yachting, information and communication technology/electronics, printing and packaging and entertainment. These said sectors are identified by the government, on the basis of a study which was done by TIDCO, for the promotion of a cluster development strategy. In the case of NEDCO it targets the following sectors: art and craft, food and beverages, fashion and fashion accessories, culture and ecotourism, bed and breakfast operations, indigenous entertainment and light manufacturing.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Low-carbon operations and production: putting training in perspective

The purpose of this paper is mainly to show how training may support low-carbon operations and production management in a more sustainable organizational context. Design/methodology/approach – A conceptual framework to facilitate the integration between training and low-carbon operations and production is presented. Findings – To accomplish better training in a low-carbon organization, some steps should be followed. Challenges may occur, including the necessity of collaboration across the supply chain. Research limitations/implications – The proposed framework should be applied and improved based on the actual conditions in organizations.

Managing Large Data Sets Using Support Vector Machines

Hundreds of Terabytes of CMS (Compact Muon Solenoid) data are being accumulated for storage day by day at the University of Nebraska-Lincoln, which is one of the eight US CMS Tier-2 sites. Managing this data includes retaining useful CMS data sets and clearing storage space for newly arriving data by deleting less useful data sets. This is an important task that is currently being done manually and it requires a large amount of time. The overall objective of this study was to develop a methodology to help identify the data sets to be deleted when there is a requirement for storage space. CMS data is stored using HDFS (Hadoop Distributed File System). HDFS logs give information regarding file access operations. Hadoop MapReduce was used to feed information in these logs to Support Vector Machines (SVMs), a machine learning algorithm applicable to classification and regression which is used in this Thesis to develop a classifier. Time elapsed in data set classification by this method is dependent on the size of the input HDFS log file since the algorithmic complexities of Hadoop MapReduce algorithms here are O(n). The SVM methodology produces a list of data sets for deletion along with their respective sizes. This methodology was also compared with a heuristic called Retention Cost which was calculated using size of the data set and the time since its last access to help decide how useful a data set is. Accuracies of both were compared by calculating the percentage of data sets predicted for deletion which were accessed at a later instance of time. Our methodology using SVMs proved to be more accurate than using the Retention Cost heuristic. This methodology could be used to solve similar problems involving other large data sets.

Engineering geological data in support of municipal land use planning-a case study in Analandia, southeast Brazil

This paper presents a method for transforming the information of an engineering geological map into useful information for non-specialists involved in land-use planning. The method consists of classifying the engineering geological units in terms of land use capability and identifying the legal and the geologic restrictions that apply in the study area. Both informations are then superimposed over the land use and a conflict areas map is created. The analysis of these data leads to the identification of existing and forthcoming land use conflicts and enables the proposal of planning measures on a regional and local scale. The map for the regional planning was compiled at a 1:50,000 scale and encompasses the whole municipal land area where uses are mainly rural. The map for the local planning was compiled at a 1:10,000 scale and encompasses the urban area. Most of the classification and operations on maps used spatial analyst tools available in the Geographical Information System. The regional studies showed that the greater part of Analandia's territory presents appropriate land uses. The local-scale studies indicate that the majority of the densely occupied urban areas are in suitable land. Although the situation is in general positive, municipal policies should address the identified and expected land use conflicts, so that it can be further improved.

Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.