912 resultados para automated planning
Resumo:
The publication of the Law 10,267 of 08/28/2001 changed the paradigm of rural registration in Brazil, because this law known as the "Law of Georeferencing" has created the National Registration of Rural Property, that unifies in a common basis different registrations present in several government agencies, such as the National Institute for Colonization and Agrarian Reform (INCRA), the Secretariat of Federal Revenue, the Brazilian Institute of Environment and Natural Resources, and the National Indian Foundation. Also, this new registration system has a graphical component which has not existed until such date, where the boundaries of rural property are georeferenced to the Brazilian Geodetic System. This new paradigm has resulted in a standardization of the survey and its representation of rural properties according to the Technical Standard for Georeferencing of Rural Properties, published by INCRA in compliance with the new legislation. Due to the georeferencing, the creation of a public GIS of free access on the Internet was possible. Among the difficulties found it may be observed the great Brazilian territory, the need for specialized professionals, and especially the certification process that INCRA has to perform for each georeferenced property. It is hoped that this last difficulty is solved with the implementation of the Land Management System that will allow automated and online certification, making the process more transparent, agile and fast.
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ABSTRACT The present study aims to present the main concepts of the sugarcane straw to energy planning. Throughout the study, the subject is contextualized highlighting broader aspects of sustainability, which is considered the main driver towards agro-energy modernization. Concerning sugarcane straw, we first evaluated its availability regarding technical and economic aspects, and then it summarized the straw production chain for energy supply purposes. As a proposal to support agro-energy planning, it is presented some spatial tools that have been barely used in the Brazilian energy planning context so far. Therefore, working on straw to electricity associated with supply chain basis, we developed a conceptual model to spatially assess this bioenergy system. Using the model proposed, it is described the whole supply chain at state level, which accounted the potential of a single mill to explore straw, as well as main costs associated with straw acquisition, investments on the straw recovery routes and electricity transmission. Bearing these concepts in mind, it is fully believed that spatial analysis can bring important information for agro-energy action plans.
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The growing importance of global sustainability issues has been causing many changes to the financial services industry. Facts such as climate change, social development and the financial crisis in 2008 have been making banks reconsider the manner that they consider environmental, social and economic factors in their decision-making process. At the same time, information technology (IT) has been transforming the financial service industry and its fast development has casted doubts on the way it should be managed within an organization. This current changing environment brings a number of uncertainties to the future that cannot be addressed using traditional forecasting techniques. This research investigates how IT can bring value to sustainability in the financial service industry in 2020. Through the use of a scenario planning technique, we analyzed how trends in the current environment (considering the relation between sustainability, financial institutions an IT) can lead to four different future scenarios. Then, we discussed how IT can improve a bank’s sustainability performance, considering the limitations of each scenario.
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Tumour cells differ from normal tissue cells in several important ways. These differences, like for example changed energy metabolism, result in altered microenvironment of malignant tumours. Non-invasive imaging of tumour microenvironment has been at the centre of intense research recently due to the important role that this changed environement plays in the development of malignant tumours and due to the role it plays in the treatment of these tumours. In this respect, perhaps the most important characteristics of the tumour microenvironment from this point of view are the lack of oxygen or hypoxia and changes in blood flow (BF). The purpose of this thesis was to investigate the processes of energy metabolism, BF and oxygenation in head and neck cancer and pancreatic tumours and to explore the possibilities of improving the methods for their quantification using positron emission tomography (PET). To this end [18F]EF5, a new PET tracer for detection of tumour hypoxia was investigated. Favourable uptake properties of the tracer were observed. In addition, it was established that the uptake of this tracer does not correlate with the uptake of existing tracers for the imaging of energy metabolism and BF, so the information about the presence of tissue hypoxia cannot therefore be obtained using tracers such as [18F]FDG or [15O]H2O. These results were complemented by the results of the follow-up study in which it was shown that the uptake of [18F]EF5 in head and neck tumours prior to treatment is also associated with the overall survival of the patients, indicating that tumour hypoxia is a negative prognostic factor and might be associated with therapeutic resistance. The influences of energy metabolism and BF on the survival of patients with pancreatic cancer were investigated in the second study. The results indicate that the best predictor of survival of patients with pancreatic cancer is the relationship between energy metabolism and BF. These results suggest that the cells with high metabolic activity in a hypoperfused tissue have the most aggressive phenotype.
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The importance of efficient supply chain management has increased due to globalization and the blurring of organizational boundaries. Various supply chain management technologies have been identified to drive organizational profitability and financial performance. Organizations have historically been concentrating heavily on the flow of goods and services, while less attention has been dedicated to the flow of money. While supply chains are becoming more transparent and automated, new opportunities for financial supply chain management have emerged through information technology solutions and comprehensive financial supply chain management strategies. This research concentrates on the end part of the purchasing process which is the handling of invoices. Efficient invoice processing can have an impact on organizations working capital management and thus provide companies with better readiness to face the challenges related to cash management. Leveraging a process mining solution the aim of this research was to examine the automated invoice handling process of four different organizations. The invoice data was collected from each organizations invoice processing system. The sample included all the invoices organizations had processed during the year 2012. The main objective was to find out whether e-invoices are faster to process in an automated invoice processing solution than scanned invoices (post entry into invoice processing solution). Other objectives included looking into the longest lead times between process steps and the impact of manual process steps on cycle time. Processing of invoices from maverick purchases was also examined. Based on the results of the research and previous literature on the subject, suggestions for improving the process were proposed. The results of the research indicate that scanned invoices were processed faster than e-invoices. This is mostly due to the more complex processing of e-invoices. It should be noted however that the manual tasks related to turning a paper invoice into electronic format through scanning are ignored in this research. The transitions with the longest lead times in the invoice handling process included both pre-automated steps as well as manual steps performed by humans. When the most common manual steps were examined in more detail, it was clear that these steps had a prolonging impact on the process. Regarding invoices from maverick purchases the evidence shows that these invoices were slower to process than invoices from purchases conducted through e-procurement systems and from preferred suppliers. Suggestions on how to improve the process included: increasing invoice matching, reducing of manual steps and leveraging of different value added services such as invoice validation service, mobile solutions and supply chain financing services. For companies that have already reaped all the process efficiencies the next step is to engage in collaborative financial supply chain management strategies that can benefit the whole supply chain.
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This paper presents an approach to the solution of moving a robot manipulator with minimum cost along a specified geometric path in the presence of obstacles. The main idea is to express obstacle avoidance in terms of the distances between potentially colliding parts. The optimal traveling time and the minimum mechanical energy of the actuators are considered together to build a multiobjective function. A simple numerical example involving a Cartesian manipulator arm with two-degree-of-freedom is described.
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Objective of this master’s thesis is to create an investment calculation model, which makes it possible to determine if the ski resort business can be profitable. The ultimate goal is to create a description with the help of theoretical knowledge, interviews and investment calculation model, how the operation of ski resort is possible to be profitable and what are the critical success factors for achieving this goal. Thesis is carried out as qualitative research, which is supported by the necessary constructive information utilizing calculations. The client company has provided valuable insights and material for this thesis. Theoretical report examines the steps of developing a business plan, investment components and methods as well as sensitivity analysis. The theoretical part is based on the articles, textbooks, interviews and researches. The empirical part of the thesis is assembled by benchmarking other same size Finnish ski resorts, conducting interviews and using investment calculation model. The empirical part provides comprehensive information about ski resort industry, the future of the project, the business plan and the profitability calculations. As the result of this thesis the investment calculation model, which makes it possible to simulate different scenarios for ski resort project, was formed. The model was used to create a picture in which kind of scenario the ski resort business would be profitable and what are the critical success factors in achieving this aim.
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Esitys KDK-käytettävyystyöryhmän järjestämässä seminaarissa: Miten käyttäjien toiveet haastavat metatietokäytäntöjämme? / How users' expectations challenge our metadata practices? 30.9.2014.
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Entrepreneurial marketing is newly established term and there is need for more specific studies in order to understand the concept fully. SMEs have entrepreneurial marketing elements more visible in their marketing and therefore provide more fruitful insights for this research. SMEs marketing has gained more recognition during the past years and in some cases innovative characteristics can be identified despite constraints such as lack of certain resources. The purpose of this research is to study entrepreneurial marketing characteristics and SME processes in order to wider understanding and gain more insights of entrepreneurial marketing. In addition, planning and implementation of entrepreneurial marketing processes is examined in order to gain full coverage of SMEs marketing activities. The research was conducted as a qualitative research and data gathering was based on semi-structured interview survey, which involved nine company interviews. Multiple case research was used to analyze data so that focus and clarity could be maintained in organized manner. Case companies were chosen from different business fields so that more variation and insights could be identified. The empirical results suggest that two examined processes networking and word-of-mouth communication are very important processes for case companies which supports the previous researches. However, the entrepreneurial marketing characteristics had variation some were more visible and recognizable than others. Examining more closely the processes companies did not fully understand that networking or word-of-mouth marketing could be used as efficiently as other conventional marketing methods.
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The objective of this project was to introduce a new software product to pulp industry, a new market for case company. An optimization based scheduling tool has been developed to allow pulp operations to better control their production processes and improve both production efficiency and stability. Both the work here and earlier research indicates that there is a potential for savings around 1-5%. All the supporting data is available today coming from distributed control systems, data historians and other existing sources. The pulp mill model together with the scheduler, allows what-if analyses of the impacts and timely feasibility of various external actions such as planned maintenance of any particular mill operation. The visibility gained from the model proves also to be a real benefit. The aim is to satisfy demand and gain extra profit, while achieving the required customer service level. Research effort has been put both in understanding the minimum features needed to satisfy the scheduling requirements in the industry and the overall existence of the market. A qualitative study was constructed to both identify competitive situation and the requirements vs. gaps on the market. It becomes clear that there is no such system on the marketplace today and also that there is room to improve target market overall process efficiency through such planning tool. This thesis also provides better overall understanding of the different processes in this particular industry for the case company.
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In the 2000’s Finland suffered from storms that caused long outages in electricity distribution, longest up to two weeks. These major disturbances increased the importance of supply security. In 2013 new Electricity Market Act was announced. It defined maximum duration for outages, 6 h for city plan areas and 36 h for other areas. The aim for this work is to determine required major disturbance proof level for a study area and find tools for prioritizing overhead lines for cabling renovation to improve supply security. Three prioritization methods were chosen to be studied: A: prioritization line sections by customer outage costs they cause, B: maximizing customers major disturbance proof network and C: minimizing excavation costs in medium voltage network. Profitability calculations showed that prioritization method A was the most profitable and C had the weakest profitability. The prioritization method C drove renovation into unreasonable locations in the study area in reliability point of view. Therefore universal rule prioritization methods couldn’t be made from the prioritization methods. This led to the conclusion that every renewing area need to be evaluated in a case by case basis.
Resumo:
The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.
Resumo:
With a Sales and Operations Planning (S&OP) process, a company aims to manage the demand and supply by planning and forecasting. The studied company uses an integrated S&OP process to improve the company's operations. The aim of this thesis is to develop this business process by finding the best possible way to manage the soft information in S&OP, whilst also understanding the importance and types (assumptions, risks and opportunities) of soft information in S&OP. The soft information in S&OP helps to refine future S&OP planning, taking into account the uncertainties that affect the balance of the long-term demand and supply (typically 12-18 months). The literature review was used to create a framework for soft information management process in S&OP. There were not found a concrete way how to manage soft information in the existing literature. In consequence of the poor literature available the Knowledge Management literature was used as the base for the framework creation, which was seen in the very same type of information management like the soft information management is. The framework created a four-stage process to manage soft information in S&OP that included also the required support systems. First phase is collecting and acquiring soft information in S&OP, which include also categorization. The categorization was the cornerstone to identify different requirements that needs to be taken into consideration when managing soft information in S&OP process. The next phase focus on storing data, which purpose is to ensure the soft information is managed in a common system (support system) in a way that the following phase makes it available to users in S&OP who need by help of sharing and applications process. The last phase target is to use the soft information to understand assumptions and thoughts of users behind the numbers in S&OP plans. With this soft management process the support system will have a key role. The support system, like S&OP tool, ensures that soft information is stored in the right places, kept up-to-date and relevancy. The soft information management process in S&OP strives to improve the relevant soft information documenting behind the S&OP plans into the S&OP support system. The process offers an opportunity to individuals to review, comment and evaluate soft information in S&OP made by their own or others. In the case company it was noticed that without a properly documented and distributed soft information in S&OP it was seen to cause mistrust towards the planning.
Resumo:
The aim of this thesis was to develop the category planning process in the case company operating in construction industry. As the interest in the field of research has just recently started to emerge towards the benefits of category management and planning, the theoretical background was derived from literature of subjects with a relation to category planning i.e. procurement strategy, purchasing portfolio model, information flow management and cost analysis. The background for the development of category planning process was derived from retail industry, to where the category planning is more researched. The empirical study was executed with mixed method approach: quantitative data of the categories was analyzed and qualitative data was gathered through semi-structured interview and discussions within the case company. As a result, the category planning process was critically analyzed and development proposals addressed for improving the process description. Additionally a tool was developed based on the empirical study to support the category planning process of the case company.
Resumo:
The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.