Leadership in high-value services for manufacturers:advanced services and their impact on vertical integration

The debate about services-led competitive strategies continues to grow with much interest emerging around the differing practices between production and servitised operations. This paper contributes to this discussion byinvestigating the vertical integration practice (in particular the micro-vertical integration otherwise known as the supply chain position)of manufacturers who are successful in their adoption of servitization.Although these are preliminary findings from a longer-term research programme, through this technical note we seek to simultaneously contribute to the debate in the research community and offer guidance to practitioners exploring the consequences of servitization. Keyword: Servitization, Product-Service Systems, Through-life Services.

Experience of Development and Application of Expert Systems for Economic Macroparameters Forecasting and Operation

In this article there are considered problems of forecasting economical macroparameters, and in the first place, index of inflation. Concept of development of synthetical forecasting methods which use directly specified expert information as well as calculation result on the basis of objective economical and mathematical models for forecasting separate “slowly changeable parameters” are offered. This article discusses problems of macroparameters operation on the basis of analysis of received prognostic magnitude.

'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling'

Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems.

'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling'

Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems.

Nitrogen fertilization in common bean crops under no-tillage and conventional systems.

Nitrogen fertilization in common bean crops under no-tillage and conventional systems. Nitrogen fertilizer is necessary for high yields in common bean crops and N responses under conditions of no-tillage and conventional systems are still basic needs. Thus, the objective of this research was to evaluate the effect of N application and common bean yield in no-tillage and conventional systems. The experimental design was a randomized block in a factorial scheme (2x8+1) with four replications. The treatments were constituted by the combination of two N doses (40 and 80 kg ha(-1)) applied at side dressing at eight distinct stadia during vegetative development of the common bean (V(4-3), V(4-4), V(4-5), V(4-6), V(4-7), V(4-8), V(4-9) and V(4-10)), in addition to a control plot without N in side dressing. The experiment was conducted over two years (2002 and 2003) in no-tillage on millet crop residues and conventional plow system. It was concluded that N fertilizer at the V(4) stadium of common bean promotes similar seed yields in no-tillage and conventional systems. Yield differences between no-tillage and conventional systems are inconsistent in the same agricultural area.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Integration of risk management in occupational health and safety systems

Risk management can be considered as part of the Occupational Health and Safety System (OHS) of an organization and can be used to develop and implement the OHS policy and manage the associated risks. The success of the integration of risk management in OHS depends on both technical and human aspects. Thus, this paper presents and discusses the case of a company working in the area of solid waste treatment. This company was certified in 2009 with an Integrated Management Systems for Quality, Environment, Occupational Health and Safety. The evolution of accidents before and after the implementation of the integrated system was analysed and a questionnaire was used to capture the perceptions of the technicians on the risk management system. The analysis of the findings showed that the frequency of accidents increased since 2009 but the severity has been reduced. Several interrelated causes and consequences were analysed and discussed. Furthermore, the analysis of the opinions of the company’s technicians permitted to highlight some important aspects on the integration of risk management in the OHS system of the company. In line with this discussion some hypothesis have been formulated.

Application of wetland systems in the treatment of acid rock mine drainage

The presented work was conducted within the Dissertation / Internship, branch of Environmental Protection Technology, associated to the Master thesis in Chemical Engineering by the Instituto Superior de Engenharia do Porto and it was developed in the Aquatest a.s, headquartered in Prague, in Czech Republic. The ore mining exploitation in the Czech Republic began in the thirteenth century, and has been extended until the twentieth century, being now evident the consequences of the intensive extraction which includes contamination of soil and sub-soil by high concentrations of heavy metals. The mountain region of Zlaté Hory was chosen for the implementation of the remediation project, which consisted in the construction of three cells (tanks), the first to raise the pH, the second for the sedimentation of the formed precipitates and a third to increase the process efficiency in order to reduce high concentrations of metals, with special emphasis on iron, manganese and sulfates. This project was initiated in 2005, being pioneer in this country and is still ongoing due to the complex chemical and biological phenomenon’s inherent to the system. At the site where the project was implemented, there is a natural lagoon, thereby enabling a comparative study of the two systems (natural and artificial) regarding the efficiency of both in the reduction/ removal of the referred pollutants. The study aimed to assist and cooperate in the ongoing investigation at the company Aquatest, in terms of field work conducted in Zlaté Hory and in terms of research methodologies used in it. Thereby, it was carried out a survey and analysis of available data from 2005 to 2008, being complemented by the treatment of new data from 2009 to 2010. Moreover, a theoretical study of the chemical and biological processes that occurs in both systems was performed. Regarding the field work, an active participation in the collection and in situ sample analyzing of water and soil from the natural pond has been attained, with the supervision of Engineer, Irena Šupiková. Laboratory analysis of water and soil were carried out by laboratory technicians. It was found that the natural lagoon is more efficient in reducing iron and manganese, being obtained removal percentages of 100%. The artificial lagoon had a removal percentage of 90% and 33% for iron and manganese respectively. Despite the minor efficiency of the constructed wetland, it must be pointed out that this system was designed for the treatment and consequent reduction of iron. In this context, it can conclude that the main goal has been achieved. In the case of sulphates, the removal optimization is yet a goal to be achieved not only in the Czech Republic but also in other places where this type of contamination persists. In fact, in the natural lagoon and in the constructed wetland, removal efficiencies of 45% and 7% were obtained respectively. It has been speculated that the water at the entrance of both systems has different sources. The analysis of the collected data shows at the entrance of the natural pond, a concentration of 4.6 mg/L of total iron, 14.6 mg/L of manganese and 951 mg/L of sulphates. In the artificial pond, the concentrations are 27.7 mg/L, 8.1 mg/L and 382 mg/L respectively for iron, manganese and sulphates. During 2010 the investigation has been expanded. The study of soil samples has started in order to observe and evaluate the contribution of bacteria in the removal of heavy metals being in its early phase. Summarizing, this technology has revealed to be an interesting solution, since in addition to substantially reduce the mentioned contaminants, mostly iron, it combines the low cost of implementation with an reduced maintenance, and it can also be installed in recreation parks, providing habitats for plants and birds.

Evolution of the application and database with aspects

Generally, the evolution process of applications has impact on their underlining data models, thus becoming a time-consuming problem for programmers and database administrators. In this paper we address this problem within an aspect-oriented approach, which is based on a meta-model for orthogonal persistent programming systems. Applying reflection techniques, our meta-model aims to be simpler than its competitors. Furthermore, it enables database multi-version schemas. We also discuss two case studies in order to demonstrate the advantages of our approach.

TV Recommendation and Personalization Systems: Integrating Broadcast and Video On-demand Services

he expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.

Towards high performance and multi-functional structural membranes using advanced fibrous and textile materials

Scientific and technological advancements in the area of fibrous and textile materials have greatly enhanced their application potential in several high-end technical and industrial sectors including construction, transportation, medical, sports, aerospace engineering, electronics and so on. Excellent performance accompanied by light-weight, mechanical flexibility, tailor-ability, design flexibility, easy fabrication and relatively lower cost are the driving forces towards wide applications of these materials. Cost-effective fabrication of various advanced and functional materials for structural parts, medical devices, sensors, energy harvesting devices, capacitors, batteries, and many others has been possible using fibrous and textile materials. Structural membranes are one of the innovative applications of textile structures and these novel building skins are becoming very popular due to flexible design aesthetics, durability, lightweight and cost benefits. Current demand on high performance and multi-functional materials in structural applications has motivated to go beyond the basic textile structures used for structural membranes and to use innovative textile materials. Structural membranes with self-cleaning, thermoregulation and energy harvesting capability (using solar cells) are examples of such recently developed multi-functional membranes. Besides these, there exist enormous opportunities to develop wide varieties of multi-functional membranes using functional textile materials. Additionally, it is also possible to further enhance the performance and functionalities of structural membranes using advanced fibrous architectures such as 2D, 3D, hybrid, multi-layer and so on. In this context, the present paper gives an overview of various advanced and functional fibrous and textile materials which have enormous application potential in structural membranes.

Preventive health care and payment systems to providers

Prevention has been a main issue of recent policy orientations in health care. This renews the interest on how different organizational designs and the definition of payment schemes to providers may affect the incentives to provide preventive health care. We present, both the normative and the positive analyses of the change from independent providers to integrated services. We show the evaluation of that change to depend on the particular way payment to providers is done. We focus on the externality resulting from referral decisions from primary to acute care providers. This makes our analysis complementary to most works in the literature allowing to address in a more direct way the issue of preventive health care.

Hard instances of algorithms and proof systems

"Vegeu el resum a l'inici del document del fitxer adjunt."

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Application and validation of a warning system for grapevine downy mildew controlusing fungicides

Most warning systems for plant disease control are based on Vinho, in Bento Gonçalves - RS, during the growing seasons 2000/ weather models dependent on the relationships between leaf wetness 01, 2002/03 and 2003/2004, using the grape cultivar Isabel. The duration and mean air temperature in this period considering the conventional system used by local growers was compared with the target disease intensity. For the development of a warning system to new warning system by using different cumulative daily disease severity control grapevine downy mildew, the equation generated by Lalancette values (CDDSV) as the criterion to schedule fungicide application and et al. (7) was used. This equation was employed to elaborate a critical reapplication. In experiments conducted in 2003/04, CDDSV of 12 - period table and program a computerized device, which records, though 14 showed promising to schedule the first spraying and the interval electronic sensors, leaf wetness duration, mean temperature in this between fungicide applications, reducing by 37.5% the number of period and automatically calculates the daily value of probability of applications and maintaining the same control efficiency in leaves infection occurrence. The system was validated at Embrapa Uva e and bunches, similarly to the conventional system.