The Complexity of Non-Iterated Probabilistic Justification Logic

The logic PJ is a probabilistic logic defined by adding (noniterated) probability operators to the basic justification logic J. In this paper we establish upper and lower bounds for the complexity of the derivability problem in the logic PJ. The main result of the paper is that the complexity of the derivability problem in PJ remains the same as the complexity of the derivability problem in the underlying logic J, which is π[p/2] -complete. This implies that the probability operators do not increase the complexity of the logic, although they arguably enrich the expressiveness of the language.

Environmental policy and knowledge. Copying with complexity through inclusive management

Scholars agree that governance of the public environment entails cooperation between science, policy and society. This requires the active role of public managers as catalysts of knowledge co-production, addressing participatory arenas in relation to knowledge integration and social learning. This paper deals with the question of whether public managers acknowledge and take on this task. A survey accessing Directors of Environmental Offices (EOs) of 64 municipalities was carried out in parallel for two regions - Tuscany (Italy) and Porto Alegre Metropolitan Region (Brazil). The survey data were analysed using the multiple correspondence method. Results showed that, regarding policy practices, EOs do not play the role of knowledge co-production catalysts, since when making environmental decisions they only use technical knowledge. We conclude that there is a gap between theory and practice, and identify some factors that may hinder local environmental managers in acting as catalyst of knowledge co-production, raising a further question for future research.

Training project management complexity in postgraduate and continuing education programs: a learning strategy in the eshe (European Space of Higher Education) framework

The objective of this paper is to address the methodological process of a teaching strategy for training project management complexity in postgraduate programs. The proposal is made up of different methods —intuitive, comparative, deductive, case study, problem-solving Project-Based Learning— and different activities inside and outside the classroom. This integration of methods motivated the current use of the concept of “learning strategy”. The strategy has two phases: firstly, the integration of the competences —technical, behavioral and contextual—in real projects; and secondly, the learning activity was oriented in upper level of knowledge, the evaluating the complexity for projects management in real situations. Both the competences in the learning strategy and the Project Complexity Evaluation are based on the ICB of IPMA. The learning strategy is applied in an international Postgraduate Program —Erasmus Mundus Master of Science— with the participation of five Universities of the European Union. This master program is fruit of a cooperative experience from one Educative Innovation Group of the UPM -GIE-Project-, two Research Groups of the UPM and the collaboration with other external agents to the university. Some reflections on the experience and the main success factors in the learning strategy were presented in the paper

Training project management complexity in postgraduate and continuing education programs: a learning strategy in the eshe (European Space of Higher Education) framework

The objective of this paper is to address the methodological process of a teaching strategy for training project management complexity in postgraduate programs. The proposal is made up of different methods —intuitive, comparative, deductive, case study, problem-solving Project-Based Learning— and different activities inside and outside the classroom. This integration of methods motivated the current use of the concept of ―learning strategy‖. The strategy has two phases: firstly, the integration of the competences —technical, behavioral and contextual—in real projects; and secondly, the learning activity was oriented in upper level of knowledge, the evaluating the complexity for projects management in real situations. Both the competences in the learning strategy and the Project Complexity Evaluation are based on the ICB of IPMA. The learning strategy is applied in an international Postgraduate Program —Erasmus Mundus Master of Science— with the participation of five Universities of the European Union. This master program is fruit of a cooperative experience from one Educative Innovation Group of the UPM -GIE-Project-, two Research Groups of the UPM and the collaboration with other external agents to the university. Some reflections on the experience and the main success factors in the learning strategy were presented in the paper.

Influence of crude protein content, ingredient complexity, feed form, and duration of feeding of the phase I diets on productive performance and nutrient digestibility of Iberian pigs.

The influence of CP content and ingredient complexity, feed form, and duration of feeding of the Phase I diets on growth performance and total tract apparent digestibility -TTAD- of energy and nutrients was studied in Iberian pigs weaned at 28 d of age. There were 12 dietary treatments with 2 type of feeds -high-quality, HQ; and low-quality, LQ-, 2 feed forms -pellets vs. mash-, and 3 durations -7, 14, and 21 d- of supply of the Phase I diets.

Non uniform embedding based on relevance analysis with reduced computational complexity: application to the detection of pathologies from biosignal recordings

Nonlinear analysis tools for studying and characterizing the dynamics of physiological signals have gained popularity, mainly because tracking sudden alterations of the inherent complexity of biological processes might be an indicator of altered physiological states. Typically, in order to perform an analysis with such tools, the physiological variables that describe the biological process under study are used to reconstruct the underlying dynamics of the biological processes. For that goal, a procedure called time-delay or uniform embedding is usually employed. Nonetheless, there is evidence of its inability for dealing with non-stationary signals, as those recorded from many physiological processes. To handle with such a drawback, this paper evaluates the utility of non-conventional time series reconstruction procedures based on non uniform embedding, applying them to automatic pattern recognition tasks. The paper compares a state of the art non uniform approach with a novel scheme which fuses embedding and feature selection at once, searching for better reconstructions of the dynamics of the system. Moreover, results are also compared with two classic uniform embedding techniques. Thus, the goal is comparing uniform and non uniform reconstruction techniques, including the one proposed in this work, for pattern recognition in biomedical signal processing tasks. Once the state space is reconstructed, the scheme followed characterizes with three classic nonlinear dynamic features (Largest Lyapunov Exponent, Correlation Dimension and Recurrence Period Density Entropy), while classification is carried out by means of a simple k-nn classifier. In order to test its generalization capabilities, the approach was tested with three different physiological databases (Speech Pathologies, Epilepsy and Heart Murmurs). In terms of the accuracy obtained to automatically detect the presence of pathologies, and for the three types of biosignals analyzed, the non uniform techniques used in this work lightly outperformed the results obtained using the uniform methods, suggesting their usefulness to characterize non-stationary biomedical signals in pattern recognition applications. On the other hand, in view of the results obtained and its low computational load, the proposed technique suggests its applicability for the applications under study.

Analysing the complexity of the model-based decision making processes within the industrial management context

PURPOSE The decision-making process plays a key role in organizations. Every decision-making process produces a final choice that may or may not prompt action. Recurrently, decision makers find themselves in the dichotomous question of following a traditional sequence decision-making process where the output of a decision is used as the input of the next stage of the decision, or following a joint decision-making approach where several decisions are taken simultaneously. The implication of the decision-making process will impact different players of the organization. The choice of the decision- making approach becomes difficult to find, even with the current literature and practitioners’ knowledge. The pursuit of better ways for making decisions has been a common goal for academics and practitioners. Management scientists use different techniques and approaches to improve different types of decisions. The purpose of this decision is to use the available resources as well as possible (data and techniques) to achieve the objectives of the organization. The developing and applying of models and concepts may be helpful to solve managerial problems faced every day in different companies. As a result of this research different decision models are presented to contribute to the body of knowledge of management science. The first models are focused on the manufacturing industry and the second part of the models on the health care industry. Despite these models being case specific, they serve the purpose of exemplifying that different approaches to the problems and could provide interesting results. Unfortunately, there is no universal recipe that could be applied to all the problems. Furthermore, the same model could deliver good results with certain data and bad results for other data. A framework to analyse the data before selecting the model to be used is presented and tested in the models developed to exemplify the ideas. METHODOLOGY As the first step of the research a systematic literature review on the joint decision is presented, as are the different opinions and suggestions of different scholars. For the next stage of the thesis, the decision-making process of more than 50 companies was analysed in companies from different sectors in the production planning area at the Job Shop level. The data was obtained using surveys and face-to-face interviews. The following part of the research into the decision-making process was held in two application fields that are highly relevant for our society; manufacturing and health care. The first step was to study the interactions and develop a mathematical model for the replenishment of the car assembly where the problem of “Vehicle routing problem and Inventory” were combined. The next step was to add the scheduling or car production (car sequencing) decision and use some metaheuristics such as ant colony and genetic algorithms to measure if the behaviour is kept up with different case size problems. A similar approach is presented in a production of semiconductors and aviation parts, where a hoist has to change from one station to another to deal with the work, and a jobs schedule has to be done. However, for this problem simulation was used for experimentation. In parallel, the scheduling of operating rooms was studied. Surgeries were allocated to surgeons and the scheduling of operating rooms was analysed. The first part of the research was done in a Teaching hospital, and for the second part the interaction of uncertainty was added. Once the previous problem had been analysed a general framework to characterize the instance was built. In the final chapter a general conclusion is presented. FINDINGS AND PRACTICAL IMPLICATIONS The first part of the contributions is an update of the decision-making literature review. Also an analysis of the possible savings resulting from a change in the decision process is made. Then, the results of the survey, which present a lack of consistency between what the managers believe and the reality of the integration of their decisions. In the next stage of the thesis, a contribution to the body of knowledge of the operation research, with the joint solution of the replenishment, sequencing and inventory problem in the assembly line is made, together with a parallel work with the operating rooms scheduling where different solutions approaches are presented. In addition to the contribution of the solving methods, with the use of different techniques, the main contribution is the framework that is proposed to pre-evaluate the problem before thinking of the techniques to solve it. However, there is no straightforward answer as to whether it is better to have joint or sequential solutions. Following the proposed framework with the evaluation of factors such as the flexibility of the answer, the number of actors, and the tightness of the data, give us important hints as to the most suitable direction to take to tackle the problem. RESEARCH LIMITATIONS AND AVENUES FOR FUTURE RESEARCH In the first part of the work it was really complicated to calculate the possible savings of different projects, since in many papers these quantities are not reported or the impact is based on non-quantifiable benefits. The other issue is the confidentiality of many projects where the data cannot be presented. For the car assembly line problem more computational power would allow us to solve bigger instances. For the operation research problem there was a lack of historical data to perform a parallel analysis in the teaching hospital. In order to keep testing the decision framework it is necessary to keep applying more case studies in order to generalize the results and make them more evident and less ambiguous. The health care field offers great opportunities since despite the recent awareness of the need to improve the decision-making process there are many opportunities to improve. Another big difference with the automotive industry is that the last improvements are not spread among all the actors. Therefore, in the future this research will focus more on the collaboration between academia and the health care sector.

Research-action Methodology between Computer Science and Educational Psychology: a Multidisciplinary Approach

Computer science studies possess a strong multidisciplinary aptitude since most graduates do their professional work outside of a computing environment, in close collaboration with professionals from many different areas. However, the training offered in computer science studies lacks that multidisciplinary factor, focusing more on purely technical aspects. In this paper we present a novel experience where computer studies and educational psychology find a common ground and realistic working through laboratory practices. Specifically, the work enables students of computer science education the development of diagnosis support systems, with artificial intelligence techniques, which could then be used for future educational psychologists. The applications developed by computer science students are the creation of a model for the diagnosis of pervasive developmental disorders (PDD), sometimes also commonly called the autism spectrum disorders (ASD). The complexity of this diagnosis, not only by the exclusive characteristics of every person who suffers from it, but also by the large numbers of variables involved in it, requires very strong and close interdisciplinary participation. This work demonstrates that it is possible to intervene in a curricular perspective, in the university, to promote the development of interpersonal skills. What can be shown, in this way, is a methodology for interdisciplinary practices design and a guide for monitoring and evaluation. The results are very encouraging since we obtained significant differences in academic achievement between students who attended a course using the new methodology and those who did not use it.

Temporal Control of Leaf Complexity by miRNA-Regulated Licensing of Protein Complexes

The tremendous diversity of leaf shapes has caught the attention of naturalists for centuries. In addition to interspecific and intraspecific differences, leaf morphologies may differ in single plants according to age, a phenomenon known as heteroblasty. In Arabidopsis thaliana, the progression from the juvenile to the adult phase is characterized by increased leaf serration. A similar trend is seen in species with more complex leaves, such as the A. thaliana relative Cardamine hirsuta, in which the number of leaflets per leaf increases with age. Although the genetic changes that led to the overall simpler leaf architecture in A. thaliana are increasingly well understood, less is known about the events underlying age-dependent changes within single plants, in either A. thaliana or C. hirsuta. Here, we describe a conserved miRNA transcription factor regulon responsible for an age-dependent increase in leaf complexity. In early leaves, miR319-targeted TCP transcription factors interfere with the function of miR164-dependent and miR164-independent CUC proteins, preventing the formation of serrations in A. thaliana and of leaflets in C. hirsuta. As plants age, accumulation of miR156-regulated SPLs acts as a timing cue that destabilizes TCP-CUC interactions. The destabilization licenses activation of CUC protein complexes and thereby the gradual increase of leaf complexity in the newly formed organs. These findings point to posttranslational interaction between unrelated miRNA-targeted transcription factors as a core feature of these regulatory circuits.

On the complexity of inferring join dependencies /

"UILU-ENG 79 1734."

On the complexity of edge labelings for trees /

"UILU-ENG 78 1740."

A study of concrete computational complexity /

"UIUCDCS-R-75-716"

Young children's understanding of oddity: reducing complexity by simple oddity and "most different" strategies

Children aged between 3 and 7 years were taught simple and dimension-abstracted oddity discrimination using learning-set training techniques, in which isomorphic problems with varying content were presented with verbal explanation and feedback. Following the training phase, simple oddity (SO), dimension-abstracted oddity with one or two irrelevant dimensions, and non-oddity (NO) tasks were presented (without feedback) to determine the basis of solution. Although dimension-abstracted oddity requires discrimination based on a stimulus that is different from the others, which are all the same as each other on the relevant dimension, this was not the major strategy. The data were more consistent with use of a simple oddity strategy by 3- to 4-year-olds, and a most different strategy by 6- to 7-year-olds. These strategies are interpreted as reducing task complexity. (C) 2002 Elsevier Science Inc. All rights reserved.

A low-complexity lattice-based low-PAR transmission scheme for DSL channels

This paper presents a new low-complexity multicarrier modulation (MCM) technique based on lattices which achieves a peak-to-average power ratio (PAR) as low as three. The scheme can be viewed as a drop in replacement for the discrete multitone (DMT) modulation of an asymmetric digital subscriber line modem. We show that the lattice-MCM retains many of the attractive features of sinusoidal-MCM, and does so with lower implementation complexity, O(N), compared with DMT, which requires O(N log N) operations. We also present techniques for narrowband interference rejection and power profiling. Simulation studies confirm that performance of the lattice-MCM is superior, even compared with recent techniques for PAR reduction in DMT.