Approximating Credal Network Inferences by Linear Programming

An algorithm for approximate credal network updating is presented. The problem in its general formulation is a multilinear optimization task, which can be linearized by an appropriate rule for fixing all the local models apart from those of a single variable. This simple idea can be iterated and quickly leads to very accurate inferences. The approach can also be specialized to classification with credal networks based on the maximality criterion. A complexity analysis for both the problem and the algorithm is reported together with numerical experiments, which confirm the good performance of the method. While the inner approximation produced by the algorithm gives rise to a classifier which might return a subset of the optimal class set, preliminary empirical results suggest that the accuracy of the optimal class set is seldom affected by the approximate probabilities

Think, code, succeed: The Programming Studio as a games-based collaboration:Paper published in the Proceedings of the Association for Teacher Education in Europe conference: Teacher Education through Partnerships and Collaborative Learning Communities, Glasgow, UK. ATEE, 2015

This paper investigates the profile of teachers in the island of Ireland who declared themselves willing to undertake professional development activities in programming, in particular to master programming by taking on-line courses involving the design of computer games. Using the Technology Acceptance Model (TAM), it compares scores for teachers “willing” to undertake the courses with scores for those who declined, and examines other differences between the groups of respondents. Findings reflect the perceived difficulties of programming and the current low status accorded to the subject in Ireland. The paper also reviews the use of games-based learning as a “hook” to engage learners in programming and discusses the role of gamification as a tool for motivating learners in an on-line course. The on-line course focusing on games design was met with enthusiasm, and there was general consensus that gamification was appropriate for motivating learners in structured courses such as those provided.

Teaching Programming - Understanding Lecture Capture YouTube Analytics

ABSTRACT
The proliferation in the use of video lecture capture in universities worldwide presents an opportunity to analyse video watching patterns in an attempt to quantify and qualify how students engage and learn with the videos. It also presents an opportunity to investigate if there are similar student learning patterns during the equivalent physical lecture. The goal of this action based research project was to capture and quantitatively analyse the viewing behaviours and patterns of a series of video lecture captures across several university Java programming modules. It sought to study if a quantitative analysis of viewing behaviours of Lecture Capture videos coupled with a qualitative evaluation from the students and lecturers could be correlated to provide generalised patterns that could then be used to understand the learning experience of students during videos and potentially face to face lectures and, thereby, present opportunities to reflectively enhance lecturer performance and the students’ overall learning experience. The report establishes a baseline understanding of the analytics of videos of several commonly used pedagogical teaching methods used in the delivery of programming courses. It reflects on possible concurrences within live lecture delivery with the potential to inform and improve lecturing performance.

The basic principles of uncertain information fusion. An organised review of merging rules in different representation frameworks.

We propose and advocate basic principles for the fusion of incomplete or uncertain information items, that should apply regardless of the formalism adopted for representing pieces of information coming from several sources. This formalism can be based on sets, logic, partial orders, possibility theory, belief functions or imprecise probabilities. We propose a general notion of information item representing incomplete or uncertain information about the values of an entity of interest. It is supposed to rank such values in terms of relative plausibility, and explicitly point out impossible values. Basic issues affecting the results of the fusion process, such as relative information content and consistency of information items, as well as their mutual consistency, are discussed. For each representation setting, we present fusion rules that obey our principles, and compare them to postulates specific to the representation proposed in the past. In the crudest (Boolean) representation setting (using a set of possible values), we show that the understanding of the set in terms of most plausible values, or in terms of non-impossible ones matters for choosing a relevant fusion rule. Especially, in the latter case our principles justify the method of maximal consistent subsets, while the former is related to the fusion of logical bases. Then we consider several formal settings for incomplete or uncertain information items, where our postulates are instantiated: plausibility orderings, qualitative and quantitative possibility distributions, belief functions and convex sets of probabilities. The aim of this paper is to provide a unified picture of fusion rules across various uncertainty representation settings.

Multilinear and Integer Programming for Markov Decision Processes with Imprecise Probabilities

Markov Decision Processes (MDPs) are extensively used to encode sequences of decisions with probabilistic effects. Markov Decision Processes with Imprecise Probabilities (MDPIPs) encode sequences of decisions whose effects are modeled using sets of probability distributions. In this paper we examine the computation of Γ-maximin policies for MDPIPs using multilinear and integer programming. We discuss the application of our algorithms to “factored” models and to a recent proposal, Markov Decision Processes with Set-valued Transitions (MDPSTs), that unifies the fields of probabilistic and “nondeterministic” planning in artificial intelligence research. 

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Convex Quadratic Programming Approach to the Maximum Matching Problem

The problem of determining a maximum matching or whether there exists a perfect matching, is very common in a large variety of applications and as been extensively studied in graph theory. In this paper we start to introduce a characterisation of a family of graphs for which its stability number is determined by convex quadratic programming. The main results connected with the recognition of this family of graphs are also introduced. It follows a necessary and sufficient condition which characterise a graph with a perfect matching and an algorithmic strategy, based on the determination of the stability number of line graphs, by convex quadratic programming, applied to the determination of a perfect matching. A numerical example for the recognition of graphs with a perfect matching is described. Finally, the above algorithmic strategy is extended to the determination of a maximum matching of an arbitrary graph and some related results are presented.

Lanthanide-organic frameworks for optical and catalytic applications

Este projecto de doutoramento tem como objetivo isolar e caracterizar sistematicamente novos polímeros de coordenação, no estado sólido. A presença de grupos rígidos possuindo, em particular, átomos de oxigénio e de azoto, deverá induzir interessantes propriedades fotoluminescentes (rendimentos quânticos e tempos de vida elevados, assim como vias de transferência de energia eficientes), que poderão permitir a utilização dos compostos poliméricos na produção de dispositivos funcionais. As diferentes abordagens sintéticas foram ajustadas para cada material e basearam-se, preferencialmente, nas sínteses hidrotérmicas e nas assistidas por radiação de microondas. A estrutura dos materiais foi elucidada a partir de métodos de difracção de raios X (de cristal único ou de pós) em conjunto com outras técnicas, tais como RMN de estado sólido, microscopia eletrónica, análises térmicas, espectroscopia vibracional e estudos de composição elementar. Os compostos microcristalinos foram sistematicamente estudados a fim de investigar outras propriedades além das de fotoluminescência. Alguns dos materiais revelaram multifuncionalidade apresentando simultaneamente tempos de vida na ordem dos milisegundos, elevados rendimentos quânticos e elevado desempenho como catalisadores heterogéneos. As propriedades magnéticas de um composto baseado em érbio foram igualmente estudadas, assim como as de adsorpção e permuta de solvente de uma estrutura porosa baseada em cério.

Metal-organic frameworks based on phosphonate linkers

During the last few decades, Metal-Organic Frameworks (MOFs), also known as Coordination Polymers, have attracted worldwide research attentions due to their incremented fascinating architectures and unique properties. These multidimensional materials have been potential applications in distinct areas: gas storage and separation, ion exchange, catalysis, magnetism, in optical sensors, among several others. The MOF research group at the University of Aveiro has prepared MOFs from the combination of phosphonate organic primary building units (PBUs) with, mainly, lanthanides. This thesis documents the last findings in this area involving the synthesis of multidimensional MOFs based on four di- or tripodal phosphonates ligands. The organic PBUs were designed and prepared by selecting and optimizing the best reaction conditions and synthetic routes. The self-assembly between phosphonate PBUs and rare-earths cations led to the formation of several 1D, 2D and 3D families of isotypical MOFs. The preparation of these materials was achieved by using distinct synthetic approaches: hydro(solvo)thermal, microwave- and ultrasound-assisted, one-pot and ionothermal synthesis. The selection of the organic PBUs showed to have an important role in the final architectures: while flexible phosphonate ligands afforded 1D, 2D and dense 3D structures, a large and rigid organic PBU isolated a porous 3D MOF. The crystal structure of these materials was successfully unveiled by powder or single-crystal X-ray diffraction. All multidimensional MOFs were characterized by standard solid-state techniques (FT-IR, electron microscopy (SEM and EDS), solid-state NMR, elemental and thermogravimetric analysis). Some MOF materials exhibited remarkable thermal stability and robustness up to ca. 400 ºC. The intrinsic properties of some MOFs were investigated. Photoluminescence studies revealed that the selected organic PBUs are suitable sensitizers of Tb3+ leading to the isolation of intense green-emitting materials. The suppression of the O−H quenchers by deuteration or dehydration processes improves substantially the photoluminescence of the optically-active Eu3+-based materials. Some MOF materials exhibited high heterogeneous catalytic activity and excellent regioselectivity in the ring-opening reaction of styrene oxide (PhEtO) with methanol (100% conversion of PhEtO at 55 ºC for 30 min). The porous MOF material was employed in gas separation processes. This compound showed the ability to separate propane over propylene. The ionexchanged form of this material (containing K+ cations into its network) exhibited higher affinity for CO2 being capable to separate acetylene over this environment non-friendly gas.

Polyhedral study of mixed integer sets arising from inventory problems

“Branch-and-cut” algorithm is one of the most efficient exact approaches to solve mixed integer programs. This algorithm combines the advantages of a pure branch-and-bound approach and cutting planes scheme. Branch-and-cut algorithm computes the linear programming relaxation of the problem at each node of the search tree which is improved by the use of cuts, i.e. by the inclusion of valid inequalities. It should be taken into account that selection of strongest cuts is crucial for their effective use in branch-and-cut algorithm. In this thesis, we focus on the derivation and use of cutting planes to solve general mixed integer problems, and in particular inventory problems combined with other problems such as distribution, supplier selection, vehicle routing, etc. In order to achieve this goal, we first consider substructures (relaxations) of such problems which are obtained by the coherent loss of information. The polyhedral structure of those simpler mixed integer sets is studied to derive strong valid inequalities. Finally those strong inequalities are included in the cutting plane algorithms to solve the general mixed integer problems. We study three mixed integer sets in this dissertation. The first two mixed integer sets arise as a subproblem of the lot-sizing with supplier selection, the network design and the vendor-managed inventory routing problems. These sets are variants of the well-known single node fixed-charge network set where a binary or integer variable is associated with the node. The third set occurs as a subproblem of mixed integer sets where incompatibility between binary variables is considered. We generate families of valid inequalities for those sets, identify classes of facet-defining inequalities, and discuss the separation problems associated with the inequalities. Then cutting plane frameworks are implemented to solve some mixed integer programs. Preliminary computational experiments are presented in this direction.

Post-synthetic modification of metal–organic frameworks

Post-synthetic modification (PSM) of metal-organic frameworks encompassing the chemical transformation of the linker present is a promising new route for engineering optical centres and tuning the light emission properties of materials, both in the visible and in the near infrared (NIR) spectral regions. Here, PSM of isoreticular metal-organic framework-3 (IRMOF-3) with ethyl oxalyl monochloride, ethyl acetoacetate, pentane-2,4-dione, 3-(2- hydroxyphenyl)-3-oxopropanal, 2-chloroacetic acid, glyoxylic acid, methyl vinyl ketone and diethyl (ethoxymethylene)malonate followed by chelation of trivalent lanthanide ions afforded intriguing near infrared (Nd3+) and visible (Eu3+, Tb3+) light emitters. IRMOF-3 was used as a case in point due to both its highly porous crystalline structure and the presence of non-coordinating amino groups on the benzenedicarboxylate (bdc) linker amenable to modification. The materials were characterised by elemental analysis, powder X-ray diffraction, optical, scanning and transmission electron microscopy, Fourier transform infrared spectroscopy, and liquid and solid-state nuclear magnetic resonance. The solid-state luminescence properties of Ln-modified-IRMOF-3 were investigated at room temperature. The presence of the bdc aromatic ring, β– diketonate and oxalate enhanced the Ln3+ sensitization via ligand-to-metal energy transfer (anthena effect). As far as photocalysis is concerned, we have synthesized metal−organic frameworks (Cr-MIL-125-AC, Ag-MIL-125-AC) by a green method (solid–vapors reactions). The resulting functionalized materials show a photocatalytic activity for methylene blue degradation up to 6.52 times larger than that of the commercial photocatalyst hombikat UV-100. These findings open the door for further research for improving the photocatalytic performance of metal-organic frameworks.

Genetic programming and bacterial algorithm for neural networks and fuzzy systems design

In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.

Genetic and bacterial programming for B-Spline neural networks design

The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.