A Case-base Approach to Workforces’ Satisfaction Assessment

It is well known that human resources play a valuable role in a sustainable organizational development. Indeed, this work will focus on the development of a decision support system to assess workers’ satisfaction based on factors related to human resources management practices. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data or knowledge in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process.

Age Prediction through Pelvis X-Ray Images - A Case Based approach to Problem Solving

It is well known that the dimensions of the pelvic bones depend on the gender and vary with the age of the individual. Indeed, and as a matter of fact, this work will focus on the development of an intelligent decision support system to predict individual’s age based on pelvis’ dimensions criteria. On the one hand, some basic image processing technics were applied in order to extract the relevant features from pelvic X-rays. On the other hand, the computational framework presented here was built on top of a Logic Programming approach to knowledge representation and reasoning, that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

An Artificial Intelligence Approach to Individuals' Age Assessment

A link between patterns of pelvic growth and human life history is supported by the finding that, cross-culturally, variation in maturation rates of female pelvis are correlated with variation in ages of menarche and first reproduction, i.e., it is well known that the human dimensions of the pelvic bones depend on the gender and vary with the age. Indeed, one feature in which humans appear to be unique is the prolonged growth of the pelvis after the age of sexual maturity. Both the total superoinferior length and mediolateral breadth of the pelvis continues to grow markedly after puberty, and do not reach adult proportions until the late teens years. This continuation of growth is accomplished by relatively late fusion of the separate centers of ossification that form the bones of the pelvis. Hence, in this work we will focus on the development of an intelligent decision support system to predict individual’s age based on a pelvis' dimensions criteria. Some basic image processing techniques were applied in order to extract the relevant features from pelvic X-rays, being the computational framework built on top of a Logic Programming approach to Knowledge Representation and Reasoning that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

A Soft Computing Approach to Quality Evaluation of General Chemistry Learning in Higher Education

In contemporary societies higher education must shape individuals able to solve problems in a workable and simpler manner and, therefore, a multidisciplinary view of the problems, with insights in disciplines like psychology, mathematics or computer science becomes mandatory. Undeniably, the great challenge for teachers is to provide a comprehensive training in General Chemistry with high standards of quality, and aiming not only at the promotion of the student’s academic success, but also at the understanding of the competences/skills required to their future doings. Thus, this work will be focused on the development of an intelligent system to assess the Quality-of-General-Chemistry-Learning, based on factors related with subject, teachers and students.

Transcription of alternative oxidase (AOX) and plastid terminal oxidase (PTOX) during stress-regulated root tissue growth in Daucus carota L. - An approach to identify functional marker candidates for breeding on carrot yield stability

A presente tese explora a hipótese de utilização dos genes da oxidase alternativa (AOX) e da oxidase terminal da plastoquinona (PTOX) como genes-alvo para o desenvolvimento de marcadores funcionais (MF) para avaliar a performance do crescimento em cenoura, fator determinante da produtividade. Para avaliar se os referidos genes estão associados com o crescimento da cenoura procedeu—se ao seu isolamento e posterior análise dos seus perfis de transcrição em diversos sistemas biológicos. O sistema in vitro selecionado, denominado sistema de culturas primárias, permitiu avaliar alterações na quantidade de transcritos desses genes durante os processos de reprogramação celular e crescimento. Ao nível da planta foi também estudado o efeito do frio na expressão precoce dos genes AOX. Ambos os genes DcAOX1 e DcAOX2a revelaram uma resposta rápida e um padrão semelhante apos stresse (inoculação in vitro e resposta ao frio). Foi igualmente verificado um incremento na expressão do gene DcPTOX durante a fase inicial do processo de reprogramação celular. Estudos de expressão dos genes AOX durante o desenvolvimento da raiz da cenoura revelaram que o gene DcAOX2a será potencialmente o gene mais envolvido neste processo. De modo a avaliar a hipótese de envolvimento do gene DcPTOX no crescimento da raíz procederam—se a estudos de expressão ao nível do tecido meristemático. Todavia, para um mais completo entendimento da ligação entre DcPTOX e o crescimento secundário e/ou acumulação de carotenos, a expressão do gene DcPTOX foi também avaliada em raízes de cenoura durante o desenvolvimento, utilizando cultivares caracterizadas por distintos conteúdos de carotenos. Os resultados obtidos demonstraram a associação do gene DcPTOX a ambos os processos. O envolvimento da PTOX no crescimento adaptativo da raiz foi analisado com um ensaio que permitiu identificar, no tecido meristemático, uma resposta precoce do gene DcPTOX face a uma diminuição da temperatura. Adicionalmente, foi efetuada a seleção de genes de referência para uma analise precisa da expressão génica por RT-qPCR em diversos sistemas biológicos de cenoura, e a importância do seu estudo ao nível do sistema biológico foi realçada. Os resultados desta tese são encorajadores para prosseguir os estudos de utilização dos genes AOX e PTOX como MF no melhoramento da performance do crescimento adaptativo em cenoura, fator determinante para a produtividade; ABSTRACT: This thesis explores the hypothesis of using the alternative oxidase (AOX) and theplastid terminal oxidase (PTOX) as target genes for functional marker (FM) development for yield-determining growth performance in carrot. To understand if these genes are associated to growth, different AOX gene family members and the single PTOX gene were isolated, and their expression patterns evaluated in diverse carrot plant systems. An in-vitro primary culture system was selected to study AOX and PTOX transcript changes during cell reprogramming and growth performance. At plant level, a putative early response of AOX to chilling was also evaluated. In fact, both DcAOXl and DcAOXZa were early responsive and showed similar patterns under stress conditions (in vitro inoculation and chilling). A role for DcPTOX during earliest events of cell reprogramming was also suggested. Next, the expression profiles of AOX gene family members during carrot tap root development were investigated. DcAOXZa was identified as the most responsive gene to root development. In order to evaluate if DcPTOX is associated with carrot tap root growth performance, DcPTOX transcript levels were measured in the central root meristem. To further understand whether DcPTOX is associated with secondary growth and/or carotenoids accumulation, DcPTOX expression was also studied in deveIOping carrot tap roots in cultivars with different carotenoids contents. The results indicated that DcPTOX associates to both carotenoid biosynthesis and secondary growth during storage root development. To obtain further insights into the involvement of PTOX on adaptive growth, the early effects of temperature decrease were explored in the root meristem, where a short—term early response in DcPTOX was found, probably associated with adaptive growth. Furthermore, a selection of the most suitable reference genes for accurate RT—qPCR analysis in several carrot experimental systems was performed and discussed. The present research provides the necessary toolbox for continuing studies in carrot AOX and PTOX genes as promising resources for FM candidates in order to assist breeding on yield—determining adaptive growth performance.

An Artificial Intelligence Approach to Dyscalculia

Dyscalculia stands for a brain-based condition that makes it hard to make sense of numbers and mathematical concepts. Some adolescents with dyscalculia cannot grasp basic number concepts. They work hard to learn and memorize basic number facts. They may know what to do in mathematical classes but do not understand why they are doing it. In other words, they miss the logic behind it. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work focuses on the development of an Intelligent System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming framework to Knowledge Representation and Reasoning, complemented with a Case-Based problem solving approach to computing, that allows for the handling of incomplete, unknown, or even contradictory information.

A Case-Based Approach to Nosocomial Infection Detection

The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.

A Case Based approach to assess Waiting Time Prediction at an Intensive Care Unity

Waiting time at an intensive care unity stands for a key feature in the assessment of healthcare quality. Nevertheless, its estimation is a difficult task, not only due to the different factors with intricate relations among them, but also with respect to the available data, which may be incomplete, self-contradictory or even unknown. However, its prediction not only improves the patients’ satisfaction but also enhance the quality of the healthcare being provided. To fulfill this goal, this work aims at the development of a decision support system that allows one to predict how long a patient should remain at an emergency unit, having into consideration all the remarks that were just stated above. It is built on top of a Logic Programming approach to knowledge representation and reasoning, complemented with a Case Base approach to computing.

Constraint-Informed Information Systems in Space Management Utilization

Declarative techniques such as Constraint Programming can be very effective in modeling and assisting management decisions. We present a method for managing university classrooms which extends the previous design of a Constraint-Informed Information System to generate the timetables while dealing with spatial resource optimization issues. We seek to maximize space utilization along two dimensions: classroom use and occupancy rates. While we want to maximize the room use rate, we still need to satisfy the soft constraints which model students’ and lecturers’ preferences. We present a constraint logic programming-based local search method which relies on an evaluation function that combines room utilization and timetable soft preferences. Based on this, we developed a tool which we applied to the improvement of classroom allocation in a University. Comparing the results to the current timetables obtained without optimizing space utilization, the initial versions of our tool manages to reach a 30% improvement in space utilization, while preserving the quality of the timetable, both for students and lecturers.

A symbolic approach to nonlinearly perturbed heat equation

We consider a system described by the linear heat equation with adiabatic boundary conditions which is perturbed periodicaly. This perturbation is nonlinear and is characterized by a one-parameter family of quadratic maps. The system, depending on the parameters, presents very complex behaviour. We introduce a symbolic framework to analyze the system and resume its most important features.

10th European Conference on Information Systems Management

The 10th European Conference on Information Systems Management is being held at The University of Evora, Portugal on the 8 /9 September 2016. The Conference Chair is Paulo Silva and the Programme Chairs are Prof. Rui Quaresma and Prof. António Guerreiro. ECISM provides an opportunity for individuals researching and working in the broad field of information systems management, including IT evaluation to come together to exchange ideas and discuss current research in the field. This has developed into a particularly important forum for the present era, where the modern challenges of managing information and evaluating the effectiveness of related technologies are constantly evolving in the world of Big Data and Cloud Computing. We hope that this year’s conference will provide you with plenty of opportunities to share your expertise with colleagues from around the world. The keynote speakers for the Conference are Carlos Zorrinho from the Portuguese Delegation and Isabel Ramos from University of Minho, Portugal. ECISM 2016 received an initial submission of 84 abstracts. After the double blind peer review process 25 aca demic papers, 7 PhD research papers, 3 Masters research paper and 5 work in progress papers have been ac cepted for publication in these Conference Proceedings. These papers represent research from around the world, including Belgium, Brazil, China, Czech Republic, Kazakhstan, Malaysia, New Zealand, Norway, Oman, Poland, Portugal, South Africa, Sweden, The Netherlands, UK and Vietnam.

An Approach to Tactical Performance Optimization in a Big Data World

The amount of data collected from an individual player during a football match has increased significantly in recent years, following technological evolution in positional tracking. However, given the short time that separates competitions, the common analysis of these data focuses on the magnitude of actions of each player, while considering either technical or physical perform- ance. This focus leads to a considerable amount of information not being taken into account in performance optimization, particularly while considering a sequence of different matches of the same team. In this presentation, we will present a tactical performance indicator that considers players’ overall positioning and their level of coordination during the match. This performance indicator will be applied in different time scales, with a particular focus on possible practical applications.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment

The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).

Cork oak transplant: A new reality? A Physiological Approach to maximize sucess rate.

Cork oak tree (Quercus suber L.), in Portugal, is considered the national tree and have special demands and legal protection when dealing with silviculture management (pruning, debarking, thinning). Being a species of slow growth, cork oak transplanting procedures can be a valuable asset either from the economic or ecological rationales to relocate trees, re-populate areas affected by high tree mortality, increase tree density to control erosion on montado ecosystems or landscape design. This study focuses the impacts and physiological responses of ten juvenile rain fed cork oak trees (with diameter at breast height between 6 and 16cm), when subjected to transplant operations. The work was conducted in a cork oak woodland experimental plot at the campus of the University of Évora (SW Portugal), during the year of 2015. Tree’s transplants were performed with a truck-mounted hydraulic spade transplanter coupled with a proposed methodology to maximize tree survival rates, addressing techniques to limit canopy transpiration and to improve root systems prior to transplant. Tree ecophysiological indicators (sap flow, leaf water potentials and stomatal conductance) were monitored comprising the periods before and after transplant operations, and water stress avoidance practices were established to promote post-transplant tree status recovery, including irrigation to match average daily accumulated sap flow. Transplant operations were considered successful when the tree's water uptake inferred from sap flow exhibited a high correlation with solar radiation and returned to its undisturbed or pre-transplant water potential gradients in the following 2 to 3 weeks. The post-transplant tree nourishment follow up included permanent sap flow measurements and identified the time elapsed after transplantation from which the tree recovers its normal transpiration thresholds and response. Our results suggest that by following the proposed methodology the sampled cork oak trees exhibited a transplant success rate of 90%.