Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

The role of automatic shape and position recognitionin streamlining manufacturing

The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

Automatic eye blink detection using consumer web cameras

This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%

A integração de técnicas BIM (Building Information Modeling) no projeto e na construção de estruturas de madeira

Dissertação de mestrado integrado em Engenharia Civil

Automatic distinction of Fernando Pessoas’ heteronyms

Text Mining has opened a vast array of possibilities concerning automatic information retrieval from large amounts of text documents. A variety of themes and types of documents can be easily analyzed. More complex features such as those used in Forensic Linguistics can gather deeper understanding from the documents, making possible performing di cult tasks such as author identi cation. In this work we explore the capabilities of simpler Text Mining approaches to author identification of unstructured documents, in particular the ability to distinguish poetic works from two of Fernando Pessoas' heteronyms: Alvaro de Campos and Ricardo Reis. Several processing options were tested and accuracies of 97% were reached, which encourage further developments.

Towards the design and implementation of aspect-oriented programming for spreadsheets

A spreadsheet usually starts as a simple and singleuser software artifact, but, as frequent as in other software systems, quickly evolves into a complex system developed by many actors. Often, different users work on different aspects of the same spreadsheet: while a secretary may be only involved in adding plain data to the spreadsheet, an accountant may define new business rules, while an engineer may need to adapt the spreadsheet content so it can be used by other software systems.Unfortunately,spreadsheetsystemsdonotoffermodular mechanisms, and as a consequence, some of the previous tasks may be defined by adding intrusive “code” to the spreadsheet. In this paper we go through the design and implementation of an aspect-oriented language for spreadsheets so that users can work on different aspects of a spreadsheet in a modular way. For example, aspects can be defined in order to introduce new business rules to an existing spreadsheet, or to manipulate the spreadsheet data to be ported to another system. Aspects are defined as aspect-oriented program specifications that are dynamically woven into the underlying spreadsheet by an aspect weaver. In this aspect-oriented style of spreadsheet development, differentusers develop,orreuse,aspects withoutaddingintrusive code to the original spreadsheet. Such code is added/executed by the spreadsheet weaving mechanism proposed in this paper.

Metaphorisms in programming

This paper introduces the metaphorism pattern of relational specification and addresses how specification following this pattern can be refined into recursive programs. Metaphorisms express input-output relationships which preserve relevant information while at the same time some intended optimization takes place. Text processing, sorting, representation changers, etc., are examples of metaphorisms. The kind of metaphorism refinement proposed in this paper is a strategy known as change of virtual data structure. It gives sufficient conditions for such implementations to be calculated using relation algebra and illustrates the strategy with the derivation of quicksort as example.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Sistemas de Tipos para Verificación de Programas Concurrentes. Type Systems for Concurrent Programs Verification.

La programación concurrente es una tarea difícil aún para los más experimentados programadores. Las investigaciones en concurrencia han dado como resultado una gran cantidad de mecanismos y herramientas para resolver problemas de condiciones de carrera de datos y deadlocks, problemas que surgen por el mal uso de los mecanismos de sincronización. La verificación de propiedades interesantes de programas concurrentes presenta dificultades extras a los programas secuenciales debido al no-determinismo de su ejecución, lo cual resulta en una explosión en el número de posibles estados de programa, haciendo casi imposible un tratamiento manual o aún con la ayuda de computadoras. Algunos enfoques se basan en la creación de lenguajes de programación con construcciones con un alto nivel de abstración para expresar concurrencia y sincronización. Otros enfoques tratan de desarrollar técnicas y métodos de razonamiento para demostrar propiedades, algunos usan demostradores de teoremas generales, model-checking o algortimos específicos sobre un determinado sistema de tipos. Los enfoques basados en análisis estático liviano utilizan técnicas como interpretación abstracta para detectar ciertos tipos de errores, de una manera conservativa. Estas técnicas generalmente escalan lo suficiente para aplicarse en grandes proyectos de software pero los tipos de errores que pueden detectar es limitada. Algunas propiedades interesantes están relacionadas a condiciones de carrera y deadlocks, mientras que otros están interesados en problemas relacionados con la seguridad de los sistemas, como confidencialidad e integridad de datos. Los principales objetivos de esta propuesta es identificar algunas propiedades de interés a verificar en sistemas concurrentes y desarrollar técnicas y herramientas para realizar la verificación en forma automática. Para lograr estos objetivos, se pondrá énfasis en el estudio y desarrollo de sistemas de tipos como tipos dependientes, sistema de tipos y efectos, y tipos de efectos sensibles al flujo de datos y control. Estos sistemas de tipos se aplicarán a algunos modelos de programación concurrente como por ejemplo, en Simple Concurrent Object-Oriented Programming (SCOOP) y Java. Además se abordarán propiedades de seguridad usando sistemas de tipos específicos. Concurrent programming has remained a dificult task even for very experienced programmers. Concurrency research has provided a rich set of tools and mechanisms for dealing with data races and deadlocks that arise of incorrect use of synchronization. Verification of most interesting properties of concurrent programs is a very dificult task due to intrinsic non-deterministic nature of concurrency, resulting in a state explosion which make it almost imposible to be manually treat and it is a serious challenge to do that even with help of computers. Some approaches attempts create programming languages with higher levels of abstraction for expressing concurrency and synchronization. Other approaches try to develop reasoning methods to prove properties, either using general theorem provers, model-checking or specific algorithms on some type systems. The light-weight static analysis approach apply techniques like abstract interpretation to find certain kind of bugs in a conservative way. This techniques scale well to be applied in large software projects but the kind of bugs they may find are limited. Some interesting properties are related to data races and deadlocks, while others are interested in some security problems like confidentiality and integrity of data. The main goals of this proposal is to identify some interesting properties to verify in concurrent systems and develop techniques and tools to do full automatic verification. The main approach will be the application of type systems, as dependent types, type and effect systems, and flow-efect types. Those type systems will be applied to some models for concurrent programming as Simple Concurrent Object-Oriented Programming (SCOOP) and Java. Other goals include the analysis of security properties also using specific type systems.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.

Estimation of nonparametric probability density functions with applications to automatic speech recognition

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2007

Multimodal automatic user disposition recognition in human-machine interaction

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2013

Automatic top-down processing explains common left occipito-temporal responses to visual words and objects.

Previous studies have demonstrated that a region in the left ventral occipito-temporal (LvOT) cortex is highly selective to the visual forms of written words and objects relative to closely matched visual stimuli. Here, we investigated why LvOT activation is not higher for reading than picture naming even though written words and pictures of objects have grossly different visual forms. To compare neuronal responses for words and pictures within the same LvOT area, we used functional magnetic resonance imaging adaptation and instructed participants to name target stimuli that followed briefly presented masked primes that were either presented in the same stimulus type as the target (word-word, picture-picture) or a different stimulus type (picture-word, word-picture). We found that activation throughout posterior and anterior parts of LvOT was reduced when the prime had the same name/response as the target irrespective of whether the prime-target relationship was within or between stimulus type. As posterior LvOT is a visual form processing area, and there was no visual form similarity between different stimulus types, we suggest that our results indicate automatic top-down influences from pictures to words and words to pictures. This novel perspective motivates further investigation of the functional properties of this intriguing region.

Automatic measurement of key ski jumping phases and temporal events with a wearable system.

We propose a new method, based on inertial sensors, to automatically measure at high frequency the durations of the main phases of ski jumping (i.e. take-off release, take-off, and early flight). The kinematics of the ski jumping movement were recorded by four inertial sensors, attached to the thigh and shank of junior athletes, for 40 jumps performed during indoor conditions and 36 jumps in field conditions. An algorithm was designed to detect temporal events from the recorded signals and to estimate the duration of each phase. These durations were evaluated against a reference camera-based motion capture system and by trainers conducting video observations. The precision for the take-off release and take-off durations (indoor < 39 ms, outdoor = 27 ms) can be considered technically valid for performance assessment. The errors for early flight duration (indoor = 22 ms, outdoor = 119 ms) were comparable to the trainers' variability and should be interpreted with caution. No significant changes in the error were noted between indoor and outdoor conditions, and individual jumping technique did not influence the error of take-off release and take-off. Therefore, the proposed system can provide valuable information for performance evaluation of ski jumpers during training sessions.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.