A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Modelo de avaliação do impacto das TSI na produtividade das organizações

Dissertação de mestrado em Sistemas de Informação

A survey of distributed data aggregation algorithms

Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.

Immersiveness of ubiquitous computing environments prototypes: A case study

The development of ubiquitous computing (ubicomp) environments raises several challenges in terms of their evaluation. Ubicomp virtual reality prototyping tools enable users to experience the system to be developed and are of great help to face those challenges, as they support developers in assessing the consequences of a design decision in the early phases of development. Given the situated nature of ubicomp environments, a particular issue to consider is the level of realism provided by the prototypes. This work presents a case study where two ubicomp prototypes, featuring different levels of immersion (desktop-based versus CAVE-based), were developed and compared. The goal was to determine the cost/benefits relation of both solutions, which provided better user experience results, and whether or not simpler solutions provide the same user experience results as more elaborate one.

Filososofía y Ciencia Computacional: Aspectos epistemológicos, ontológicos y metodológicos. Philosophy and Computing Sciencs: Epistemological, Ontological and Methodological Aspects.

Uno de los temas centrales del proyecto concierne la naturaleza de la ciencia de la computación. La reciente aparición de esta disciplina sumada a su origen híbrido como ciencia formal y disciplina tecnológica hace que su caracterización aún no esté completa y menos aún acordada entre los científicos del área. En el trabajo Three paradigms of Computer Science de A. Eden, se presentan tres posiciones admitidamente exageradas acerca de como entender tanto el objeto de estudio (ontología) como los métodos de trabajo (metodología) y la estructura de la teoría y las justificaciones del conocimiento informático (epistemología): La llamada racionalista, la cual se basa en la idea de que los programas son fórmulas lógicas y que la forma de trabajo es deductiva, la tecnocrática que presenta a la ciencia computacional como una disciplina ingenieril y la ahi llamada científica, la cual asimilaría a la computación a las ciencias empíricas. Algunos de los problemas de ciencia de la computación están relacionados con cuestiones de filosofía de la matemática, en particular la relación entre las entidades abstractas y el mundo. Sin embargo, el carácter prescriptivo de los axiomas y teoremas de las teorías de la programación puede permitir interpretaciones alternativas y cuestionaría fuertemente la posibilidad de pensar a la ciencia de la computación como una ciencia empírica, al menos en el sentido tradicional. Por otro lado, es posible que el tipo de análisis aplicado a las ciencias de la computación propuesto en este proyecto aporte nuevas ideas para pensar problemas de filosofía de la matemática. Un ejemplo de estos posibles aportes puede verse en el trabajo de Arkoudas Computers, Justi?cation, and Mathematical Knowledge el cual echa nueva luz al problema del significado de las demostraciones matemáticas.Los objetivos del proyecto son: Caracterizar el campo de las ciencias de la computación.Evaluar los fundamentos ontológicos, epistemológicos y metodológicos de la ciencia de la computación actual.Analizar las relaciones entre las diferentes perspectivas heurísticas y epistémicas y las practicas de la programación.

monitoring-based approach to object-oriented real-time computing

Monitoring, object-orientation, real-time, execution-time, scheduling

maintenance model for systems with phase-type distributed times to failure

Magdeburg, Univ., Fak. für Mathematik, Diss., 2010

Keyword search across distributed heterogenous structured data sources

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Collaboration process design for ideation in distributed environments : approaches to support collaborative ideation in global virtual groups using technological support

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Conceptual Foundations of Modelling of Innovative Production Projects

At the moment there is a lack of methodological approaches to formalization of management of innovative projects relating to production systems, as well as to adaptation and practical use of the existing approaches. This article is about one potential approach to the management of innovative projects, which makes the building of innovative process models possible based on objective approach. It outlines the frameworks for the building of innovative project models, and describes the method of transition from conceptual modelling to innovative project management. In this case, the model alone and together with parameters used for evaluation of the project may be unique and depends on the special features of the project, preferences of decision-making person, and production and economic system in which it is to be implemented. Unlike existing approaches, this concept does not place any restrictions on types of models and makes it possible to take into account the specificities of economic and production systems. Principles embodied in the model allow its usage as a basis for simulation model to be used in one of specialized simulation systems, as well as for information system providing information support of decision-making process in production and economic systems both newly developed by the company (enterprise) and designed on the basis of available information systems that interact through the exchange of data. In addition, this article shows that the development of conceptual foundations of innovative project management in the economic and production systems is inseparable from the development of the theory of industrial control systems, and their comprehensive study may be reduced to a set of elements represented as certain algorithms, models and evaluations. Thus, the study of innovative process may be conducted in both directions: from general to particular, and vice versa.

Cost Factors in Digital Projects: A Model Useful in Other Applications

Description of a costing model developed by digital production librarian to determine the cost to put an item into the Claremont Colleges Digital Library at the Claremont University Consortium. This case study includes variables such as material types and funding sources, data collection methods, and formulas and calculations for analysis. This model is useful for grant applications, cost allocations, and budgeting for digital project coordinators and digital library projects.