A model of Distributed Ayurvedic Diagnosis and Therapy System for Hridroga Using Agents

Diagnosis of Hridroga (cardiac disorders) in Ayurveda requires the combination of many different types of data, including personal details, patient symptoms, patient histories, general examination results, Ashtavidha pareeksha results etc. Computer-assisted decision support systems must be able to combine these data types into a seamless system. Intelligent agents, an approach that has been used chiefly in business applications, is used in medical diagnosis in this case. This paper is about a multi-agent system named “Distributed Ayurvedic Diagnosis and Therapy System for Hridroga using Agents” (DADTSHUA). It describes the architecture of the DADTSHUA model .This system is using mobile agents and ontology for passing data through the network. Due to this, transport delay can be minimized. It is a system which will be very helpful for the beginning physicians to eliminate his ambiguity in diagnosis and therapy. The system is implemented using Java Agent DEvelopment framework (JADE), which is a java-complaint mobile agent platform from TILab.

Achieving Real-Time Mode Estimation through Offline Compilation

As exploration of our solar system and outerspace move into the future, spacecraft are being developed to venture on increasingly challenging missions with bold objectives. The spacecraft tasked with completing these missions are becoming progressively more complex. This increases the potential for mission failure due to hardware malfunctions and unexpected spacecraft behavior. A solution to this problem lies in the development of an advanced fault management system. Fault management enables spacecraft to respond to failures and take repair actions so that it may continue its mission. The two main approaches developed for spacecraft fault management have been rule-based and model-based systems. Rules map sensor information to system behaviors, thus achieving fast response times, and making the actions of the fault management system explicit. These rules are developed by having a human reason through the interactions between spacecraft components. This process is limited by the number of interactions a human can reason about correctly. In the model-based approach, the human provides component models, and the fault management system reasons automatically about system wide interactions and complex fault combinations. This approach improves correctness, and makes explicit the underlying system models, whereas these are implicit in the rule-based approach. We propose a fault detection engine, Compiled Mode Estimation (CME) that unifies the strengths of the rule-based and model-based approaches. CME uses a compiled model to determine spacecraft behavior more accurately. Reasoning related to fault detection is compiled in an off-line process into a set of concurrent, localized diagnostic rules. These are then combined on-line along with sensor information to reconstruct the diagnosis of the system. These rules enable a human to inspect the diagnostic consequences of CME. Additionally, CME is capable of reasoning through component interactions automatically and still provide fast and correct responses. The implementation of this engine has been tested against the NEAR spacecraft advanced rule-based system, resulting in detection of failures beyond that of the rules. This evolution in fault detection will enable future missions to explore the furthest reaches of the solar system without the burden of human intervention to repair failed components.

Enhancing fault management performance of two-step QoS routing algorithms in GMPLS networks

In this paper a novel methodology aimed at minimizing the probability of network failure and the failure impact (in terms of QoS degradation) while optimizing the resource consumption is introduced. A detailed study of MPLS recovery techniques and their GMPLS extensions are also presented. In this scenario, some features for reducing the failure impact and offering minimum failure probabilities at the same time are also analyzed. Novel two-step routing algorithms using this methodology are proposed. Results show that these methods offer high protection levels with optimal resource consumption

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is often associated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcifications is performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcifications have been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the sense of adding new features not only related to the shape

SQualTrack: A Tool for Robust Fault Detection

One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper

Estimation of zero-sequence impedance of undergrounds cables for single-phase fault location in distribution systems with electric arc

This paper focus on the problem of locating single-phase faults in mixed distribution electric systems, with overhead lines and underground cables, using voltage and current measurements at the sending-end and sequence model of the network. Since calculating series impedance for underground cables is not as simple as in the case of overhead lines, the paper proposes a methodology to obtain an estimation of zero-sequence impedance of underground cables starting from previous single-faults occurred in the system, in which an electric arc occurred at the fault location. For this reason, the signal is previously pretreated to eliminate its peaks voltage and the analysis can be done working with a signal as close as a sinus wave as possible

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system

An Interval Intelligent-based Approach for Fault Detection and Modelling

Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

Expert supervision based on cases

The paper focuses on taking advantage of large amounts of data that are systematically stored in plants (by means of SCADA systems), but not exploited enough in order to achieve supervisory goals (fault detection, diagnosis and reconfiguration). The methodology of case base reasoning (CBR) is proposed to perform supervisory tasks in industrial processes by re-using the stored data. The goal is to take advantage of experiences, registered in a suitable structure as cam, avoiding the tedious task of knowledge acquisition and representation needed by other reasoning techniques as expert systems. An outlook of CBR terminology and basic concepts are presented. The adaptation of CBR in performing expert supervisory tasks, taking into account the particularities and difficulties derived from dynamic systems, is discussed. A special interest is focused in proposing a general case definition suitable for supervisory tasks. Finally, this structure and the whole methodology is tested in a application example for monitoring a real drier chamber

La responsabilidad patrimonial del Estado por la falla en la prestación del servicio médico asistencial. Acto médico defectuoso en las entidades de salud del Estado. -Una visión desde la doctrina y desarrollo jurisprudencial del Consejo de Estado-.

La complejidad que supone abarcar el estudio de la responsabilidad patrimonial del Estado en el ámbito médico sanitario, hace preciso prestar atención a ciertos temas que resultan especialmente relevantes y que han sido decantados jurisprudencialmente por el Honorable Consejo de Estado. De esta manera el presente trabajo desarrolla temas descollantes y novedosos en materia de imputabilidad como viene a ser la prueba de la falla médica mediante la teoría "res ipsa loquitur"; la prueba del nexo causal a través de la prueba indiciaria y la teoría de la probabilidad preponderante. Así mismo se estudian los diversos tipos de daños antijurídicos que pueden darse dentro de la prestación médica a cargo del Estado, destacando especialmente la lesión al derecho a recibir una atención oportuna y eficaz, la pérdida de una oportunidad debida a la no obtención del consentimiento informado del paciente, lo que supone, a su vez, el cercenamiento del derecho de este a elegir someterse o no a determinado tratamiento, previo valoración de pros y contras de la terapia sugerida por el galeno (principio de no agravación). Así mismo se analizanlas hipótesis de daños antijurídicos derivados del error en el diagnóstico, la falla por la omisión de las entidades de control y vigilancia, falla en gineco-obstetricia, así como las hipótesis de responsabilidad objetiva del Estado por óblito quirúrgico, para finalmente tratar el tema novedoso del alea terapéutica con sus particulares características y eventual aplicabilidad en el sistema jurídico colombiano.

Diagnosis y corrección de las dificultades en el aprendizaje de la suma, resta, multiplicación y división.

El presente proyecto intenta realizar un diagnóstico lo más completo posible de las dificultades del fracaso escolar y posibles dificultades que presente el alumno en la asimilación de las operaciones fundamentales (cálculo operacional) y establecer al mismo tiempo una enseñanza correctiva de esas dificultades, que estén de acuerdo con los resultados del diagnóstico y adaptados a las necesidades del alumno.

Effects of pulmonary rehabilitation program in a patient with severe asthma diagnosis

Objective: to present the effectiveness of pulmonary rehabilitation programs in the treatmentof a patient with asthma, this is the case of a young Caucasian girl —17 years old— with severe asthma diagnosis, with symptoms since she was eight years old, 10th grade student. Method: She was referred to the program of Pulmonary Rehabilitation after three hospitalizations during the last year due to asthmatic crises, dyspnoea in activities of daily living, and intolerance to physical exercise. In the initial evaluation, a patient with non-controlled asthma was found; she was receiving short-acting medication admitting that she was not complying with regular use and with a prescribed dose of the pharmacological treatment and that she ignored the importance of this commitment for optimal evolution. The patient expressed concern about the progressive deterioration at her respiratory and functional level during the last year and her fear and anxiety for not being able to breathe during activities befitting her age. Results: One month after receiving bronchodilators and long-acting steroids permanently and complying with recommendations about regular use and adequate inhalatory technique, the patient was included in a three-times a-week program of pulmonary rehabilitation during eight weeks for upper and lower extremity endurance and resistance training. Conclusion: This intervention showed significant changes in the patient at functional level and a greater social participation.

Educació, immigració, fracàs social, qualitat educativa i èxit escolar : dades per a una diagnosi. 'Educación, inmigración, fracaso social, calidad educativa y éxito escolar : datos para una diagnosis'.

Resumen de la revista en catalán

Diagnosis matemática en EGB.

Probar que las pruebas-diagnóstico son válidas para el diagnóstico y pronóstico didáctico del alumno de cada uno de los cursos del primer ciclo de EGB, en el área matemática. Y que éstas conllevan para el profesor objetividad, precisión y rapidez en la realización del diagnóstico. La pre-experimentación con 460 alumnos del CN Bruguera (Girona) entre los cursos de primero a quinto de EGB. Las pruebas diagnóstico de experimentación se llevaron a cabo en 22 centros escolares de Barcelona y Gerona, que se catalogaron en cuatro grupos, siendo realizadas por 4886 individuos de primer ciclo de EGB. De las 4886 se rechazaron 334. Por lo tanto, el estudio se apoya en 4552 individuos. Inteligencia (percentil). Evaluación global del grupo. Puntuación en la prueba diagnóstico. Se realiza una submuestra estratificada de 50 alumnos respecto a cada una de las pruebas. Tabulación de datos. Test TFI (Inteligencia). Cuestionario ad hoc. Pruebas de diagnóstico matemático en cada uno de los niveles de primer ciclo de EGB. El numero de ítems por nivel es: 1-30, 2-40, 3-50, 4-60, 5-60. Pruebas de Kolmogorov. Análisis de la varianza. Método descriptivo. Análisis factorial (de correspondencias Benzecri). A partir de la prueba diagnóstico el docente puede iniciar enseñanzas de recuperación oportunas. Con una enseñanza de la Matemática más profunda y racional aumenta su valor educativo. Los niveles didácticos de las fichas diagnóstico son un completo desarrollo del contenido de la Matemática en los primeros cursos de EGB.

Aproximació a una diagnosi de la competència lingüística de l'alumne fill d'immigrants al torn de nit de l'I.B. Vicenç Plantada de Mollet del Vallès. 'Aproximación a una diagnosis de la competencia lingüística del alumno hijo de inmigrantes en el turno de noche del I.B. Vicenç Plantada de Mollet del Vallès'.

Un resumen de este documento está publicado en la revista Guix, Barcelona, 1993, n 192, octubre; p. 59-60