Search results for: sepsis diagnosis
398 Pulse Oximeter Concept for Vascular Occlusion Test
Authors: Fatanah M. Suhaimi, J. Geoffrey Chase, Christopher G. Pretty, Rodney Elliott, Geoffrey M. Shaw
Microcirculatory dysfunction is very common in sepsis and may results in organ failure and increased risk of death. Analyzing oxygen utilization can potentially assess microcirculation function of an individual. In this study, a modified pulse oximeter is used to extract information signals due to absorption of red (R) and infrared (IR) light. IR and R signal are related to the overall blood volume and reduced hemoglobin, respectively. Differences between these two signals thus represent the amount of oxygenated hemoglobin. Avascular occlusion test has been conducted on healthy individuals to validate the pulse oximeter concept. In this test, both R and IR signals rapidly changed according to the occlusion process. The pulse oximeter concept presented is capable of extracting valuable information to assess microcirculation condition. Implementing this concept on ICU patients has the potential to aid sepsis diagnosis and provide more accurate tracking of patient state and sepsis status.
Keywords: Microcirculation, sepsis, sepsis diagnosis, oxygen extraction.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1904
397 Whole Body CT for a Patient with Sepsis
Authors: Y. Yanagawa, K. Aihara, S. Watanabe, M. Takemoto, T. Naito, T. Iba, H. Tanaka
This study retrospectively investigated the significance of whole body CT (WCT) for patients with sepsis. A medical chart review was retrospectively performed for all patients with systemic inflammatory response syndrome that were treated initially between April 2011 and March 2012. The subjects were divided into a WCT group that underwent WCT on arrival and a control group. Results of this study suggested that WCT for sepsis was useful for elderly patients whose chief complaint or physiological findings could not suggest the anatomical site of infection, to determine the infectious focus and indications/method for surgery, to diagnose the basic diseases associated with opportunistic infections and to evaluate complicated diseases
Keywords: Sepsis, CT, outcome.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1724
396 Early Onset Neonatal Sepsis Pathogens in Malaysian Hospitals: Determining Empiric Antibiotic
Authors: Nazedah Ain Ibrahim, Mohamed Mansor Manan
Information regarding early onset neonatal sepsis (EONS) pathogens may vary between regions. Global perspectives showed Group B Streptococcal (GBS) as the most common causative pathogens, but the widespread use of intrapartum antibiotics has changed the pathogens pattern towards gram negative microorganisms, especially E. coli. Objective of this study is to describe the pathogens isolated, to assess current treatment and risk of EONS. Records of 899 neonates born in three General Hospitals between 2009 until 2012 were retrospectively reviewed. Proven was found in 22 (3%) neonates. The majority was isolated with gram positive organisms, 17 (2.3%). All grams positive and most gram negative organisms showed sensitivity to the tested antibiotics. Only two rare gram negative organisms showed total resistant. Male was possible risk of proven EONS. Although proven EONS remains uncommon in Malaysia, nonetheless, the effect of intrapartum antibiotics still required continuous surveillance.
Keywords: Early onset neonatal sepsis, neonates, pathogens, gram positive, gram negative.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2963
395 Design of Multi-disease Diagnosis Processor using Hypernetworks Technique
Authors: Jae-Yeon Song, Seung-Yerl Lee, Kyu-Yeul Wang, Byung-Soo Kim, Sang-Seol Lee, Seong-Seob Shin, Jae-Young Choi, Chong Ho Lee, Jeahyun Park, Duck-Jin Chung
Abstract:In this paper, we propose disease diagnosis hardware architecture by using Hypernetworks technique. It can be used to diagnose 3 different diseases (SPECT Heart, Leukemia, Prostate cancer). Generally, the disparate diseases require specified diagnosis hardware model for each disease. Using similarities of three diseases diagnosis processor, we design diagnosis processor that can diagnose three different diseases. Our proposed architecture that is combining three processors to one processor can reduce hardware size without decrease of the accuracy.
Keywords: Diagnosis processor, Hypernetworks, Leukemia, Mask, Prostate cancer, SPECT Heart dataProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1214
394 Modified Data Mining Approach for Defective Diagnosis in Hard Disk Drive Industry
Authors: S. Soommat, S. Patamatamkul, T. Prempridi, M. Sritulyachot, P. Ineure, S. Yimman
Abstract:Currently, slider process of Hard Disk Drive Industry become more complex, defective diagnosis for yield improvement becomes more complicated and time-consumed. Manufacturing data analysis with data mining approach is widely used for solving that problem. The existing mining approach from combining of the KMean clustering, the machine oriented Kruskal-Wallis test and the multivariate chart were applied for defective diagnosis but it is still be a semiautomatic diagnosis system. This article aims to modify an algorithm to support an automatic decision for the existing approach. Based on the research framework, the new approach can do an automatic diagnosis and help engineer to find out the defective factors faster than the existing approach about 50%.
Keywords: Slider process, Defective diagnosis and Data mining.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1084
393 Motor Gear Fault Diagnosis by Current, Noise and Vibration on AC Machine Considering Environment
Authors: Sun-Ki Hong, Ki-Seok Kim, Yong-Ho Cho
Abstract:Lots of motors have been being used in industry. Therefore many researchers have studied about the failure diagnosis of motors. In this paper, the effect of measuring environment for diagnosis of gear fault connected to a motor shaft is studied. The fault diagnosis is executed through the comparison of normal gear and abnormal gear. The measured FFT data are compared with the normal data and analyzed for q-axis current, noise and vibration. For bad and good environment, the diagnosis results are compared. From these, it is shown that the bad measuring environment may not be able to detect exactly the motor gear fault. Therefore it is emphasized that the measuring environment should be carefully prepared.
Keywords: Motor fault, Diagnosis, FFT, Vibration, Noise, q-axis current, measuring environment.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2287
392 Application of Fuzzy Logic in Fault Diagnosis in Transformers using Dissolved Gas based on Different Standards
Authors: Rahmatollah Hooshmand, Mahdi Banejad
Abstract:One of the problems in fault diagnosis of transformer based on dissolved gas, is lack of matching the result of fault diagnosis of different standards with the real world. In this paper, the result of the different standards is analyzed using fuzzy and the result is compared with the empirical test. The comparison between the suggested method and existing methods indicate the capability of the suggested method in on-line fault diagnosis of the transformers. In addition, in some cases the existing standards are not able to diagnose the fault. In theses cases, the presented method has the potential of diagnosing the fault. The information of three transformers is used to the show the capability of the suggested method in diagnosing the fault. The results validate the capability of the presented method in fault diagnosis of the transformer.
Keywords: Fault Diagnosis of Transformer, Dissolved Gas, Fuzzy Logic.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2182
391 On-line Testing of Software Components for Diagnosis of Embedded Systems
Authors: Thi-Quynh Bui, Oum-El-Kheir Aktouf
Abstract:This paper studies the dependability of componentbased applications, especially embedded ones, from the diagnosis point of view. The principle of the diagnosis technique is to implement inter-component tests in order to detect and locate the faulty components without redundancy. The proposed approach for diagnosing faulty components consists of two main aspects. The first one concerns the execution of the inter-component tests which requires integrating test functionality within a component. This is the subject of this paper. The second one is the diagnosis process itself which consists of the analysis of inter-component test results to determine the fault-state of the whole system. Advantage of this diagnosis method when compared to classical redundancy faulttolerant techniques are application autonomy, cost-effectiveness and better usage of system resources. Such advantage is very important for many systems and especially for embedded ones.
Keywords: Dependability, diagnosis, middlewares, embeddedsystems, fault tolerance, inter-component testing.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1625
390 A Framework for Early Differential Diagnosis of Tropical Confusable Diseases Using the Fuzzy Cognitive Map Engine
Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji
The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.
Keywords: Medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1930
389 Diagnosis of Multivariate Process via Nonlinear Kernel Method Combined with Qualitative Representation of Fault Patterns
Authors: Hyun-Woo Cho
Abstract:The fault detection and diagnosis of complicated production processes is one of essential tasks needed to run the process safely with good final product quality. Unexpected events occurred in the process may have a serious impact on the process. In this work, triangular representation of process measurement data obtained in an on-line basis is evaluated using simulation process. The effect of using linear and nonlinear reduced spaces is also tested. Their diagnosis performance was demonstrated using multivariate fault data. It has shown that the nonlinear technique based diagnosis method produced more reliable results and outperforms linear method. The use of appropriate reduced space yielded better diagnosis performance. The presented diagnosis framework is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. The use of reduced model space helps to mitigate the sensitivity of the fault pattern to noise.
Keywords: Real-time Fault diagnosis, triangular representation of patterns in reduced spaces, Nonlinear kernel technique, multivariate statistical modeling.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478
388 Analysis of Image Segmentation Techniques for Diagnosis of Dental Caries in X-ray Images
Authors: V. Geetha, K. S. Aprameya
Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.
Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 966
387 Integrated Reasoning Approach for Car Faulty Diagnosis
Authors: Diana M.L. Wong
Abstract:This paper presents an integrated case based and rule based reasoning method for car faulty diagnosis. The reasoning method is done through extracting the past cases from the Proton Service Center while comparing with the preset rules to deduce a diagnosis/solution to a car service case. New cases will be stored to the knowledge base. The test cases examples illustrate the effectiveness of the proposed integrated reasoning. It has proven accuracy of similar reasoning if carried out by a service advisor from the service center.
Keywords: component; case based reasoning (CBR), rule basedreasoning (RBR), decision support systems, diagnosis tool.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1777
386 A Novel Fuzzy-Neural Based Medical Diagnosis System
Authors: S. Moein, S. A. Monadjemi, P. Moallem
Abstract:In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and applied to a MLP neural network. The results of the experiments and also the advantages of using a fuzzy approach were discussed as well. Outcomes suggest the role of effective symptoms selection and the advantages of data fuzzificaton on a neural networks-based automatic medical diagnosis system.
Keywords: Artificial Neural Networks, Fuzzy Logic, MedicalDiagnosis, Symptoms, Fuzzification.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2152
385 Application of Intuitionistic Fuzzy Cross Entropy Measure in Decision Making for Medical Diagnosis
Authors: Shikha Maheshwari, Amit Srivastava
In medical investigations, uncertainty is a major challenging problem in making decision for doctors/experts to identify the diseases with a common set of symptoms and also has been extensively increasing in medical diagnosis problems. The theory of cross entropy for intuitionistic fuzzy sets (IFS) is an effective approach in coping uncertainty in decision making for medical diagnosis problem. The main focus of this paper is to propose a new intuitionistic fuzzy cross entropy measure (IFCEM), which aid in reducing the uncertainty and doctors/experts will take their decision easily in context of patient’s disease. It is shown that the proposed measure has some elegant properties, which demonstrates its potency. Further, it is also exemplified in detail the efficiency and utility of the proposed measure by using a real life case study of diagnosis the disease in medical science.
Keywords: Intuitionistic fuzzy cross entropy (IFCEM), intuitionistic fuzzy set (IFS), medical diagnosis, uncertainty.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1920
384 Remote Rehabilitation Development Status in China–To Eliminate the Disabled People`s Space Obstacles
Authors: Ning Liu, Jue Wang, Zhe Li
Abstract:The remote diagnosis and remote medical smoked to part. In China, in accordance with the requirements of different applications of remote diagnosis and Relates to the technical difference, which can be divided into special purpose remote diagnosis and treatment system, the remote will Referral system, remote medical consultation system, remote rehabilitation technology and remote operation technology. In this article, will introduce China for the special purpose of service remote diagnosis and treatment system and technology, including: China disabled status and virtual reality technology; China 's domestic family medical care system and China 's current situation of the development of telemedicine.
Keywords: China, Remote rehabilitation, The disabled peopleProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1472
383 Multidisciplinary Approach to Diagnosis of Primary Progressive Aphasia in a Younger Middle Aged Patient
Authors: Robert Krause
Primary progressive aphasia (PPA) is a neurodegenerative disease similar to frontotemporal and semantic dementia, while having a different clinical image and anatomic pathology topography. Nonetheless, they are often included under an umbrella term: frontotemporal lobar degeneration (FTLD). In the study, examples of diagnosing PPA are presented through the multidisciplinary lens of specialists from different fields (neurologists, psychiatrists, clinical speech therapists, clinical neuropsychologists and others) using a variety of diagnostic tools such as MR, PET/CT, genetic screening and neuropsychological and logopedic methods. Thanks to that, specialists can get a better and clearer understanding of PPA diagnosis. The study summarizes the concrete procedures and results of different specialists while diagnosing PPA in a patient of younger middle age and illustrates the importance of multidisciplinary approach to differential diagnosis of PPA.
Keywords: Primary progressive aphasia, etiology, diagnosis, younger middle age.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 453
382 Parkinsons Disease Classification using Neural Network and Feature Selection
Authors: Anchana Khemphila, Veera Boonjing
In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.
Keywords: Data mining, classification, Parkinson disease, artificial neural networks, feature selection, information gain.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3579
381 Rule-Based Expert System for Headache Diagnosis and Medication Recommendation
Authors: Noura Al-Ajmi, Mohammed A. Almulla
Abstract:With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.
Keywords: Headache diagnosis system, treatment recommender system, rule-based expert system.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 499
380 Segmentation of Lungs from CT Scan Images for Early Diagnosis of Lung Cancer
Authors: Nisar Ahmed Memon, Anwar Majid Mirza, S.A.M. Gilani
Abstract:Segmentation is an important step in medical image analysis and classification for radiological evaluation or computer aided diagnosis. The CAD (Computer Aided Diagnosis ) of lung CT generally first segment the area of interest (lung) and then analyze the separately obtained area for nodule detection in order to diagnosis the disease. For normal lung, segmentation can be performed by making use of excellent contrast between air and surrounding tissues. However this approach fails when lung is affected by high density pathology. Dense pathologies are present in approximately a fifth of clinical scans, and for computer analysis such as detection and quantification of abnormal areas it is vital that the entire and perfectly lung part of the image is provided and no part, as present in the original image be eradicated. In this paper we have proposed a lung segmentation technique which accurately segment the lung parenchyma from lung CT Scan images. The algorithm was tested against the 25 datasets of different patients received from Ackron Univeristy, USA and AGA Khan Medical University, Karachi, Pakistan.
Keywords: Computer Aided Diagnosis, Medical ImageProcessing, Region Growing, Segmentation, Thresholding,Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2446
379 A Comparative Study into Observer based Fault Detection and Diagnosis in DC Motors: Part-I
Authors: Padmakumar S., Vivek Agarwal, Kallol Roy
Abstract:A model based fault detection and diagnosis technique for DC motor is proposed in this paper. Fault detection using Kalman filter and its different variants are compared. Only incipient faults are considered for the study. The Kalman Filter iterations and all the related computations required for fault detection and fault confirmation are presented. A second order linear state space model of DC motor is used for this work. A comparative assessment of the estimates computed from four different observers and their relative performance is evaluated.
Keywords: DC motor model, Fault detection and diagnosis Kalman Filter, Unscented Kalman FilterProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2355
378 Data Mining Techniques in Computer-Aided Diagnosis: Non-Invasive Cancer Detection
Authors: Florin Gorunescu
Abstract:Diagnosis can be achieved by building a model of a certain organ under surveillance and comparing it with the real time physiological measurements taken from the patient. This paper deals with the presentation of the benefits of using Data Mining techniques in the computer-aided diagnosis (CAD), focusing on the cancer detection, in order to help doctors to make optimal decisions quickly and accurately. In the field of the noninvasive diagnosis techniques, the endoscopic ultrasound elastography (EUSE) is a recent elasticity imaging technique, allowing characterizing the difference between malignant and benign tumors. Digitalizing and summarizing the main EUSE sample movies features in a vector form concern with the use of the exploratory data analysis (EDA). Neural networks are then trained on the corresponding EUSE sample movies vector input in such a way that these intelligent systems are able to offer a very precise and objective diagnosis, discriminating between benign and malignant tumors. A concrete application of these Data Mining techniques illustrates the suitability and the reliability of this methodology in CAD.
Keywords: Endoscopic ultrasound elastography, exploratorydata analysis, neural networks, non-invasive cancer detection.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1737
377 A Two-Stage Expert System for Diagnosis of Leukemia Based on Type-2 Fuzzy Logic
Authors: Ali Akbar Sadat Asl
Diagnosis and deciding about diseases in medical fields is facing innate uncertainty which can affect the whole process of treatment. This decision is made based on expert knowledge and the way in which an expert interprets the patient's condition, and the interpretation of the various experts from the patient's condition may be different. Fuzzy logic can provide mathematical modeling for many concepts, variables, and systems that are unclear and ambiguous and also it can provide a framework for reasoning, inference, control, and decision making in conditions of uncertainty. In systems with high uncertainty and high complexity, fuzzy logic is a suitable method for modeling. In this paper, we use type-2 fuzzy logic for uncertainty modeling that is in diagnosis of leukemia. The proposed system uses an indirect-direct approach and consists of two stages: In the first stage, the inference of blood test state is determined. In this step, we use an indirect approach where the rules are extracted automatically by implementing a clustering approach. In the second stage, signs of leukemia, duration of disease until its progress and the output of the first stage are combined and the final diagnosis of the system is obtained. In this stage, the system uses a direct approach and final diagnosis is determined by the expert. The obtained results show that the type-2 fuzzy expert system can diagnose leukemia with the average accuracy about 97%.
Keywords: Expert system, leukemia, medical diagnosis, type-2 fuzzy logic.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 857
376 Feature Selection for Breast Cancer Diagnosis: A Case-Based Wrapper Approach
Authors: Mohammad Darzi, Ali AsgharLiaei, Mahdi Hosseini, HabibollahAsghari
Abstract:This article addresses feature selection for breast cancer diagnosis. The present process contains a wrapper approach based on Genetic Algorithm (GA) and case-based reasoning (CBR). GA is used for searching the problem space to find all of the possible subsets of features and CBR is employed to estimate the evaluation result of each subset. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer (WDBC) dataset.
Keywords: Case-based reasoning; Breast cancer diagnosis; Genetic algorithm; Wrapper feature selectionProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2683
375 On Fault Diagnosis of Asynchronous Sequential Machines with Parallel Composition
Authors: Jung-Min Yang
Abstract:Fault diagnosis of composite asynchronous sequential machines with parallel composition is addressed in this paper. An adversarial input can infiltrate one of two submachines comprising the composite asynchronous machine, causing an unauthorized state transition. The objective is to characterize the condition under which the controller can diagnose any fault occurrence. Two control configurations, state feedback and output feedback, are considered in this paper. In the case of output feedback, the exact estimation of the state is impossible since the current state is inaccessible and the output feedback is given as the form of burst. A simple example is provided to demonstrate the proposed methodology.
Keywords: Asynchronous sequential machines, parallel composition, fault diagnosis.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 848
374 Design of a Pneumonia Ontology for Diagnosis Decision Support System
Authors: Sabrina Azzi, Michal Iglewski, Véronique Nabelsi
Diagnosis error problem is frequent and one of the most important safety problems today. One of the main objectives of our work is to propose an ontological representation that takes into account the diagnostic criteria in order to improve the diagnostic. We choose pneumonia disease since it is one of the frequent diseases affected by diagnosis errors and have harmful effects on patients. To achieve our aim, we use a semi-automated method to integrate diverse knowledge sources that include publically available pneumonia disease guidelines from international repositories, biomedical ontologies and electronic health records. We follow the principles of the Open Biomedical Ontologies (OBO) Foundry. The resulting ontology covers symptoms and signs, all the types of pneumonia, antecedents, pathogens, and diagnostic testing. The first evaluation results show that most of the terms are covered by the ontology. This work is still in progress and represents a first and major step toward a development of a diagnosis decision support system for pneumonia.
Keywords: Clinical decision support system, diagnostic errors, ontology, pneumonia.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 744
373 A Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Wavelet Transformation and Fractal Dimension as a Preprocessor
This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with  and , which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.
Keywords: Analog circuits, fault diagnosis, tolerance, wavelettransform, fractal dimension, box dimension.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2053
372 The Contribution of the PCR-Enzymatic Digestion in the Positive Diagnosis of Proximal Spinal Muscular Atrophy in the Moroccan Population
Authors: H. Merhni, A. Sbiti, I. Ratbi, A. Sefiani
Abstract:The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco.
Keywords: Exon7, PCR-digestion, SMA, SMN gene.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 857
371 Expert-Driving-Criteria Based on Fuzzy Logic Approach for Intelligent Driving Diagnosis
Authors: Andrés C. Cuervo Pinilla, Christian G. Quintero M., Chinthaka Premachandra
Abstract:This paper considers people’s driving skills diagnosis under real driving conditions. In that sense, this research presents an approach that uses GPS signals which have a direct correlation with driving maneuvers. Besides, it is presented a novel expert-driving-criteria approximation using fuzzy logic which seeks to analyze GPS signals in order to issue an intelligent driving diagnosis. Based on above, this works presents in the first section the intelligent driving diagnosis system approach in terms of its own characteristics properties, explaining in detail significant considerations about how an expert-driving-criteria approximation must be developed. In the next section, the implementation of our developed system based on the proposed fuzzy logic approach is explained. Here, a proposed set of rules which corresponds to a quantitative abstraction of some traffics laws and driving secure techniques seeking to approach an expert-driving- criteria approximation is presented. Experimental testing has been performed in real driving conditions. The testing results show that the intelligent driving diagnosis system qualifies driver’s performance quantitatively with a high degree of reliability.
Keywords: Driver support systems, intelligent transportation systems, fuzzy logic, real time data processing.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1068
370 An Investigative Study into Observer based Non-Invasive Fault Detection and Diagnosis in Induction Motors
Authors: Padmakumar S., Vivek Agarwal, Kallol Roy
Abstract:A new observer based fault detection and diagnosis scheme for predicting induction motors- faults is proposed in this paper. Prediction of incipient faults, using different variants of Kalman filter and their relative performance are evaluated. Only soft faults are considered for this work. The data generation, filter convergence issues, hypothesis testing and residue estimates are addressed. Simulink model is used for data generation and various types of faults are considered. A comparative assessment of the estimates of different observers associated with these faults is included.
Keywords: Extended Kalman Filter, Fault detection and diagnosis, Induction motor model, Unscented Kalman FilterProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1760
369 Biological Diagnosis and Physiopathology of von Willebrand-s Disease in a Part of the Algerian Population in the East and the South
Authors: H. Djaara, M. Yahia, H. Bousselsela, N Khelif, A. Zidani, S. Benbia.
Abstract:Von Willebrand-s disease is the most common inherited bleeding disorder in humans, it caused by qualitative abnormalities of the von Willebrand factor (vWF). Our objective is to determine the prevalence of this disease at part of the Algerian population in the East and the South by a biological diagnosis based on specific biological tests (automated platelet count, the bleeding time (TS), the time of cephalin + activator (TCA), measure of the prothrombin rate (TP), vWF rate and factor VIII rate, Molecular electrophoresis of vWF multimers in agarose gel in the presence of SDS). Four patients of type III or severe Willebrand-s disease were found on 200 suspect cases. All cases are showed a deficit in vWF rate (< 5%), and factor VIII (P<0, 0001), and lengthening very significantly high of the TCA (P<0, 0001) and of the bleeding time (P<0,0001), with a normal blood platelet rate (P=0,7433) and a normal prothrombin rate (P=0,5808), an absence of all the multimers of vWF in plasma patients. The severe Willebrand-s disease is not only one pathology of primary haemostasis, but it can be accompanied by coagulation-s anomaly due to deficit in factor VIII. At this studied population, von Willebrand-s disease is less frequent (2%) than other hemorrhagic syndromes identified by the differential diagnosis like the thrombocytopenia (36%).
Keywords: Von Willebrand's disease, differential diagnosis, von Willebrand factor, factor VIII, biological diagnosis, thrombocytopenia.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1615