Search results for: fault diagnosis and tolerance
193 Intelligent System for Breast Cancer Prognosis using Multiwavelet Packets and Neural Network
Authors: Sepehr M.H.Jamarani, M.H.Moradi, H.Behnam, G.A.Rezai Rad
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This paper presents an approach for early breast cancer diagnostic by employing combination of artificial neural networks (ANN) and multiwaveletpacket based subband image decomposition. The microcalcifications correspond to high-frequency components of the image spectrum, detection of microcalcifications is achieved by decomposing the mammograms into different frequency subbands,, reconstructing the mammograms from the subbands containing only high frequencies. For this approach we employed different types of multiwaveletpacket. We used the result as an input of neural network for classification. The proposed methodology is tested using the Nijmegen and the Mammographic Image Analysis Society (MIAS) mammographic databases and images collected from local hospitals. Results are presented as the receiver operating characteristic (ROC) performance and are quantified by the area under the ROC curve.Keywords: Breast cancer, neural networks, diagnosis, multiwavelet packet, microcalcification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1400192 Towards a Sustainable Regeneration: The Case Study of the San Mateo Neighborhood, in Jerez de la Frontera (Andalusia)
Authors: J.L. Higuera Trujillo, F.J. Montero Fernández
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Based on different experiences in the historic centers of Spain, we propose an global strategy for the regeneration of the pre-tertiary fabrics and its application to the specific case of San Mateo neighborhood, in Jerez de la Frontera (Andalusia), through a diagnosis that focus particularly on the punishments the last-decade economic situation (building boom and crisis) and shows the tragic transition from economic center to an imminent disappearance with an image similar to the ruins of war, due to the loss of their traditional roles. From it we will learn their historically-tested mechanisms of environment adaptation, which distill the vernacular architecture essence and that we will apply to our strategy of action based on a dotacional-and-free-space rhizome which rediscovers its hidden character. The architectural fact will be crystallized in one of the example-pieces proposed: The Artistic Revitalization Center.Keywords: Jerez de la Frontera, pre-tertiary fabrics, sustainable architecture, urban regeneration
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1310191 Bayesian Network Based Intelligent Pediatric System
Authors: Jagmohan Mago, Parvinder S. Sandhu, Neeru Chawla
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In this paper, a Bayesian Network (BN) based system is presented for providing clinical decision support to healthcare practitioners in rural or remote areas of India for young infants or children up to the age of 5 years. The government is unable to appoint child specialists in rural areas because of inadequate number of available pediatricians. It leads to a high Infant Mortality Rate (IMR). In such a scenario, Intelligent Pediatric System provides a realistic solution. The prototype of an intelligent system has been developed that involves a knowledge component called an Intelligent Pediatric Assistant (IPA); and User Agents (UA) along with their Graphical User Interfaces (GUI). The GUI of UA provides the interface to the healthcare practitioner for submitting sign-symptoms and displaying the expert opinion as suggested by IPA. Depending upon the observations, the IPA decides the diagnosis and the treatment plan. The UA and IPA form client-server architecture for knowledge sharing.Keywords: Network, Based Intelligent, Pediatric System
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2216190 An Application of Path Planning Algorithms for Autonomous Inspection of Buried Pipes with Swarm Robots
Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov
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This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.
Keywords: Autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1014189 Words Reordering based on Statistical Language Model
Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou
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There are multiple reasons to expect that detecting the word order errors in a text will be a difficult problem, and detection rates reported in the literature are in fact low. Although grammatical rules constructed by computer linguists improve the performance of grammar checker in word order diagnosis, the repairing task is still very difficult. This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The comparative advantage of this method is that works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns.Keywords: Permutations filtering, Statistical languagemodel N-grams, Word order errors
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1587188 EEG-Based Screening Tool for School Student’s Brain Disorders Using Machine Learning Algorithms
Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary
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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.
Keywords: ADHD, autism, epilepsy, EEG, SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 997187 Fusion of Colour and Depth Information to Enhance Wound Tissue Classification
Authors: Darren Thompson, Philip Morrow, Bryan Scotney, John Winder
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Patients with diabetes are susceptible to chronic foot wounds which may be difficult to manage and slow to heal. Diagnosis and treatment currently rely on the subjective judgement of experienced professionals. An objective method of tissue assessment is required. In this paper, a data fusion approach was taken to wound tissue classification. The supervised Maximum Likelihood and unsupervised Multi-Modal Expectation Maximisation algorithms were used to classify tissues within simulated wound models by weighting the contributions of both colour and 3D depth information. It was found that, at low weightings, depth information could show significant improvements in classification accuracy when compared to classification by colour alone, particularly when using the maximum likelihood method. However, larger weightings were found to have an entirely negative effect on accuracy.Keywords: Classification, data fusion, diabetic foot, stereophotogrammetry, tissue colour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1710186 An ANN-Based Predictive Model for Diagnosis and Forecasting of Hypertension
Authors: O. O. Obe, V. Balanica, E. Neagoe
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The effects of hypertension are often lethal thus its early detection and prevention is very important for everybody. In this paper, a neural network (NN) model was developed and trained based on a dataset of hypertension causative parameters in order to forecast the likelihood of occurrence of hypertension in patients. Our research goal was to analyze the potential of the presented NN to predict, for a period of time, the risk of hypertension or the risk of developing this disease for patients that are or not currently hypertensive. The results of the analysis for a given patient can support doctors in taking pro-active measures for averting the occurrence of hypertension such as recommendations regarding the patient behavior in order to lower his hypertension risk. Moreover, the paper envisages a set of three example scenarios in order to determine the age when the patient becomes hypertensive, i.e. determine the threshold for hypertensive age, to analyze what happens if the threshold hypertensive age is set to a certain age and the weight of the patient if being varied, and, to set the ideal weight for the patient and analyze what happens with the threshold of hypertensive age.
Keywords: Neural Network, hypertension, data set, training set, supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1660185 Promotion of Growth and Modulation of As- Induced Stress Ethylene in Maize by As- Tolerant ACC Deaminase Producing Bacteria
Authors: Charlotte C. Shagol, Tongmin Sa
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One of the major pollutants in the environment is arsenic (As). Due to the toxic effects of As to all organisms, its remediation is necessary. Conventional technologies used in the remediation of As contaminated soils are expensive and may even compromise the structure of the soil. An attractive alternative is phytoremediation, which is the use of plants which can take up the contaminant in their tissues. Plant growth promoting bacteria (PGPB) has been known to enhance growth of plants through several mechanisms such as phytohormone production, phosphate solubilization, siderophore production and 1-aminocyclopropane-1- carboxylate (ACC) deaminase production, which is an essential trait that aids plants especially under stress conditions such as As stress. Twenty one bacteria were isolated from As-contaminated soils in the vicinity of the Janghang Smelter in Chungnam Province, South Korea. These exhibited high tolerance to either arsenite (As III) or arsenate (As V) or both. Most of these isolates possess several plant growth promoting traits which can be potentially exploited to increase phytoremediation efficiency. Among the identified isolates is Pseudomonas sp. JS1215, which produces ACC deaminase, indole acetic acid (IAA), and siderophore. It also has the ability to solubilize phosphate. Inoculation of JS1215 significantly enhanced root and shoot length and biomass accumulation of maize under normal conditions. In the presence of As, particularly in lower As level, inoculation of JS1215 slightly increased root length and biomass. Ethylene increased with increasing As concentration, but was reduced by JS1215 inoculation. JS1215 can be a potential bioinoculant for increasing phytoremediation efficiency.
Keywords: As-tolerant bacteria, plant growth promoting bacteria, As stress, phytoremediation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1722184 Auditor with the Javanese Characters and Non Javanese in Audit Firm: Conflict of Interest
Authors: Krisna Damayanti, Lilis Ardini
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Many issues about the relationship between auditors in auditing practices with its stakeholders often heard. It appears in perspectives of bringing out the variety of phenomena affecting from the audit practice of greed and not appreciating from the independency of the audit profession and professional code of ethics. It becomes a logical consequence in practicing of capitalism in accounting. The main purpose of this article would like to uncover the existing auditing practices in Indonesia, especially in Java that associated with a strong influence of Javanese culture with reluctant /”shy", politely, "legowo (gratefully accepted)", "ngemong" (friendly), "not mentholo" (lenient), "tepo seliro" (tolerance), "ngajeni" (respectful), "acquiescent" and also reveals its relationships with Non Javanese culture in facing the conflict of interest in practical of auditing world. The method used by interpretive approach that emphasizes the role of language, interpret and understand and see social reality as something other than a label, name or concept. Global practices in auditing of each country have particular cultures that affect the standard set by those regulatory standards results the adaptation of IAS. The majority of parties in Indonesia is dominated by Javanese racial regulators, so Java culture is embedded in every audit practices and those conditions in Java leads auditors in having similar behaviour, sometimes interfere with standard Java code of conduct must be executed by an auditor. Auditors who live in Java have the characters of Javanese culture that is hard to avoid in the audit practice. However, practically, the auditors still are relevant in their profession.
Keywords: Auditors, java, character, profession, code of ethics, client.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2331183 Monitoring the Effect of Doxorubicin Liposomal in VX2 Tumor Using Magnetic Resonance Imaging
Authors: Ren-Jy Ben, Jo-Chi Jao, Chiu-Ya Liao, Ya-Ru Tsai, Lain-Chyr Hwang, Po-Chou Chen
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Cancer is still one of the serious diseases threatening the lives of human beings. How to have an early diagnosis and effective treatment for tumors is a very important issue. The animal carcinoma model can provide a simulation tool for the studies of pathogenesis, biological characteristics, and therapeutic effects. Recently, drug delivery systems have been rapidly developed to effectively improve the therapeutic effects. Liposome plays an increasingly important role in clinical diagnosis and therapy for delivering a pharmaceutic or contrast agent to the targeted sites. Liposome can be absorbed and excreted by the human body, and is well known that no harm to the human body. This study aimed to compare the therapeutic effects between encapsulated (doxorubicin liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox) anti-tumor drugs using magnetic resonance imaging (MRI). Twenty-four New Zealand rabbits implanted with VX2 carcinoma at left thighs were classified into three groups: control group (untreated), Dox-treated group, and LipoDox-treated group, 8 rabbits for each group. MRI scans were performed three days after tumor implantation. A 1.5T GE Signa HDxt whole body MRI scanner with a high resolution knee coil was used in this study. After a 3-plane localizer scan was performed, three-dimensional (3D) fast spin echo (FSE) T2-weighted Images (T2WI) was used for tumor volumetric quantification. Afterwards, two-dimensional (2D) spoiled gradient recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was used for tumor perfusion evaluation. DCE-MRI was designed to acquire four baseline images, followed by contrast agent Gd-DOTA injection through the ear vein of rabbit. A series of 32 images were acquired to observe the signals change over time in the tumor and muscle. The MRI scanning was scheduled on a weekly basis for a period of four weeks to observe the tumor progression longitudinally. The Dox and LipoDox treatments were prescribed 3 times in the first week immediately after the first MRI scan; i.e. 3 days after VX2 tumor implantation. ImageJ was used to quantitate tumor volume and time course signal enhancement on DCE images. The changes of tumor size showed that the growth of VX2 tumors was effectively inhibited for both LipoDox-treated and Dox-treated groups. Furthermore, the tumor volume of LipoDox-treated group was significantly lower than that of Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is significantly lower than that of the other two groups, which implies that targeted therapeutic drug remained in the tumor tissue. This study provides a radiation-free and non-invasive MRI method for therapeutic monitoring of targeted liposome on an animal tumor model.Keywords: Doxorubicin, dynamic contrast-enhanced MRI, lipodox, magnetic resonance imaging, VX2 tumor model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1991182 Observations about the Principal Components Analysis and Data Clustering Techniques in the Study of Medical Data
Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz
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The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.Keywords: Data clustering, medical data, principal components analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1501181 Antioxidant Capacity of Maize Corn under Drought Stress from the Different Zones of Growing
Authors: Astghik R. Sukiasyan
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The semidental sweet maize of Armenian population under drought stress and pollution by some heavy metals (HMs) in sites along the river Debet was studied. Accordingly, the objective of this work was to investigate the antioxidant status of maize plant in order to identify simple and reliable criteria for assessing the degree of adaptation of plants to abiotic stress of drought and HMs. It was found that in the case of removal from the mainstream of the river, the antioxidant status of the plant varies. As parameters, the antioxidant status of the plant has been determined by the activity of malondialdehyde (MDA) and Ferric Reducing Ability of Plasma (FRAP), taking into account the characteristics of natural drought of this region. The possibility of using some indicators which characterized the antioxidant status of the plant was concluded. The criteria for assessing the extent of environmental pollution could be HMs. This fact can be used for the early diagnosis of diseases in the population who lives in these areas and uses corn as the main food.Keywords: Antioxidant status, maize corn, drought stress, heavy metal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1314180 LabVIEW with Fuzzy Logic Controller Simulation Panel for Condition Monitoring of Oil and Dry Type Transformer
Authors: N. A. Muhamad, S.A.M. Ali
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Condition monitoring of electrical power equipment has attracted considerable attention for many years. The aim of this paper is to use Labview with Fuzzy Logic controller to build a simulation system to diagnose transformer faults and monitor its condition. The front panel of the system was designed using LabVIEW to enable computer to act as customer-designed instrument. The dissolved gas-in-oil analysis (DGA) method was used as technique for oil type transformer diagnosis; meanwhile terminal voltages and currents analysis method was used for dry type transformer. Fuzzy Logic was used as expert system that assesses all information keyed in at the front panel to diagnose and predict the condition of the transformer. The outcome of the Fuzzy Logic interpretation will be displayed at front panel of LabVIEW to show the user the conditions of the transformer at any time.Keywords: LabVIEW, Fuzzy Logic, condition monitoring, oiltransformer, dry transformer, DGA, terminal values.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3232179 Diagnosis on Environmental Impacts of Tourism at Caju Beach in Palmas, Tocantins, Brazil
Authors: Mary L. G. S. Senna, Veruska, C. Dutra, Jr., Keity L. F. Oliveira, Patrícia A. Santos, Alana C. M. Santana
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Environmental impacts are the changes in the physical, chemical or biological properties of natural areas that are most often caused by human actions on the environment and which have consequences for human health, society and the elements of nature. The identification of the environmental impacts is important so that they are mitigated, and above all that the mitigating measures are applied in the area. This work aims to identify the environmental impacts generated in the Praia do Caju area in the city of Palmas/Brazil and show that the lack of structure on the beach intensifies the environmental impacts. The present work was carried out having as parameter, the typologies of exploratory and descriptive and quantitative research through a matrix of environmental impacts through direct observation and registration. The study took place during the holidays from August to December 2016 and photographic record of impacts. From the collected data it was possible to verify that Caju beach suffers constant degradation due to irregular deposition.
Keywords: Leisure, tourism, environmental impacts, Brazil.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 735178 Medical Advances in Diagnosing Neurological and Genetic Disorders
Authors: Simon B. N. Thompson
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Retinoblastoma is a rare type of childhood genetic cancer that affects children worldwide. The diagnosis is often missed due to lack of education and difficulty in presentation of the tumor. Frequently, the tumor on the retina is noticed by photography when the red-eye flash, commonly seen in normal eyes, is not produced. Instead, a yellow or white colored patch is seen or the child has a noticeable strabismus. Early detection can be life-saving though often results in removal of the affected eye. Remaining functioning in the healthy eye when the child is young has resulted in super-vision and high or above-average intelligence. Technological advancement of cameras has helped in early detection. Brain imaging has also made possible early detection of neurological diseases and, together with the monitoring of cortisol levels and yawning frequency, promises to be the next new early diagnostic tool for the detection of neurological diseases where cortisol insufficiency is particularly salient, such as multiple sclerosis and Cushing’s disease.Keywords: Cortisol, Neurological Disease, Retinoblastoma, Thompson Cortisol Hypothesis, Yawning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1327177 Statistical Models of Network Traffic
Authors: Barath Kumar, Oliver Niggemann, Juergen Jasperneite
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Model-based approaches have been applied successfully to a wide range of tasks such as specification, simulation, testing, and diagnosis. But one bottleneck often prevents the introduction of these ideas: Manual modeling is a non-trivial, time-consuming task. Automatically deriving models by observing and analyzing running systems is one possible way to amend this bottleneck. To derive a model automatically, some a-priori knowledge about the model structure–i.e. about the system–must exist. Such a model formalism would be used as follows: (i) By observing the network traffic, a model of the long-term system behavior could be generated automatically, (ii) Test vectors can be generated from the model, (iii) While the system is running, the model could be used to diagnose non-normal system behavior. The main contribution of this paper is the introduction of a model formalism called 'probabilistic regression automaton' suitable for the tasks mentioned above.Keywords: Model-based approach, Probabilistic regression automata, Statistical models and Timed automata.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1540176 An Evaluation of Sputum Smear Conversion and Haematological Parameter Alteration in Early Detection Period of New Pulmonary Tuberculosis (PTB) Patients
Authors: Tasnuva Tamanna, Sanjida Halim Topa
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Sputum smear conversion after one month of antituberculosis therapy in new smear positive pulmonary tuberculosis patients (PTB+) is a vital indicator towards treatment success. The objective of this study is to determine the rate of sputum smear conversion in new PTB+ patients after one month under treatment of National Institute of Diseases of the Chest and Hospital (NIDCH). Analysis of sputum smear conversion was done by re-clinical examination with sputum smear microscopic test after one month. Socio-demographic and hematological parameters were evaluated to perceive the correlation with the disease status. Among all enrolled patients only 33.33% were available for follow up diagnosis and of them only 42.86% patients turned to smear negative. Probably this consequence is due to non-coherence to the proper disease management. 66.67% and 78.78% patients reported low haemoglobin and packed cell volume level respectively whereas 80% and 93.33% patients accounted accelerated platelet count and erythrocyte sedimentation rate correspondingly.Keywords: Followed up patients, PTB+ patients, sputum smear conversion, and sputum smear microscopic test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2171175 A Real-Time Image Change Detection System
Authors: Madina Hamiane, Amina Khunji
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Detecting changes in multiple images of the same scene has recently seen increased interest due to the many contemporary applications including smart security systems, smart homes, remote sensing, surveillance, medical diagnosis, weather forecasting, speed and distance measurement, post-disaster forensics and much more. These applications differ in the scale, nature, and speed of change. This paper presents an application of image processing techniques to implement a real-time change detection system. Change is identified by comparing the RGB representation of two consecutive frames captured in real-time. The detection threshold can be controlled to account for various luminance levels. The comparison result is passed through a filter before decision making to reduce false positives, especially at lower luminance conditions. The system is implemented with a MATLAB Graphical User interface with several controls to manage its operation and performance.Keywords: Image change detection, Image processing, image filtering, thresholding, B/W quantization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2563174 Concepts Extraction from Discharge Notes using Association Rule Mining
Authors: Basak Oguz Yolcular
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A large amount of valuable information is available in plain text clinical reports. New techniques and technologies are applied to extract information from these reports. In this study, we developed a domain based software system to transform 600 Otorhinolaryngology discharge notes to a structured form for extracting clinical data from the discharge notes. In order to decrease the system process time discharge notes were transformed into a data table after preprocessing. Several word lists were constituted to identify common section in the discharge notes, including patient history, age, problems, and diagnosis etc. N-gram method was used for discovering terms co-Occurrences within each section. Using this method a dataset of concept candidates has been generated for the validation step, and then Predictive Apriori algorithm for Association Rule Mining (ARM) was applied to validate candidate concepts.Keywords: association rule mining, otorhinolaryngology, predictive apriori, text mining
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614173 An Improved C-Means Model for MRI Segmentation
Authors: Ying Shen, Weihua Zhu
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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.
Keywords: Magnetic Resonance Image, C-means model, image segmentation, information entropy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 918172 Computational Methods in Official Statistics with an Example on Calculating and Predicting Diabetes Mellitus [DM] Prevalence in Different Age Groups within Australia in Future Years, in Light of the Aging Population
Authors: D. Hilton
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An analysis of the Australian Diabetes Screening Study estimated undiagnosed diabetes mellitus [DM] prevalence in a high risk general practice based cohort. DM prevalence varied from 9.4% to 18.1% depending upon the diagnostic criteria utilised with age being a highly significant risk factor. Utilising the gold standard oral glucose tolerance test, the prevalence of DM was 22-23% in those aged >= 70 years and <15% in those aged 40-59 years. Opportunistic screening in Australian general practice potentially can identify many persons with undiagnosed type 2 DM. An Australian Bureau of Statistics document published three years ago, reported the highest rate of DM in men aged 65-74 years [19%] whereas the rate for women was highest in those over 75 years [13%]. If you consider that the Australian Bureau of Statistics report in 2007 found that 13% of the population was over 65 years of age and that this will increase to 23-25% by 2056 with a further projected increase to 25-28% by 2101, obviously this information has to be factored into the equation when age related diabetes prevalence predictions are calculated. This 10-15% proportional increase of elderly persons within the population demographics has dramatic implications for the estimated number of elderly persons with DM in these age groupings. Computational methodology showing the age related demographic changes reported in these official statistical documents will be done showing estimates for 2056 and 2101 for different age groups. This has relevance for future diabetes prevalence rates and shows that along with many countries worldwide Australia is facing an increasing pandemic. In contrast Japan is expected to have a decrease in the next twenty years in the number of persons with diabetes.
Keywords: Epidemiological methods, aging, prevalence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1954171 Development of a Smart System for Measuring Strain Levels of Natural Gas and Petroleum Pipelines on Earthquake Fault Lines in Türkiye
Authors: Ahmet Yetik, Seyit Ali Kara, Cevat Özarpa
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Load changes occur on natural gas and oil pipelines due to natural disasters. The displacement of the soil around the natural gas and oil pipes due to situations that may cause erosion, such as earthquakes, landslides, and floods, is the source of this load change. The exposure of natural gas and oil pipes to variable loads causes deformation, cracks, and breaks in these pipes. Such cracks and breaks can cause significant damage to people and the environment, including the risk of explosions. Especially with the examinations made after natural disasters, it can be easily understood which of the pipes has sustained more damage in those quake-affected regions. It has been determined that earthquakes in Türkiye have caused permanent damage to pipelines. This project was initiated in response to the identification of cracks and gas leaks in the insulation gaskets placed in the pipelines, especially at the junction points. In this study, a SCADA (Supervisory Control and Data Acquisition) application has been developed to monitor load changes caused by natural disasters. The developed SCADA application monitors the changes in the x, y, and z axes of the stresses occurring in the pipes with the help of strain gauge sensors placed on the pipes. For the developed SCADA system, test setups in accordance with the standards were created during the fieldwork. The test setups created were integrated into the SCADA system, and the system was followed up. Thanks to the SCADA system developed with the field application, the load changes that will occur on the natural gas and oil pipes are instantly monitored, and the accumulations that may create a load on the pipes and their surroundings are immediately intervened, and new risks that may arise are prevented. It has contributed to energy supply security, asset management, pipeline holistic management, and overall sustainability in the industry.
Keywords: Earthquake, natural gas pipes, oil pipes, voltage measurement, landslide.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 113170 Multidimensional Performance Management
Authors: David Wiese
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In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Keywords: Data Warehousing, OLAP, Multidimensional Navigation, Performance Diagnosis, Performance Management, Performance Tuning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2135169 Legal Basis for Water Resources Management in Brazil: Case Study of the Rio Grande Basin
Authors: Janaína F. Guidolini, Jean P. H. B. Ometto, Angélica Giarolla, Peter M. Toledo, Carlos A. Valera
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The water crisis, a major problem of the 21st century, occurs mainly due to poor management. The central issue that should govern the management is the integration of the various aspects that interfere with the use of water resources and their protection, supported by legal basis. A watershed is a unit of water interacting with the physical, biotic, social, economic and cultural variables. The Brazilian law recognized river basin as the territorial management unit. Based on the diagnosis of the current situation of the water resources of the Rio Grande Basin, a discussion informed in the Brazilian legal basis was made to propose measures to fight or mitigate damages and environmental degradation in the Basin. To manage water resources more efficiently, conserve water and optimize their multiple uses, the integration of acquired scientific knowledge and management is essential. Moreover, it is necessary to monitor compliance with environmental legislation.
Keywords: Conservation of soil and water, river basin, sustainability, water governance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 985168 Hypogenic Karstification and Conduit System Controlling by Tectonic Pattern in Foundation Rocks of the Salman Farsi Dam in South-Western Iran
Authors: Mehran Koleini, Jan Louis Van Rooy, Adam Bumby
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The Salman Farsi dam project is constructed on the Ghareh Agahaj River about 140km south of Shiraz city in the Zagros Mountains of southwestern Iran. This tectonic province of south-western Iran is characterized by a simple folded sedimentary sequence. The dam foundation rocks compose of the Asmari Formation of Oligo-miocene and generally comprise of a variety of karstified carbonate rocks varying from strong to weak rocks. Most of the rocks exposed at the dam site show a primary porosity due to incomplete diagenetic recrystallization and compaction. In addition to these primary dispositions to weathering, layering conditions (frequency and orientation of bedding) and the subvertical tectonic discontinuities channeled preferably the infiltrating by deep-sited hydrothermal solutions. Consequently the porosity results to be enlarged by dissolution and the rocks are expected to be karstified and to develop cavities in correspondence of bedding, major joint planes and fault zones. This kind of karsts is named hypogenic karsts which associated to the ascendant warm solutions. Field observations indicate strong karstification and vuggy intercalations especially in the middle part of the Asmari succession. The biggest karst in the dam axis which identified by speleological investigations is Golshany Cave with volume of about 150,000 m3. The tendency of the Asmari limestone for strong dissolution can alert about the seepage from the reservoir and area of the dam locality.
Keywords: Asmari Limestone, Karstification, Salman Farsi Dam, Tectonic Pattern.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2692167 Wavelet based Image Registration Technique for Matching Dental x-rays
Authors: P. Ramprasad, H. C. Nagaraj, M. K. Parasuram
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Image registration plays an important role in the diagnosis of dental pathologies such as dental caries, alveolar bone loss and periapical lesions etc. This paper presents a new wavelet based algorithm for registering noisy and poor contrast dental x-rays. Proposed algorithm has two stages. First stage is a preprocessing stage, removes the noise from the x-ray images. Gaussian filter has been used. Second stage is a geometric transformation stage. Proposed work uses two levels of affine transformation. Wavelet coefficients are correlated instead of gray values. Algorithm has been applied on number of pre and post RCT (Root canal treatment) periapical radiographs. Root Mean Square Error (RMSE) and Correlation coefficients (CC) are used for quantitative evaluation. Proposed technique outperforms conventional Multiresolution strategy based image registration technique and manual registration technique.Keywords: Diagnostic imaging, geometric transformation, image registration, multiresolution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1762166 Neural Network based Texture Analysis of Liver Tumor from Computed Tomography Images
Authors: K.Mala, V.Sadasivam, S.Alagappan
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Advances in clinical medical imaging have brought about the routine production of vast numbers of medical images that need to be analyzed. As a result an enormous amount of computer vision research effort has been targeted at achieving automated medical image analysis. Computed Tomography (CT) is highly accurate for diagnosing liver tumors. This study aimed to evaluate the potential role of the wavelet and the neural network in the differential diagnosis of liver tumors in CT images. The tumors considered in this study are hepatocellular carcinoma, cholangio carcinoma, hemangeoma and hepatoadenoma. Each suspicious tumor region was automatically extracted from the CT abdominal images and the textural information obtained was used to train the Probabilistic Neural Network (PNN) to classify the tumors. Results obtained were evaluated with the help of radiologists. The system differentiates the tumor with relatively high accuracy and is therefore clinically useful.
Keywords: Fuzzy c means clustering, texture analysis, probabilistic neural network, LVQ neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2988165 Behaviour of Base-Isolated Structures with High Initial Isolator Stiffness
Authors: Ajay Sharma, R.S. Jangid
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Analytical seismic response of multi-story building supported on base isolation system is investigated under real earthquake motion. The superstructure is idealized as a shear type flexible building with lateral degree-of-freedom at each floor. The force-deformation behaviour of the isolation system is modelled by the bi-linear behaviour which can be effectively used to model all isolation systems in practice. The governing equations of motion of the isolated structural system are derived. The response of the system is obtained numerically by step-by-method under three real recorded earthquake motions and pulse motions associated in the near-fault earthquake motion. The variation of the top floor acceleration, interstory drift, base shear and bearing displacement of the isolated building is studied under different initial stiffness of the bi-linear isolation system. It was observed that the high initial stiffness of the isolation system excites higher modes in base-isolated structure and generate floor accelerations and story drift. Such behaviour of the base-isolated building especially supported on sliding type of isolation systems can be detrimental to sensitive equipment installed in the building. On the other hand, the bearing displacement and base shear found to reduce marginally with the increase of the initial stiffness of the initial stiffness of the isolation system. Further, the above behaviour of the base-isolated building was observed for different parameters of the bearing (i.e. post-yield stiffness and characteristic strength) and earthquake motions (i.e. real time history as well as pulse type motion).Keywords: base isolation, base shear, bi-linear, earthquake, floor accelerations, inter-story drift, multi-story building, pulsemotion, stiffness ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2307164 A Predictive Rehabilitation Software for Cerebral Palsy Patients
Authors: J. Bouchard, B. Prosperi, G. Bavre, M. Daudé, E. Jeandupeux
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Young patients suffering from Cerebral Palsy are facing difficult choices concerning heavy surgeries. Diagnosis settled by surgeons can be complex and on the other hand decision for patient about getting or not such a surgery involves important reflection effort. Proposed software combining prediction for surgeries and post surgery kinematic values, and from 3D model representing the patient is an innovative tool helpful for both patients and medicine professionals. Beginning with analysis and classification of kinematics values from Data Base extracted from gait analysis in 3 separated clusters, it is possible to determine close similarity between patients. Prediction surgery best adapted to improve a patient gait is then determined by operating a suitable preconditioned neural network. Finally, patient 3D modeling based on kinematic values analysis, is animated thanks to post surgery kinematic vectors characterizing the closest patient selected from patients clustering.
Keywords: Cerebral Palsy, Clustering, Crouch Gait, 3-D Modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2007