Search results for: fault detection and identification
672 Audio Watermarking Based on Compression-expansion Technique
Authors: Say Wei Foo, Qi Dong
Abstract:
A novel robust audio watermarking scheme is proposed in this paper. In the proposed scheme, the host audio signals are segmented into frames. Two consecutive frames are assessed if they are suitable to represent a watermark bit. If so, frequency transform is performed on these two frames. The compressionexpansion technique is adopted to generate distortion over the two frames. The distortion is used to represent one watermark bit. Psychoacoustic model is applied to calculate local auditory mask to ensure that the distortion is not audible. The watermarking schemes using mono and stereo audio signals are designed differently. The correlation-based detection method is used to detect the distortion and extract embedded watermark bits. The experimental results show that the quality degradation caused by the embedded watermarks is perceptually transparent and the proposed schemes are very robust against different types of attacks.Keywords: Audio watermarking, Compression-expansion, Stereo signals, Robustness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1632671 A Comparison and Analysis of Name Matching Algorithms
Authors: Chakkrit Snae
Abstract:
Names are important in many societies, even in technologically oriented ones which use e.g. ID systems to identify individual people. Names such as surnames are the most important as they are used in many processes, such as identifying of people and genealogical research. On the other hand variation of names can be a major problem for the identification and search for people, e.g. web search or security reasons. Name matching presumes a-priori that the recorded name written in one alphabet reflects the phonetic identity of two samples or some transcription error in copying a previously recorded name. We add to this the lode that the two names imply the same person. This paper describes name variations and some basic description of various name matching algorithms developed to overcome name variation and to find reasonable variants of names which can be used to further increasing mismatches for record linkage and name search. The implementation contains algorithms for computing a range of fuzzy matching based on different types of algorithms, e.g. composite and hybrid methods and allowing us to test and measure algorithms for accuracy. NYSIIS, LIG2 and Phonex have been shown to perform well and provided sufficient flexibility to be included in the linkage/matching process for optimising name searching.Keywords: Data mining, name matching algorithm, nominaldata, searching system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11066670 Local Linear Model Tree (LOLIMOT) Reconfigurable Parallel Hardware
Authors: A. Pedram, M. R. Jamali, T. Pedram, S. M. Fakhraie, C. Lucas
Abstract:
Local Linear Neuro-Fuzzy Models (LLNFM) like other neuro- fuzzy systems are adaptive networks and provide robust learning capabilities and are widely utilized in various applications such as pattern recognition, system identification, image processing and prediction. Local linear model tree (LOLIMOT) is a type of Takagi-Sugeno-Kang neuro fuzzy algorithm which has proven its efficiency compared with other neuro fuzzy networks in learning the nonlinear systems and pattern recognition. In this paper, a dedicated reconfigurable and parallel processing hardware for LOLIMOT algorithm and its applications are presented. This hardware realizes on-chip learning which gives it the capability to work as a standalone device in a system. The synthesis results on FPGA platforms show its potential to improve the speed at least 250 of times faster than software implemented algorithms.
Keywords: LOLIMOT, hardware, neurofuzzy systems, reconfigurable, parallel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3863669 Words Reordering based on Statistical Language Model
Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou
Abstract:
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 1572668 Predictive Modelling Techniques in Sediment Yield and Hydrological Modelling
Authors: Adesoji T. Jaiyeola, Josiah Adeyemo
Abstract:
This paper presents an extensive review of literature relevant to the modelling techniques adopted in sediment yield and hydrological modelling. Several studies relating to sediment yield are discussed. Many research areas of sedimentation in rivers, runoff and reservoirs are presented. Different types of hydrological models, different methods employed in selecting appropriate models for different case studies are analysed. Applications of evolutionary algorithms and artificial intelligence techniques are discussed and compared especially in water resources management and modelling. This review concentrates on Genetic Programming (GP) and fully discusses its theories and applications. The successful applications of GP as a soft computing technique were reviewed in sediment modelling. Some fundamental issues such as benchmark, generalization ability, bloat, over-fitting and other open issues relating to the working principles of GP are highlighted. This paper concludes with the identification of some research gaps in hydrological modelling and sediment yield.Keywords: Artificial intelligence, evolutionary algorithm, genetic programming, sediment yield.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1847667 Identification and Analysis of Binding Site Residues in Protein-Protein Complexes
Authors: M. Michael Gromiha, Kiyonobu Yokota, Kazuhiko Fukui
Abstract:
We have developed an energy based approach for identifying the binding sites and important residues for binding in protein-protein complexes. We found that the residues and residuepairs with charged and aromatic side chains are important for binding. These residues influence to form cation-¤Ç, electrostatic and aromatic interactions. Our observation has been verified with the experimental binding specificity of protein-protein complexes and found good agreement with experiments. The analysis on surrounding hydrophobicity reveals that the binding residues are less hydrophobic than non-binding sites, which suggests that the hydrophobic core are important for folding and stability whereas the surface seeking residues play a critical role in binding. Further, the propensity of residues in the binding sites of receptors and ligands, number of medium and long-range contacts, and influence of neighboring residues will be discussed.
Keywords: Protein-protein interactions, energy based approach;binding sites, propensity, long-range contacts, hydrophobicity
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1385666 Fast Facial Feature Extraction and Matching with Artificial Face Models
Authors: Y. H. Tsai, Y. W. Chen
Abstract:
Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy.Keywords: Facial feature extraction, AdaBoost, Active shapemodel, Hausdorff distance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1796665 Vehicle Type Classification with Geometric and Appearance Attributes
Authors: Ghada S. Moussa
Abstract:
With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management.
This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.
Keywords: Appearance attributes, Geometric attributes, Support vector machine, Vehicle classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4260664 Rapid Study on Feature Extraction and Classification Models in Healthcare Applications
Authors: S. Sowmyayani
Abstract:
The advancement of computer-aided design helps the medical force and security force. Some applications include biometric recognition, elderly fall detection, face recognition, cancer recognition, tumor recognition, etc. This paper deals with different machine learning algorithms that are more generically used for any health care system. The most focused problems are classification and regression. With the rise of big data, machine learning has become particularly important for solving problems. Machine learning uses two types of techniques: supervised learning and unsupervised learning. The former trains a model on known input and output data and predicts future outputs. Classification and regression are supervised learning techniques. Unsupervised learning finds hidden patterns in input data. Clustering is one such unsupervised learning technique. The above-mentioned models are discussed briefly in this paper.
Keywords: Supervised learning, unsupervised learning, regression, neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 322663 Ultrasonic Echo Image Adaptive Watermarking Using the Just-Noticeable Difference Estimation
Authors: Amnach Khawne, Kazuhiko Hamamoto, Orachat Chitsobhuk
Abstract:
Most of the image watermarking methods, using the properties of the human visual system (HVS), have been proposed in literature. The component of the visual threshold is usually related to either the spatial contrast sensitivity function (CSF) or the visual masking. Especially on the contrast masking, most methods have not mention to the effect near to the edge region. Since the HVS is sensitive what happens on the edge area. This paper proposes ultrasound image watermarking using the visual threshold corresponding to the HVS in which the coefficients in a DCT-block have been classified based on the texture, edge, and plain area. This classification method enables not only useful for imperceptibility when the watermark is insert into an image but also achievable a robustness of watermark detection. A comparison of the proposed method with other methods has been carried out which shown that the proposed method robusts to blockwise memoryless manipulations, and also robust against noise addition.
Keywords: Medical image watermarking, Human Visual System, Image Adaptive Watermark
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1589662 Vessel Inscribed Trigonometry to Measure the Vessel Progressive Orientations in the Digital Fundus Image
Authors: Pil Un Kim, Yunjung Lee, Gihyoun Lee, Jin Ho Cho, Myoung Nam Kim
Abstract:
In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.
Keywords: Angle measurement, Optic disc, Retina vessel, Vessel progression orientation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1401661 PmSPARQL: Extended SPARQL for Multi-paradigm Path Extraction
Authors: Thabet Slimani, Boutheina Ben Yaghlane, Khaled Mellouli
Abstract:
In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.
Keywords: Association extraction, query Language, relationships, knowledge base, multi-paradigm query.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1429660 Energy Efficient Clustering and Data Aggregation in Wireless Sensor Networks
Authors: Surender Kumar Soni
Abstract:
Wireless Sensor Networks (WSNs) are wireless networks consisting of number of tiny, low cost and low power sensor nodes to monitor various physical phenomena like temperature, pressure, vibration, landslide detection, presence of any object, etc. The major limitation in these networks is the use of nonrechargeable battery having limited power supply. The main cause of energy consumption WSN is communication subsystem. This paper presents an efficient grid formation/clustering strategy known as Grid based level Clustering and Aggregation of Data (GCAD). The proposed clustering strategy is simple and scalable that uses low duty cycle approach to keep non-CH nodes into sleep mode thus reducing energy consumption. Simulation results demonstrate that our proposed GCAD protocol performs better in various performance metrics.Keywords: Ad hoc network, Cluster, Grid base clustering, Wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3123659 Measuring the CSR Company-Stakeholder Fit
Authors: Armando Calabrese, Roberta Costa, Tamara Menichini, Francesco Rosati
Abstract:
As a company competitiveness depends more and more on the relationship with its stakeholders, the topic of companystakeholder fit is becoming increasingly important. This fit affects the extent to which a stakeholder perceives CSR company commitment, values and behaviors and, therefore, stakeholder identification in a company and his/her loyalty to it. Consequently, it is important to measure the alignment or the gap between stakeholder CSR demands, values, preferences and perceptions, and the company CSR disclosed commitment, values and policies. In this paper, in order to assess the company-stakeholder fit about corporate responsibility, an innovative CSR fit positioning matrix is proposed. This matrix is based on the measurement of a company CSR disclosed commitment and stakeholder perceived and required commitment. The matrix is part of a more complex methodology based on Global Reporting Initiative (GRI) indicators, content analysis and stakeholder questionnaires. This methodology provides appropriate indications for helping companies to achieve CSR company-stakeholder fit, by leveraging both CSR commitment and communication. Moreover, it could be used by top management for comparing different companies and stakeholders, and for planning specific CSR strategies, policies and activities.
Keywords: Company-Stakeholder fit, Corporate Social Responsibility (CSR), CSR Positioning Matrix, Global Reporting Initiative (GRI), Stakeholder Orientation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2941658 A Design-Based Approach to Developing a Mobile Learning System
Authors: Martina Holenko Dlab, Natasa Hoic-Bozic, Ivica Boticki
Abstract:
This paper presents technologically innovative and scalable mobile learning solution within the SCOLLAm project (“Opening up education through Seamless and COLLAborative mobile learning on tablet computers”). The main research method applied during the development of the SCOLLAm mobile learning system is design-based research. It assumes iterative refinement of the system guided by collaboration between researches and practitioners. Following the identification of requirements, a multiplatform mobile learning system SCOLLAm [in]Form was developed. Several experiments were designed and conducted in the first and second grade of elementary school. SCOLLAm [in]Form system was used to design learning activities for math classes during which students practice calculation. System refinements were based on experience and interaction data gathered during class observations. In addition to implemented improvements, the data were used to outline possible improvements and deficiencies of the system that should be addressed in the next phase of the SCOLLAm [in]Form development.
Keywords: Adaptation, collaborative learning, educational technology, mobile learning, tablet computers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1214657 Post-Compression Consideration in Video Watermarking for Wireless Communication
Authors: Chuen-Ching Wang, Yao-Tang Chang, Yu-Chang Hsu
Abstract:
A simple but effective digital watermarking scheme utilizing a context adaptive variable length coding (CAVLC) method is presented for wireless communication system. In the proposed approach, the watermark bits are embedded in the final non-zero quantized coefficient of each DCT block, thereby yielding a potential reduction in the length of the coded block. As a result, the watermarking scheme not only provides the means to check the authenticity and integrity of the video stream, but also improves the compression ratio and therefore reduces both the transmission time and the storage space requirements of the coded video sequence. The results confirm that the proposed scheme enables the detection of malicious tampering attacks and reduces the size of the coded H.264 file. Therefore, the current study is feasible to apply in the video applications of wireless communication such as 3G systemKeywords: 3G, wireless communication, CAVLC, digitalwatermarking, motion compensation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1854656 Identification of Slum Areas for Improvement Inputs in Lafia Town, Nasarawa State
Authors: Bashayi Obadiah, Barau Daniel
Abstract:
One of the United Nations Millennium Development targets is to 'achieve significant improvement in lives of at least 100 million slum dwellers, by 2020'. To monitor progress on this target a first step is to develop an operational definition to identify slum settlements. The indicators selected are: access to water and sanitation, sufficient living area, a house with durable material on a non-hazardous location and with tenure security. This paper describes the techniques of identifying slums and applied the techniques in identifying slum in Lafia town. The methodology used was selection of one district in Lafia town for this study and the district was zoned into four units. The total of 10% sample size out of 2,482 households of 250 questionnaires was administered using systematic sampling method based on proportion of houses at each zones as 90, 70, 40 and 50 respectively. The result shows that the area is a second order degeneration that needs a major improvement. Recommendations were made in this regard for urgent intervention in improving or upgrading of housing and infrastructural facilities
Keywords: Urban slums, security, safety, degeneration, upgrading.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2995655 Machine Learning for Aiding Meningitis Diagnosis in Pediatric Patients
Authors: Karina Zaccari, Ernesto Cordeiro Marujo
Abstract:
This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.
Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1083654 Auditory Brainstem Response in Wave VI for the Detection of Learning Disabilities
Authors: M.Victoria Garcia-Camba, M.Isabel Garcia-Planas
Abstract:
The use of brain stem auditory evoked potential (BAEP) is a common way to study the hearing function of people, a way to learn the functionality of a part of the brain neuronal groups that intervene in the learning process by studying the behaviour of wave VI. The latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of innocuous, low-cost and easy-access techniques such as, among others, the BAEP that can help us to detect early possible neurodevelopmental difficulties for their subsequent assessment and cure. To date and the authors best knowledge, only the latency data obtained, observing the first to V waves and mainly in the left ear, were taken into account. This work shows that it is essential to consider both ears; with these latest data, it has been possible to diagnose more precisely some cases than with the previous data had been diagnosed as “normal”despite showing signs of some alteration that motivated the new consultation to the specialist.
Keywords: Ear, neurodevelopment, auditory evoked potentials, intervals of normality, learning disabilities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 483653 Detection and Quantification of Ozone in Screen Printing Facilities
Authors: Kiurski J., Adamović S., Oros I., Krstić J., Đogo M.
Abstract:
Most often the contaminants are not taken seriously into consideration, and this behavior comes out directly from the lack of monitoring and professional reporting about pollution in the printing facilities in Serbia. The goal of planned and systematic ozone measurements in ambient air of the screen printing facilities in Novi Sad is to examine of its impact on the employees health, and to track trends in concentration. In this study, ozone concentrations were determined by using discontinuous and continuous method during the automatic and manual screen printing process. Obtained results indicates that the average concentrations of ozone measured during the automatic process were almost 3 to 28 times higher for discontinuous and 10 times higher for continuous method (1.028 ppm) compared to the values prescribed by OSHA. In the manual process, average concentrations of ozone were within prescribed values for discontinuous and almost 3 times higher for continuous method (0.299 ppm).
Keywords: indoor pollution, ozone, screen printing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2130652 Knowledge Based Wear Particle Analysis
Authors: Mohammad S. Laghari, Qurban A. Memon, Gulzar A. Khuwaja
Abstract:
The paper describes a knowledge based system for analysis of microscopic wear particles. Wear particles contained in lubricating oil carry important information concerning machine condition, in particular the state of wear. Experts (Tribologists) in the field extract this information to monitor the operation of the machine and ensure safety, efficiency, quality, productivity, and economy of operation. This procedure is not always objective and it can also be expensive. The aim is to classify these particles according to their morphological attributes of size, shape, edge detail, thickness ratio, color, and texture, and by using this classification thereby predict wear failure modes in engines and other machinery. The attribute knowledge links human expertise to the devised Knowledge Based Wear Particle Analysis System (KBWPAS). The system provides an automated and systematic approach to wear particle identification which is linked directly to wear processes and modes that occur in machinery. This brings consistency in wear judgment prediction which leads to standardization and also less dependence on Tribologists.Keywords: Computer vision, knowledge based systems, morphology, wear particles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1730651 The Scale of Farms and Development Perspectives in Georgia
Authors: M. Chavleishvili, E. Kharaishvili, G. Erkomaishvili
Abstract:
The article presents the development trends of farms, estimates on the optimal scope of farming, as well as the experience of local and foreign countries in this area. As well, the advantages of small and large farms are discussed; herewith, the scales of farms are compared to the local reality. The study analyzes the results of farm operations and the possibilities of diversification of farms. The indicators of an effective use of land resources and land fragmentation are measured; also, a comparative analysis with other countries is presented, in particular, the measurements of agricultural lands for farming, as well as the indicators of population ensuring. The conducted research shows that most of the farms in Georgia are small and their development is at the initial stage, which outlines that the country has a high resource potential to increase the scale of the farming industry and its full integration into market relations. On the basis of the obtained results, according to the research on the scale of farming in Georgia and the identification of hampering factors of farming development, the conclusions are presented and the relevant recommendations are suggested.
Keywords: Farm cooperatives, farms, farm scale, land fragmentation, small and large farms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 809650 OCR For Printed Urdu Script Using Feed Forward Neural Network
Authors: Inam Shamsher, Zaheer Ahmad, Jehanzeb Khan Orakzai, Awais Adnan
Abstract:
This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.Keywords: Algorithm, Feed Forward Neural Networks, Supervised learning, Pattern Matching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3013649 An ANN-Based Predictive Model for Diagnosis and Forecasting of Hypertension
Authors: O. O. Obe, V. Balanica, E. Neagoe
Abstract:
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 1652648 MITAutomatic ECG Beat Tachycardia Detection Using Artificial Neural Network
Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade
Abstract:
The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2271647 Selection of Pichia kudriavzevii Strain for the Production of Single-Cell Protein from Cassava Processing Waste
Authors: Phakamas Rachamontree, Theerawut Phusantisampan, Natthakorn Woravutthikul, Peerapong Pornwongthong, Malinee Sriariyanun
Abstract:
A total of 115 yeast strains isolated from local cassava processing wastes were measured for crude protein content. Among these strains, the strain MSY-2 possessed the highest protein concentration (>3.5 mg protein/mL). By using molecular identification tools, it was identified to be a strain of Pichia kudriavzevii based on similarity of D1/D2 domain of 26S rDNA region. In this study, to optimize the protein production by MSY-2 strain, Response Surface Methodology (RSM) was applied. The tested parameters were the carbon content, nitrogen content, and incubation time. Here, the value of regression coefficient (R2) = 0.7194 could be explained by the model which is high to support the significance of the model. Under the optimal condition, the protein content was produced up to 3.77 g per L of the culture and MSY-2 strain contains 66.8 g protein per 100 g of cell dry weight. These results revealed the plausibility of applying the novel strain of yeast in single-cell protein production.Keywords: Single cell protein, response surface methodology, yeast, cassava processing waste.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2662646 Counterfeit Drugs Prevention in Pharmaceutical Industry with RFID: A Framework Based On Literature Review
Authors: Zeeshan Hamid, Asher Ramish
Abstract:
The purpose of this paper is to focus on security and safety issues facing by pharmaceutical industry globally when counterfeit drugs are in question. Hence, there is an intense need to secure and authenticate pharmaceutical products in the emerging counterfeit product market. This paper will elaborate the application of radio frequency identification (RFID) in pharmaceutical industry and to identify its key benefits for patient’s care. The benefits are: help to co-ordinate the stream of supplies, accuracy in chains of supplies, maintaining trustworthy information, to manage the operations in appropriate and timely manners and finally deliver the genuine drug to patient. It is discussed that how RFID supported supply chain information sharing (SCIS) helps to combat against counterfeit drugs. And a solution how to tag pharmaceutical products; since, some products prevent RFID implementation in this industry. In this paper, a proposed model for pharma industry distribution suggested to combat against the counterfeit drugs when they are in supply chain.
Keywords: Supply chain, RFID, pharmaceutical industry, counterfeit drugs, patients care.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4632645 Computer Aided Classification of Architectural Distortion in Mammograms Using Texture Features
Authors: Birmohan Singh, V. K. Jain
Abstract:
Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Architectural distortions, masses and microcalcifications are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support vector machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and an accuracy of 96% for mammogram images collected from digital database for screening mammography database.Keywords: Architecture Distortion, GLCM Texture features, GLRLM Texture Features, Mammograms, Support Vector Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2248644 Identifying Relationships between Technology-based Services and ICTs: A Patent Analysis Approach
Authors: Chulhyun Kim, Seungkyum Kim, Moon-soo Kim
Abstract:
A variety of new technology-based services have emerged with the development of Information and Communication Technologies (ICTs). Since technology-based services have technology-driven characteristics, the identification of relationships between technology-based services and ICTs would give meaningful implications. Thus, this paper proposes an approach for identifying the relationships between technology-based services and ICTs by analyzing patent documents. First, business model (BM) patents are classified into relevant service categories. Second, patent citation analysis is conducted to investigate the technological linkage and impacts between technology-based services and ICTs at macro level. Third, as a micro level analysis, patent co-classification analysis is employed to identify the technological linkage and coverage. The proposed approach could guide and help managers and designers of technology-based services to discover the opportunity of the development of new technology-based services in emerging service sectors.Keywords: Technology-based Services, Information and Communication Technology (ICT), Business Model (BM) Patent, Patent Analysis, Technological Relationship
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1969643 Identification of High Stress and Strain Regions in Proximal Femur during Single-Leg Stance and Sideways Fall Using QCT-Based Finite Element Model
Authors: H. Kheirollahi, Y. Luo
Abstract:
Studying stress and strain trends in the femur and recognizing femur failure mechanism is very important for preventing hip fracture in the elderly. The aim of this study was to identify high stress and strain regions in the femur during normal walking and falling to find the mechanical behavior and failure mechanism of the femur. We developed a finite element model of the femur from the subject’s quantitative computed tomography (QCT) image and used it to identify potentially high stress and strain regions during the single-leg stance and the sideways fall. It was found that fracture may initiate from the superior region of femoral neck and propagate to the inferior region during a high impact force such as sideways fall. The results of this study showed that the femur bone is more sensitive to strain than stress which indicates the effect of strain, in addition to effect of stress, should be considered for failure analysis.Keywords: Finite element analysis, hip fracture, strain, stress.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2495