Search results for: non-invasive cancer detection.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1762

Search results for: non-invasive cancer detection.

562 Prediction of Cardiovascular Disease by Applying Feature Extraction

Authors: Nebi Gedik

Abstract:

Heart disease threatens the lives of a great number of people every year around the world. Heart issues lead to many of all deaths; therefore, early diagnosis and treatment are critical. The diagnosis of heart disease is complicated due to several factors affecting health such as high blood pressure, raised cholesterol, an irregular pulse rhythm, and more. Artificial intelligence has the potential to assist in the early detection and treatment of diseases. Improving heart failure prediction is one of the primary goals of research on heart disease risk assessment. This study aims to determine the features that provide the most successful classification prediction in detecting cardiovascular disease. The performances of each feature are compared using the K-Nearest Neighbor machine learning method. The feature that gives the most successful performance has been identified.

Keywords: Cardiovascular disease, feature extraction, supervised learning, k-NN.

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561 Evaluation of Clustering Based on Preprocessing in Gene Expression Data

Authors: Seo Young Kim, Toshimitsu Hamasaki

Abstract:

Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.

Keywords: Gene expression, clustering, data preprocessing.

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560 Derivative Spectrophotometry Applied to the Determination of Triprolidine Hydrochloride and Pseudoephedrine Hydrochloride in Tablets and Dissolution Testing

Authors: L. Sriphong, A. Chaidedgumjorn, K. Chaisuroj

Abstract:

A spectrophotometric method was developed for simultaneous quantification of pseudoephedrine hydrochloride (PSE) triprolidine hydrochloride (TRI) using second derivative method (zero-crossing technique). The second derivative amplitudes of PSE and TRI were measured at 271 and 321 nm, respectively. The calibration curves were linear in the range of 200 to 1,000 g/ml for PSE and 10 to 50 g/ml for TRI. The method was validated for specificity, accuracy, precision, limit of detection and limit of quantitation. The proposed method was applied to the assaying and dissolution of PSE and TRI in commercial tablets without any chemical separation. The results were compared with those obtained by the official USP31 method and statistical tests showed that there is no significant between the methods at 95% confidence level. The proposed method is simple, rapid and suitable for the routine quality control application. KeywordsTriprolidine, Pseudoephedrine, Derivative spectrophotometry, Dissolution testing.

Keywords: Triprolidine, Pseudoephedrine, Derivative spectrophotometry, Dissolution testing.

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559 De-noising Infrared Image Using OWA Based Filter

Authors: Ruchika, Munish Vashisht, S. Qamar

Abstract:

Detection of small ship is crucial task in many automatic surveillance systems which are employed for security of maritime boundaries of a country. To address this problem, image de-noising is technique to identify the target ship in between many other ships in the sea. Image de-noising technique needs to extract the ship’s image from sea background for the analysis as the ship’s image may submerge in the background and flooding waves. In this paper, a noise filter is presented that is based on fuzzy linguistic ‘most’ quantifier. Ordered weighted averaging (OWA) function is used to remove salt-pepper noise of ship’s image. Results obtained are in line with the results available by other well-known median filters and OWA based approach shows better performance.

Keywords: Linguistic quantifier, impulse noise, OWA filter, median filter.

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558 Manufacturing Process and Cost Estimation through Process Detection by Applying Image Processing Technique

Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

Abstract:

In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: Image processing technique, Feature detections, Surface registrations, Capturing multi-view images, Production costs, and Manufacturing processes.

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557 Experimentation on Piercing with Abrasive Waterjet

Authors: Johan Fredin, Anders Jönsson

Abstract:

Abrasive waterjet cutting (AWJ) is a highly efficient method for cutting almost any type of material. When holes shall be cut the waterjet first needs to pierce the material.This paper presents a vast experimental analysis of piercing parameters effect on piercing time. Results from experimentation on feed rates, work piece thicknesses, abrasive flow rates, standoff distances and water pressure are also presented as well as studies on three methods for dynamic piercing. It is shown that a large amount of time and resources can be saved by choosing the piercing parameters in a correct way. The large number of experiments puts demands on the experimental setup. An automated experimental setup including piercing detection is presented to enable large series of experiments to be carried out efficiently.

Keywords: Waterjet cutting, Piercing, Experimentation

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556 Detection of Pathogenic Escherichia coli Strains Pollution in Red Deer Meat in Latvia and Determination the Compatibility of VT1, VT2, eae A Genes in their Isolate

Authors: S. Liepina, A. Jemeljanovs

Abstract:

Tasks of the work were study the possible E.coli contamination in red deer meat, identify pathogenic strains from isolated E.coli, determine their incidence in red deer meat and determine the presence of VT1, VT2 and eaeA genes for the pathogenic E.coli. 8 (10%) samples were randomly selected from 80 analysed isolates of E.coli and PCR reaction was performed on them. PCR was done both on initial materials – samples of red deer meat - and for already isolated liqueurs. Two of analysed venison samples contain verotoxin-producing strains of E. coli. It means that this meat is not safe to consumer. It was proven by the sequestration reaction of E. coli and by comparison of the obtained results with the database of microorganism genome available on the internet that the isolated culture corresponds to region 16S rDNS of E. coli thus presenting correctness of the microbiological methods.

Keywords: Deer meat, pathogenic Escherichia coli

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555 High Impedance Faults Detection Technique Based on Wavelet Transform

Authors: Ming-Ta Yang, Jin-Lung Guan, Jhy-Cherng Gu

Abstract:

The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.

Keywords: Continuous wavelet transform, discrete wavelet transform, high impedance faults, statistical confidence.

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554 Pilot Directional Protection Scheme Using Wireless Communication

Authors: Nitish Sharma, G. G. Karady

Abstract:

This paper presents a scheme for the protection of loop system from all type of faults using the direction of fault current. The presence of distributed generation in today’s system increases the complexity of fault detection as the power flow is bidirectional. Hence, protection scheme specific to this purpose needs to be developed. This paper shows a fast protection scheme using communication which can be fiber optic or wireless. In this paper, the possibility of wireless communication for protection is studied to exchange the information between the relays. The negative sequence and positive sequence directional elements are used to determine the direction of fault current. A PSCAD simulation is presented and validated using commercial SEL relays.

Keywords: Smart grid protection, pilot protection, power system simulation, wireless communication.

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553 Enhancement of m-FISH Images using Spectral Unmixing

Authors: Martin De Biasio, Raimund Leitner, Franz G. Wuertz, Sergey Verzakov, Pierre J. Elbischger

Abstract:

Breast carcinoma is the most common form of cancer in women. Multicolour fluorescent in-situ hybridisation (m-FISH) is a common method for staging breast carcinoma. The interpretation of m-FISH images is complicated due to two effects: (i) Spectral overlap in the emission spectra of fluorochrome marked DNA probes and (ii) tissue autofluorescence. In this paper hyper-spectral images of m-FISH samples are used and spectral unmixing is applied to produce false colour images with higher contrast and better information content than standard RGB images. The spectral unmixing is realised by combinations of: Orthogonal Projection Analysis (OPA), Alterating Least Squares (ALS), Simple-to-use Interactive Self-Modeling Mixture Analysis (SIMPLISMA) and VARIMAX. These are applied on the data to reduce tissue autofluorescence and resolve the spectral overlap in the emission spectra. The results show that spectral unmixing methods reduce the intensity caused by tissue autofluorescence by up to 78% and enhance image contrast by algorithmically reducing the overlap of the emission spectra.

Keywords: breast carcinoma, hyperspectral imaging, m-FISH, spectral unmixing

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552 A Comparison of SVM-based Criteria in Evolutionary Method for Gene Selection and Classification of Microarray Data

Authors: Rameswar Debnath, Haruhisa Takahashi

Abstract:

An evolutionary method whose selection and recombination operations are based on generalization error-bounds of support vector machine (SVM) can select a subset of potentially informative genes for SVM classifier very efficiently [7]. In this paper, we will use the derivative of error-bound (first-order criteria) to select and recombine gene features in the evolutionary process, and compare the performance of the derivative of error-bound with the error-bound itself (zero-order) in the evolutionary process. We also investigate several error-bounds and their derivatives to compare the performance, and find the best criteria for gene selection and classification. We use 7 cancer-related human gene expression datasets to evaluate the performance of the zero-order and first-order criteria of error-bounds. Though both criteria have the same strategy in theoretically, experimental results demonstrate the best criterion for microarray gene expression data.

Keywords: support vector machine, generalization error-bound, feature selection, evolutionary algorithm, microarray data

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551 On SNR Estimation by the Likelihood of near Pitch for Speech Detection

Authors: Young-Hwan Song, Doo-Heon Kyun, Jong-Kuk Kim, Myung-Jin Bae

Abstract:

People have the habitual pitch level which is used when people say something generally. However this pitch should be changed irregularly in the presence of noise. So it is useful to estimate SNR of speech signal by pitch. In this paper, we obtain the energy of input speech signal and then we detect a stationary region on voiced speech. And we get the pitch period by NAMDF for the stationary region that is not varied pitch rapidly. After getting pitch, each frame is divided by pitch period and the likelihood of closed pitch is estimated. In this paper, we proposed new parameter, NLF, to estimate the SNR of received speech signal. The NLF is derived from the correlation of near pitch periods. The NLF is obtained for each stationary region in voiced speech. Finally we confirmed good performance of the estimation of the SNR of received input speech in the presence of noise.

Keywords: Likelihood, pitch, SNR, speech.

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550 Evaluation of Multilevel Modulation Formats for 100Gbps Transmission with Direct Detection

Authors: Majed Omar Al-Dwairi

Abstract:

This paper evaluate the multilevel modulation for different techniques such as amplitude shift keying (M-ASK), MASK, differential phase shift keying (M-ASK-Bipolar), Quaternary Amplitude Shift Keying (QASK) and Quaternary Polarization-ASK (QPol-ASK) at a total bit rate of 107 Gbps. The aim is to find a costeffective very high speed transport solution. Numerical investigation was performed using Monte Carlo simulations. The obtained results indicate that some modulation formats can be operated at 100Gbps in optical communication systems with low implementation effort and high spectral efficiency.

Keywords: Optical communication, multilevel amplitude shift keying (M-ASK), Differential phase shift keying (DPSK), Quaternary Amplitude Shift Keying (QASK), Quaternary Polarization-ASK (QPol-ASK).

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549 Robust Adaptation to Background Noise in Multichannel C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev, Viktor M. Denisov

Abstract:

A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: Guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture.

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548 Genetic Combined with a Simplex Algorithm as an Efficient Method for the Detection of a Depressed Ellipsoidal Flaw using the Boundary Element Method

Authors: Clio G. Vossou, Ioannis N. Koukoulis, Christopher G. Provatidis

Abstract:

The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.

Keywords: Defect identification, genetic algorithms, optimization.

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547 The Robot Hand System that can Control Grasping Power by SEMG

Authors: Tsubasa Seto, Kentaro Nagata, Kazushige Magatani

Abstract:

SEMG (Surface Electromyogram) is one of the bio-signals and is generated from the muscle. And there are many research results that use forearm EMG to detect hand motions. In this paper, we will talk about our developed the robot hand system that can control grasping power by SEMG. In our system, we suppose that muscle power is proportional to the amplitude of SEMG. The power is estimated and the grip power of a robot hand is able to be controlled using estimated muscle power in our system. In addition, to perform a more precise control can be considered to build a closed loop feedback system as an object to a subject to pressure from the edge of hand. Our objectives of this study are the development of a method that makes perfect detection of the hand grip force possible using SEMG patterns, and applying this method to the man-machine interface.

Keywords: SEMG, multi electrode, robot hand, power control

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546 Development of an Immunoassay Platform for Diagnosis of Acute Kidney Injury

Authors: T. Bovornvirakit, K. Viravaidya

Abstract:

Acute kidney injury (AKI) is a new worldwide public health problem. A diagnosis of this disease using creatinine is still a problem in clinical practice. Therefore, a measurement of biomarkers responsible for AKI has received much attention in the past couple years. Cytokine interleukin-18 (IL-18) was reported as one of the early biomarkers for AKI. The most commonly used method to detect this biomarker is an immunoassay. This study used a planar platform to perform an immunoassay using fluorescence for detection. In this study, anti-IL-18 antibody was immobilized onto a microscope slide using a covalent binding method. Make-up samples were diluted at the concentration between 10 to 1000 pg/ml to create a calibration curve. The precision of the system was determined using a coefficient of variability (CV), which was found to be less than 10%. The performance of this immunoassay system was compared with the measurement from ELISA.

Keywords: Acute kidney injury, Acute renal failure, Antibody immobilization, Interleukin-18

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545 Novel Schemes of Pilot-Aided Integer Frequency Offset Estimation for OFDM-Based DVB-T Systems

Authors: Youngyoon Lee, Dahae Chong, Myungsoo Lee, Seongho Chae, Seokho Yoon

Abstract:

This paper proposes two novel schemes for pilot-aided integer frequency offset (IFO) estimation in orthogonal frequency division multiplexing (OFDM)-based digital video broadcastingterrestrial (DVB-T) systems. The conventional scheme proposed for estimating the IFO uses only partial information of combinations that pilots can provide, which stems from a rigorous assumption that the channel responses of pilots used for estimating the IFO change very rapidly. Thus, in this paper, we propose the novel IFO estimation schemes exploiting all information of combinations that pilots can provide to improve the performance of IFO estimation. The simulation results show that the proposed schemes are highly accurate in terms of the IFO detection probability.

Keywords: OFDM, DVB-T, pilot, IFO, estimation

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544 Automatic Extraction of Water Bodies Using Whole-R Method

Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

Abstract:

Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R color component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: Chromaticity, Feature Extraction, Remote Sensing, Spectral library, Water Index.

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543 A Novel Tracking Method Using Filtering and Geometry

Authors: Sang Hoon Lee, Jong Sue Bae, Taewan Kim, Jin Mo Song, Jong Ju Kim

Abstract:

Image target detection and tracking methods based on target information such as intensity, shape model, histogram and target dynamics have been proven to be robust to target model variations and background clutters as shown by recent researches. However, no definitive answer has been given to occluded target by counter measure or limited field of view(FOV). In this paper, we will present a novel tracking method using filtering and computational geometry. This paper has two central goals: 1) to deal with vulnerable target measurements; and 2) to maintain target tracking out of FOV using non-target-originated information. The experimental results, obtained with airborne images, show a robust tracking ability with respect to the existing approaches. In exploring the questions of target tracking, this paper will be limited to consideration of airborne image.

Keywords: Tracking, Computational geometry, Homography, Filter

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542 Artificial Intelligence Applications in Aggregate Quarries: A Reality

Authors: J. E. Ortiz, P. Plaza, J. Herrero, I. Cabria, J. L. Blanco, J. Gavilanes, J. I. Escavy, I. López-Cilla, V. Yagüe, C. Pérez, S. Rodríguez, J. Rico, C. Serrano, J. Bernat

Abstract:

The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: Aggregates, artificial intelligence, automatization, mining operations.

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541 A Functional Beverage: Lemonade

Authors: F. Z. Yekeler, H. Ozyurek, C. E. Tamer

Abstract:

Fruits and vegetables are the essentials of a healthy diet, mainly because of their antioxidant properties contributing to disease blockage especially for some certain types of cancer. Being a favourite fruit, citrus are produced for economic and commercial purposes worldwide. Particularly, lemon fruit (Citrus limon L.), has an important place in export products of Turkey. Lemon has a great importance on human nutrition with regard to being a source of nutrients, flavonoids, vitamin C and minerals. It is used for food flavouring and pickling and also processed for lemonade. By processing citrus into fruit juices, consumption may increase and also become easier. Like many fruits and vegetables lemons are cheap and abundant during harvesting period, while they are quite expensive in other seasons. Lemon juice and concentrate production allows consumers to get benefits from lemon fruit in any time of the year. Lemonade is getting in to the focus of consumers’ attention preferring non-carbonated drinks. The demand of healthy, convenient functional foods affects consumer trends through innovative products. For this reason, lemonade could be enriched with different natural herb extracts such as ginger (Zingiber officinale), linden (Tilia cordata), and mint (Mentha piperita).

Keywords: Lemonade, herb extracts, antioxidant activity.

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540 Analysis of Image Segmentation Techniques for Diagnosis of Dental Caries in X-ray Images

Authors: V. Geetha, K. S. Aprameya

Abstract:

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.

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539 Wavelet-Based ECG Signal Analysis and Classification

Authors: Madina Hamiane, May Hashim Ali

Abstract:

This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm.  The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.

Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.

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538 An Amalgam Approach for DICOM Image Classification and Recognition

Authors: J. Umamaheswari, G. Radhamani

Abstract:

This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.

Keywords: Recognition, classification, Relaxed Median Filter, Adaptive thresholding, clustering and Neural Networks

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537 Multiple Crack Identification Using Frequency Measurement

Authors: J.W. Xiang, M. Liang

Abstract:

This paper presents a method to detect multiple cracks based on frequency information. When a structure is subjected to dynamic or static loads, cracks may develop and the modal frequencies of the cracked structure may change. To detect cracks in a structure, we construct a high precision wavelet finite element (EF) model of a certain structure using the B-spline wavelet on the interval (BSWI). Cracks can be modeled by rotational springs and added to the FE model. The crack detection database will be obtained by solving that model. Then the crack locations and depths can be determined based on the frequency information from the database. The performance of the proposed method has been numerically verified by a rotor example.

Keywords: Rotor, frequency measurement, multiple cracks, wavelet finite element method, identification.

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536 Fiber Optic Sensors for Hydrogen Peroxide Vapor Measurement

Authors: H. Akbari Khorami, P. Wild, N. Djilali

Abstract:

This paper reports on the response of a fiber-optic sensing probe to small concentrations of hydrogen peroxide (H2O2) vapor at room temperature. H2O2 has extensive applications in industrial and medical environments. Conversely, H2O2 can be a health hazard by itself. For example, H2O2 induces cellular damage in human cells and its presence can be used to diagnose illnesses such as asthma and human breast cancer. Hence, development of reliable H2O2 sensor is of vital importance to detect and measure this species. Ferric ferrocyanide, referred to as Prussian Blue (PB), was deposited on the tip of a multimode optical fiber through the single source precursor technique and served as an indicator of H2O2 in a spectroscopic manner. Sensing tests were performed in H2O2-H2O vapor mixtures with different concentrations of H2O2. The results of sensing tests show the sensor is able to detect H2O2 concentrations in the range of 50.6 ppm to 229.5 ppm. Furthermore, the sensor response to H2O2 concentrations is linear in a log-log scale with the adjacent R-square of 0.93. This sensing behavior allows us to detect and quantify the concentration of H2O2 in the vapor phase.

Keywords: Chemical deposition, fiber-optic sensors, hydrogen peroxide vapor, prussian blue.

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535 Effect of Copper Ions Doped-Hydroxyapatite 3D Fiber Scaffold

Authors: Adil Elrayah, Jie Weng, Esra Suliman

Abstract:

The mineral in human bone is not pure stoichiometric calcium phosphate (Ca/P) as it is partially substituted by in organic elements. In this study, the copper ions (Cu2+) substituted hydroxyapatite (CuHA) powder has been synthesized by the co-precipitation method. The CuHA powder has been used to fabricate CuHA fiber scaffolds by sol-gel process and the following sinter process. The resulted CuHA fibers have slightly different microstructure (i.e. porosity) compared to HA fiber scaffold, which is denser. The mechanical properties test was used to evaluate CuHA, and the results showed decreases in both compression strength and hardness tests. Moreover, the in vitro used endothelial cells to evaluate the angiogenesis of CuHA. The result illustrated that the viability of endothelial cell on CuHA fiber scaffold surfaces tends to antigenic behavior. The results obtained with CuHA scaffold give this material benefit in biological applications such as antimicrobial, antitumor, antigens, compacts, filling cavities of the tooth and for the deposition of metal implants anti-tumor, anti-cancer, bone filler, and scaffold.

Keywords: Fiber scaffold, copper ions, hydroxyapatite, hardness, in vitro, mechanical properties.

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534 A Novel Modified Adaptive Fuzzy Inference Engine and Its Application to Pattern Classification

Authors: J. Hossen, A. Rahman, K. Samsudin, F. Rokhani, S. Sayeed, R. Hasan

Abstract:

The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a novel Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data sets. A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and rules by the fuzzy c-means clustering and Apriori algorithm technique, respectively. The generated adaptive fuzzy inference engine is adjusted by the least-squares fit and a conjugate gradient descent algorithm towards better performance with a minimal set of rules. The proposed MAFIE is able to reduce the number of rules which increases exponentially when more input variables are involved. The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher-s Iris and Wisconsin breast cancer data sets and shown to be very competitive.

Keywords: Apriori algorithm, Fuzzy C-means, MAFIE, TSK

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533 Determination of Volatile Organic Compounds in Human Breath by Optical Fiber Sensing

Authors: C. I. L. Justino, L. I. B. Silva, K. Duarte, A. C. Freitas, T. A. P. Rocha-Santos, A. C. Duarte

Abstract:

This work proposes an optical fiber system (OF) for sensing various volatile organic compounds (VOCs) in human breath for the diagnosis of some metabolic disorders as a non-invasive methodology. The analyzed VOCs are alkanes (i.e., ethane, pentane, heptane, octane, and decane), and aromatic compounds (i.e., benzene, toluene, and styrene). The OF displays high analytical performance since it provides near real-time responses, rapid analysis, and low instrumentation costs, as well as it exhibits useful linear range and detection limits; the developed OF sensor is also comparable to a reference methodology (gas chromatography-mass spectrometry) for the eight tested VOCs.

Keywords: Breath analysis, gas chromatography-mass spectrometry, optical fiber sensor, volatile organic compounds

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