Search results for: Processing maps.
771 Word Recognition and Learning based on Associative Memories and Hidden Markov Models
Authors: Zöhre Kara Kayikci, Günther Palm
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A word recognition architecture based on a network of neural associative memories and hidden Markov models has been developed. The input stream, composed of subword-units like wordinternal triphones consisting of diphones and triphones, is provided to the network of neural associative memories by hidden Markov models. The word recognition network derives words from this input stream. The architecture has the ability to handle ambiguities on subword-unit level and is also able to add new words to the vocabulary during performance. The architecture is implemented to perform the word recognition task in a language processing system for understanding simple command sentences like “bot show apple".Keywords: Hebbian learning, hidden Markov models, neuralassociative memories, word recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1509770 Speech Enhancement of Vowels Based on Pitch and Formant Frequency
Authors: R. Rishma Rodrigo, R. Radhika, M. Vanitha Lakshmi
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Numerous signal processing based speech enhancement systems have been proposed to improve intelligibility in the presence of noise. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A method is presented for recording high-frequency speech components into a low-frequency region, to increase audibility for hearing loss listeners. The purpose of the paper is to enhance the formant of the speech based on the Kaiser window. The pitch and formant of the signal is based on the auto correlation, zero crossing and magnitude difference function. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain. A MATLAB software’s are used for the implementation of the system with low complexity is developed.
Keywords: Formant estimation, formant enhancement, pitch detection, speech analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1630769 Iterative Joint Power Control and Partial Crosstalk Cancellation in Upstream VDSL
Authors: H. Bagheri, H. Emami, M. R. Pakravan
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Crosstalk is the major limiting issue in very high bit-rate digital subscriber line (VDSL) systems in terms of bit-rate or service coverage. At the central office side, joint signal processing accompanied by appropriate power allocation enables complex multiuser processors to provide near capacity rates. Unfortunately complexity grows with the square of the number of lines within a binder, so by taking into account that there are only a few dominant crosstalkers who contribute to main part of crosstalk power, the canceller structure can be simplified which resulted in a much lower run-time complexity. In this paper, a multiuser power control scheme, namely iterative waterfilling, is combined with previously proposed partial crosstalk cancellation approaches to demonstrate the best ever achieved performance which is verified by simulation results.
Keywords: iterative waterfilling, partial crosstalk cancellation, run-time complexity, VDSL.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1386768 Multiwavelet and Biological Signal Processing
Authors: Morteza Moazami-Goudarzi, Ali Taheri, Mohammad Pooyan, Reza Mahboobi
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In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.
Keywords: ECG compression, Prefiltering, Cardinal Balanced Multiwavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1842767 Hydrolytic Properties of Ellagic Acid in Commercial Pomegranate Juices
Authors: Sibel Uzuner, Jale Acar
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Pomegranate and pomegranate juices (PJs) have taken great attention for their health benefits in the last years. As there is an increasing concern about potential health benefits of ellagic acid, it is of great interest to evaluate alterations in ellagic acid concentration of commercial PJs. The purpose of this study is to analyze total phenolic, free and total ellagic acid content of six commercial PJs sold in Turkish markets using HPLC. The results showed that some commercial PJs had markedly high total phenolic and ellagic acid content. Total phenolic substances of commercial PJs range from 796.71 to 4608.91 mg GAE/l. Free amount of ellagic acid in commercial PJs range from 27.64 to 111.78 mg/l. Samples are hydrolyzed with concentrated HCl at 93oC for 2 and 24 hour and influences of temperature and time parameters on hydrolization were investigated. Thermal processing for pasteurization increased ellagic acid via ellagitannins hydrolysis.Keywords: Ellagic acid, ellagitannin, pomegranate juice, total phenolic compounds
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2197766 A Keyword-Based Filtering Technique of Document-Centric XML using NFA Representation
Authors: Changwoo Byun, Kyounghan Lee, Seog Park
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XML is becoming a de facto standard for online data exchange. Existing XML filtering techniques based on a publish/subscribe model are focused on the highly structured data marked up with XML tags. These techniques are efficient in filtering the documents of data-centric XML but are not effective in filtering the element contents of the document-centric XML. In this paper, we propose an extended XPath specification which includes a special matching character '%' used in the LIKE operation of SQL in order to solve the difficulty of writing some queries to adequately filter element contents using the previous XPath specification. We also present a novel technique for filtering a collection of document-centric XMLs, called Pfilter, which is able to exploit the extended XPath specification. We show several performance studies, efficiency and scalability using the multi-query processing time (MQPT).Keywords: XML Data Stream, Document-centric XML, Filtering Technique, Value-based Predicates.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1751765 3D Digitalization of the Human Body for Use in Orthotics and Prosthetics
Authors: D. Koutny, D. Palousek, T. Koutecky, A. Zatocilova, J. Rosicky, M. Janda
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The motivation of this work was to find a suitable 3D scanner for human body parts digitalization in the field of prosthetics and orthotics. The main project objective is to compare the three hand-held portable scanners (two optical and one laser) and two optical tripod scanners. The comparison was made with respect of scanning detail, simplicity of operation and ability to scan directly on the human body. Testing was carried out on a plaster cast of the upper limb and directly on a few volunteers. The objective monitored parameters were time of digitizing and post-processing of 3D data and resulting visual data quality. Subjectively, it was considered level of usage and handling of the scanner. The new tripod was developed to improve the face scanning conditions. The results provide an overview of the suitability of different types of scanners.Keywords: 3D digitization, prosthetics and orthotics, human body digitization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4212764 Active Contours with Prior Corner Detection
Authors: U.A.A. Niroshika, Ravinda G.N. Meegama
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Deformable active contours are widely used in computer vision and image processing applications for image segmentation, especially in biomedical image analysis. The active contour or “snake" deforms towards a target object by controlling the internal, image and constraint forces. However, if the contour initialized with a lesser number of control points, there is a high probability of surpassing the sharp corners of the object during deformation of the contour. In this paper, a new technique is proposed to construct the initial contour by incorporating prior knowledge of significant corners of the object detected using the Harris operator. This new reconstructed contour begins to deform, by attracting the snake towards the targeted object, without missing the corners. Experimental results with several synthetic images show the ability of the new technique to deal with sharp corners with a high accuracy than traditional methods.Keywords: Active Contours, Image Segmentation, Harris Operator, Snakes
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2267763 Face Recognition Using Morphological Shared-weight Neural Networks
Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani
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We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1507762 Comparative Study of Filter Characteristics as Statistical Vocal Correlates of Clinical Psychiatric State in Human
Authors: Thaweesak Yingthawornsuk, Chusak Thanawattano
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Acoustical properties of speech have been shown to be related to mental states of speaker with symptoms: depression and remission. This paper describes way to address the issue of distinguishing depressed patients from remitted subjects based on measureable acoustics change of their spoken sound. The vocal-tract related frequency characteristics of speech samples from female remitted and depressed patients were analyzed via speech processing techniques and consequently, evaluated statistically by cross-validation with Support Vector Machine. Our results comparatively show the classifier's performance with effectively correct separation of 93% determined from testing with the subjectbased feature model and 88% from the frame-based model based on the same speech samples collected from hospital visiting interview sessions between patients and psychiatrists.Keywords: Depression, SVM, Vocal Extract, Vocal Tract
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1533761 Fuzzy Inference System Based Unhealthy Region Classification in Plant Leaf Image
Authors: K. Muthukannan, P. Latha
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In addition to environmental parameters like rain, temperature diseases on crop is a major factor which affects production quality & quantity of crop yield. Hence disease management is a key issue in agriculture. For the management of disease, it needs to be detected at early stage. So, treat it properly & control spread of the disease. Now a day, it is possible to use the images of diseased leaf to detect the type of disease by using image processing techniques. This can be achieved by extracting features from the images which can be further used with classification algorithms or content based image retrieval systems. In this paper, color image is used to extract the features such as mean and standard deviation after the process of region cropping. The selected features are taken from the cropped image with different image size samples. Then, the extracted features are taken in to the account for classification using Fuzzy Inference System (FIS).Keywords: Image Cropping, Classification, Color, Fuzzy Rule, Feature Extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1881760 Fish Marketing: A Panacea towards Sustainable Agriculture in Ogun State, Nigeria
Authors: A. M. Omoare, E. O. Fakoya, B. G. Abiona, W. O. Oyediran
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This study assessed fish marketing as panacea towards sustainable agriculture in Ogun State, Nigeria. Multi-stage sampling technique was used in the selection of 150 fish marketers for this study. Descriptive statistics were used for the objectives while Product Pearson Moment Correlation was used to test the hypothesis. Result of the findings revealed that the mean age of the respondents was 38.60 years. Majority (93.33%) of the respondents had acceptable levels of formal education. Many (44.00%) of the respondents had spent 1-5 years in fish marketing. The average quantity of fish sold in a day was 94.10kg. However, efficient fish marketing were hindered by inadequate processing equipment, storage rooms and ice holding facilities (86.67%). There was a significant relationship between socio-economic characteristics and profit realized from fish marketing (p < 0.05). It was recommended that storage and warehousing facilities should be provided to the fish marketers in the study area.
Keywords: Fish marketers, panacea, retail markets, sustainable.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2265759 A Forecast Model for Projecting the Amount of Hazardous Waste
Authors: J. Vilgerts, L. Timma, D. Blumberga
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The objective of the paper is to develop the forecast model for the HW flows. The methodology of the research included 6 modules: historical data, assumptions, choose of indicators, data processing, and data analysis with STATGRAPHICS, and forecast models. The proposed methodology was validated for the case study for Latvia. Hypothesis on the changes in HW for time period of 2010-2020 have been developed and mathematically described with confidence level of 95.0% and 50.0%. Sensitivity analysis for the analyzed scenarios was done. The results show that the growth of GDP affects the total amount of HW in the country. The total amount of the HW is projected to be within the corridor of – 27.7% in the optimistic scenario up to +87.8% in the pessimistic scenario with confidence level of 50.0% for period of 2010-2020. The optimistic scenario has shown to be the least flexible to the changes in the GDP growth.Keywords: Forecast models, hazardous waste management, sustainable development, waste management indicators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1848758 Multi-Agent System Architecture Oriented Prometheus Methodology Design for Reverse Logistics
Authors: F. Lhafiane, A. Elbyed, M. Bouchoum
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The design of Reverse logistics Network has attracted growing attention with the stringent pressures from both environmental awareness and business sustainability. Reverse logistical activities include return, remanufacture, disassemble and dispose of products can be quite complex to manage. In addition, demand can be difficult to predict, and decision making is one of the challenges task in such network. This complexity has amplified the need to develop an integrated architecture for product return as an enterprise system. The main purpose of this paper is to design Multi Agent System (MAS) architecture using the Prometheus methodology to efficiently manage reverse logistics processes. The proposed MAS architecture includes five types of agents: Gate keeping Agent, Collection Agent, Sorting Agent, Processing Agent and Disposal Agent which act respectively during the five steps of reverse logistics Network.Keywords: Reverse logistics, multi agent system, Prometheus methodology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2907757 A Hybrid Approach for Color Image Quantization Using K-means and Firefly Algorithms
Authors: Parisut Jitpakdee, Pakinee Aimmanee, Bunyarit Uyyanonvara
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Color Image quantization (CQ) is an important problem in computer graphics, image and processing. The aim of quantization is to reduce colors in an image with minimum distortion. Clustering is a widely used technique for color quantization; all colors in an image are grouped to small clusters. In this paper, we proposed a new hybrid approach for color quantization using firefly algorithm (FA) and K-means algorithm. Firefly algorithm is a swarmbased algorithm that can be used for solving optimization problems. The proposed method can overcome the drawbacks of both algorithms such as the local optima converge problem in K-means and the early converge of firefly algorithm. Experiments on three commonly used images and the comparison results shows that the proposed algorithm surpasses both the base-line technique k-means clustering and original firefly algorithm.Keywords: Clustering, Color quantization, Firefly algorithm, Kmeans.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2212756 Image Compression Using Multiwavelet and Multi-Stage Vector Quantization
Authors: S. Esakkirajan, T. Veerakumar, V. Senthil Murugan, P. Navaneethan
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The existing image coding standards generally degrades at low bit-rates because of the underlying block based Discrete Cosine Transform scheme. Over the past decade, the success of wavelets in solving many different problems has contributed to its unprecedented popularity. Due to implementation constraints scalar wavelets do not posses all the properties such as orthogonality, short support, linear phase symmetry, and a high order of approximation through vanishing moments simultaneously, which are very much essential for signal processing. New class of wavelets called 'Multiwavelets' which posses more than one scaling function overcomes this problem. This paper presents a new image coding scheme based on non linear approximation of multiwavelet coefficients along with multistage vector quantization. The performance of the proposed scheme is compared with the results obtained from scalar wavelets.
Keywords: Image compression, Multiwavelets, Multi-stagevector quantization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1925755 Investigation of New Method to Achieve Well Dispersed Multiwall Carbon Nanotubes Reinforced Al Matrix Composites
Authors: A.H.Javadi, Sh.Mirdamadi, M.A.Faghisani, S.Shakhesi
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Nanostructured materials have attracted many researchers due to their outstanding mechanical and physical properties. For example, carbon nanotubes (CNTs) or carbon nanofibres (CNFs) are considered to be attractive reinforcement materials for light weight and high strength metal matrix composites. These composites are being projected for use in structural applications for their high specific strength as well as functional materials for their exciting thermal and electrical characteristics. The critical issues of CNT-reinforced MMCs include processing techniques, nanotube dispersion, interface, strengthening mechanisms and mechanical properties. One of the major obstacles to the effective use of carbon nanotubes as reinforcements in metal matrix composites is their agglomeration and poor distribution/dispersion within the metallic matrix. In order to tap into the advantages of the properties of CNTs (or CNFs) in composites, the high dispersion of CNTs (or CNFs) and strong interfacial bonding are the key issues which are still challenging. Processing techniques used for synthesis of the composites have been studied with an objective to achieve homogeneous distribution of carbon nanotubes in the matrix. Modified mechanical alloying (ball milling) techniques have emerged as promising routes for the fabrication of carbon nanotube (CNT) reinforced metal matrix composites. In order to obtain a homogeneous product, good control of the milling process, in particular control of the ball movement, is essential. The control of the ball motion during the milling leads to a reduction in grinding energy and a more homogeneous product. Also, the critical inner diameter of the milling container at a particular rotational speed can be calculated. In the present work, we use conventional and modified mechanical alloying to generate a homogenous distribution of 2 wt. % CNT within Al powders. 99% purity Aluminium powder (Acros, 200mesh) was used along with two different types of multiwall carbon nanotube (MWCNTs) having different aspect ratios to produce Al-CNT composites. The composite powders were processed into bulk material by compaction, and sintering using a cylindrical compaction and tube furnace. Field Emission Scanning electron microscopy (FESEM), X-Ray diffraction (XRD), Raman spectroscopy and Vickers macro hardness tester were used to evaluate CNT dispersion, powder morphology, CNT damage, phase analysis, mechanical properties and crystal size determination. Despite the success of ball milling in dispersing CNTs in Al powder, it is often accompanied with considerable strain hardening of the Al powder, which may have implications on the final properties of the composite. The results show that particle size and morphology vary with milling time. Also, by using the mixing process and sonication before mechanical alloying and modified ball mill, dispersion of the CNTs in Al matrix improves.Keywords: multiwall carbon nanotube, Aluminum matrixcomposite, dispersion, mechanical alloying, sintering
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2312754 The Effect of Precipitation on Weed Infestation of Spring Barley under Different Tillage Conditions
Authors: J. Winkler, S. Chovancová
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The article deals with the relation between rainfall in selected months and subsequent weed infestation of spring barley. The field experiment was performed at Mendel University agricultural enterprise in Žabčice, Czech Republic. Weed infestation was measured in spring barley vegetation in years 2004 to 2012. Barley was grown in three tillage variants: conventional tillage technology (CT), minimization tillage technology (MT), and no tillage (NT). Precipitation was recorded in one-day intervals. Monthly precipitation was calculated from the measured values in the months of October through to April. The technique of canonical correspondence analysis was applied for further statistical processing. 41 different species of weeds were found in the course of the 9-year monitoring period. The results clearly show that precipitation affects the incidence of most weed species in the selected months, but acts differently in the monitored variants of tillage technologies.
Keywords: Weeds, precipitation, tillage, weed infestation forecast.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1631753 Utilizing the Principal Component Analysis on Multispectral Aerial Imagery for Identification of Underlying Structures
Authors: M. Bosques-Perez, W. Izquierdo, H. Martin, L. Deng, J. Rodriguez, T. Yan, M. Cabrerizo, A. Barreto, N. Rishe, M. Adjouadi
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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.
Keywords: Big data, image processing, multispectral, principal component analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32752 Entropy based Expeditive Methodology for Rating Curves Assessment
Authors: D. Mirauda, M. Greco, P. Moscarelli
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The river flow forecasting represents a crucial point to employ for improving a management policy addressed to the right use of water resources as well as for conjugating prevention and defense actions against environmental degradation. The difficulties occurring during the field activities encourage the development and implementation of operative computation and measuring methods addressed to time reduction for data acquisition and processing maintaining a good level of accuracy. Therefore, the aim of the present work is to test a new entropy based expeditive methodology for the evaluation of the rating curves on three gauged sections with different geometric and morphological characteristics. The methodology requires the choice of only three verticals along the measure section and the sampling of only the maximum velocity. The results underline how in most conditions the rating curves drawn can replace those built with classic methodologies, simplifying thus the procedures of data monitoring and calculation.
Keywords: gauged station, entropic approach, expeditive methodology, rating curves.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1399751 Effect of Pretreatment Method on the Content of Phenolic Compounds, Vitamin C and Antioxidant Activity of Dried Dill
Authors: Ruta Galoburda, Zanda Kruma, Karina Ruse
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Dill contains range of phytochemicals, such as vitamin C and polyphenols, which significantly contribute to their total antioxidant activity. The aim of the current research was to determine the best blanching method for processing of dill prior to microwave vacuum drying based on the content of phenolic compounds, vitamin C and free radical scavenging activity. Two blanching mediums were used – water and steam, and for part of the samples microwave pretreatment was additionally used. Evaluation of vitamin C, phenolic contents and scavenging of DPPH˙ radical in dried dill was performed. Blanching had an effect on all tested parameters and the blanching conditions are very important. After evaluation of the results, as the best method for dill pretreatment was established blanching at 90 °C for 30 seconds.
Keywords: blanching, microwave vacuum drying, TPC, vitamin C.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3079750 Grid–SVC: An Improvement in SVC Algorithm, Based On Grid Based Clustering
Authors: Farhad Hadinejad, Hasan Saberi, Saeed Kazem
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Support vector clustering (SVC) is an important kernelbased clustering algorithm in multi applications. It has got two main bottle necks, the high computation price and labeling piece. In this paper, we presented a modified SVC method, named Grid–SVC, to improve the original algorithm computationally. First we normalized and then we parted the interval, where the SVC is processing, using a novel Grid–based clustering algorithm. The algorithm parts the intervals, based on the density function of the data set and then applying the cartesian multiply makes multi-dimensional grids. Eliminating many outliers and noise in the preprocess, we apply an improved SVC method to each parted grid in a parallel way. The experimental results show both improvement in time complexity order and the accuracy.
Keywords: Grid–based clustering, SVC, Density function, Radial basis function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1735749 Design and Implementation of a Neural Network for Real-Time Object Tracking
Authors: Javed Ahmed, M. N. Jafri, J. Ahmad, Muhammad I. Khan
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Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.
Keywords: Image processing, machine vision, neural networks, real-time object tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3498748 A Context-Centric Chatbot for Cryptocurrency Using the Bidirectional Encoder Representations from Transformers Neural Networks
Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li
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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.Keywords: BERT, chatbot, cryptocurrency, deep learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 957747 MONARC: A Case Study on Simulation Analysis for LHC Activities
Authors: Ciprian Dobre
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The scale, complexity and worldwide geographical spread of the LHC computing and data analysis problems are unprecedented in scientific research. The complexity of processing and accessing this data is increased substantially by the size and global span of the major experiments, combined with the limited wide area network bandwidth available. We present the latest generation of the MONARC (MOdels of Networked Analysis at Regional Centers) simulation framework, as a design and modeling tool for large scale distributed systems applied to HEP experiments. We present simulation experiments designed to evaluate the capabilities of the current real-world distributed infrastructure to support existing physics analysis processes and the means by which the experiments bands together to meet the technical challenges posed by the storage, access and computing requirements of LHC data analysis within the CMS experiment.Keywords: Modeling and simulation, evaluation, large scale distributed systems, LHC experiments, CMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1800746 Loop Back Connected Component Labeling Algorithm and Its Implementation in Detecting Face
Authors: A. Rakhmadi, M. S. M. Rahim, A. Bade, H. Haron, I. M. Amin
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In this study, a Loop Back Algorithm for component connected labeling for detecting objects in a digital image is presented. The approach is using loop back connected component labeling algorithm that helps the system to distinguish the object detected according to their label. Deferent than whole window scanning technique, this technique reduces the searching time for locating the object by focusing on the suspected object based on certain features defined. In this study, the approach was also implemented for a face detection system. Face detection system is becoming interesting research since there are many devices or systems that require detecting the face for certain purposes. The input can be from still image or videos, therefore the sub process of this system has to be simple, efficient and accurate to give a good result.Keywords: Image processing, connected components labeling, face detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2289745 An Automated Method to Segment and Classify Masses in Mammograms
Authors: Viet Dzung Nguyen, Duc Thuan Nguyen, Tien Dzung Nguyen, Van Thanh Pham
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Mammography is the most effective procedure for an early diagnosis of the breast cancer. Nowadays, people are trying to find a way or method to support as much as possible to the radiologists in diagnosis process. The most popular way is now being developed is using Computer-Aided Detection (CAD) system to process the digital mammograms and prompt the suspicious region to radiologist. In this paper, an automated CAD system for detection and classification of massive lesions in mammographic images is presented. The system consists of three processing steps: Regions-Of- Interest detection, feature extraction and classification. Our CAD system was evaluated on Mini-MIAS database consisting 322 digitalized mammograms. The CAD system-s performance is evaluated using Receiver Operating Characteristics (ROC) and Freeresponse ROC (FROC) curves. The archived results are 3.47 false positives per image (FPpI) and sensitivity of 85%.Keywords: classification, computer-aided detection, featureextraction, mass detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1646744 Contrast Enhancement of Masses in Mammograms Using Multiscale Morphology
Authors: Amit Kamra, V. K. Jain, Pragya
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Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other stateof- the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.Keywords: Enhancement, mammography, multi-scale, mathematical morphology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2247743 Time Delay Estimation Using Signal Envelopes for Synchronisation of Recordings
Authors: Sergei Aleinik, Mikhail Stolbov
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In this work, a method of time delay estimation for dual-channel acoustic signals (speech, music, etc.) recorded under reverberant conditions is investigated. Standard methods based on cross-correlation of the signals show poor results in cases involving strong reverberation, large distances between microphones and asynchronous recordings. Under similar conditions, a method based on cross-correlation of temporal envelopes of the signals delivers a delay estimation of acceptable quality. This method and its properties are described and investigated in detail, including its limits of applicability. The method’s optimal parameter estimation and a comparison with other known methods of time delay estimation are also provided.
Keywords: Cross-correlation, delay estimation, signal envelope, signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3054742 Hit-or-Miss Transform as a Tool for Similar Shape Detection
Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer
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This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.
Keywords: Hit-or/and-Miss Operator/Transform, HMT, binary morphological operation, shape detection, binary images processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5116