Search results for: microwave-assisted extraction
1198 A Method for Quantifying Arsenolipids in Sea Water by HPLC-High Resolution Mass Spectrometry
Authors: Muslim Khan, Kenneth B. Jensen, Kevin A. Francesconi
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Trace amounts (ca 1 µg/L, 13 nM) of arsenic are present in sea water mostly as the oxyanion arsenate. In contrast, arsenic is present in marine biota (animals and algae) at very high levels (up to100,000 µg/kg) a significant portion of which is present as lipid-soluble compounds collectively termed arsenolipids. The complex nature of sea water presents an analytical challenge to detect trace compounds and monitor their environmental path. We developed a simple method using liquid-liquid extraction combined with HPLC-High Resolution Mass Spectrometer capable of detecting trace of arsenolipids (99 % of the sample matrix while recovering > 80 % of the six target arsenolipids with limit of detection of 0.003 µg/L.)Keywords: arsenolipids, sea water, HPLC-high resolution mass spectrometry
Procedia PDF Downloads 3601197 Analysis of Nonlinear and Non-Stationary Signal to Extract the Features Using Hilbert Huang Transform
Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar
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It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)
Procedia PDF Downloads 5711196 Automatic Moment-Based Texture Segmentation
Authors: Tudor Barbu
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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes
Procedia PDF Downloads 4121195 A Proposed Approach for Emotion Lexicon Enrichment
Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees
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Document Analysis is an important research field that aims to gather the information by analyzing the data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enriching the lexicon with adapting their content based on semantic patterns extraction. The proposed approach has been presented, and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results.Keywords: document analysis, sentimental analysis, emotion detection, WEKA tool, NRC lexicon
Procedia PDF Downloads 4261194 Electro-Winning of Dilute Solution of Copper Metal from Sepon Mine, Lao PDR
Authors: S. Vasailor, C. Rattanakawin
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Electro-winning of copper metal from dilute sulfate solution (13.7 g/L) was performed in a lab electrolytic cell with stainless-steel cathode and lead-alloy anode. The effects of various parameters including cell voltage, electro-winning temperature and time were studied in order to acquire an appropriate current efficiency of copper deposition. The highest efficiency is about 95% obtaining from electro-winning condition of 3V, 55°C and 3,600 s correspondingly. The cathode copper with 95.5% Cu analyzed using atomic absorption spectrometry can be obtained from this single-winning condition. In order to increase the copper grade, solvent extraction should be used to increase the sulfate concentration, say 50 g/L, prior to winning the cathode copper effectively.Keywords: copper metal, current efficiency, dilute sulfate solution, electro-winning
Procedia PDF Downloads 1321193 Analysis of Business Intelligence Tools in Healthcare
Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore
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In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.Keywords: CDSS, EHR, business intelliegence, tools
Procedia PDF Downloads 1301192 Concentrations and History of Heavy Metals in Sediment Cores: Geochemistry and Geochronology Using 210Pb
Authors: F. Fernandes, C. Poleto
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This paper aims at assessing the concentrations of heavy metals and the isotopic composition of lead 210Pb in different fractions of sediment produced in the watershed that makes up the Mãe d'água dam and thus characterizing the distribution of metals along the sedimentary column and inferencing in the urbanization of the same process. Sample collection was carried out in June 2014; eight sediment cores were sampled in the lake of the dam. For extraction of the sediments core, a core sampler “Piston Core” was used. The trace metal concentrations were determined by conventional atomic absorption spectrophotometric methods. The samples were subjected to radiochemical analysis of 210Po. 210Pb activity was obtained by measuring 210Po activity. The chronology was calculated using the constant rate of supply (CRS). 210Pb is used to estimate the sedimentation rate.Keywords: ²¹⁰Pb dating method, heavy metal, lakes urban, pollution history
Procedia PDF Downloads 2931191 Urban Land Cover from GF-2 Satellite Images Using Object Based and Neural Network Classifications
Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi
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China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron
Procedia PDF Downloads 3831190 Development of Algorithms for the Study of the Image in Digital Form for Satellite Applications: Extraction of a Road Network and Its Nodes
Authors: Zineb Nougrara
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In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.Keywords: satellite image, road network, nodes, image analysis and processing
Procedia PDF Downloads 2691189 Automatic Segmentation of the Clean Speech Signal
Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze
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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate
Procedia PDF Downloads 4901188 Different Biological and Chemical Parameters that Influence the Polyphenols from Some Medicinal Plants in Western Algeria
Authors: Mustapha Mahmoud, Fouzia Toumi Benali, Mohamed Benyahia, Sofiane Bouazza
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This work focuses on the influences of biological and chemical parameters on the phenolic compounds such as flavonoids and tannins in different medicinal plants in western Algeria (Papaver rhoeas, Daphnegnidium, Lavandula multifida, Lavandula dentata, Lavandula stoicha, ...). Thus we look the difference between species of the same genus, difference between the different organs of the same species, the influence of environment all temperature influences, time, percentage of solvent on the extraction. Quantification of the phenolic compounds was performed by spectrophotometric method then treated with statistics tools such as variance analysis, multivariant analyzes, response surface methodology). The results show that the polyphenols are influenced by the parameters mentioned.Keywords: polyphenols, influences, medicinal plants, west Algeria
Procedia PDF Downloads 2851187 The Leaching Kinetics of Zinc from Industrial Zinc Slag Waste
Authors: Hilary Rutto
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The investigation was aimed at determining the extent at which the zinc will be extracted from secondary sources generated from galvanising process using dilute sulphuric acid under controlled laboratory conditions of temperature, solid-liquid ratio, and agitation rate. The leaching experiment was conducted for a period of 2 hours and to total zinc extracted calculated in relation to the amount of zinc dissolved at a unit time in comparison to the initial zinc content of the zinc ash. Sulphuric acid was found to be an effective leaching agent with an overall extraction of 91.1% when concentration is at 2M, and solid/liquid ratio kept at 1g/200mL leaching solution and temperature set at 65ᵒC while slurry agitation is at 450rpm. The leaching mechanism of zinc ash with sulphuric acid was conformed well to the shrinking core model.Keywords: leaching, kinetics, shrinking core model, zinc slag
Procedia PDF Downloads 1431186 Aesthetic Analysis and Socio-Cultural Significance of Eku Idowo and Anipo Masquerades of the Anetuno (Ebira Chao)
Authors: Lamidi Lawal Aduozava
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Masquerade tradition is an indigenous culture of the Anetuno an extraction of the Ebira referred to as Ebira chao. This paper seeks to make aesthetic analysis of the masquerades in terms of their costumes and socio-cultural significance. To this end, the study examined and documented the functions and roles of Anipo and Idowo masquerades in terms of therapeutic, economic, prophetic and divination, entertainment, and funeral functions to the owner community(Eziobe group of families) in Igarra, Edo State of Nigeria, West Africa. For the purpose of data collection, focus group discussion, participatory, visual and observatory methods of data collection were used. All the data collected were aesthetically, descriptively and historically analyzed.Keywords: Aesthetics, , Costume, , Masquerades, , Significance.
Procedia PDF Downloads 1531185 Risk Factors for Maternal and Neonatal Morbidities Associated with Operative Vaginal Deliveries
Authors: Maria Reichenber Arcilla
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Objective: To determine the risk factors for maternal and neonatal complications associated with operative vaginal deliveries. Methods: A retrospective chart review of 435 patients who underwent operative vaginal deliveries was done. Patient profiles – age, parity, AOG, duration of labor – and outcomes – birthweight, maternal and neonatal complications - were tabulated and multivariable analysis and logistic regression were performed using SPSS® Statistics Base. Results and Conclusion: There was no significant difference in the incidence of maternal and neonatal complications between those that underwent vacuum and forceps extraction. Among the variables analysed, parity and duration of labor reached statistical significance. The odds of maternal complications were 3 times higher among nulliparous patients. Neonatal complications were seen in those whose labor lasted more than 9 hours.Keywords: operative vaginal deliveries, maternal, neonatal, morbidity
Procedia PDF Downloads 4001184 Physico-Chemical, GC-MS Analysis and Cold Saponification of Onion (Allium cepa L) Seed Oil
Authors: A. A Warra, S. Fatima
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The experimental investigation revealed that the hexane extract of onion seed oil has acid value, iodine value, peroxide value, saponification value, relative density and refractive index of 0.03±0.01 mgKOH/g, 129.80±0.21 gI2/100g, 3.00± 0.00 meq H2O2 203.00±0.71 mgKOH/g, 0.82±0.01and 1.44±0.00 respectively. The percentage yield was 50.28±0.01%. The colour of the oil was light green. We restricted our GC-MS spectra interpretation to compounds identification, particularly fatty acids and they are identified as palmitic acid, linolelaidic acid, oleic acid, stearic acid, behenic acid, linolenic acid and eicosatetraenoic acid. The pH , foam ability (cm³), total fatty matter, total alkali and percentage chloride of the onion oil soap were 11.03± 0.02, 75.13±0.15 (cm³), 36.66 ± 0.02 %, 0.92 ± 0.02% and 0.53 ± 0.15 % respectively. The texture was soft and the colour was lighter green. The results indicated that the hexane extract of the onion seed oil has potential for cosmetic industries.Keywords: onion seeds, soxhlet extraction, physicochemical, GC-MS, cold saponification
Procedia PDF Downloads 3061183 Heterogeneous Artifacts Construction for Software Evolution Control
Authors: Mounir Zekkaoui, Abdelhadi Fennan
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The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture
Procedia PDF Downloads 4341182 Automatic Method for Classification of Informative and Noninformative Images in Colonoscopy Video
Authors: Nidhal K. Azawi, John M. Gauch
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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.Keywords: colonoscopy classification, feature extraction, image alignment, machine learning
Procedia PDF Downloads 2461181 Audio Information Retrieval in Mobile Environment with Fast Audio Classifier
Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral
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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.Keywords: audio classification, audio extraction, environment mobile, musical information retrieval
Procedia PDF Downloads 5391180 Development and Implementation of Curvature Dependent Force Correction Algorithm for the Planning of Forced Controlled Robotic Grinding
Authors: Aiman Alshare, Sahar Qaadan
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A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm
Procedia PDF Downloads 3541179 Evaluating Performance of an Anomaly Detection Module with Artificial Neural Network Implementation
Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez
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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module
Procedia PDF Downloads 3341178 Recognition of Cursive Arabic Handwritten Text Using Embedded Training Based on Hidden Markov Models (HMMs)
Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss
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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.Keywords: recognition, handwriting, Arabic text, HMMs, embedded training
Procedia PDF Downloads 3451177 Cigarette Smoke Detection Based on YOLOV3
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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction
Procedia PDF Downloads 781176 Analysis of Various Copy Move Image Forgery Techniques for Better Detection Accuracy
Authors: Grishma D. Solanki, Karshan Kandoriya
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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.Keywords: copy-move image forgery, digital forensics, image forensics, image forgery
Procedia PDF Downloads 2791175 Dependence of Autoignition Delay Period on Equivalence Ratio for i-Octane, Primary Reference Fuel
Authors: Sunil Verma
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In today’s world non-renewable sources are depleting quickly, so there is a need to produce efficient and unconventional engines to minimize the use of fuel. Also, there are many fatal accidents happening every year during extraction, distillation, transportation and storage of fuel. Reason for explosions of gaseous fuel is unwanted autoignition. Autoignition characterstics of fuel are mandatory to study to build efficient engines and to avoid accidents. This report is concerned with study of autoignition delay characteristics of iso-octane by using rapid compression machine. The paper clearly explains the dependence of ignition delay characteristics on variation of equivalence ratios from lean to rich mixtures. The equivalence ratio is varied from 0.3 to 1.2.Keywords: autoignition, iso-octane, combustion, rapid compression machine, equivalence ratio, ignition delay
Procedia PDF Downloads 4391174 Plantation Forests Height Mapping Using Unmanned Aerial System
Authors: Shiming Li, Qingwang Liu, Honggan Wu, Jianbing Zhang
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Plantation forests are useful for timber production, recreation, environmental protection and social development. Stands height is an important parameter for the estimation of forest volume and carbon stocks. Although lidar is suitable technology for the vertical parameters extraction of forests, but high costs make it not suitable for operational inventory. With the development of computer vision and photogrammetry, aerial photos from unmanned aerial system can be used as an alternative solution for height mapping. Structure-from-motion (SfM) photogrammetry technique can be used to extract DSM and DEM information. Canopy height model (CHM) can be achieved by subtraction DEM from DSM. Our result shows that overlapping aerial photos is a potential solution for plantation forests height mapping.Keywords: forest height mapping, plantation forests, structure-from-motion photogrammetry, UAS
Procedia PDF Downloads 2721173 CMOS Solid-State Nanopore DNA System-Level Sequencing Techniques Enhancement
Authors: Syed Islam, Yiyun Huang, Sebastian Magierowski, Ebrahim Ghafar-Zadeh
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This paper presents system level CMOS solid-state nanopore techniques enhancement for speedup next generation molecular recording and high throughput channels. This discussion also considers optimum number of base-pair (bp) measurements through channel as an important role to enhance potential read accuracy. Effective power consumption estimation offered suitable rangeof multi-channel configuration. Nanopore bp extraction model in statistical method could contribute higher read accuracy with longer read-length (200 < read-length). Nanopore ionic current switching with Time Multiplexing (TM) based multichannel readout system contributed hardware savings.Keywords: DNA, nanopore, amplifier, ADC, multichannel
Procedia PDF Downloads 4481172 Automatic Detection of Suicidal Behaviors Using an RGB-D Camera: Azure Kinect
Authors: Maha Jazouli
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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition
Procedia PDF Downloads 1791171 Life Cycle Datasets for the Ornamental Stone Sector
Authors: Isabella Bianco, Gian Andrea Blengini
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The environmental impact related to ornamental stones (such as marbles and granites) is largely debated. Starting from the industrial revolution, continuous improvements of machineries led to a higher exploitation of this natural resource and to a more international interaction between markets. As a consequence, the environmental impact of the extraction and processing of stones has increased. Nevertheless, if compared with other building materials, ornamental stones are generally more durable, natural, and recyclable. From the scientific point of view, studies on stone life cycle sustainability have been carried out, but these are often partial or not very significant because of the high percentage of approximations and assumptions in calculations. This is due to the lack, in life cycle databases (e.g. Ecoinvent, Thinkstep, and ELCD), of datasets about the specific technologies employed in the stone production chain. For example, databases do not contain information about diamond wires, chains or explosives, materials commonly used in quarries and transformation plants. The project presented in this paper aims to populate the life cycle databases with specific data of specific stone processes. To this goal, the methodology follows the standardized approach of Life Cycle Assessment (LCA), according to the requirements of UNI 14040-14044 and to the International Reference Life Cycle Data System (ILCD) Handbook guidelines of the European Commission. The study analyses the processes of the entire production chain (from-cradle-to-gate system boundaries), including the extraction of benches, the cutting of blocks into slabs/tiles and the surface finishing. Primary data have been collected in Italian quarries and transformation plants which use technologies representative of the current state-of-the-art. Since the technologies vary according to the hardness of the stone, the case studies comprehend both soft stones (marbles) and hard stones (gneiss). In particular, data about energy, materials and emissions were collected in marble basins of Carrara and in Beola and Serizzo basins located in the province of Verbano Cusio Ossola. Data were then elaborated through an appropriate software to build a life cycle model. The model was realized setting free parameters that allow an easy adaptation to specific productions. Through this model, the study aims to boost the direct participation of stone companies and encourage the use of LCA tool to assess and improve the stone sector environmental sustainability. At the same time, the realization of accurate Life Cycle Inventory data aims at making available, to researchers and stone experts, ILCD compliant datasets of the most significant processes and technologies related to the ornamental stone sector.Keywords: life cycle assessment, LCA datasets, ornamental stone, stone environmental impact
Procedia PDF Downloads 2261170 A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments
Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda
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In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction
Procedia PDF Downloads 5061169 Combined Odd Pair Autoregressive Coefficients for Epileptic EEG Signals Classification by Radial Basis Function Neural Network
Authors: Boukari Nassim
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This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network
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