Search results for: biosignal processing

Authors: Assel Jaxylykova, Alexnder Pak

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This study utilized a Self-Organizing Map (SOM) for unsupervised learning on the CONLL-2003 dataset for Named Entity Recognition (NER). The process involved encoding words into 300-dimensional vectors using FastText. These vectors were input into a SOM grid, where training adjusted node weights to minimize distances. The SOM provided a topological representation for identifying and clustering named entities, demonstrating its efficacy without labeled examples. Results showed an F1-measure of 0.86, highlighting SOM's viability. Although some methods achieve higher F1 measures, SOM eliminates the need for labeled data, offering a scalable and efficient alternative. The SOM's ability to uncover hidden patterns provides insights that could enhance existing supervised methods. Further investigation into potential limitations and optimization strategies is suggested to maximize benefits.

Keywords: named entity recognition, natural language processing, self-organizing map, CONLL-2003, semantics

Procedia PDF Downloads 43

Authors: Subha D. Puthankattil, Paul K. Joseph

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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.

Keywords: EEG, depression, wavelet entropy, approximate entropy, relative wavelet energy, multiresolution decomposition

Procedia PDF Downloads 331

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 tasks. 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

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Authors: Gaurangi Saxena, Ravindra Saxena

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Lately, cloud computing is used to enhance the ability to attain corporate goals more effectively and efficiently at lower cost. This new computing paradigm “The Cloud Computing” has emerged as a powerful tool for optimum utilization of resources and gaining competitiveness through cost reduction and achieving business goals with greater flexibility. Realizing the importance of this new technique, most of the well known companies in computer industry like Microsoft, IBM, Google and Apple are spending millions of dollars in researching cloud computing and investigating the possibility of producing interface hardware for cloud computing systems. It is believed that by using the right middleware, a cloud computing system can execute all the programs a normal computer could run. Potentially, everything from most simple generic word processing software to highly specialized and customized programs designed for specific company could work successfully on a cloud computing system. A Cloud is a pool of virtualized computer resources. Clouds are not limited to grid environments, but also support “interactive user-facing applications” such as web applications and three-tier architectures. Cloud Computing is not a fundamentally new paradigm. It draws on existing technologies and approaches, such as utility Computing, Software-as-a-service, distributed computing, and centralized data centers. Some companies rent physical space to store servers and databases because they don’t have it available on site. Cloud computing gives these companies the option of storing data on someone else’s hardware, removing the need for physical space on the front end. Prominent service providers like Amazon, Google, SUN, IBM, Oracle, Salesforce etc. are extending computing infrastructures and platforms as a core for providing top-level services for computation, storage, database and applications. Application services could be email, office applications, finance, video, audio and data processing. By using cloud computing system a company can improve its customer relationship management. A CRM cloud computing system may be highly useful in delivering a sales team a blend of unique functionalities to improve agent/customer interactions. This paper attempts to first define the cloud computing as a tool for running business activities more effectively and efficiently at a lower cost; and then it distinguishes cloud computing with grid computing. Based on exhaustive literature review, authors discuss application of cloud computing in different disciplines of management especially in the field of marketing with special reference to use of cloud computing in CRM. Study concludes that CRM cloud computing platform helps a company track any data, such as orders, discounts, references, competitors and many more. By using CRM cloud computing, companies can improve its customer interactions and by serving them more efficiently that too at a lower cost can help gaining competitive advantage.

Keywords: cloud computing, competitive advantage, customer relationship management, grid computing

Procedia PDF Downloads 311

Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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Authors: Lumindu Dilumka, Ranaweera I. D., Sudusinghe S. P., Sanduni Kanchana A. M. K.

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This study was motivated by the challenges experienced by parents and guardians in ensuring the safety of children in cyberspace. In the last two or three years, online education has become very popular all over the world due to the Covid 19 pandemic. Therefore, parents, guardians and teachers must ensure the safety of children in cyberspace. Children are more likely to go astray and there are plenty of online programs are waiting to get them on the wrong track and also, children who are engaging in the online education can be distracted at any moment. Therefore, parents should keep a close check on their children's online activity. Apart from that, due to the unawareness of children, they tempt to share their sensitive information, causing a chance of being a victim of phishing attacks from outsiders. These problems can be overcome through the proposed web-based system. We use feature extraction, web tracking and analysis mechanisms, image processing and name entity recognition to implement this web-based system.

Keywords: online education, cyber bullying, social media, face recognition, web tracker, privacy data

Procedia PDF Downloads 86

Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

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This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

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Authors: Ihsane Modhaffar

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Fiber orientation is essential for the physical properties of composite materials. The theoretical parameters of a given reinforcement are usually known and widely used to predict the behavior of the material. In this work, we propose an image processing approach to estimate true principal directions and fiber orientation during injection molding processes of short fiber reinforced thermoplastics. Generally, a group of fibers are described in terms of probability distribution function or orientation tensor. Numerical techniques for the prediction of fiber orientation are also considered for concentrated situations. The flow was considered to be incompressible, and behave as Newtonian fluid containing suspensions of short-fibers. The governing equations, of this problem are: the continuity, the momentum and the energy. The obtained results were compared to available experimental findings. A good agreement between the numerical results and the experimental data was achieved.

Keywords: injection, composites, short-fiber reinforced thermoplastics, fiber orientation, incompressible fluid, numerical simulation

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Authors: Saleem Abuleil, Khalid S. Alsamara

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Events represent a significant source of information on the web; they deliver information about events that occurred around the world in all kind of subjects and areas. These events can be collected and organized to provide valuable and useful information for decision makers, researchers, as well as any person seeking knowledge. In this paper, we discuss an ongoing research to target stock markets domain to observe and record changes (events) when they happen, collect them, understand the meaning of each one of them, and organize the information along with meaning in a well-structured format. By using Semantic Role Labeling (SRL) technique, we identified four factors for each event in this paper: verb of action and three roles associated with it, entity name, attribute, and attribute value. We have generated a set of rules and techniques to support our approach to analyze and understand the meaning of the events taking place in stock markets.

Keywords: natuaral language processing, Arabic language, event extraction and understanding, sematic role labeling, stock market

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Authors: Shengzhu Cao, Hui Zhou, Gan Wu, Lanxi Wanhg, Kaifeng Zhang, Rui Wang, Hu Wang

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The functional micro and nanostructures, which can endow material surface with unique properties such as super-absorptance, hydrophobic and drag reduction. Recently, femtosecond laser ablation has been demonstrated to be a promising technology for surface functional micro and nanostructures fabrication. In this paper, using femtosecond laser ablation processing technique, we fabricated functional micro and nanostructures on Ti and Al alloy surfaces, test results showed that processed surfaces have 82%~96% absorptance over a broad wavelength range from ultraviolet to infrared. The surface function properties, which determined by micro and nanostructures, could be modulated by variation laser parameters. These functional surfaces may find applications in such areas as photonics, plasmonics, spaceborne devices, thermal radiation sources, solar energy absorbers and biomedicine.

Keywords: surface functional, micro and nanostructures, femtosecond laser, ablation

Procedia PDF Downloads 365

Authors: Drago Diaz Aleman, Jose Luis Saorin Perez, Cecile Meier, Itahisa Perez Conesa, Jorge De La Torre Cantero

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Traditional manufacturing techniques used in artistic contexts compete with highly productive and efficient industrial procedures. The craft techniques and associated business models tend to disappear under the pressure of the appearance of mass-produced products that compete in all niche markets, including those traditionally reserved for the work of art. The surplus value derived from the prestige of the author, the exclusivity of the product or the mastery of the artist, do not seem to be sufficient reasons to preserve this productive model. In the last years, the adoption of open source digital manufacturing technologies in small art workshops can favor their permanence by assuming great advantages such as easy accessibility, low cost, and free modification, adapting to specific needs of each workshop. It is possible to use pieces modeled by computer and made with FDM (Fused Deposition Modeling) 3D printers that use PLA (polylactic acid) in the procedures of artistic casting. Models printed by PLA are limited to approximate minimum sizes of 3 cm, and optimal layer height resolution is 0.1 mm. Due to these limitations, it is not the most suitable technology for artistic casting processes of smaller pieces. An alternative to solve size limitation, are printers from the type (SLS) "selective sintering by laser". And other possibility is a laser hardens, by layers, metal powder and called DMLS (Direct Metal Laser Sintering). However, due to its high cost, it is a technology that is difficult to introduce in small artistic foundries. The low-cost DLP (Digital Light Processing) type printers can offer high resolutions for a reasonable cost (around 0.02 mm on the Z axis and 0.04 mm on the X and Y axes), and can print models with castable resins that allow the subsequent direct artistic casting in precious metals or their adaptation to processes such as electroforming. In this work, the design of a DLP 3D printer is detailed, using backlit LCD screens with ultraviolet light. Its development is totally "open source" and is proposed as a kit made up of electronic components, based on Arduino and easy to access mechanical components in the market. The CAD files of its components can be manufactured in low-cost FDM 3D printers. The result is less than 500 Euros, high resolution and open-design with free access that allows not only its manufacture but also its improvement. In future works, we intend to carry out different comparative analyzes, which allow us to accurately estimate the print quality, as well as the real cost of the artistic works made with it.

Keywords: traditional artistic techniques, DLP 3D printer, artistic casting, electroforming

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Authors: Selma Hamimed, Abdelwaheb Chatti

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The current study deals with the biological treatment of saline wastewaters generated by various agro-food industries using Yarrowia lipolytica. The ability of this yeast was studied on the mixture of olive mill wastewater and tuna wash processing wastewater. Results showed that the high proportion of olive mill wastewater in the mixture about (75:25) is the suitable one for the highest Y. lipolytica biomass production, reaching 11.3 g L⁻¹ after seven days. In addition, results showed significant removal of chemical oxygen demand (COD) and phosphorous of 97.49 % and 98.90 %, respectively. On the other hand, Y. lipolytica was found to be effective to desalinate all mixtures reaching a removal of 92.21 %. Moreover, the analytical results using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) confirmed the biosorption of NaCl on the surface of the yeast as nanocrystals form with a size of 47.3 nm.

Keywords: nanocrystallization of NaCl, desalination, wastewater treatment, yarrowia lipolytica

Procedia PDF Downloads 186

Authors: Brady Manescau, Ilyas Sellami, Khaled Chetehouna, Charles De Izarra, Rachid Nait-Said, Fati Zidani

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During a fire in an oil and gas refinery, several thermal accidents can occur and cause serious damage to people and environment. Among these accidents, the BLEVE (Boiling Liquid Expanding Vapor Explosion) is most observed and remains a major concern for risk decision-makers. It corresponds to a violent vaporization of explosive nature following the rupture of a vessel containing a liquid at a temperature significantly higher than its normal boiling point at atmospheric pressure. Their effects on the environment generally appear in three ways: blast overpressure, radiation from the fireball if the liquid involved is flammable and fragment hazards. In order to estimate the potential damage that would be caused by such an explosion, risk decision-makers often use quantitative risk analysis (QRA). This analysis is a rigorous and advanced approach that requires a reliable data in order to obtain a good estimate and control of risks. However, in most cases, the data used in QRA are obtained from the empirical correlations. These empirical correlations generally overestimate BLEVE effects because they are based on simplifications and do not take into account real parameters like the geometry effect. Considering that these risk analyses are based on an assessment of BLEVE effects on human life and plant equipment, more precise and reliable data should be provided. From this point of view, the CFD modeling of BLEVE effects appears as a solution to the empirical law limitations. In this context, the main objective is to develop a numerical tool in order to predict BLEVE thermal effects using the CFD code FDS version 6. Simulations are carried out with a mesh size of 1 m. The fireball source is modeled as a vertical release of hot fuel in a short time. The modeling of fireball dynamics is based on a single step combustion using an EDC model coupled with the default LES turbulence model. Fireball characteristics (diameter, height, heat flux and lifetime) issued from the large scale BAM experiment are used to demonstrate the ability of FDS to simulate the various steps of the BLEVE phenomenon from ignition up to total burnout. The influence of release parameters such as the injection rate and the radiative fraction on the fireball heat flux is also presented. Predictions are very encouraging and show good agreement in comparison with BAM experiment data. In addition, a numerical study is carried out on an operational propane accumulator in an Algerian gas processing plant of SONATRACH company located in the Hassi R’Mel Gas Field (the largest gas field in Algeria).

Keywords: BLEVE effects, CFD, FDS, fireball, LES, QRA

Procedia PDF Downloads 184

Authors: Manjula Sutagundar, B. G. Sheeparamatti, D. S. Jangamshetti

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Micro Electro Mechanical Systems (MEMS) resonators have shown the potential of replacing quartz crystal technology for sensing and high frequency signal processing applications because of inherent advantages like small size, high quality factor, low cost, compatibility with integrated circuit chips. This paper presents the optimization and modelling and simulation of the optimized micro cantilever resonator. The objective of the work is to optimize the dimensions of a micro cantilever resonator for a specified range of resonant frequency and specific quality factor. Optimization is carried out using genetic algorithm. The genetic algorithm is implemented using MATLAB. The micro cantilever resonator is modelled in CoventorWare using the optimized dimensions obtained from genetic algorithm. The modeled cantilever is analysed for resonance frequency.

Keywords: MEMS resonator, genetic algorithm, modelling and simulation, optimization

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Authors: Nirmal Sugathan, Santosh Maruthy

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Background: A considerable number of studies have evidenced that phonological encoding (PE) and working memory (WM) skills operate differently in adults who stutter (AWS). In order to tap these skills, several paradigms have been employed such as phonological priming, phoneme monitoring, and nonword repetition tasks. This study, however, utilizes a word jumble paradigm to assess both PE and WM using different modalities and this may give a better understanding of phonological processing deficits in AWS. Aim: The present study investigated PE and WM abilities in conjunction with lexical access in AWS using jumbled words. The study also aimed at investigating the effect of increase in cognitive load on phonological processing in AWS by comparing the speech reaction time (SRT) and accuracy scores across various syllable lengths. Method: Participants were 11 AWS (Age range=19-26) and 11 adults who do not stutter (AWNS) (Age range=19-26) matched for age, gender and handedness. Stimuli: Ninety 3-, 4-, and 5-syllable jumbled words (JWs) (n=30 per syllable length category) constructed from Kannada words served as stimuli for jumbled word paradigm. In order to generate jumbled words (JWs), the syllables in the real words were randomly transpositioned. Procedures: To assess PE, the JWs were presently visually using DMDX software and for WM task, JWs were presented through auditory mode through headphones. The participants were asked to silently manipulate the jumbled words to form a Kannada real word and verbally respond once. The responses for both tasks were audio recorded using record function in DMDX software and the recorded responses were analyzed using PRAAT software to calculate the SRT. Results: SRT: Mann-Whitney test results demonstrated that AWS performed significantly slower on both tasks (p < 0.001) as indicated by increased SRT. Also, AWS presented with increased SRT on both the tasks in all syllable length conditions (p < 0.001). Effect of syllable length: Wilcoxon signed rank test was carried out revealed that, on task assessing PE, the SRT of 4syllable JWs were significantly higher in both AWS (Z= -2.93, p=.003) and AWNS (Z= -2.41, p=.003) when compared to 3-syllable words. However, the findings for 4- and 5-syllable words were not significant. Task Accuracy: The accuracy scores were calculated for three syllable length conditions for both PE and PM tasks and were compared across the groups using Mann-Whitney test. The results indicated that the accuracy scores of AWS were significantly below that of AWNS in all the three syllable conditions for both the tasks (p < 0.001). Conclusion: The above findings suggest that PE and WM skills are compromised in AWS as indicated by increased SRT. Also, AWS were progressively less accurate in descrambling JWs of increasing syllable length and this may be interpreted as, rather than existing as a uniform deficiency, PE and WM deficits emerge when the cognitive load is increased. AWNS exhibited increased SRT and increased accuracy for JWs of longer syllable length whereas AWS was not benefited from increasing the reaction time, thus AWS had to compromise for both SRT and accuracy while solving JWs of longer syllable length.

Keywords: adults who stutter, phonological ability, working memory, encoding, jumbled words

Procedia PDF Downloads 238

Authors: Peyman Sheikholharam Mashhadi

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Difficulties in analyzing real world images in classical image processing and machine vision framework have motivated researchers towards considering the biology-based vision. It is a common belief that mammalian visual cortex has been adapted to the statistics of the real world images through the evolution process. There are two well-known successful models of mammalian visual cortical cells: Independent Component Analysis (ICA) and Independent Subspace Analysis (ISA). In this paper, we statistically analyze the dependencies which remain in the components after applying these models to the natural images. Also, we investigate the response of feature detectors to gratings with various parameters in order to find optimal parameters of the feature detectors. Finally, the selectiveness of feature detectors to phase, in both models is considered.

Keywords: statistics, independent component analysis, independent subspace analysis, phase, natural images

Procedia PDF Downloads 338

Authors: Seyed Ata Khalkhkali Sharifi, Gholamhossein Majzoubi, Farhad Abroush

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Developing mechanical properties of pure titanium has been reviewed in this paper by using ECAP process. At the first step of this article, the experimental samples were prepared as mentioned in the standards. Then pure grade 2 Ti was processed via equal-channel angular pressing (ECAp) for 2 passes following route-A at 400°C. After processing, the microstructural evolution, tensile, fatigue, hardness properties and wear behavior were investigated. Finally, the effect of ECAP process on these samples was analyzed. The results showed improvement in strength values with a slight decrease in ductility. The analysis on 30 points within the sample showed hardness increase in each pass. Also, it was concluded that fatigue properties were increased too.

Keywords: equal-channel angular pressing, titanium, mechanical behavior, engineering materials and applications

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Authors: M. T. Artese, G. Ciocca, I. Gagliardi

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Food is a social and cultural aspect of every individual. Food products, processing, and traditions have been identified as cultural objects carrying history and identity of social groups. Traditional recipes are passed down from one generation to the other, often to strengthen the link with the territory. The paper presents CookIT, a web portal developed to collect Italian traditional recipes related to regional cuisine, with the purpose to disseminate the knowledge of typical Italian recipes and the Mediterranean diet which is a significant part of Italian cuisine. The system designed is completed with multimodal means of browsing and data retrieval. Stored recipes can be retrieved integrating and combining a number of different methods and keys, while the results are displayed using classical styles, such as list and mosaic, and also using maps and graphs, with which users can play using available keys for interaction.

Keywords: collaborative portal, Italian cuisine, intangible cultural heritage, traditional recipes, searching and browsing

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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

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Authors: Noura Al-Ajmi, Mohammed A. Almulla

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With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

Keywords: headache diagnosis system, prescription recommender system, expert system, backward rule-based system

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Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

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At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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Authors: Kunj Parikh, S. Bhattacharya, V. Natarajan

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TCAD numerical simulation is one of the most tried and tested powerful tools for designing devices in semiconductor foundries worldwide. It has also been used to explain conduction in organic thin films where the processing temperature is often enough to make homogeneous samples (often imperfect, but homogeneously imperfect). In this report, we have presented the results of TCAD simulation in multi-grain thin films. The work has addressed the inhomogeneity in one dimension, but can easily be extended to two and three dimensions. The effect of grain boundaries has mainly been approximated as barriers located at the junction between two adjacent grains. The effect of the value of grain boundary barrier, the bulk traps, and the measurement temperature have been investigated.

Keywords: polycrystalline thin films, space charge limited conduction, Technology Computer-Aided Design (TCAD) simulation, traps

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Authors: D. Sun, L. Saw, A. Onyianta, D. O’Rourke, Z. Lu, C. See, C. Wilson, C. Popescu, M. Dorris

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With the rapid development of wearable technology (e.g., smartwatch, activity trackers and health monitor devices), flexible dielectric materials with environmental-friendly, low-cost and high-energy efficiency characteristics are in increasing demand. In this work, a flexible dielectric nanocomposite was processed by incorporating two components: cellulose nanofibrils and alum sludge in a polymer matrix. The two components were used in the reinforcement phase as well as for enhancing the dielectric properties; they were processed using waste materials that would otherwise be disposed to landfills. Alum sludge is a by-product of the water treatment process in which aluminum sulfate is prevalently used as the primary coagulant. According to the data from a project partner-Scottish Water: there are approximately 10k tons of alum sludge generated as a waste from the water treatment work to be landfilled every year in Scotland. The industry has been facing escalating financial and environmental pressure to develop more sustainable strategies to deal with alum sludge wastes. In the available literature, some work on reusing alum sludge has been reported (e.g., aluminum recovery or agriculture and land reclamation). However, little work can be found in applying it to processing energy materials (e.g., dielectrics) for enhanced energy density and efficiency. The alum sludge was collected directly from a water treatment plant of Scottish Water and heat-treated and refined before being used in preparing composites. Cellulose nanofibrils were derived from water hyacinth, an invasive aquatic weed that causes significant ecological issues in tropical regions. The harvested water hyacinth was dried and processed using a cost-effective method, including a chemical extraction followed by a homogenization process in order to extract cellulose nanofibrils. Biodegradable elastomer polydimethylsiloxane (PDMS) was used as the polymer matrix and the nanocomposites were processed by casting raw materials in Petri dishes. The processed composites were characterized using various methods, including scanning electron microscopy (SEM), rheological analysis, thermogravimetric and X-ray diffraction analysis. The SEM result showed that cellulose nanofibrils of approximately 20nm in diameter and 100nm in length were obtained and the alum sludge particles were of approximately 200um in diameters. The TGA/DSC analysis result showed that a weight loss of up to 48% can be seen in the raw material of alum sludge and its crystallization process has been started at approximately 800°C. This observation coincides with the XRD result. Other experiments also showed that the composites exhibit comprehensive mechanical and dielectric performances. This work depicts that it is a sustainable practice of reusing such waste materials in preparing flexible, lightweight and miniature dielectric materials for wearable technology applications.

Keywords: cellulose, biodegradable, sustainable, alum sludge, nanocomposite, wearable technology, dielectric

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Authors: Senem Suna

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Extraction of bioactive compounds from several food/food products comes as an important topic and new trend related with health promoting effects. As a result of the increasing interest in natural foods, different methods are used for the acquisition of these components especially polyphenols. However, special attention has to be paid to the selection of proper techniques or several processing technologies (supercritical fluid extraction, microwave-assisted extraction, ultrasound-assisted extraction, powdered extracts production) for each kind of food to get maximum benefit as well as the obtainment of phenolic compounds. In order to meet consumer’s demand for healthy food and the management of quality and safety requirements, advanced research and development are needed. In this review, advantages, and disadvantages of different extraction methods, their opportunities to be used in food industry and the effects of polyphenols are mentioned in details. Consequently, with the evaluation of the results of several studies, the selection of the most suitable food specific method was aimed.

Keywords: bioactives, extraction, powdered extracts, supercritical fluid extraction

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

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The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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Authors: Rogelio Luck, Yucheng Liu

Abstract:

This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

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Authors: Daniel S. Brox

Abstract:

Starting from earthquake fault dynamic equations, a correspondence between earthquake occurrence statistics in a seismic region before a major earthquake and eigenvalue statistics of a differential operator whose bound state eigenfunctions characterize the distribution of stress in the seismic region is derived. Modeling these eigenvalue statistics with a 2D Coulomb gas statistical physics model, previously reported deviation of seismic activation earthquake occurrence statistics from Gutenberg-Richter statistics in time intervals preceding the major earthquake is derived. It also explains how statistical physics modeling predicts a finite-dimensional nonlinear dynamic system that describes real-time velocity model evolution in the region undergoing seismic activation and how this prediction can be tested experimentally.

Keywords: seismic activation, statistical physics, geodynamics, signal processing

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Authors: Amit Kamra, V. K. Jain, Pragya

Abstract:

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 state-of-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

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Authors: Faiza Hussain, Usman Qamar

Abstract:

Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

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Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

Abstract:

Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

Procedia PDF Downloads 257