Search results for: fields extraction from administrative documents
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5352

Search results for: fields extraction from administrative documents

4932 Density Determination by Dilution for Extra Heavy Oil Residues Obtained Using Molecular Distillation and Supercritical Fluid Extraction as Upgrading and Refining Process

Authors: Oscar Corredor, Alexander Guzman, Adan Leon

Abstract:

Density is a bulk physical property that indicates the quality of a petroleum fraction. It is also a useful property to estimate various physicochemical properties of fraction and petroleum fluids; however, the determination of density of extra heavy residual (EHR) fractions by standard methodologies, (ASTM D70) shows limitations for samples with higher densities than 1.0879 g/cm3. For this reason, a dilution methodology was developed in order to determinate density for those particular fractions, 87 (EHR) fractions were obtained as products of the fractionation of Colombian typical Vacuum Distillation Residual Fractions using molecular distillation (MD) and extraction with Solvent N-hexane in Supercritical Conditions (SFEF) pilot plants. The proposed methodology showed reliable results that can be demonstrated with the standard deviation of repeatability and reproducibility values of 0.0031 and 0.0061 g/ml respectively. In the same way, it was possible to determine densities in fractions EHR up to 1.1647g/cm3 and °API values obtained were ten times less than the water reference value.

Keywords: API, density, vacuum residual, molecular distillation, supercritical fluid extraction

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4931 Breakthrough Highly-Effective Extraction of Perfluoroctanoic Acid Using Natural Deep Eutectic Solvents

Authors: Sana Eid, Ahmad S. Darwish, Tarek Lemaoui, Maguy Abi Jaoude, Fawzi Banat, Shadi W. Hasan, Inas M. AlNashef

Abstract:

Addressing the growing challenge of per- and polyfluoroalkyl substances (PFAS) pollution in water bodies, this study introduces natural deep eutectic solvents (NADESs) as a pioneering solution for the efficient extraction of perfluorooctanoic acid (PFOA), one of the most persistent and concerning PFAS pollutants. Among the tested NADESs, trioctylphosphine oxide: lauric acid (TOPO:LauA) in a 1:1 molar ratio was distinguished as the most effective, achieving an extraction efficiency of approximately 99.52% at a solvent-to-feed (S:F) ratio of 1:2, room temperature, and neutral pH. This efficiency is achieved within a notably short mixing time of only one min, which is significantly less than the time required by conventional methods, underscoring the potential of TOPO:LauA for rapid and effective PFAS remediation. TOPO:LauA maintained consistent performance across various operational parameters, including a range of initial PFOA concentrations (0.1 ppm to 1000 ppm), temperatures (15 °C to 100 °C), pH values (3 to 9), and S:F ratios (2:3 to 1:7), demonstrating its versatility and robustness. Furthermore, its effectiveness was consistently high over seven consecutive extraction cycles, highlighting TOPO:LauA as a sustainable, environmentally friendly alternative to hazardous organic solvents, with promising applications for reliable, repeatable use in combating persistent water pollutants such as PFOA.

Keywords: deep eutectic solvents, natural deep eutectic solvents, perfluorooctanoic acid, water remediation

Procedia PDF Downloads 37
4930 Biomedical Definition Extraction Using Machine Learning with Synonymous Feature

Authors: Jian Qu, Akira Shimazu

Abstract:

OOV (Out Of Vocabulary) terms are terms that cannot be found in many dictionaries. Although it is possible to translate such OOV terms, the translations do not provide any real information for a user. We present an OOV term definition extraction method by using information available from the Internet. We use features such as occurrence of the synonyms and location distances. We apply machine learning method to find the correct definitions for OOV terms. We tested our method on both biomedical type and name type OOV terms, our work outperforms existing work with an accuracy of 86.5%.

Keywords: information retrieval, definition retrieval, OOV (out of vocabulary), biomedical information retrieval

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4929 Interoperability Standard for Data Exchange in Educational Documents in Professional and Technological Education: A Comparative Study and Feasibility Analysis for the Brazilian Context

Authors: Giovana Nunes Inocêncio

Abstract:

The professional and technological education (EPT) plays a pivotal role in equipping students for specialized careers, and it is imperative to establish a framework for efficient data exchange among educational institutions. The primary focus of this article is to address the pressing need for document interoperability within the context of EPT. The challenges, motivations, and benefits of implementing interoperability standards for digital educational documents are thoroughly explored. These documents include EPT completion certificates, academic records, and curricula. In conjunction with the prior abstract, it is evident that the intersection of IT governance and interoperability standards holds the key to transforming the landscape of technical education in Brazil. IT governance provides the strategic framework for effective data management, aligning with educational objectives, ensuring compliance, and managing risks. By adopting interoperability standards, the technical education sector in Brazil can facilitate data exchange, enhance data security, and promote international recognition of qualifications. The utilization of the XML (Extensible Markup Language) standard further strengthens the foundation for structured data exchange, fostering efficient communication, standardization of curricula, and enhancing educational materials. The IT governance, interoperability standards, and data management critical role in driving the quality, efficiency, and security of technical education. The adoption of these standards fosters transparency, stakeholder coordination, and regulatory compliance, ultimately empowering the technical education sector to meet the dynamic demands of the 21st century.

Keywords: interoperability, education, standards, governance

Procedia PDF Downloads 51
4928 Study of Chemical Compounds of Garlic

Authors: Bazaraliyeva Aigerim Bakytzhanovna, Turgumbayeva Aknur Amanbekovna

Abstract:

The phytosubstance from garlic was obtained by extraction with liquid carbon dioxide under critical conditions. Methods of processing raw materials are proposed, and the chemical composition of garlic is studied by gas chromatography and mass spectrometry. The garlic extract's composition was determined using gas chromatography (GC) and gas chromatography-mass spectrophotometry (GC-MS). The phytosubstance had 54 constituents. The extract included the following main compounds: Manool (39.56%), Viridifrolol (7%), Podocarpa-1,8,11,13-tetraen-3-one, 14-isopropyl-1,13-dimethoxy- 5,15 percent, (+)-2-Bornanone (4.29%), Thujone (3.49%), Linolic acid ethyl ester (3.41%), and 12-O-Methylcarn.

Keywords: allium sativum, bioactive compounds of garlic, carbon dioxide extraction of garlic, GS-MS method

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4927 Optimization of Ultrasound-Assisted Extraction and Microwave-Assisted Acid Digestion for the Determination of Heavy Metals in Tea Samples

Authors: Abu Harera Nadeem, Kingsley Donkor

Abstract:

Tea is a popular beverage due to its flavour, aroma and antioxidant properties—with the most consumed varieties being green and black tea. Antioxidants in tea can lower the risk of Alzheimer’s and heart disease and obesity. However, these teas contain heavy metals such as Hg, Cd, or Pb, which can cause autoimmune diseases like Graves disease. In this study, 11 heavy metals in various commercial green, black, and oolong tea samples were determined using inductively coupled plasma-mass spectrometry (ICP-MS). Two methods of sample preparation were compared for accuracy and precision, which were microwave-assisted digestion and ultrasonic-assisted extraction. The developed method was further validated by detection limit, precision, and accuracy. Results showed that the proposed method was highly sensitive with detection limits within parts-per-billion levels. Reasonable method accuracy was obtained by spiked experiments. The findings of this study can be used to delve into the link between tea consumption and disease and to provide information for future studies on metal determination in tea.

Keywords: ICP-MS, green tea, black tea, microwave-assisted acid digestion, ultrasound-assisted extraction

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4926 The Impact of Total Quality Management Practices on Innovation: An Empirical Study

Authors: Oumayma Tajouri

Abstract:

The relationship between total quality management (TQM) practices and innovation is conflictual. Some scholars suggest that TQM has an effect on incremental improvement and would not lead to innovation and creativity. The purpose of this paper is to analyse the association between TQM and different types of innovation. Our goal is to examine to what extent the implementation of TQM practices is indeed supporting innovation in the Tunisian ISO 9001 certified industries. Using a self-administered survey to sample ISO9001 certified industry companies, this study examines five hypotheses and tests the relation between TQM practices and innovation. The principal finding of this study is that TQM has significant and positive effects on innovation in the Tunisian context. The results support that TQM has an influence on incremental, radical, and administrative innovation.

Keywords: total quality management, incremental innovation product and/service, radical innovation product/service, incremental innovation process, radical innovation process, administrative innovation

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4925 Comparative Pre-treatment Analysis of RNA-Extraction Methods and Efficient Detection of SARS-COV-2 and PMMoV in Influents and 1ˢᵗ Sedimentation from a Wastewater Treatment Plan

Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Fumitake Nishimura, Jaiyeop Lee

Abstract:

This study aimed to compare two pre-treatment and two RNA extraction methods, namely PEG, and Nano bubble, Viral RNA Soil, and Mini Kit, in terms of their efficiency in detecting SARS-CoV-2 and PMMoV in influent and 1st sedimentation samples from a wastewater treatment plant. The extracted RNA samples were quantified and evaluated for purity, yield, and integrity. The results indicated that the nanobubble PEG method provided the highest yield of RNA, while the QIAamp Viral RNA Mini Kit produced the purest RNA samples. In terms of sensitivity and specificity, all these methods were able to detect SARS-CoV-2 and PMMoV in both influent and 1st sedimentation samples. However, the nanobubble PEG method showed slightly higher sensitivity compared to the other methods. These findings suggest that the choice of RNA extraction method should depend on the downstream application and the quality of the RNA required. The study also highlights the potential of wastewater-based epidemiology as an effective and non-invasive method for monitoring the spread of infectious diseases in a community.

Keywords: influent, PMMoV, SARS-CoV-2, wastewater based epidemiology

Procedia PDF Downloads 75
4924 Product Features Extraction from Opinions According to Time

Authors: Kamal Amarouche, Houda Benbrahim, Ismail Kassou

Abstract:

Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone...); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic.

Keywords: opinion mining, product feature extraction, sentiment analysis, SentiWordNet

Procedia PDF Downloads 377
4923 Exploring Syntactic and Semantic Features for Text-Based Authorship Attribution

Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

Abstract:

Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

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4922 Status of Bio-Graphene Extraction from Biomass: A Review

Authors: Simon Peter Wafula, Ziporah Nakabazzi Kitooke

Abstract:

Graphene is a carbon allotrope made of a two-dimensional shape. This material has got a number of materials researchers’ interest due to its properties that are special compared to ordinary material. Graphene is thought to enhance a number of material properties in the manufacturing, energy, and construction industries. Many studies consider graphene to be a wonder material, just like plastic in the 21st century. This shows how much should be invested in graphene research. This review highlights the status of graphene extracted from various biomass sources together with their appropriate extraction techniques, including the pretreatment methods for a better product. The functional groups and structure of graphene extracted using several common methods of synthesis are in this paper as well. The review explores methods like chemical vapor deposition (CVD), hydrothermal, chemical exfoliation method, liquid exfoliation, and Hummers. Comparative analysis of the various extraction techniques gives an insight into each of their advantages, challenges, and potential scalability. The review also highlights the pretreatment process for biomass before carbonation for better quality of bio-graphene. The various graphene modes, as well as their applications, are in this study. Recommendations for future research for improving the efficiency and sustainability of bio-graphene are highlighted.

Keywords: exfoliation, nanomaterials, biochar, large-scale, two-dimension

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4921 Comprehensive Feature Extraction for Optimized Condition Assessment of Fuel Pumps

Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

Abstract:

The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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4920 Teachers’ Role and Principal’s Administrative Functions as Correlates of Effective Academic Performance of Public Secondary School Students in Imo State, Nigeria

Authors: Caroline Nnokwe, Iheanyi Eneremadu

Abstract:

Teachers and principals are vital and integral parts of the educational system. For educational objectives to be met, the role of teachers and the functions of the principals are not to be overlooked. However, the inability of teachers and principals to carry out their roles effectively has impacted the outcome of the students’ performance. The study, therefore, examined teachers’ roles and principal’s administrative functions as correlates of effective academic performance of public secondary school students in Imo state, Nigeria. Four research questions and two hypotheses guided the study. The study adopted a correlation research design. The sample size was 5,438 respondents via the Yaro-Yamane technique, which consists of 175 teachers, 13 principals and 5,250 students using the proportional stratified random sampling technique. The instruments for data collection were a researcher-made questionnaire titled Teachers’ Role/Principals’ Administrative Functions Questionnaire (TRPAFQ) with a Cronbach Alpha coefficient of .82 and student's internal results obtained from the school authorities. Data collected were analyzed using the Pearson product-moment correlation coefficient and simple linear regression. Research questions were answered using Pearson Product Moment Correlation statistics, while the hypotheses were tested at 0.05 level of significance using regression analysis. The findings of the study showed that the educational qualification of teachers, organizing, and planning correlated student’s academic performance to a great extent, while availability and proper use of instructional materials by teachers correlated the academic performance of students to a very high extent. The findings also revealed that there is a significant relationship between teachers’ role, principals’ administrative functions and student’s academic performance of public secondary schools in Imo State, The study recommended among others that there is the need for government, through the ministry of education, and education authorities to adequately staff their supervisory department in order to carry out proper supervision of secondary school teachers, and also provide adequate instructional materials to ensure greater academic performance among secondary school students of Imo state, Nigeria.

Keywords: instructional materials, principals’ administrative functions, students’ academic performance, teacher role

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4919 Feature Extraction and Classification Based on the Bayes Test for Minimum Error

Authors: Nasar Aldian Ambark Shashoa

Abstract:

Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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4918 Keypoints Extraction for Markerless Tracking in Augmented Reality Applications: A Case Study in Dar As-Saraya Museum

Authors: Jafar W. Al-Badarneh, Abdalkareem R. Al-Hawary, Abdulmalik M. Morghem, Mostafa Z. Ali, Rami S. Al-Gharaibeh

Abstract:

Archeological heritage is at the heart of each country’s national glory. Moreover, it could develop into a source of national income. Heritage management requires socially-responsible marketing that achieves high visitor satisfaction while maintaining high site conservation. We have developed an Augmented Reality (AR) experience for heritage and cultural reservation at Dar-As-Saraya museum in Jordan. Our application of this notion relied on markerless-based tracking approach. This approach uses keypoints extraction technique where features of the environment are identified and defined into the system as keypoints. A set of these keypoints forms a tracker for an augmented object to be displayed and overlaid with a real scene at Dar As-Saraya museum. We tested and compared several techniques for markerless tracking and then applied the best technique to complete a mosaic artifact with AR content. The successful results from our application open the door for applications in open archeological sites where markerless tracking is mostly needed.

Keywords: augmented reality, cultural heritage, keypoints extraction, virtual recreation

Procedia PDF Downloads 318
4917 Integration of the Electro-Activation Technology for Soy Meal Valorization

Authors: Natela Gerliani, Mohammed Aider

Abstract:

Nowadays, the interest of using sustainable technologies for protein extraction from underutilized oilseeds is growing. Currently, a major disposal problem for the oil industry is by-products of plant food processing such as soybean meal. That is why valorization of soybean meal is important for the oil industry since it contains high-quality proteins and other valuable components. Generally, soybean meal is used in livestock and poultry feed but is rarely used in human feed. Though chemical composition of this meal compensate nutritional deficiency and can be used to balance protein in human food. Regarding the efficiency of soybean meal valorization, extraction is a key process for obtaining enriched protein ingredient, which can be incorporated into the food matrix. However, most of the food components such as proteins extracted from oilseeds by-products imply the utilization of organic and inorganic chemicals (e.g. acids, bases, TCA-acetone) having a significant environmental impact. In a context of sustainable production, the use of an electro-activation technology seems to be a good alternative. Indeed, the electro-activation technology requires only water, food grade salt and electricity as main materials. Moreover, this innovative technology helps to avoid special equipment and trainings for workers safety as well as transport and storage of hazardous materials. Electro-activation is a technology based on applied electrochemistry for the generation of acidic and alkaline solutions on the basis of the oxidation-reduction reactions that occur at the vicinity electrode/solution interfaces. It is an eco-friendly process that can be used to replace the conventional acidic and alkaline extraction. In this research, the electro-activation technology for protein extraction from soybean meal was carried out in the electro-activation reactor. This reactor consists of three compartments separated by cation and anion exchange membranes that allow creating non-contacting acidic and basic solutions. Different current intensities (150 mA, 300 mA and 450 mA) and treatment durations (10 min, 30 min and 50 min) were tested. The results showed that the extracts obtained by the electro-activation method have good quality in comparison to conventional extracts. For instance, extractability obtained with electro-activation method was 55% whereas with the conventional method it was only 36%. Moreover, a maximum protein quantity of 48 % in the extract was obtained with the electro-activation technology comparing to the maximum amount of protein obtained by conventional extraction of 41 %. Hence, the environmentally sustainable electro-activation technology seems to be a promising type of protein extraction that can replace conventional extraction technology.

Keywords: by-products, eco-friendly technology, electro-activation, soybean meal

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4916 The Effect of Electromagnetic Stirring during Solidification of Nickel Based Alloys

Authors: Ricardo Paiva, Rui Soares, Felix Harnau, Bruno Fragoso

Abstract:

Nickel-based alloys are materials well suited for service in extreme environments subjected to pressure and heat. Some industrial applications for Nickel-based alloys are aerospace and jet engines, oil and gas extraction, pollution control and waste processing, automotive and marine industry. It is generally recognized that grain refinement is an effective methodology to improve the quality of casted parts. Conventional grain refinement techniques involve the addition of inoculation substances, the control of solidification conditions, or thermomechanical treatment with recrystallization. However, such methods often lead to non-uniform grain size distribution and the formation of hard phases, which are detrimental to both wear performance and biocompatibility. Stirring of the melt by electromagnetic fields has been widely used in continuous castings with success for grain refinement, solute redistribution, and surface quality improvement. Despite the advantages, much attention has not been paid yet to the use of this approach on functional castings such as investment casting. Furthermore, the effect of electromagnetic stirring (EMS) fields on Nickel-based alloys is not known. In line with the gaps/needs of the state-of-art, the present research work targets to promote new advances in controlling grain size and morphology of investment cast Nickel based alloys. For such a purpose, a set of experimental tests was conducted. A high-frequency induction furnace with vacuum and controlled atmosphere was used to cast the Inconel 718 alloy in ceramic shells. A coil surrounded the casting chamber in order to induce electromagnetic stirring during solidification. Aiming to assess the effect of the electromagnetic stirring on Ni alloys, the samples were subjected to microstructural analysis and mechanical tests. The results show that electromagnetic stirring can be an effective methodology to modify the grain size and mechanical properties of investment-cast parts.

Keywords: investment casting, grain refinement, electromagnetic stirring, nickel alloys

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4915 Applying Unmanned Aerial Vehicle on Agricultural Damage: A Case Study of the Meteorological Disaster on Taiwan Paddy Rice

Authors: Chiling Chen, Chiaoying Chou, Siyang Wu

Abstract:

Taiwan locates at the west of Pacific Ocean and intersects between continental and marine climate. Typhoons frequently strike Taiwan and come with meteorological disasters, i.e., heavy flooding, landslides, loss of life and properties, etc. Global climate change brings more extremely meteorological disasters. So, develop techniques to improve disaster prevention and mitigation is needed, to improve rescue processes and rehabilitations is important as well. In this study, UAVs (Unmanned Aerial Vehicles) are applied to take instant images for improving the disaster investigation and rescue processes. Paddy rice fields in the central Taiwan are the study area. There have been attacked by heavy rain during the monsoon season in June 2016. UAV images provide the high ground resolution (3.5cm) with 3D Point Clouds to develop image discrimination techniques and digital surface model (DSM) on rice lodging. Firstly, image supervised classification with Maximum Likelihood Method (MLD) is used to delineate the area of rice lodging. Secondly, 3D point clouds generated by Pix4D Mapper are used to develop DSM for classifying the lodging levels of paddy rice. As results, discriminate accuracy of rice lodging is 85% by image supervised classification, and the classification accuracy of lodging level is 87% by DSM. Therefore, UAVs not only provide instant images of agricultural damage after the meteorological disaster, but the image discriminations on rice lodging also reach acceptable accuracy (>85%). In the future, technologies of UAVs and image discrimination will be applied to different crop fields. The results of image discrimination will be overlapped with administrative boundaries of paddy rice, to establish GIS-based assist system on agricultural damage discrimination. Therefore, the time and labor would be greatly reduced on damage detection and monitoring.

Keywords: Monsoon, supervised classification, Pix4D, 3D point clouds, discriminate accuracy

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4914 Development of Metal-Organic Frameworks-Type Hybrid Functionalized Materials for Selective Uranium Extraction

Authors: Damien Rinsant, Eugen Andreiadis, Michael Carboni, Daniel Meyer

Abstract:

Different types of materials have been developed for the solid/liquid uranium extraction processes, such as functionalized organic polymers, hybrid silica or inorganic adsorbents. In general, these materials exhibit a moderate affinity for uranyl ions and poor selectivity against impurities like iron, vanadium or molybdenum. Moreover, the structural organization deficiency of these materials generates ion diffusion issues inside the material. Therefore, the aim of our study is to developed efficient and organized materials, stable in the acid media encountered in uranium extraction processes. Metal organic frameworks (MOFs) are hybrid crystalline materials consisting of an inorganic part (cluster or metal ions) and tailored organic linkers connected via coordination bonds. These hierarchical materials have exceptional surface area, thermal stability and a large variety of tunable structures. However, due to the reversibility of constitutive coordination bonds, MOFs have moderate stability in strongly complexing or acidic media. Only few of them are known to be stable in aqueous media and only one example is described in strong acidic media. However, these conditions are very often encountered in the environmental pollution remediation of mine wastewaters. To tackle the challenge of developing MOFs adapted for uranium extraction from acid mine waters, we have investigated the stability of several materials. To ensure a good stability we have synthetized and characterized different materials based on highly coordinated metal clusters, such as LnOFs and Zirconium based materials. Among the latter, the UiO family shows a great stability in sulfuric acid media even in the presence of 1.4 M sodium sulfate at pH 2. However, the stability in phosphoric media is reduced due to the high affinity between zirconium and phosphate ligand. Based on these results, we have developed a tertiary amine functionalized MOF denoted UiO-68-NMe2 particularly adapted for the extraction of anionic uranyl (VI) sulfate complexes mainly present in the acid mine solutions. The adsorption capacity of the material has been determined upon varying total sulfate concentration, contact time and uranium concentration. The extraction tests put in evidence different phenomena due to the complexity of the extraction media and the interaction between the MOF and sulfate anion. Finally, the extraction mechanisms and the interaction between uranyl and the MOF structure have been investigated. The functionalized material UiO-68-NMe2 has been characterized in the presence and absence of uranium by FT-IR, UV and Raman techniques. Moreover, the stability of the protonated amino functionalized MOF has been evaluated. The synthesis, characterization and evaluation of this type of hybrid material, particularly adapted for uranium extraction in sulfuric acid media by an anionic exchange mechanism, paved the way for the development of metal organic frameworks functionalized by different other chelating motifs, such as bifunctional ligands showing an enhanced affinity and selectivity for uranium in acid and complexing media. Work in this direction is currently in progress.

Keywords: extraction, MOF, ligand, uranium

Procedia PDF Downloads 139
4913 Review on Effective Texture Classification Techniques

Authors: Sujata S. Kulkarni

Abstract:

Effective and efficient texture feature extraction and classification is an important problem in image understanding and recognition. This paper gives a review on effective texture classification method. The objective of the problem of texture representation is to reduce the amount of raw data presented by the image, while preserving the information needed for the task. Texture analysis is important in many applications of computer image analysis for classification include industrial and biomedical surface inspection, for example for defects and disease, ground classification of satellite or aerial imagery and content-based access to image databases.

Keywords: compressed sensing, feature extraction, image classification, texture analysis

Procedia PDF Downloads 409
4912 Time-Frequency Feature Extraction Method Based on Micro-Doppler Signature of Ground Moving Targets

Authors: Ke Ren, Huiruo Shi, Linsen Li, Baoshuai Wang, Yu Zhou

Abstract:

Since some discriminative features are required for ground moving targets classification, we propose a new feature extraction method based on micro-Doppler signature. Firstly, the time-frequency analysis of measured data indicates that the time-frequency spectrograms of the three kinds of ground moving targets, i.e., single walking person, two people walking and a moving wheeled vehicle, are discriminative. Then, a three-dimensional time-frequency feature vector is extracted from the time-frequency spectrograms to depict these differences. At last, a Support Vector Machine (SVM) classifier is trained with the proposed three-dimensional feature vector. The classification accuracy to categorize ground moving targets into the three kinds of the measured data is found to be over 96%, which demonstrates the good discriminative ability of the proposed micro-Doppler feature.

Keywords: micro-doppler, time-frequency analysis, feature extraction, radar target classification

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4911 Data Mining Meets Educational Analysis: Opportunities and Challenges for Research

Authors: Carla Silva

Abstract:

Recent development of information and communication technology enables us to acquire, collect, analyse data in various fields of socioeconomic – technological systems. Along with the increase of economic globalization and the evolution of information technology, data mining has become an important approach for economic data analysis. As a result, there has been a critical need for automated approaches to effective and efficient usage of massive amount of educational data, in order to support institutions to a strategic planning and investment decision-making. In this article, we will address data from several different perspectives and define the applied data to sciences. Many believe that 'big data' will transform business, government, and other aspects of the economy. We discuss how new data may impact educational policy and educational research. Large scale administrative data sets and proprietary private sector data can greatly improve the way we measure, track, and describe educational activity and educational impact. We also consider whether the big data predictive modeling tools that have emerged in statistics and computer science may prove useful in educational and furthermore in economics. Finally, we highlight a number of challenges and opportunities for future research.

Keywords: data mining, research analysis, investment decision-making, educational research

Procedia PDF Downloads 333
4910 Influence of Alcohol to Quality Iota Type Carrageenan

Authors: Andi Hasizah Mochtar, Meta Mahendradatta, Amran Laga, Metusalach Metusalach, Salengke Salengke, Mariati Bilang, Andi Amijoyo Mochtar, Reta Reta, Aminah Muhdar, Sri Suhartini

Abstract:

This study aims to determine the effect of alcohol type on the quality of iota carrageenan-based on extraction technology through the application of ohmic reactor. Results of this analysis will be used as a reference for selecting the proper type of alcohol used for carrageenan precipitated after extraction by technology based ohmic. The results of analysis performed included analysis of viscosity, gel strength, and yield of iota carrageenan. Viscosity is the highest obtained at precipitated by using isopropyl alcohol with an average of 291.5 Cp (at 160 rpm), then with methanol at an average of 282 Cp, then precipitated by using ethanol at an average of 206.5 Cp. Gel strength is the lowest obtained 67.74 on precipitated by using ethanol, then an average of 74.34 in precipitated that using methanol, and the highest average of 80.11 in precipitated that using isopropyl alcohol.

Keywords: extraction of carrageenan, gel strength, ohmic technology, precipitated, seaweed (Eucheuma spinosum), viscosity

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4909 Algorithm for Information Retrieval Optimization

Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

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When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: information retrieval, document relevance, performance measures, personalization

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4908 Nonconventional Method for Separation of Rosmarinic Acid: Synergic Extraction

Authors: Lenuta Kloetzer, Alexandra C. Blaga, Dan Cascaval, Alexandra Tucaliuc, Anca I. Galaction

Abstract:

Rosmarinic acid, an ester of caffeic acid and 3-(3,4-dihydroxyphenyl) lactic acid, is considered a valuable compound for the pharmaceutical and cosmetic industries due to its antimicrobial, antioxidant, antiviral, anti-allergic, and anti-inflammatory effects. It can be obtained by extraction from vegetable or animal materials, by chemical synthesis and biosynthesis. Indifferent of the method used for rosmarinic acid production, the separation and purification process implies high amount of raw materials and laborious stages leading to high cost for and limitations of the separation technology. This study focused on separation of rosmarinic acid by synergic reactive extraction with a mixture of two extractants, one acidic (acid di-(2ethylhexyl) phosphoric acid, D2EHPA) and one with basic character (Amberlite LA-2). The studies were performed in experimental equipment consisting of an extraction column where the phases’ mixing was made by mean of a perforated disk with 45 mm diameter and 20% free section, maintained at the initial contact interface between the aqueous and organic phases. The vibrations had a frequency of 50 s⁻¹ and 5 mm amplitude. The extraction was carried out in two solvents with different dielectric constants (n-heptane and dichloromethane) in which the extractants mixture of varying concentration was dissolved. The pH-value of initial aqueous solution was varied between 1 and 7. The efficiency of the studied extraction systems was quantified by distribution and synergic coefficients. For calculating these parameters, the rosmarinic acid concentration in the initial aqueous solution and in the raffinate have been measured by HPLC. The influences of extractants concentrations and solvent polarity on the efficiency of rosmarinic acid separation by synergic extraction with a mixture of Amberlite LA-2 and D2EHPA have been analyzed. In the reactive extraction system with a constant concentration of Amberlite LA-2 in the organic phase, the increase of D2EHPA concentration leads to decrease of the synergic coefficient. This is because the increase of D2EHPA concentration prevents the formation of amine adducts and, consequently, affects the hydrophobicity of the interfacial complex with rosmarinic acid. For these reasons, the diminution of synergic coefficient is more important for dichloromethane. By maintaining a constant value of D2EHPA concentration and increasing the concentration of Amberlite LA-2, the synergic coefficient could become higher than 1, its highest values being reached for n-heptane. Depending on the solvent polarity and D2EHPA amount in the solvent phase, the synergic effect is observed for Amberlite LA-2 concentrations over 20 g/l dissolved in n-heptane. Thus, by increasing the concentration of D2EHPA from 5 to 40 g/l, the minimum concentration value of Amberlite LA-2 corresponding to synergism increases from 20 to 40 g/l for the solvent with lower polarity, namely, n-heptane, while there is no synergic effect recorded for dichloromethane. By analysing the influences of the main factors (organic phase polarity, extractant concentration in the mixture) on the efficiency of synergic extraction of rosmarinic acid, the most important synergic effect was found to correspond to the extractants mixture containing 5 g/l D2EHPA and 40 g/l Amberlite LA-2 dissolved in n-heptane.

Keywords: Amberlite LA-2, di(2-ethylhexyl) phosphoric acid, rosmarinic acid, synergic effect

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4907 Extraction, Recovery and Bioactivities of Chlorogenic Acid from Unripe Green Coffee Cherry Waste of Coffee Processing Industry

Authors: Akkasit Jongjareonrak, Supansa Namchaiya

Abstract:

Unripe green coffee cherry (UGCC) accounting about 5 % of total raw material weight receiving to the coffee bean production process and is, in general, sorting out and dump as waste. The UGCC is known to rich in phenolic compounds such as caffeoylquinic acids, feruloylquinic acids, chlorogenic acid (CGA), etc. CGA is one of the potent bioactive compounds using in the nutraceutical and functional food industry. Therefore, this study aimed at optimization the extraction condition of CGA from UGCC using Accelerated Solvent Extractor (ASE). The ethanol/water mixture at various ethanol concentrations (50, 60 and 70 % (v/v)) was used as an extraction solvent at elevated pressure (10.34 MPa) and temperatures (90, 120 and 150 °C). The recovery yield of UGCC crude extract, total phenolic content, CGA content and some bioactivities of UGCC extract were investigated. Using of ASE at lower temperature with higher ethanol concentration provided higher CGA content in the UGCC crude extract. The maximum CGA content was observed at the ethanol concentration of 70% ethanol and 90 °C. The further purification of UGCC crude extract gave a higher purity of CGA with a purified CGA yield of 4.28 % (w/w, of dried UGCC sample) containing 72.52 % CGA equivalent. The antioxidant activity and antimicrobial activity of purified CGA extract were determined. The purified CGA exhibited the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity at 0.88 mg Trolox equivalent/mg purified CGA sample. The antibacterial activity against Escherichia coli was observed with the minimum inhibitory concentration (MIC) at 3.12 mg/ml and minimum bactericidal concentration (MBC) at 12.5 mg/ml. These results suggested that using of high concentration of ethanol and low temperature under elevated pressure of ASE condition could accelerate the extraction of CGA from UGCC. The purified CGA extract could be a promising alternative source of bioactive compound using for nutraceutical and functional food industry.

Keywords: bioactive, chlorogenic acid, coffee, extraction

Procedia PDF Downloads 241
4906 Tetrad field and torsion vectors in Schwarzschild solution

Authors: M.A.Bakry1, *, Aryn T. Shafeek1, +

Abstract:

In this article, absolute Parallelism geometry is used to study the torsional gravitational field. And discovered the tetrad fields, torsion vector, and torsion scalar of Schwarzschild space. The new solution of the torsional gravitational field is a generalization of Schwarzschild in the context of general relativity. The results are applied to the planetary orbits.

Keywords: absolute parallelism geometry, tetrad fields, torsion vectors, torsion scalar

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4905 Modelling Asymmetric Magnetic Recording Heads with an Underlayer Using Superposition

Authors: Ammar Edress Mohamed, Mustafa Aziz, David Wright

Abstract:

This paper analyses and calculates the head fields of asymmetrical 2D magnetic recording heads when the soft-underlayer is present using the appropriate Green's function to derive the surface potential/field by utilising the surface potential for asymmetrical head without underlayer. The results follow closely the corners, while the gap region shows a linear behaviour for d/g < 0.5 compared with the calculated fields from finite-element.

Keywords: magnetic recording, finite elements, asymmetrical magnetic heads, superposition, Laplace's equation

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4904 Biofilm Text Classifiers Developed Using Natural Language Processing and Unsupervised Learning Approach

Authors: Kanika Gupta, Ashok Kumar

Abstract:

Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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4903 Literary Works as Historical Documents: A New Historicist Reflection on Ahmadou Kourouma's Texts

Authors: Busari Lasisi

Abstract:

Literary works are often devalued to mere fictions and are left with no essence and contributions to history. The sub-structured rational delineating literary works from history is anchored on the aesthetic and flowery expressions that are therein embedded for artistic enrichment. This does not distance a literary work (from whichever genres it is drawn) reflecting the socio-economic, cultural and political cum religious perspectives of a given people and society. This is the very reason justifying the veracity that a writer does not anchor his writing outside of his society. He writes mirroring (his or a given society’s) events, places and duration of consciousness thereby making history evident. In the light of this reality, literary works are not just seen as fictions, imaginative and unrealistic pieces; for they are never unconnected to history. Thus, making authors of literary works historians and their works engrafted useful historical documents. Using the works of Ahmadou Korouma, a renown Ivorian writer, the praxis of this paper therefore in New Historicism approach postulates that literary works are underlying unexplored historic materials, and literature a jumelle to history.

Keywords: literature, history, New Historicism, authors

Procedia PDF Downloads 271