Search results for: contextual meaning extraction

Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Henri El Zakhem, Christina Romanos, Charlie Bakhos, Hassan Chahal, Jessica Koura

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Squalene is a valuable component of the oil composed of 30 carbon atoms and is mainly used for cosmetic materials. The main concern of this article is to study the Squalene composition in the Lebanese olive oil and to compare it with foreign oil results. To our knowledge, extraction of Squalene from the Lebanese olive oil has not been conducted before. Three different techniques were studied and experiments were performed on three brands of olive oil, Al Wadi Al Akhdar, Virgo Bio and Boulos. The techniques performed are the Fractional Crystallization, the Soxhlet and the Esterification. By comparing the results, it is found that the Lebanese oil contains squalene and Soxhlet method is the most effective between the three methods extracting about 6.5E-04 grams of Squalene per grams of olive oil.

Keywords: squalene, extraction, crystallization, Soxhlet

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Authors: Kyi Pyar Zaw, Zin Mar Kyu

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Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.

Keywords: chain code frequency, character recognition, feature extraction, features matching, segmentation

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Authors: Girma Yohannis Bade, Olga Kolesnikova, Grigori Sidorov

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Named entity recognition (NER) is a building block for information extraction. Though the information extraction process has been automated using a variety of techniques to find and extract a piece of relevant information from unstructured documents, the discovery of targeted knowledge still poses a number of research difficulties because of the variability and lack of structure in Web data. NER, a subtask of information extraction (IE), came to exist to smooth such difficulty. It deals with finding the proper names (named entities), such as the name of the person, country, location, organization, dates, and event in a document, and categorizing them as predetermined labels, which is an initial step in IE tasks. This survey paper presents the roles and importance of NER to IE from the perspective of different algorithms and application area domains. Thus, this paper well summarizes how researchers implemented NER in particular application areas like finance, medicine, defense, business, food science, archeology, and so on. It also outlines the three types of sequence labeling algorithms for NER such as feature-based, neural network-based, and rule-based. Finally, the state-of-the-art and evaluation metrics of NER were presented.

Keywords: the role of NER, named entity recognition, information extraction, sequence labeling algorithms, named entity application area

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Authors: S. Probine

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The visual arts have been proven to be a central means through which young children can communicate their ideas, reflect on experience, and construct new knowledge. Despite this, perceptions of, and the degree to which the visual arts are valued within education, vary widely within political, educational, community and family contexts. These differing perceptions informed my doctoral research project, which explored the contextual factors that affect how young children come to value and use the visual arts in their lives and learning. The qualitative methodology of narrative inquiry with inclusion of arts-based methods was most appropriate for this inquiry. Using a sociocultural framework, the stories collected were analysed through the sociocultural theories of Lev Vygotsky as well as the work of Urie Bronfenbrenner, together with postmodern theories about identity formation. The use of arts-based methods such as teacher’s reflective art journals and the collection of images by child participants and their parent/caregivers allowed the research participants to have a significant role in the research. Three early childhood settings at which the visual arts were deeply valued as a meaning-making device in children’s learning, were purposively selected to be involved in the research. At each setting, the study found a unique and complex web of influences and interconnections, which shaped how children utilised the visual arts to mediate their thinking. Although the teachers' practices at all three centres were influenced by sociocultural theories, each settings' interpretations of these theories were unique and resulted in innovative interpretations of the role of the teacher in supporting visual arts learning. These practices had a significant impact on children’s experiences of the visual arts. For many of the children involved in this study, visual art was the primary means through which they learned. The children in this study used visual art to represent their experiences, relationships, to explore working theories, their interests (including those related to popular culture), to make sense of their own and other cultures, and to enrich their imaginative play. This research demonstrates that teachers have fundamental roles in fostering and disseminating the importance of the visual arts within their educational communities.

Keywords: arts-based methods, early childhood education, teacher's visual arts pedagogies, visual arts

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Authors: Rabia Bashir, Sajjad Akbar

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There is an inevitable demand of web mining due to rapid increase of huge information on the Internet, but the striking variety of web structures has made required content retrieval a difficult task. To counter this issue, Web Content Mining (WCM) emerges as a potential candidate which extracts and integrates suitable resources of data to users. In past few years, research has been done on several extraction techniques for WCM i.e. agent-based, template-based, assumption-based, statistic-based, wrapper-based and machine learning. However, it is still unclear that either these approaches are efficiently tackling the significant challenges of WCM or not. To answer this question, this paper identifies these challenges such as language independency, structure flexibility, performance, automation, dynamicity, redundancy handling, intelligence, relevant content retrieval, and privacy. Further, mapping of these challenges is done with existing extraction mechanisms which helps to adopt the most suitable WCM approach, given some conditions and characteristics at hand.

Keywords: content mining challenges, web content mining, web content extraction approaches, web information retrieval

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Authors: Steffen Happel

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Non-standard isotopes such as Sc-44/47, Zr-89, and Sn-117mare finding interest is increasing in radiopharmaceutical applications. Methods for the separation of these elements from typical target materials were developed. The methods used in this paper are based on the use of extraction chromatographic resins such as UTEVA, TBP, and DGA resin. Information on the selectivity of the resins (Dw values of selected elements in HCl and HNO3 of varying concentration) will be presented as well as results of the method development such as elution studies, chemical recoveries, and decontamination factors. Developed methods are based on the use of vacuum supported separation allowing for fast and selective separation.

Keywords: elution, extraction chromatography, radiopharmacy, decontamination factors

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Authors: Geeta Gahlawat, Sanjeev Kumar Soni

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An imprudent use of environmentally hazardous petrochemical-based plastics and limited availability of fossil fuels have provoked research interests towards production of biodegradable plastics - polyhydroxyalkanoate (PHAs). However, the industrial application of PHAs based products is primarily restricted by their high cost of recovery and extraction protocols. Moreover, solvents used for the extraction and purification are toxic and volatile which causes adverse environmental hazards. Development of efficient downstream recovery strategies along with utilization of non-toxic solvents will accelerate their commercialization. In this study, various extraction strategies were designed for sustainable and cost-effective recovery of PHAs from Cupriavidus necator using non-toxic environment friendly solvents viz. 1,2-propylene carbonate, ethyl acetate, isoamyl alcohol, butyl acetate. The effect of incubation time i.e. 10, 30 and 50 min and temperature i.e. 60, 80, 100, 120°C was tested to identify the most suitable solvent. PHAs extraction using a recyclable solvent, 1,2 propylene carbonate, showed the highest recovery yield (90%) and purity (93%) at 120°C and 30 min incubation. Ethyl acetate showed the better capacity to recover PHAs from cells than butyl acetate. Extraction with ethyl acetate exhibited high recovery yield and purity of 96% and 92%, respectively at 100°C. Effect of non-toxic surfactant such as linear alkylbenzene sulfonic acid (LAS) was also studied at 40, 60 and 80°C, and detergent pH range of 3.0, 5.0, 7.0 and 9.0 for the extraction of PHAs from the cells. LAS gave highest yield of 86% and purity of 88% at temperature 80°C and 5.0 pH.

Keywords: polyhydroxyalkanoates, Cupriavidus necator, extraction, recovery yield

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Authors: Akinfiresoye W. A., Olarewaju O. O., Okunola, Okunola I. O.

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An indigenous honey-extracting machine was designed, fabricated and evaluated at the workshop of the department of Agricultural Technology, Federal Polytechnic, Ile-Oluji, Nigeria using locally available materials. It has the extraction unit, the presser, the honey collector and the frame. The harvested honeycomb is placed inside the cylindrical extraction unit with perforated holes. The press plate was then placed on the comb while the hydraulic press of 3 tons was placed on it, supported by the frame. The hydraulic press, which is manually operated, forces the oil out of the extraction chamber through the perforated holes into the honey collector positioned at the lowest part of the extraction chamber. The honey-extracting machine has an average throughput of 2.59 kg/min and an efficiency of about 91%. The cost of producing the honey extracting machine is NGN 31, 700: 00, thirty-one thousand and seven hundred nairas only or $70 at NGN 452.8 to a dollar. This cost is affordable to beekeepers and would-be honey entrepreneurs. The honey-extracting machine is easy to operate and maintain without any complex technical know-how.

Keywords: honey, extractor, cost, efficiency

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Authors: Siti Rafeah Md Rafei, Karen Wang Yanping, Park Mi Kyoung

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Tissue samples are precious supply for molecular studies or disease identification diagnosed using molecular assays, namely real-time PCR (qPCR). It is critical to establish the most favorable nucleic acid extraction that gives the PCR-amplifiable genomic DNA. Furthermore, automated nucleic acid extraction is an appealing alternative to labor-intensive manual methods. Operational complexity, defined as the number of steps required to obtain an extracted sample, is one of the criteria in the comparison. Here we are comparing the One BioMed’s automated X8 platform with the commercially available manual-operated kits from QIAGEN Mini Kit and Roche. We extracted DNA from rat fresh-frozen tissue (from different type of organs) in the matrices. After tissue pre-treatment, it is added to the One BioMed’s X8 pre-filled cartridge, and the QIAGEN QIAmp column respectively. We found that the results after subjecting the eluates to the Real Time PCR using BIORAD CFX are comparable.

Keywords: DNA extraction, frozen tissue, PCR, qPCR, rat

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Authors: R. Kandiah, K. Miyamoto

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In Sri Lanka, the Jaffna area is a high drought affected area and depends mainly on groundwater aquifers for water needs. Water for daily activities is extracted from wells. As households manually extract water from the wells, it is not drawn from mid evening to early morning. The water inflow at night provides the maximum water level that decreases during the daytime due to extraction. The storage volume of water in wells is limited or at its lowest level during the dry season. This study analyzes the domestic water budget during the dry season in the Jaffna area. In order to evaluate the water inflow rate into wells, storage volume and extraction volume from wells over time, water pressure is measured at the bottom of three wells, which are located in coastal area denoted as well A, in nonspecific area denoted as well B, and agricultural area denoted as well C. The water quality at the wells A, B, and C, are mostly fresh, modest fresh, and saline respectively. From the monitoring, we can find that the daily inflow amount of water into the wells and daily water extraction depend on each other, that is, higher extraction yields higher inflow. And, in the dry season, the daily inflow volume and the daily extraction volume of each well are almost in balance.

Keywords: accessible volume, consumption volume, inflow rate, water budget

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Asad Abbas, Muhammad Fezan Afzal, Muhammad Latif Anjum, Muhammad Azmat

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The Internet of Things (IoT) is used to link up real objects that use the internet to interact. IoT applications allow handling and operating the equipment in accordance with environmental needs, such as transportation and healthcare. IoT devices are linked together via a number of agents that act as a middleman for communications. The operation of a heat sensor differs indoors and outside because agent applications work with environmental variables. In this article, we suggest using Software Product Line (SPL) to model IoT agents and applications' features on an XML-based basis. The contextual diversity within the same domain of application can be handled, and the reusability of features is increased by XML-based feature modelling. For the purpose of managing contextual variability, we have embraced XML for modelling IoT applications, agents, and internet-connected devices.

Keywords: IoT agents, IoT applications, software product line, feature model, XML

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Authors: Sophia Cyril Vincent

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Background: As per the Indian Census 2011, there is nearly 104 million elderly population aged above 60 years (53 million females and 51 males), and the count is expected to be 173 million by the end of 2026. Nearly 5.5% of women and 1.5% of men are living alone.1 In India, even though it is the moral duty of the children to take care of aged parents, many elders are landing in old age homes due to the social transformation factors like mushrooming of nuclear families, migration of children, cultural echoes, differences in mindset and values. Nearly 728 old age homes are seen across the country, out of which 78 old age homes with approximately 3000 inmates are seen only in Bangalore2. The existing literature shows that elderly women residing in old age homes experience the challenges like- loneliness, health issues, rejection from children, grief, death anxiety, etc, which leads to mental and physical wellbeing in numerous and tangible ways3. Hence the best and cost-effective way to improve the meaning and quality of life among elderly females is logotherapy, a type of psychotherapeutic analysis and treatment, motivating and driving force4 within the human experience to lead a decent life. Aim: The current research is aimed at studying the effectiveness of a logotherapy intervention on meaning and quality of life among elderly women of old age homes. Samples:200 women aged < 60 years and staying in the old age home for more than 1 year were randomly allocated to the control group and experimental group. Methodology: Using the Meaning in life questionnaire (MLQ)and the World health organization quality of life (WHOQOL) questionnaire, meaning and quality of life were assessed among both groups' women. Intensive Logotherapy and meaning in life program for five days were provided for the experimental group and the control group, with no treatment. Result: Under analysis. Conclusion: It is the right of the elderly woman to lead a happy and peaceful life till her death irrespective of the residing place. Hence, continuous monitoring and effective management are necessary for elderly women.

Keywords: quality of life, meaning of life, logo therapy, old age home

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Authors: Gordana Ćetković, Sanja Podunavac-Kuzmanović, Jasna Čanadanović-Brunet, Vesna Tumbas Šaponjac, Vanja Šeregelj, Jelena Vulić, Slađana Stajčić

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The color of food is one of the decisive factors for consumers. Potential toxicity of artificial food colorants has led to the consumers' preference for natural products over products with artificial colors. Natural pigments have many bioactive functions, such as antioxidant, provitamin and many other. Having this in mind, the acceptability of natural colorants by the consumers is much higher. Being present in all photosynthetic plant tissues carotenoids are probably most widespread pigments in nature. Carrot (Daucus carota) is a good source of functional food components. Carrot is especially rich in carotenoids, mainly α- and β-carotene and lutein. For this study, carrot was extracted using classical extraction with hexane and ethyl acetate, as well as supercritical CO₂ extraction. The extraction efficiency was evaluated by estimation of carotenoid yield determined spectrophotometrically. Classical extraction using hexane (18.27 mg β-carotene/100 g DM) was the most efficient method for isolation of carotenoids, compared to ethyl acetate classical extraction (15.73 mg β-carotene/100 g DM) and supercritical CO₂ extraction (0.19 mg β-carotene/100 g DM). Three carrot extracts were tested in terms of antioxidant activity using DPPH and reducing power assay as well. Surprisingly, ethyl acetate extract had the best antioxidant activity on DPPH radicals (AADPPH=120.07 μmol TE/100 g) while hexane extract showed the best reducing power (RP=1494.97 μmol TE/100 g). Hexane extract was chosen as the most potent source of carotenoids and was encapsulated in whey protein by freeze-drying. Carotenoid encapsulation efficiency was found to be high (89.33%). Based on our results it can be concluded that carotenoids from carrot can be efficiently extracted using hexane and classical extraction method. This extract has the potential to be applied in encapsulated form due to high encapsulation efficiency and coloring capacity. Therefore it can be used for dietary supplements development and food fortification.

Keywords: carotenoids, carrot, extraction, encapsulation

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Authors: Sarai Alvarado Pineda, Ricardo Maldonado Soto

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The acquisition of Verb Particle Constructions is a challenge for Spanish speakers learning English. The acquisition is particularly difficult for speakers of languages with no verb particle constructions. The purpose of the current study is to define the procedural steps in the acquisition of constructions with the particle on. There are three outstanding meanings for the particle on; Surface: The movie is based on a true story, Activation: John turn on the light, Continuity: The band played on all night. The central aim of this study is to measure how Mexican Spanish participants respond to both the three meanings mentioned above and the degree of meaning transparency/opacity of on verb particle constructions. Forty Mexican Spanish learners of English (20 basic and 20 advanced) are compared against a control group of 20 American native English speakers through a reaction time test (PsychoPy2 2015). The participants were asked to discriminate 90 items based on their knowledge of these constructions. There are 30 items per meaning divided into two groups of transparent and opaque meaning. Results revealed three major findings: Advanced students have a reaction time similar to that of native speakers (advanced 4.5s versus native 3.7s), while students with a lower level of English proficiency, show a high reaction time (7s). Likewise, there is a shorter reaction time in constructions with lower opacity in the three groups of participants, with differences between each level (basic 6.7s, advanced 4.3s, and native 3.4s). Finally, a difference in reaction time can be identified according to the meaning provided by the construction. The reaction time for the activation category (5.27s) is greater than continuity (5.04s), and this category is also slower than the surface (4.94s). The study shows that the level of sensitivity of English learners increases significantly aiming towards native speaker patterns as determined by the level of transparency of meaning of each construction as well as the degree of entrenchment of each constructional meaning.

Keywords: meaning of the particle, opacity, reaction time, verb particle constructions

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Authors: Lamzira Ebralidze, Aleksandre Tsertsvadze, Dali Berashvili, Aliosha Bakuridze

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Nowadays, there is an increasing demand for biologically active substances from vegetable, animal, and mineral resources. In terms of the use of natural compounds, pharmaceutical, cosmetic, and nutrition industry has big interest. The biggest drawback of conventional extraction methods is the need to use a large volume of organic extragents. The removal of the organic solvent is a multi-stage process. And their absolute removal cannot be achieved, and they still appear in the final product as impurities. A large amount of waste containing organic solvent damages not only human health but also has the harmful effects of the environment. Accordingly, researchers are focused on improving the extraction methods, which aims to minimize the use of organic solvents and energy sources, using alternate solvents and renewable raw materials. In this context, green extraction principles were formed. Green Extraction is a need of today’s environment. Green Extraction is the concept, and it totally corresponds to the challenges of the 21st century. The extraction of biologically active compounds based on green extraction principles is vital from the view of preservation and maintaining biodiversity. Novel technologies of green extraction are known, such as "cold methods" because during the extraction process, the temperature is relatively lower, and it doesn’t have a negative impact on the stability of plant compounds. Novel technologies provide great opportunities to reduce or replace the use of organic toxic solvents, the efficiency of the process, enhance excretion yield, and improve the quality of the final product. The objective of the research is the development of green technologies of flavonoids containing preparations. Methodology: At the first stage of the research, flavonoids containing preparations (Tincture Herba Leonuri, flamine, rutine) were prepared based on conventional extraction methods: maceration, bismaceration, percolation, repercolation. At the same time, the same preparations were prepared based on green technologies, microwave-assisted, UV extraction methods. Product quality characteristics were evaluated by pharmacopeia methods. At the next stage of the research technological - economic characteristics and cost efficiency of products prepared based on conventional and novel technologies were determined. For the extraction of flavonoids, water is used as extragent. Surface-active substances are used as co-solvent in order to reduce surface tension, which significantly increases the solubility of polyphenols in water. Different concentrations of water-glycerol mixture, cyclodextrin, ionic solvent were used for the extraction process. In vitro antioxidant activity will be studied by the spectrophotometric method, using DPPH (2,2-diphenyl-1- picrylhydrazyl) as an antioxidant assay. The advantage of green extraction methods is also the possibility of obtaining higher yield in case of low temperature, limitation extraction process of undesirable compounds. That is especially important for the extraction of thermosensitive compounds and maintaining their stability.

Keywords: extraction, green technologies, natural resources, flavonoids

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Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

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Authors: Kyohei Yoshino, Masahiko Matsumiya, Yuji Sasaki

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Recently, studies have been conducted on Au(III) extraction using ionic liquids (ILs) as extractants or diluents. ILs such as piperidinium, pyrrolidinium, and pyridinium have been studied as extractants for noble metal extractions. Furthermore, the polarity, hydrophobicity, and solvent miscibility of these ILs can be adjusted depending on their intended use. Therefore, the unique properties of ILs make them functional extraction media. The extraction mechanism of Au(III) using phosphonium-based ILs and relevant thermodynamic studies are yet to be reported. In the present work, we focused on the mechanism of Au(III) extraction and related thermodynamic analyses using phosphonium-based ILs. Triethyl-n-pentyl, triethyl-n-octyl, and triethyl-n-dodecyl phosphonium bis(trifluoromethyl-sulfonyl)amide, [P₂₂₂ₓ][NTf₂], (X = 5, 8, and 12) were investigated for Au(III) extraction. The IL–Au complex was identified as [P₂₂₂₅][AuCl₄] using UV–Vis–NIR and Raman spectroscopic analyses. The extraction behavior of Au(III) was investigated with a change in the [P₂₂₂ₓ][NTf₂]IL concentration from 1.0 × 10–4 to 1.0 × 10–1 mol dm−3. The results indicate that Au(III) can be easily extracted by the anion-exchange reaction in the [P₂₂₂ₓ][NTf₂]IL. The slope range 0.96–1.01 on the plot of log D vs log[P₂₂₂ₓ][NTf2]IL indicates the association of one mole of IL with one mole of [AuCl4−] during extraction. Consequently, [P₂₂₂ₓ][NTf₂] is an anion-exchange extractant for the extraction of Au(III) in the form of anions from chloride media. Thus, this type of phosphonium-based IL proceeds via an anion exchange reaction with Au(III). In order to evaluate the thermodynamic parameters on the Au(III) extraction, the equilibrium constant (logKₑₓ’) was determined from the temperature dependence. The plot of the natural logarithm of Kₑₓ’ vs the inverse of the absolute temperature (T–1) yields a slope proportional to the enthalpy (ΔH). By plotting T–1 vs lnKₑₓ’, a line with a slope range 1.129–1.421 was obtained. Thus, the result indicated that the extraction reaction of Au(III) using the [P₂₂₂ₓ][NTf₂]IL (X=5, 8, and 12) was exothermic (ΔH=-9.39〜-11.81 kJ mol-1). The negative value of TΔS (-4.20〜-5.27 kJ mol-1) indicates that microscopic randomness is preferred in the [P₂₂₂₅][NTf₂]IL extraction system over [P₂₂₂₁₂][NTf₂]IL. The total negative alternation in Gibbs energy (-5.19〜-6.55 kJ mol-1) for the extraction reaction would thus be relatively influenced by the TΔS value on the number of carbon atoms in the alkyl side length, even if the efficiency of ΔH is significantly influenced by the total negative alternations in Gibbs energy. Electrochemical analysis revealed that extracted Au(III) can be reduced in two steps: (i) Au(III)/Au(I) and (ii) Au(I)/Au(0). The diffusion coefficients of the extracted Au(III) species in [P₂₂₂ₓ][NTf₂] (X = 5, 8, and 12) were evaluated from 323 to 373 K using semi-integral and semi-differential analyses. Because of the viscosity of the IL medium, the diffusion coefficient of the extracted Au(III) increases with increasing alkyl chain length. The 4f7/2 spectrum based on X-ray photoelectron spectroscopy revealed that the Au electrodeposits obtained after 10 cycles of continuous extraction and electrodeposition were in the metallic state.

Keywords: au(III), electrodeposition, phosphonium-based ionic liquids, solvent extraction

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Authors: Samina Khalid, Shamila Nasreen

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Dimensionality reduction as a preprocessing step to machine learning is effective in removing irrelevant and redundant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection and feature extraction methods with respect to efficiency and effectiveness. In the field of machine learning and pattern recognition, dimensionality reduction is important area, where many approaches have been proposed. In this paper, some widely used feature selection and feature extraction techniques have analyzed with the purpose of how effectively these techniques can be used to achieve high performance of learning algorithms that ultimately improves predictive accuracy of classifier. An endeavor to analyze dimensionality reduction techniques briefly with the purpose to investigate strengths and weaknesses of some widely used dimensionality reduction methods is presented.

Keywords: age related macular degeneration, feature selection feature subset selection feature extraction/transformation, FSA’s, relief, correlation based method, PCA, ICA

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Authors: J. Švarc-Gajić, A. Cvetanović

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Apigenin is a flavone synthetized by many plants and quite abundant in chamomile (Matricaria recutita) in its free form and in the form of its glucoside and different acylated forms. Many beneficial health effects have been attributed to apigenin, such as chemo-preventive, anxiolytic, anti-inflammatory, antioxidant and antispasmodic. It is reported that free apigenin is much more bioactive in comparison to its bound forms. Subcritical water offers numerous advantages in comparison to conventional extraction techniques, such as good selectivity, low price and safety. Superheated water exhibits high hydrolytical potential which must be carefully balanced when using this solvent for the extraction of bioactive molecules. Moderate hydrolytical potential can be exploited to liberate apigenin from its bound forms, thus increasing biological potential of obtained extracts. The polarity of pressurized water and its hydrolytical potential are highly dependent on the temperature. In this research chamomile ligulate flowers were extracted by pressurized hot water in home-made subcritical water extractor in conditions of convective mass transfer. The influence of the extraction temperature was investigated at 30 bars. Extraction yields of total phenols, total flavonoids and apigenin depending on the operational temperature were calculated based on spectrometric assays. Optimal extraction temperature for maximum yields of total phenols and flavonoids showed to be 160°C, whereas apigenin yield was the highest at 120°C.

Keywords: superheated water, temperature, chamomile, apigenin

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Authors: Korban Oosthuizen, Robert C. Luckay

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Due to the growing popularity of electric vehicles and the importance of cobalt as part of the cathode material for lithium-ion batteries, demand for this metal is on the rise. Recycling of the cathode materials by means of solvent extraction is an attractive means of recovering cobalt and easing the pressure on limited natural resources. In this study, a series of straight chain and macrocyclic diamine ligands were developed for the selective recovery of cobalt from the solution containing nickel and manganese by means of solvent extraction. This combination of metals is the major cathode material used in electric vehicle batteries. The ligands can be protonated and function as ion-pairing ligands targeting the anionic [CoCl₄]²⁻, a species which is not observed for Ni or Mn. Selectivity for Co was found to be good at very high chloride concentrations and low pH. Longer chains or larger macrocycles were found to enhance selectivity, and linear chains on the amide side groups also resulted in greater selectivity over the branched groups. The cation of the chloride salt used for adjusting chloride concentrations seems to play a major role in extraction through salting-out effects. The ligands developed in this study show good selectivity for Co over Ni and Mn but require very high chloride concentrations to function. This research does, however, open the door for further investigations into using diamines as solvent extraction ligands for the recovery of cobalt from spent lithium-ion batteries.

Keywords: hydrometallurgy, solvent extraction, cobalt, lithium-ion batteries

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Authors: Fariba Tadayon, Nika Gharahgolooyan, Ateke Tadayon, Mostafa Jafarian

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Carotenoid pigments are a various group of lipophilic compounds that generate the yellow to red colors of many plants, foods and flowers. A well-known type of carotenoids which is pro-vitamin A is β-carotene. Due to the color of citrus fruit’s peel, the peel can be a good source of different carotenoids. Ostrich oil is one of the most valuable foundations in many branches of industry, medicine, cosmetics and nutrition. The animal-based ostrich oil could be considered as an alternative and green solvent. Following this study, wastes of citrus peel will recycle by a simple method and extracted carotenoids can increase properties of ostrich oil. In this work, a simple and efficient method for extraction of carotenoids from tangerine peel was designed. Ultrasound-assisted extraction (UAE) showed significant effect on the extraction rate by increasing the mass transfer rate. Ostrich oil can be used as a green solvent in many studies to eliminate petroleum-based solvents. Since tangerine peel is a complex source of different carotenoids separation and determination was performed by high-performance liquid chromatography (HPLC). In addition, the ability of ostrich oil and sunflower oil in carotenoid extraction from tangerine peel and carrot was compared. The highest yield of β-carotene extracted from tangerine peel using sunflower oil and ostrich oil were 75.741 and 88.110 (mg/L), respectively. Optimization of the process was achieved by response surface methodology (RSM) and the optimal extraction conditions were tangerine peel powder particle size of 0.180 mm, ultrasonic intensity of 19 W/cm2 and sonication time of 30 minutes.

Keywords: β-carotene, carotenoids, citrus peel, ostrich oil, response surface methodology, ultrasound-assisted extraction

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Authors: I. A. Ibrahim, T. A. Elbarbary, N. Abdelaty, A. T. Kandil, H. K. Farhan

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The present work aims to study the leaching of Abu Ghalaga ilmenite ore by hydrochloric acid and simultaneous reduction by iron powder method to dissolve its titanium and iron contents. Iron content in the produced liquor is separated by solvent extraction using TBP as a solvent. All parameters affecting the efficiency of the dissolution process were separately studied including the acid concentration, solid/liquid ratio which controls the ilmenite/acid molar ratio, temperature, time and grain size. The optimum conditions at which maximum leaching occur are 30% HCl acid with a solid/liquid ratio of 1/30 at 80 °C for 4 h using ore ground to -350 mesh size. At the same time, all parameters affecting on solvent extraction and stripping of iron content from the produced liquor were studied. Results show that the best extraction is at solvent/solution 1/1 by shaking at 240 RPM for 45 minutes at 30 °C whereas best striping of iron at H₂O/solvent 2/1.

Keywords: ilmenite ore, leaching, titanium solvent extraction, Abu Ghalaga ilmenite ore

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Hung-Sheng Lin, Cheng-Hsuan Li

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Over the past few years, kernel-based algorithms have been widely used to extend some linear feature extraction methods such as principal component analysis (PCA), linear discriminate analysis (LDA), and nonparametric weighted feature extraction (NWFE) to their nonlinear versions, kernel principal component analysis (KPCA), generalized discriminate analysis (GDA), and kernel nonparametric weighted feature extraction (KNWFE), respectively. These nonlinear feature extraction methods can detect nonlinear directions with the largest nonlinear variance or the largest class separability based on the given kernel function. Moreover, they have been applied to improve the target detection or the image classification of hyperspectral images. The double nearest proportion feature extraction (DNP) can effectively reduce the overlap effect and have good performance in hyperspectral image classification. The DNP structure is an extension of the k-nearest neighbor technique. For each sample, there are two corresponding nearest proportions of samples, the self-class nearest proportion and the other-class nearest proportion. The term “nearest proportion” used here consider both the local information and other more global information. With these settings, the effect of the overlap between the sample distributions can be reduced. Usually, the maximum likelihood estimator and the related unbiased estimator are not ideal estimators in high dimensional inference problems, particularly in small data-size situation. Hence, an improved estimator by shrinkage estimation (regularization) is proposed. Based on the DNP structure, LDA is included as a special case. In this paper, the kernel method is applied to extend DNP to kernel-based DNP (KDNP). In addition to the advantages of DNP, KDNP surpasses DNP in the experimental results. According to the experiments on the real hyperspectral image data sets, the classification performance of KDNP is better than that of PCA, LDA, NWFE, and their kernel versions, KPCA, GDA, and KNWFE.

Keywords: feature extraction, kernel method, double nearest proportion feature extraction, kernel double nearest feature extraction

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Authors: Mary Titilayo Olowe

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The controversies that trailed the political campaign and eventual choice of Donald Trump as the American president is so great that expectations are high as to what the content of his inaugural speech will portray. Given the fact that language is a dynamic vehicle of expressing intentions, the speech needs to be objectively assessed so as to access its content in the manner intended through the three strands of meaning postulated by the Systemic Functional Grammar (SFG): the ideational, the interpersonal and the textual. The focus of this paper, however, is on the interpersonal meaning which deals with how language exhibits social roles and relationship. This paper, therefore, attempts to analyse President Donald Trump’s inaugural speech to elicit interpersonal meaning in it. The analysis is done from the perspective of mood and modality which are housed in SFG. Results of the mood choice which is basically declarative, reveal an information-centered speech while the high option for the modal verb operator ‘will’ shows president Donald Trump’s ability to establish an equal and reliant relationship with his audience, i.e., the Americans. In conclusion, the appeal of the speech to different levels of Interpersonal meaning is largely responsible for its overall effectiveness. One can, therefore, understand the reason for the massive reaction it generates at the center of global discourse.

Keywords: interpersonal, modality, mood, systemic functional grammar

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Authors: Amanda Cristina de Oliveira, Elias de Souza Monteiro Filho, Roberta Ceriani

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Liquid-liquid extraction in aqueous two-phase systems (ATPSs) constitutes a powerful tool for purifying bio-materials, such as cells, organelles, proteins, among others. In this work, the extraction of the bovine serum albumin (BSA) has been studied in systems formed by polyethylene glycol (PEG) (1500, 4000, and 6000 g.mol⁻¹) + potassium sodium tartrate + water at 303.15°K. Phase diagrams were obtained by turbidimetry and Merchuk’s method (1998). The experimental tie-lines were described using the Othmer-Tobias and Bancroft correlations. ATPSs were correlated with the nonrandom two-liquid (NRTL) model. The results were considered excellent according to global root-mean-square deviations found which were between 0,72 and 1,13%. The concentrations of the proteins in each phase were determined by spectrophotometry at 280 nm, finding partition efficiencies greater than 71%.

Keywords: aqueous two phases systems, bovine serum albumin , liquid-liquid extraction, polyethylene glycol

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Authors: P. Zakikhani, R. Zahari, M. T. H. Sultan, D. L. Majid

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Natural plant fibres reinforced polymeric composite materials have been used in many fields of our lives to save the environment. Especially, bamboo fibres due to its environmental sustainability, mechanical properties, and recyclability have been utilized as reinforced polymer matrix composite in construction industries. In this review study bamboo structure and three different methods such as mechanical, chemical and combination of mechanical and chemical to extract fibres from bamboo are summarized. Each extraction method has been done base on the application of bamboo. In addition Bamboo fibre is compared with glass fibre from various aspects and in some parts it has advantages over the glass fibre.

Keywords: bamboo fibres, natural fibres, bio composite, mechanical extraction, glass fibres

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Authors: Kahina Bedda, Boudjema Hamada

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Environmental regulations have been introduced in many countries around the world to reduce the sulfur content of diesel fuel to ultra low levels with the intention of lowering diesel engine’s harmful exhaust emissions and improving air quality. Removal of sulfur containing compounds from diesel feedstocks to produce ultra low sulfur diesel fuel by extraction with selective solvents has received increasing attention in recent years. This is because the sulfur extraction technologies compared to the hydrotreating processes could reduce the cost of desulfurization substantially since they do not demand hydrogen, and are carried out at atmospheric pressure. In this work, the desulfurization of distillate gasoil by liquid-liquid extraction with N, N-dimethylformamide was investigated. This fraction was recovered from a mixture of Hassi Messaoud crude oils and Hassi R'Mel gas-condensate in Algiers refinery. The sulfur content of this cut is 281 ppm. Experiments were performed in six-stage with a ratio of solvent:feed equal to 3:1. The effect of the extraction temperature was investigated in the interval 30 ÷ 110°C. At 110°C the yield of refined gas oil was 82% and its sulfur content was 69 ppm.

Keywords: desulfurization, gasoil, N, N-dimethylformamide, sulfur content

Procedia PDF Downloads 352