Search results for: end-user trained information extraction

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

Procedia PDF Downloads 74

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

Procedia PDF Downloads 156

Authors: Yash Jain

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The US Center for Disease Control has recommended wearing masks to slow the spread of the virus. The research uses a video feed from a camera to conduct real-time classifications of whether or not a human is correctly wearing a mask, incorrectly wearing a mask, or not wearing a mask at all. Utilizing two distinct datasets from the open-source website Kaggle, a mask detection network had been trained. The first dataset that was used to train the model was titled 'Face Mask Detection' on Kaggle, where the dataset was retrieved from and the second dataset was titled 'Face Mask Dataset, which provided the data in a (YOLO Format)' so that the TinyYoloV3 model could be trained. Based on the data from Kaggle, two machine learning models were implemented and trained: a Tiny YoloV3 Real-time model and a two-stage neural network classifier. The two-stage neural network classifier had a first step of identifying distinct faces within the image, and the second step was a classifier to detect the state of the mask on the face and whether it was worn correctly, incorrectly, or no mask at all. The TinyYoloV3 was used for the live feed as well as for a comparison standpoint against the previous two-stage classifier and was trained using the darknet neural network framework. The two-stage classifier attained a mean average precision (MAP) of 80%, while the model trained using TinyYoloV3 real-time detection had a mean average precision (MAP) of 59%. Overall, both models were able to correctly classify stages/scenarios of no mask, mask, and incorrectly worn masks.

Keywords: datasets, classifier, mask-detection, real-time, TinyYoloV3, two-stage neural network classifier

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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: Han Xue, Zhang Lanyue

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In order to seek more effective feature extraction technology, feature extraction method based on MFCC combined with vector hydrophone is exposed in the paper. The sound pressure signal and particle velocity signal of two kinds of ships are extracted by using MFCC and its evolution form, and the extracted features are fused by using fisher-ratio and correlated distance criterion. The features are then identified by BP neural network. The results showed that MFCC, First-Order Differential MFCC and Second-Order Differential MFCC features can be used as effective features for recognition of underwater targets, and the fusion feature can improve the recognition rate. Moreover, the results also showed that the recognition rate of the particle velocity signal is higher than that of the sound pressure signal, and it reflects the superiority of vector signal processing.

Keywords: vector information, MFCC, differential MFCC, fusion feature, BP neural network

Procedia PDF Downloads 527

Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

Procedia PDF Downloads 259

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

Procedia PDF Downloads 270

Authors: Harunori Kawabe, Hideyuki Aoshima, Koji Murakami, Minoru Kawakami, Yuka Nakano, David D. Ordinario, C. W. Crawford, Iri Sato-Baran

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With the recent advances in gene editing technologies allowing the rewriting of genetic sequences, additional market growth in the global floriculture market beyond previous trends is anticipated through increasingly sophisticated plant breeding techniques. As a prerequisite for gene editing, the gene sequence of the target plant must first be identified. This necessitates the genetic analysis of plants with unknown gene sequences, the extraction of RNA, and comprehensive expression analysis. Consequently, a technology capable of consistently and effectively extracting high-purity DNA and RNA from plants is of paramount importance. Although model plants, such as Arabidopsis and tobacco, have established methods for DNA and RNA extraction, floricultural species such as roses present unique challenges. Different techniques to extract DNA and RNA from various floricultural species were investigated. Upon sampling and grinding the petals of several floricultural species, it was observed that nucleic acid extraction from the ground petal solutions of low viscosity was straightforward; solutions of high viscosity presented a significant challenge. It is postulated that the presence of substantial quantities of polysaccharides and polyphenols in the plant tissue was responsible for the inhibition of nucleic acid extraction. Consequently, attempts were made to extract high-purity DNA and RNA by improving the CTAB method and combining it with commercially available nucleic acid extraction kits. The quality of the total extracted DNA and RNA was evaluated using standard methods. Finally, the effectiveness of the extraction method was assessed by determining whether it was possible to create a library that could be applied as a suitable template for a next-generation sequencer. In conclusion, a method was developed for consistent and accurate nucleic acid extraction from high-viscosity floricultural samples. These results demonstrate improved techniques for DNA and RNA extraction from flowers, help facilitate gene editing of floricultural species and expand the boundaries of research and commercial opportunities.

Keywords: floriculture, gene editing, next-generation sequencing, nucleic acid extraction

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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: Juzhong Tan, William Kerr

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Roasting is one critical procedure in chocolate processing, where special favors are developed, moisture content is decreased, and better processing properties are developed. Therefore, determination of roasting degree of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products, and it also decides the commercial value of cocoa beans collected from cocoa farmers. The roasting degree of cocoa beans currently relies on human specialists, who sometimes are biased, and chemical analysis, which take long time and are inaccessible to many manufacturers and farmers. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was used to detecting the gas generated by cocoa beans with a different roasting degree (0min, 20min, 30min, and 40min) and the signals collected by gas sensors were used to train a three-layers ANN. Chemical analysis of the graded beans was operated by traditional GC-MS system and the contents of volatile chemical compounds were used to train another ANN as a reference to electronic nosed signals trained ANN. Both trained ANN were used to predict cocoa beans with a different roasting degree for validation. The best accuracy of grading achieved by electronic nose signals trained ANN (using signals from TGS 813 826 820 880 830 2620 2602 2610) turned out to be 96.7%, however, the GC trained ANN got the accuracy of 83.8%.

Keywords: artificial neutron network, cocoa bean, electronic nose, roasting

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Authors: Yu Hung Chiang, Hei Chia Wang

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In the academic area, it is important for research to find proper research domain. Many researchers may refer to conference issues to find their interesting or new topics. Furthermore, conferences issues can help researchers realize current research trends in their field and learn about cutting-edge developments in their specialty. However, online published conference information may widely be distributed; it is not easy to be concluded. Many researchers use search engine of journals or conference issues to filter information in order to get what they want. However, this search engine has its limitation. There will still be some issues should be considered; i.e. researchers cannot find the associated topics which may be useful information for them. Hence, use Knowledge Management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted; but most existed ontology construction methods do not consider social information between target users. To effective in academic KM, this study proposes a method of constructing research Topic Maps using Open Directory Project (ODP) and Social Information Processing (SIP). Through catching of social information in conference website: i.e. the information of co-authorship or collaborator, research topics can be associated among related researchers. Finally, the experiments show Topic Maps successfully help researchers to find the information they need more easily and quickly as well as construct associations between research topics.

Keywords: knowledge management, topic map, social information processing, ontology extraction

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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: Saleem Abuleil, Khalid S. Alsamara

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

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

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Jaouadi Ikram, Machhout Mohsen

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The development of a quantum key distribution (QKD) system on a field-programmable gate array (FPGA) platform is the subject of this paper. A quantum cryptographic protocol is designed based on the properties of quantum information and the characteristics of FPGAs. The proposed protocol performs key extraction, reconciliation, error correction, and privacy amplification tasks to generate a perfectly secret final key. We modeled the presence of the spy in our system with a strategy to reveal some of the exchanged information without being noticed. Using an FPGA card with a 100 MHz clock frequency, we have demonstrated the evolution of the error rate as well as the amounts of mutual information (between the two interlocutors and that of the spy) passing from one step to another in the key generation process.

Keywords: QKD, BB84, protocol, cryptography, FPGA, key, security, communication

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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: Lae-Jeong Park, Kyusoo Chung, Jungho Moon

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This paper introduces an effective method of segmenting Korean text (place names in Korean) from a Korean road sign image. A Korean advanced directional road sign is composed of several types of visual information such as arrows, place names in Korean and English, and route numbers. Automatic classification of the visual information and extraction of Korean place names from the road sign images make it possible to avoid a lot of manual inputs to a database system for management of road signs nationwide. We propose a series of problem-specific heuristics that correctly segments Korean place names, which is the most crucial information, from the other information by leaving out non-text information effectively. The experimental results with a dataset of 368 road sign images show 96% of the detection rate per Korean place name and 84% per road sign image.

Keywords: segmentation, road signs, characters, classification

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Authors: Jiawen Wang, Qijun Chen

Abstract:

The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

Abstract:

The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

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

Abstract:

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

Abstract:

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

Abstract:

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

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Authors: Zeineb Ben Azzouz, Wahiba Ben Abdessalem Karaa

Abstract:

The automated extraction of UML class diagram from natural language requirements is a highly challenging task. Many approaches, frameworks and tools have been presented in this field. Nonetheless, the experiments of these tools have shown that there is no approach that can work best all the time. In this context, we propose a new accurate approach to facilitate the automatic mapping from textual requirements to UML class diagram. Our new approach integrates the best properties of statistical Natural Language Processing (NLP) techniques to reduce ambiguity when analysing natural language requirements text. In addition, our approach follows the best practices defined by conceptual modelling experts to determine some patterns indispensable for the extraction of basic elements and concepts of the class diagram. Once the relevant information of class diagram is captured, a XMI document is generated and imported with a CASE tool to build the corresponding UML class diagram.

Keywords: class diagram, user’s requirements, XMI, software engineering

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Authors: M. Bouhoun Ali, A. Y. Badjah Hadj Ahmed, M. Attou, A. Elias, M. A. Didi

Abstract:

The extraction of uranium(VI) from aqueous solutions has been investigated using 1-hydroxyhexadecylidene-1,1-diphosphonic acid (HHDPA) and 1-hydroxydodecylidene-1,1-diphosphonic acid (HDDPA), which were synthesized and characterized by elemental analysis and by FT-IR, 1H NMR, 31P NMR spectroscopy. In this paper, we propose a tentative assignment for the shifts of those two ligands and their specific complexes with uranium(VI). We carried out the extraction of uranium(VI) by HHDPA and HDDPA from [carbon tetrachloride + 2-octanol (v/v: 90%/10%)] solutions. Various factors such as contact time, pH, organic/aqueous phase ratio and extractant concentration were considered. The optimum conditions obtained were: contact time= 20 min, organic/aqueous phase ratio = 1, pH value = 3.0 and extractant concentration = 0.3M. The extraction yields are more significant in the case of the HHDPA which is equipped with a hydrocarbon chain, longer than that of the HDDPA. Logarithmic plots of the uranium(VI) distribution ratio vs. pHeq and the extractant concentration showed that the ratio of extractant to extracted uranium(VI) (ligand/metal) is 2:1. The formula of the complex of uranium(VI) with the HHDPA and the DHDPA is UO2(H3L)2 (HHDPA and DHDPA are denoted as H4L). A spectroscopic analysis has showed that coordination of uranium(VI) takes place via oxygen atoms.

Keywords: liquid-liquid extraction, uranium(vi), 1-hydroxyalkylidene-1, 1-diphosphonic acids, hhdpa, hddpa, aqueous solution

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

Procedia PDF Downloads 197