Search results for: feature extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3137

Search results for: feature extraction

2717 Bayesian Network and Feature Selection for Rank Deficient Inverse Problem

Authors: Kyugneun Lee, Ikjin Lee

Abstract:

Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.

Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis

Procedia PDF Downloads 286
2716 Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes

Authors: Vincent Liu

Abstract:

Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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2715 Protein Isolates from Chickpea (Cicer arietinum L.) and Its Application in Cake

Authors: Mohamed Abdullah Ahmed

Abstract:

In a study of chickpea protein isolate (CPI) preparation, the wet alkaline extraction was carried out. The objectives were to determine the optimal extracting conditions of CPI and apply CPI into a sponge cake recipe to replace egg and make acceptable product. The design used in extraction was a central composite design. The response surface methodology was preferred to graphically express the relationship between extraction time and pH with the output variables of percent yield and protein content of CPI. It was noted that optimal extracting conditions were 60 min and pH 10.5 resulting in 90.07% protein content and 89.15% yield of CPI. The protein isolate (CPI) could be incorporated in cake to 20% without adversely affecting the cake physical properties such as cake hardness and sensory attributes. The higher protein content in cake was corresponding to the amount of CPI added. Therefore, adding CPI can significantly (p<0.05) increase protein content in cake. However, sensory evaluation showed that adding more than 20% of CPI decreased the overall acceptability. The results of this investigation could be used as a basic knowledge of CPI utilization in other food products.

Keywords: chick bean protein isolate, sponge cake, utilization, sponge

Procedia PDF Downloads 340
2714 Feature Extraction Technique for Prediction the Antigenic Variants of the Influenza Virus

Authors: Majid Forghani, Michael Khachay

Abstract:

In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition

Procedia PDF Downloads 131
2713 LuMee: A Centralized Smart Protector for School Children who are Using Online Education

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

Abstract:

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

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

Procedia PDF Downloads 55
2712 The Effect of Supercritical Carbon Dioxide Process Variables on The Recovery of Extracts from Bentong Ginger: Study on Process Variables

Authors: Muhamad Syafiq Hakimi Kamaruddin, Norhidayah Suleiman

Abstract:

Ginger extracts (Zingiber officinale Rosc.) have been attributed therapeutic properties primarily as antioxidant, anticancer, and anti-inflammatory properties. Conventional extractions including Soxhlet and maceration are commonly used to extract the bioactive compounds from plant material. Nevertheless, high energy consumption and being non-environmentally friendly are the predominant limitations of the conventional extractions method. Herein, green technology, namely supercritical carbon dioxide (scCO2) extraction, is used to study process variables' effects on extract yields. Herein, green technology, namely supercritical carbon dioxide (scCO2) extraction, is used to study process variables' effects on extract yields. A pressure (10-30 MPa), temperature (40-60 °C), and median particle size (300-600 µm) were conducted at a CO2 flow rate of 0.9 ± 0.2 g/min for 120 mins. The highest overall yield was 4.58% obtained by the scCO2 extraction conditions of 300 bar and 60 °C with 300µm of ginger powder for 120 mins. In comparison, the yield of the extract was increased considerably within a short extraction time. The results show that scCO2 has a remarkable ability over ginger extract and is a promising technology for extracting bioactive compounds from plant material.

Keywords: conventional, ginger, non-environmentally, supercritical carbon dioxide, technology

Procedia PDF Downloads 91
2711 Change Detection Method Based on Scale-Invariant Feature Transformation Keypoints and Segmentation for Synthetic Aperture Radar Image

Authors: Lan Du, Yan Wang, Hui Dai

Abstract:

Synthetic aperture radar (SAR) image change detection has recently become a challenging problem owing to the existence of speckle noises. In this paper, an unsupervised distribution-free change detection for SAR image based on scale-invariant feature transform (SIFT) keypoints and segmentation is proposed. Firstly, the noise-robust SIFT keypoints which reveal the blob-like structures in an image are extracted in the log-ratio image to reduce the detection range. Then, different from the traditional change detection which directly obtains the change-detection map from the difference image, segmentation is made around the extracted keypoints in the two original multitemporal SAR images to obtain accurate changed region. At last, the change-detection map is generated by comparing the two segmentations. Experimental results on the real SAR image dataset demonstrate the effectiveness of the proposed method.

Keywords: change detection, Synthetic Aperture Radar (SAR), Scale-Invariant Feature Transformation (SIFT), segmentation

Procedia PDF Downloads 355
2710 Evaluation of Two DNA Extraction Methods for Minimal Porcine (Pork) Detection in Halal Food Sample Mixture Using Taqman Real-time PCR Technique

Authors: Duaa Mughal, Syeda Areeba Nadeem, Shakil Ahmed, Ishtiaq Ahmed Khan

Abstract:

The identification of porcine DNA in Halal food items is critical to ensuring compliance with dietary restrictions and religious beliefs. In Islam, Porcine is prohibited as clearly mentioned in Quran (Surah Al-Baqrah, Ayat 173). The purpose of this study was to compare two DNA extraction procedures for detecting 0.001% of porcine DNA in processed Halal food sample mixtures containing chicken, camel, veal, turkey and goat meat using the TaqMan Real-Time PCR technology. In this research, two different commercial kit protocols were compared. The processed sample mixtures were prepared by spiking known concentration of porcine DNA to non-porcine food matrices. Afterwards, TaqMan Real-Time PCR technique was used to target a particular porcine gene from the extracted DNA samples, which was quantified after extraction. The results of the amplification were evaluated for sensitivity, specificity, and reproducibility. The results of the study demonstrated that two DNA extraction techniques can detect 0.01% of porcine DNA in mixture of Halal food samples. However, as compared to the alternative approach, Eurofins| GeneScan GeneSpin DNA Isolation kit showed more effective sensitivity and specificity. Furthermore, the commercial kit-based approach showed great repeatability with minimal variance across repeats. Quantification of DNA was done by using fluorometric assay. In conclusion, the comparison of DNA extraction methods for detecting porcine DNA in Halal food sample mixes using the TaqMan Real-Time PCR technology reveals that the commercial kit-based approach outperforms the other methods in terms of sensitivity, specificity, and repeatability. This research helps to promote the development of reliable and standardized techniques for detecting porcine DNA in Halal food items, religious conformity and assuring nutritional.

Keywords: real time PCR (qPCR), DNA extraction, porcine DNA, halal food authentication, religious conformity

Procedia PDF Downloads 39
2709 Potential Application of Modified Diglycolamide Resin for Rare Earth Element Extraction

Authors: Junnile Romero, Ilhwan Park, Vannie Joy Resabal, Carlito Tabelin, Richard Alorro, Leaniel Silva, Joshua Zoleta, Takunda Mandu, Kosei Aikawa, Mayumi Ito, Naoki Hiroyoshi

Abstract:

Rare earth elements (REE) play a vital role in technological advancement due to their unique physical and chemical properties essential for various renewable energy applications. However, this increasing demand represents a challenging task for sustainability that corresponds to various research interests relating to the development of various extraction techniques, particularly on the extractant being used. In this study, TK221 (a modified polymer resin containing diglycolamide, carbamoyl methyl phosphine oxide (CMPO), and diglycolamide (DGA-N)) has been investigated as a conjugate extractant. FTIR and SEM analysis results confirmed the presence of CMPO and DGA-N being coated onto the PS-DVB support of TK221. Moreover, the kinetic rate law and adsorption isotherm batch test was investigated to understand the corresponding adsorption mechanism. The results show that REEs’ (Nd, Y, Ce, and Er) obtained pseudo-second-order kinetics and Langmuir isotherm, suggesting that the adsorption mechanism undergoes a single monolayer adsorption site via a chemisorption process. The Qmax values of Nd, Ce, Er, Y, and Fe were 45.249 mg/g, 43.103 mg/g, 35.088 mg/g, 15.552 mg/g, and 12.315 mg/g, respectively. This research further suggests that TK221 polymer resin can be used as an alternative absorbent material for an effective REE extraction.

Keywords: rare earth element, diglycolamide, characterization, extraction resin

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2708 Optimization of Poly-β-Hydroxybutyrate Recovery from Bacillus Subtilis Using Solvent Extraction Process by Response Surface Methodology

Authors: Jayprakash Yadav, Nivedita Patra

Abstract:

Polyhydroxybutyrate (PHB) is an interesting material in the field of medical science, pharmaceutical industries, and tissue engineering because of its properties such as biodegradability, biocompatibility, hydrophobicity, and elasticity. PHB is naturally accumulated by several microbes in their cytoplasm during the metabolic process as energy reserve material. PHB can be extracted from cell biomass using halogenated hydrocarbons, chemicals, and enzymes. In this study, a cheaper and non-toxic solvent, acetone, was used for the extraction process. The different parameters like acetone percentage, and solvent pH, process temperature, and incubation periods were optimized using the Response Surface Methodology (RSM). RSM was performed and the determination coefficient (R2) value was found to be 0.8833 from the quadratic regression model with no significant lack of fit. The designed RSM model results indicated that the fitness of the response variable was significant (P-value < 0.0006) and satisfactory to denote the relationship between the responses in terms of PHB recovery and purity with respect to the values of independent variables. Optimum conditions for the maximum PHB recovery and purity were found to be solvent pH 7, extraction temperature - 43 °C, incubation time - 70 minutes, and percentage acetone – 30 % from this study. The maximum predicted PHB recovery was found to be 0.845 g/g biomass dry cell weight and the purity was found to be 97.23 % using the optimized conditions.

Keywords: acetone, PHB, RSM, halogenated hydrocarbons, extraction, bacillus subtilis.

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2707 A Relational Case-Based Reasoning Framework for Project Delivery System Selection

Authors: Yang Cui, Yong Qiang Chen

Abstract:

An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

Procedia PDF Downloads 399
2706 The Utilization of Tea Extract within the Realm of the Food Industry

Authors: Raana Babadi Fathipour

Abstract:

Tea, a beverage widely cherished across the globe, has captured the interest of scholars with its recent acknowledgement for possessing noteworthy health advantages. Of particular significance is its proven ability to ward off ailments such as cancer and cardiovascular afflictions. Moreover, within the realm of culinary creations, lipid oxidation poses a significant challenge for food product development. In light of these aforementioned concerns, this present discourse turns its attention towards exploring diverse methodologies employed in extracting polyphenols from various types of tea leaves and examining their utility within the vast landscape of the ever-evolving food industry. Based on the discoveries unearthed in this comprehensive investigation, it has been determined that the fundamental constituents of tea are polyphenols possessed of intrinsic health-enhancing properties. This includes an assortment of catechins, namely epicatechin, epigallocatechin, epicatechin gallate, and epigallocatechin gallate. Moreover, gallic acid, flavonoids, flavonols and theaphlavins have also been detected within this aromatic beverage. Of these myriad components examined vigorously in this study's analysis, catechin emerges as particularly beneficial. Multiple techniques have emerged over time to successfully extract key compounds from tea plants, including solvent-based extraction methodologies, microwave-assisted water extraction approaches and ultrasound-assisted extraction techniques. In particular, consideration is given to microwave-assisted water extraction method as a viable scheme which effectively procures valuable polyphenols from tea extracts. This methodology appears adaptable for implementation within sectors such as dairy production along with meat and oil industries alike.

Keywords: camellia sinensis, extraction, food application, shelf life, tea

Procedia PDF Downloads 45
2705 Functionalized Magnetic Iron Oxide Nanoparticles for Extraction of Protein and Metal Nanoparticles from Complex Fluids

Authors: Meenakshi Verma, Mandeep Singh Bakshi, Kultar Singh

Abstract:

Magnetic nanoparticles have received incredible importance in view of their diverse applications, which arise primarily due to their response to the external magnetic field. The magnetic behaviour of magnetic nanoparticles (NPs) helps them in numerous different ways. The most important amongst them is the ease with which they can be purified and also can be separated from the media in which they are present merely by applying an external magnetic field. This exceptional ease of separation of the magnetic NPs from an aqueous media enables them to use for extracting/removing metal pollutants from complex aqueous medium. Functionalized magnetic NPs can be subjected for the metallic impurities extraction if are favourably adsorbed on the NPs surfaces. We have successfully used the magnetic NPs as vehicles for gold and silver NPs removal from the complex fluids. The NPs loaded with gold and silver NPs pollutant fractions has been easily removed from the aqueous media by using external magnetic field. Similarly, we have used the magnetic NPs for extraction of protein from complex media and then constantly washed with pure water to eliminate the unwanted surface adsorbed components for quantitative estimation. The purified and protein loaded magnetic NPs are best analyzed with SDS Page to not only for characterization but also for separating the protein fractions. A collective review of the results indicates that we have synthesized surfactant coated iron oxide NPs and then functionalized these with selected materials. These surface active magnetic NPs work very well for the extraction of metallic NPs from the aqueous bulk and make the whole process environmentally sustainable. Also, magnetic NPs-Au/Ag/Pd hybrids have excellent protein extracting properties. They are much easier to use in order to extract the magnetic impurities as well as protein fractions under the effect of external magnetic field without any complex conventional purification methods.

Keywords: magnetic nanoparticles, protein, functionalized, extraction

Procedia PDF Downloads 79
2704 Smartphone-Based Human Activity Recognition by Machine Learning Methods

Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

Procedia PDF Downloads 122
2703 Improved Pitch Detection Using Fourier Approximation Method

Authors: Balachandra Kumaraswamy, P. G. Poonacha

Abstract:

Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors.

Keywords: pitch, fourier series, yin, normalization of the auto- correlation function, harmonic product, mean square error

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2702 Surface Modification of TiO2 Layer with Phosphonic Acid Monolayer in Perovskite Solar Cells: Effect of Chain Length and Terminal Functional Group

Authors: Seid Yimer Abate, Ding-Chi Huang, Yu-Tai Tao

Abstract:

In this study, charge extraction characteristics at the perovskite/TiO2 interface in the conventional perovskite solar cell is studied by interface engineering. Self-assembled monolayers of phosphonic acids with different chain length and terminal functional group were used to modify mesoporous TiO2 surface to modulate the surface property and interfacial energy barrier to investigate their effect on charge extraction and transport from the perovskite to the mp-TiO2 and then the electrode. The chain length introduces a tunnelling distance and the end group modulate the energy level alignment at the mp-TiO2 and perovskite interface. The work function of these SAM-modified mp-TiO2 varied from −3.89 eV to −4.61 eV, with that of the pristine mp-TiO2 at −4.19 eV. A correlation of charge extraction and transport with respect to the modification was attempted. The study serves as a guide to engineer ETL interfaces with simple SAMs to improve the charge extraction, carrier balance and device long term stability. In this study, a maximum PCE of ~16.09% with insignificant hysteresis was obtained, which is 17% higher than the standard device.

Keywords: Energy level alignment, Interface engineering, Perovskite solar cells, Phosphonic acid monolayer, Tunnelling distance

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2701 Deployed Confidence: The Testing in Production

Authors: Shreya Asthana

Abstract:

Testers know that the feature they tested on stage is working perfectly in production only after release went live. Sometimes something breaks in production and testers get to know through the end user’s bug raised. The panic mode starts when your staging test results do not reflect current production behavior. And you started doubting your testing skills when finally the user reported a bug to you. Testers can deploy their confidence on release day by testing on production. Once you start doing testing in production, you will see test result accuracy because it will be running on real time data and execution will be a little faster as compared to staging one due to elimination of bad data. Feature flagging, canary releases, and data cleanup can help to achieve this technique of testing. By this paper it will be easier to understand the steps to achieve production testing before making your feature live, and to modify IT company’s testing procedure, so testers can provide the bug free experience to the end users. This study is beneficial because too many people think that testing should be done in staging but not in production and now this is high time to pull out people from their old mindset of testing into a new testing world. At the end of the day, it all just matters if the features are working in production or not.

Keywords: bug free production, new testing mindset, testing strategy, testing approach

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2700 Research on Construction of Subject Knowledge Base Based on Literature Knowledge Extraction

Authors: Yumeng Ma, Fang Wang, Jinxia Huang

Abstract:

Researchers put forward higher requirements for efficient acquisition and utilization of domain knowledge in the big data era. As literature is an effective way for researchers to quickly and accurately understand the research situation in their field, the knowledge discovery based on literature has become a new research method. As a tool to organize and manage knowledge in a specific domain, the subject knowledge base can be used to mine and present the knowledge behind the literature to meet the users' personalized needs. This study designs the construction route of the subject knowledge base for specific research problems. Information extraction method based on knowledge engineering is adopted. Firstly, the subject knowledge model is built through the abstraction of the research elements. Then under the guidance of the knowledge model, extraction rules of knowledge points are compiled to analyze, extract and correlate entities, relations, and attributes in literature. Finally, a database platform based on this structured knowledge is developed that can provide a variety of services such as knowledge retrieval, knowledge browsing, knowledge q&a, and visualization correlation. Taking the construction practices in the field of activating blood circulation and removing stasis as an example, this study analyzes how to construct subject knowledge base based on literature knowledge extraction. As the system functional test shows, this subject knowledge base can realize the expected service scenarios such as a quick query of knowledge, related discovery of knowledge and literature, knowledge organization. As this study enables subject knowledge base to help researchers locate and acquire deep domain knowledge quickly and accurately, it provides a transformation mode of knowledge resource construction and personalized precision knowledge services in the data-intensive research environment.

Keywords: knowledge model, literature knowledge extraction, precision knowledge services, subject knowledge base

Procedia PDF Downloads 135
2699 Nanofluid-Based Emulsion Liquid Membrane for Selective Extraction and Separation of Dysprosium

Authors: Maliheh Raji, Hossein Abolghasemi, Jaber Safdari, Ali Kargari

Abstract:

Dysprosium is a rare earth element which is essential for many growing high-technology applications. Dysprosium along with neodymium plays a significant role in different applications such as metal halide lamps, permanent magnets, and nuclear reactor control rods preparation. The purification and separation of rare earth elements are challenging because of their similar chemical and physical properties. Among the various methods, membrane processes provide many advantages over the conventional separation processes such as ion exchange and solvent extraction. In this work, selective extraction and separation of dysprosium from aqueous solutions containing an equimolar mixture of dysprosium and neodymium by emulsion liquid membrane (ELM) was investigated. The organic membrane phase of the ELM was a nanofluid consisting of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as carrier, kerosene as base fluid, and nitric acid solution as internal aqueous phase. Factors affecting separation of dysprosium such as carrier concentration, MWCNT concentration, feed phase pH and stripping phase concentration were analyzed using Taguchi method. Optimal experimental condition was obtained using analysis of variance (ANOVA) after 10 min extraction. Based on the results, using MWCNT nanofluid in ELM process leads to increase the extraction due to higher stability of membrane and mass transfer enhancement and separation factor of 6 for dysprosium over neodymium can be achieved under the optimum conditions. Additionally, demulsification process was successfully performed and the membrane phase reused effectively in the optimum condition.

Keywords: emulsion liquid membrane, MWCNT nanofluid, separation, Taguchi method

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2698 Recovery of Rare Earths and Scandium from in situ Leaching Solutions

Authors: Maxim S. Botalov, Svetlana М. Titova, Denis V. Smyshlyaev, Grigory M. Bunkov, Evgeny V. Kirillov, Sergey V. Kirillov, Maxim A. Mashkovtsev, Vladimir N. Rychkov

Abstract:

In uranium production, in-situ leaching (ISL) with its relatively low cost has become an important technology. As the orebody containing uranium most often contains a considerable value of other metals, particularly rare earth metals it has rendered feasible to recover the REM from the barren ISL solutions, from which the major uranium content has been removed. Ural Federal University (UrFU, Ekaterinburg, Russia) have performed joint research on the development of industrial technologies for the extraction of REM and Scandium compounds from Uranium ISL solutions. Leaching experiments at UrFU have been supported with multicomponent solution model. The experimental work combines solvent extraction with advanced ion exchange methodology in a pilot facility capable of treating 500 kg/hr of solids. The pilot allows for the recovery of a 99% concentrate of scandium oxide and collective concentrate with over 50 % REM content, with further recovery of heavy and light REM concentrates (99%).

Keywords: extraction, ion exchange, rare earth elements, scandium

Procedia PDF Downloads 207
2697 Cellulose Extraction from Pomelo Peel: Synthesis of Carboxymethyl Cellulose

Authors: Jitlada Chumee, Drenpen Seeburin

Abstract:

The cellulose was extracted from pomelo peel and an etherification reaction used for converting cellulose to carboxymethyl cellulose (CMC). The pomelo peel was refluxed with 0.5 M HCl and 1 M NaOH solution at 90°C for 1 h and 2 h, respectively. The cellulose was bleached with calcium hypochlorite and used as precursor. The precursor was soaked in mixed solution between isopropyl alcohol and 40%w/v NaOH for 12 h. After that, chloroacetic acid was added and reacted at 55°C for 6 h. The optimum condition was 5 g of cellulose: 0.25 mole of NaOH : 0.07 mole of ClCH2COOH with 78.00% of yield. Moreover, the product had 0.54 of degree of substitution (DS).

Keywords: pomelo peel, carboxymethyl cellulose, bioplastic, extraction

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2696 Determination of the Volatile Organic Compounds, Antioxidant and Antimicrobial Properties of Microwave-Assisted Green Extracted Ficus Carica Linn Leaves

Authors: Pelin Yilmaz, Gizemnur Yildiz Uysal, Elcin Demirhan, Belma Ozbek

Abstract:

The edible fig plant, Ficus carica Linn, belongs to the Moraceae family, and the leaves are mainly considered agricultural waste after harvesting. It has been demonstrated in the literature that fig leaves contain appealing properties such as high vitamins, fiber, amino acids, organic acids, and phenolic or flavonoid content. The extraction of these valuable products has gained importance. Microwave-assisted extraction (MAE) is a method using microwave energy to heat the solvents, thereby transferring the bioactive compounds from the sample to the solvent. The main advantage of the MAE is the rapid extraction of bioactive compounds. In the present study, the MAE was applied to extract the bioactive compounds from Ficus carica L. leaves, and the effect of microwave power (180-900 W), extraction time (60-180 s), and solvent to sample amount (mL/g) (10-30) on the antioxidant property of the leaves. Then, the volatile organic component profile was determined at the specified extraction point. Additionally, antimicrobial studies were carried out to determine the minimum inhibitory concentration of the microwave-extracted leaves. As a result, according to the data obtained from the experimental studies, the highest antimicrobial properties were obtained under the process parameters such as 540 W, 180 s, and 20 mL/g concentration. The volatile organic compound profile showed that isobergapten, which belongs to the furanocoumarins family exhibiting anticancer, antioxidant, and antimicrobial activity besides promoting bone health, was the main compound. Acknowledgments: This work has been supported by Yildiz Technical University Scientific Research Projects Coordination Unit under project number FBA-2021-4409. The authors would like to acknowledge the financial support from Tubitak 1515 - Frontier R&D Laboratory Support Programme.

Keywords: Ficus carica Linn leaves, volatile organic component, GC-MS, microwave extraction, isobergapten, antimicrobial

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2695 Phenolic Compounds and Antimicrobial Properties of Pomegranate (Punica granatum) Peel Extracts

Authors: P. Rahnemoon, M. Sarabi Jamab, M. Javanmard Dakheli, A. Bostan

Abstract:

In recent years, tendency to use of natural antimicrobial agents in food industry has increased. Pomegranate peels containing phenolic compounds and anti-microbial agents, are counted as valuable source for extraction of these compounds. In this study, the extraction of pomegranate peel extract was carried out at different ethanol/water ratios (40:60, 60:40, and 80:20), temperatures (25, 40, and 55 ˚C), and time durations (20, 24, and 28 h). The extraction yield, phenolic compounds, flavonoids, and anthocyanins were measured. ‎Antimicrobial activity of pomegranate peel extracts were determined against some food-borne ‎microorganisms such as Salmonella enteritidis, Escherichia coli, Listeria monocytogenes, ‎‎Staphylococcus aureus, Aspergillus niger, and Saccharomyces cerevisiae by agar diffusion and MIC methods. Results showed that at ethanol/water ratio 60:40, 25 ˚C and 24 h maximum amount of phenolic compounds ‎(‎‎349.518‎‏ ‏mg gallic acid‏/‏g dried extract), ‎flavonoids (250.124 mg rutin‏/‏g dried extract), anthocyanins (252.047 ‎‏‏mg ‎cyanidin‎3‎glucoside‏/‏‎100 g dried extract), and the strongest antimicrobial activity were obtained. ‎All extracts’ antimicrobial activities were demonstrated against every tested ‎‎microorganisms.‎Staphylococcus aureus showed the highest sensitivity among the tested ‎‎‎microorganisms.

Keywords: antimicrobial agents, phenolic compounds, pomegranate peel, solvent extraction‎

Procedia PDF Downloads 236
2694 An Object-Based Image Resizing Approach

Authors: Chin-Chen Chang, I-Ta Lee, Tsung-Ta Ke, Wen-Kai Tai

Abstract:

Common methods for resizing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image resizing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

Keywords: energy map, visual saliency, gradient map, seam carving

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2693 Back Extraction and Isolation of Alkaloids from Ionic Liquid-Based Extracts

Authors: Rozalina Keremedchieva, Ivan Svinyarov, Milen G. Bogdanov

Abstract:

In continuation of a research project on the application of ionic liquids (ILs) as an alternative to the conventional organic solvents used in the recovery of value added chemicals of industrial interest1-3 we developed a procedure for back extraction and isolation in pure form of the biologically active alkaloid glaucine from IL-based aqueous solutions. One of the approaches applied was the formation of two-phase systems (IL-ATPS) by the addition of kosmotropic salts to the plant extract. The ability of the salts (Na2CO3, MgSO4, (NH4)2SO4, NaH2PO4) to induce the formation of two-phase systems and the influence of pH value on the partition coefficients of glaucine was comprehensively studied. As a result, it was found that the target alkaloid is preferably partitioned into the IL-rich phase regardless of the pH value of the medium and thus shows the inapplicability of the approach used for the isolation of the target compound from the ionic liquid. However, the results obtained can be used as a platform for the development of an analytical method for the quantitative determination of low concentrations of glaucine in biological samples. We further examined the ability of a series of organic solvents such as diethyl ether, Tert-butylmethyl ether, ethyl acetate, butyl acetate, toluene, chloroform, dichloromethane to recover glaucine form raw IL-based aqueous extracts. Optimal conditions for quantitative extraction of glaucine into chloroform were found from which, after removal of the solvent and subsequent recrystallization from ethanol, the target compound was isolated in a high purity as a hydrobromide salt – The form in which it entrance as an active ingredient in various medicines.

Keywords: natural products, ionic liquids, solid-liquid extraction, liquid-liquid extraction

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2692 Extraction of Compound Words in Malay Sentences Using Linguistic and Statistical Approaches

Authors: Zamri Abu Bakar Zamri, Normaly Kamal Ismail Normaly, Mohd Izani Mohamed Rawi Izani

Abstract:

Malay noun compound are phrases that consist of two or more nouns. The key characteristic behind noun compounds lies on its frequent occurrences within the text. Therefore, extracting these noun compounds is essential for several domains of research such as Information Retrieval, Sentiment Analysis and Question Answering. Many research efforts have been proposed in terms of extracting Malay noun compounds using linguistic and statistical approaches. Most of the existing methods have concentrated on the extraction of bi-gram noun+noun compound. However, extracting noun+verb, noun+adjective and noun+prepositional is challenging due to the difficulty of selecting an appropriate method with effective results. Thus, there is still room for improvement in terms of enhancing the effectiveness of compound word extraction. Therefore, this study proposed a combination of linguistic approach and statistical measures in order to enhance the extraction of compound words. Several preprocessing steps are involved including normalization, tokenization, and stemming. The linguistic approach that has been used in this study is Part-of-Speech (POS) tagging. In addition, a new linguistic pattern for named entities has been utilized using a list of Malays named entities in order to enhance the linguistic approach in terms of noun compound recognition. The proposed statistical measures consists of NC-value, NTC-value and NLC value.

Keywords: Compound Word, Noun Compound, Linguistic Approach, Statistical Approach

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2691 GC and GCxGC-MS Composition of Volatile Compounds from Cuminum cyminum and Carum carvi by Using Techniques Assisted by Microwaves

Authors: F. Benkaci-Ali, R. Mékaoui, G. Scholl, G. Eppe

Abstract:

The new methods as accelerated steam distillation assisted by microwave (ASDAM) is a combination of microwave heating and steam distillation, performed at atmospheric pressure at very short extraction time. Isolation and concentration of volatile compounds are performed by a single stage. (ASDAM) has been compared with (ASDAM) with cryogrinding of seeds (CG) and a conventional technique, hydrodistillation assisted by microwave (HDAM), hydro-distillation (HD) for the extraction of essential oil from aromatic herb as caraway and cumin seeds. The essential oils extracted by (ASDAM) for 1 min were quantitatively (yield) and qualitatively (aromatic profile) no similar to those obtained by ASDAM-CG (1 min) and HD (for 3 h). The accelerated microwave extraction with cryogrinding inhibits numerous enzymatic reactions as hydrolysis of oils. Microwave radiations constitute the adequate mean for the extraction operations from the yields and high content in major component majority point view, and allow to minimise considerably the energy consumption, but especially heating time too, which is one of essential parameters of artifacts formation. The ASDAM and ASDAM-CG are green techniques and yields an essential oil with higher amounts of more valuable oxygenated compounds comparable to the biosynthesis compounds, and allows substantial savings of costs, in terms of time, energy and plant material.

Keywords: microwave, steam distillation, caraway, cumin, cryogrinding, GC-MS, GCxGC-MS

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2690 Examining How Youth Use Mobile Devices for Health Information: Preliminary Findings of a Survey Study with High School Students in Croatia

Authors: Sung Un Kim, Ivana Martinović, Snježana Stanarević Katavić

Abstract:

As more and more youth use mobile devices, such as tablets and smartphones, for information seeking in their everyday lives, the purpose of this study is to understand the behaviors of youth seeking health information on mobile devices. The specific objective of this study is to examine 1) for what health issues youth use mobile devices, 2) for what reasons youth use mobile devices to obtain health information, 3) in what ways youth use mobile devices for health information, and 4) the features of health applications that youth find useful. The researchers devised a questionnaire for this study. Four hundred eight students from two high schools, located in Osijek, Croatia, participated by answering the questionnaire (281 girls and 127 boys). The collected data were analyzed using descriptive statistics and content analysis. The results show that among all participants, about 85 percent (n = 344) reported having used mobile devices for health information. The most frequent health topic for which they had been using mobile devices is physical activity (n = 273), followed by eating issues and nutrition (n = 224), mental health (n = 160), sexual health (n = 157), alcohol, drugs, and tobacco (n = 125), safety (n = 96) and particular diseases (n = 62). They use mobile devices to obtain health information due to the ease of use (n = 342), the ease of sharing health information (n = 281), portability (n = 215), timeliness (n = 162), and the ease of tracking/recording/monitoring health status (n = 147). Of those who have used mobile devices for health information, three-quarters (n = 261) use mobile devices to search health information, while 32.8% (n =113) use applications and 31.7% (n =109) browse information. Those who have used applications for health information (n = 113) consider the alert feature (n=107) as the most useful, followed by the tracking/recording/monitoring feature (n =92), the customized information feature (n = 86), the video feature (n = 58), and the sharing feature (n =39). It is notable that although health applications have been actively developed and studied, a majority of the participants search for or browse information on mobile devices, instead of using applications. The researchers will discuss reasons that some of them did not use mobile devices to obtain health information, students’ concerns about using health applications, and features that they wish to have in health applications.

Keywords: Croatia, health information, information seeking behaviors, mobile devices, youth

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2689 Research and Application of Multi-Scale Three Dimensional Plant Modeling

Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

Abstract:

Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

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2688 Challenges and Opportunities: One Stop Processing for the Automation of Indonesian Large-Scale Topographic Base Map Using Airborne LiDAR Data

Authors: Elyta Widyaningrum

Abstract:

The LiDAR data acquisition has been recognizable as one of the fastest solution to provide the basis data for topographic base mapping in Indonesia. The challenges to accelerate the provision of large-scale topographic base maps as a development plan basis gives the opportunity to implement the automated scheme in the map production process. The one stop processing will also contribute to accelerate the map provision especially to conform with the Indonesian fundamental spatial data catalog derived from ISO 19110 and geospatial database integration. Thus, the automated LiDAR classification, DTM generation and feature extraction will be conducted in one GIS-software environment to form all layers of topographic base maps. The quality of automated topographic base map will be assessed and analyzed based on its completeness, correctness, contiguity, consistency and possible customization.

Keywords: automation, GIS environment, LiDAR processing, map quality

Procedia PDF Downloads 342