Search results for: end-user trained information extraction

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

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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

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

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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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Authors: Vanessa G. P. Severino, JOÃO Gabriel M. Junqueira, Michelle N. G. do Nascimento, Francisco W. B. Aquino, João B. Fernandes, Ana P. Terezan

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The scientific interest in analyzing VOCs represents a significant modern research field as a result of importance in most branches of the present life and industry. Therefore it is extremely important to investigate, identify and isolate volatile substances, since they can be used in different areas, such as food, medicine, cosmetics, perfumery, aromatherapy, pesticides, repellents and other household products through methods for extracting volatile constituents, such as solid phase microextraction (SPME), hydrodistillation (HD), solvent extraction (SE), Soxhlet extraction, supercritical fluid extraction (SFE), stream distillation (SD) and vacuum distillation (VD). The Chemometrics is an area of chemistry that uses statistical and mathematical tools for the planning and optimization of the experimental conditions, and to extract relevant chemical information multivariate chemical data. In this context, the focus of this work was the study of the chemical VOCs by SPME of the specie X. aromatica, in search of constituents that can be used in the industrial sector as well as in food, cosmetics and perfumery, since these areas industrial has a considerable role. In addition, by chemometric analysis, we sought to maximize the answers of this research, in order to search for the largest number of compounds. The investigation of flowers from X. aromatica in vitro and in alive mode proved consistent, but certain factors supposed influence the composition of metabolites, and the chemometric analysis strengthened the analysis. Thus, the study of the chemical composition of X. aromatica contributed to the VOCs knowledge of the species and a possible application.

Keywords: chemometrics, flowers, HS-SPME, Xylopia aromatica

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

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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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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Zainuddin Zakaria, Sun Woh Lye

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Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resolution are two key factors that impact their use. This paper proposes a methodology to unearth and classify ATCO conflict resolution strategies from simulator data of trained and qualified ATCOs. The methodology involves the extraction of ATCO executive control actions and the establishment of a system of strategy resolution classification based on ATCO radar commands and prevailing flight parameters in deconflicting a pair of aircraft. Six main strategies used to handle various categories of conflict were identified and discussed. It was found that ATCOs were about twice more likely to choose only vertical maneuvers in conflict resolution compared to horizontal maneuvers or a combination of both vertical and horizontal maneuvers.

Keywords: air traffic control strategies, conflict resolution, simulator data, strategy classification system

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Arish Iqbal, Santosh Kumar Singh

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Energy from coal is one of the major source of energy throughout the world but taking into consideration its effect on environment 'Clean Coal Technologies' (CCT) came into existence. In this paper we have we studied why CCT’s are essential and what are the different types of CCT’s. Also, the coal and CCT scenario in India is introduced. Coal Bed Methane one of major CCT area is studied in detail. Different types of coal bed methane and its methods of extraction are discussed. The different problem areas during the extraction of CBM are identified and discussed. How CBM can be used as a fuel for future is also discussed.

Keywords: CBM (coal bed methane), CCS (carbon capture and storage), CCT (clean coal technology), CMM (coal mining methane)

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Bina Gupta, Rashmi Singh, Harshit Mahandra

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Molybdenum is a strategic metal and finds applications in petroleum refining, thermocouples, X-ray tubes and in making of steel alloy owing to its high melting temperature and tensile strength. The growing significance and economic value of molybdenum has increased interest in the development of efficient processes aiming its recovery from secondary sources. Main secondary sources of Mo are molybdenum catalysts which are used for hydrodesulphurisation process in petrochemical refineries. The activity of these catalysts gradually decreases with time during the desulphurisation process as the catalysts get contaminated with toxic material and are dumped as waste which leads to environmental issues. In this scenario, recovery of molybdenum from spent catalyst is significant from both economic and environmental point of view. Recently ionic liquids have gained prominence due to their low vapour pressure, high thermal stability, good extraction efficiency and recycling capacity. The present study reports recovery of molybdenum from Mo-Co spent leach liquor using Cyphos IL 102[trihexyl(tetradecyl)phosphonium bromide] as an extractant. Spent catalyst was leached with 3.0 mol/L HCl, and the leach liquor containing Mo-870 ppm, Co-341 ppm, Al-508 ppm and Fe-42 ppm was subjected to extraction step. The effect of extractant concentration on the leach liquor was investigated and almost 85% extraction of Mo was achieved with 0.05 mol/L Cyphos IL 102. Results of stripping studies revealed that 2.0 mol/L HNO3 can effectively strip 94% of the extracted Mo from the loaded organic phase. McCabe- Thiele diagrams were constructed to determine the number of stages required for quantitative extraction and stripping of molybdenum and were confirmed by countercurrent simulation studies. According to McCabe- Thiele extraction and stripping isotherms, two stages are required for quantitative extraction and stripping of molybdenum at A/O= 1:1. Around 95.4% extraction of molybdenum was achieved in two-stage counter current at A/O= 1:1 with the negligible extraction of Co and Al. However, iron was coextracted and removed from the loaded organic phase by scrubbing with 0.01 mol/L HCl. Quantitative stripping (~99.5 %) of molybdenum was achieved with 2.0 mol/L HNO₃ in two stages at O/A=1:1. Overall ~95.0% molybdenum with 99 % purity was recovered from Mo-Co spent catalyst. From the strip solution, MoO₃ was obtained by crystallization followed by thermal decomposition. The product obtained after thermal decomposition was characterized by XRD, FE-SEM and EDX techniques. XRD peaks of MoO₃ correspond to molybdite Syn-MoO₃ structure. FE-SEM depicts the rod-like morphology of synthesized MoO₃. EDX analysis of MoO₃ shows 1:3 atomic percentage of molybdenum and oxygen. The synthesised MoO₃ can find application in gas sensors, electrodes of batteries, display devices, smart windows, lubricants and as a catalyst.

Keywords: cyphos Il 102, extraction, spent mo-co catalyst, recovery

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Ching-Ting Hsu, Wei-Hua Ho, Yi-Chun Chang

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Video object tracking is one of the popular research topics in computer graphics area. The trajectory can be applied in security, traffic control, even the sports training. The trajectory for sports training can be utilized to analyze the athlete’s performance without traditional sensors. There are many relevant works which utilize mean shift algorithm with background subtraction. This kind of the schemes should select a kernel function which may affect the accuracy and performance. In this paper, we consider the motion information in the pre-coded bitstream. The proposed algorithm extracts the trajectory by composing the motion vectors from the pre-coded bitstream. We gather the motion vectors from the overlap area of the object and calculate mean of the overlapped motion vectors. We implement and simulate our proposed algorithm in H.264 video codec. The performance is better than relevant works and keeps the accuracy of the object trajectory. The experimental results show that the proposed trajectory extraction can extract trajectory form the pre-coded bitstream in high accuracy and achieve higher performance other relevant works.

Keywords: H.264, video bitstream, video object tracking, sports training

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Authors: Bina Gupta, Rashmi Singh, Harshit Mahandra

Abstract:

Molybdenum is a strategic metal and finds applications in petroleum refining, thermocouples, X-ray tubes and in making of steel alloy owing to its high melting temperature and tensile strength. The growing significance and economic value of molybdenum have increased interest in the development of efficient processes aiming its recovery from secondary sources. Main secondary sources of Mo are molybdenum catalysts which are used for hydrodesulphurisation process in petrochemical refineries. The activity of these catalysts gradually decreases with time during the desulphurisation process as the catalysts get contaminated with toxic material and are dumped as waste which leads to environmental issues. In this scenario, recovery of molybdenum from spent catalyst is significant from both economic and environmental point of view. Recently ionic liquids have gained prominence due to their low vapour pressure, high thermal stability, good extraction efficiency and recycling capacity. Present study reports recovery of molybdenum from Mo-Co spent leach liquor using Cyphos IL 102[trihexyl(tetradecyl)phosphonium bromide] as an extractant. Spent catalyst was leached with 3 mol/L HCl and the leach liquor containing Mo-870 ppm, Co-341 ppm, Al-508 ppm and Fe-42 ppm was subjected to extraction step. The effect of extractant concentration on the leach liquor was investigated and almost 85% extraction of Mo was achieved with 0.05 mol/L Cyphos IL 102. Results of stripping studies revealed that 2 mol/L HNO3 can effectively strip 94% of the extracted Mo from the loaded organic phase. McCabe-Thiele diagrams were constructed to determine the number of stages required for quantitative extraction and stripping of molybdenum and were confirmed by counter current simulation studies. According to McCabe-Thiele extraction and stripping isotherms, two stages are required for quantitative extraction and stripping of molybdenum at A/O= 1:1. Around 95.4% extraction of molybdenum was achieved in two stage counter current at A/O= 1:1 with negligible extraction of Co and Al. However, iron was coextracted and removed from the loaded organic phase by scrubbing with 0.01 mol/L HCl. Quantitative stripping (~99.5 %) of molybdenum was achieved with 2.0 mol/L HNO3 in two stages at O/A=1:1. Overall ~95.0% molybdenum with 99 % purity was recovered from Mo-Co spent catalyst. From the strip solution, MoO3 was obtained by crystallization followed by thermal decomposition. The product obtained after thermal decomposition was characterized by XRD, FE-SEM and EDX techniques. XRD peaks of MoO3correspond to molybdite Syn-MoO3 structure. FE-SEM depicts the rod like morphology of synthesized MoO3. EDX analysis of MoO3 shows 1:3 atomic percentage of molybdenum and oxygen. The synthesised MoO3 can find application in gas sensors, electrodes of batteries, display devices, smart windows, lubricants and as catalyst.

Keywords: cyphos IL 102, extraction, Mo-Co spent catalyst, recovery

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Authors: Hazlin Kadir Shahar, Razaleigh Muhamat Kawangit, Badlihisham Mohd Nasir, Rosmawati Mohamad Rasit

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Stigma and discrimination have become the main topic of discussion when dealing with HIV/AIDS issues. They affect the daily life of People Living With HIV(PLHIV), families, friends and people around them indirectly. This paper discusses the potential measurement in helping to reduce stigma and discrimination existence among Islamic Religious Officers towards PLHIV in Malaysia. These people have been trained with special programmes to tackle the HIV/AIDS issues by using a manual, namely as ‘The Manual of Islam and HIV/AIDS’, specifically designed by the Islamic Development Department of Malaysia (JAKIM). The objectives of the training programmes are to give the accurate information about HIV/AIDS and to suggest ways on how to handle the PLHIV issues in Islamic perspective. This research used quantitative methodology by survey. A pilot test had been done over thirty (30) trained Islamic Religious Officers in Malaysia. The findings have shown that the trainings have given a positive impact for them as they managed to acquire the knowledge of HIV/AIDS from both primer and authorized sources such as medical practitioners, Muslim chaplains and social workers. The knowledge they have acquired from the trainings has guided them in changing their perception, thus helping to reduce their own stigma and discrimination towards PLHIV. The training programmes have given them opportunities to practice what they have learned through several outreach sessions as they have had the opportunities to approach PLHIV directly.

Keywords: Islamic religious officers, people with HIV, stigma and discrimination, training programmes

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Authors: Mikiyas Adugna

Abstract:

Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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Authors: Udeshika Yapa Bandara, Chamindri Witharana, Preethi Soysa

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Pomegranate fruits are used in cancer treatment in Ayurveda, Sri Lanka. Due to prevailing therapeutic effects of phytochemicals, this study was focus on anti-cancer properties of the constituents in the parts of Pomegranate fruit. Furthermore, the method of extraction, plays a crucial step of the phytochemical analysis. Therefore, this study was focus on different extraction methods. Five techniques were involved for the peel and the pericarp to evaluate the most effective extraction method; Boiling with electric burner (BL), Sonication (SN), Microwaving (MC), Heating in a 50°C water bath (WB) and Sonication followed by Microwaving (SN-MC). The presence of polyphenolic and flavonoid contents were evaluated to recognize the best extraction method for polyphenols. The total phenolic content was measured spectrophotometrically by Folin-Ciocalteu method and expressed as Gallic Acid Equivalents (w/w% GAE). Total flavonoid content was also determined spectrophotometrically with Aluminium chloride colourimetric assay and expressed as Quercetin Equivalents (w/w % QE). Pomegranate juice was taken as fermented juice (with Saccharomyces bayanus) and fresh juice. Powdered seeds were refluxed, filtered and freeze-dried. 2g of freeze-dried powder of each component was dissolved in 100ml of De-ionized water for extraction. For the comparison of antioxidant activity and total phenol content, the polyphenols were removed by the Polyvinylpolypyrrolidone (PVVP) column and fermented and fresh juice were tested for the 1, 1-diphenyl-2-picrylhydrazil (DPPH) radical scavenging activity, before and after the removal of polyphenols. For the peel samples of Pomegranate fruit, total phenol and flavonoid contents were high in Sonication (SN). In pericarp, total phenol and flavonoid contents were highly exhibited in method of Sonication (SN). A significant difference was observed (P< 0.05) in total phenol and flavonoid contents, between five extraction methods for both peel and pericarp samples. Fermented juice had a greatest polyphenolic and flavonoid contents comparative to fresh juice. After removing polyphenols of fermented juice and fresh juice using Polyvinyl polypyrrolidone (PVVP) column, low antioxidant activity was resulted for DPPH antioxidant activity assay. Seeds had a very low total phenol and flavonoid contents according to the results. Although, Pomegranate peel is the main waste component of the fruit, it has an excellent polyphenolic and flavonoid contents compared to other parts of the fruit, devoid of the method of extraction. Polyphenols play a major role for antioxidant activity.

Keywords: antioxidant activity, flavonoids, polyphenols, pomegranate

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: Abdoulaye Maihatchi Ahamed, Zubin Arora, Benjamin Swobada, Jean-yves Lansot, Alexandre Chagnes

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Lithium-ion battery (LiB) is the technology of choice in the development of electric vehicles. But there are still many challenges, including the development of positive electrode materials exhibiting high cycle ability, high energy density, and low environmental impact. For this latter, LiBs must be manufactured in a circular approach by developing the appropriate strategies to reuse and recycle them. Presently, the recycling of LiBs is carried out by the pyrometallurgical route, but more and more processes implement or will implement the hydrometallurgical route or a combination of pyrometallurgical and hydrometallurgical operations. After producing the black mass by mineral processing, the hydrometallurgical process consists in leaching the black mass in order to uptake the metals contained in the cathodic material. Then, these metals are extracted selectively by liquid-liquid extraction, solid-liquid extraction, and/or precipitation stages. However, liquid-liquid extraction combined with precipitation/crystallization steps is the most implemented operation in the LiB recycling process to selectively extract copper, aluminum, cobalt, nickel, manganese, and lithium from the leaching solution and precipitate these metals as high-grade sulfate or carbonate salts. Liquid-liquid extraction consists in contacting an organic solvent and an aqueous feed solution containing several metals, including the targeted metal(s) to extract. The organic phase is non-miscible with the aqueous phase. It is composed of an extractant to extract the target metals and a diluent, which is usually aliphatic kerosene produced from the petroleum industry. Sometimes, a phase modifier is added in the formulation of the extraction solvent to avoid the third phase formation. The extraction properties of the diluent do not depend only on the chemical structure of the extractant, but it may also depend on the nature of the diluent. Indeed, the interactions between the diluent can influence more or less the interactions between extractant molecules besides the extractant-diluent interactions. Only a few studies in the literature addressed the influence of the diluent on the extraction properties, while many studies focused on the effect of the extractants. Recently, new low-carbon footprint aliphatic diluents were produced by catalytic dearomatisation and distillation of bio-based oil. This study aims at investigating the influence of the nature of the diluent on the extraction properties of three extractants towards cobalt, nickel, manganese, copper, aluminum, and lithium: Cyanex®272 for nickel-cobalt separation, DEHPA for manganese extraction, and Acorga M5640 for copper extraction. The diluents used in the formulation of the extraction solvents are (i) low-odor aliphatic kerosene produced from the petroleum industry (ELIXORE 180, ELIXORE 230, ELIXORE 205, and ISANE IP 175) and (ii) bio-sourced aliphatic diluents (DEV 2138, DEV 2139, DEV 1763, DEV 2160, DEV 2161 and DEV 2063). After discussing the effect of the diluents on the extraction properties, this conference will address the development of a low carbon footprint process based on the use of the best bio-sourced diluent for the production of high-grade cobalt sulfate, nickel sulfate, manganese sulfate, and lithium carbonate, as well as metal copper.

Keywords: diluent, hydrometallurgy, lithium-ion battery, recycling

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Toktam Khatibi

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Self-supervised learning (SSL) includes machine learning models that are trained on one aspect and/or one part of the input to learn other aspects and/or part of it. SSL models are divided into two different categories, including pre-text task-based models and contrastive learning ones. Pre-text tasks are some auxiliary tasks learning pseudo-labels, and the trained models are further fine-tuned for downstream tasks. However, one important disadvantage of SSL using pre-text task solving is defining an appropriate pre-text task for each image dataset with a variety of image modalities. Therefore, it is required to design an appropriate pretext task automatically for each dataset and each downstream task. To the best of our knowledge, the automatic designing of pretext tasks for image analysis has not been considered yet. In this paper, we present a framework based on In-context learning that describes each task based on its input and output data using a pre-trained image transformer. Our proposed method combines the input image and its learned description for optimizing the pre-text task design and its hyper-parameters using Meta-learning models. The representations learned from the pre-text tasks are fine-tuned for solving the downstream tasks. We demonstrate that our proposed framework outperforms the compared ones on unseen tasks and image modalities in addition to its superior performance for previously known tasks and datasets.

Keywords: in-context learning (ICL), meta learning, self-supervised learning (SSL), vision-language domain, transformers

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Authors: Daham Owaid Matrood, Naqaa Hussein Raheem

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Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.

Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization

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Authors: Abe D. Desta

Abstract:

This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: A. B. Bazaralieva, A. A. Turgumbayeva

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

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

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Authors: Alev Atak

Abstract:

In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Emmanuelle Maria, Pierre Crançon, Gaëtane Lespes

Abstract:

Colloids are ubiquitous in the environment and are known to play a major role in enhancing the transport of trace elements, thus being an important vector for contaminants dispersion. Colloids study and characterization are necessary to improve our understanding of the fate of pollutants in the environment. However, in stream water and groundwater, colloids are often very poorly concentrated. It is therefore necessary to pre-concentrate colloids in order to get enough material for analysis, while preserving their initial structure. Many techniques are used to extract and/or pre-concentrate the colloidal phase from bulk aqueous phase, but yet there is neither reference method nor estimation of the impact of these different techniques on the colloids structure, as well as the bias introduced by the separation method. In the present work, we have tested and compared several methods of colloidal phase extraction/pre-concentration, and their impact on colloids properties, particularly their size distribution and their elementary composition. Ultrafiltration methods (frontal, tangential and centrifugal) have been considered since they are widely used for the extraction of colloids in natural waters. To compare these methods, a ‘synthetic groundwater’ was used as a reference. The size distribution (obtained by Field-Flow Fractionation (FFF)) and the chemical composition of the colloidal phase (obtained by Inductively Coupled Plasma Mass Spectrometry (ICPMS) and Total Organic Carbon analysis (TOC)) were chosen as comparison factors. In this way, it is possible to estimate the pre-concentration impact on the colloidal phase preservation. It appears that some of these methods preserve in a more efficient manner the colloidal phase composition while others are easier/faster to use. The choice of the extraction/pre-concentration method is therefore a compromise between efficiency (including speed and ease of use) and impact on the structural and chemical composition of the colloidal phase. In perspective, the use of these methods should enhance the consideration of colloidal phase in the transport of pollutants in environmental assessment studies and forensics.

Keywords: chemical composition, colloids, extraction, preconcentration methods, size distribution

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Authors: Tatyana Alexandrova, Alexandr Alexandrov, Nadezhda Nikolaeva

Abstract:

A problem of complex mineral resources development is urgent and priority, it is aimed at realization of the processes of their ecologically safe development, one of its components is revealing the influence of the forms of element compounds in raw materials and in the processing products. In view of depletion of the precious metal reserves at the traditional deposits in the XXI century the large-size open cast deposits, localized in black shale strata begin to play the leading role. Carbonaceous (black) shales carry a heightened metallogenic potential. Black shales with high content of carbon are widely distributed within the scope of Bureinsky massif. According to academician Hanchuk`s data black shales of Sutirskaya series contain generally PGEs native form. The presence of high absorptive towards carbonaceous matter gold and PGEs compounds in crude ore results in decrease of valuable components extraction because of their sorption into dissipated carbonaceous matter.

Keywords: сarbonaceous rocks, bitumens, precious metals, concentration, extraction

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Authors: Alafara A. Baba, Kuranga I. Ayinla, Folahan A. Adekola, Rafiu B. Bale

Abstract:

Due to increasing demands and diverse applications of copper oxide as pigment in ceramics, cuprammonium hydroxide solution for rayon, p-type semi-conductor, dry cell batteries production and as safety disposal of hazardous materials, a study on the hydrometallurgical operations involving leaching, solvent extraction and precipitation for the recovery of copper for producing high grade copper oxide from a Nigerian chalcopyrite ore in chloride media has been examined. At a particular set of experimental parameter with respect to acid concentration, reaction temperature and particle size, the leaching investigation showed that the ore dissolution increases with increasing acid concentration, temperature and decreasing particle diameter at a moderate stirring. The kinetics data has been analyzed and was found to follow diffusion control mechanism. At optimal conditions, the extent of ore dissolution reached 94.3%. The recovery of the total copper from the hydrochloric acid-leached chalcopyrite ore was undertaken by solvent extraction and precipitation techniques, prior to the beneficiation of the purified solution as copper oxide. The purification of the leach liquor was firstly done by precipitation of total iron and manganese using Ca(OH)2 and H2O2 as oxidizer at pH 3.5 and 4.25, respectively. An extraction efficiency of 97.3% total copper was obtained by 0.2 mol/L Dithizone in kerosene at 25±2ºC within 40 minutes, from which ≈98% Cu from loaded organic phase was successfully stripped by 0.1 mol/L HCl solution. The beneficiation of the recovered pure copper solution was carried out by crystallization through alkali addition followed by calcination at 600ºC to obtain high grade copper oxide (Tenorite, CuO: 05-0661). Finally, a simple hydrometallurgical scheme for the operational extraction procedure amenable for industrial utilization and economic sustainability was provided.

Keywords: chalcopyrite ore, Nigeria, copper, copper oxide, solvent extraction

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Authors: Kabil Boukhari

Abstract:

In the context of information retrieval, the selection of the most relevant words is a very important step. In fact, the text cleaning allows keeping only the most representative words for a better use. In this paper, we propose a library for the purpose text preprocessing within an implemented application to facilitate this task. This study has two purposes. The first, is to present the related work of the various steps involved in text preprocessing, presenting the segmentation, stemming and lemmatization algorithms that could be efficient in the rest of study. The second, is to implement a developed tool for text preprocessing in French and English. This library accepts unstructured text as input and provides the preprocessed text as output, based on a set of rules and on a base of stop words for both languages. The proposed library has been made on different corpora and gave an interesting result.

Keywords: text preprocessing, segmentation, knowledge extraction, normalization, text generation, information retrieval

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Authors: Maycon dos Santos, Marivane Turim Koschevic, Karina Sayuri Ueda, Marcello Lima Bertuci, Farayde Matta Fackhouri, Silvia Maria Martelli

Abstract:

The use of cellulose nanocrystals as reinforcing agents in polymer nanocomposites is promising. In this study, we tested four different methods of mercerization were divided into two stages. The sample was treated in 5% NaOH solution for 30 minutes at 50 ° C in the first stage and 30vol H2O2 for 2 hours at 50 ° C in the second step, which showed better results. For the extraction of the sample obtained nanocrystals positive result was that the solution was treated with H2SO4 60% (w / w) for 1 hour at 50 ° C. The results were positive and showed that it is possible to extract CNC at low temperatures.

Keywords: soy pods, cellulose nanocrystals, temperature, acid concentration

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Authors: Shannon Steinmetz, Ellen Gethner

Abstract:

In this paper, a theoretical foundation is developed for patterned segmentation of audio using the geometry of music and statistical manifold. We demonstrate image content clustering using conic space sonification. The algorithm takes a geodesic curve as a model estimator of the three-parameter Gamma distribution. The random variable is parameterized by musical centricity and centric velocity. Model parameters predict audio segmentation in the form of duration and frame count based on the likelihood of musical geometry transition. We provide an example using a database of randomly selected images, resulting in statistically significant clusters of similar image content.

Keywords: sonification, musical information geometry, image, content extraction, automated quantification, audio segmentation, pattern recognition

Procedia PDF Downloads 199