Search results for: comprehensive feature extraction

Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction

Procedia PDF Downloads 344

Authors: Pradeep Kumar, Abhishek Kumar Chandra, Ashok Khanna

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Extraction of Strontium by crown ether (DCH18C6) hasbeen investigated in [BMIM][TF2N] Ionic Liquid (IL) giving higher extraction ~98% and distribution ratio as compared to other organic solvents (Dodecane, Hexane, & Isodecyl alcohol + Dodecane). Distribution ratio of Sr in IL at 0.15M DCH18C6 indicates an enhancement of 20000, 2000, 500 times over Dodecane, Hexane and 5% Isodecyl Alcohol + 95 % Dodecane at 0.01M aqueous acidity respectively. In presence of IL, Sr extraction decreases with increase in HNO3 concentration in aqueous phase whereas opposite trend was observed with organic solvents.Extraction of Sr initially increases with increase in DCH18C6 concentration in IL, finally reaching an asymptotic constant.

Keywords: distribution ratio, ionic liquid, ligand, organic solvent, stripping

Procedia PDF Downloads 412

Authors: Lila Boulekbache-Makhlouf, Kahina Djaoud, Myriam Tazarourte, Samir Hadjal, Khodir Madani

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In Algeria, important quantities of secondary date variety (Phoenix dactylifera L.) are generated in each campaign; their chemical composition is similar to that of commercial dates. The present work aims to valorize this common date variety (Degla-Beida) which is often poorly exploited. In this context, we tried to prepare syrup from the secondary date variety and to evaluate the effect of conventional extraction (CE) or water bath extraction (WBE) and alternative extraction (microwaves assisted extraction (MAE), and ultrasounds assisted extraction (UAE)) on its total sugar content (TSC), using response surface methodology (RSM). Then, the analysis of individual sugars was performed by high-performance liquid chromatography (HPLC). Maximum predicted TSC recoveries under the optimized conditions for MAE, UAE and CE were 233.248 ± 3.594 g/l, 202.889 ± 5.797 g/l, and 233.535 ± 5.412 g/l, respectively, which were close to the experimental values: 233.796 ± 1.898 g/l; 202.037 ± 3.401 g/l and 234.380 ± 2.425 g/l. HPLC analysis revealed high similarity in the sugar composition of date juices obtained by MAE (60.11% sucrose, 16.64% glucose and 23.25% fructose) and CE (50.78% sucrose, 20.67% glucose and 28.55% fructose), although a large difference was detected for that obtained by UAE (0.00% sucrose, 46.94% glucose and 53.06% fructose). Microwave-assisted extraction was the best method for the preparation of date syrup with an optimal recovery of total sugar content. However, ultrasound-assisted extraction was the best one for the preparation of date syrup with high content of reducing sugars.

Keywords: dates, extraction, RSM, sugars, syrup

Procedia PDF Downloads 129

Authors: A. Bara, D. Barkat

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The liquid-liquid extraction of copper (II) from aqueous solution by capric acid (HL) in chloroform at 25°C has been studied. The ionic strength effect of the aqueous phase shows that the extraction of copper(II) increases with the increase in ionic strength. with different ionic strengths 1, 0.5, 0.25, 0.125 and 0.1M in the aqueous phase. Cu (II) is extracted as the complex CuL2(ClO4).

Keywords: liquid-liquid extraction, ionic strength, copper (II), capric acid

Procedia PDF Downloads 506

Authors: Khaled Mawardi

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Bay laurel (Laurus nobilis L.) is an evergreen of the Laurus genus of the Lauraceae Family. It is a plant native to the southern Mediterranean and widespread in Syria. It is a plant with enormous industrial applications. For instance, they are used as platform chemicals in food, pharmaceutical and cosmetic applications. Herein, we report an efficient extraction of Bay laurel oil from Bay laurel fruits via a comparative investigation of boiled water conventional extraction technique and microwave-assisted extraction (MAE) by microwave heating at atmospheric pressure. In order to optimize the extraction efficiency, we investigated several extraction parameters, such as extraction time and microwave power. In addition, to demonstrate the feasibility of the method, oil obtained under optimal conditions by method (MAE) was compared quantitatively and qualitatively with that obtained by the conventional method. After 1h of microwave-assisted extraction (power of 600W), an oil yield of 9.8% with identified lauric acid content of 22.7%. In comparison, an extended extraction of up to 4h was required to obtain a 9.7% yield of oil extraction with 21.2% of lauric acid content. The change in microwave power impacts the fatty acids profile and also the quality parameters of Laurel Oil. It was found that the profile of fatty acids changed with the power, where the lauric acid content increased from 22.7% at 600W to 30.5% at 1200W owing to a decrease of oleic acid content from 32.8% at 600W to 28.3% at 1200W and linoleic acid content from 22.3% at 600W to 20.6% at 1200W. In addition, we observed a decrease in oil yield from 9.8% at 600W to 5.1% at 1200W. Summarily, the overall results indicated that the extraction of laurel fruit oils could be successfully performed using (MAE) at a short extraction time and lower energy compared with the fixed oil obtained by conventional processes of extraction. Microwave heating exerted more aggressive effects on the oil. Indeed, microwave heating inflicted changes in the fatty acids profile of oil; the most affected fraction was the unsaturated fatty acids, with higher susceptibility to oxidation.

Keywords: microwaves, extraction, Laurel oil, solvent-free

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Authors: Karam Ignaim, Joao M. Fernandes, Andre L. Ferreira

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Mapping the artifacts coming from a set of similar products family developed in an ad-hoc manner to make up the resulting software product line (SPL) plays a key role to maintain the consistency between requirements and code. This paper presents a feature mapping approach that focuses on tracing the artifact coming from the migration process, the current feature model (FM), to the other artifacts of the resulting SPL, the reference architecture, and code. Thus, our approach relates each feature of the current FM to its locations in the implementation code, using the reference architecture as an intermediate artifact (as a centric point) to preserve consistency among them during an SPL evolution. The approach uses a particular artifact (i.e., traceability tree) as a solution for managing the mapping process. Tool support is provided using friendlyMapper. We have evaluated the feature mapping approach and tool support by putting the approach into practice (i.e., conducting a case study) of the automotive domain for Classical Sensor Variants Family at Bosch Car Multimedia S.A. The evaluation reveals that the mapping approach presented by this paper fits the automotive domain.

Keywords: feature location, feature models, mapping, software product lines, traceability

Procedia PDF Downloads 91

Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

Procedia PDF Downloads 89

Authors: Elham Mahdian, Reza Karazhian, Rahele Dehghan Tanha

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Pepper (Capsicum annum L.) which belong to the family Solananceae, are known for their versatility as a vegetable crop and are consumed both as fresh vegetables or dehydrated for spices. Pepper is considered an excellent source of bioactive nutrients. Ascorbic acid, carotenoids and phenolic compounds are its main antioxidant constituents. Ultrasound assisted extraction is an inexpensive, simple and efficient alternative to conventional extraction techniques. The mechanism of action for ultrasound-assisted extraction are attributed to cavitations, mechanical forces and thermal impact, which result in disruption of cells walls, reduce particle size, and enhance mass transfer across cell membranes. In this study, response surface methodology was used to optimize experimental conditions for ultrasonic assisted extraction of carotenoid compounds from Chili peppers. Variables were included extraction temperatures at 3 levels (30, 40 and 50 °C), extraction times at 3 levels (10, 25 and 40 minutes) and power at 3 levels (30, 60 and 90 %). It was observed that ultrasound waves applied at temperature of 49°C, time of 10 minutes and power 89 % resulted to the highest carotenoids contents (lycopene and β-carotene), while the lowest value was recorded in the control. Thus, results showed that ultrasound waves have strong impact on extraction of carotenoids from pepper.

Keywords: carotenoids, optimization, pepper, response surface methodology

Procedia PDF Downloads 436

Authors: Sergio S. De Jesus, Aline Santana, Rubens Maciel Filho

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The objective of this study was to choose and determine a green solvent system with similar extraction efficiencies as the traditional Bligh and Dyer method. Sunflower seed oil was extracted using Bligh and Dyer method with 2-methyltetrahydrofuran and isoamyl using alcohol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. At the same time comparative experiments was performed with chloroform and methanol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. Comparison study was done using 5 replicates (n=5). Statistical analysis was performed using Microsoft Office Excel (Microsoft, USA) to determine means and Tukey’s Honestly Significant Difference test for comparison between treatments (α = 0.05). The results showed that using classic method with methanol and chloroform presented the extraction oil yield with the values of 31-44% (w/w) and values of 36-45% (w/w) using green solvents for extractions. Among the two extraction methods, 2 methyltetrahydrofuran and isoamyl alcohol ratio 2:1 provided the best results (45% w/w), while the classic method using chloroform and methanol with ratio of 3:1 presented a extraction oil yield of 44% (w/w). It was concluded that the proposed extraction method using 2-methyltetrahydrofuran and isoamyl alcohol in this work allowed the same efficiency level as chloroform and methanol.

Keywords: extraction, green solvent, lipids, sugarcane

Procedia PDF Downloads 348

Authors: A. Zonouzi, M. Auli, M. Javanmard Dakheli, M. A. Hejazi

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Microalgae are tiny photosynthetic plants. Nowadays, microalgae are being used as nutrient-dense foods and sources of fine chemicals. They have significant amounts of lipid, carotenoids, vitamins, protein, minerals, chlorophyll, and pigments. Oil extraction from algae is a hotly debated topic currently because introducing an efficient method could decrease the process cost. This can determine the sustainability of algae-based foods. Scientific research works show that solvent extraction using chloroform/methanol (2:1) mixture is one of the efficient methods for oil extraction from algal cells, but both methanol and chloroform are toxic solvents, and therefore, the extracted oil will not be suitable for food application. In this paper, the effect of two food grade solvents (hexane and hexane/ isopropanol) on oil extraction yield from microalgae Dunaliella sp. was investigated and the results were compared with chloroform/methanol (2:1) extraction yield. It was observed that the oil extraction yield using hexane, hexane/isopropanol (3:2) and chloroform/methanol (2:1) mixture were 5.4, 13.93, and 17.5 (% w/w, dry basis), respectively. The fatty acid profile derived from GC illustrated that the palmitic (36.62%), oleic (18.62%), and stearic acids (19.08%) form the main portion of fatty acid composition of microalgae Dunalliela sp. oil. It was concluded that, the addition of isopropanol as polar solvent could increase the extraction yield significantly. Isopropanol solves cell wall phospholipids and enhances the release of intercellular lipids, which improves accessing of hexane to fatty acids.

Keywords: fatty acid profile‎, microalgae‎, oil extraction‎, polar solvent‎

Procedia PDF Downloads 343

Authors: Analise Borg, Paul Micallef

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Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organize the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that non-parametric analysis offer potential results as the ones mentioned in the literature.

Keywords: audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7

Procedia PDF Downloads 394

Authors: Muhammad Fezan Afzal, Asad Abbas, Imran Khan, Salma Imtiaz

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Software Product Line (SPL) paradigm is used for the development of the family of software products that share common and variable features. Feature model is a domain of SPL that consists of common and variable features with predefined relationships and constraints. Multiple SPLs consist of a number of similar common and variable features, such as mobile phones and Tabs. Reusability of common and variable features from the different domains of SPL is a complex task due to the external relationships and constraints of features in the feature model. To increase the reusability of feature model resources from domain engineering, it is required to manage the commonality of features at the level of SPL application development. In this research, we have proposed an approach that combines multiple SPLs into a single domain and converts them to a common feature model. Extracting the common features from different feature models is more effective, less cost and time to market for the application development. For extracting features from multiple SPLs, the proposed framework consists of three steps: 1) find the variation points, 2) find the constraints, and 3) combine the feature models into a single feature model on the basis of variation points and constraints. By using this approach, reusability can increase features from the multiple feature models. The impact of this research is to reduce the development of cost, time to market and increase products of SPL.

Keywords: software product line, feature model, variability management, multi-SPLs

Procedia PDF Downloads 40

Authors: G. C. Jadeja, M. A. Desai, D. R. Bhatt, J. K. Parikh

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Green extraction techniques are fast paving ways into various industrial sectors due to the stringent governmental regulations leading to the banning of toxic chemicals’ usage and also due to the increasing health/environmental awareness. The present work describes the ionic liquids based sonication method for selectively extracting patchoulol from the leaves of patchouli. 1-Butyl-3-methylimidazolium tetrafluoroborate ([Bmim]BF4) and N,N,N,N’,N’,N’-Hexaethyl-butane-1,4-diammonium dibromide (dicationic ionic liquid - DIL) were selected for extraction. Ultrasound assisted ionic liquid extraction was employed considering concentration of ionic liquid (4–8 %, w/w), ultrasound power (50–150 W for [Bmim]BF4 and 20–80 W for DIL), temperature (30–50 oC) and extraction time (30–50 min) as major parameters influencing the yield of patchoulol. Using the Taguchi method, the parameters were optimized and analysis of variance (ANOVA) was performed to find the most influential factor in the selected extraction method. In case of [Bmim]BF4, the optimum conditions were found to be: 4 % (w/w) ionic liquid concentration, 50 W power, 30 oC temperature and extraction time of 30 min. The yield obtained under the optimum conditions was 3.99 mg/g. In case of DIL, the optimum conditions were obtained as 6 % (w/w) ionic liquid concentration, 80 W power, 30 oC temperature and extraction time of 40 min, for which the yield obtained was 4.03 mg/g. Temperature was found to be the most significant factor in both the cases. Extraction time was the insignificant parameter while extracting the product using [Bmim]BF4 and in case of DIL, power was found to be the least significant factor affecting the process. Thus, a green method of recovering patchoulol is proposed.

Keywords: green extraction, ultrasound, patchoulol, ionic liquids

Procedia PDF Downloads 331

Authors: Praneeth Puvvula

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Autonomy in has become increasingly common in modern automotive cars. There are 5 levels of autonomy as defined by SAE. This paper focuses on a SAE level 2 feature which, by definition, is able to control the vehicle longitudinally and laterally at the same time. The system keeps the vehicle centred with in the lane by detecting the lane boundaries while maintaining the vehicle speed. As with the features from SAE level 1 to level 3, the primary responsibility of dynamic driving task lies with the driver. This will need monitoring techniques to ensure the driver is always engaged even while the feature is active. This paper focuses on the these techniques, which would help the safe usage of the feature and provide appropriate warnings to the driver.

Keywords: autonomous driving, safety, adas, automotive technology

Procedia PDF Downloads 55

Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Oshin Anand, Atanu Rakshit

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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

Procedia PDF Downloads 363

Authors: Angela Justina Kumalaputri

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Indonesia, as a maritime country, has abundant marine living resources yet has not been optimally utilized. So far, we only focusing on fisheries. In the other hand, Indonesia, as the country with the fourth longest coastline, is a very good cultivation place for microalgae. Microalgae can be diversified to many important products, such as food, fuel, pharmaceutical products, functional food, and cosmetics.This research is focusing on the literature study about types of microalgae as sources for functional foods (such as antioxidants), including the contents and the separation methods. The research methods which we use are: (1) Literature study about various microalgaes (2) Literature study about extractions using supercritical fluid of CO₂, which are free from toxic organic solvents, environmentally friendly, and safe for food products. Supercritical fluid extraction using CO₂ (low critical points: temperature at 31.1 oC and pressure at 72.9 bars) could be done at a low temperature which are suitable for temperature labile compounds, low energy, and faster extraction time compared with conventional method of extraction.

Keywords: antioxidants, supercritical fluid extraction, solvent-free extraction, microalgae

Procedia PDF Downloads 45

Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

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This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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Authors: Mario Pérez-Won, Vilbett Briones L., Guido Trautmann, María José Bugueño, Gipsy Tabilo-Munizaga, Luis Gonzalez-Cavieres

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The fishing industry generates a significant amount of shrimp byproducts, which often result in environmental contamination. Protein extraction from these by-products is a potential solution to minimize waste and revalue the by-products. To improve the extraction of proteins (by chemical method) from shrimp (Pleuroncodes monodon) by-products, the emerging technologies of ohmic heating (OH), microwaves (MW) and pulsed electric fields (PEF) were used. The results show that microwaves, electrical pulses, and ohmic heating improved performance by 28.19%, 19.25%, and 3.65%, respectively. Furthermore, conformational changes were studied by DSC and FTIR. Subsequently, the use of these proteins in electrospinning technology was evaluated. In conclusion, this study demonstrates that the application of emerging technologies, can significantly improve the extraction yield of proteins from shrimp by-products.

Keywords: electrospinning, emerging technologies, improving extraction, shrimp by-products

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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Authors: Chih-Yi Ho, Tzu-Fang Chang, Chih-Chia Huang, Chia-Yen Lee

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In dental clinics, the dentists use the periapical radiography image to assess the effectiveness of endodontic treatment of teeth with chronic apical periodontitis. Periapical radiography images are taken at different times to assess alveolar bone variation before and after the root canal treatment, and furthermore to judge whether the treatment was successful. Current clinical assessment of apical tissue recovery relies only on dentist personal experience. It is difficult to have the same standard and objective interpretations due to the dentist or radiologist personal background and knowledge. If periapical radiography images at the different time could be registered well, the endodontic treatment could be evaluated. In the image registration area, it is necessary to assign representative control points to the transformation model for good performances of registration results. However, detection of representative control points (feature points) on periapical radiography images is generally very difficult. Regardless of which traditional detection methods are practiced, sufficient feature points may not be detected due to the low-contrast characteristics of the x-ray image. Barnard detector is an algorithm for feature point detection based on grayscale value gradients, which can obtain sufficient feature points in the case of gray-scale contrast is not obvious. However, the Barnard detector would detect too many feature points, and they would be too clustered. This study uses the local extrema of clustering feature points and the suppression radius to overcome the problem, and compared different feature point detection methods. In the preliminary result, the feature points could be detected as representative control points by the proposed method.

Keywords: feature detection, Barnard detector, registration, periapical radiography image, endodontic treatment

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Authors: Rob Gesley Capistrano, Jasper James Isaac, Rose Mae Moralda, Therese Anne Peleo, Danica Rillo, Maria Virginia Santillian

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One of the valuable things that shows the intelligence among individuals is the academic background specifically their Grade Weighted Average and the significant result of the Comprehensive Examination. The general objective of the researchers to this study is to determine if there is a significant difference between General Weighted Average and Comprehensive Examination Result of Psychometrician Board Passers and Non-Board Passers. The respondents of this study composed of board passers and non-board passers. The researchers used purposive sampling technique. The result utilized by using T-test Independent Sample to determine the comparison of General Weighted Average and Comprehensive Examination Result of Board Passers and Non Board Passers. At the end, it concluded that the General Weighted Average of Board Passers and Non-Board Passers shows that there is no significant difference, but the average showed a minimal variation. The Comprehensive Examination Result of Board Passers and Non-Board Passers result revealed that there is a significant difference. The performance of comprehensive examination that will test the overall knowledge of an individual and will determine whose more proficient will likely to have a higher score. The result of the comprehensive examination had an impact in the passing performance of board examination.

Keywords: board passers, comprehensive examination result, grade weighted average, non board passers

Procedia PDF Downloads 152

Authors: Anil Kawan, Soon Jae Yu, Jong Min Park

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GaN-based 365 nm wavelength ultraviolet (UV) light emitting diodes (LED) have various applications: curing, molding, purification, deodorization, and disinfection etc. However, their usage is limited by very low output power, because of the light absorption in the GaN layers. In this study, we demonstrate a method utilizing removal of 365 nm absorption layer buffer GaN and thinning the n-type GaN so as to improve the light extraction efficiency of the GaN-based 365 nm UV LED. The UV flip chip LEDs of chip size 1.3 mm x 1.3 mm were fabricated using GaN epilayers on a sapphire substrate. Via-hole n-type contacts and highly reflective Ag metal were used for efficient light extraction. LED wafer was aligned and bonded to AlN carrier wafer. To improve the extraction efficiency of the flip chip LED, sapphire substrate and absorption layer buffer GaN were removed by using laser lift-off and dry etching, respectively. To further increase the extraction efficiency of the LED, exposed n-type GaN thickness was reduced by using inductively coupled plasma etching.

Keywords: extraction efficiency, light emitting diodes, n-GaN thinning, ultraviolet

Procedia PDF Downloads 392

Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

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Authors: Reihaneh Ahmadzadeh Ghavidel

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Free radicals such as reactive oxygen species (ROS) have detrimental effects on human health through several mechanisms. On the other hand, antioxidant molecules reduce free radical generation in biologic systems. Synthetic antioxidants, which are used in food industry, have also negative impact on human health. Therefore recognition of natural antioxidants such as anthocyanins can solve these problems simultaneously. Coleus (Solenostemon scutellarioides) with red leaves is a rich source of anthocyanins compounds. In this study we evaluated the effect of time (10, 20 and 30 min) and temperature (40, 50 and 60° C) on optimization of anthocyanin extraction using surface response method. In addition, the study was aimed to determine maximum extraction for anthocyanin from coleus plant using ultrasound method. The results indicated that the optimum conditions for extraction were 39.84 min at 69.25° C. At this point, total compounds were achieved 3.7451 mg 100 ml⁻¹. Furthermore, under optimum conditions, anthocyanin concentration, extraction efficiency, ferric reducing ability, total phenolic compounds and EC50 were registered 3.221931, 6.692765, 223.062, 3355.605 and 2.614045, respectively.

Keywords: anthocyanin, antioxidant, coleus, extraction, sonication

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

Abstract:

Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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Authors: A. Degale Desta, Cheng Jian

Abstract:

Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Débora P. Jaeschke, Eduardo A. Merlo, Rosane Rech, Giovana D. Mercali, Ligia D. F. Marczak

Abstract:

Carotenoids are high value added pigments that can be alternatively extracted from some microalgae species. However, the application of carotenoids synthetized by microalgae is still limited due to the utilization of organic toxic solvents. In this context, studies involving alternative extraction methods have been conducted with more sustainable solvents to replace and reduce the solvent volume and the extraction time. The aim of the present work was to evaluate the extraction time of carotenoids from the microalgae Heterochlorella luteoviridis using moderate electric field (MEF) as a pre-treatment to the extraction. The extraction methodology consisted of a pre-treatment in the presence of MEF (180 V) and ethanol (25 %, v/v) for 10 min, followed by a diffusive step performed for 50 min using a higher ethanol concentration (75 %, v/v). The extraction experiments were conducted at 30 °C and, to keep the temperature at this value, it was used an extraction cell with a water jacket that was connected to a water bath. Also, to enable the evaluation of MEF effect on the extraction, control experiments were performed using the same cell and conditions without voltage application. During the extraction experiments, samples were withdrawn at 1, 5 and 10 min of the pre-treatment and at 1, 5, 30, 40 and 50 min of the diffusive step. Samples were, then, centrifuged and carotenoids analyses were performed in the supernatant. Furthermore, an exhaustive extraction with ethyl acetate and methanol was performed, and the carotenoids content found for this analyses was considered as the total carotenoids content of the microalgae. The results showed that the application of MEF as a pre-treatment to the extraction influenced the extraction yield and the extraction time during the diffusive step; after the MEF pre-treatment and 50 min of the diffusive step, it was possible to extract up to 60 % of the total carotenoids content. Also, results found for carotenoids concentration of the extracts withdrawn at 5 and 30 min of the diffusive step did not presented statistical difference, meaning that carotenoids diffusion occurs mainly in the very beginning of the extraction. On the other hand, the results for control experiments showed that carotenoids diffusion occurs mostly during 30 min of the diffusive step, which evidenced MEF effect on the extraction time. Moreover, carotenoids concentration on samples withdrawn during the pre-treatment (1, 5 and 10 min) were below the quantification limit of the analyses, indicating that the extraction occurred in the diffusive step, when ethanol (75 %, v/v) was added to the medium. It is possible that MEF promoted cell membrane permeabilization and, when ethanol (75 %) was added, carotenoids interacted with the solvent and the diffusion occurred easily. Based on the results, it is possible to infer that MEF promoted the decrease of carotenoids extraction time due to the increasing of the permeability of the cell membrane which facilitates the diffusion from the cell to the medium.

Keywords: moderate electric field (MEF), pigments, microalgae, ethanol

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Authors: Saurabh Satija, Munish Garg

Abstract:

Present work reports an efficient extraction method using microwaves based solvent–sample duo-heating mechanism, for the extraction of an important anti-diabetic plant Tinospora cordifolia from AYUSH system for estimation of berberine content. The process is based on simultaneous heating of sample matrix and extracting solvent under microwave energy. Methanol was used as the extracting solvent, which has excellent berberine solubilizing power and warms up under microwave attributable to its great dispersal factor. Extraction conditions like time of irradition, microwave power, solute-solvent ratio and temperature were optimized using Taguchi design and berberine was quantified using high performance thin layer chromatography. The ranked optimized parameters were microwave power (rank 1), irradiation time (rank 2) and temperature (rank 3). This kind of extraction mechanism under dual heating provided choice of extraction parameters for better precision and higher yield with significant reduction in extraction time under optimum extraction conditions. This developed extraction protocol will lead to extract higher amounts of berberine which is a major anti-diabetic moiety in Tinospora cordifolia which can lead to development of cheaper formulations of the plant Tinospora cordifolia and can help in rapid prevention of diabetes in the world.

Keywords: berberine, microwave, optimization, Taguchi

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Authors: Deepak Kumar, Jahangeer, Brijesh Kumar Yadav, Shashi Mathur

Abstract:

In-situ remediation is a technique which can remediate either surface or groundwater at the site of contamination. In the present study, simulation optimization approach has been used to develop management strategy for remediating LNAPL (Light Non-Aqueous Phase Liquid) contaminated aquifers. Benzene, toluene, ethyl benzene and xylene are the main component of LNAPL contaminant. Collectively, these contaminants are known as BTEX. In in-situ bioremediation process, a set of injection and extraction wells are installed. Injection wells supply oxygen and other nutrient which convert BTEX into carbon dioxide and water with the help of indigenous soil bacteria. On the other hand, extraction wells check the movement of plume along downstream. In this study, optimal design of the system has been done using PSO (Particle Swarm Optimization) algorithm. A comprehensive management strategy for pumping of injection and extraction wells has been done to attain a maximum allowable concentration of 5 ppm and 4.5 ppm. The management strategy comprises determination of pumping rates, the total pumping volume and the total running cost incurred for each potential injection and extraction well. The results indicate a high pumping rate for injection wells during the initial management period since it facilitates the availability of oxygen and other nutrients necessary for biodegradation, however it is low during the third year on account of sufficient oxygen availability. This is because the contaminant is assumed to have biodegraded by the end of the third year when the concentration drops to a permissible level.

Keywords: groundwater, in-situ bioremediation, light non-aqueous phase liquid, BTEX, particle swarm optimization

Procedia PDF Downloads 409