Search results for: Object Extraction

Authors: S. M. Ghoreishi, R. Gholami Shahrestani, S. H. Ghaziaskar

Abstract:

Subcritical water extraction was investigated as a novel and alternative technology in the food and pharmaceutical industry for the separation of Mannitol from olive leaves and its results was compared with those of Soxhlet extraction. The effects of temperature, pressure, and flow rate of water and also momentum and mass transfer dimensionless variables such as Reynolds and Peclet Numbers on extraction yield and equilibrium partition coefficient were investigated. The 30-110 bars, 60-150°C, and flow rates of 0.2-2 mL/min were the water operating conditions. The results revealed that the highest Mannitol yield was obtained at 100°C and 50 bars. However, extraction of Mannitol was not influenced by the variations of flow rate. The mathematical modeling of experimental measurements was also investigated and the model is capable of predicting the experimental measurements very well. In addition, the results indicated higher extraction yield for the subcritical water extraction in contrast to Soxhlet method.

Keywords: Extraction, Mannitol, Modeling, Olive leaves, Soxhlet extraction, Subcritical water.

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Authors: Abdulsalam A. Al-Sudairi

Abstract:

Object-oriented simulation is considered one of the most sophisticated techniques that has been widely used in planning, designing, executing and maintaining construction projects. This technique enables the modeler to focus on objects which is extremely important for thorough understanding of a system. Thus, identifying an object is an essential point of building a successful simulation model. In a maintenance process an object is a maintenance work order (MWO). This study demonstrates a maintenance simulation model for the building maintenance division of Saudi Consolidated Electric Company (SCECO) in Dammam, Saudi Arabia. The model focused on both types of maintenance processes namely: (1) preventive maintenance (PM) and (2) corrective maintenance (CM). It is apparent from the findings that object-oriented simulation is a good diagnostic and experimental tool. This is because problems, limitations, bottlenecks and so forth are easily identified. These features are very difficult to obtain when using other tools.

Keywords: Object oriented, simulation, maintenance, process, work orders

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Authors: S. I. Abu Alasal, M. M. Esbeih, E. R. Fayyad, R. S. Gharaibeh, M. Z. Ali, A. A. Freewan, M. M. Jamhawi

Abstract:

This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Keywords: Meshes, Point Clouds, Surface Reconstruction Protocols, 3D Reconstruction.

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Authors: Sami Hidouri, Taoufik Aguili

Abstract:

We consider fast and accurate solutions of scattering problems by large perfectly conducting objects (PEC) formulated by an optimization of the Method of Auxiliary Sources (MAS). We present various techniques used to reduce the total computational cost of the scattering problem. The first technique is based on replacing the object by an array of finite number of small (PEC) object with the same shape. The second solution reduces the problem on considering only the half of the object.These t

Keywords: Method of Auxiliary Sources, Scattering, large object, RCS, computational resources.

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Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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Authors: Jehad Al Dallal

Abstract:

Class cohesion is an important object-oriented software quality attribute. It indicates how much the members in a class are related. Assessing the class cohesion and improving the class quality accordingly during the object-oriented design phase allows for cheaper management of the later phases. In this paper, the notion of distance between pairs of methods and pairs of attribute types in a class is introduced and used as a basis for introducing a novel class cohesion metric. The metric considers the methodmethod, attribute-attribute, and attribute-method direct interactions. It is shown that the metric gives more sensitive values than other well-known design-based class cohesion metrics.

Keywords: Object-oriented software quality, object-orienteddesign, class cohesion.

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Authors: Ghulam Mueen-ud-Din, Salim-ur-Rehman, Faqir M. Anjum, Haq Nawaz, Mian A. Murtaza

Abstract:

The effect of wheat flour extraction rates on flour composition, farinographic characteristics and the quality of sourdough naans was investigated. The results indicated that by increasing the extraction rate, the amount of protein, fiber, fat and ash increased, whereas moisture content decreased. Farinographic characteristic like water absorption and dough development time increased with an increase in flour extraction rate but the dough stabilities and tolerance indices were reduced with an increase in flour extraction rates. Titratable acidity for both sourdough and sourdough naans also increased along with flour extraction rate. The study showed that overall quality of sourdough naans were affected by both flour extraction rate and starter culture used. Sensory analysis of sourdough naans revealed that desirable extraction rate for sourdough naan was 76%.

Keywords: Extraction rates, Farinographic characteristics, Flour composition, Sourdough naans, Wheat flour.

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Authors: D. R. Awang Rambli, S. Sulaiman, M.Y. Nayan, A.R. Asoruddin

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Existing image-based virtual reality applications allow users to view image-based 3D virtual environment in a more interactive manner. User could “walkthrough"; looks left, right, up and down and even zoom into objects in these virtual worlds of images. However what the user sees during a “zoom in" is just a close-up view of the same image which was taken from a distant. Thus, this does not give the user an accurate view of the object from the actual distance. In this paper, a simple technique for zooming in an object in a virtual scene is presented. The technique is based on the 'hotspot' concept in existing application. Instead of navigation between two different locations, the hotspots are used to focus into an object in the scene. For each object, several hotspots are created. A different picture is taken for each hotspot. Each consecutive hotspot created will take the user closer to the object. This will provide the user with a correct of view of the object based on his proximity to the object. Implementation issues and the relevance of this technique in potential application areas are highlighted.

Keywords: Hotspots, image-based VR, camera zooms, virtualreality.

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Authors: Ratchadaporn Oonsivilai, Jutarat Manatwiyangkool, Anant Oonsivilai

Abstract:

Theoptimal extraction condition of dried Phaseolus vulgaris powderwas studied. The three independent variables are raw material concentration, shaking and centrifugaltime. The dependent variables are both yield percentage of crude extract and alphaamylase enzyme inhibition activity. The experimental design was based on box-behnkendesign. Highest yield percentage of crude extract could get from extraction condition at concentration of 1, 0,1, concentration of 0.15 M ,extraction time for 2hour, and separationtime for60 min. Moreover, the crude extract with highest alpha-amylase enzyme inhibition activityoccurred by extraction condition at concentration of 0.10 M, extraction time for 2 min, and separation time for 45 min

Keywords: Extraction time, Optimal condition, Alpha-amylase enzymeinhibition activity

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Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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Authors: Nang Thwe Thwe Oo

Abstract:

Traditional object segmentation methods are time consuming and computationally difficult. In this paper, onedimensional object detection along the secant lines is applied. Statistical features of texture images are computed for the recognition process. Example matrices of these features and formulae for calculation of similarities between two feature patterns are expressed. And experiments are also carried out using these features.

Keywords: 1-D object segmentation, secant lines, objectoccurrence(frequency) matrix, contiguity matrix, statistical features.

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Authors: R. Manaffar, R. Maleki, S. Zare, N. Agh, S. Soltanian, B. Sehatnia, P. Sorgeloos, P. Bossier, G. Van Stappen

Abstract:

Artemia is one of the most conspicuous invertebrates associated with aquaculture. It can be considered as a model organism, offering numerous advantages for comprehensive and multidisciplinary studies using morphologic or molecular methods. Since DNA extraction is an important step of any molecular experiment, a new and a rapid method of DNA extraction from adult Artemia was described in this study. Besides, the efficiency of this technique was compared with two widely used alternative techniques, namely Chelex® 100 resin and SDS-chloroform methods. Data analysis revealed that the new method is the easiest and the most cost effective method among the other methods which allows a quick and efficient extraction of DNA from the adult animal.

Keywords: APD, Artemia, DNA extraction, Molecularexperiments

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Authors: Doaa Hegazy, Joachim Denzler

Abstract:

SoftBoost is a recently presented boosting algorithm, which trades off the size of achieved classification margin and generalization performance. This paper presents a performance evaluation of SoftBoost algorithm on the generic object recognition problem. An appearance-based generic object recognition model is used. The evaluation experiments are performed using a difficult object recognition benchmark. An assessment with respect to different degrees of label noise as well as a comparison to the well known AdaBoost algorithm is performed. The obtained results reveal that SoftBoost is encouraged to be used in cases when the training data is known to have a high degree of noise. Otherwise, using Adaboost can achieve better performance.

Keywords: SoftBoost algorithm, AdaBoost algorithm, Generic object recognition.

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Authors: Nuttawan Yoswathana, M. N. Eshtiaghi

Abstract:

Rambutan is a tropical fruit which peel possesses antioxidant properties. This work was conducted to optimize extraction conditions of phenolic compounds from rambutan peel. Response surface methodology (RSM) was adopted to optimize subcritical water extraction (SWE) on temperature, extraction time and percent solvent mixture. The results demonstrated that the optimum conditions for SWE were as follows: temperature 160°C, extraction time 20min. and concentration of 50% ethanol. Comparison of the phenolic compounds from the rambutan peels in maceration 6h, soxhlet 4h, and SWE 20min., it indicated that total phenolic content (using Folin-Ciocalteu-s phenol reagent) was 26.42, 70.29, and 172.47mg of tannic acid equivalent (TAE) per g dry rambutan peel, respectively. The comparative study concluded that SWE was a promising technique for phenolic compounds extraction from rambutan peel, due to much more two times of conventional techniques and shorter extraction times.

Keywords: Subcritical water extraction, Rambutan peel, phenolic compounds, response surface methodology

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Authors: Lekbir Adel, Alloui-Lombarkia Ourida, Mekentichi Sihem, Noui Yassine, Baississe Salima

Abstract:

The objective of this study was to optimize the extraction conditions for phenolic compounds, total flavonoids, and antioxidant activity from Deglet-Nour variety. The extraction of active components from natural sources depends on different factors. The knowledge of the effects of different extraction parameters is useful for the optimization of the process, as well for the ability to predict the extraction yield. The effects of extraction variables, namely types of solvent (methanol, ethanol and acetone) and extraction time (1h, 6h, 12h and 24h) on phenolics extraction yield were evaluated. It has been shown that the time of extraction and types of solvent have a statistically significant influence on the extraction of phenolic compounds from Deglet-Nour variety. The optimised conditions yielded values of 80.19 ± 6.37 mg GAE/100 g FW for TPC, 2.34 ± 0.27 mg QE/100 g FW for TFC and 90.20 ± 1.29% for antioxidant activity were methanol solvent and 6 hours of time. According to the results obtained in this study, Deglet-Nour variety can be considered as a natural source of phenolic compounds with good antioxidant capacity.

Keywords: Deglet-Nour variety, Date palm Fruit, Phenolic compounds, Total flavonoids, Antioxidant activity, Extraction, Optimization.

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Authors: Yuan J. Lui

Abstract:

Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.

Keywords: classification, keyphrase extraction, machine learning, summarization

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: Deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator.

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Authors: Chen-Chien Hsu, Guo-Tang Dai

Abstract:

This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

Keywords: multiple object tracking, particle swarm optimization, gray-level histogram, image

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Authors: S. Hellam, Y. Oulahrir, F. El Mounchid, A. Sadiq, S. Mbarki

Abstract:

In this paper, we propose a new method for threedimensional object indexing based on D.A.M.C-S.H.C descriptor (Direct and Analytical Method for Calculating the Spherical Harmonics Coefficients). For this end, we propose a direct calculation of the coefficients of spherical harmonics with perfect precision. The aims of the method are to minimize, the processing time on the 3D objects database and the searching time of similar objects to a request object. Firstly we start by defining the new descriptor using a new division of 3-D object in a sphere. Then we define a new distance which will be tested and prove his efficiency in the search for similar objects in the database in which we have objects with very various and important size.

Keywords: 3D Object indexing, 3D shape descriptor, spherical harmonic, 3D Object similarity.

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Authors: Delowar Hossain, Genci Capi

Abstract:

This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: Deep learning, genetic algorithm, object recognition, robot grasping.

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Authors: Muhammad Hazwan H., Azlina M.F., Hasfalina C.M., Zurina Z.A., Hishamuddin J

Abstract:

Gaharu that produced by Aquilaria spp. is classified as one of the most valuable forest products traded internationally as it is very resinous, fragrant and highly valuable heartwood. Gaharu has been widely used in aromatheraphy, medicine, perfume and religious practices. This work aimed to determine the factors affecting solid liquid extraction of gaharu oil using hexane as solvent under experimental condition. The kinetics of extraction was assumed and verified based on a second-order mechanism. The effect of three main factors, which were temperature, reaction time and solvent to solid ratio were investigated to achieve maximum oil yield. The optimum condition were found at temperature 65°C, 9 hours reaction time and solvent to solid ratio of 12:1 with 14.5% oil yield. The kinetics experimental data agrees and well fitted with the second order extraction model. The initial extraction rate (h) was 0.0115 gmL-1min-1; the extraction capacity (Cs) was 1.282gmL-1; the second order extraction constant (k) was 0.007 mLg-1min-1 and coefficient of determination, R2 was 0.945.

Keywords: Gaharu, solid liquid extraction, optimization, kinetics.

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Authors: A. Brinda Lakshmi, J. Lakshmi Priya

Abstract:

Cantaloupes (muskmelon and watermelon) contain biologically active molecules such as carotenoids which are natural pigments used as food colorants and afford health benefits. ß-carotene is the major source of carotenoids present in muskmelon and watermelon shell. Carotenoids were extracted using Microwave assisted extraction (MAE) and Ultrasound assisted extraction (UAE) utilising organic lipophilic solvents such as acetone, methanol, and hexane. Extraction conditions feed-solvent ratio, microwave power, ultrasound frequency, temperature and particle size were varied and optimized. It was found that the yield of carotenoids was higher using UAE than MAE, and muskmelon had the highest yield of carotenoids when was ethanol used as a solvent for 0.5 mm particle size.

Keywords: Carotenoids, extraction, muskmelon shell, watermelon shell.

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Authors: George Karkavitsas, Maria Rangoussi

Abstract:

We present a genetic algorithm application to the problem of object registration (i.e., object detection, localization and recognition) in a class of medical images containing various types of blood cells. The genetic algorithm approach taken here is seen to be most appropriate for this type of image, due to the characteristics of the objects. Successful cell registration results on real life microscope images of blood cells show the potential of the proposed approach.

Keywords: Genetic algorithms, object registration, pattern recognition, blood cell microscope images.

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R color component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: Chromaticity, Feature Extraction, Remote Sensing, Spectral library, Water Index.

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Authors: Mussarat Abdullah, Fazal Wahab

Abstract:

Data hiding into text documents itself involves pretty complexities due to the nature of text documents. A robust text watermarking scheme targeting an object based environment is presented in this research. The heart of the proposed solution describes the concept of watermarking an object based text document where each and every text string is entertained as a separate object having its own set of properties. Taking advantage of the z-ordering of objects watermark is applied with the z-axis letting zero fidelity disturbances to the text. Watermark sequence of bits generated against user key is hashed with selected properties of given document, to determine the bit sequence to embed. Bits are embedded along z-axis and the document has no fidelity issues when printed, scanned or photocopied.

Keywords: Digital Watermarking, Object Based Environment, Watermark, z-ordering.

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Authors: S. Mousavian, D. Ashouri, F. Mousavian, V. Nikkhah Rashidabad, N. Ghazinia

Abstract:

PH, temperature and time of extraction of each stage,  agitation speed and delay time between stages effect on efficiency of  zinc extraction from concentrate. In this research, efficiency of zinc  extraction was predicted as a function of mentioned variable by  artificial neural networks (ANN). ANN with different layer was  employed and the result show that the networks with 8 neurons in  hidden layer has good agreement with experimental data.

 

Keywords: Zinc extraction, Efficiency, Neural networks, Operating condition.

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Authors: M A Hannan, A. Hussain, S. A. Samad, K. A. Ishak, A. Mohamed

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This paper presents a general trainable framework for fast and robust upright human face and non-human object detection and verification in static images. To enhance the performance of the detection process, the technique we develop is based on the combination of fast neural network (FNN) and classical neural network (CNN). In FNN, a useful correlation is exploited to sustain high level of detection accuracy between input image and the weight of the hidden neurons. This is to enable the use of Fourier transform that significantly speed up the time detection. The combination of CNN is responsible to verify the face region. A bootstrap algorithm is used to collect non human object, which adds the false detection to the training process of the human and non-human object. Experimental results on test images with both simple and complex background demonstrate that the proposed method has obtained high detection rate and low false positive rate in detecting both human face and non-human object.

Keywords: Algorithm, detection of human and non-human object, FNN, CNN, Image training.

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Authors: Miika Toivanen, Jouko Lampinen

Abstract:

This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.

Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.

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Authors: Tafere Aga Bullo

Abstract:

The peels of avocados, like other fruit peels, are commonly discarded, not knowing their potential use. This study carried out to extract oils from avocado peels and to characterize the extracted oils with the view to determine their suitability for consumption and other uses. Soxhlet apparatus was used for extraction using n-hexane as a solvent, which is chosen based on the fact that it has a very low value of toxicity and a great extraction rate. The proximate analysis and physicochemical properties of the extracted oil were investigated. The percentage yield of oil extracted from the peel was found to be 40.6%. From this study, the optimum operating conditions for the extraction of oil from avocado peel oil for the particle size of 2.6 mm, solvent type N-hexane and extraction time of 3-5 hr. were considered. A general factorial design was applied to investigate the effect of process variables on oil yield. Maximum oil yield of 40.6% was obtained at an extraction time of 5 hr. The extracted avocado peel oil can be widely used in pharmaceutical and energy production.

Keywords: Avocado fruits, avocado oil, avocado peel oil, characterization.

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Authors: Dewi S. Fardhyanti, Panut Mulyono, Wahyudi B. Sediawan, Muslikhin Hidayat

Abstract:

Coal tar is a liquid by-product of the process of coal gasification and carbonation. This liquid oil mixture contains various kinds of useful compounds such as phenol, o-cresol, and p-cresol. These compounds are widely used as raw material for insecticides, dyes, medicines, perfumes, coloring matters, and many others. This research needed to be done that given the optimum conditions for the separation of phenol, o-cresol, and p-cresol from the coal tar by solvent extraction process. The aim of the present work was to study the effect of two kinds of aqueous were used as solvents: methanol and acetone solutions, the effect of temperature (298, 306, and 313K) and mixing (30, 35, and 40rpm) for the separation of phenol, o-cresol, and p-cresol from coal tar by solvent extraction. Results indicated that phenol, o-cresol, and p-cresol in coal tar were selectivity extracted into the solvent phase and these components could be separated by solvent extraction. The aqueous solution of methanol, mass ratio of solvent to feed, Eo/Ro=1, extraction temperature 306K and mixing 35 rpm were the most efficient for extraction of phenol, o-cresol, and p-cresol from coal tar.

Keywords: Coal tar, Distribution coefficient, Extraction, Yield.

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