Search results for: text localization and extraction.

Authors: Rajender Singh Chillar, Barjesh Kochar

Abstract:

All Text processing systems allow their users to search a pattern of string from a given text. String matching is fundamental to database and text processing applications. Every text editor must contain a mechanism to search the current document for arbitrary strings. Spelling checkers scan an input text for words in the dictionary and reject any strings that do not match. We store our information in data bases so that later on we can retrieve the same and this retrieval can be done by using various string matching algorithms. This paper is describing a new string matching algorithm for various applications. A new algorithm has been designed with the help of Rabin Karp Matcher, to improve string matching process.

Keywords: Algorithm, Complexity, Matching-patterns, Pattern, Rabin-Karp, String, text-processing.

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Authors: Ágoston Winkler, Sándor Juhász

Abstract:

The localization of software products is essential for reaching the users of the international market. An important task for this is the translation of the user interface into local national languages. As graphical interfaces are usually optimized for the size of the texts in the original language, after the translation certain user controls (e.g. text labels and buttons in dialogs) may grow in such a manner that they slip above each other. This not only causes an unpleasant appearance but also makes the use of the program more difficult (or even impossible) which implies that the arrangement of the controls must be corrected subsequently. The correction should preserve the original structure of the interface (e.g. the relation of logically coherent controls), furthermore, it is important to keep the nicely proportioned design: the formation of large empty areas should be avoided. This paper describes an algorithm that automatically rearranges the controls of a graphical user interface based on the principles above. The algorithm has been implemented and integrated into a translation support system and reached results pleasant for the human eye in most test cases.

Keywords: Graphical user interface, GUI, natural languages, software localization, translation support systems.

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Authors: Xu Zhao

Abstract:

Text categorization techniques are widely used to many Information Retrieval (IR) applications. In this paper, we proposed a simple but efficient method that can automatically find the relationship between any pair of terms and documents, also an indexing matrix is established for text categorization. We call this method Indexing Matrix Categorization Machine (IMCM). Several experiments are conducted to show the efficiency and robust of our algorithm.

Keywords: Text categorization, Sub-space learning, Latent Semantic Space

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Authors: Azam Marjani, Saeed Shirazian

Abstract:

In this study is presented a general methodology to predict the performance of a continuous near-critical fluid extraction process to remove compounds from aqueous solutions using hollow fiber membrane contactors. A comprehensive 2D mathematical model was developed to study Porocritical extraction process. The system studied in this work is a membrane based extractor of ethanol and acetone from aqueous solutions using near-critical CO2. Predictions of extraction percentages obtained by simulations have been compared to the experimental values reported by Bothun et al. [5]. Simulations of extraction percentage of ethanol and acetone show an average difference of 9.3% and 6.5% with the experimental data, respectively. More accurate predictions of the extraction of acetone could be explained by a better estimation of the transport properties in the aqueous phase that controls the extraction of this solute.

Keywords: Solvent extraction, Membrane, Mass transfer, Densegas, Modeling

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Authors: Tudor Barbu

Abstract:

We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.

Keywords: Text-independent speaker recognition, mel cepstral analysis, speech feature vector, Hausdorff-based metric, supervised classification.

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Authors: Zhila Safari, Ali Ashrafizadeh, Najaf Hedayat

Abstract:

Thermodynamics characterization Sesame oil extraction by Acetone, Hexane and Benzene has been evaluated. The 120 hours experimental Data were described by a simple mathematical model. According to the simulation results and the essential criteria, Acetone is superior to other solvents but under certain conditions where oil extraction takes place Hexane is superior catalyst.

Keywords: Liquid-solid extraction, seed oil, ThermodynamicStudy.

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Authors: Yi Xu, Zexiang Li

Abstract:

In inspection and workpiece localization, sampling point data is an important issue. Since the devices for sampling only sample discrete points, not the completely surface, sampling size and location of the points will be taken into consideration. In this paper a method is presented for determining the sampled points size and location for achieving efficient sampling. Firstly, uncertainty analysis of the localization parameters is investigated. A localization uncertainty model is developed to predict the uncertainty of the localization process. Using this model the minimum size of the sampled points is predicted. Secondly, based on the algebra theory an eigenvalue-optimal optimization is proposed. Then a freeform surface is used in the simulation. The proposed optimization is implemented. The simulation result shows its effectivity.

Keywords: eigenvalue-optimal optimization, freeform surface inspection, sampling size and location, sampled points.

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Authors: Omid Sojodishijani, Saeed Ebrahimijam, Vahid Rostami

Abstract:

This paper presents an optimized algorithm for robot localization which increases the correctness and accuracy of the estimating position of mobile robot to more than 150% of the past methods [1] in the uncertain and noisy environment. In this method the odometry and vision sensors are combined by an adapted well-known discrete kalman filter [2]. This technique also decreased the computation process of the algorithm by DKF simple implementation. The experimental trial of the algorithm is performed on the robocup middle size soccer robot; the system can be used in more general environments.

Keywords: Discrete Kalman filter, odometry sensor, omnidirectional vision sensor, Robot Localization.

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Authors: Dennis L. Owuor, Okuthe P. Kogeda, Johnson I. Agbinya

Abstract:

Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.

Keywords: Indoor localization, waterfall, digital forensics, tracking and cloud.

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Authors: Jonghyun Park, Toan Nguyen Dinh, Gueesang Lee

Abstract:

In this paper, we present a novel approach to accurately detect text regions including shop name in signboard images with complex background for mobile system applications. The proposed method is based on the combination of text detection using edge profile and region segmentation using fuzzy c-means method. In the first step, we perform an elaborate canny edge operator to extract all possible object edges. Then, edge profile analysis with vertical and horizontal direction is performed on these edge pixels to detect potential text region existing shop name in a signboard. The edge profile and geometrical characteristics of each object contour are carefully examined to construct candidate text regions and classify the main text region from background. Finally, the fuzzy c-means algorithm is performed to segment and detected binarize text region. Experimental results show that our proposed method is robust in text detection with respect to different character size and color and can provide reliable text binarization result.

Keywords: Text detection, edge profile, signboard image, fuzzy clustering.

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Authors: E. Danso-Boateng

Abstract:

The effects of enzyme action and heat pretreatment on oil extraction yield from sunflower kernels were analysed using hexane extraction with Soxhlet, and aqueous extraction with incubator shaker. Ground kernels of raw and heat treated kernels, each with and without Viscozyme treatment were used. Microscopic images of the kernels were taken to analyse the visible effects of each treatment on the cotyledon cell structure of the kernels. Heat pretreated kernels before both extraction processes produced enhanced oil extraction yields than the control, with steam explosion the most efficient. In hexane extraction, applying a combination of steam explosion and Viscozyme treatments to the kernels before the extraction gave the maximum oil extractable in 1 hour; while for aqueous extraction, raw kernels treated with Viscozyme gave the highest oil extraction yield. Remarkable cotyledon cell disruption was evident in kernels treated with Viscozyme; whereas steam explosion and conventional heat treated kernels had similar effects.

Keywords: Enzyme-assisted aqueous and hexane extraction, heatpretreatment, sunflower cotyledon structure, sunflower oil extraction

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Authors: Imran Sarwar Bajwa

Abstract:

Internet is one of the major sources of information for the person belonging to almost all the fields of life. Major language that is used to publish information on internet is language. This thing becomes a problem in a country like Pakistan, where Urdu is the national language. Only 10% of Pakistan mass can understand English. The reason is millions of people are deprived of precious information available on internet. This paper presents a system for translation from English to Urdu. A module LESSA is used that uses a rule based algorithm to read the input text in English language, understand it and translate it into Urdu language. The designed approach was further incorporated to translate the complete website from English language o Urdu language. An option appears in the browser to translate the webpage in a new window. The designed system will help the millions of users of internet to get benefit of the internet and approach the latest information and knowledge posted daily on internet.

Keywords: Natural Language Translation, Text Understanding, Knowledge extraction, Text Processing

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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: Hany Mahgoub, Dietmar Rösner, Nabil Ismail, Fawzy Torkey

Abstract:

This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. In this work, the EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The main contributions of the technique are that it integrates XML technology with Information Retrieval scheme (TFIDF) (for keyword/feature selection that automatically selects the most discriminative keywords for use in association rules generation) and use Data Mining technique for association rules discovery. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), Association Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on WebPages news documents related to the outbreak of the bird flu disease. The extracted association rules contain important features and describe the informative news included in the documents collection. The performance of the EART system compared with another system that uses the Apriori algorithm throughout the execution time and evaluating extracted association rules.

Keywords: Text mining, data mining, association rule mining

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Authors: Nhu Van NGUYEN, Jean-Marc OGIER, Salvatore TABBONE, Alain BOUCHER

Abstract:

The state-of-the-art Bag of Words model in Content- Based Image Retrieval has been used for years but the relevance feedback strategies for this model are not fully investigated. Inspired from text retrieval, the Bag of Words model has the ability to use the wealth of knowledge and practices available in text retrieval. We study and experiment the relevance feedback model in text retrieval for adapting it to image retrieval. The experiments show that the techniques from text retrieval give good results for image retrieval and that further improvements is possible.

Keywords: Relevance feedback, bag of words model, probabilistic model, vector space model, image retrieval

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Authors: Marcin Ciura, Damian Grund, S

Abstract:

This paper describes a system, in which various methods of text summarizing can be adapted to Polish. A structure of the system is presented. A modular construction of the system and access to the system via the Internet are signaled.

Keywords: Automatic summary generation, linguistic analysis, text generation.

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Authors: M. F. Zaiyadi, B. Baharudin

Abstract:

Text document categorization involves large amount of data or features. The high dimensionality of features is a troublesome and can affect the performance of the classification. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the performance. There were many approaches has been implemented by various researchers to overcome this problem. This paper proposed a novel hybrid approach for feature selection in text document categorization based on Ant Colony Optimization (ACO) and Information Gain (IG). We also presented state-of-the-art algorithms by several other researchers.

Keywords: Ant colony optimization, feature selection, information gain, text categorization, text representation.

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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: Abhijit Mitra, C. Ardil

Abstract:

We investigate sonic cues for binaural sound localization within classrooms and present a structural model for the same. Two of the primary cues for localization, interaural time difference (ITD) and interaural level difference (ILD) created between the two ears by sounds from a particular point in space, are used. Although these cues do not lend any information about the elevation of a sound source, the torso, head, and outer ear carry out elevation dependent spectral filtering of sounds before they reach the inner ear. This effect is commonly captured in head related transfer function (HRTF) which aids in resolving the ambiguity from the ITDs and ILDs alone and helps localize sounds in free space. The proposed structural model of HRTF produces well controlled horizontal as well as vertical effects. The implemented HRTF is a signal processing model which tries to mimic the physical effects of the sounds interacting with different parts of the body. The effectiveness of the method is tested by synthesizing spatial audio, in MATLAB, for use in listening tests with human subjects and is found to yield satisfactory results in comparison with existing models.

Keywords: Auditory localization, Binaural sound, Head related impulse response, Head related transfer function, Interaural level difference, Interaural time difference, Localization cues.

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Authors: Diego Felix, Eugene Hyun, Michael McGuire, Mihai Sima

Abstract:

Terminal localization for indoor Wireless Local Area Networks (WLANs) is critical for the deployment of location-aware computing inside of buildings. A major challenge is obtaining high localization accuracy in presence of fluctuations of the received signal strength (RSS) measurements caused by multipath fading. This paper focuses on reducing the effect of the distance-varying noise by spatial filtering of the measured RSS. Two different survey point geometries are tested with the noise reduction technique: survey points arranged in sets of clusters and survey points uniformly distributed over the network area. The results show that the location accuracy improves by 16% when the filter is used and by 18% when the filter is applied to a clustered survey set as opposed to a straight-line survey set. The estimated locations are within 2 m of the true location, which indicates that clustering the survey points provides better localization accuracy due to superior noise removal.

Keywords: Position measurement, Wireless LAN, Radio navigation, Filtering

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Authors: Z. Shaaban

Abstract:

This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate.

Keywords: Neural Networks, character recognition, feature extraction, multiple networks, Arabic text.

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Authors: Lu Zhang, Chunping Li, Jun Liu, Hui Wang

Abstract:

Text similarity measurement is a fundamental issue in many textual applications such as document clustering, classification, summarization and question answering. However, prevailing approaches based on Vector Space Model (VSM) more or less suffer from the limitation of Bag of Words (BOW), which ignores the semantic relationship among words. Enriching document representation with background knowledge from Wikipedia is proven to be an effective way to solve this problem, but most existing methods still cannot avoid similar flaws of BOW in a new vector space. In this paper, we propose a novel text similarity measurement which goes beyond VSM and can find semantic affinity between documents. Specifically, it is a unified graph model that exploits Wikipedia as background knowledge and synthesizes both document representation and similarity computation. The experimental results on two different datasets show that our approach significantly improves VSM-based methods in both text clustering and classification.

Keywords: Text classification, Text clustering, Text similarity, Wikipedia

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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: Ashok Kumar, Vinod Kumar

Abstract:

Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Keywords: localization, range free, received signal strength, link quality indicator, Mamdani fuzzy logic inference, Sugeno fuzzy logic inference.

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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: Meiling Yang, Shuguo Xie, Yilong Zhu

Abstract:

Nowadays, due to diverse electric products and complex electromagnetic environment, the localization and troubleshooting of the electromagnetic radiation source is urgent and necessary especially on the condition of far field. However, based on the existing DOA positioning method, the system or devices are complex, bulky and expensive. To address this issue, this paper proposes a single antenna radiation source localization method. A single antenna moves to form a virtual antenna array combined with DOA and MUSIC algorithm to position accurately, meanwhile reducing the cost and simplify the equipment. As shown in the results of simulations and experiments, the virtual antenna array DOA estimation modeling is correct and its positioning is credible.

Keywords: Virtual antenna array, DOA, localization, far field.

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Authors: G. Ramesh, S. Sundara Vadivelu

Abstract:

For several high speed networks, providing resilience against failures is an essential requirement. The main feature for designing next generation optical networks is protecting and restoring high capacity WDM networks from the failures. Quick detection, identification and restoration make networks more strong and consistent even though the failures cannot be avoided. Hence, it is necessary to develop fast, efficient and dependable fault localization or detection mechanisms. In this paper we propose a new fault localization algorithm for WDM networks which can identify the location of a failure on a failed lightpath. Our algorithm detects the failed connection and then attempts to reroute data stream through an alternate path. In addition to this, we develop an algorithm to analyze the information of the alarms generated by the components of an optical network, in the presence of a fault. It uses the alarm correlation in order to reduce the list of suspected components shown to the network operators. By our simulation results, we show that our proposed algorithms achieve less blocking probability and delay while getting higher throughput.

Keywords: Alarm correlation, blocking probability, delay, fault localization, WDM networks.

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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: Min Ah Kang, Sangbae Jeong, Minsoo Hahn

Abstract:

This paper presents the source extraction system which can extract only target signals with constraints on source localization in on-line systems. The proposed system is a kind of methods for enhancing a target signal and suppressing other interference signals. But, the performance of proposed system is superior to any other methods and the extraction of target source is comparatively complete. The method has a beamforming concept and uses an improved time-frequency (TF) mask-based BSS algorithm to separate a target signal from multiple noise sources. The target sources are assumed to be in front and test data was recorded in a reverberant room. The experimental results of the proposed method was evaluated by the PESQ score of real-recording sentences and showed a noticeable speech enhancement.

Keywords: Beam forming, Non-stationary noise reduction, Source separation, TF mask.

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