Search results for: sequential extraction

Authors: Srestha Chaturabul, Wanchalerm Srirachat, Thanaporn Wannachod, Prakorn Ramakul, Ura Pancharoen, Soorathep Kheawhom

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The separation of mercury(II) from petroleum-produced water from the Gulf of Thailand was carried out using a hollow fiber supported liquid membrane system (HFSLM). Optimum parameters for feed pretreatment were 0.2 M HCl, 4% (v/v) Aliquat 336 for extractant and 0.1 M thiourea for stripping solution. The best percentage obtained for extraction was 99.73% and for recovery 90.11%, respectively. The overall separation efficiency noted was 94.92% taking account of both extraction and recovery prospects. The model for this separation developed along a combined flux principle i.e. convection–diffusion–kinetic. The results showed excellent agreement with theoretical data at an average standard deviation of 1.5% and 1.8%, respectively.

Keywords: separation, mercury(ii), petroleum produced water, hollow fiber, liquid membrane

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Authors: Hanlin Liu, Hua Li, Yintan AI

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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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Authors: Patricia Jiménez, Rafael Corchuelo

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Nowadays the World Wide Web is the most popular source of information that relies on billions of on-line documents. Web mining is used to crawl through these documents, collect the information of interest and process it by applying data mining tools in order to use the gathered information in the best interest of a business, what enables companies to promote theirs. Unfortunately, it is not easy to extract the information a web site provides automatically when it lacks an API that allows to transform the user-friendly data provided in web documents into a structured format that is machine-readable. Rule-based information extractors are the tools intended to extract the information of interest automatically and offer it in a structured format that allow mining tools to process it. However, the performance of an information extractor strongly depends on the search heuristic employed since bad choices regarding how to learn a rule may easily result in loss of effectiveness and/or efficiency. Improving search heuristics regarding efficiency is of uttermost importance in the field of Web Information Extraction since typical datasets are very large. In this paper, we employ an information extractor based on a classical top-down algorithm that uses the so-called Information Gain heuristic introduced by Quinlan and Cameron-Jones. Unfortunately, the Information Gain relies on some well-known problems so we analyse an intuitive alternative, Termini, that is clearly more efficient; we also analyse other proposals in the literature and conclude that none of them outperforms the previous alternative.

Keywords: information extraction, search heuristics, semi-structured documents, web mining.

Procedia PDF Downloads 311

Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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Authors: Tamrat Tesfaye, Tilahun Seyoum, K. Shabaridharan

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The objective of this paper was to determine the effect of NaOH concentration, soaking time, soaking temperature and their interaction on percentage yield of fibre extract using Response Surface Methodology (RSM). A Box-Behnken design was employed to optimize the extraction process of cellulosic fibre from sugar cane by-product bagasse using low alkaline extraction technique. The quadratic model with the optimal technological conditions resulted in a maximum fibre yield of 56.80% at 0.55N NaOH concentration, 4 h steeping time and 60ᵒC soaking temperature. Among the independent variables concentration was found to be the most significant (P < 0.005) variable and the interaction effect of concentration and soaking time leads to securing the optimized processes.

Keywords: sugarcane bagasse, low alkaline, Box-Behnken, fibre

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Authors: Zexin Lei, Timothy Langrish

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Lutein is a type of carotene believed to be beneficial to the eyes. This study aims to explore the possibility of using a closed cycle spray drying system to produce lutein. The system contains a spray dryer, a condenser, a heater, and a pressure seal. Hexane, ethanol, and isopropanol will be used as organic solvents to compare the extraction effects. Several physical and chemical methods of cell disruption will be compared. By continuously sweeping the system with nitrogen, the oxygen content will be controlled below 2%, reducing the concentration of organic solvent below the explosion limit and preventing lutein from being oxidized. Lutein powder will be recovered in the collection device. The volatile organic solvent will be cooled in the condenser and deposited in the bottom until it is discharged from the bottom of the condenser.

Keywords: closed cycle spray drying system, Chlorella vulgaris, organic solvent, solvent recovery

Procedia PDF Downloads 114

Authors: Yoshifumi Hino

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An infinitely repeated prisoner’s dilemma is a typical model that represents teamwork situation. If both players choose costly actions and contribute to the team, then both players are better off. However, each player has an incentive to choose a selfish action. We analyze the game under costly observation. Each player can observe the action of the opponent only when he pays an observation cost in that period. In reality, teamwork situations are often costly observation. Members of some teams sometimes work in distinct rooms, areas, or countries. In those cases, they have to spend their time and money to see other team members if they want to observe it. The costly observation assumption makes the cooperation difficult substantially because the equilibrium must satisfy the incentives not only on the action but also on the observational decision. Especially, it is the most difficult to cooperate each other when the stage-game is prisoner's dilemma because players have to communicate through only two actions. We examine whether or not players can cooperate each other in prisoner’s dilemma under costly observation. Specifically, we check whether symmetric Pareto efficient payoff vectors in repeated prisoner’s dilemma can be approximated by sequential equilibria or not (efficiency result). We show the efficiency result without any randomization device under certain circumstances. It means that players can cooperate with each other without any randomization device even if the observation is costly. Next, we assume that public randomization device is available, and then we show that any feasible and individual rational payoffs in prisoner’s dilemma can be approximated by sequential equilibria under a specific situation (folk theorem). It implies that players can achieve asymmetric teamwork like leadership situation when public randomization device is available.

Keywords: cost observation, efficiency, folk theorem, prisoner's dilemma, private monitoring, repeated games.

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Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

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Authors: Anne Mette Nyvad, Ken Ramshøj Christensen

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In the syntax literature, it has standardly been assumed that relative clauses and complement wh-clauses are islands for extraction in English, and that constraints on extraction from syntactic islands are universal. However, the Mainland Scandinavian languages has been known to provide counterexamples. Previous research on Danish has shown that neither relative clauses nor embedded questions are strong islands in Danish. Instead, extraction from this type of syntactic environment is degraded due to structural complexity and it interacts with nonstructural factors such as the frequency of occurrence of the matrix verb, the possibility of temporary misanalysis leading to semantic incongruity and exposure over time. We argue that these facts can be accounted for with parametric variation in the availability of CP-recursion, resulting in the patterns observed, as Danish would then “suspend” the ban on movement out of relative clauses and embedded questions. Given that Danish does not seem to adhere to allegedly universal syntactic constraints, such as the Complex NP Constraint and the Wh-Island Constraint, what happens in L2 English? We present results from a study investigating how native Danish speakers judge extractions from island structures in L2 English. Our findings suggest that Danes transfer their native language parameter setting when asked to judge island constructions in English. This is compatible with the Full Transfer Full Access Hypothesis, as the latter predicts that Danish would have difficulties resetting their [+/- CP-recursion] parameter in English because they are not exposed to negative evidence.

Keywords: syntax, islands, second language acquisition, danish

Procedia PDF Downloads 94

Authors: S. A. Jumare, A. O. Tijani, M. F. Siraj, B. V. Babatunde

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This research investigated the comparative analysis of oil extracted from cotton and watermelon seeds using solvent extraction process. Normal ethyl-ether was used as solvent in the extraction process. The AOAC method of Analysis was employed in the determination of the physiochemical properties of the oil. The chemical properties of the oil determined include the saponification value, free fatty acid, iodine value, peroxide value and acid value. The physical properties of the oil determined include specific gravity, refractive index, colour, odour, taste and pH. The value obtained for cottonseed oil are saponification value (187mgKOH/g), free fatty acid (5.64mgKOH/g), iodine value (95.2g/100), peroxide value (9.33meq/kg), acid value (11.22mg/KOH/g), pH value (4.62), refractive index (1.46), and specific gravity (0.9) respectively, it has a bland odour, a reddish brown colour and a mild taste. The values obtained for watermelon seed oil are saponification value (83.3mgKOH/g), free fatty acid (6.58mg/KOH/g), iodine value (122.6g/100), peroxide value (5.3meq/kg), acid value (3.74mgKOH/g), pH value (6.3), refractive index (1.47), and specific gravity (0.9) respectively, it has a nutty flavour, a golden yellow colour and a mild taste. From the result obtained, it shows that cottonseed oil has high acid value which shows the stability of the oil and its stability to rancidity. Consequently, watermelon seed oil is order wise.

Keywords: extraction, solvent, cotton seeds, watermelon seeds

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Authors: Saeid Rabiei Majd, Motahareh Alvandi, Bahareh Asefi

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Extraction of maximum natural resources is one of the common policies of governments, especially petroleum resources that have high economic and strategic value. The incentive to access and maintain profitable oil markets for governments or international oil companies, causing neglects them to pay attention to environmental principles and sustainable development, which in turn drives up environmental and climate change. Significant damage to the environment can cause severe damage to citizens and indigenous people, such as the compulsory evacuation of their zone due to contamination of water and air resources, destruction of animals and plants. Hawizeh Marshes is a common aquatic and environmental ecosystem along the Iran-Iraq border that also has oil resources. This marsh has been very rich in animal, vegetative, and oil resources. Since 1990, the political motives, the strategic importance of oil extraction, and the disregard for the environmental rights of the Iraqi and Iranian governments in the region have caused 90% of the marshes and forced migration of indigenous people. In this paper, we examine the environmental degradation factors resulting from the adoption of policies and practices of governments in this region based on the principles of environmental rights and sustainable development. Revision of the implementation of the government’s policies and natural resource utilization systems can prevent the spread of climate change, which is a serious international challenge today.

Keywords: climate change, indigenous rights, petroleum operation, sustainable development principles, sovereignty on resources

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Authors: Angelina Chiglintseva, Vladislav Shagapov

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We know from the geological data that quite sufficient gas reserves are concentrated in hydrates that occur on the Earth and on the ocean floor. Therefore, the development of these sources of energy and the storage of large reserves of gas hydrates is an acute global problem. An advanced technology for utilizing gas is to store it in a gas-hydrate state. Under natural conditions, storage facilities can be established, e.g., in underground reservoirs, where quite large volumes of gas can be conserved compared with reservoirs of pure gas. An analysis of the available experimental data of the kinetics and the mechanism of the gas-hydrate formation process shows the self-conservation effect that allows gas to be stored at negative temperatures and low values of pressures of up to several atmospheres. A theoretical model has been constructed for the gas-hydrate reservoir that represents a unique natural chemical reactor, and the principal possibility of the full extraction of gas from a hydrate due to the thermal reserves of the reservoirs themselves and the surrounding rocks has been analyzed. The influence exerted on the evolution of a gas hydrate reservoir by the reservoir thicknesses and the parameters that determine its initial state (a temperature, pressure, hydrate saturation) has been studied. It has been established that the shortest time of exploitation required by the reservoirs with a thickness of a few meters for the total hydrate decomposition is recorded in the cyclic regime when gas extraction alternated with the subsequent conservation of the gas hydrate deposit. The study was performed by a grant from the Russian Science Foundation (project No.15-11-20022).

Keywords: conservation, equilibrium state, gas hydrate reservoir, rocks

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Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

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The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: acoustic features, autonomous robots, feature extraction, terrain classification

Procedia PDF Downloads 339

Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: cloud storage, decision trees, diagnostic image, search, telemedicine

Procedia PDF Downloads 182

Authors: Dewi Selvia Fardhyanti, Astrilia Damayanti

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Coal tar is a liquid by-product of the process of coal gasification and carbonation, also in some industries such as steel, power plant, cement, and others. This liquid oil mixture contains various kinds of useful compounds such as aromatic compounds and phenolic compounds. These compounds are widely used as raw material for insecticides, dyes, medicines, perfumes, coloring matters, and many others. This research investigates thermodynamic modelling of liquid-liquid equilibria (LLE) in solvent extraction of o-Cresol from the coal tar. The equilibria are modeled by ternary components of Wohl, Van Laar, and Three-Suffix Margules models. The values of the parameters involved are obtained by curve-fitting to the experimental data. Based on the comparison between calculated and experimental data, it turns out that among the three models studied, the Three-Suffix Margules seems to be the best to predict the LLE of o-Cresol for those system.

Keywords: coal tar, o-Cresol, Wohl, Van Laar, three-suffix margules

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Authors: Seok Hong Min, Tae Kwon Ha

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With the increasing interest on Ti alloys, the extraction process of Ti from its typical ore, TiO₂, has long been and will be important issue. As an intermediate product for the production of pigment or titanium metal sponge, tetrachloride (TiCl₄) is produced by fluidized bed using high TiO₂ feedstock. The purity of TiCl₄ after chlorination is subjected to the quality of the titanium feedstock. Since the impurities in the TiCl₄ product are reported to final products, the purification process of the crude TiCl₄ is required. The purification process includes fractional distillation and chemical treatment, which depends on the nature of the impurities present and the required quality of the final product. In this study, thermodynamic analysis on the impurity effect in the chlorination process, which is the first step of extraction of Ti from TiO₂, has been conducted. All thermodynamic calculations were performed using the FactSage thermodynamical software.

Keywords: rutile, titanium, chlorination process, impurities, thermodynamic calculation, FactSage

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Authors: Nurlan Akhmetov, Abilmansur Yeshmuratov, Aliya Kurbanova, Gulnar Sugurbekova, Murat Baisariyev

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Extraction of the vanadium and nickel compounds is complex due to the high stability of porphyrin, nickel is catalytic poison which deactivates catalysis during the catalytic cracking of the oil, while vanadyl is abrasive and valuable metal. Thus, high concentration of the Ni and V in the crude oil makes their removal relevant. Two methods of the demetallization of crude oil were tested, therefore, the present research is conducted for comparative analysis of the deasphalting with organic solvents (cyclohexane, carbon tetrachloride, chloroform) and electrochemical method. Percentage of Ni extraction reached maximum of approximately 55% by using the electrochemical method in electrolysis cell, which was developed for this research and consists of three sections: oil and protonating agent (EtOH) solution between two conducting membranes which divides it from two capsules of 10% sulfuric acid and two graphite electrodes which cover all three parts in electrical circuit. Ions of metals pass through membranes and remain in acid solutions. The best result was obtained in 60 minutes with ethanol to oil ratio 25% to 75% respectively, current fits in to the range from 0.3A to 0.4A, voltage changed from 12.8V to 17.3V. Maximum efficiency of deasphalting, with cyclohexane as the solvent, in Soxhlet extractor was 66.4% for Ni and 51.2% for V. Thus, applying the voltammetry, ICP MS (Inductively coupled plasma mass spectrometry) and AAS (atomic absorption spectroscopy), these mentioned types of metal extraction methods were compared in this paper.

Keywords: electrochemistry, deasphalting of crude oil, demetallization of crude oil, petrolium engineering

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

Procedia PDF Downloads 186

Authors: Yu-Che Cheng, Min-Lih Chang, Ke-Hao Cheng, Chuan-Cheng Wang

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Taiwan is an island located along the southeastern coast of the Asian continent, located between Japan and the Philippines. It is surrounded by the sea on all sides. However, due to the presence of the Central Mountain Range, the rivers on the east and west coasts of Taiwan are relatively short. This geographical feature results in a phenomenon where, despite having rainfall that is 2.6 times the world average, 58.5% of the rainwater flows into the ocean. Moreover, approximately 80% of the annual rainfall occurs between May and October, leading to distinct wet and dry periods. To address these challenges, Taiwan relies on large reservoirs, storage ponds, and groundwater extraction for water resource allocation. It is necessary to construct water treatment facilities at suitable locations to provide the population with a stable and reliable water supply. In general, the construction of a new water treatment plant requires careful planning and evaluation. The process involves acquiring land and issuing contracts for construction in a sequential manner. With the increasing severity of global warming and climate change, there is a heightened risk of extreme hydrological events and severe water situations in the future. In cases of urgent water supply needs in a region, relying on traditional lengthy processes for constructing water treatment plants might not be sufficient to meet the urgent demand. Therefore, this study aims to explore the use of simplified water treatment procedures and the construction of rapid "temporary water treatment plants" to tackle the challenges posed by extreme climate conditions (such as a century-long drought) and situations where water treatment plant construction cannot keep up with the pace of water source development.

Keywords: temporary water treatment plant, emergency water supply, construction site groundwater, drought

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Authors: Issam Ben Jami

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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.

Keywords: feature matching, historical documents, pattern recognition, word spotting

Procedia PDF Downloads 249

Authors: Houda Oueriemmi, Petra Susan Kidd, Carmen Trasar-Cepeda, Beatriz Rodríguez-Garrido, Mohamed Moussa, Ángeles Prieto-Fernández, Mohamed Ouessar

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Organic amendments are generally used for improving the fertility of arid and semi-arid soils. However, the price of farmyard manure, the organic amendment typically applied to many arid and semi-arid soils has highly increased in the last years. To investigate at field scale whether cheap, highly available organic amendments, such as sewage sludge compost and municipal solid waste compost, may be acceptable as substitutes for farmyard manure is therefore of great interest. A field plots experiment was carried out to assess the effects of a single application of three organic amendments on soil fertility, distribution of trace elements and on barley yield. Municipal solid waste compost (MSWC), farmyard manure (FYM) and sewage sludge compost (SSC) were applied at rates of 0, 20, 40 and 60 t ha⁻¹, and barley was cultivated in two consecutive years. Plant samples and soils were collected for laboratory analyses after two consecutive harvests. Compared with unamended soil, the application of the three organic residues improved the fertility of the topsoil, showing a significant dose-dependent increase of TOC, N, P contents up to the highest dose of 60 t ha⁻¹ (0.74%, 0.06% and 40 mg kg⁻¹, respectively). The enhancement of soil nutrient status impacted positively on grain yield (up to 51%). The distribution of trace elements in the soil, analysed by a sequential extraction procedure, revealed that the MSWC increased the acid-extractable Co and Cu and reducible Ni, while SSC increased reducible Co and Ni and oxidisable Cu, relative to the control soil.

Keywords: municipal solid waste compost, sewage sludge compost, fertility, trace metals

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Authors: Arash Rafiei, Carroll Moore

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Leaching process as the first stage of hydrometallurgy is a multidisciplinary system including material properties, chemistry, reactor design, mechanics and fluid dynamics. Therefore, doing leaching system optimization by pure scientific methods need lots of times and expenses. In this work, a mixture of two titanium ores and one titanium slag are used for extracting titanium for leaching stage of TiO2 pigment production procedure. Optimum titanium extraction can be obtained from following strategies: i) Maximizing titanium extraction without selective digestion; and ii) Optimizing selective titanium extraction by balancing between maximum titanium extraction and minimum impurity digestion. The main difference between two strategies is due to process optimization framework. For the first strategy, the most important stage of production process is concerned as the main stage and rest of stages would be adopted with respect to the main stage. The second strategy optimizes performance of more than one stage at once. The second strategy has more technical complexity compared to the first one but it brings more economical and technical advantages for the leaching system. Obviously, each strategy has its own optimum operational zone that is not as same as the other one and the best operational zone is chosen due to complexity, economical and practical aspects of the leaching system. Experimental design has been carried out by using Taguchi method. The most important advantages of this methodology are involving different technical aspects of leaching process; minimizing the number of needed experiments as well as time and expense; and concerning the role of parameter interactions due to principles of multifactor-at-time optimization. Leaching tests have been done at batch scale on lab with appropriate control on temperature. The leaching tank geometry has been concerned as an important factor to provide comparable agitation conditions. Data analysis has been done by using reactor design and mass balancing principles. Finally, optimum zone for operational parameters are determined for each leaching strategy and discussed due to their economical and practical aspects.

Keywords: titanium leaching, optimization, experimental design, performance analysis

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Authors: U. Ravi Babu, Mohd Mastan

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The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-of-the-art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking

Procedia PDF Downloads 371

Authors: S. Bilal, S. A. Bhat, I. Hussain, J. D. Parrah, S. P. Ahmad, M. R. Mir

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Background: The wound healing involves a highly coordinated cascade of cellular and immunological response over a period including coagulation, inflammation, granulation tissue formation, epithelialization, collagen synthesis and tissue remodeling. Wounds in aged heal more slowly than those in younger, mainly because of comorbidities that occur as one age. The present study is about the influence of age on wound healing. 1x1cm^2 (100 mm) wounds were created on the back of the animal. The animals were divided into two groups; one group had animals in the age group of 3-9 months while another group had animals in the age group of 15-21 months. Materials and Methods: 24 clinically healthy rabbits in the age group of 3-21 months were used as experimental animals and divided into two groups viz A and B. All experimental parameters, i.e., Excision wound model, Measurement of wound area, Protein extraction and estimation, Protein extraction and estimation and DNA extraction and estimation were done by standard methods. Results: The parameters studied were wound contraction, hydroxyproline, glucosamine, protein, and DNA. A significant increase (p<0.005) in the hydroxyproline, glucosamine, protein and DNA and a significant decrease in wound area (p<0.005) was observed in the age group of 3-9 months when compared to animals of an age group of 15-21 months. Wound contraction together with hydroxyproline, glucosamine, protein and DNA estimations suggest that advanced age results in retarded wound healing. Conclusion: The decrease wound contraction and accumulation of hydroxyproline, glucosamine, protein and DNA in group B animals may be associated with the reduction or delay in growth factors because of the advancing age.

Keywords: age, wound healing, excision wound, hydroxyproline, glucosamine

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Authors: Rafia Asghar, Abdul Hafeez

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The current research was related with natural dyes’ extraction from the powder of Neem (Azadirachta indica) bark and studied characterization of this dye under microwave radiation’s influence. Both cotton fabric and dyeing powder were exposed to microwave rays for different time intervals (2minutes, 4 minutes, 6 minutes, 8 minutes and 10 minutes) using conventional oven. Aqueous, 60% Methanol and Ethyl Acetate solubilized extracts obtained from Neem (Azadirachta indica) bark were also exposed to different time intervals (2minutes, 4 minutes, 6 minutes, 8 minutes and 10 minutes) of microwave rays exposure. Pre, meta and post mordanting with Alum (2%, 4%, 6%, 8%, and 10%) was done to improve color strength of the extracted dye. Exposure of Neem (Azadirachta indica) bark extract and cotton to microwave rays enhanced the extraction process and dyeing process by reducing extraction time, dyeing time and dyeing temperature. Microwave rays treatment had a very strong influence on color fastness and color strength properties of cotton that was dyes using Neem (Azadirachta indica) bark for 30 minutes and dyeing cotton with that Neem bark extract for 75 minutes at 30°C. Among pre, meta and post mordanting, results indicated that 5% concentration of Alum in meta mordanting exhibited maximum color strength.

Keywords: dyes, natural dyeing, ecofriendly dyes, microwave treatment

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Authors: Pratima Kumari, Sukha Ranjan Samadder

Abstract:

This research aims to contribute to the sustainable production of graphene materials by exploring the extraction of graphite from spent primary and secondary batteries. The increasing demand for graphene materials, a versatile and high-performance material, necessitates environmentally friendly methods for its synthesis. The process involves a well-planned methodology, beginning with the gathering and categorization of batteries, followed by the disassembly and careful removal of graphite from anode structures. The use of environmentally friendly solvents and mechanical techniques ensures an efficient and eco-friendly extraction of graphite. Advanced approaches such as the modified Hummers' method and chemical reduction process are utilized for the synthesis of graphene materials, with a focus on optimizing parameters. Various analytical techniques such as Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and Raman spectroscopy were employed to validate the quality and structure of the produced graphene materials. The major findings of this study reveal the successful implementation of the methodology, leading to the production of high-quality graphene materials suitable for advanced material applications. Thorough characterization using various advanced techniques validates the structural integrity and purity of the graphene. The economic viability of the process is demonstrated through a comprehensive economic analysis, highlighting the potential for large-scale production. This research contributes to the field of sustainable production of graphene materials by offering a systematic methodology that efficiently transforms spent batteries into valuable graphene resources. Furthermore, the findings not only showcase the potential for upcycling electronic waste but also address the pressing need for environmentally conscious processes in advanced material synthesis.

Keywords: spent primary batteries, spent secondary batteries, graphite extraction, advanced material synthesis, circular economy approach

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

Abstract:

Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

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Authors: Kanika Kalra, Harmeet Kaur, Dinesh Goyal

Abstract:

Total phenolics were extracted from waste orange peels by solvent extraction and alkali hydrolysis method. The most efficient solvents for extracting phenolic compounds from waste biomass were methanol (60%) > dimethyl sulfoxide > ethanol (60%) > distilled water. The extraction yields were significantly impacted by solvents (ethanol, methanol, and dimethyl sulfoxide) due to varying polarity and concentrations. Extraction of phenolics using 60% methanol yielded the highest phenolics (in terms of gallic acid equivalent (GAE) per gram of biomass) in orange peels. Alkali hydrolyzed extract from orange peels contained 7.58±0.33 mg GAE g⁻¹. By using the solvent extraction technique, it was observed that 60% methanol is comparatively the best-suited solvent for extracting polyphenolic compounds and gave the maximum yield of 4.68 ± 0.47 mg GAE g⁻¹ in orange peel extracts. DPPH radical scavenging activity and reducing the power of orange peel extract were checked, where 60% methanolic extract showed the highest antioxidant activity, 85.50±0.009% for DPPH, and dimethyl sulfoxide (DMSO) extract gave the highest yield of 1.75±0.01% for reducing power ability of the orange peels extract. Characterization of the polyphenolic compounds was done by using Fourier transformation infrared (FTIR) spectroscopy. Solvent and alkali hydrolysed extracts were evaluated for antibacterial activity using the agar well diffusion method against Gram-positive Bacillus subtilis MTCC441 and Gram-negative Escherichia coli MTCC729. Methanolic extract at 300µl concentration showed an inhibition zone of around 16.33±0.47 mm against Bacillus subtilis, whereas, for Escherichia coli, it was comparatively less. Broth-based turbidimetric assay revealed the antibacterial effect of different volumes of orange peel extracts against both organisms.

Keywords: orange peels, total phenolic content, antioxidant, antibacterial

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