Search results for: rules extraction

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.

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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: Lassaad Smirani

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In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

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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

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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

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Authors: Despina Yiakoumi, Agathe Rouaix

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Laboratory experiments were run to investigate the impact of different design characteristics of the auctions, which have been implemented to procure capacity in the UK’s reformed electricity markets. The experiment studies competition among bidders in procurement multi-unit discrete descending clock auctions under different feedback policies and pricing rules. Theory indicates that feedback policy in combination with the two common pricing rules; last-accepted bid (LAB) and first-rejected bid (FRB), could affect significantly the auction outcome. Two information feedback policies regarding the bidding prices of the participants are considered; with feedback and without feedback. With feedback, after each round participants are informed of the number of items still in the auction and without feedback, after each round participants have no information about the aggregate supply. Under LAB, winning bidders receive the amount of the highest successful bid and under the FRB the winning bidders receive the lowest unsuccessful bid. Based on the theoretical predictions of the alternative auction designs, it was decided to run three treatments. First treatment considers LAB with feedback; second treatment studies LAB without feedback; third treatment investigates FRB without feedback. Theoretical predictions of the game showed that under FRB, the alternative feedback policies are indifferent to the auction outcome. Preliminary results indicate that LAB with feedback and FRB without feedback achieve on average higher clearing prices in comparison to the LAB treatment without feedback. However, the clearing prices under LAB with feedback and FRB without feedback are on average lower compared to the theoretical predictions. Although under LAB without feedback theory predicts the clearing price will drop to the competitive equilibrium, experimental results indicate that participants could still engage in cooperative behavior and drive up the price of the auction. It is showed, both theoretically and experimentally, that the pricing rules and the feedback policy, affect the bidding competitiveness of the auction by providing opportunities to participants to engage in cooperative behavior and exercise market power. LAB without feedback seems to be less vulnerable to market power opportunities compared to the alternative auction designs. This could be an argument for the use of LAB pricing rule in combination with limited feedback in the UK capacity market in an attempt to improve affordability for consumers.

Keywords: descending clock auctions, experiments, feedback policy, market design, multi-unit auctions, pricing rules, procurement auctions

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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: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

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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

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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

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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

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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

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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: Dorothy Chyung

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In the psychiatric interview, the mental status exam begins with an assessment of the patient's appearance, noting aspects such as grooming and hygiene. However, it is not well established whether further examination of a patient's attire can provide further useful information. The popular assumption is that those who are mentally unwell will manifest this in unusual clothing. In the moral treatment of the 19th century, proper clothing was also seen as a pivotal therapeutic concern. This project examines assumptions about clothing, both as a reflection of and treatment for psychopathology. The methodology considers the opinions expressed in 19th century art and journals, as well as asylum rules, in comparison to contemporary psychiatric practice and research evidence. Per moral treatment in the 19th century, self-discipline and a proper environment would cure insanity. Madness was evident in the opposite of these ideals—such as ragged or ‘improper’ clothing—and rules about attire delineated the most correct (i.e. sane) ways to dress. These rules applied not only for the patients but also for staff. Despite these ideals, accusations were made that asylums, in fact, dressed patients to look more mentally unwell and further removed patients’ agency. Current practice in psychiatric hospitals retains remnants of moral treatment. Patients are expected to dress ‘appropriately’ while retaining some choice to build self-esteem, with arguments about safety being used to justify the removal of choice. Meanwhile, staff is expected to dress professionally and as role models, based on the assumption that conservative dress is least pathological. Research on this subject is limited, and there is little evidence that discrete psychiatric diagnoses manifest in the particular dress, nor that conservative dress would result in a reduction in pathology. Dressing unusually has become a privilege granted only to those without association with mental illness.

Keywords: fashion, history of psychiatry, medical humanities, mental health treatment

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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: Nurulhuda A. Manaf, Nor Najihah Zainal Abidin, Nur Amalina Jamaludin

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Coordinating service interactions are a vital part of developing distributed applications that are built up as networks of autonomous participants, e.g., software components, web services, online resources, involve a collaboration between a diverse number of participant services on different providers. The complexity in coordinating service interactions reflects how important the techniques and approaches require for designing and coordinating the interaction between participant services to ensure the overall goal of a collaboration between participant services is achieved. The objective of this research is to develop capability of steering a complex service interaction towards a desired outcome. Therefore, an efficient technique for modelling, generating, and verifying the coordination of service interactions is developed. The developed model describes service interactions using service choreographies approach and focusing on a declarative approach, advocating an Object Management Group (OMG) standard, Semantics of Business Vocabulary and Rules (SBVR). This model, namely, SBVR model for service choreographies focuses on a declarative deontic rule expressing both obligation and prohibition, which can be more useful in working with coordinating service interactions. The generated SBVR model is then be formulated and be transformed into Alloy model using Alloy Analyzer for verifying the generated SBVR model. The transformation of SBVR into Alloy allows to automatically generate the corresponding coordination of service interactions (service choreography), hence producing an immediate instance of execution that satisfies the constraints of the specification and verifies whether a specific request can be realised in the given choreography in the generated choreography.

Keywords: service choreography, service coordination, behavioural modelling, complex interactions, declarative specification, verification, model transformation, semantics of business vocabulary and rules, SBVR

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Authors: Pratima Kumari, Sukha Ranjan Samadder

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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

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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: Avinash S. Jagtap, Sharad D. Gore, Rajendra G. Gurao

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Decision rules become more and more complex as the number of conditions increase. As a consequence, the complexity of the decision rule also influences the time complexity of computer implementation of such a rule. Consider, for example, a decision that depends on four conditions A, B, C and D. For simplicity, suppose each of these four conditions is binary. Even then the decision rule will consist of 16 lines, where each line will be of the form: If A and B and C and D, then action 1. If A and B and C but not D, then action 2 and so on. While executing this decision rule, each of the four conditions will be checked every time until all the four conditions in a line are satisfied. The minimum number of logical comparisons is 4 whereas the maximum number is 64. This paper proposes to present a complex decision rule in the form of a decision tree. A decision tree divides the cases into branches every time a condition is checked. In the form of a decision tree, every branching eliminates half of the cases that do not satisfy the related conditions. As a result, every branch of the decision tree involves only four logical comparisons and hence is significantly simpler than the corresponding complex decision rule. The conclusion of this paper is that every complex decision rule can be represented as a decision tree and the decision tree is mathematically equivalent but computationally much simpler than the original complex decision rule

Keywords: strategic, tactical, operational, adaptive, innovative

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Authors: Mikhail Zarechnev, Bora I. Kumova

Abstract:

A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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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: Qusai Alshahwan

Abstract:

The arbitrator’s duties of independence and impartiality play a significant role in delivering arbitral awards which legitimate the fundamental of arbitration concepts. For this reason, the international and national arbitration rules require arbitrators to be independent and impartial to solve the arbitration disputes fairly between the parties. However, solving the disputes fairly also requires arbitrators to disclose any existing conflicts of interest with the parties to avoid misunderstanding and late challenges. In contrary with the international and national arbitration rules, the English Arbitration Act 1996 does not include independence as a separate ground for arbitrator’s removal, and importantly the English Arbitration Act 1996 is deliberately silent to the arbitrator duty of disclosure. The absence of arbitrator duty of disclosure is an issue had generated uncertainty and concerns for the arbitration community under the English jurisdiction, particularly when the English courts rejected the IBA guidelines of arbitrator conflict of interest such as in case of Halliburton v Chubb for example. This article is highlighting on the legal consequences of the absence of arbitrator duty of disclosure under the English Arbitration Act 1996 and the arbitrator's contractual obligations.

Keywords: arbitration, impartiality, independence, duty of disclosure, English Arbitration Act 1996

Procedia PDF Downloads 114