Search results for: document clustering

Authors: Abdelsabour G. A. Khaled, Galal A.R. El-Sherbeny, Ahmed M. Hassanein, Gameel M. G. Aly

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Classical methods of identification, based on agronomical characterization, are not always the most accurate way due to the instability of these characteristics under the influence of the different environments. In order to estimate the genetic diversity, molecular markers provided excellent tools. In this study, Genetic variation of nine Egyptian jojoba shrubs was tested using ISSR (inter simple sequences repeats), RAPD (random amplified polymorphic DNA) markers and based on the morphological characterization. The average of the percentage of polymorphism (%P) ranged between 58.17% and 74.07% for ISSR and RAPD markers, respectively. The range of genetic similarity percents among shrubs based on ISSR and RAPD markers were from 82.9 to 97.9% and from 85.5 to 97.8%, respectively. The average of PIC (polymorphism information content) values were 0.19 (ISSR) and 0.24 (RAPD). In the present study, RAPD markers were more efficient than the ISSR markers. Where the RAPD technique exhibited higher marker index (MI) average (1.26) compared to ISSR one (1.11). There was an insignificant correlation between the ISSR and RAPD data (0.076, P > 0.05). The dendrogram constructed by the combined RAPD and ISSR data gave a relatively different clustering pattern.

Keywords: correlation, molecular markers, polymorphism, marker index

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Authors: N. Perini, M. C. Thaller, F. Mercuri, S. Orlanducci, A. Rubechini, L. Migliore

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The preservation of cultural heritage is one of the major challenges of today’s society, because of the fundamental right of future generations to inherit it as the continuity with their historical and cultural identity. Parchments, consisting of a semi-solid matrix of collagen produced from animal skin (i.e., sheep or goats), are a significant part of the cultural heritage, being used as writing material for many centuries. Due to their animal origin, parchments easily undergo biodeterioration. The most common biological damage is characterized by isolated or coalescent purple spots that often leads to the detachment of the superficial layer and the loss of the written historical content of the document. Although many parchments with the same biodegradative features were analyzed, no common causative agent has been found so far. Very recently, a study was performed on a purple-damaged parchment roll dated back 1244 A.D, the A.A. Arm. I-XVIII 3328, belonging to the oldest collection of the Vatican Secret Archive (Fondo 'Archivum Arcis'), by comparing uncolored undamaged and purple damaged areas of the same document. As a whole, the study gave interesting results to hypothesize a model of biodeterioration, consisting of a microbial succession acting in two main phases: the first one, common to all the damaged parchments, is characterized by halophilic and halotolerant bacteria fostered by the salty environment within the parchment maybe induced by bringing of the hides; the second one, changing with the individual history of each parchment, determines the identity of its colonizers. The design of this model was pivotal to this study, performed by different labs of the Tor Vergata University (Rome, Italy), in collaboration with the Vatican Secret Archive. Three documents, belonging to a collection of dramatically damaged parchments archived as 'Faldone Patrizi A 19' (dated back XVII century A.D.), were analyzed through a multidisciplinary approach, including three updated technologies: (i) Next Generation Sequencing (NGS, Illumina) to describe the microbial communities colonizing the damaged and undamaged areas, (ii) RAMAN spectroscopy to analyze the purple pigments, (iii) Light Transmitted Analysis (LTA) to evaluate the kind and entity of the damage to native collagen. The metagenomic analysis obtained from NGS revealed DNA sequences belonging to Halobacterium salinarum mainly in the undamaged areas. RAMAN spectroscopy detected pigments within the purple spots, mainly bacteriorhodopsine/rhodopsin-like pigments, a purple transmembrane protein containing retinal and present in Halobacteria. The LTA technique revealed extremely damaged collagen structures in both damaged and undamaged areas of the parchments. In the light of these data, the study represents a first confirmation of the microbial succession model described above. The demonstration of this model is pivotal to start any possible new restoration strategy to bring back historical parchments to their original beauty, but also to open opportunities for intervention on a huge amount of documents.

Keywords: biodeterioration, parchments, purple spots, ecological succession

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Authors: Hamid R. Lashgarian Azad, Seyed N. Shetab Boushehri

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Wireless sensor networks (WSN) have become progressively popular due to their wide range of applications. Wireless Sensor Network is made of numerous tiny sensor nodes that are battery-powered. It is a very significant problem to maximize the lifetime of wireless sensor networks. In this paper, we propose a two-stage protocol based on an imperialist competitive algorithm (2S-ICA) to solve a sensor network optimization problem. The energy of the sensors can be greatly reduced and the lifetime of the network reduced by long communication distances between the sensors and the sink. We can minimize the overall communication distance considerably, thereby extending the lifetime of the network lifetime through connecting sensors into a series of independent clusters using 2SICA. Comparison results of the proposed protocol and LEACH protocol, which is common to solving WSN problems, show that our protocol has a better performance in terms of improving network life and increasing the number of transmitted data.

Keywords: wireless sensor network, imperialist competitive algorithm, LEACH protocol, k-means clustering

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Authors: Agria Rhamdhan

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WhatsApp as the most popular mobile messaging app has been used as evidence in many criminal cases. As the use of mobile messages generates large amounts of data, forensic investigation faces the challenge of large data problems. The hardest part of finding this important evidence is because current practice utilizes tools and technique that require manual analysis to check all messages. That way, analyze large sets of mobile messaging data will take a lot of time and effort. Our work offers methodologies based on forensic triage to reduce large data to manageable sets resulting easier to do detailed reviews, then show the results through interactive visualization to show important term, entities and relationship through intelligent ranking using Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) Model. By implementing this methodology, investigators can improve investigation processing time and result's accuracy.

Keywords: forensics, triage, visualization, WhatsApp

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Authors: M. G. Dirodi, G. Gugliotta, C. Leonardi

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The member states shall establish zones and agglomerations throughout their territory to assess and manage air quality in order to comply with European directives. In Italy decree 155/2010, transposing Directive 2008/50/EC on ambient air quality and cleaner air for Europe, merged into a single act the previous provisions on ambient air quality assessment and management, including those resulting from the implementation of Directive 2004/107/EC relating to arsenic, cadmium, nickel, mercury, and polycyclic aromatic hydrocarbons in ambient air. Decree 155/2010 introduced stricter rules for identifying zones on the basis of the characteristics of the territory in spite of considering pollution levels, as it was in the past. The implementation of such new criteria has reduced the great variability of the previous zoning, leading to a significant reduction of the total number of zones and to a complete and uniform ambient air quality assessment and management throughout the Country. The present document is related to the new zones definition in Italy according to Decree 155/2010. In particular, the paper contains the description and the analysis of the outcome of zoning and classification.

Keywords: zones, agglomerations, air quality assessment, classification

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Authors: Aurelija Burinskiene

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This paper presents the study for an e-commerce warehouse. The study is aiming to improve order fulfillment activity by identifying the strategy presenting the best performance. A simulation model was proposed to reach the target of this research. This model enables various scenario tests in an e-commerce warehouse, allowing them to find out for the best order fulfillment strategy. By using simulation, model authors investigated customers’ orders representing on-line purchases for one month. Experiments were designed to evaluate various order picking methods applicable to the fulfillment of customers’ orders. The research uses cost components analysis and helps to identify the best possible order picking method improving the overall performance of e-commerce warehouse and fulfillment service to the customers. The results presented show that the application of order batching strategy is the most applicable because it brings distance savings of around 6.7 percentage. This result could be improved by taking an assortment clustering action until 8.34 percentage. So, the recommendations were given to apply the method for future e-commerce warehouse operations.

Keywords: e-commerce, order, fulfilment, strategy, simulation

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Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Tarik Bazgour, Cedric Heuchenne, Danielle Sougne

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We examine time variation in the market beta of portfolios sorted on quality, liquidity level and liquidity beta characteristics across stock market phases. Using US stock market data for the period 1970-2010, we find, first, the US stock market was driven by four regimes. Second, during the crisis regime, low (high) quality, high (low) liquidity beta and illiquid (liquid) stocks exhibit an increase (a decrease) in their market betas. This finding is consistent with the flight-to-quality and liquidity phenomena. Third, we document the same pattern across stocks when the market volatility is low. We argue that, during low volatility times, investors shift their portfolios towards low quality and illiquid stocks to seek portfolio gains. The pattern observed in the tranquil regime can be, therefore, explained by a flight-to-low-quality and to illiquidity. Finally, our results reveal that liquidity level is more important than liquidity beta during the crisis regime.

Keywords: financial crises, quality, liquidity, liquidity risk, regime-switching models

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Authors: Ali Dulla

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This paper introduces a new dataset (and the methodology used to generate it) based on a wide range of historical Arabic documents containing clean data simple and homogeneous-page layouts. The experiments are implemented on printed and handwritten documents obtained respectively from some important libraries such as Qatar Digital Library, the British Library and the Library of Congress. We have gathered and commented on 150 archival document images from different locations and time periods. It is based on different documents from the 17th-19th century. The dataset comprises differing page layouts and degradations that challenge text line segmentation methods. Ground truth is produced using the Aletheia tool by PRImA and stored in an XML representation, in the PAGE (Page Analysis and Ground truth Elements) format. The dataset presented will be easily available to researchers world-wide for research into the obstacles facing various historical Arabic documents such as geometric correction of historical Arabic documents.

Keywords: dataset production, ground truth production, historical documents, arbitrary warping, geometric correction

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Authors: Luisa Carrer, Lorenzo De Masi

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In this paper, we exploit the massive amount of information from Facebook to build a measure of gender attitudes in Italy at a previously impossible resolution—the municipal level. We construct our index via a machine learning method to replicate a benchmark region-level measure. Interestingly, we find that most of the variation in our Gender Norms Index (GNI) is across towns within narrowly defined geographical areas rather than across regions or provinces. In a second step, we show how this local variation in norms can be leveraged for identification purposes. In particular, we use our index to investigate whether these differences in norms carry over to the policy activity of politicians elected in the Italian Parliament. We document that females are more likely to sit in parliamentary committees focused on gender-sensitive matters, labor, and social issues, but not if they come from a relatively conservative town. These effects are robust to conditioning the legislative term and electoral district, suggesting the importance of social norms in shaping legislators’ policy activity.

Keywords: gender equality, gender norms index, Facebook, machine learning, politics

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Authors: Jen-Fu Lee

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From the 1980s, the ministry of education in Taiwan moves the instrument ‘Recorder’ into the 9-year compulsory schooling system. The recorder is widely popularized successfully in Taiwan. The research aims to document the history of how the recorder came into Taiwan, what the process of the recorder moving into the schooling system is; what the meaning for the recorder moving into the schooling system is by searching the papers about the recorder in Taiwan and interviewing the people who had participated the process. The research discovers that the recorder in Taiwan was popularized nongovernmental by Shang-Ren, Wang. Shang-Ren, Wang imported 200 recorders from Japan in 1982 and then founded a publishing house which publishes the books and sheets about the recorder in 1983. The reason of Shang-Ren, Wang committed to popularizing the recorder is to spread the Orff Approach in Taiwan. Except for the technique of playing the recorder, the knowledge of the history of the recorder and the role that it plays in Early Music is not available in school. The recorder only plays a ‘Cheap and Easy’ instrument which is suitable for the schooling system in Taiwan, cannot develop to a professional instrument.

Keywords: recorder, Taiwan, Shang-Ren, Wang, compulsory schooling system

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Authors: Ariel Barel, Rotem Manor, Alfred M. Bruckstein

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We present a probabilistic gathering algorithm for agents that can only detect the presence of other agents in front of or behind them. The agents act in the plane and are identical and indistinguishable, oblivious, and lack any means of direct communication. They do not have a common frame of reference in the plane and choose their orientation (direction of possible motion) at random. The analysis of the gathering process assumes that the agents act synchronously in selecting random orientations that remain fixed during each unit time-interval. Two algorithms are discussed. The first one assumes discrete jumps based on the sensing results given the randomly selected motion direction, and in this case, extensive experimental results exhibit probabilistic clustering into a circular region with radius equal to the step-size in time proportional to the number of agents. The second algorithm assumes agents with continuous sensing and motion, and in this case, we can prove gathering into a very small circular region in finite expected time.

Keywords: control, decentralized, gathering, multi-agent, simple sensors

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Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

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Authors: Tutku Ak, A. Esra Cengiz, Çiğdem Ayhan Kaptan

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The conservation community has been increasingly promoting the concept of ecological connectivity towards the prevention and mitigation of landscape fragmentation. Many tools have been proposed for this purpose in not only Europe, but also around the world. Spatial planning for building connectivity, however, has many problems associated with the complexity of ecological processes at spatial and temporal scales. Furthermore, on the ground implementation could be very difficult potentially leading to ecologically disastrous results and waste of resources. These problems, on the other hand, can be avoided or rectified as more experience is gained with implementation. Therefore, it is the objective of this study to document the experiences gained with connectivity planning in Turkish landscapes. This paper is a preliminary review of the conservation initiatives and projects aimed at protecting and building ecological connectivity in and around Turkey. The objective is to scope existing conservation plans, tools and implementation approaches in Turkey and the ultimate goal is to understand to what degree they have been implemented and what are the constraints and opportunities that are being faced.

Keywords: ecological connectivity, large-scale landscapes, planning and implementation, Turkey

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Authors: Francis Alterado, Jennifer Enriquez

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Semantic Based Analysis in Complaint Management System with Analytics is an enhanced tool of providing complaints by the clients as well as a mechanism for Palawan Polytechnic College to gather, process, and monitor status of these complaints. The study has a mobile application that serves as a remote facility of communication between the students and the school management on the issues encountered by the student and the solution of every complaint received. In processing the complaints, text mining and clustering algorithms were utilized. Every module of the systems was tested and based on the results; these are 100% free from error before integration was done. A system testing was also done by checking the expected functionality of the system which was 100% functional. The system was tested by 10 students by forwarding complaints to 10 departments. Based on results, the students were able to submit complaints, the system was able to process accordingly by identifying to which department the complaints are intended, and the concerned department was able to give feedback on the complaint received to the student. With this, the system gained 4.7 rating which means Excellent.

Keywords: technology adoption, emerging technology, issues challenges, algorithm, text mining, mobile technology

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Authors: Louis Nwachi

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Urban planning systems in most countries still rely on expert-driven, top-down technocratic plan-making processes rather than a public and people-led process. This paper set out to evaluate the need for public participation in the plan-making process and to highlight the factors that affect public participation in the plan-making process. In doing this, it adopted a qualitative approach based on document review and interviews taken from real-world phenomena. A case study strategy using the Metropolitan Area of Abuja, the capital of Nigeria, as the study sample was used in carrying out the research. The research finds that participation is an important tool in the plan-making process and that public engagement in the process contributes to the identification of key urban issues that are unique to the specific local areas, thereby contributing to the establishment of priorities and, in turn, to the mobilization of resources to meet the identified needs. It also finds that the development of a participation model by city authorities encourages public engagement and helps to develop trust between those in authority and the different key stakeholder groups involved in the plan-making process.

Keywords: plan-making, participation, urban planning, city

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Authors: Jeoffrey Oostrom, Robbert James Schlingmann, Hani Alers

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This document depicts the research into the indicators of dementia progression, the automation of quality of life assignments, and the visualization of it. To do this, the Smart Teddy project was initiated to make a smart companion that both monitors the senior citizen as well as processing the captured data into an insightful dashboard. With around 50 million diagnoses worldwide, dementia proves again and again to be a bothersome strain on the lives of many individuals, their relatives, and society as a whole. In 2015 it was estimated that dementia care cost 818 billion U.S Dollars globally. The Smart Teddy project aims to take away a portion of the burden from caregivers by automating the collection of certain data, like movement, geolocation, and sound-levels. This paper proves that the Smart Teddy has the potential to become a useful tool for caregivers but won’t pose as a solution. The Smart Teddy still faces some problems in terms of emotional privacy, but its non-intrusive nature, as well as diversity in usability, can make up for it.

Keywords: dementia care, medical data visualization, quality of life, smart companion

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Authors: Noury Bakrim

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When dealing with motivation/arbitrariness, forming form (Forma Formans) and morphodynamics are to be grasped as relevant implications of enunciation/enactment, schematization within the specificity of language as sound/meaning articulation. Thus, the fact that a language is a form does not contradict stasis/dynamic enunciation (reflexivity vs double articulation). Moreover, some languages exemplify the role of the forming form, uttering, and schematization (roots in Semitic languages, the Chinese case). Beyond the evolutionary biosemiotic process (form/substance bifurcation, the split between realization/representation), non-isomorphism/asymmetry between linguistic form/norm and linguistic realization (phonetics for instance) opens up a new horizon problematizing the role of Brain – sensorimotor contribution in the continuous forming form. Therefore, we hypothesize biotization as both process/trace co-constructing motivation/forming form. Henceforth, referring to our findings concerning distribution and motivation patterns within Berber written texts (pulse based obstruents and nasal-lateral levels in poetry) and oral storytelling (consonant intensity clustering in quantitative and semantic/prosodic motivation), we understand consonant clustering, motivation and schematization as a complex phenomenon partaking in patterns of oral/written iconic prosody and reflexive metalinguistic representation opening the stable form. We focus our inquiry on both Amazigh and English clusters (/spl/, /spr/) and iconic consonant iteration in [gnunnuy] (to roll/tumble), [smummuy] (to moan sadly or crankily). For instance, the syllabic structures of /splaeʃ/ and /splaet/ imply an anamorphic representation of the state of the world: splash, impact on aquatic surfaces/splat impact on the ground. The pair has stridency and distribution as distinctive features which specify its phonetic realization (and a part of its meaning) /ʃ/ is [+ strident] and /t/ is [+ distributed] on the vocal tract. Schematization is then a process relating both physiology/code as an arthron vocal/bodily, vocal/practical shaping of the motor-articulatory system, leading to syntactic/semantic thematization (agent/patient roles in /spl/, /sm/ and other clusters or the tense uvular /qq/ at the initial position in Berber). Furthermore, the productivity of serial syllable sequencing in Berber points out different expressivity forms. We postulate two Components of motivated formalization: i) the process of memory paradigmatization relating to sequence modeling under sensorimotor/verbal specific categories (production/perception), ii) the process of phonotactic selection - prosodic unconscious/subconscious distribution by virtue of iconicity. Basing on multiple tests including a questionnaire, phonotactic/visual recognition and oral/written reproduction, we aim at patterning/conceptualizing consonant schematization and motivation among EFL and Amazigh (Berber) learners and speakers integrating biolinguistic hypotheses.

Keywords: consonant motivation and prosody, language and order of life, anamorphic representation, represented representation, biotization, sensori-motor and brain representation, form, formalization and schematization

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Authors: Renzo Palomino, Alessandra Trujillo, Lidia Pacheco

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The document presents a study based on the incremental bearing capacity of silty clay soil with the incorporation of crushed PET fibers. For a better understanding of the behavior of soil, it is necessary to know its origin. The analyzed samples came from the subgrade layer of a highway that connects the cities of Muniches and Yurimaguas in Loreto, Peru. The material in this area usually has properties such as low support index, medium to high plasticity, and other characteristics that make it considered a ‘problematic’ soil due to factors such as climate, humidity, and geographical location. In addition, PET fibers are obtained from the decomposition of plastic bottles that are polluting agents with a high production rate in our country; in that sense, their use in a construction process represents a considerable reduction in environmental impact. Moreover, to perform a precise analysis of the behavior of this soil mixed with PET, tests such as the hydrometer test, Proctor and CBR with 15%, 10%, 5%, 4%, 3%, and 1% of PET with respect to the mass of the sample of natural soil were carried out. The results show that when a low percentage of PET is used, the support index increases.

Keywords: environmental impact, geotechnics, PET, silty clay soil

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Authors: Gaurav Kumar, Shilpa

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Digital libraries have been established all over the world to create, maintain and to preserve the digital materials. This paper focuses on operational digital preservation systems specifically in educational organizations in India. It considers the broad range of digital objects including e-journals, technical reports, e-records, project documents, scientific data, etc. This paper describes the main objectives, process and technological issues involved in preservation of digital materials. Digital preservation refers to the various methods of keeping digital materials alive for the future. It includes everything from electronic publications on CD-ROM to Online database and collections of experimental data in digital format maintains the ability to display, retrieve and use digital collections in the face of rapidly changing technological and organizational infrastructures elements. This paper exhibits the importance and objectives of digital preservation. The necessities of preservation are hardware and software technology to interpret the digital documents and discuss various aspects of digital preservation.

Keywords: preservation, digital preservation, digital dark age, conservation, archive, repository, document, information technology, hardware, software, organization, machine readable format

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Authors: Thirsa Sherry, Utkarsh Shrivastav, Kannan B. T., Iynthezhuton K.

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The field of aerodynamics and aeroacoustics remains one of the most poignant and well-researched fields of today. The current paper aims to investigate the predominant problem concerning the effects of noise of varying frequencies and waveforms on airflow surrounding an airfoil. Using a single speaker beneath the airfoil at different positions, we wish to simulate the effects of sound directly impinging on an airfoil and study its direct effects on airflow. We wish to study the same using smoke visualization methods with incense as our smoke-generating material in a variable-speed subsonic wind tunnel. Using frequencies and wavelengths similar to those of common engine noise, we wish to simulate real-world conditions of engine noise interfering with airflow and document the arising trends. These results will allow us to look into the real-world effects of noise on airflow and how to minimize them and expand on the possible relation between waveforms and noise. The parameters used in the study include frequency, Reynolds number, waveforms, angle of attack, and the effects on airflow when varying these parameters.

Keywords: engine noise, aeroacoustics, acoustic excitation, low speed

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Authors: Krystian Chachula, Robert Nowak

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Manufacturing home-made explosives and synthetic drugs is an increasing problem in Europe. To combat that, a data fusion system is proposed for the detection and localization of production sites in urban environments. The data consists of measurements of properties of wastewater performed by various sensors installed in a sewage network. A four-stage fusion strategy allows detecting sources of waste products from known chemical reactions. First, suspicious measurements are used to compute the amount and position of discharged compounds. Then, this information is propagated through the sewage network to account for missing sensors. The next step is clustering and the formation of tracks. Eventually, tracks are used to reconstruct discharge events. Sensor measurements are simulated by a subsystem based on real-world data. In this paper, different discharge scenarios are considered to show how the parameters of used algorithms affect the effectiveness of the proposed system. This research is a part of the SYSTEM project (SYnergy of integrated Sensors and Technologies for urban sEcured environMent).

Keywords: continuous monitoring, information fusion and sensors, internet of things, multisensor fusion

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Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: Haifa Ben Saber, Mourad Elloumi

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In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of constant rows with a group of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed. We introduce a new algorithm called, Enumerative tree (EnumTree) for biclustering of binary microarray data. is an algorithm adopting the approach of enumerating biclusters. This algorithm extracts all biclusters consistent good quality. The main idea of ​​EnumLat is the construction of a new tree structure to represent adequately different biclusters discovered during the process of enumeration. This algorithm adopts the strategy of all biclusters at a time. The performance of the proposed algorithm is assessed using both synthetic and real DNA micryarray data, our algorithm outperforms other biclustering algorithms for binary microarray data. Biclusters with different numbers of rows. Moreover, we test the biological significance using a gene annotation web tool to show that our proposed method is able to produce biologically relevent biclusters.

Keywords: DNA microarray, biclustering, gene expression data, tree, datamining.

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Authors: Yahya N. Alfraidi, Abdel Halim Boussabaine

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Climate change risk impacts are one of the most challenging aspects that faces the built environment now and the near future. The impacts of climate change on buildings are considered in four different dimensions: physical, economic, social, and management. For each of these, the risks are discussed as they arise from various effects linked to climate change, including windstorms, precipitation, temperature change, flooding, and sea-level rise. For example, building assets in cities will be exposed to extreme hot summer days and nights due to the urban heat island effect and pollution. Buildings also could be vulnerable to water, electricity, gas, etc., scarcity. Building materials, fabric and systems could also be stressed by the emerging climate risks. More impotently the building users might experience extreme internal and extern comfort conditions leading to lower productivity, wellbeing and health problems. Thus, the main aim of this paper to document the emerging risks from climate change on building assets. An in-depth discussion on the consequences of these climate change risk is provided. It is expected that the outcome of this research will be a set of risk design indicators for developing and procuring resilient building assets.

Keywords: climate change, risks of climate change, risks on building from climate change, buildings

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Authors: William Huang

Abstract:

Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

Procedia PDF Downloads 131

Authors: A. Bouzabata, A. Boukhari

Abstract:

Curcuma longa L. (Zingiberaceae), commonly known as turmeric, has a long history of traditional uses for culinary purposes as a spice and a food colorant. The present study aimed to document the ethnobotanical knowledge about Curcuma longa and to assess the variation in the herbalists’ experience in Northeastern Algeria. Data were collected by semi-structured questionnaires and direct interviews with 30 herbalists. Ethnobotanical indices, including the fidelity level (FL%), the relative frequency citation (RFC) and use value (UV) were determined by quantitative methods. Diversity in the knowledge was analyzed using univariate, non-parametric and multivariate statistical methods. Three main categories of uses were recorded for C. longa: for food, for medicine and for cosmetic purposes. As a medicine, turmeric was used for the treatment of gastrointestinal, dermatological and hepatic diseases. Medicinal and food uses were correlated with both forms of use (rhizome and powder). The age group did not influence the use. Multivariate analyses showed a significant variation in traditional knowledge, associated with the use value, origin, quality and efficacy of the drug. These findings suggested that the geographical origin of C. longa affected the use in Algeria.

Keywords: curcuma, indices, knowledge, variation

Procedia PDF Downloads 531

Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

Procedia PDF Downloads 440