Search results for: spatial data analysis tools.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14353

Search results for: spatial data analysis tools.

13483 Saudi Twitter Corpus for Sentiment Analysis

Authors: Adel Assiri, Ahmed Emam, Hmood Al-Dossari

Abstract:

Sentiment analysis (SA) has received growing attention in Arabic language research. However, few studies have yet to directly apply SA to Arabic due to lack of a publicly available dataset for this language. This paper partially bridges this gap due to its focus on one of the Arabic dialects which is the Saudi dialect. This paper presents annotated data set of 4700 for Saudi dialect sentiment analysis with (K= 0.807). Our next work is to extend this corpus and creation a large-scale lexicon for Saudi dialect from the corpus.

Keywords: Arabic, Sentiment Analysis, Twitter, annotation.

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13482 Teaching Turn-Taking Rules and Pragmatic Principles to Empower EFL Students and Enhance Their Learning in Speaking Modules

Authors: O. F. Elkommos

Abstract:

Teaching and learning EFL speaking modules is one of the most challenging productive modules for both instructors and learners. In a student-centered interactive communicative language teaching approach, learners and instructors should be aware of the fact that the target language must be taught as/for communication. The student must be empowered by tools that will work on more than one level of their communicative competence. Communicative learning will need a teaching and learning methodology that will address the goal. Teaching turn-taking rules, pragmatic principles and speech acts will enhance students' sociolinguistic competence, strategic competence together with discourse competence. Sociolinguistic competence entails the mastering of speech act conventions and illocutionary acts of refusing, agreeing/disagreeing; emotive acts like, thanking, apologizing, inviting, offering; directives like, ordering, requesting, advising, and hinting, among others. Strategic competence includes enlightening students’ consciousness of the various particular turn-taking systemic rules of organizing techniques of opening and closing conversation, adjacency pairs, interrupting, back-channeling, asking for/giving opinion, agreeing/disagreeing, using natural fillers for pauses, gaps, speaker select, self-select, and silence among others. Students will have the tools to manage a conversation. Students are engaged in opportunities of experiencing the natural language not as a mere extra student talking time but rather an empowerment of knowing and using the strategies. They will have the component items they need to use as well as the opportunity to communicate in the target language using topics of their interest and choice. This enhances students' communicative abilities. Available websites and textbooks now use one or more of these tools of turn-taking or pragmatics. These will be students' support in self-study in their independent learning study hours. This will be their reinforcement practice on e-Learning interactive activities. The students' target is to be able to communicate the intended meaning to an addressee that is in turn able to infer that intended meaning. The combination of these tools will be assertive and encouraging to the student to beat the struggle with what to say, how to say it, and when to say it. Teaching the rules, principles and techniques is an act of awareness raising method engaging students in activities that will lead to their pragmatic discourse competence. The aim of the paper is to show how the suggested pragmatic model will empower students with tools and systems that would support their learning. Supporting students with turn taking rules, speech act theory, applying both to texts and practical analysis and using it in speaking classes empowers students’ pragmatic discourse competence and assists them to understand language and its context. They become more spontaneous and ready to learn the discourse pragmatic dimension of the speaking techniques and suitable content. Students showed a better performance and a good motivation to learn. The model is therefore suggested for speaking modules in EFL classes.

Keywords: Communicative competence, EFL, empowering learners, enhance learning, speech acts, teaching speaking, turn-taking, learner centered, pragmatics.

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13481 XML Integration of Data from CloudSat Satellite and GMS-6 Water Vapor Satellite

Authors: W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

Abstract:

This study aimed at developing visualization tools for integrating CloudSat images and Water Vapor Satellite images. KML was used for integrating data from CloudSat Satellite and GMS-6 Water Vapor Satellite. CloudSat 2D images were transformed into 3D polygons in order to achieve 3D images. Before overlaying the images on Google Earth, GMS-6 water vapor satellite images had to be rescaled into linear images. Web service was developed using webMathematica. Shoreline from GMS-6 images was compared with shoreline from LandSat images on Google Earth for evaluation. The results showed that shoreline from GMS-6 images was highly matched with the shoreline in LandSat images from Google Earth. For CloudSat images, the visualizations were compared with GMS-6 images on Google Earth. The results showed that CloudSat and GMS-6 images were highly correlated.

Keywords: CloudSat, Water vapor, Satellite images, GoogleEarth™.

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13480 Knowledge Discovery and Data Mining Techniques in Textile Industry

Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

Abstract:

This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: Data mining, textile production, decision trees, classification.

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13479 The Comparison of Data Replication in Distributed Systems

Authors: Iman Zangeneh, Mostafa Moradi, Ali Mokhtarbaf

Abstract:

The necessity of ever-increasing use of distributed data in computer networks is obvious for all. One technique that is performed on the distributed data for increasing of efficiency and reliablity is data rplication. In this paper, after introducing this technique and its advantages, we will examine some dynamic data replication. We will examine their characteristies for some overus scenario and the we will propose some suggestion for their improvement.

Keywords: data replication, data hiding, consistency, dynamicdata replication strategy

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13478 Robust Human Rights Governance: Developing International Criteria

Authors: Helen P. Greatrex

Abstract:

Many states are now committed to implementing international human rights standards domestically. In terms of practical governance, how might effectiveness be measured? A facevalue answer can be found in domestic laws and institutions relating to human rights. However, this article provides two further tools to help states assess their status on the spectrum of robust to fragile human rights governance. The first recognises that each state has its own 'human rights history' and the ideal end stage is robust human rights governance, and the second is developing criteria to assess robustness. Although a New Zealand case study is used to illustrate these tools, the widespread adoption of human rights standards by many states inevitably means that the issues are relevant to other countries. This is even though there will always be varying degrees of similarity-difference in constitutional background and developed or emerging human rights systems.

Keywords: robust human rights governance, fragile states.

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13477 Real Time Force Sensing Mat for Human Gait Analysis

Authors: Darwin Gouwanda, S. M. N. Arosha Senanayake, M. M. Danushka Ranjana Marasinghe, Mervin Chandrapal, Jeya Mithra Kumar, Tung Mun Hon, Yulius

Abstract:

This paper presents a real time force sensing instrument that is designed for human gait analysis purposes. This instrument mainly consists of three main elements: the force sensing mat, signal conditioning and switching circuit and data acquisition device. In order to control and to process the incoming signals from the force sensing mat, Force-Logger and Force-Reloader program are developed using Labview 8.0. This paper describes the architecture of the force sensing mat, signal conditioning and switching circuit and the real time streaming of the incoming data from the force sensing mat.

Keywords: Force platform, Force sensing resistor, human gait analysis

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13476 Unsteady Transonic Aerodynamic Analysis for Oscillatory Airfoils using Time Spectral Method

Authors: Mohamad Reza. Mohaghegh, Majid. Malek Jafarian

Abstract:

This research proposes an algorithm for the simulation of time-periodic unsteady problems via the solution unsteady Euler and Navier-Stokes equations. This algorithm which is called Time Spectral method uses a Fourier representation in time and hence solve for the periodic state directly without resolving transients (which consume most of the resources in a time-accurate scheme). Mathematical tools used here are discrete Fourier transformations. It has shown tremendous potential for reducing the computational cost compared to conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy. The accuracy and efficiency of this technique is verified by Euler and Navier-Stokes calculations for pitching airfoils. Because of flow turbulence nature, Baldwin-Lomax turbulence model has been used at viscous flow analysis. The results presented by the Time Spectral method are compared with experimental data. It has shown tremendous potential for reducing the computational cost compared to the conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy, because results verify the small number of time intervals per pitching cycle required to capture the flow physics.

Keywords: Time Spectral Method, Time-periodic unsteadyflow, Discrete Fourier transform, Pitching airfoil, Turbulence flow

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13475 A Study on a Research and Development Cost-Estimation Model in Korea

Authors: Babakina Alexandra, Yong Soo Kim

Abstract:

In this study, we analyzed the factors that affect research funds using linear regression analysis to increase the effectiveness of investments in national research projects. We collected 7,916 items of data on research projects that were in the process of being finished or were completed between 2010 and 2011. Data pre-processing and visualization were performed to derive statistically significant results. We identified factors that affected funding using analysis of fit distributions and estimated increasing or decreasing tendencies based on these factors.

Keywords: R&D funding, Cost estimation, Linear regression, Preliminary feasibility study.

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13474 Rock Textures Classification Based on Textural and Spectral Features

Authors: Tossaporn Kachanubal, Somkait Udomhunsakul

Abstract:

In this paper, we proposed a method to classify each type of natural rock texture. Our goal is to classify 26 classes of rock textures. First, we extract five features of each class by using principle component analysis combining with the use of applied spatial frequency measurement. Next, the effective node number of neural network was tested. We used the most effective neural network in classification process. The results from this system yield quite high in recognition rate. It is shown that high recognition rate can be achieved in separation of 26 stone classes.

Keywords: Texture classification, SFM, neural network, rock texture classification.

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13473 Sustainable Perspectives and Local Development Potential through Tourism

Authors: Pedro H. S. Messetti, Mary L. G. S. Senna, Afonso R. Aquino

Abstract:

Sustainability is a very important and heavily discussed subject, expanding through tourism as well. The study proposition was to collect data and present it to the competent bodies so they can mold their public policies to improve the conditions of the site. It was hypothesized that the lack of data is currently affecting the quality of life and the sustainable development of the site and the tourism. The research was held in Mateiros, a city in the state of Tocantins (TO)/Brasil near Palmas, its capital city. Because of the concentration of tourists during the high season and several tourist attractions being around, the research took place in Mateiros. The methodological procedure had a script of theoretical construction and investigation of the deductive scientific method parameters through a case study in the Jalapão/TO/Brazil region, using it as a tool for a questionnaire given to the competent bodies in an interview system with the UN sustainability indexes as a base. In the three sustainable development scope: environmental, social and economic, the results indicated that the data presented by the interviewed were scarce or nonexistent. It shows that more research is necessary, providing the tools for the ones responsible to propose action plans to improve the site, strengthening the tourism and making it even more sustainable.

Keywords: Jalapão/Brazil State Park, sustainable tourism, UN sustainability indexes.

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13472 The Paralinguistic Function of Emojis in Twitter Communication

Authors: Yasmin Tantawi, Mary Beth Rosson

Abstract:

In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: Computer mediated communication, content analysis, paralinguistics, sociology.

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13471 Integration of Big Data to Predict Transportation for Smart Cities

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: Big data, bus headway prediction, machine learning, public transportation.

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13470 An Identification Method of Geological Boundary Using Elastic Waves

Authors: Masamitsu Chikaraishi, Mutsuto Kawahara

Abstract:

This paper focuses on a technique for identifying the geological boundary of the ground strata in front of a tunnel excavation site using the first order adjoint method based on the optimal control theory. The geological boundary is defined as the boundary which is different layers of elastic modulus. At tunnel excavations, it is important to presume the ground situation ahead of the cutting face beforehand. Excavating into weak strata or fault fracture zones may cause extension of the construction work and human suffering. A theory for determining the geological boundary of the ground in a numerical manner is investigated, employing excavating blasts and its vibration waves as the observation references. According to the optimal control theory, the performance function described by the square sum of the residuals between computed and observed velocities is minimized. The boundary layer is determined by minimizing the performance function. The elastic analysis governed by the Navier equation is carried out, assuming the ground as an elastic body with linear viscous damping. To identify the boundary, the gradient of the performance function with respect to the geological boundary can be calculated using the adjoint equation. The weighed gradient method is effectively applied to the minimization algorithm. To solve the governing and adjoint equations, the Galerkin finite element method and the average acceleration method are employed for the spatial and temporal discretizations, respectively. Based on the method presented in this paper, the different boundary of three strata can be identified. For the numerical studies, the Suemune tunnel excavation site is employed. At first, the blasting force is identified in order to perform the accuracy improvement of analysis. We identify the geological boundary after the estimation of blasting force. With this identification procedure, the numerical analysis results which almost correspond with the observation data were provided.

Keywords: Parameter identification, finite element method, average acceleration method, first order adjoint equation method, weighted gradient method, geological boundary, navier equation, optimal control theory.

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13469 Improvement in Power Transformer Intelligent Dissolved Gas Analysis Method

Authors: S. Qaedi, S. Seyedtabaii

Abstract:

Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.

Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)

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13468 Mobile Phone as a Tool for Data Collection in Field Research

Authors: Sandro Mourão, Karla Okada

Abstract:

The necessity of accurate and timely field data is shared among organizations engaged in fundamentally different activities, public services or commercial operations. Basically, there are three major components in the process of the qualitative research: data collection, interpretation and organization of data, and analytic process. Representative technological advancements in terms of innovation have been made in mobile devices (mobile phone, PDA-s, tablets, laptops, etc). Resources that can be potentially applied on the data collection activity for field researches in order to improve this process. This paper presents and discuss the main features of a mobile phone based solution for field data collection, composed of basically three modules: a survey editor, a server web application and a client mobile application. The data gathering process begins with the survey creation module, which enables the production of tailored questionnaires. The field workforce receives the questionnaire(s) on their mobile phones to collect the interviews responses and sending them back to a server for immediate analysis.

Keywords: Data Gathering, Field Research, Mobile Phone, Survey.

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13467 Cross Project Software Fault Prediction at Design Phase

Authors: Pradeep Singh, Shrish Verma

Abstract:

Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. Earlier we predicted the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven datasets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: Software Metrics, Fault prediction, Cross project, Within project.

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13466 Quad Tree Decomposition Based Analysis of Compressed Image Data Communication for Lossy and Lossless Using WSN

Authors: N. Muthukumaran, R. Ravi

Abstract:

The Quad Tree Decomposition based performance analysis of compressed image data communication for lossy and lossless through wireless sensor network is presented. Images have considerably higher storage requirement than text. While transmitting a multimedia content there is chance of the packets being dropped due to noise and interference. At the receiver end the packets that carry valuable information might be damaged or lost due to noise, interference and congestion. In order to avoid the valuable information from being dropped various retransmission schemes have been proposed. In this proposed scheme QTD is used. QTD is an image segmentation method that divides the image into homogeneous areas. In this proposed scheme involves analysis of parameters such as compression ratio, peak signal to noise ratio, mean square error, bits per pixel in compressed image and analysis of difficulties during data packet communication in Wireless Sensor Networks. By considering the above, this paper is to use the QTD to improve the compression ratio as well as visual quality and the algorithm in MATLAB 7.1 and NS2 Simulator software tool.

Keywords: Image compression, Compression Ratio, Quad tree decomposition, Wireless sensor networks, NS2 simulator.

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13465 Investigation of Learning Challenges in Building Measurement Unit

Authors: Argaw T. Gurmu, Muhammad N. Mahmood

Abstract:

The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: Building measurement, construction management, learning challenges, evaluate survey.

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13464 The Investigation of 5th Grade Turkish Students- Comprehension Scores According to Different Variables

Authors: Omer Kutlu, Ozen Yildirim, Safiye Bilican

Abstract:

The aim of this study is to examine the reading comprehension scores of Turkish 5th grade students according to the variables given in the student questionnaire. In this descriptive survey study research participated 279 5th grade students, who studied at 10 different primary schools in four provinces of Ankara in 2008-2009 academic year. Two different data collection tools were made use of in the study: “Reading Comprehension Test" and “Student Information Questionnaire". Independent sample t-test, oneway Anova and two-way Anova tests were used in the analyses of the gathered data. The results of the study indicate that the reading comprehension scores of the students differ significantly according to sex of the students, the number of books in their houses, the frequency of summarizing activities on the reading text of free and the frequency reading hours provided by their teachers; but, differ not significantly according to educational level of their mothers and fathers.

Keywords: Primary School Education, Reading, ReadingComprehension.

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13463 A New Approach to Design Policies for the Adoption of Alternative Fuel-Technology Powertrains

Authors: Reza Fazeli, Vitor Leal, Jorge Pinho de Sousa

Abstract:

Planning the transition period for the adoption of alternative fuel-technology powertrains is a challenging task that requires sophisticated analysis tools. In this study, a system dynamic approach was applied to analyze the bi-directional interaction between the development of the refueling station network and vehicle sales. Besides, the developed model was used to estimate the transition cost to reach a predefined target (share of alternative fuel vehicles) in different scenarios. Several scenarios have been analyzed to investigate the effectiveness and cost of incentives on the initial price of vehicles, and on the evolution of fuel and refueling stations. Obtained results show that a combined set of incentives will be more effective than just a single specific type of incentives.

Keywords: adoption of Alternative Fuel Vehicles, System Dynamic Analysis, Plug-in Hybrid Vehicles

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13462 Bridging the Green-Value-Gap: A South African Approach

Authors: E.J. Cilliers

Abstract:

Green- spaces might be very attractive, but where are the economic benefits? What value do nature and landscape have for us? What difference will it make to jobs, health and the economic strength of areas struggling with deprivation and social problems? [1].There is a need to consider green spaces from a different perspective. Green planning is not just about flora and fauna, but also about planning for economic benefits [2]. It is worth trying to quantify the value of green spaces since nature and landscape are crucially important to our quality of life and sustainable development. The reality, however, is that urban development often takes place at the expense of green spaces. Urbanization is an ongoing process throughout the world; however, hyper-urbanization without environmental planning is destructive, not constructive [3]. Urban spaces are believed to be more valuable than other land uses, particular green areas, simply because of the market value connected to urban spaces. However, attractive landscapes can help raise the quality and value of the urban market even more. In order to reach these objectives of integrated planning, the Green-Value-Gap needs to be bridged. Economists have to understand the concept of Green-Planning and the spinoffs, and Environmentalists have to understand the importance of urban economic development and the benefits thereof to green planning. An interface between Environmental Management, Economic Development and sustainable Spatial Planning are needed to bridge the Green-Value-Gap.

Keywords: Spatial Planning, Environmental Management, Green-Value-Gap, Compensation, Participation.

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13461 A Survey of Sentiment Analysis Based on Deep Learning

Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

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: Natural language processing, sentiment analysis, document analysis, multimodal sentiment analysis, deep learning.

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13460 Testing of DISAL D240 and D420 Ceramic Tool Materials with an Interrupted Cut Simulator

Authors: Robert Cep, Marek Sadilek, Lenka Ocenasova, Josef Brychta, Michal Hatala, Branimir Barisic

Abstract:

This paper presents a solution for ceramic cutting tools availability in interrupted machining. Experiments were performed on a special fixture – the interrupted cut simulator. This fixture was constructed at our Department of Machining and Assembly within the scope of a project by the Czech Science Foundation. The goals of the tests were to contribute to the wider usage of these cutting materials in machining, especially in interrupted machining. Through the centuries, producers of ceramic cutting tools have taken big steps forward. Namely, increasing durability in maintaining high levels of strength and hardness lends an advantage. Some producers of these materials advise cutting inserts for interrupted machining at the present time [1, 2].

Keywords: Ceramic cutting tool, cutting tool tests, interrupted cutting, machining.

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13459 Prediction of the Epileptic Events 'Epileptic Seizures' by Neural Networks and Expert Systems

Authors: Kifah Tout, Nisrine Sinno, Mohamad Mikati

Abstract:

Many studies have focused on the nonlinear analysis of electroencephalography (EEG) mainly for the characterization of epileptic brain states. It is assumed that at least two states of the epileptic brain are possible: the interictal state characterized by a normal apparently random, steady-state EEG ongoing activity; and the ictal state that is characterized by paroxysmal occurrence of synchronous oscillations and is generally called in neurology, a seizure. The spatial and temporal dynamics of the epileptogenic process is still not clear completely especially the most challenging aspects of epileptology which is the anticipation of the seizure. Despite all the efforts we still don-t know how and when and why the seizure occurs. However actual studies bring strong evidence that the interictal-ictal state transition is not an abrupt phenomena. Findings also indicate that it is possible to detect a preseizure phase. Our approach is to use the neural network tool to detect interictal states and to predict from those states the upcoming seizure ( ictal state). Analysis of the EEG signal based on neural networks is used for the classification of EEG as either seizure or non-seizure. By applying prediction methods it will be possible to predict the upcoming seizure from non-seizure EEG. We will study the patients admitted to the epilepsy monitoring unit for the purpose of recording their seizures. Preictal, ictal, and post ictal EEG recordings are available on such patients for analysis The system will be induced by taking a body of samples then validate it using another. Distinct from the two first ones a third body of samples is taken to test the network for the achievement of optimum prediction. Several methods will be tried 'Backpropagation ANN' and 'RBF'.

Keywords: Artificial neural network (ANN), automatic prediction, epileptic seizures analysis, genetic algorithm.

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13458 A Research on Determining the Viability of a Job Board Website for Refugees in Kenya

Authors: Prince Mugoya, Collins Oduor Ondiek, Patrick Kanyi Wamuyu

Abstract:

Refugee Job Board Website is a web-based application that provides a platform for organizations to post jobs specifically for refugees. Organizations upload job opportunities and refugees can view them on the website. The website also allows refugees to input their skills and qualifications. The methodology used to develop this system is a waterfall (traditional) methodology. Software development tools include Brackets which will be used to code the website and PhpMyAdmin to store all the data in a database.

Keywords: Information technology, refugee, skills, utilization, economy, jobs.

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13457 A Hybrid DEA Model for the Measurement of the Enviromental Performance

Authors: A. Hadi-Vencheh, N. Shayesteh Moghadam

Abstract:

Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Since some of the environmental performance indicators cannot be controlled by companies managers, it is necessary to develop the model in a way that it could be applied when discretionary and/or non-discretionary factors were involved. In this paper, we present a semi-radial DEA approach to measuring environmental performance, which consists of non-discretionary factors. The model, then, has been applied on a real case.

Keywords: Environmental performance, efficiency, non-discretionary variables, data envelopment analysis.

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13456 'Performance-Based' Seismic Methodology and Its Application in Seismic Design of Reinforced Concrete Structures

Authors: Jelena R. Pejović, Nina N. Serdar

Abstract:

This paper presents an analysis of the “Performance-Based” seismic design method, in order to overcome the perceived disadvantages and limitations of the existing seismic design approach based on force, in engineering practice. Bearing in mind, the specificity of the earthquake as a load and the fact that the seismic resistance of the structures solely depends on its behaviour in the nonlinear field, traditional seismic design approach based on force and linear analysis is not adequate. “Performance-Based” seismic design method is based on nonlinear analysis and can be used in everyday engineering practice. This paper presents the application of this method to eight-story high reinforced concrete building with combined structural system (reinforced concrete frame structural system in one direction and reinforced concrete ductile wall system in other direction). The nonlinear time-history analysis is performed on the spatial model of the structure using program Perform 3D, where the structure is exposed to forty real earthquake records. For considered building, large number of results were obtained. It was concluded that using this method we could, with a high degree of reliability, evaluate structural behavior under earthquake. It is obtained significant differences in the response of structures to various earthquake records. Also analysis showed that frame structural system had not performed well at the effect of earthquake records on soil like sand and gravel, while a ductile wall system had a satisfactory behavior on different types of soils.

Keywords: Ductile wall, frame system, nonlinear time-history analysis, performance-based methodology, RC building.

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13455 Mechanisms of Organic Contaminants Uptake and Degradation in Plants

Authors: E.Kvesitadze, T.Sadunishvili, G.Kvesitadze

Abstract:

As a result of urbanization, the unpredictable growth of industry and transport, production of chemicals, military activities, etc. the concentration of anthropogenic toxicants spread in nature exceeds all the permissible standards. Most dangerous among these contaminants are organic compounds having great persistence, bioaccumulation, and toxicity along with our awareness of their prominent occurrence in the environment and food chain. Among natural ecological tools, plants still occupying above 40% of the world land, until recently, were considered as organisms having only a limited ecological potential, accumulating in plant biomass and partially volatilizing contaminants of different structure. However, analysis of experimental data of the last two decades revealed the essential role of plants in environment remediation due to ability to carry out intracellular degradation processes leading to partial or complete decomposition of carbon skeleton of different structure contaminants. Though, phytoremediation technologies still are in research and development, their various applications have been successfully used. The paper aims to analyze mechanisms of organic contaminants uptake and detoxification in plants, being the less studied issue in evaluation and exploration of plants potential for environment remediation.

Keywords: organic contaminants, Detoxification, metalloenzymes, plant ultrastructure.

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13454 Influence of Tool Geometry on Surface Roughness and Tool Wear When Turning AISI 304L Using Taguchi Optimisation Methodology

Authors: Salah Gariani, Taher Dao, Ahmed Lajili

Abstract:

This paper presents an experimental optimisation of surface roughness (Ra) and tool wear in the precision turning of AISI 304L alloy using a wiper and conventional cutting tools under wet cutting conditions. The machining trials were conducted based on Taguchi methodology employing an L9 orthogonal array design with four process parameters: feed rate, spindle speed, depth of cut, and cutting tool type. The experimental results were utilised to characterise the main factors affecting Ra and tool wear using the analyses of means (AOM) and variance (ANOVA). The results show that the wiper tools outperformed conventional tools in terms of surface quality and tool wear at optimal cutting conditions. The ANOVA results indicate that the main factors contributing to lower Ra are cutting tool type and feed rate, with percentage contribution ratios (PCRs) of 58.69% and 25.18% respectively. This confirms that tool type is the most significant factor affecting surface quality when turning AISI 304L. Additionally, a substantial reduction in tool wear was observed when a wiper insert was used, whereas noticeable increases in tool wear occurred when higher cutting speeds were employed for both tool types. These trends confirm the ANOVA outcomes that cutting speed has a significant effect on tool wear, with a PCR value of 39.22%, followed by tool type with a PCR of 27.40%. All machining trials generated similar continuous spiral or curl-shaped chips. A noticeable difference was found in the radius of the produced curl-shaped chips at different cutting speeds when turning AISI 304L under wet cutting conditions.

Keywords: AISI 304L alloy, conventional and wiper carbide tools, wet turning, average surface roughness, tool wear.

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