Search results for: historical data
6829 Visual Analytics in K 12 Education - Emerging Dimensions of Complexity
Authors: Linnea Stenliden
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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors within Actor-network theory (ANT). The learning conditions are found to be distinguished by broad complexity, characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.
Keywords: Analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16846828 An Energy Efficient Cluster Formation Protocol with Low Latency In Wireless Sensor Networks
Authors: A. Allirani, M. Suganthi
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Data gathering is an essential operation in wireless sensor network applications. So it requires energy efficiency techniques to increase the lifetime of the network. Similarly, clustering is also an effective technique to improve the energy efficiency and network lifetime of wireless sensor networks. In this paper, an energy efficient cluster formation protocol is proposed with the objective of achieving low energy dissipation and latency without sacrificing application specific quality. The objective is achieved by applying randomized, adaptive, self-configuring cluster formation and localized control for data transfers. It involves application - specific data processing, such as data aggregation or compression. The cluster formation algorithm allows each node to make independent decisions, so as to generate good clusters as the end. Simulation results show that the proposed protocol utilizes minimum energy and latency for cluster formation, there by reducing the overhead of the protocol.Keywords: Sensor networks, Low latency, Energy sorting protocol, data processing, Cluster formation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27296827 The Pixel Value Data Approach for Rainfall Forecasting Based on GOES-9 Satellite Image Sequence Analysis
Authors: C. Yaiprasert, K. Jaroensutasinee, M. Jaroensutasinee
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To develop a process of extracting pixel values over the using of satellite remote sensing image data in Thailand. It is a very important and effective method of forecasting rainfall. This paper presents an approach for forecasting a possible rainfall area based on pixel values from remote sensing satellite images. First, a method uses an automatic extraction process of the pixel value data from the satellite image sequence. Then, a data process is designed to enable the inference of correlations between pixel value and possible rainfall occurrences. The result, when we have a high averaged pixel value of daily water vapor data, we will also have a high amount of daily rainfall. This suggests that the amount of averaged pixel values can be used as an indicator of raining events. There are some positive associations between pixel values of daily water vapor images and the amount of daily rainfall at each rain-gauge station throughout Thailand. The proposed approach was proven to be a helpful manual for rainfall forecasting from meteorologists by which using automated analyzing and interpreting process of meteorological remote sensing data.
Keywords: Pixel values, satellite image, water vapor, rainfall, image processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18466826 Multistage Data Envelopment Analysis Model for Malmquist Productivity Index Using Grey's System Theory to Evaluate Performance of Electric Power Supply Chain in Iran
Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh
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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.
Keywords: Malmquist Index, Grey's Theory, Charnes Cooper & Rhodes (CCR) Model, network data envelopment analysis, Iran electricity power chain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5436825 Comparative Analysis of the Public Funding for Greek Universities: An Ordinal DEA/MCDM Approach
Authors: Yiannis Smirlis, Dimitris K. Despotis
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This study performs a comparative analysis of the 21 Greek Universities in terms of their public funding, awarded for covering their operating expenditure. First it introduces a DEA/MCDM model that allocates the fund into four expenditure factors in the most favorable way for each university. Then, it presents a common, consensual assessment model to reallocate the amounts, remaining in the same level of total public budget. From the analysis it derives that a number of universities cannot justify the public funding in terms of their size and operational workload. For them, the sufficient reduction of their public funding amount is estimated as a future target. Due to the lack of precise data for a number of expenditure criteria, the analysis is based on a mixed crisp-ordinal data set.Keywords: Data envelopment analysis, Greek universities, operating expenditures, ordinal data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17456824 Inversion of Electrical Resistivity Data: A Review
Authors: Shrey Sharma, Gunjan Kumar Verma
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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.Keywords: Resistivity, inversion, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 60476823 Increasing the System Availability of Data Centers by Using Virtualization Technologies
Authors: Chris Ewe, Naoum Jamous, Holger Schrödl
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Like most entrepreneurs, data center operators pursue goals such as profit-maximization, improvement of the company’s reputation or basically to exist on the market. Part of those aims is to guarantee a given quality of service. Quality characteristics are specified in a contract called the service level agreement. Central part of this agreement is non-functional properties of an IT service. The system availability is one of the most important properties as it will be shown in this paper. To comply with availability requirements, data center operators can use virtualization technologies. A clear model to assess the effect of virtualization functions on the parts of a data center in relation to the system availability is still missing. This paper aims to introduce a basic model that shows these connections, and consider if the identified effects are positive or negative. Thus, this work also points out possible disadvantages of the technology. In consequence, the paper shows opportunities as well as risks of data center virtualization in relation to system availability.
Keywords: Availability, cloud computing IT service, quality of service, service level agreement, virtualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9816822 Data Oriented Modeling of Uniform Random Variable: Applied Approach
Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mirkamal Mirnia, Mohamad Teshnelab, Ehsan Shahamatnia
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In this paper we introduce new data oriented modeling of uniform random variable well-matched with computing systems. Due to this conformity with current computers structure, this modeling will be efficiently used in statistical inference.Keywords: Uniform random variable, Data oriented modeling, Statistical inference, Prodigraph, Statistically complete tree, Uniformdigital probability digraph, Uniform n-complete probability tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16126821 Topic Modeling Using Latent Dirichlet Allocation and Latent Semantic Indexing on South African Telco Twitter Data
Authors: Phumelele P. Kubheka, Pius A. Owolawi, Gbolahan Aiyetoro
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Twitter is one of the most popular social media platforms where users share their opinions on different subjects. Twitter can be considered a great source for mining text due to the high volumes of data generated through the platform daily. Many industries such as telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model in this experiment. A higher topic coherence score indicates better performance of the model.
Keywords: Big data, latent Dirichlet allocation, latent semantic indexing, Telco, topic modeling, Twitter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4276820 Prediction of Compressive Strength of SCC Containing Bottom Ash using Artificial Neural Networks
Authors: Yogesh Aggarwal, Paratibha Aggarwal
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The paper presents a comparative performance of the models developed to predict 28 days compressive strengths using neural network techniques for data taken from literature (ANN-I) and data developed experimentally for SCC containing bottom ash as partial replacement of fine aggregates (ANN-II). The data used in the models are arranged in the format of six and eight input parameters that cover the contents of cement, sand, coarse aggregate, fly ash as partial replacement of cement, bottom ash as partial replacement of sand, water and water/powder ratio, superplasticizer dosage and an output parameter that is 28-days compressive strength and compressive strengths at 7 days, 28 days, 90 days and 365 days, respectively for ANN-I and ANN-II. The importance of different input parameters is also given for predicting the strengths at various ages using neural network. The model developed from literature data could be easily extended to the experimental data, with bottom ash as partial replacement of sand with some modifications.Keywords: Self compacting concrete, bottom ash, strength, prediction, neural network, importance factor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22096819 The Dialectical Unity of Capital and Non-Capital: The Role of Overpopulation in Popular Rebellion Today
Authors: Wim Dierckxsens, Andrés Piqueras
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Throughout its history, Capital has established a decisive form of discrimination that has effectively strengthened its power against Labor: discrimination between an endogenous labor force (integrated, with certain guarantees and rights in the capitalist nexus) and an exogenous labor force (yet to be incorporated or incorporated as ‘heterochthonous’, without such guarantees and rights). We refer to the historical incorporation of the exogenous population from the non-capitalist to the capitalist nexus (with the consequent replaceability of the endogenous labor force) as absolute mobility.
The more possibilities Capital has of accessing a population in the non-capitalist nexus and of being able to incorporate it through absolute mobility into the capitalist nexus, the greater its unilaterality or class domination. In contrast, when these possibilities run dry, Capital is more inclined towards reformism or negotiation.
However, this absolute mobility has historically been combined with relative mobility of the labor force, which includes various processes of which labor force migration is a fundamental component.
This paper holds that both types of mobility are at the core of class struggles.
Keywords: Absolute mobility, capital-labor antagonism, relative mobility, substitutability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12136818 An Integrated Model of Urban Conservation and Revitalization from the Point of Immigration and Its Effects on Reyhan Urban Site in Turkey as a Case Study
Authors: Ozlem Koprulu Bagbanci, M.Bilal Bagbanci
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This paper presents the effects of migration at the urban sites with an integrated model under the sustainable local development policies for the conservation and revitalization of the site areas as a case at Reyhan heritage site in Bursa. It is known as the “City of immigrants" because of its richness of cultural plurality. The city has always regarded the dynamic impact of immigration as a positive contribution. As a result of this situation, the city created the earliest urbanization practices: being the first capital city of the Ottoman Empire. Bursa created the first modern movement practices and set the first Organized Industrial Zone. The most important aim of the study is to be offer a model for the similar areas with the context of conservation and revitalization of the historical areas, subjected to the local integrated sustainable development policies of local goverments.Keywords: integration, migration, local policies, sustainability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17286817 A Review: Comparative Analysis of Different Categorical Data Clustering Ensemble Methods
Authors: S. Sarumathi, N. Shanthi, M. Sharmila
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Over the past epoch a rampant amount of work has been done in the data clustering research under the unsupervised learning technique in Data mining. Furthermore several algorithms and methods have been proposed focusing on clustering different data types, representation of cluster models, and accuracy rates of the clusters. However no single clustering algorithm proves to be the most efficient in providing best results. Accordingly in order to find the solution to this issue a new technique, called Cluster ensemble method was bloomed. This cluster ensemble is a good alternative approach for facing the cluster analysis problem. The main hope of the cluster ensemble is to merge different clustering solutions in such a way to achieve accuracy and to improve the quality of individual data clustering. Due to the substantial and unremitting development of new methods in the sphere of data mining and also the incessant interest in inventing new algorithms, makes obligatory to scrutinize a critical analysis of the existing techniques and the future novelty. This paper exposes the comparative study of different cluster ensemble methods along with their features, systematic working process and the average accuracy and error rates of each ensemble methods. Consequently this speculative and comprehensive analysis will be very useful for the community of clustering practitioners and also helps in deciding the most suitable one to rectify the problem in hand.
Keywords: Clustering, Cluster Ensemble methods, Co-association matrix, Consensus function, Median partition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25876816 Application of Data Envelopment Analysis to Assess Quality Management Efficiency
Authors: Chuen Tse Kuah, Kuan Yew Wong, Farzad Behrouzi
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This paper is aimed to give an illustration on the application of Data Envelopment Analysis (DEA) as a tool to assess Quality Management (QM) efficiency. A variant of DEA, slack based measure (SBM) is used for this purpose. From this study, it is found that DEA is suitable to measure QM efficiency and give improvement suggestions to the inefficient QM.Keywords: Quality Management, Data Envelopment Analysis, Slack Based Measure, Efficiency Measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20736815 Exploring the Correlation between Population Distribution and Urban Heat Island under Urban Data: Taking Shenzhen Urban Heat Island as an Example
Authors: Wang Yang
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Shenzhen is a modern city of China's reform and opening-up policy, the development of urban morphology has been established on the administration of the Chinese government. This city`s planning paradigm is primarily affected by the spatial structure and human behavior. The subjective urban agglomeration center is divided into several groups and centers. In comparisons of this effect, the city development law has better to be neglected. With the continuous development of the internet, extensive data technology has been introduced in China. Data mining and data analysis has become important tools in municipal research. Data mining has been utilized to improve data cleaning such as receiving business data, traffic data and population data. Prior to data mining, government data were collected by traditional means, then were analyzed using city-relationship research, delaying the timeliness of urban development, especially for the contemporary city. Data update speed is very fast and based on the Internet. The city's point of interest (POI) in the excavation serves as data source affecting the city design, while satellite remote sensing is used as a reference object, city analysis is conducted in both directions, the administrative paradigm of government is broken and urban research is restored. Therefore, the use of data mining in urban analysis is very important. The satellite remote sensing data of the Shenzhen city in July 2018 were measured by the satellite Modis sensor and can be utilized to perform land surface temperature inversion, and analyze city heat island distribution of Shenzhen. This article acquired and classified the data from Shenzhen by using Data crawler technology. Data of Shenzhen heat island and interest points were simulated and analyzed in the GIS platform to discover the main features of functional equivalent distribution influence. Shenzhen is located in the east-west area of China. The city’s main streets are also determined according to the direction of city development. Therefore, it is determined that the functional area of the city is also distributed in the east-west direction. The urban heat island can express the heat map according to the functional urban area. Regional POI has correspondence. The research result clearly explains that the distribution of the urban heat island and the distribution of urban POIs are one-to-one correspondence. Urban heat island is primarily influenced by the properties of the underlying surface, avoiding the impact of urban climate. Using urban POIs as analysis object, the distribution of municipal POIs and population aggregation are closely connected, so that the distribution of the population corresponded with the distribution of the urban heat island.
Keywords: POI, satellite remote sensing, the population distribution, urban heat island thermal map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8996814 Prototype of a Federative Factory Data Management for the Support of Factory Planning Processes
Authors: Christian Mosch, Reiner Anderl, Antonio Álvaro de Assis Moura, Klaus Schützer
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Due to short product life cycles, increasing variety of products and short cycles of leap innovations manufacturing companies have to increase the flexibility of factory structures. Flexibility of factory structures is based on defined factory planning processes in which product, process and resource data of various partial domains have to be considered. Thus factory planning processes can be characterized as iterative, interdisciplinary and participative processes [1]. To support interdisciplinary and participative character of planning processes, a federative factory data management (FFDM) as a holistic solution will be described. FFDM is already implemented in form of a prototype. The interim results of the development of FFDM will be shown in this paper. The principles are the extracting of product, process and resource data from documents of various partial domains providing as web services on a server. The described data can be requested by the factory planner by using a FFDM-browser.Keywords: BRAGECRIM, Factory Planning Process, FactoryData Management, Web Services
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14796813 Task-Based Language Teaching: A Paradigm Shift in ESL/EFL Teaching and Learning: A Case Study-Based Approach
Authors: Zehra Sultan
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The study is based on the Task-based Language Teaching (TBLT) approach which is found to be very effective in the EFL/ESL classroom. This approach engages learners to acquire the usage of authentic language skills by interacting with the real world through a sequence of pedagogical tasks. The use of technology enhances the effectiveness of this approach. This study throws light on the historical background of TBLT, and its efficacy in the EFL /ESL classroom. In addition, this study precisely talks about the implementation of this approach in the General Foundation Program (GFP) of Muscat College, Oman. It furnishes the list of the pedagogical tasks embedded in the language curriculum of the GFP which are skillfully allied to the College graduate attributes. Moreover, the study also discusses the challenges pertaining to this approach from the point of view of teachers, students and its classroom application. Additionally, the operational success of this methodology is gauged through formative assessments of the GFP which is apparent in the students’ progress.
Keywords: Task-based language teaching, authentic language, communicative approach, real world activities, ESL/EFL activities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9056812 Analysis of a WDM System for Tanzania
Authors: Shaban Pazi, Chris Chatwin, Rupert Young, Philip Birch
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Internet infrastructures in most places of the world have been supported by the advancement of optical fiber technology, most notably wavelength division multiplexing (WDM) system. Optical technology by means of WDM system has revolutionized long distance data transport and has resulted in high data capacity, cost reductions, extremely low bit error rate, and operational simplification of the overall Internet infrastructure. This paper analyses and compares the system impairments, which occur at data transmission rates of 2.5Gb/s and 10 Gb/s per wavelength channel in our proposed optical WDM system for Internet infrastructure in Tanzania. The results show that the data transmission rate of 2.5 Gb/s has minimum system impairments compared with a rate of 10 Gb/s per wavelength channel, and achieves a sufficient system performance to provide a good Internet access service.Keywords: Internet infrastructure, WDM system, standard single mode fibers, system impairments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16496811 Comparison of Data Reduction Algorithms for Image-Based Point Cloud Derived Digital Terrain Models
Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu
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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.
Keywords: DTM, unmanned aerial vehicle, UAV, random, Kriging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7866810 Frequent Itemset Mining Using Rough-Sets
Authors: Usman Qamar, Younus Javed
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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and roughsets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.
Keywords: Rough-sets, Classification, Feature Selection, Entropy, Outliers, Frequent itemset mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24256809 Analysis of Cross-Sectional and Retrograde Data on the Prevalence of Marginal Gingivitis
Authors: Ilma Robo, Saimir Heta, Nedja Hysi, Vera Ostreni
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Introduction: Marginal gingivitis is a disease with considerable frequency among patients who present routinely for periodontal control and treatment. In fact, this disease may not have alarming symptoms in patients and may go unnoticed by themselves when personal hygiene conditions are optimal. The aim of this study was to collect retrograde data on the prevalence of marginal gingiva in the respective group of patients, evaluated according to specific periodontal diagnostic tools. Materials and methods: The study was conducted in two patient groups. The first group was with 34 patients, during December 2019-January 2020, and the second group was with 64 patients during 2010-2018 (each year in the mentioned monthly period). Bacterial plaque index, hemorrhage index, amount of gingival fluid, presence of xerostomia and candidiasis were recorded in patients. Results: Analysis of the collected data showed that susceptibility to marginal gingivitis shows higher values according to retrograde data, compared to cross-sectional ones. Susceptibility to candidiasis and the occurrence of xerostomia, even in the combination of both pathologies, as risk factors for the occurrence of marginal gingivitis, show higher values according to retrograde data. The female are presented with a reduced bacterial plaque index than the males, but more importantly, this index in the females is also associated with a reduced index of gingival hemorrhage, in contrast to the males. Conclusions: Cross-sectional data show that the prevalence of marginal gingivitis is more reduced, compared to retrograde data, based on the hemorrhage index and the bacterial plaque index together. Changes in production in the amount of gingival fluid show a higher prevalence of marginal gingivitis in cross-sectional data than in retrograde data; this is based on the sophistication of the way data are recorded, which evolves over time and also based on professional sensitivity to this phenomenon.
Keywords: Marginal gingivitis, cross-sectional, retrograde, prevalence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4886808 Reducing SAGE Data Using Genetic Algorithms
Authors: Cheng-Hong Yang, Tsung-Mu Shih, Li-Yeh Chuang
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Serial Analysis of Gene Expression is a powerful quantification technique for generating cell or tissue gene expression data. The profile of the gene expression of cell or tissue in several different states is difficult for biologists to analyze because of the large number of genes typically involved. However, feature selection in machine learning can successfully reduce this problem. The method allows reducing the features (genes) in specific SAGE data, and determines only relevant genes. In this study, we used a genetic algorithm to implement feature selection, and evaluate the classification accuracy of the selected features with the K-nearest neighbor method. In order to validate the proposed method, we used two SAGE data sets for testing. The results of this study conclusively prove that the number of features of the original SAGE data set can be significantly reduced and higher classification accuracy can be achieved.Keywords: Serial Analysis of Gene Expression, Feature selection, Genetic Algorithm, K-nearest neighbor method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15946807 Growing Self Organising Map Based Exploratory Analysis of Text Data
Authors: Sumith Matharage, Damminda Alahakoon
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Textual data plays an important role in the modern world. The possibilities of applying data mining techniques to uncover hidden information present in large volumes of text collections is immense. The Growing Self Organizing Map (GSOM) is a highly successful member of the Self Organising Map family and has been used as a clustering and visualisation tool across wide range of disciplines to discover hidden patterns present in the data. A comprehensive analysis of the GSOM’s capabilities as a text clustering and visualisation tool has so far not been published. These functionalities, namely map visualisation capabilities, automatic cluster identification and hierarchical clustering capabilities are presented in this paper and are further demonstrated with experiments on a benchmark text corpus.
Keywords: Text Clustering, Growing Self Organizing Map, Automatic Cluster Identification, Hierarchical Clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19776806 The American Christian Right Women’s Advocacy Groups and US Foreign Policy
Authors: Mohd Afandi Salleh
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The paper examines two women advocacy groups of the American Christian Right, namely: Concerned Women for America (CWA) and Eagle Forum. Focus will be placed on their interests in American foreign policy and global social policy particularly during the George W. Bush administration. It examines the organizations’ historical backgrounds, and study their agendas, issues and forms of international engagement which relate to American foreign policy. The paper shows that the Christian Right movement is not a monolithic movement in term of its focus, objectives or activism. Despite their diversity, various actions of these advocacy groups have strengthened the role of the Christian Right in exerting its influence on US foreign policy. Finally, it contends that, although traditionally the Christian Right advocacy groups’ motives for activism are strongly based on the Bible and Judeo–Christian values, the arguments and ideas behind their present struggle are presented in a very nationalistic, secular and pragmatic vein.
Keywords: Christian Right, Concerned Women for America, Eagle Forum, Global social policy, US foreign policy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16816805 Impact of Fixation Time on Subjective Video Quality Metric: a New Proposal for Lossy Compression Impairment Assessment
Authors: M. G. Albanesi, R. Amadeo
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In this paper, a new approach for quality assessment tasks in lossy compressed digital video is proposed. The research activity is based on the visual fixation data recorded by an eye tracker. The method involved both a new paradigm for subjective quality evaluation and the subsequent statistical analysis to match subjective scores provided by the observer to the data obtained from the eye tracker experiments. The study brings improvements to the state of the art, as it solves some problems highlighted in literature. The experiments prove that data obtained from an eye tracker can be used to classify videos according to the level of impairment due to compression. The paper presents the methodology, the experimental results and their interpretation. Conclusions suggest that the eye tracker can be useful in quality assessment, if data are collected and analyzed in a proper way.Keywords: eye tracker, video compression, video qualityassessment, visual attention
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15926804 Reuse of Huge Industrial Areas
Authors: Martina Perinkova, Lenka Kolarcikova, Marketa Twrda
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Brownfields are one of the most important problems that must be solved by today's cities. The topic of this article is description of developing a comprehensive transformation of postindustrial area of the former iron factory national cultural heritage lower Vítkovice. City of Ostrava used to be industrial superpower of the Czechoslovak Republic, especially in the area of coal mining and iron production, after declining industrial production and mining in the 80s left many unused areas of former factories generally brownfields and backfields. Since the late 90s we are observing how the city officials or private entities seeking to remedy this situation. Regeneration of brownfields is a very expensive and long-term process. The area is now rebuilt for tourists and residents of the city in the entertainment, cultural, and social center. It was necessary do the reconstruction of the industrial monuments. Equally important was the construction of new buildings, which helped reusing of the entire complex. This is a unique example of transformation of technical monuments and completion of necessary new objects, so that the area could start working again and reintegrate back into the urban system.Keywords: Brownfields, conversion, historical and industrial buildings, reconstruction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15646803 Reliable Consensus Problem for Multi-Agent Systems with Sampled-Data
Authors: S. H. Lee, M. J. Park, O. M. Kwon
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In this paper, reliable consensus of multi-agent systems with sampled-data is investigated. By using a suitable Lyapunov-Krasovskii functional and some techniques such as Wirtinger Inequality, Schur Complement and Kronecker Product, the results of such system are obtained by solving a set of Linear Matrix Inequalities (LMIs). One numerical example is included to show the effectiveness of the proposed criteria.
Keywords: Multi-agent, Linear Matrix Inequalities (LMIs), Kronecker Product, Sampled-Data, Lyapunov method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17306802 Deep-Learning Based Approach to Facial Emotion Recognition Through Convolutional Neural Network
Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah
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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. However, accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER benefiting from deep learning, especially CNN and VGG16. First, the data are pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.
Keywords: CNN, deep-learning, facial emotion recognition, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6766801 Balanced k-Anonymization
Authors: Sabah S. Al-Fedaghi
Abstract:
The technique of k-anonymization has been proposed to obfuscate private data through associating it with at least k identities. This paper investigates the basic tabular structures that underline the notion of k-anonymization using cell suppression. These structures are studied under idealized conditions to identify the essential features of the k-anonymization notion. We optimize data kanonymization through requiring a minimum number of anonymized values that are balanced over all columns and rows. We study the relationship between the sizes of the anonymized tables, the value k, and the number of attributes. This study has a theoretical value through contributing to develop a mathematical foundation of the kanonymization concept. Its practical significance is still to be investigated.Keywords: Balanced tables, k-anonymization, private data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12136800 Exploring Influence Range of Tainan City Using Electronic Toll Collection Big Data
Authors: Chen Chou, Feng-Tyan Lin
Abstract:
Big Data has been attracted a lot of attentions in many fields for analyzing research issues based on a large number of maternal data. Electronic Toll Collection (ETC) is one of Intelligent Transportation System (ITS) applications in Taiwan, used to record starting point, end point, distance and travel time of vehicle on the national freeway. This study, taking advantage of ETC big data, combined with urban planning theory, attempts to explore various phenomena of inter-city transportation activities. ETC, one of government's open data, is numerous, complete and quick-update. One may recall that living area has been delimited with location, population, area and subjective consciousness. However, these factors cannot appropriately reflect what people’s movement path is in daily life. In this study, the concept of "Living Area" is replaced by "Influence Range" to show dynamic and variation with time and purposes of activities. This study uses data mining with Python and Excel, and visualizes the number of trips with GIS to explore influence range of Tainan city and the purpose of trips, and discuss living area delimited in current. It dialogues between the concepts of "Central Place Theory" and "Living Area", presents the new point of view, integrates the application of big data, urban planning and transportation. The finding will be valuable for resource allocation and land apportionment of spatial planning.
Keywords: Big Data, ITS, influence range, living area, central place theory, visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 967