226 research outputs found

    Geovisualization Using HTML5 : a case study to improve animations of historical geographic data

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    Popular science Visualize geographic data Using HTML5 The Scanian Economic-Demographic Database (SEDD) has been assembled by the Centre for Economic Demography (CED), Lund University. It contains demographic and economic information of Scania from the 17th century until the present. The SEDD database has been integrated with geographic data, which are digitized from four independent historical maps. To help the users well understand these data, a web mapping application called SEDD Map has been developed and tested. The previous version of SEDD Map is constructed using Silverlight plugin. It cannot run on most popular portable devices. As Hypertext Markup Languages (HTML) continue to develop, a recent version, HTML5, was published in 2012. It aims to support the latest multimedia formats and reduce the need for plugins. So, to improve the compatibility of SEDD Map, this work using HTML5 to developed a new version of SEDD Map. Before we constructed the new version of SEDD Map, a set of web mapping applications and programs were evaluated. From this evaluation and comparison, we found that SEDD Map could be improved in many area, such as improving the animation of historical geographic data. Animation is a useful tool when presenting historical data. The geographic data in SEDD Map are taken from four independent historical maps. To visualize geographic data as an animation, we need to create a time sense sequential dataset. In this study, we used linear interpolation and the four historical maps as start years and end years to simulate 159 maps to visualize the geographic data as animations. From this study, we found that: The commonly used web mapping applications for investigating demographic data contain functions, such as interactive visualization, statistical graphics, basic map tools, animations, etc; HTML5 can replace (and improve) the used of Silverlight for web mapping; Animations can be generated (filling in what is missing is to improve the data sets).The Scanian Economic-Demographic Database (SEDD) has been assembled by the Centre for Economic Demography (CED), Lund University. It contains information about the demographic and economic conditions of people that have lived in 5 parishes in Scania from the 17th century until the present. The SEDD database has been integrated with geographic data, which are digitized from four independent historical maps. To visualize and analyze these data, a GIS based web mapping application called SEDD Map has been developed and tested. The previous version of SEDD Map is constructed using Silverlight. As a result, it only can be used on computers which have installed the Silverlight plugin. As Hypertext Markup Languages (HTML) continue to develop, a recent version, HTML5, was published in 2012. It aims to support the latest multimedia formats and reduce the need for plugins. In this study, we use HTML5, Cascading Style Sheets (CSS3), JavaScript and the ArcGIS API for JavaScript to create a new version of SEDD Map to visualize data stored in the SEDD database. Before we constructed the new version of SEDD Map, a set of web mapping applications and programs were evaluated by the requirements which were needed to create the new version of SEDD Map. From this evaluation and comparison, we found that SEDD Map could be improved in many area, such as improving the animation of historical geographic data. Animation is a useful tool when presenting historical data. The geographic data in SEDD Map are taken from four independent historical maps. To visualize geographic data as an animation, we need to create a time sense sequential dataset, which is done in a parallel project. In this study, we evaluate techniques for data animation. We used linear interpolation and the four historical maps as start years and end years to simulate 159 maps to visualize the geographic data as animations. The conclusions are as follows: 1) The commonly used web mapping applications for investigating demographic data contain functions, such as interactive visualization, statistical graphics, basic map tools, animations, etc. 2) HTML5 can replace (and improve) the used of Silverlight for web mapping. 3) Animations can be generated (filling in what is missing is to improve the data sets)

    Comparative analysis of classification techniques for network fault management

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    Network troubleshooting is a significant process. Many studies were conducted about it. The first step in the troubleshooting procedures is represented in collecting information. It's collected in order to identify the problems. Syslog messages which are sent by almost all network devices include a massive amount of data that concern the network problems. Based on several studies, it was found that analyzing syslog data (which) can be a guideline for network problems and their causes. The detection of network problems can become more efficient if the detected problems have been classified based on the network layers. Classifying syslog data requires identifying the syslog messages that describe the network problems for each layer. It also requires taking into account the formats of syslog for vendors' devices. The present study aimed to propose a method for classifying the syslog messages which identify the network problem.This classification is conducted based on the network layers. This method uses data mining instrument to classify the syslog messages. The description part of the syslog message was used for carrying out the classification process.The relevant syslog messages were identified. The features were then selected to train the classifiers. Six classification algorithms were learned; LibSVM, SMO, KNN, Naïve Bayes, J48, and Random Forest. A real data set was obtained from an educational network device. This dataset was used for the prediction stage. It was found that that LibSVM outperforms other classifiers in terms of the probability rate of the classified instances where it was in the range of 89.90%-32.80%. Furthermore, the validation results indicate that the probability rate of the correctly classified instances is >70%. © 2020 Turkiye Klinikleri. All rights reserved

    Interactive Learning System for E-commerce, Technopreneursip

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    This report is based on an ongoing study about Interactive Learning System for E-commerce, Technopreneurship. As the knowledge and information is increasingly being published or converted into a digital form, one of the greatest challenges is designing systems that enable users to find what they need. This is because, today, people are to busy and so they have limited time to go to the library to find the desired books about e-commerce and technopreneurship. The project proposed is to build a new enhanced system that would help users, including academic institutions. In developing this system, the tools that will be involved include adopting Open Source technology and Knowledge Management technology. Along the project timeline, various study and research must be made to ensure the successful of this project. This includes the study of using the software that will be used which are; Macromedia Flash, mySQL and PHP. Still, a few other elements need to be considering in this system to ensure that it provides the fullest functions. Therefore, the project is basically tries to enhance the features and functions of the existing e-commerce advice web site. The main focus in this project is that the web site will have a search engine to let the users look for their favorite topics, to let the user have another choice for building the database. The learning system will provide a few question and quizzes. When the solutions are complete, it is hoped that the system will run with its objectives

    Interactive Learning System forE-commerce, Technopreneursip

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    This report is based on an ongoing study about Interactive Learning System for Ecommerce, Technopreneurship. As the knowledge and information is increasingly being published or converted into a digital form, one of the greatest challenges is designing systems that enable users to fmd what they need. This is because, today, people are to busy and so they have limited time to go to the library to find the desired books about ecommerce and technopreneurship. The project proposed is to build a new enhanced system that would help users, including academic institutions. In developing this system, the tools that will be involved include adopting Open Source technology and Knowledge Management technology. Along the project timeline, various study and research must be made to ensure the successful of this project. This includes the study of using the software that will be used which are; Macromedia Flash, mySQL and PHP. Still, a few other elements need to be considering in this system to ensure that it provides the fullest functions. Therefore, the project is basically tries to enhance the features and functions of the existing e"commerce advice web site. The main focus in this project is that the web site will have a search engine to let the users look for their favorite topics, to let the user have another choice for building the database. The learning system will provide a few question and quizzes. When the solutions are complete, it is hoped that the system will run with its objectives

    Fine Scale Simulation of Fractured Reservoirs: Applications and Comparison

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    Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption

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    استرجاع الصور المستند إلى المحتوى (CBIR) هو تقنية تستخدم لاسترداد الصور من قاعدة بيانات الصور. ومع ذلك، فإن عملية CBIR تعاني من دقة أقل في استرداد الصور من قاعدة بيانات صور واسعة النطاق وضمان خصوصية الصور. تهدف هذه الورقة إلى معالجة قضايا الدقة باستخدام تقنيات التعلم العميق كطريقة CNN. أيضًا، توفير الخصوصية اللازمة للصور باستخدام طرق تشفير متماثلة تمامًا بواسطة Cheon و Kim و Kim و Song (CKKS). ولتحقيق هذه الأهداف تم اقتراح نظام RCNN_CKKS يتضمن جزأين. يستخرج الجزء الأول (المعالجة دون اتصال بالإنترنت–) لاستخراج الخصائص العالية المستوى استنادًا إلى طبقة التسطيح في شبكة عصبية تلافيفية (CNN) ثم يخزن هذه الميزات في مجموعة بيانات جديدة. في الجزء الثاني (المعالجة عبر الإنترنت) ، يرسل العميل الصورة المشفرة إلى الخادم ، والتي تعتمد على نموذج CNN المدرب لاستخراج ميزات الصورة المرسلة. بعد ذلك، تتم مقارنة الميزات المستخرجة مع الميزات المخزنة باستخدام طريقة Hamming Distance لاسترداد جميع الصور المتشابهة. أخيرًا، يقوم الخادم بتشفير جميع الصور المسترجعة وإرسالها إلى العميل. كانت نتائج التعلم العميق على الصور العادية 97.94٪ للتصنيف و98.94٪ للصور المسترجعة. في الوقت نفسه، تم استخدام اختبار NIST للتحقق من أمان CKKS عند تطبيقه على مجموعة بيانات المعهد الكندي للأبحاث المتقدمة (CIFAR-10). من خلال هذه النتائج، استنتج الباحثون أن التعلم العميق هو وسيلة فعالة لاستعادة الصور وأن طريقة CKKS مناسبة لحماية خصوصية الصورة.A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a new dataset. In the second part (online processing), the client sends the encrypted image to the server, which depends on the CNN model trained to extract features of the sent image. Next, the extracted features are compared with the stored features using a Hamming distance method to retrieve all similar images. Finally, the server encrypts all retrieved images and sends them to the client. Deep-learning results on plain images were 97.94% for classification and 98.94% for retriever images. At the same time, the NIST test was used to check the security of CKKS when applied to Canadian Institute for Advanced Research (CIFAR-10) dataset. Through these results, researchers conclude that deep learning is an effective method for image retrieval and that a CKKS method is appropriate for image privacy protection

    Adversarial Learning of Privacy-Preserving and Task-Oriented Representations

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    Data privacy has emerged as an important issue as data-driven deep learning has been an essential component of modern machine learning systems. For instance, there could be a potential privacy risk of machine learning systems via the model inversion attack, whose goal is to reconstruct the input data from the latent representation of deep networks. Our work aims at learning a privacy-preserving and task-oriented representation to defend against such model inversion attacks. Specifically, we propose an adversarial reconstruction learning framework that prevents the latent representations decoded into original input data. By simulating the expected behavior of adversary, our framework is realized by minimizing the negative pixel reconstruction loss or the negative feature reconstruction (i.e., perceptual distance) loss. We validate the proposed method on face attribute prediction, showing that our method allows protecting visual privacy with a small decrease in utility performance. In addition, we show the utility-privacy trade-off with different choices of hyperparameter for negative perceptual distance loss at training, allowing service providers to determine the right level of privacy-protection with a certain utility performance. Moreover, we provide an extensive study with different selections of features, tasks, and the data to further analyze their influence on privacy protection

    A high performance wireless fieldbus in industrial multimedia-related environment

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    This paper summarises the most important solutions that have emerged from the work carried out by our team within the framework of the EU (IST-1999-11316) project RFieldbus - High Performance Wireless Fieldbus in Industrial Multimedia-Related Environment. Within this project, Profibus was chosen as the fieldbus platform. Essentially, extensions to the current Profibus standard are being developed in order to provide Profibus with wireless, mobility and industrialmultimedia capabilities. In fact, providing these extensions means fulfilling strong requirements, namely to encompass the communication between wired (currently available) and wireless/mobile devices and to support real-time control traffic and multimedia traffic in the same network.Comissão Europei
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