957 resultados para XML HTML CSS JavaScript jQuery Cordova Android eLearning mLearning IncidentalLearning eLocal Gamification Geolocalizzazione


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In the past decade there has been massive growth of data on the internet. Many people rely on XML based RSS feeds to receive updates from websites. In this paper, we propose a method for managing the RSS feeds from various news websites. A web service is developed to deliver filtered news items from RSS feeds to a mobile client. Each news item is indexed, subsequently, the indexes are used for filtering news items. Indexing is done in two steps. First, classical text categorization algorithms are used to assign a category to each news item, second, geoparsing is used to assign geolocation data to each news item. An android application is developed to access filtered news items by consuming the proposed web service. A prototype is implemented using Rapid miner 5.0 as the data mining tool and SVM as the classification algorithm. Geoparsing and geocoding web services, and Android API are used to implement location-based access to news items. Experimental results prove that the proposed approach is effective and saves a significant amount of information overload processing time.

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Content authenticity and correctness is one of the important challenges in eLearning as there can be many solutions for one specific problem in the cyber space. Therefore, we feel the necessity of mapping problem to solutions using graph partition and weighted bipartite matching. This paper presents a novel architecture and methodology for a personal eLearning system called PELS that is developed by us. We also present an efficient algorithm to partition question-answer (QA) space and explore best possible solution to a particular problem. Our approach can be efficiently applied to social eLearning space where there is one-to-many and many-to-many relationship with a level of bonding. The main advantage of our approach is that we use QA ranking by adjusted edge weights provided by subject matter experts (SME) or expert database. Finally, we use statistical methods called confidence interval and hypothesis test on the data to check the reliability and dependability of the quality of results.

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Content authenticity and correctness is one of the important challenges in eLearning as there can be many solutions to one specific problem in cyber space. Therefore, the authors feel it is necessary to map problems to solutions using graph partition and weighted bipartite matching. This article proposes an efficient algorithm to partition question-answer (QA) space and explores the best possible solution to a particular problem. The approach described can be efficiently applied to social eLearning space where there are one-to-many and many-to-many relationships with a level of bonding. The main advantage of this approach is that it uses QA ranking by adjusted edge weights provided by subject-matter experts or the authors' expert database.

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This article explores Don DeLillo's literary activism through Arendtian perspectives to investigate what the demise of literature's relevance, specifically in a political context, may mean in the current era of an increasingly complex and conflicting 'web of human relationships'.  In that it is accepted that narrative has a particular ability to reveal insights as prelinguistic elements that are distinct from all we are able to access through our limited human perceptions, it remarks the Lacanian paradox that if being is in excess of language, then language is the medium by which this is accessed in the world. For DeLillo, writers may be under threat in a dynamic but destabilizing era, their art superceded by technology and fundamentalist terrorism, however, as suggested in Mao II, this renders the writer all the more necessary.  It is at the point at which the writer has nothing to say or is under duress to say noting, that a human crisis is reached. I ask, do current forms of political pressure to censure literature constitute a further diminishing of the Arendtian political public domain in which speech as action has primacy?

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The Android platform uses a permission system model to allow users and developers to regulate access to private information and system resources required by applications. Permissions have been proved to be useful for inferring behaviors and characteristics of an application. In this paper, a novel method to extract contrasting permission patterns for clean and malicious applications is proposed. Contrary to existing work, both required and used permissions were considered when discovering the patterns. We evaluated our methodology on a clean and a malware dataset, each comprising of 1227 applications. Our empirical results suggest that our permission patterns can capture key differences between clean and malicious applications, which can assist in characterizing these two types of applications.

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Regular expressions are used to parse textual data to match patterns and extract variables. They have been implemented in a vast number of programming languages with a significant quantity of research devoted to improving their operational efficiency. However, regular expressions are limited to finding linear matches. Little research has been done in the field of object-oriented results which would allow textual or binary data to be converted to multi-layered objects. This is significantly relevant as many of todaypsilas data formats are object-based. This paper extends our previous work by detailing an algorithmic approach to perform object-oriented parsing, and provides an initial study of benchmarks of the algorithms of our contribution

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Android is a new generation of an open operating system directed at mobile devices that are carried every day. The openness of this architecture is leading to new applications and opportunities including a host of multimedia services, new interfaces and browsers, multitasking including support for wireless local, personal and wide area networking services. Security with mobility and wireless connectivity thus becomes even more important with all these exciting developments. Vital security issues such as leakage of private information, file stealing and spambots abound in networks in practice and Android networks continue to be subject to these same families of vulnerabilities. This paper provides a demonstration of such vulnerabilities in spite of the best efforts of designers and implementers. In particular it describes examples of data leakage and file stealing (address books, contact lists, SMS messages, pictures) as well as demonstrating how Android devices can create spambots. © 2013 IEEE.

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Recent studies have determined that many Android applications in both official and non-official online markets expose details of the users' smartphones without user consent. In this paper, we explain why such applications leak, how they leak and where the data is leaked to. In order to achieve this, we combine static and dynamic analysis to examine Java classes and application behaviour for a set of popular, clean applications from the Finance and Games categories. We observed that all the applications in our data set which leaked information (10%) had third-party advertising libraries embedded in their respective Java packages.

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On Friday evening I saw one of the finest theatre performances from an actor. Her subtle movements, her natural cadence, her ability to portray her character in a way that demonstrated diligent devotion, careful analysis and measured construction, was simply awe-inspiring. Which actor gave this fine performance? It was an android.

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An Android application uses a permission system to regulate the access to system resources and users' privacy-relevant information. Existing works have demonstrated several techniques to study the required permissions declared by the developers, but little attention has been paid towards used permissions. Besides, no specific permission combination is identified to be effective for malware detection. To fill these gaps, we have proposed a novel pattern mining algorithm to identify a set of contrast permission patterns that aim to detect the difference between clean and malicious applications. A benchmark malware dataset and a dataset of 1227 clean applications has been collected by us to evaluate the performance of the proposed algorithm. Valuable findings are obtained by analyzing the returned contrast permission patterns. © 2013 Elsevier B.V. All rights reserved.

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As the risk of malware is sharply increasing in Android platform, Android malware detection has become an important research topic. Existing works have demonstrated that required permissions of Android applications are valuable for malware analysis, but how to exploit those permission patterns for malware detection remains an open issue. In this paper, we introduce the contrasting permission patterns to characterize the essential differences between malwares and clean applications from the permission aspect. Then a framework based on contrasting permission patterns is presented for Android malware detection. According to the proposed framework, an ensemble classifier, Enclamald, is further developed to detect whether an application is potentially malicious. Every contrasting permission pattern is acting as a weak classifier in Enclamald, and the weighted predictions of involved weak classifiers are aggregated to the final result. Experiments on real-world applications validate that the proposed Enclamald classifier outperforms commonly used classifiers for Android Malware Detection.

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 Mobile platform security solution has become especially important for mobile computing paradigms, due to the fact that increasing amounts of private and sensitive information are being stored on the smartphones' on-device memory or MicroSD/SD cards. This paper aims to consider a comparative approach to the security aspects of the current smartphone systems, including: iOS, Android, BlackBerry (QNX), and Windows Phone.

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Featuring a life-like humanoid robot, Seinendan Theatre Company (Japan) brought their performance Sayonara: Android-Human Theatre to Melbourne in August 2012. Geminoid F, an android, starred alongside Canadian actress Bryerly Long, in a performance that asks the question: What does life and death mean for humans as opposed to robots?