991 resultados para server java android logica


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Providing reliable and efficient services are primary goals in designing a web server system. Data replication can be used to improve the reliability of the system. However, mapping mechanism is one of the primary concerns to data replication. In this paper, we propose a mapping mechanism model called enhanced domain name server (E-DNS) that dispatches the user requests through the URL-name to IP-address under Neighbor Replica Distribution Technique (NRDT) to improve the reliability of the system.

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1. List of Illustrations -- 2. Notes on Text -- 3. Introduction -- 4. ONE Letters from Rockmini -- 5. TWO Letters from Kardinah -- 6. THREE Letters from Kardinah --7. FOUR Letters from Soematri -- 8. Appendix Documents Relating to the Establishment of the Wismo Pranowo School

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This chapter discusses an action research study towards the development of a decision framework to support a fully integrated multi disciplinary Building Information Model (BIM) using a Model Server. The framework was proposed to facilitate multi disciplinary collaborative BIM adoption through, informed selection of a project specific BIM approach and tools contingent upon project collaborators’ readiness, tool capabilities and workflow dependencies. The aim of the research was to explore the technical concerns in relation to Model Servers to support multi disciplinary model integration and collaboration; however it became clear that there were both technical and non technical issues that needed consideration. The evidence also suggests that there are varying levels of adoption which impacts upon further diffusion of the technologies. Therefore the need for a decision framework was identified based on the findings from an exploratory study conducted to investigate industry expectations. The study revealed that even the market leaders who are early technology adopters in the Australian industry in many cases have varying degrees of practical experiential knowledge of BIM and hence at times low levels of confidence of the future diffusion of BIM technology throughout the industry. The study did not focus on the benefits of BIM implementation as this was not the intention, as the industry partners involved are market leaders and early adopters of the technology and did not need convincing of the benefits. Coupled with this there are various other past studies that have contributed to the ‘benefits’ debate. There were numerous factors affecting BIM adoption which were grouped in to two main areas; technical tool functional requirements and needs, and non technical strategic issues. The need for guidance on where to start, what tools were available and how to work through the legal, procurement and cultural challenges was evidenced in the exploratory study. Therefore a BIM decision framework was initiated, based upon these industry concerns. Eight case studies informed the development of the framework and a summary of the key findings is presented. Primary and secondary case studies from firms that have adopted a structured approach to technology adoption are presented. The Framework consists of four interrelated key elements including a strategic purpose and scoping matrix, work process mapping, technical requirements for BIM tools and Model Servers, and framework implementation guide. The BIM framework was presented in draft format again to key industry stakeholders and considered in comparison with current best practice BIM adoption to further validate the framework. There was no request to change any part of the Framework. However, it is an ongoing process and it will be presented again to industry through the various project partners. The Framework may be refined within the boundaries of the action research process as an ongoing activity as more experiential knowledge can be incorporated.

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Practical experience in porting a large virtual reality system from C/C++ to Java indicates that porting this type of real-time application is both feasible, and has several merits. The ability to transfer objects in space and time allows useful facilities such as distributed agent support and persistence to be added. Reflection and type comparisons allow flexible manipulations of objects of different types at run-time. Native calls and native code compilation reduce or remove the overhead of interpreting code.Problems encountered include difficulty in achieving cross-platform code portability, limitations of the networking libraries in Java, and clumsy coding practices forced by the language.

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Since its establishment, the Android applications market has been infected by a proliferation of malicious applications. Recent studies show that rogue developers are injecting malware into legitimate market applications which are then installed on open source sites for consumer uptake. Often, applications are infected several times. In this paper, we investigate the behavior of malicious Android applications, we present a simple and effective way to safely execute and analyze them. As part of this analysis, we use the Android application sandbox Droidbox to generate behavioral graphs for each sample and these provide the basis of the development of patterns to aid in identifying it. As a result, we are able to determine if family names have been correctly assigned by current anti-virus vendors. Our results indicate that the traditional anti-virus mechanisms are not able to correctly identify malicious Android applications.

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Google advertises the Android permission framework as one of the core security features present on its innovative and flexible mobile platform. The permissions are a means to control access to restricted AP/s and system resources. However, there are Android applications which do not request permissions at all.In this paper, we analyze the repercussions of installing an Android application that does not include any permission and the types of sensitive information that can be accessed by such an application. We found that even app/icaaons with no permissions are able to access sensitive information (such the device ID) and transmit it to third-parties.

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An increasing number of Android devices are being infected and at risk of becoming part of a botnet. Among all types of botnets, control and cornmand based botnets are very popular. In this paper we introduce an effective and efficient method to ddect SMS-based control commands ftvm infected Android devices. Specifically, we rely on the important radio activities recorded in Android log files. These radio activities are currently overlooked by researchers. We show the effectiveness of our rnethod by using the examples frorn published literature. Our method requires much less user knowledge but is more generic than traditional approaches.

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Recent investigations have determined that many Android applications in both official and non-official online markets expose details of the user's mobile phone without user consent. In this paper, for the first time in the research literature, we provide a full investigation of why such applications leak, how they leak and where the data is leaked to. In order to achieve this, we employ a combination of static and dynamic analysis based on examination of Java classes and application behaviour for a data set of 123 samples, all pre-determined as being free from malicious software. Despite the fact that anti-virus vendor software did not flag any of these samples as malware, approximately 10% of them are shown to leak data about the mobile phone to a third-party; applications from the official market appear to be just as susceptible to such leaks as applications from the non-official markets.

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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.