Simulation is used for developing and testing different scenarios under controlled and reproducible situations. Proper handling of the initial transient effect for steady state simulations, proper selection of simulat...
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Simulation is used for developing and testing different scenarios under controlled and reproducible situations. Proper handling of the initial transient effect for steady state simulations, proper selection of simulation length and proper statistical analysis of results are essential for conducting credible simulations. Akaroa2, a universal controller for quantitative discrete event simulation, has been designed to improve credibility of simulation results. It automatically handles the initial transient effect, carries out statistical analysis of results and controls simulation length by stopping the simulation when the required precision is achieved based on continuous analysis of mean values. Simulation programs can be made to run under Akaroa2 to provide statistically valid results. OPNET is a popular simulator used for carrying out telecommunication and networking related simulations, but it does not provide automated simulation length control and initial transient effect handling. We have developed an interface using OPNET co-simulation capabilities to run OPNET simulations under Akaroa2 control. It will allow the user of OPNET to control the length of simulation on basis of the accuracy of statistical results. OPNET and Akaroa2 are available for free for non-profit research at universities.
One of the key issues that should be considered when addressing reliable evolution is to place a software system in a consistent status before and after change. This issue becomes more critical at runtime because it m...
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This work introduces a novel, automated methodology for performing functional analysis of integrated circuits (ICs), such as microcontrollers and smart cards. By selectively executing code on a given chip, the resulti...
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Business and design decisions regarding software development should be based on data, not opinions among developers, domain experts or managers. The company running the most and fastest experiments among the customer ...
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Business and design decisions regarding software development should be based on data, not opinions among developers, domain experts or managers. The company running the most and fastest experiments among the customer base against the lowest cost per experiment outcompetes others by having the data to engineer products with outstanding qualities such as power consumption and user experience. Innovation experiment systems for mass-produced devices with embedded software is an evolution of current R&D practices, going from where innovations are internally evaluated by the original equipment manufacturer to where they are tried by real users in a scale relevant to the full customer base. The turnaround time from developing and deploying an embedded product to getting customer feedback is decreased to weeks, the limit being the speed of the software development teams. The paper presents an embedded architecture for realising such a novel innovation experiment system based on a set of scenarios of what to evaluate in the experiments. A case is presented implementing an architecture in a prototype in-vehicle infotainment system where comparative testing between two software alternatives was performed.
Transfer learning aims to leverage the knowledge in the source domain to facilitate the learning tasks in the tar- get domain. It has attracted extensive research interests recently due to its effectiveness in a wide ...
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User interface development and maintenance presents a burden for many developers. UI development approaches often restate information already captured in the application model such as entity attributes, validation, se...
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In order to develop web mashups, designers need an in-depth understanding of each Web API they are using. However, Web API documentation is rather heterogeneous, represented by big HTML files or collection of files in...
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Cloud computing has emerged in recent years as a major segment of the IT industry; however, security concerns remain the primary impediment to full-scale adoption. Leveraging properties of virtualization, virtual mach...
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Cloud computing has emerged in recent years as a major segment of the IT industry; however, security concerns remain the primary impediment to full-scale adoption. Leveraging properties of virtualization, virtual machine introspection (VMI) has yielded promising research for cloud security yet adoption of these approaches in production environments remains minimal due to a semantic gap: the extraction of high-level knowledge of the guest operating system's state from low-level artifacts collected out-of-VM. Within the field of forensic memory analysis (FMA), a similar semantic gap exists from the reconstruction of physical memory dumps. We implement a production oriented prototype utilizing designs that combines and narrows these semantic gaps in a modular framework to function as an intrusion detection system (IDS) detecting and defeating post-exploitation activity.
The explosive growth of image data leads to severe challenges to the traditional image retrieval methods. In order to manage massive images more accurate and efficient, this paper firstly proposes a scalable architect...
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The explosive growth of image data leads to severe challenges to the traditional image retrieval methods. In order to manage massive images more accurate and efficient, this paper firstly proposes a scalable architecture for image retrieval based on a uniform data model and makes this function a sub-engine of AUDR, an advanced unstructured data management system, which can simultaneously manage several kinds of unstructured data including image, video, audio and text. The paper then proposes a new image retrieval algorithm, which incorporates rich visual features and two text models for multi-modal retrieval. Experiments on both ImageNet dataset and ImageCLEF medical dataset show that our proposed architecture and the new retrieval algorithm are appropriate for efficient management of massive image.
There are many factors that provide input into the software development process, such as the values, beliefs, norms, practices, skills, behaviors, knowledge and goals of stakeholders. Research has shown that successfu...
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There are many factors that provide input into the software development process, such as the values, beliefs, norms, practices, skills, behaviors, knowledge and goals of stakeholders. Research has shown that successful software system development relies on alignment or congruence between these factors. How to monitor the level of congruence between these factors and how to use the congruence as an indicator or a measure to monitor a software development process is a challenge in softwareengineering. This paper proposes a model that uses three congruence measures to examine the levels of social-technical congruence in software development processes. Using a controlled experiment with seven student teams developing a robot project, this paper demonstrates that the proposed congruence measures provide results consistent with the assessment by the course lecturers.
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