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Ever since the dawn of the modern avionics era features like economy of weight, power and space; improved reliability; safeguards against the lurking danger of obsolescence; efficient use of available resources such as processing power, interfaces, and memory; and change containment owing to the insertion of advanced systems; have always been imperative. Aircraft avionics architectures can be divided...
Business Intelligence (BI) provides historical, current and predictive views of business operations with the help of some technologies, that include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. As analytics plays a major role in...
Recent emerging growth of data created so many challenges in data mining. Data mining is the process of extracting valid, previously known & comprehensive datasets for the future decision making. As the improved technology by World Wide Web the streaming data come into picture with its challenges. The data which change with time & update its value is known as streaming data. As the...
Research on software architecture knowledge management (SAKM) within the last 10 years has focused on capturing and storing design decisions and their underlying rationales. Recent attempts have tried to combine SAKM with variability management to support the capture of knowledge for a set of related products. To assess the current state of the art of variability management in the context of SAKM,...
Today, data from different sources and different phases of the product life cycle are usually analyzed in isolation and with considerable time delay. Real-time integrated analytics is especially beneficial in a production context. We present an architecture for data- and analytics-driven exception escalation in manufacturing and show the advantages of integrating unstructured data.
Recent emergence of diverse services have led to explosive traffic growth in cellular data networks. Understanding the service dynamics in large cellular networks is important for network design, trouble shooting, quality of service (QoE) support, and resource allocation. In this paper, we present our study to reveal the distributions and temporal patterns of different services in cellular data network...
Our proposed architecture of dynamically reconfigurable hardware for protocol processing (DRHPP) provides flexibility with high area efficiency. It can be used for a communications system-on-a-chip (SoC) in access networks. The DRHPP enables the modification and addition of various functions for protocol processing. Our architecture consists of three types of cells. The optimized number of these types...
Thanks to the rapid advances in Internet-based applications, data acquisition and storage technologies, petabyte-sized network data collections are becoming more and more common, thus prompting the need for scalable data analysis solutions. By leveraging today's ubiquitous many-core computer architectures and the increasingly popular cloud computing paradigm, the applicability of data mining algorithms...
Cloud Computing has emerged as a new paradigm in the field of network-based services within many industrial and application domains. The major benefits that it provides in terms of IT efficiency and business agility represent a huge competitive advantage for an organization. However, building new services in the cloud or designing cloud-based solutions into existing business context in general is...
Many organizations look for a proper way to make better and faster decisions about their businesses. Data warehouse has unique features such as data mining and ad hoc querying on data collected and integrated from many of the computerized systems used in organization. Data warehouse can be built using a number of architectures. Each one of the architecture has its own advantages and disadvantages...
Due to the advances in GPU technology, there have been many approaches to utilize the GPU for general applications. Many research papers that dramatically improved the performance of traditional CPU-based data mining algorithms have been published. Clustering is an important data mining problem that is often found in many areas. DBSCAN is the most widely used density-based clustering algorithm, but...
In this paper, a novel measurement data management system, based on cloud technology, is proposed. The system aims at maximizing the potential of the information assets of large electronic manufacturing companies through the collection, management and analysis of the so called Big Data generated by means of test processes, performed during the life-cycle of the products.
With the arrival of big data and cloud computing as a computing concept, it is becoming ever more critical to efficiently choose the most optimum machine on which to execute a program, for example in the healthcare environment. This process of choice is also complicated by the fact that numerous machines are available as virtual machines. Hence, predicting the most optimum choice of machine based...
Agent is a computing entity which mimics the behavior of a human being in problem solving strategy. Multi agents systems are the group of agents which have different tasks and work in cooperation, coordination and in communication to each other. Apart from wide applications in software engineering tasks, design, development and testing, it has a vital role in software maintenance also. Few effective...
The widespread availability of multi-core processors and specialized co-processors has generally not been matched by the actual use of parallel software by users. In this work we experimentally verify the simplicity of code parallelization by implementing two kinds of data mining algorithms on two parallel platforms with a view to building upon them in future projects. We use CUDA on a graphics card...
Learn2Mine is a cloud-based environment developed to support the teaching of data science. This paper discusses the architecture of Learn2Mine, the research that guided its development, and the pilot implementation and formative assessment of its use in teaching data science. Learn2Mine was pilot-tested in Fall 2013 in an introductory data science source. At the end of the term, a survey of students...
With the rise of video surveillance applications for analyzing real-time and batching video data in large scales, traditional video processing systems are being challenged due to real-time, intelligence and fault-tolerance demand for networked high resolution and large-scale video processing. These challenges can be further exacerbated by the existing predicaments of multi-platform, multi-format,...
To determine the circumstances of an incident, investigators need to reconstruct events that occurred in the past. The large amount of data spread across the crime scene makes this task very tedious and complex. In particular, the analysis of the reconstructed timeline, due to the huge quantity of events that occurred on a digital system, is almost impossible and leads to cognitive overload. Therefore,...
Beliefs play an important role in human-robot teaming scenarios, where the robots must reason about other agents' intentions and beliefs in order to inform their own plan generation process, and to successfully coordinate plans with the other agents. In this paper, we cast the evolving and complex structure of beliefs, and inference over them, as a planning and plan recognition problem. We use agent...
With the legerity of the Internet, daily life of a common man has changed. Rapid growth of the Internet has a diverse effect on the daily life. The influence of the Internet has changed the way we live and even the way we think. The use of Internet for purchasing different products of the daily needs has increased exponentially in recent years. Now customers prefer online shopping for the acquisition...
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