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Many scientific experiments in Bioinformatics are executed as computational workflows. Frequently, it is necessary to re-run an experiment under the original circumstances in which it was run to recognize and validate it. Data provenance concerns the origin of data. Knowing the data source facilitates the understanding and analysis of the results, by detailing and documenting the history and the paths...
With the rapidly increasing applications of deep learning, LSTM-RNNs are widely used. Meanwhile, the complex data dependence and intensive computation limit the performance of the accelerators. In this paper, we first proposed a hybrid network expansion model to exploit the finegrained data parallelism. Based on the model, we implemented a Reconfigurable Processing Unit(RPU) using Processing In Memory(PIM)...
The visual and automatic classification of vehicles plays an important role in the Transport Area. Besides of security issues, the monitoring of the type of traffic in streets and highways, as well the traffic dynamics over time, allows the optimization of use and of resources related to such public infrastructure. In this work we propose a novel method, called 2D-DBM, for robust and efficient automatic...
Earlier research has identified network analysis techniques, methods, and models used to analyze structural aspects of an enterprise architecture (EA) modeled as a network or graph. However, there is still no common set of conceptual elements for such research that could allow one to identify the information requirements needed to perform this type of analysis. In the present research, we organize...
We focus on dynamic model usability and utility, performed throughout system engineering. The dynamic model is designed in relation to the system use scenarios. We generate then automatically the static models (data model, component model) from the dynamic one. A dynamic functional modeling based method is proposed to generate automatically the static and the dynamic organic architecture of a system...
In this paper, we propose a model to learn a feature-category latent representation of the data, that is guided by a semi-supervised auxiliary task. The goal of this auxiliary task is to assign labels to unlabeled data and regularize the feature space. Our model is represented by a modified version of a Categorical Variational Autoencoder, i.e., a probabilistic generative model that approximates a...
Re-engineering is essential for maintaining the competitiveness of enterprises. Enterprise re-engineering involves addressing (emergent) changes, re-organizing, outsourcing, realigning, etc. In this paper, we investigate how to re-engineer enterprises by coupling high-level requirements and the data warehouse, leading to a process re-design that makes the business layer of an enterprise more effective...
The use of an Application Lifecycle Management (ALM) system to promote cross-discipline data capture, tracking and traceability has shown to provide a dramatic improvement during airworthiness audits of software-centric avionics systems by reducing both the time to locate relevant information and rework associated with errors in captured data and their traceability. When configured correctly, an ALM...
Recurrent neural network (RNN) has been broadly applied to natural language processing (NLP) and machine translation problems, by creating a deep learning model for sequential data. Hanmun is a Korean term for Chinese characters, and there are many cases in which Korean is pronounced by borrowing only the Chinese characters. Also, there are proper nouns and place names in the traditional Korean which...
We present here the initial results of our investigation of a system architecture for location-based publish/subscribe services utilizing a graph-based model for managing data and computations. This architecture is implemented on a cluster computer using the facilities and the computation model provided by the Beehive framework which supports a transactional model of parallel computing on dynamic...
Multi-level clustering offers the scalability that is essential to large-scale ad hoc and sensor networks in addition to supporting energy-efficient strategies for gathering data. The optimality of a multi-level network largely depends on two design variables: 1) The number of levels, and 2) The number of nodes operating at each level. We characterize these variables within a multi-hop, multi-level...
Diverse methods abstracting plant architectures are applied in different FSPMs (Functional Structural Plant Models). The abstracted plant architectural data are not applicable for every FSPM because the data models applied in the diverse methods are not compatible. In this paper, we introduce a logical data exchange model EG (Exchange Graph) for adapting different methods abstracting plant architecture...
The emergence of IoT devices is revolutionizing various aspects of human life, including healthcare, where the use of such devices can potentially improve health outcomes for millions. However, the efficacy of treatments and protocols based on IoT devices is measured through the use of rigorous double-blind studies, which can be quite expensive to conduct as they traditionally require a third party...
Defending against cache pollution attacks, highly detrimental attacks that are easy to implement in Named-Data Networking (NDN), currently suffers from the lack of coordination. Solving cache pollution attacks is a prerequisite for the deployment of NDN, which is widely considered to be the basis for the future Internet. We present CoMon++ to this end, a framework for lightweight coordination that...
Recent advances in the Internet-of-Things has given rise to the possibility of connecting different kinds of devices to the internet. With low computing resources constraining most IoT devices and their networks, managing the capabilities and services of the various constrained devices over the internet has been an issue for IoT implementations. Existing approaches to this problem lack end-to-end...
Apply Integrated Logistics Support (ILS) to weapon equipment can efficiently improve equipment's automation and digital level. ILS needs support of various integrated support systems, which have demands for data editing. Nowadays, most of data editing software used in these systems are customized and provide a form-based editing approach, which becomes an obstacle to carry out ILS. This paper brings...
One-shot pose estimation for tasks such as body joint localization, camera pose estimation, and object tracking are generally noisy, and temporal filters have been extensively used for regularization. One of the most widely-used methods is the Kalman filter, which is both extremely simple and general. However, Kalman filters require a motion model and measurement model to be specified a priori, which...
The paper proposes a methodology for the development of a marketing decision support system using Big Data technology and data mining techniques. The approach was inspired by the CRISP-DM methodology, which is not oriented towards Big Data projects. Therefore, we have modified this methodology with respect to the purpose and technological requirements of the project. The proposed methodology was tested...
System specifications can be modeled using various types of notations and diagrams regarding applications of the particular model. In this paper, we present an overview of the existing solutions, focusing on UML, BPMN and DMN models and the diagrams provided by these notations. We perform a comparison of these approaches and provide examples of representing system requirements in these notations.
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