Устройство универсальной перепаковки потоков данных
The existing device repacking data streams and options for their implementation as application specific integrated circuits, so on the FPGA is studied. Revealed their limitations and shortcomings of the synchronization of the data flow transformation. A device universal repacking data streams is offered. The function chart and timing diagrams of his work is shown.
Large-scale classification of text streams is an essential problem that is hard to solve. Batch processing systems are scalable and proved their effectiveness for machine learning but do not provide low latency. On the other hand, state-of-the-art distributed stream processing systems are able to achieve low latency but do not support the same level of fault tolerance and determinism. In this work, we discuss how the distributed streaming computational model and fault tolerance mechanisms can affect the correctness of text classification data flow. We also propose solutions that can mitigate the revealed pitfalls.
The 11th International Conference on Security and its Applications (CNSA 2018) was held in Zurich, Switzerland, during January 02~03, 2018. The 5th International Conference on Data Mining and Database (DMDB 2018) and The 5th International Conference on Artificial Intelligence and Applications (AIAP 2018) was collocated with The 11th International Conference on Security and its Applications (CNSA 2018). The conferences attracted many local and international delegates, presenting a balanced mixture of intellect from the East and from the West. The goal of this conference series is to bring together researchers and practitioners from academia and industry to focus on understanding computer science and information technology and to establish new collaborations in these areas. Authors are invited to contribute to the conference by submitting articles that illustrate research results, projects, survey work and industrial experiences describing significant advances in all areas of computer science and information technology.
Provides an overview of the different ways to implement the high-speed I/O data to the PC using FPGA based on the use of commercially available modules. The possibility of developing a specialized unit that provides the present-simplification of the equipment.
Issue of identification emergency electrical discharge for electrical network is studied. Structure chart of detector is shown. Algorithm of DSP module is offered. Timing diagram of identification process and realization example of algorithm in Matlab is given
Proceedings of 2018 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)
This article presents a method of the automated control of distributed radio direction finding system (RDFS) providing the construction of an automated system of technical diagnostics and recovery of distributed RDFS performance on the specified requirements. This dual-circuit method includes diagnosing and reliability operations, redundancy recommendations, and also control algorithms of the constituent elements of the system. The structure and mathematical apparatus of the operations, recommendations, and algorithms of the proposed method are shown. The basic requirements and restrictions under which the construction of automated technical diagnosis system is carried out are specified.
Text stream classification is an important problem that is difficult to solve at scale. Batch processing systems, widely adopted for text classification tasks, cannot provide for low latency. Distributed stream processing systems can offer low latency, but do not support the same level of fault tolerance and determinism as the batch systems. In this work, we demonstrate how the distributed stream processing features can affect the results of a typical text classification data flow. Our analysis shows emerged trade-offs between fault tolerance and reproducibility on the one side, and performance on the other side. We outline potential ways to solve the revealed issues and to handle streaming features.