Sonar Data Simulation

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

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QSM reconstruction challenge 2.0: A realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures

Magnetic Resonance in Medicine ◽

10.1002/mrm.28716 ◽

2021 ◽

Vol 86 (1) ◽

pp. 526-542

Author(s):

José P. Marques ◽

Jakob Meineke ◽

Carlos Milovic ◽

Berkin Bilgic ◽

Kwok‐Shing Chan ◽

...

Keyword(s):

In Silico ◽

Susceptibility Mapping ◽

Data Simulation ◽

Simulation And Evaluation

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Development of a Hydropower Turbine Using Seawater from a Fish Farm

Processes ◽

10.3390/pr9020266 ◽

2021 ◽

Vol 9 (2) ◽

pp. 266

Author(s):

Md Rakibuzzaman ◽

Sang-Ho Suh ◽

Hyoung-Ho Kim ◽

Youngtae Ryu ◽

Kyung Yup Kim

Keyword(s):

Power Plants ◽

Guide Vane ◽

Cross Flow ◽

Synchronous Generator ◽

Fish Farm ◽

Hydropower Plant ◽

Fish Farms ◽

Data Simulation ◽

Small Hydropower ◽

Hydropower Plants

Discharge water from fish farms is a clean, renewable, and abundant energy source that has been used to obtain renewable energy via small hydropower plants. Small hydropower plants may be installed at offshore fish farms where suitable water is obtained throughout the year. It is necessary to meet the challenges of developing small hydropower systems, including sustainability and turbine efficiency. The main objective of this study was to investigate the possibility of constructing a small hydropower plant and develop 100 kW class propeller-type turbines in a fish farm with a permanent magnet synchronous generator (PMSG). The turbine was optimized using a computer simulation, and an experiment was conducted to obtain performance data. Simulation results were then validated with experimental results. Results revealed that streamlining the designed shape of the guide vane reduced the flow separation and improved the efficiency of the turbine. Optimizing the shape of the runner vane decreased the flow rate, reducing the water power and increasing the efficiency by about 5.57%. Also, results revealed that tubular or cross-flow turbines could be suitable for use in fish farm power plants, and the generator used should be waterproofed to avoid exposure to seawater.

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Research on the framework of university ideological and political education management system based on artificial intelligence

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219134 ◽

2021 ◽

pp. 1-10

Author(s):

Xuying Sun ◽

Yu Zhang

Keyword(s):

Artificial Intelligence ◽

Political Theory ◽

Outlier Detection ◽

Management System ◽

Detection Algorithm ◽

Colleges And Universities ◽

Ideological And Political Education ◽

Political Education ◽

Data Simulation ◽

Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

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