scholarly journals Mallard Detection Using Microphone Arrays Combined with Delay-and-Sum Beamforming for Smart and Remote Rice–Duck Farming

2021 ◽  
Vol 12 (1) ◽  
pp. 108
Author(s):  
Hirokazu Madokoro ◽  
Satoshi Yamamoto ◽  
Kanji Watanabe ◽  
Masayuki Nishiguchi ◽  
Stephanie Nix ◽  
...  
Keyword(s):  
Natural Enemies ◽  
Estimation Method ◽  
Outdoor Environment ◽  
Microphone Arrays ◽  
Prototype System ◽  
Rice Farming ◽  
Acoustic Information ◽  
Efficient Management ◽  
Adequate Accuracy ◽  
Benchmark Evaluation

This paper presents an estimation method for a sound source of pre-recorded mallard calls from acoustic information using two microphone arrays combined with delay-and-sum beamforming. Rice farming using mallards saves labor because mallards work instead of farmers. Nevertheless, the number of mallards declines when they are preyed upon by natural enemies such as crows, kites, and weasels. We consider that efficient management can be achieved by locating and identifying the locations of mallards and their natural enemies using acoustic information that can be widely sensed in a paddy field. For this study, we developed a prototype system that comprises two sets of microphone arrays. We used 64 microphones in all installed on our originally designed and assembled sensor mounts. We obtained three acoustic datasets in an outdoor environment for our benchmark evaluation. The experimentally obtained results demonstrated that the proposed system provides adequate accuracy for application to rice–duck farming.

scholarly journals A Mobile Sensing System for UrbanPM2.5Monitoring with Adaptive Resolution

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Hongjie Guo ◽  
Guojun Dai ◽  
Jin Fan ◽  
Yifan Wu ◽  
Fangyao Shen ◽  
...  
Keyword(s):  
Air Quality ◽  
Meteorological Data ◽  
Computational Cost ◽  
Estimation Method ◽  
Mobile Sensing ◽  
Prototype System ◽  
Adaptive Grids ◽  
Sensing System ◽  
Adaptive Resolution ◽  
Wide Range

This paper develops a mobile sensing system, the first system used in adaptive resolution urban air quality monitoring. In this system, we employ several taxis as sensor carries to collect originalPM2.5data and collect a variety of datasets, including meteorological data, traffic status data, and geographical data in the city. This paper also presents a novel method AG-PCEM (Adaptive Grid-Probabilistic Concentration Estimation Method) to infer thePM2.5concentration for undetected grids using dynamic adaptive grids. We gradually collect the measurements throughout a year using a prototype system in Xiasha District of Hangzhou City, China. Experimental data has verified that the proposed system can achieve good performance in terms of computational cost and accuracy. The computational cost of AG-PCEM is reduced by about 40.2% compared with a static grid method PCEM under the condition of reaching the close accuracy, and the accuracy of AG-PCEM is far superior as widely used artificial neural network (ANN) and Gaussian process (GP), enhanced by 38.8% and 14.6%, respectively. The system can be expanded to wide-range air quality monitor by adjusting the initial grid resolution, and our findings can tell citizens actual air quality and help official management find pollution sources.

scholarly journals PlantES: A Plant Electrophysiological Multi-Source Data Online Analysis and Sharing Platform

2018 ◽  
Vol 8 (11) ◽  
pp. 2269 ◽  
Author(s):  
Chao Song ◽  
Xiao-Huang Qin ◽  
Qiao Zhou ◽  
Zi-Yang Wang ◽  
Wei-He Liu ◽  
...  
Keyword(s):  
Data Sharing ◽  
Template Matching ◽  
Distributed Storage ◽  
Prototype System ◽  
Fast Analysis ◽  
Online Analysis ◽  
Electrical Signals ◽  
Electrophysiological Data ◽  
Efficient Management ◽  
Source Data

At present, plant electrophysiological data volumes and complexity are increasing rapidly. It causes the demand for efficient management of big data, data sharing among research groups, and fast analysis. In this paper, we proposed PlantES (Plant Electrophysiological Data Sharing), a distributed computing-based prototype system that can be used to store, manage, visualize, analyze, and share plant electrophysiological data. We deliberately designed a storage schema to manage the multi-source plant electrophysiological data by integrating distributed storage systems HDFS and HBase to access all kinds of files efficiently. To improve the online analysis efficiency, parallel computing algorithms on Spark were proposed and implemented, e.g., plant electrical signals extraction method, the adaptive derivative threshold algorithm, and template matching algorithm. The experimental results indicated that Spark efficiently improves the online analysis. Meanwhile, the online visualization and sharing of multiple types of data in the web browser were implemented. Our prototype platform provides a solution for web-based sharing and analysis of plant electrophysiological multi-source data and improves the comprehension of plant electrical signals from a systemic perspective.

scholarly journals Binaural Modelling and Spatial Auditory Cue Analysis of 3D-Printed Ears

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 227
Author(s):  
Te Meng Ting ◽  
Nur Syazreen Ahmad ◽  
Patrick Goh ◽  
Junita Mohamad-Saleh
Keyword(s):  
Sound Source ◽  
Elevation Angle ◽  
Three Dimensional ◽  
Estimation Method ◽  
Distance Estimation ◽  
Outdoor Environment ◽  
Average Error ◽  
Spectral Cues ◽  
Polar Coordinate ◽  
3D Printed

In this work, a binaural model resembling the human auditory system was built using a pair of three-dimensional (3D)-printed ears to localize a sound source in both vertical and horizontal directions. An analysis on the proposed model was firstly conducted to study the correlations between the spatial auditory cues and the 3D polar coordinate of the source. Apart from the estimation techniques via interaural and spectral cues, the property from the combined direct and reverberant energy decay curve is also introduced as part of the localization strategy. The preliminary analysis reveals that the latter provides a much more accurate distance estimation when compared to approximations via sound pressure level approach, but is alone not sufficient to disambiguate the front-rear confusions. For vertical localization, it is also shown that the elevation angle can be robustly encoded through the spectral notches. By analysing the strengths and shortcomings of each estimation method, a new algorithm is formulated to localize the sound source which is also further improved by cross-correlating the interaural and spectral cues. The proposed technique has been validated via a series of experiments where the sound source was randomly placed at 30 different locations in an outdoor environment up to a distance of 19 m. Based on the experimental and numerical evaluations, the localization performance has been significantly improved with an average error of 0.5 m from the distance estimation and a considerable reduction of total ambiguous points to 3.3%.

scholarly journals Review on the Battery Model and SOC Estimation Method

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1685
Author(s):  
Wenlu Zhou ◽  
Yanping Zheng ◽  
Zhengjun Pan ◽  
Qiang Lu
Keyword(s):  
Estimation Method ◽  
Estimation Algorithm ◽  
Management Control ◽  
Research Progress ◽  
Estimation Algorithms ◽  
Soc Estimation ◽  
Advantages And Disadvantages ◽  
Battery Model ◽  
Efficient Management ◽  
Power Battery

The accuracy of the power battery model and SOC estimation directly affects the vehicle energy management control strategy and the performance of the electric vehicle, which is of great significance to the efficient management of the battery and the improvement of the reliability of the vehicle. Based on the research of domestic and foreign battery models and the previous results of SOC estimation, this paper classifies power battery models into electrochemical mechanism models, equivalent circuit models and data-driven models. This paper analyzes the advantages and disadvantages of various battery models and current research progress. According to the choice of battery model, the previous research results of the power battery SOC estimation method are divided into three categories: the direct measurement method not based on battery model, the estimation method using black box battery model, and the battery model SOC estimation method based on state space. This paper will summarize and analyze the principles, applicable scenarios and research progress of the three categories of estimation algorithms aiming to provide references for future in-depth research. Finally, in view of the shortcomings of the battery model and estimation algorithm of the existing method, the future improvement direction is proposed.

Study on Assembly Cost Based on Product Concurrent Design

2011 ◽  
Vol 314-316 ◽  
pp. 1863-1866
Author(s):  
Qing Liang Zeng ◽  
Lian Min Cao ◽  
Xi Wei Wang
Keyword(s):  
Cost Estimation ◽  
Cost Reduction ◽  
Theoretical Basis ◽  
Estimation Method ◽  
Concurrent Design ◽  
Prototype System ◽  
Feature Mapping ◽  
Assembly Cost ◽  
Depth Study ◽  
Product Assembly

This thesis makes in-depth study on product assembly costs in the theoretical basis of feature mappings and cost estimation method of concurrent design. It builds up a mathematical model of feature mapping from product design domain to assemble domain, proposes a prototype system framework of assembly cost estimation and also provides theoretical and technical support for design of product cost reduction.

Fast Cutter Workpiece Engagement Estimation Method for Prediction of Instantaneous Cutting Force in Continuous Multi-Axis Controlled Machining

2013 ◽  
Vol 7 (4) ◽  
pp. 391-400 ◽  
Author(s):  
Jun’ichi Kaneko ◽  
◽  
Kenichiro Horio
Keyword(s):  
Parallel Processing ◽  
Cutting Force ◽  
Real Time ◽  
Estimation Method ◽  
Processing Technology ◽  
Prototype System ◽  
Processing Unit ◽  
Rough Machining ◽  
Machining Processes ◽  
High Productivity

In order to realize high productivity in rough machining processes, a fast simulation system is needed for multi axis controlled machining to predict instantaneous cutting force. The new efficient algorithm to estimate an engagement between the end mill cutter and the machined workpiece in continuous multi axis controlled machining processes is proposed. In order to shorten calculation time for the engagement area, and to improve the real-time prediction of instantaneous cutting force, a new concept is introduced for adapting ultra-parallel processing technology. The proposed method assumes the engagement as a large number of divisions located on the locus of cutting edges. The inclusion estimation process between an estimation point in each division and the machined workpiece volume is resolved into two kinds of simple inclusion estimation – and between the estimation point and tool swept volume and the other between the estimation point and initial workpiece shape. In this paper, a new prototype system based on parallel processing technology known as the general purposed graphic processing unit (GPGPU) is developed and the proposed algorithm is verified with the prototype system. The system shows good performance for complicated NC programs generated by commercial CAM system and realizes real-time simulation of instantaneous cutting force.

Runtime Memory Controller Profiling with Performance Analysis for DRAM Memory Controllers

2018 ◽  
Vol 27 (08) ◽  
pp. 1850126
Author(s):  
Dong-Ik Jeon ◽  
Min-Kyu Lee ◽  
Ji-Chan Kim ◽  
Ki-Seok Chung
Keyword(s):  
Performance Analysis ◽  
Memory Performance ◽  
Estimation Method ◽  
Random Access ◽  
Main Memory ◽  
Memory Access ◽  
Prototype System ◽  
Memory Controller ◽  
Processor Core ◽  
Field Programmable

The main memory system has become crucial not only because it has to meet an increasing bandwidth requirement, but also because it has to seamlessly support many concurrently executing applications. In order to improve memory performance, a memory controller with efficient arbitration is necessary. It is well known that memory performance is dependent on the memory access patterns. The offline performance analysis has difficulty analyzing the Dynamic Random Access Memory (DRAM) performance accurately because a huge set of trace patterns is needed. This paper proposes a novel profiler that is synthesized with a memory controller in order to monitor and analyze the memory controller performance at runtime. In this paper, five key metrics for performance evaluation are defined and they are monitored and evaluated at runtime by the proposed profiler. A prototype system with a processor core, a memory controller, DRAM modules, and peripheral devices are implemented on a field-programmable gate array (FPGA) board to carry out the experiments. It has been observed that the worst latency overhead differs for each benchmark. In addition, a new overall overhead estimation method is proposed to estimate the memory access latency overhead in time, and this method can be used to evaluate the performance of a certain memory arbitration method depending on running applications.

Sign in / Sign up

Export Citation Format

Share Document