An Unequal Clustering Data Collection Algorithm for Unreliable Links

2019 ◽  
Author(s):  
Han Yu Lao
Keyword(s):  
Data Collection ◽  
Unequal Clustering ◽  
Clustering Data ◽  
Unreliable Links

scholarly journals Segmentasi Perkebunan Kelapa Sawit dengan Data Mining Teknik K-Means Clustering Berdasarkan Luas Areal, Produksi dan Produktivitas

2021 ◽  
Vol 2 (2) ◽  
pp. 56
Author(s):  
Trisna Yuniarti ◽  
Dahliyah Hayati
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Oil Palm ◽  
Data Sets ◽  
Segmentation Method ◽  
Data Mining Technique ◽  
Mining Technique ◽  
The Government ◽  
Clustering Data ◽  
Medium Potential

The oil palm is the most productive plantation product in Indonesia. Government strategies and policies related to oil palm plantations continue to be carried out considering that the plantation area is increasing every year. Segmentation of oil palm plantations based on area, production, and productivity aims to identify groups of potential oil palm plantations in the territory of Indonesia. This segmentation can provide consideration in formulating strategies and policies that will be made by the government. The segmentation method for grouping oil palm plantations uses the K-Means Clustering Data Mining technique with 3 clusters specified. Data mining stages start from data collection until representation is carried out, where 34 data sets are collected, only 25 data sets can be processed further. The results of this grouping obtained three plantation segments, namely 72% of the plantation group with low potential, 20% of the plantation group with medium potential, and 8% of the plantation group with high potential.

2C-CTP: A Centralized Clustering Data Collection Protocol based on CTP

2016 ◽  
Vol 10 (9) ◽  
pp. 179-196
Author(s):  
Lingyun Xu ◽  
Tao Li ◽  
Baowei Wang ◽  
Xingming Sun ◽  
Xingang You ◽  
...  
Keyword(s):  
Data Collection ◽  
Clustering Data

Data Reconstructing Algorithm in Unreliable Links Based on Matrix Completion for Heterogeneous Wireless Sensor Networks

2019 ◽  
Vol 33 (13) ◽  
pp. 1951012 ◽  
Author(s):  
Shuang Zhai ◽  
Zhihong Qian ◽  
Bingtao Yang ◽  
Xue Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Compressed Sensing ◽  
Matrix Completion ◽  
Wireless Sensor ◽  
Reconstruction Accuracy ◽  
Heterogeneous Wireless Sensor Networks ◽  
Unreliable Links

In heterogeneous wireless sensor networks, the data collection method based on compressed sensing technology is susceptible to packet loss and noise, which leads to a decrease in data reconstruction accuracy in unreliable links. Combining compressed sensing and matrix completion, we propose a clustering optimization algorithm based on structured noise matrix completion, in which the cluster head transmits the compressed sampling data and compression strategy to the base station. The algorithm we proposed can reduce the energy consumption of the node in the process of data collection, redundant data and transmission delay. The rank-1 matrix completion algorithm constructs an extremely sparse observation matrix, which is adopted by the sink node to complete the reconstruction of the whole network data. Simulation experiments show that the proposed algorithm reduces network transmission data, balances node energy consumption, improves data transmission efficiency and reconstruction accuracy, and extends the network life cycle.

Electron Diffraction of Wet Biological Membranes

1974 ◽  
Vol 32 ◽  
pp. 158-159
Author(s):  
S.W. Hui ◽  
D.F. Parsons
Keyword(s):  
Electron Diffraction ◽  
Data Collection ◽  
Biological Membranes ◽  
Small Areas ◽  
Electron Diffraction Technique ◽  
Electron Microscopes ◽  
Collection Time ◽  
Camera Length

The development of the hydration stages for electron microscopes has opened up the application of electron diffraction in the study of biological membranes. Membrane specimen can now be observed without the artifacts introduced during drying, fixation and staining. The advantages of the electron diffraction technique, such as the abilities to observe small areas and thin specimens, to image and to screen impurities, to vary the camera length, and to reduce data collection time are fully utilized. Here we report our pioneering work in this area.

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