Rice Quality Evaluation Using a Taste-Sensing System

2013 ◽  
pp. 127-141
Author(s):  
Uyen Tran ◽  
Ken’ichi Ohtsubo
Keyword(s):  
Quality Evaluation ◽  
Rice Quality ◽  
Sensing System

Rice Kernel Separations Using Contour Analysis and Skeleton

2015 ◽  
Vol 781 ◽  
pp. 515-518
Author(s):  
Chaladchai Siriwongkul ◽  
Pattarawit Polpinit
Keyword(s):  
Quality Evaluation ◽  
Median Filter ◽  
Processing Method ◽  
Separation Process ◽  
Contour Analysis ◽  
Separation Algorithm ◽  
Rice Quality ◽  
Binary Images ◽  
Separation Line ◽  
Broken Rice

Determine the percentage of broken rice kernel is crucial for rice quality evaluation. This paper studies a digital image processing method that can effectively separate touching rice kernels in an image of rice used for quality evaluation. An alternative separation algorithm based on contour analysis and skeleton is proposed to separate touching rice kernels. The proposed algorithm can be divided into three parts, namely, pre-processing, obtaining the candidates for separation line endpoints, and analysis for separation process. In the pre-processing, the images are converted into grayscale images. Then the median filter is applied in order to remove noise. Finally the binary images are obtained using Otsu’s algorithm. The next step is to obtain the candidates for separation line endpoints from concave points on the contour of rice kernels. The final step is to draw a separation lines among the candidates using several categories based on concave analysis and skeleton. The experimental results show that the proposed algorithm can accurately separate touching rice kernels and as a result the accurate percentage of broken rice can be obtained.

scholarly journals An Efficient and Secure Malicious User Detection Scheme Based on Reputation Mechanism for Mobile Crowdsensing VANET

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Zhihua Wang ◽  
Jiahao Liu ◽  
Chaoqi Guo ◽  
Shuailiang Hu ◽  
Yongjian Wang ◽  
...  
Keyword(s):  
Data Quality ◽  
Traffic Safety ◽  
Quality Evaluation ◽  
Experimental Simulation ◽  
Detection Scheme ◽  
Mobile Crowdsensing ◽  
Sensing Data ◽  
Malicious User ◽  
Sensing System ◽  
Evaluation Phase

With the increasing development of wireless communication technology and Vehicular Ad hoc Network (VANET), as well as the continuous popularization of various sensors, Mobile Crowdsensing (MCS) paradigm has been widely concerned in the field of transportation. As a currently popular data sensing way, it mainly relies on wireless sensing devices to complete large-scale and complex sensing tasks. However, since vehicles are highly mobile in this scenario and the sensing system is open, that is, any vehicle equipped with sensing device can join the system, the credibility of all participating vehicles cannot be guaranteed. In addition, malicious users will upload false data in the sensing system, which makes the sensing data not meet the needs of the sensing tasks and will threaten traffic safety in some serious cases. There are many solutions to the above problems, such as cryptography, incentive mechanism, and reputation mechanisms. Unfortunately, although these schemes guaranteed the credibility of users, they did not give much thought to the reliability of data. In addition, some schemes brought a lot of overhead, some used a centralized server management architecture, and some were not suitable for the scenario of VANET. Therefore, this paper firstly proposes the MCS-VANET architecture-based blockchain, which consists of participating vehicles (PVs), road side units (RSUs), cloud server (CS), and the blockchain (BC), and then designs a malicious user detection scheme composed of three phases. In the data collecting phase, to reduce the data uploading overhead, data aggregation and machine learning technologies are combined by fully considering the historical reputation value of PVs, and the proportion of data uploading is determined based on the historical data quality evaluation result of PVs. In the data quality evaluation phase, a new reputation computational model is proposed to effectively evaluate the sensing data, which contains four indicators: the reputation history of PVs, the data unbiasedness, the leadership of PVs, and the spatial force of PVs. In the reputation updating phase, to achieve the effective change of reputation values, the logistic model function curve is introduced and the result of the reputation updating is stored in the blockchain for security publicity. Finally, on real datasets, the feasibility and effectiveness of our proposed scheme are demonstrated through the experimental simulation and security analysis. Compared with existing schemes, the proposed scheme not only reduces the cost of data uploading but also has better performance.

Optical Sensing System for Real-Time Physical Quality Evaluation of Hand Reeled Silk Yarn

2021 ◽  
pp. 1-1
Author(s):  
Kosom Chaitavon ◽  
Sarun - Sumriddetchkajorn ◽  
Chakkrit Kamtongdee ◽  
Sataporn Chanhorm
Keyword(s):  
Real Time ◽  
Quality Evaluation ◽  
Optical Sensing ◽  
Physical Quality ◽  
Sensing System ◽  
Silk Yarn
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