scholarly journals Quality grade classification of China commercial moxa floss using electronic nose

Medicine ◽  
2020 ◽  
Vol 99 (33) ◽  
pp. e21556
Author(s):  
Min Yee Lim ◽  
Jian Huang ◽  
Fu-rong He ◽  
Bai-xiao Zhao ◽  
Hui-qin Zou ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Grade Classification ◽  
Quality Grade ◽  
Moxa Floss

scholarly journals Feature Extraction and Classification of Citrus Juice by Using an Enhanced L-KSVD on Data Obtained from Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 916 ◽  
Author(s):  
Wen Cao ◽  
Chunmei Liu ◽  
Pengfei Jia
Keyword(s):  
Feature Extraction ◽  
Kernel Function ◽  
Electronic Nose ◽  
Classification Accuracy ◽  
Extraction Methods ◽  
Object Function ◽  
Optimal Value ◽  
Processed Products

Aroma plays a significant role in the quality of citrus fruits and processed products. The detection and analysis of citrus volatiles can be measured by an electronic nose (E-nose); in this paper, an E-nose is employed to classify the juice which is stored for different days. Feature extraction and classification are two important requirements for an E-nose. During the training process, a classifier can optimize its own parameters to achieve a better classification accuracy but cannot decide its input data which is treated by feature extraction methods, so the classification result is not always ideal. Label consistent KSVD (L-KSVD) is a novel technique which can extract the feature and classify the data at the same time, and such an operation can improve the classification accuracy. We propose an enhanced L-KSVD called E-LCKSVD for E-nose in this paper. During E-LCKSVD, we introduce a kernel function to the traditional L-KSVD and present a new initialization technique of its dictionary; finally, the weighted coefficients of different parts of its object function is studied, and enhanced quantum-behaved particle swarm optimization (EQPSO) is employed to optimize these coefficients. During the experimental section, we firstly find the classification accuracy of KSVD, and L-KSVD is improved with the help of the kernel function; this can prove that their ability of dealing nonlinear data is improved. Then, we compare the results of different dictionary initialization techniques and prove our proposed method is better. Finally, we find the optimal value of the weighted coefficients of the object function of E-LCKSVD that can make E-nose reach a better performance.

Intelligent Classification of Cocoa Bean using E-nose

Mekatronika ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 28-35
Author(s):  
Nur Amanda Nazli ◽  
Muhammad Sharfi Najib ◽  
Suhaimi Mohd Daud ◽  
Mujahid Mohammad
Keyword(s):  
Electronic Nose ◽  
Chemical Sensors ◽  
Classification Accuracy ◽  
Electronic Device ◽  
Raw Material ◽  
Cocoa Bean ◽  
Cocoa Beans ◽  
Microsoft Excel ◽  
Specificity And Sensitivity

Cocoa bean (Theobrama cacao) is an essential raw material in the manufacture of chocolate, and their classification is crucial for the synthesis of good chocolate flavour. Cocoa beans appear to be very similar to one another when visualised. Hence, an electronic device named the electronic nose (E-Nose) is used to classify the odor of cocoa beans to give the best cocoa bean quality. E-nose is a set of an array of chemical sensors used to sense the gas vapours produced by the cocoa bean and the raw data collected was kept in Microsoft Excel, and the classification took place in Octave. They then underwent normalisation technique to increase classification accuracy, and their features were extracted using mean calculation. The features were classified using CBR, and the similarity value is obtained. The results show that CBR's classification accuracy, specificity and sensitivity are all 100%.

Primary Pulmonary Meningioma With Rhabdoid Features

2018 ◽  
Vol 27 (4) ◽  
pp. 457-463 ◽  
Author(s):  
Rūta Žulpaitė ◽  
Žymantas Jagelavičius ◽  
Ugnius Mickys ◽  
Ričardas Janilionis
Keyword(s):  
World Health Organization ◽  
Wedge Resection ◽  
Neck Region ◽  
Disease Recurrence ◽  
World Health ◽  
Head And Neck Region ◽  
Grade Classification ◽  
Health Organization ◽  
Rhabdoid Features

Only 1% to 2% of meningiomas have primary extrameningeal location, which is mostly head and neck region. Primary pulmonary meningiomas (PPMs) are even more uncommon with up to 50 cases reported in the literature. Only 5 cases of PPM with confirmed or possible malignancy have been previously described. Three-grade classification of meningiomas with the accordingly growing risk of aggressive behavior of the tumor has been proposed by the World Health Organization. As it is based on correlations between morphological and clinical features of intracranial meningiomas, the analogous prediction of ectopic tumors prognosis remains questionable due to scarce number of cases. In this article, we present a rare case of PPM with rhabdoid features (World Health Organization grade III), which lacked other signs of malignancy. The patient is doing well for 2 years after the thoracoscopic wedge resection without evidence of the disease recurrence.

Classification of buildings mold threat using electronic nose

2017 ◽  
Author(s):  
Grzegorz Łagód ◽  
Zbigniew Suchorab ◽  
Łukasz Guz ◽  
Henryk Sobczuk
Keyword(s):  
Electronic Nose

scholarly journals Deteksi Formalin Pada Buah Tomat (Lycopersicum esculentum Mill) Dengan Teknologi Hidung Elektronik (Electronic Nose)

2019 ◽  
Vol 4 (2) ◽  
pp. 359-366
Author(s):  
Irfan Maibriadi ◽  
Ratna Ratna ◽  
Agus Arip Munawar
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Lycopersicum Esculentum ◽  
Olfactory Ability ◽  
Pca Method ◽  
The Difference ◽  
Electronic Nose Technology

Abstrak,  Tujuan dari penelitian ini adalah mendeteksi kandungan dan kadar formalin pada buah tomat dengan menggunakan instrument berbasis teknologi Electronic nose. Penelitian ini menggunakan buah tomat yang telah direndam dengan formalin dengan kadar 0.5%, 1%, 2%, 3%, 4%, dan buah tomat tanpa perendaman dengan formalin (0%). Jumlah sampel yang digunakan pada penelitian ini adalah sebanyak 18 sampel. Pengukuran spektrum beras menggunakan sensor Piezoelectric Tranducer. Klasifikasi data spektrum buah tomat menggunakan metode Principal Component Analysis (PCA) dengan pretreatment nya adalah Gap Reduction. Hasil penelitian ini diperoleh yaitu: Hidung elektronik mulai merespon aroma formalin pada buah tomat pada detik ke-8.14, dan dapat mengklasifikasikan kandungan dan kadar formalin pada buah tomat pada detik ke 25.77. Hidung elektronik yang dikombinasikan dengan metode principal component analysis (PCA) telah berhasil mendeteksikandungan dan kadar formalin pada buah tomat dengan tingkat keberhasilan sebesar 99% (PC-1 sebesar 93% dan PC-2 sebesar 6%). Perbedaan kadar formalin menjadi faktor utama yang menyebabkan Elektronik nose mampu membedakan sampel buah tomat yang diuji, karena semakin tinggi kadar formalin pada buah tomat maka aroma khas dari buah tomat pun semakin menghilang, sehingga Electronic nose yang berbasis kemampuan penciuman dapat membedakannya.Detect Formaldehyde on Tomato (Lycopersicum esculentum Mill) With Electronic Nose TechnologyAbstract, The purpose of this study is to detect the contents and levels of formalin in tomatoes by using instruments based on Electronic nose technology. This study used tomatoes that have been soaked in formalin with a concentration of 0.5%, 1%, 2%, 3%, 4%, 5% and tomatoes without soaking with formalin (0%). The samples in this study were 18 samples. The measurements of the intensity on tomatoes aroma were using Piezoelectric Transducer sensors. The classification of tomato spectrum data was using the Principal Component Analysis (PCA) method with Gap Reduction pretreatment. The results of this study were obtained: the Electronic nose began to respond the smell of formalin on tomatoes at 8.14 seconds, and it could classify the content and formalin levels in tomatoes at 25.77 seconds. Electronic nose combined with the principal component analysis (PCA) method have successfully detected the content and levels of formalin in tomatoes with a success rate at 99% (PC-1 of 93% and PC-2 of 6%). The difference of grade formalin levels is the main factor that causes Electronic nose to be able to distinguish the tomato samples tested, because the higher of formalin content in tomatoes, the distinctive of tomatoes aroma is increasingly disappearing. Thereby, the Electronic nose based on  the olfactory ability can distinguish them. 

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