scholarly journals Suhu Pemanas Sampel Optimal Untuk Klasifikasi Teh Hitam Menggunakan Electronic Nose

2019 ◽  
Vol 9 (1) ◽  
pp. 45 ◽  
Author(s):  
Danang Lelono ◽  
Kuwat Triyana
Keyword(s):  
Electronic Nose ◽  
Heating Temperature ◽  
Principal Component ◽  
Black Tea ◽  
Total Sample ◽  
Sensor Response ◽  
Sample Heating ◽  
Total Data ◽  
Temperature Optimization ◽  
Measured Sample

 The optimization of heating temperature of black tea samples for the measurement of aroma with electronic nose (e-nose) has been successfully performed. Sample heating is done because black tea has a low aroma intensity and easily lost. However, the selection of such temperature should be selective because it can result in damage to the aroma of the sample. Therefore, temperature optimization needs to be done so that the resulting sensor response comes from the transformation of the undamaged aroma.The method used to obtain the optimum heating temperature by analyzing the sensor response of the aroma transformation that is captured by e-nose. Consistency and pattern changes formed from the sensor response are used as a comparison of optimal heating temperature selection. The measured sample varied in temperature (30 - 60 °C) so that the resulting sensor response was observed. Change in patterns indicate the aroma has been burning. After optimal temperature is obtained then black tea (50 gr) Broken Orange Pokoe, Broken Pokoe II and Bohea with a total sample of 300 bags were measured with e-nose. For further analysis, the result of classification by method of Principal Component Analysis (PCA) as proof of sample heating temperature optimization successfully done.The experimental results show optimal sample heating for black tea 3 quality 40 - 45 °C. After then with the third PCA the sample can be classified up to 92.5% of the total data variant. This indicates the aroma of tea is relatively constant and there is no pattern change.

scholarly journals Klasifikasi Teh Hijau dan Teh Hitam Tambi-Pagilaran dengan Metode Principal Component Analysis (PCA) Menggunakan E-Nose

2018 ◽  
Vol 8 (1) ◽  
pp. 61
Author(s):  
Inca Inca ◽  
Triyogatama Wahyu Widodo ◽  
Danang Lelono
Keyword(s):  
Feature Extraction ◽  
Green Tea ◽  
Principal Component ◽  
Black Tea ◽  
Extraction Process ◽  
Sensor Response ◽  
Tea Quality ◽  
Pca Method ◽  
The Difference

This research aims to classification of samples of green tea and black tea originated from different planting sites,  Tambi and Pagilaran. Samples of green tea and black tea; quality I (BOP), quality II (BP), quality III (Bohea) were each collected from Tambi and Pagilaran to analyze the charasteristic of both sample from both sites. Measurements of tea samples were performed using a dynamic e-nose device based on a MOS gas sensor, with a maximum set point temperature of 40ºC, flushing 300 seconds, collecting 120 seconds, and purging 80 seconds for 10 cycles repeatedly. The resulting sensor response is then processed using the difference method for baseline manipulation. Characteristic of extraction process on the sensor response results is carried out in three methods; relative, fractional change, and integral. Matrix data of the feature extraction results was reduced using the PCA method by mapping the aroma patterns of each sample using 2-PCA components. The PCA reduction results in integral feature extraction showed the largest percentage of cumulative variance in classifying green tea sample data by 97% and black tea by 100%. The large percentage value of cumulative variance indicates PCA can differentiate samples of green tea and black tea from Tambi and Pagilaran well.

scholarly journals Klasifikasi Kemurnian Daging Sapi Berbasis Electronic Nose dengan Metode Principal Component Analysis

2016 ◽  
Vol 6 (1) ◽  
pp. 47 ◽  
Author(s):  
Fachri Rosyad ◽  
Danang Lenono
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Total Sample ◽  
Component Analysis ◽  
Test Method ◽  
Total Variance ◽  
Sample Mass ◽  
Metal Oxide Gas Sensor ◽  
Classification Test

AbstrakDaging merupakan bahan makanan yang dikonsumsi secara luas, sehingga dibutuhkan standar kualitas tertentu agar dapat aman dikonsumsi dan tidak merugikan konsumen. Standar tersebut diantaranya adalah kesegaran dan kemurnian. Dalam praktek jual beli daging ditemukan adanya kasus pencampuran daging sapi dengan daging babi sehingga dapat merugikan konsumen. Untuk mengetahui kemurnian daging sapi tersebut dibutuhkan pengujian dengan menggunakan tes aroma berbasis electronic nose.Sampel daging sapi campuran dibuat dengan variasi kandungan daging babi sebesar 20%, 40%, 60%, dan 80% dari total massa sampel, dengan massa sampel adalah 20 gram. Pengambilan data selama 10 hari dilakukan dengan proses sensing dan flushing masing-masing selama 180 detik dengan pengulangan sebanyak 6 kali per hari. Pengolahan data dilakukan dalam beberapa tahap yang meliputi prapemrosesan sinyal dengan manipulasi baseline, ekstraksi ciri dengan menghitung luas kurva sinyal menggunakan pendekatan integral aturan trapesium, dan analisis multivariat menggunakan Principal Component Analysis (PCA).Hasil persentase variansi kumulatif dua komponen utama pada pengujian klasifikasi antara daging sapi dengan daging babi adalah sebesar 99,9%, sedangkan pada pengujian klasifikasi antara daging sapi murni dengan daging sapi campuran adalah sebesar 99,6%. Dengan demikian, electronic nose dapat membedakan antara daging sapi murni dengan daging sapi campuran. Kata kunci— Electronic nose, sensor gas metal oksida, klasifikasi, kemurnian daging, Principal Component Analysis. AbstractMeat is a widely consumed food, therefore it requires certain quality standards to be safe to consumed and does not harm the consumers. Several of those standards including meat freshness and meat purity. Recently it has been found some cases of pork adulteration in beef which consequently could harm the consumers. In order to examine the purity of beef, it required test method based on odor characteristics by using electronic nose.Adulterated beef samples were prepared with pork content within samples varied by 20%, 40%, 60%, and 80% of total sample mass where the sample mass is 20 grams. The 10 days data collecting consists of sensing and flushing cycles for 180 seconds each cycles, with 6 times process repeating over 1 day. Data processing was carried out in several stages which including signal preprocessing based on baseline manipulation, feature extraction by calculating the area of the response signal curve by using trapezoidal rule of integral approximation, and multivariate analysis using PCA.Cumulative percentage of variance of two principal components of beef and pork classification test yields at 99.9% of total variance, and classification test between pure beef and adulterated beef resulting in 99.6% of total variance. Therefore, it can be concluded that electronic nose can classify between pure beef and adulterated beef. Keywords— Electronic nose, metal-oxide gas sensor, classification, meat purity, Principal Component Analysis.

scholarly journals The Electronic Nose Coupled with Chemometric Tools for Discriminating the Quality of Black Tea Samples In Situ

Chemosensors ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 29 ◽  
Author(s):  
Shidiq Nur Hidayat ◽  
Kuwat Triyana ◽  
Inggrit Fauzan ◽  
Trisna Julian ◽  
Danang Lelono ◽  
...  
Keyword(s):  
Electronic Nose ◽  
External Validation ◽  
Principal Component ◽  
Black Tea ◽  
Oxide Semiconductor ◽  
Support Vector ◽  
Quality Level ◽  
Validation Data ◽  
Signal Preprocessing

An electronic nose (E-nose), comprising eight metal oxide semiconductor (MOS) gas sensors, was used in situ for real-time classification of black tea according to its quality level. Principal component analysis (PCA) coupled with signal preprocessing techniques (i.e., time set value preprocessing, F1; area under curve preprocessing, F2; and maximum value preprocessing, F3), allowed grouping the samples from seven brands according to the quality level. The E-nose performance was further checked using multivariate supervised statistical methods, namely, the linear and quadratic discriminant analysis, support vector machine together with linear or radial kernels (SVM-linear and SVM-radial, respectively). For this purpose, the experimental dataset was split into two subsets, one used for model training and internal validation using a repeated K-fold cross-validation procedure (containing the samples collected during the first three days of tea production); and the other, for external validation purpose (i.e., test dataset, containing the samples collected during the 4th and 5th production days). The results pointed out that the E-nose-SVM-linear model together with the F3 signal preprocessing method was the most accurate, allowing 100% of correct predictive classifications (external-validation data subset) of the samples according to their quality levels. So, the E-nose-chemometric approach could be foreseen has a practical and feasible classification tool for assessing the black tea quality level, even when applied in-situ, at the harsh industrial environment, requiring a minimum and simple sample preparation. The proposed approach is a cost-effective and fast, green procedure that could be implemented in the near future by the tea industry.

Cardiorespiratory fitness is positively associated with both healthy and western dietary pattern in Iranian middle-aged

2020 ◽  
pp. 1-10
Author(s):  
Hossein Shahinfar ◽  
Farhang Djafari ◽  
Nadia Babaei ◽  
Samira Davarzani ◽  
Mojdeh Ebaditabar ◽  
...  
Keyword(s):  
Cardiorespiratory Fitness ◽  
Dietary Patterns ◽  
Dietary Pattern ◽  
Principal Component ◽  
Total Sample ◽  
Linear Regression Models ◽  
Middle Aged ◽  
Anthropometric Measures ◽  
Western Dietary Pattern ◽  
Healthy Dietary Pattern

Abstract. Background: The association between dietary patterns and cardiorespiratory fitness (CRF) is not well established. Objective: We sought to investigate association between a posteriori dietary pattern and CRF in middle-aged adults. Design: Adults (n = 276), aged 20–74 years, who were residents of Tehran, Iran were recruited. Diet was assessed by using a validated 168-item semi-quantitative food frequency questionnaire. Principal component analysis was used to derive dietary patterns. Socio-economic status, anthropometric measures, body composition, and blood pressure were recorded. CRF was assessed by using a graded exercise treadmill test. Analysis of variance and linear regression models were used to discern the association between dietary patterns and CRF. Results: Higher scores of the healthy dietary pattern had no association with VO2max (p = 0.13 ). After controlling for potential confounders, VO2max was positively associated across tertiles of healthy dietary patterns (p < 0.001). Higher adherence to the “mixed” dietary pattern was inversely related to VO2max (p < 0.01). After adjusting for confounders, the significant association disappeared (p = 0.14). Higher scores of the “Western” dietary pattern was not associated with VO2max (p = 0.06). However, after controlling for potential confounders, VO2max was positively associated with the “Western” dietary pattern (p = 0.01). A positive linear association between the “healthy” dietary pattern and CRF for the total sample (R2 = 0.02; p < 0.01) were presented. Conclusions: Overall, our findings suggest that higher adherence to a “healthy” and “Western” dietary pattern was positively associated with CRF. However, further studies are required to examine and clarify the causal relationship between dietary patterns and CRF.

Investigating Occupation Wise Perception of Customers Towards Access to Cooperative Banking Services

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Neetu Andotra ◽  
Tarsem Lal
Keyword(s):  
Secondary Data ◽  
Principal Component ◽  
Himachal Pradesh ◽  
Primary Data ◽  
Varimax Rotation ◽  
Banking Services ◽  
Banking Service ◽  
Total Data ◽  
Cooperative Banks ◽  
Secondary Information

The present paper aims at investigating the occupation-wise perception of customers towards access to cooperative banking services. The study is both expressive and evaluative in nature. In order to investigate the perception of customers towards access to cooperative banking services, both primary and secondary data has been collected. The primary data have been collected from 540 customers of cooperative banks operating in three northern states of India i.e J&K, Himachal Pradesh, and Punjab. The technique of factor analysis has been used through SPSS (version 17.00) with Principal Component Analysis along with varimax rotation for summarisation of the total data into minimum factors. Secondary information was collected from published sources i.e books, journals, files, cooperative bulletins, organizational reports, annual drafts of Planning and Statistical Department (Government of J&K, Himachal Pradesh, and Punjab), RBI reports, magazines, and Internet. ANOVA has been applied for data analysis. The results of the study shows that there exits significant means difference between perception of customers towards access to Cooperative banking service.

scholarly journals STATISTICAL MULTIVARIATE ANALYSIS APPLIED TO ENVIRONMENTAL CHARACTERIZATION OF SOIL IN SEMIARID REGION1

2019 ◽  
Vol 32 (1) ◽  
pp. 200-210
Author(s):  
Antônio Italcy de Oliveira Júnior ◽  
Luiz Alberto Ribeiro Mendonça ◽  
Sávio de Brito Fontenele ◽  
Adriana Oliveira Araújo ◽  
Maria Gorethe de Sousa Lima Brito
Keyword(s):  
Organic Matter Content ◽  
Principal Component ◽  
Matter Content ◽  
Multivariate Statistical ◽  
Statistical Tool ◽  
Environmental Characterization ◽  
Hierarchical Grouping ◽  
Two Factors ◽  
Total Data

ABSTRACT Soil is a dynamic and complex system that requires a considerable number of samples for analysis and research purposes. Using multivariate statistical methods, favorable conditions can be created by analyzing the samples, i.e., structural reduction and simplification of the data. The objective of this study was to use multivariate statistical analysis, including factorial analysis (FA) and hierarchical groupings, for the environmental characterization of soils in semiarid regions, considering anthropic (land use and occupation) and topographic aspects (altitude, moisture, granulometry, PR, and organic-matter content). As a case study, the São José Hydrographic Microbasin, which is located in the Cariri region of Ceará, was considered. An FA was performed using the principal component method, with normalized varimax rotation. In hierarchical grouping analysis, the “farthest neighbor” method was used as the hierarchical criterion for grouping, with the measure of dissimilarity given by the “square Euclidean distance.” The FA indicated that two factors explain 75.76% of the total data variance. In the analysis of hierarchical groupings, the samples were agglomerated in three groups with similar characteristics: one with samples collected in an area of the preserved forest and two with samples collected in areas with more anthropized soils. This indicates that the statistical tool used showed sensitivity to distinguish the most conserved soils and soils with different levels of anthropization.

Refinement and Psychometric Properties of the Self-Efficacy for Sleep Hygiene Inventory

2020 ◽  
pp. 019394592094097
Author(s):  
Christine S. Gipson ◽  
Jenifer M. Chilton ◽  
Eric Stocks
Keyword(s):  
Young Adults ◽  
Focus Groups ◽  
Self Efficacy ◽  
Psychometric Testing ◽  
Principal Component ◽  
Sleep Hygiene ◽  
Total Sample ◽  
The Self ◽  
Reliable Measure ◽  
Electronic Survey

The purpose of this study was to determine key concepts of self-efficacy for sleep hygiene among young adults/college students and sleep experts, and to refine the Self-Efficacy for Sleep Hygiene Inventory. The Self-Efficacy for Sleep Hygiene Inventory was revised using input from young adult focus groups and experts. Information from focus groups informed instrument revision. The revised instrument was distributed using an electronic survey to young adults age 18–26 years for a total sample of 296. A principal component analysis with Varimax Orthogonal Rotation was conducted resulting in a three-factor solution. Cronbach’s alphas were: .85 for Behaviors to Adopt (nine items), .79 for Manage Mindset and Environment (eight items), .70 for Behaviors to Avoid (eight items), and .88 for the inventory (twenty-five items). Initial psychometric testing of the Self-Efficacy for Sleep Hygiene Inventory-Revised indicates that it is a reliable measure of self-efficacy for sleep hygiene in young adults age 18–26 years.

scholarly journals Discrimination between Alternative Herbal Medicines from Different Categories with the Electronic Nose

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2936 ◽  
Author(s):  
Xianghao Zhan ◽  
Xiaoqing Guan ◽  
Rumeng Wu ◽  
Zhan Wang ◽  
You Wang ◽  
...  
Keyword(s):  
Herbal Medicine ◽  
Electronic Nose ◽  
Nearest Neighbor ◽  
Herbal Medicines ◽  
Principal Component ◽  
Support Vector ◽  
Linear Discriminant ◽  
Convenient Means ◽  
Electronic Nose System ◽  
Insight Into

As alternative herbal medicine gains soar in popularity around the world, it is necessary to apply a fast and convenient means for classifying and evaluating herbal medicines. In this work, an electronic nose system with seven classification algorithms is used to discriminate between 12 categories of herbal medicines. The results show that these herbal medicines can be successfully classified, with support vector machine (SVM) and linear discriminant analysis (LDA) outperforming other algorithms in terms of accuracy. When principal component analysis (PCA) is used to lower the number of dimensions, the time cost for classification can be reduced while the data is visualized. Afterwards, conformal predictions based on 1NN (1-Nearest Neighbor) and 3NN (3-Nearest Neighbor) (CP-1NN and CP-3NN) are introduced. CP-1NN and CP-3NN provide additional, yet significant and reliable, information by giving the confidence and credibility associated with each prediction without sacrificing of accuracy. This research provides insight into the construction of a herbal medicine flavor library and gives methods and reference for future works.

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