Preference Classification Method Using EEG Analysis Based on Gray Theory and Personality Analysis

This paper introduces a method to classify the preference patterns of sounds on the basis of an electroencephalogram (EEG) analysis and a personality analysis. We analyze the EEG of the left prefrontal cortex by single-point sensing. For EEG recording, a dry-type sensor and few electrodes were used. The proposed feature extraction method employs gray relational grade detection on the frequency bands of EEG and egogram. The gray relational grade is used for extracting the EEG feature. The egogram is extracted for quantifying the subject’s personality. The preference patterns generated when the subject is hearing a sound are classified using the nearest neighbor method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data. These results show that the accuracy rate of the preference classification using the proposed method is better than that using the method that does not to consider the subject’s personality

Preference Classification Method Using EEG Analysis Based on Gray Theory and Personality Analysis

This paper introduces a method to classify the preference patterns of sounds on the basis of an electroencephalogram (EEG) analysis and a personality analysis. We analyze the EEG of the left prefrontal cortex by single-point sensing. For EEG recording, a dry-type sensor and few electrodes were used. The proposed feature extraction method employs gray relational grade detection on the frequency bands of EEG and egogram. The gray relational grade is used for extracting the EEG feature. The egogram is extracted for quantifying the subject’s personality. The preference patterns generated when the subject is hearing a sound are classified using the nearest neighbor method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data. These results show that the accuracy rate of the preference classification using the proposed method is better than that using the method that does not to consider the subject’s personality

OPTIMIZATION OF PROCESS PARAMETERS IN 3D PRINTING FDM BY USING THE TAGUCHI AND GREY RELATIONAL ANALYSIS METHODS

The 3D printing technology is one of the technologies that is developing currently. This machine can make products easily, quickly, and precisely. 3D printing is used to print models, prototypes/modeling, teaching aids for education, health support devices, product design, and many more in 3D shapes. Fused Deposition Modeling (FDM) is the most popular among others 3D printing techniques. In simple concept, it does not need maintenance regarding solvents or glue. The spare parts can be found easily and cheaply.  In this research, we create objects by using Autodesk inventor that is called human denture. Then, it converted to G-Code using Simplyfy3D software version 4.1.2. The G-Code data is used in the 3D printer for making the product. We select parameters to print the product. In this study, we find the optimal parameters of the effect of shrinkage and hardness of the product. The 3 parameters are in this study namely; layer height, print speed, temperature print. The material of human denture is filament PLA +. The Taguchi method and Grey analysis are used to analyze the data result. The results of the analysis for optimal parameters are at Layer Height 0.15 mm, Print Speed 25 mm/s, and Print Temperature 210⁰C

Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm

In any metaheuristic, the parameter values strongly affect the efficiency of an algorithm’s search. This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. For optimal maintenance scheduling with low cost, high reliability, and low violation, the parameter values of the PACS algorithm were tuned using the Taguchi and Gray Relational Analysis (Taguchi-GRA) method through search-based approach. The new parameter values were tested on two systems. i.e., 26- and 36-unit systems for window with operational hours [3000-5000]. The gray relational grade (GRG) performance metric and the Friedman test were used to evaluate the algorithm’s performance. The Taguchi-GRA method that produced the new values for the algorithm’s parameters was shown to be able to provide a better multi-objective generator maintenance scheduling (GMS) solution. These values can be benchmarked in solving multi-objective GMS problems using the multi-objective PACS algorithm and its variants

Antioxidant activity, nutritional, and phenolic composition of sweet potato leaves as affected by harvesting period

In the present study, the nutritional and phenolic composition as well as the antioxidant activity of sweet potato leaves (SPL) harvested in 3 different periods were determined and compared. Furthermore, gray relational analysis was used to compare the comprehensive nutritional value. Results showed SPL HP1 had the highest protein value (30.8 ± 0.4 g/100 g dw), while SPL HP3 had the highest content of vitamin C (104.6 ± 4.9 mg/100 g dw), vitamin E (5.8 ± 0.4 mg/100 g dw), total polyphenol content (9.1 ± 0.3 g/100 g dw), antioxidant activity (DPPH: 7.4 ± 0.1 g VcE/100 g dw; ABTS: 10.6 ± 0.7 g VcE/100 g dw; FRAP: 0.617 ± 0.005 µmol TroloxE/100 g dw), and comprehensive nutritional value (weighted gray relational grade 0.8336). The individual phenolic composition showed the presence of six caffeoylquinic acids, caffeic acid, and two flavonoids (quercetin and isoquercetin), which were significantly different among different harvest periods. In conclusion, HP3 was an optimal period for harvesting SPLFil: Suárez, Santiago. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; Argentina. Chinese Academy of Agricultural Sciences; ChinaFil: Mu, Taihua. Chinese Academy of Agricultural Sciences; ChinaFil: Sun, Hongnan. Chinese Academy of Agricultural Sciences; ChinaFil: Añon, Maria Cristina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; Argentin

Antioxidant activity, nutritional, and phenolic composition of sweet potato leaves as affected by harvesting period

In the present study, the nutritional and phenolic composition as well as the antioxidant activity of sweet potato leaves (SPL) harvested in 3 different periods were determined and compared. Furthermore, gray relational analysis was used to compare the comprehensive nutritional value. Results showed SPL HP1 had the highest protein value (30.8 ± 0.4 g/100 g dw), while SPL HP3 had the highest content of vitamin C (104.6 ± 4.9 mg/100 g dw), vitamin E (5.8 ± 0.4 mg/100 g dw), total polyphenol content (9.1 ± 0.3 g/100 g dw), antioxidant activity (DPPH: 7.4 ± 0.1 g VcE/100 g dw; ABTS: 10.6 ± 0.7 g VcE/100 g dw; FRAP: 0.617 ± 0.005 μmol TroloxE/100 g dw), and comprehensive nutritional value (weighted gray relational grade 0.8336). The individual phenolic composition showed the presence of six caffeoylquinic acids, caffeic acid, and two flavonoids (quercetin and isoquercetin), which were significantly different among different harvest periods. In conclusion, HP3 was an optimal period for harvesting SPL.Centro de Investigación y Desarrollo en Criotecnología de Alimento