Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that serio...Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that seriously affect everyday life. In this paper, the simultaneous capacity (SIMKAP) experiment-based EEG workload analysis was presented using 45 subjects for multitasking mental workload estimation with subject wise attention loss calculation as well as short term memory loss measurement. Using an open access preprocessed EEG dataset, Discrete wavelet transforms (DWT) was utilized for feature extraction and Minimum redundancy and maximum relevancy (MRMR) technique was used to select most relevance features. Wavelet decomposition technique was also used for decomposing EEG signals into five sub bands. Fourteen statistical features were calculated from each sub band signal to form a 5 × 14 window size. The Neural Network (Narrow) classification algorithm was used to classify dataset for low and high workload conditions and comparison was made using some other machine learning models. The results show the classifier’s accuracy of 86.7%, precision of 84.4%, F1 score of 86.33%, and recall of 88.37% that crosses the state-of-the art methodologies in the literature. This prediction is expected to greatly facilitate the improved way in memory and attention loss impairments assessment.展开更多
A numerical analysis on dual core photonic crystal fiber (DC-PCF) based surface plasmon resonance (SPR) refractive index sensor is presented. The guiding parameters and required sensing performances are examined with ...A numerical analysis on dual core photonic crystal fiber (DC-PCF) based surface plasmon resonance (SPR) refractive index sensor is presented. The guiding parameters and required sensing performances are examined with finite element method (FEM) based software under MATLAB environment. According to simulation, it is warranted that the proposed refractive index sensor offers the maximum amplitude sensitivity of 554.9 refractive index unit (RIU-1) and 636.5 RIU 1 with the maximum wavelength sensitivity of 5800nm/RIU and 11 500nm/RIU, and the sensor resolutions of 1.72 ×10^-5RIU and 8.7× 10^-6 RIU, at analyte refractive index (RI) of 1.40 for x- and y-polarized modes, respectively. As the sensing performance in different wavelength ranges is quite high, the proposed sensor can be used in simultaneous detection for different wavelength ranges. Therefore, the proposed device is of a suitable platform for detecting biological, chemical, biochemical, and organic chemical analytes.展开更多
文摘Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that seriously affect everyday life. In this paper, the simultaneous capacity (SIMKAP) experiment-based EEG workload analysis was presented using 45 subjects for multitasking mental workload estimation with subject wise attention loss calculation as well as short term memory loss measurement. Using an open access preprocessed EEG dataset, Discrete wavelet transforms (DWT) was utilized for feature extraction and Minimum redundancy and maximum relevancy (MRMR) technique was used to select most relevance features. Wavelet decomposition technique was also used for decomposing EEG signals into five sub bands. Fourteen statistical features were calculated from each sub band signal to form a 5 × 14 window size. The Neural Network (Narrow) classification algorithm was used to classify dataset for low and high workload conditions and comparison was made using some other machine learning models. The results show the classifier’s accuracy of 86.7%, precision of 84.4%, F1 score of 86.33%, and recall of 88.37% that crosses the state-of-the art methodologies in the literature. This prediction is expected to greatly facilitate the improved way in memory and attention loss impairments assessment.
文摘A numerical analysis on dual core photonic crystal fiber (DC-PCF) based surface plasmon resonance (SPR) refractive index sensor is presented. The guiding parameters and required sensing performances are examined with finite element method (FEM) based software under MATLAB environment. According to simulation, it is warranted that the proposed refractive index sensor offers the maximum amplitude sensitivity of 554.9 refractive index unit (RIU-1) and 636.5 RIU 1 with the maximum wavelength sensitivity of 5800nm/RIU and 11 500nm/RIU, and the sensor resolutions of 1.72 ×10^-5RIU and 8.7× 10^-6 RIU, at analyte refractive index (RI) of 1.40 for x- and y-polarized modes, respectively. As the sensing performance in different wavelength ranges is quite high, the proposed sensor can be used in simultaneous detection for different wavelength ranges. Therefore, the proposed device is of a suitable platform for detecting biological, chemical, biochemical, and organic chemical analytes.
