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
Antennas are an indispensable element in wireless networks. For long-distance wireless communication, antenna gains need to be very strong (highly directive) because the signal from the antenna loses a lot of str...Antennas are an indispensable element in wireless networks. For long-distance wireless communication, antenna gains need to be very strong (highly directive) because the signal from the antenna loses a lot of strength as it travels over long distances. This is true in the military with missile, radar, and satellite systems, etc. Antenna arrays are commonly employed to focus electromagnetic waves in a certain direction that cannot be achieved perfectly with a single-element antenna. The goal of this study is to design a rectangular microstrip high-gain 2 × 1 array antenna using ADS Momentum. This microstrip patch array design makes use of the RT-DUROID 5880 as a substrate with a dielectric constant of 2.2, substrate height of 1.588 mm, and tangent loss of 0.001. To achieve efficient gain and return loss characteristics for the proposed array antenna, RT-Duroid is a good choice of dielectric material. The designed array antenna is made up of two rectangular patches, which have a resonance frequency of 3.3 GHz. These rectangular patches are excited by microstrip feed lines with 13 mm lengths and 4.8 mm widths. The impedance of the patches is perfectly matched by these transmission lines, which helps to get better antenna characteristics. At a resonance frequency of 3.3 GHz, the suggested antenna array has a directivity of 10.50 dB and a maximum gain of 9.90 dB in the S-band. The S parameters, 3D radiation pattern, directivity, gain, and efficiency of the constructed array antenna are all available in ADS Momentum.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Antennas are an indispensable element in wireless networks. For long-distance wireless communication, antenna gains need to be very strong (highly directive) because the signal from the antenna loses a lot of strength as it travels over long distances. This is true in the military with missile, radar, and satellite systems, etc. Antenna arrays are commonly employed to focus electromagnetic waves in a certain direction that cannot be achieved perfectly with a single-element antenna. The goal of this study is to design a rectangular microstrip high-gain 2 × 1 array antenna using ADS Momentum. This microstrip patch array design makes use of the RT-DUROID 5880 as a substrate with a dielectric constant of 2.2, substrate height of 1.588 mm, and tangent loss of 0.001. To achieve efficient gain and return loss characteristics for the proposed array antenna, RT-Duroid is a good choice of dielectric material. The designed array antenna is made up of two rectangular patches, which have a resonance frequency of 3.3 GHz. These rectangular patches are excited by microstrip feed lines with 13 mm lengths and 4.8 mm widths. The impedance of the patches is perfectly matched by these transmission lines, which helps to get better antenna characteristics. At a resonance frequency of 3.3 GHz, the suggested antenna array has a directivity of 10.50 dB and a maximum gain of 9.90 dB in the S-band. The S parameters, 3D radiation pattern, directivity, gain, and efficiency of the constructed array antenna are all available in ADS Momentum.
