The behaviors of children with autism spectrum disorder (ASD) are often erratic and difficult to predict. Most of the time, they are unable to communicate effectively in their own language. Instead, they communicate using hand gestures and pointing phrases. Because of this, it can be difficult for caregivers to grasp their patients’ requirements, although early detection of the condition can make this much simpler. Assistive technology and the Internet of Things (IoT) can alleviate the absence of verbal and nonverbal communication in the community. The IoT-based solutions use machine Learning (ML) and deep learning (DL) algorithms to diagnose and enhance the lives of patients. A thorough review of ASD techniques in the setting of IoT devices is presented in this research. Identifying important trends in IoT-based health care research is the primary objective of this review. There is also a technical taxonomy for organizing the current articles on ASD algorithms and methodologies based on different factors such as AI, SS network, ML, and IoT. On the basis of criteria such as accuracy and sensitivity, the statistical and operational analyses of the examined ASD techniques are presented.

This paper presents the analysis and design of the harmonic rejection (HR) low-noise amplifier (LNA) with the fully passive source degeneration notch filter. The proposed HR LNA provides the rejection for the strong harmonics ( 3 r d ) of the local oscillator (LO) frequencies, where the HR mixer does not provide sufficient HR performance. The proposed 3 r d harmonic notch filter modulates the source degeneration factor and the impedance matching performance thereafter. This effect further helps the blocking of the harmonic signal. The proposed LNA provides 11 dB gain at the fundamental frequency (2.1 GHz) while rejecting the 3rd harmonic component by 37 dBc. Compared to the conventional LNA, the 3rd harmonic notch performance is improved by 23 dB. Additionally, the LNA achieves a minimum noise figure of 3.1 dB, third order input intercept point ( I I P 3 ) of 0.5 dBm, input reflection (S 11 ) below −10 dB from 1.8 GHz–2.3 GHz operational frequency range, and consumed 19 mW of power from a 1.2 V supply.

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Due to global efforts to save energy, digital light processing (DLP) and direct view televisions (DVTVs) are being replaced by energy-efficient liquid crystal display (LCD) and light emitting diode (LED) televisions. However, these energy-efficient appliances cause harmonics to be injected into the power distribution system, posing a threat to power quality. This study investigates the harmonics generated by common domestic appliances, particularly LCD and LED TVs used in homes in Ghana. Field harmonic measurements were taken using a C.A. 8335 Power Quality Analyzer at a selected facility and were then replicated in a simulation using MATLAB/SIMULINK to model the facility's area network capacity of 100-kVA, 11kV/433V. The study proposes a notch filter as a harmonic mitigation technique, which is integrated into the simulation design and found to be effective at reducing total harmonic distortion current to 0.05 % when applied in parallel to nonlinear loads. The study also compares the harmonic distortion generated by LED TVs and LCD TVs, finding that both types generate high levels of distortion.