The Partially Observable Markov Decision Process (POMDP), a mathematical framework for decision-making in uncertain environments suffers from the curse of dimensionality. There are various methods that can handle huge sizes of POMDP matrices to create approximate solutions, but no serious effort has been reported to effectively control the size of the POMDP matrices. Manually creating the high-dimension matrices of a POMDP model is a cumbersome and sometimes even impossible task. The PCMRPP (POMDP file Creator for Mobile Robot Path Planning) software package implements a novel algorithm to programmatically generate these matrices such that: •The sizes of the matrices can be controlled by configuring the granularity of discretization of the components of the state and•The sparseness of the matrices can be controlled by configuring the spread of the observation probability distribution. This kind of flexibility allows one to achieve a trade-off between time complexity and the level of robustness of the POMDP solution.
This paper investigates micromachined antenna performance operating at 5 GHz for radio frequency (RF) energy harvesting applications by comparing different substrate materials and fabrication modes. The research aims to discover appropriate antenna designs that can be integrated with the rectifier circuit and fabricated in a CMOS (Complementary Metal-Oxide Semiconductor)-compatible process approach. Therefore, the investigation involves the comparison of three different micromachined antenna substrate materials, including micromachined Si surface, micromachined Si bulk with air gaps, and micromachined glass-surface antenna, as well as conventional RT/Duroid-5880 (Rogers Corp., Chandler, AZ, USA)-based antenna as the reference. The characteristics of the antennas have been analysed using CST-MWS (CST MICROWAVE STUDIO®-High Frequency EM Simulation Tool). The results show that the Si-surface micromachined antenna does not meet the parameter requirement for RF antenna specification. However, by creating an air gap on the Si substrate using a micro-electromechanical system (MEMS) process, the antenna performance could be improved. On the other hand, the glass-based antenna presents a good S11 parameter, wide bandwidth, VSWR (Voltage Standing Wave Ratio) ≤ 2, omnidirectional radiation pattern and acceptable maximum gain of >5 dB. The measurement results on the fabricated glass-based antenna show good agreement with the simulation results. The study on the alternative antenna substrates and structures is especially useful for the development of integrated patch antennas for RF energy harvesting systems.
Since diagnostic laboratories handle large COVID-19 samples, researchers have established laboratory-based assays and developed biosensor prototypes. Both share the same purpose; to ascertain the occurrence of air and surface contaminations by the SARS-CoV-2 virus. However, the biosensors further utilize internet-of-things (IoT) technology to monitor COVID-19 virus contamination, specifically in the diagnostic laboratory setting. The IoT-capable biosensors have great potential to monitor for possible virus contamination. Numerous studies have been done on COVID-19 virus air and surface contamination in the hospital setting. Through reviews, there are abundant reports on the viral transmission of SARS-CoV-2 through droplet infections, person-to-person close contact and fecal-oral transmission. However, studies on environmental conditions need to be better reported. Therefore, this review covers the detection of SARS-CoV-2 in airborne and wastewater samples using biosensors with comprehensive studies in methods and techniques of sampling and sensing (2020 until 2023). Furthermore, the review exposes sensing cases in public health settings. Then, the integration of data management together with biosensors is well explained. Last, the review ended with challenges to having a practical COVID-19 biosensor applied for environmental surveillance samples.