Long-range Transmission Research Articles

Two-Lane DNN Equalizer Using Balanced Random-Oversampling for W-Band PS-16QAM RoF Delivery over 4.6 km

For W-band long-range mm-wave wireless transmission systems, nonlinearity issues resulting from photoelectric devices, optical fibers, and wireless power amplifiers can be handled by deep learning equalization algorithms. In addition, the PS technique is considered an effective measure to further increase the capacity of the modulation-constraint channel. However, since the probabilistic distribution of m-QAM varies with the amplitude, there have been difficulties in learning valuable information from the minority class. This limits the benefit of nonlinear equalization. To overcome the imbalanced machine learning problem, we propose a novel two-lane DNN (TLD) equalizer using the random oversampling (ROS) technique in this paper. The combination of PS at the transmitter and ROS at the receiver improved the overall performance of the W-band wireless transmission system, and our 4.6-km ROF delivery experiment verified its effectiveness for the W-band mm-wave PS-16QAM system. Based on our proposed equalization scheme, we achieved single-channel 10-Gbaud W-band PS-16QAM wireless transmission over a 100 m optical fiber link and a 4.6 km wireless air-free distance. The results show that compared with the typical TLD without ROS, the TLD-ROS can improve the receiver‘s sensitivity by 1 dB. Furthermore, a reduction of 45.6% in complexity was achieved, and we were able to reduce training samples by 15.5%. Considering the actual wireless physical layer and its requirements, there is much to be gained from the joint use of deep learning and balanced data pre-processing techniques.

Student close contact behavior and COVID-19 transmission in China's classrooms.

Classrooms are high-risk indoor environments, so analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in classrooms is important for determining optimal interventions. Due to the absence of human behavior data, it is challenging to accurately determine virus exposure in classrooms. A wearable device for close contact behavior detection was developed, and we recorded >250,000 data points of close contact behaviors of students from grades 1 to 12. Combined with a survey on students' behaviors, we analyzed virus transmission in classrooms. Close contact rates for students were 37 ± 11% during classes and 48 ± 13% during breaks. Students in lower grades had higher close contact rates and virus transmission potential. The long-range airborne transmission route is dominant, accounting for 90 ± 3.6% and 75 ± 7.7% with and without mask wearing, respectively. During breaks, the short-range airborne route became more important, contributing 48 ± 3.1% in grades 1 to 9 (without wearing masks). Ventilation alone cannot always meet the demands of COVID-19 control; 30 m3/h/person is suggested as the threshold outdoor air ventilation rate in a classroom. This study provides scientific support for COVID-19 prevention and control in classrooms, and our proposed human behavior detection and analysis methods offer a powerful tool to understand virus transmission characteristics and can be employed in various indoor environments.

TRANSMISSION LINE FAULT DETECTION SYSTEM

Transmission line is the most important part of the power system. Transmission lines a principal amount of power. The requirement of power and its allegiance has grown up exponentially over the modern era, and the major role of a transmission line is to transmit electric power from the source area to the distribution network. The exploded between limited production and a tremendous claim has grown the focus on minimizing power losses. Losses like transmission loss and also conjecture factors as like as physical losses to various technical losses, Another thing is the primary factor it has a reactive power and voltage deviation are momentous in the long-range transmission power line. In essentially, fault analysis is a very focusing issue in power system engineering to clear fault in short time and re-establish power system as quickly as possible on very minimum interruption. However, the fault detection that interrupts the transmission line is itself challenging task to investigate fault as well as improving the reliability of the system. The transmission line is susceptible given all parameters that connect the whole power system. This paper presents a review of transmission line fault detection.

TRANSMISSION LINE FAULT DETECTION SYSTEM

Transmission line is the most important part of the power system. Transmission lines a principal amount of power. The requirement of power and its allegiance has grown up exponentially over the modern era, and the major role of a transmission line is to transmit electric power from the source area to the distribution network. The exploded between limited production and a tremendous claim has grown the focus on minimizing power losses. Losses like transmission loss and also conjecture factors as like as physical losses to various technical losses, Another thing is the primary factor it has a reactive power and voltage deviation are momentous in the long-range transmission power line. In essentially, fault analysis is a very focusing issue in power system engineering to clear fault in short time and re-establish power system as quickly as possible on very minimum interruption. However, the fault detection that interrupts the transmission line is itself challenging task to investigate fault as well as improving the reliability of the system. The transmission line is susceptible given all parameters that connect the whole power system. This paper presents a review of transmission line fault detection.

Differential Diagnosis, Prevention, and Treatment of mpox (Monkeypox): A Review for Dermatologists.

The current 2022 mpox (monkeypox) outbreak has been officially recognized as a public health emergency. The mpox clinical symptoms include high fever, fatigue, chills, headache, swollen lymph nodes, muscle aches, and a disseminated painful rash. However, recent cases of mpox have shown a shift in clinical symptoms, with anogenital skin lesions emerging as the predominant feature. Due to the predominant skin manifestations of mpox, dermatologists could be crucial in detecting new mpox cases and educating frontline healthcare professionals about mpox. The mpox virus is continuously evolving and has several variants. Genome sequencing has revealed that the Clade IIb variant is responsible for the 2022 mpox outbreak. Mpox spread may occur through animal-to-human and human-to-human transmission; however, unlike coronavirus disease 2019 (COVID-19), long-range airborne transmission has not been reported. Healthcare professionals are at higher risk of becoming infected since they are usually in close contact with both the patients and potentially contaminated fomites (e.g., examination table, gowns, gloves). Both public and healthcare professionals should take preventive and avoidance measures to limit the spread. Mpox is usually self-limiting and may require only symptomatic treatment; however, it may cause severe complications in special populations such as immunocompromised individuals. For severe infection, clinicians may consider antiviral drugs (off-label), tecovirimat and brincidofovir, originally approved for smallpox treatment. Two smallpox vaccines, ACAM2000® and JYNNEOSTM, can be used as pre-exposure prophylaxis against mpox. JYNNEOSTM, which carries approval for mpox use, has less adverse effect potential than ACAM2000®, and may also be used as post-exposure prophylaxis, preferably within 4 days of exposure.

Metavalent Bonding-Mediated Dual 6s2 Lone Pair Expression Leads to Intrinsic Lattice Shearing in n-Type TlBiSe2.

Metavalent bonding has attracted immense interest owing to its capacity to impart a distinct property portfolio to materials for advanced functionality. Coupling metavalent bonding to lone pair expression can be an innovative way to propagate lattice anharmonicity from lone pair-induced local symmetry-breaking via the soft p-bonding electrons to achieve long-range phonon dampening in crystalline solids. Motivated by the shared chemical design pool for topological quantum materials and thermoelectrics, we based our studies on a three-dimensional (3D) topological insulator TlBiSe2 that held prospects for 6s2 dual-cation lone pair expression and metavalent bonding to investigate if the proposed hypothesis can deliver a novel thermoelectric material. Herein, we trace the inherent phononic origin of low thermal conductivity in n-type TlBiSe2 to dual 6s2 lone pair-induced intrinsic lattice shearing that strongly suppresses the lattice thermal conductivity to a low value of 1.1-0.4 Wm-1 K-1 between 300 and 715 K. Through synchrotron X-ray pair distribution function and first-principles studies, we have established that TlBiSe2 exists not in a monomorphous R-3m structure but as a distribution of distorted configurations. Via a cooperative movement of the constituent atoms akin to a transverse shearing mode facilitated by metavalent bonding in TlBiSe2, the structure shuttles between various energetically accessible low-symmetry structures. The orbital interactions and ensuing multicentric bonding visualized through Wannier functions augment the long-range transmission of atomic displacement effects in TlBiSe2. With additional point-defect scattering, a κlatt of 0.3 Wm-1 K-1 was achieved in TlBiSeS with a maximum n-type thermoelectric figure of merit (zT) of ∼0.8 at 715 K.

Safe CO2 threshold limits for indoor long-range airborne transmission control of COVID-19

CO2-based infection risk monitoring is highly recommended during the current COVID-19 pandemic. However, the CO2 monitoring thresholds proposed in the literature are mainly for spaces with fixed occupants. Determining CO2 threshold is challenging in spaces with changing occupancy due to the co-existence of quanta and CO2 remaining from previous occupants. Here, we propose a new calculation framework for deriving safe excess CO2 thresholds (above outdoor level), Ct, for various spaces with fixed/changing occupancy and analyze the uncertainty involved. We categorized common indoor spaces into three scenarios based on their occupancy conditions, e.g., fixed or varying infection ratios (infectors/occupants). We proved that the rebreathed fraction-based model can be applied directly for deriving Ct in the case of a fixed infection ratio (Scenario 1 and Scenario 2). In the case of varying infection ratios (Scenario 3), Ct derivation must follow the general calculation framework due to the existence of initial quanta/excess CO2. Otherwise, Ct can be significantly biased (e.g., 260 ppm) when the infection ratio varies greatly. Ct can vary significantly based on specific space factors such as occupant number, physical activity, and community prevalence, e.g., 7 ppm for gym and 890 ppm for lecture hall, indicating Ct must be determined on a case-by-case basis. An uncertainty of up to 6 orders of magnitude for Ct was found for all cases due to uncertainty in emissions of quanta and CO2, thus emphasizing the role of accurate emissions data in determining Ct.

Low Genetic Diversity of Vector-Borne Haemoparasites in Dogs and Their Ticks Revealed Local and Long-Range Transmission in Peninsular Malaysia

Molecular methods coupled with phylogenetic analysis are sensitive tools for detecting and classifying parasites. This study used nuclear and mitochondrial gene markers to investigate the host-vector interaction of the vector-borne haemoparasites. The population genetic structures of important vector-borne haemoparasites in dogs, namely, Anaplasma platys, Ehrlichia canis, Babesia vogeli, and Babesia gibsoni, were determined from the nuclear gene of 16S or 18S rRNA gene, gltA and groESL and mitochondrial gene of COX1 across dogs and vector ticks. A total of 220 blood samples and 140 ticks were collected from shelter dogs in Peninsular Malaysia. Out of the positive samples for the vector-borne haemoparasites, 28 positive blood isolates and six tick isolates were selected and characterised. There was a low diversity in tick sequences, while varying degree of variability was observed in dogs’ sequences. Overlapped haplotypes were observed in sequences of dogs and ticks, revealing the possibility of the same infection origin. No regional separation was detected, but similar haplotypes from different regions were observed. These findings contribute to the epidemiology of vector-borne haemoparasites in dogs in Malaysia.

Low Genetic Diversity of Vector-Borne Haemoparasites in Dogs and Their Ticks Revealed Local and Long-Range Transmission in Peninsular Malaysia

Molecular methods coupled with phylogenetic analysis are sensitive tools for detecting and classifying parasites. This study used nuclear and mitochondrial gene markers to investigate the host-vector interaction of the vector-borne haemoparasites. The population genetic structures of important vector-borne haemoparasites in dogs, namely, Anaplasma platys, Ehrlichia canis, Babesia vogeli, and Babesia gibsoni, were determined from the nuclear gene of 16S or 18S rRNA gene, gltA and groESL and mitochondrial gene of COX1 across dogs and vector ticks. A total of 220 blood samples and 140 ticks were collected from shelter dogs in Peninsular Malaysia. Out of the positive samples for the vector-borne haemoparasites, 28 positive blood isolates and six tick isolates were selected and characterised. There was a low diversity in tick sequences, while varying degree of variability was observed in dogs’ sequences. Overlapped haplotypes were observed in sequences of dogs and ticks, revealing the possibility of the same infection origin. No regional separation was detected, but similar haplotypes from different regions were observed. These findings contribute to the epidemiology of vector-borne haemoparasites in dogs in Malaysia.

Review of animal transmission experiments of respiratory viruses: Implications for transmission risk of SARS-COV-2 in humans via different routes.

Exploring transmission risk of different routes has major implications for epidemic control. However, disciplinary boundaries have impeded the dissemination of epidemic information, have caused public panic about "air transmission," "air-conditioning transmission," and "environment-to-human transmission," and have triggered "hygiene theater." Animal experiments provide experimental evidence for virus transmission, but more attention is paid to whether transmission is driven by droplets or aerosols and using the dichotomy to describe most transmission events. Here, according to characteristics of experiment setups, combined with patterns of human social interactions, we reviewed and grouped animal transmission experiments into four categories-close contact, short-range, fomite, and aerosol exposure experiments-and provided enlightenment, with experimental evidence, on the transmission risk of severe acute respiratory syndrome coronavirus (SARS-COV-2) in humans via different routes. When referring to "air transmission," context should be showed in elaboration results, rather than whether close contact, short or long range is uniformly described as "air transmission." Close contact and short range are the major routes. When face-to-face, unprotected, horizontally directional airflow does promote transmission, due to virus decay and dilution in air, the probability of "air conditioning transmission" is low; the risk of "environment-to-human transmission" highly relies on surface contamination and human behavior based on indirect path of "fomite-hand-mucosa or conjunctiva" and virus decay on surfaces. Thus, when discussing the transmission risk of SARS-CoV-2, we should comprehensively consider the biological basis of virus transmission, environmental conditions, and virus decay. Otherwise, risk of certain transmission routes, such as long-range and fomite transmission, will be overrated, causing public excessive panic, triggering ineffective actions, and wasting epidemic prevention resources.

Long-Range EM Communication Underwater With Ultracompact ELF Magneto-Mechanical Antenna

In this article, a long-range underwater electromagnetic (EM) communication system is proposed based on an ultracompact extremely low-frequency (ELF) magnetomechanical transmission antenna (UEMTA). The transmitter mainly includes a waveform generator, a variable frequency drive (VFD), and a three-phase induction motor. The receiver consists of a 200-turn coil and signal analyzer. Based on the equivalent model of a rotating magnetic dipole, the principles of the EM transmission underwater and across the interface of water and air are analyzed. ELF wave propagating underwater in the adjacent area was stronger and decays slowly, which was certificated by the experiment and simulation. Thus, the long-range transmission underwater in the ELF band with digital coding modulation based on the UEMTA is realized, and the longest distance can reach 210 m underwater in the experiment. The transmission of ELF wave across water–air medium based on the system is also tested by the experiment too. The long-range transmission of digital coding modulation across the water–air interface is realized with the longest distance of about 210 m. The ELF transmission technology based on the UEMTA can greatly promote flexible long-distance underwater transmission, the development of satellite-to-submarine communication, and ocean exploration.

Echo State Network Based Nonlinear Equalization for 4.6 km 135 GHz D-Band Wireless Transmission

Reservoir computing (RC) is a novel computational framework derived from recurrent neural networks (RNN). It can reduce the training complexity of RNN and is suitable for time-series learning tasks. The echo state network (ESN) is one of the most popular forms of RC. In this paper, an ESN-based equalizer is applied to perform signal equalization in a wireless D-band communication system to compensate for the nonlinear distortion. Based on the photonics-based technology and multiple amplifiers, a long-range wireless transmission system is successfully established at D-band. We experimentally demonstrated that our proposed wireless transmission link can realize up to 4.6-km wireless delivery of over 8 Gbit/s quadrature phase shift keying (QPSK) millimeter-wave signal at 135 GHz with a bit-error-rate (BER) less than the hard decision forward error correction (HD-FEC) threshold of 3.8 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> . Compared with the traditional CMA equalizer and the Volterra equalizer, the experimental results show that the ESN-based equalizer can achieve a better balance between the BER performance and the computational complexity.

Physics-based acoustic inversion of sound velocity and attenuation in low-velocity marine sediments

Using data from the Yellow Sea, arrival times of the direct wave and surface/bottom reflections from explosive sources to a vertical hydrophone array are used to precisely determine each explosive source’s location, the source energy spectral density (SESD), and the water depth. Long-range propagation waveforms reveal modal dispersion: the ground wave, water wave, Airy phase, etc. There are two high-frequency (HF) groups of water waves. One propagates with the sound speed in the water below the thermocline, the other with a speed close to the sound speed in the water above the thermocline. The HF group arrival times offer a time reference for dispersion analyses, including the ground wave speed at the cutoff frequency and the group velocity at Airy frequency. Associated with a top layer oflow-velocity sediments (LVS), seafloor reflections have two pulses: one from the water-sediment interface, one from the sediment-basement interface; Long-range transmission loss (TL) exhibits abnormal peaks at selected frequencies. Above-mentioned physics characteristics and the SESD-normalized TL(r) and TL(f) in 50–5000 Hz range up to 27.6 km are used for observationally driven inferences of seafloor geo-acoustic parameters, such as the sound velocity and attenuation in the LVS layer, its thickness, the sound velocity in the basement, etc.

Design and Implementation of a Low-Cost Air Quality Network for the Aburra Valley Surrounding Mountains

The densest network for measuring air pollutant concentrations in Colombia is in Medellin, where most sensors are located in the heavily polluted lower parts of the valley. Measuring stations in the higher elevations on the mountains surrounding the valley are not available, which limits our understanding of the valley’s pollutant dynamics and hinders the effectiveness of data assimilation studies using chemical transport models such as LOTOS-EUROS. To address this gap in measurements, we have designed a new network of low-cost sensors to be installed at altitudes above 2000 m.a.s.l. The network consists of custom-built, solar-powered, and remotely connected sensors. Locations were strategically selected using the LOTOS-EUROS model driven by diverse meteorology-simulated fields to explore the effects of the valley wind representation on the transport of pollutants. The sensors transmit collected data to internet gateways for posterior analysis. Various tests to verify the critical characteristics of the equipment, such as long-range transmission modeling and experiments with an R score of 0.96 for the best propagation model, energy power system autonomy, and sensor calibration procedures, besides case exposure to dust and water experiments, to ensure IP certifications. An inter-calibration procedure was performed to characterize the sensors against reference sensors and describe the observation error to provide acceptable ranges for the data assimilation algorithm (&lt;10% nominal). The design, installation, testing, and implementation of this air quality network, oriented towards data assimilation over the Aburrá Valley, constitute an initial experience for the simulation capabilities toward the system’s operative capabilities. Our solution approach adds value by removing the disadvantages of low-cost devices and offers a viable solution from a developing country’s perspective, employing hardware explicitly designed for the situation.

Analysis of Laser Cell Response Characteristics under Different Irradiation Conditions

Although the application of laser wireless energy transmission technology in many fields such as UAV power supply is increasing, the laser incidence angle and beam shift remain the key factors limiting the efficiency of long-range laser wireless energy transmission. In this study, a laser cell response test platform was built to measure and analyze the response characteristics of a laser cell under different laser incidence angles and beam shifts. The results show that the increase in the incident angle intensifies the reflection on the irradiated surface, resulting in a linear decrease in the power density received by the laser cell, which eventually leads to a significant decrease in the output power, and the output power tends to be close to 0 when the incident angle exceeds 75°. The increase in the beam offset distance increases the reverse bias of the cell, which is the main reason for the significant decrease in the output power. The local irradiation also leads to an increase in the heat generation power; when the beam coverage is below 50%, the overall output power tends to be close to 0. This study provides a reference for improving the laser wireless energy transmission efficiency and laser cell optimization.

Design of an IoT platform for data analytics based fault detection and classification in solar PV power plants using CFKC and ODENN

New policies are commenced all over the globe to diminish the use of fossil fuels, which gives rise to the augmented utilization of solar energy (SE). The photovoltaic (PV) system’s performance is extremely environmental variables reliant. Long-range transmission of SE is incompetent as well as complex to carry in the PV system. It can be affected by disparate sorts of faults, which cause severe energy loss all through the system operation. Thus, it is vital to incessantly monitor the solar PV (SPV) system to detect as well classify the faults by preventing energy losses. The IoT applications in SE production engage sensor devices that are fixed to the generation, and transmission, together with distribution equipment. These devices assist in monitoring the operation of the SPV power plant (SPVPP) system remotely in real-time. Presenting a new algorithm that can perform fault detection and classification in a PV system to a higher level of accuracy is the major contribution of this work. Thus, this work designs as well as develops an IoT platform for carrying out analytical tasks that can analyze data generated as of IoT operating systems to detect as well as classify faults in the SPVPP. Initially, the data collected from the dataset is pre-processed in which data duplication is performed using Hadoop distributed file system (HDFS) and then the fault is detected from the pre-processed data using the cosine function based k-means clustering (CFKC) technique in the SPV system. Finally, the obtained fault data is fed into the optimized deep learning centered ENN (ODENN) method which classifies the faults. The proposed techniques detect as well as classify the faults effectively that are experimentally proved by means of comparing them with the prevailing techniques, namely ENN, ANN and SVM, along with KNN in terms of some quality measures. The obtained results for ODENN showed an accuracy of 98.99%, specificity of 97.6%, and a sensitivity of 97.02%.

Photonic-Assisted Scheme for Simultaneous Self-Interference Cancellation, Fiber Dispersion Immunity, and High-Efficiency Harmonic Down-Conversion.

A photonic approach to the cancellation of self-interference in the optical domain with fiber dispersion immunity and harmonic frequency down-conversion function is proposed based on an integrated, dual-parallel, dual-drive Mach-Zehnder modulator (DP-DMZM). A dual-drive Mach-Zehnder modulator (DMZM) is used as an optical interference canceller, which cancels the self-interference from the impaired signal before fiber transmission to avoid the effect of fiber transmission on the cancellation performance. Another DMZM is used to provide carrier-suppressed, local-oscillation (LO)-modulated, high-order double optical sidebands for harmonic frequency down-conversion to release the strict demand for high-frequency LO sources. By regulating the DC bias of the main modulator, the signal of interest (SOI) can be down-converted to the intermediated frequency (IF) band after photoelectric conversion with improved frequency-conversion efficiency, immunity to the fiber-dispersion-induced power-fading (DIPF) effect, and effective signal recovery. Theoretical analyses and simulation results show that the desired SOI in the X and K bands with a bandwidth of 500 MHz and different modulation formats can be down-converted to the IF frequency. The self-interference noise with the 2 GHz bandwidth is canceled, and successful signal recovery is achieved after a 10 km fiber transmission. The recovery performance of down-converted signals and the self-interference cancellation depth under different interference-to-signal ratios (ISRs) is also investigated. In addition, the compensation performance of DIPF is verified, and a 6 dB improvement in frequency conversion gain is obtained compared with previous work. The proposed scheme is compact, cost-effective, and thus superior in wideband self-interference cancellation, long-range signal transmission, and effective recovery of weak desired signals.

Numerical study of transient indoor airflow and virus-laden droplet dispersion: Impact of interactive human movement

Human movement affects indoor airflow and the airborne transmission of respiratory infectious diseases, which has attracted scholars. However, the interactive airflow between moving and stationary people has yet to be studied in detail. This study used the numerical method validated by experimental data to explore the transient indoor airflow and virus-laden droplet dispersion in scenes with interactive human movement. Human-shaped numerical models and the dynamic mesh method were adopted to realize human movement in scenes with different lateral distances (0.2–1.2 m) between a moving person and stationary (standing/sitting) persons. The interactive human movement obviously impacts other persons' respiratory airflow, and the lateral fusion ranged about 0.6 m. The interactive human movement strengthens the indoor airflow convection, and some exhaled virus-laden droplets were carried into wake flow and enhanced long-range airborne transmission. The impact of interactive human movement on sitting patients' exhalation airflow seems more evident than on standing patients. The impact might last over 2 min after movement stopped, and people in the affected area might be at a higher exposure. The results can provide a reference for epidemic control in indoor environments.

Programmable frequency-bin quantum states in a nano-engineered silicon device

Photonic qubits should be controllable on-chip and noise-tolerant when transmitted over optical networks for practical applications. Furthermore, qubit sources should be programmable and have high brightness to be useful for quantum algorithms and grant resilience to losses. However, widespread encoding schemes only combine at most two of these properties. Here, we overcome this hurdle by demonstrating a programmable silicon nano-photonic chip generating frequency-bin entangled photons, an encoding scheme compatible with long-range transmission over optical links. The emitted quantum states can be manipulated using existing telecommunication components, including active devices that can be integrated in silicon photonics. As a demonstration, we show our chip can be programmed to generate the four computational basis states, and the four maximally-entangled Bell states, of a two-qubits system. Our device combines all the key properties of on-chip state reconfigurability and dense integration, while ensuring high brightness, fidelity, and purity.

Ventilation Methods against Indoor Aerosol Infection of COVID-19 in Japan

The importance of effective ventilation as one of the measures against COVID-19 is widely recognized worldwide. In Japan, at the early stage of the pandemic, in March 2020, an official announcement was made about basic ventilation measures against COVID-19. WHO also used the term “long-range aerosol or long-range airborne transmission” for the first time in December 2021. Based on the aerosol infection control measures before 2021 by the Japanese government, we conducted experiments on methods related to partition placement as an element of effective ventilation methods. In July 2022, the governmental subcommittee on Novel Coronavirus Disease Control provided an emergent proposal about effective ventilation methods to prevent two types of aerosol infection; infection by large aerosol on the air current and infection by small floating aerosol diffusion in a room. They also showed the way of setting droplet prevention partitions, which do not block off ventilation based on this investigation’s results.