Rain Effect to A 60 GHz Broadband Wireless System’s Performance: Study Case In Purwakarta

Nowadays, world wide telecommunication researchers are developing 5G technology. One of most important key technology in 5G is Milimeter-Wave (mmWave). This study measure 60 GHz broadband wireless system performance because of it’s promising potentials. However, the use of these frequencies is quite sensitive to rain that resulting an atenuation in the channel. Therefore, this study proposes two schemes to address the problem. The first scheme is the use of QAM modulation (Quadrature Amplitude Modulation) and the second scheme is an addition of LDPC (Low Density Parity Check) code techniques. From the results of this study, by using 4-QAM modulation and LDPC coderate 1/2, the broadband wireless system’s performance on the second scheme is better compared to the first scheme with 8.33 dB Signal to Noise Ratio (SNR) value to provides BER (Bit Error Rate) 10-4

A Study on Establishment of Drought Index for Agricultural Disaster Prediction

This study aims to establish a drought index for disaster prediction in Gyeongsangnam-do, where the most agricultural drought damage occurred from 1965 to 2018. The drought index was analyzed for each duration (3, 6, 9, 12 months) targeting the SPI. Damage characteristics of the duration of agricultural drought were calculated. SPI for each duration of agricultural drought damage period in Gyeongsangnam-do was at least -2.0 or less, and the maximum was -1.0 or more, and weak and moderate drought were analyzed. However, due to the heavy rain effect during the rainy season, the average SPI12 was -1.06, and the impact of agricultural drought was negligible. It was analyzed that the correlation between the damage period of agricultural drought and the SPI by duration was high. However, there is not much difference in SPI for each duration to determine the occurrence of damage. In this study, the criterion for disaster prediction of agricultural drought was calculated as representative drought index by year as the minimum drought index of SPI for each duration of damage occurrence period of past agricultural drought. The Standard of drought index for disaster prediction was set to -1.64, the average of the SPI for each duration of year in which damage occurred in the past.

A Neural Network-Based Rain Effect Correction Method for HY-2A Scatterometer Backscatter Measurements

The backscattering coefficients measured by Ku-band scatterometers are strongly affected by rainfall, resulting in a systematic error in sea surface wind field retrieval. In rainy conditions, the radar signals are subject to absorption by the raindrops in their round-trip propagation through the atmosphere, while the backscatter of raindrops raises the echo energy. In addition, raindrops give rise to roughness by impinging the ocean surface, resulting in an increase in the echo energy measured by a scatterometer. Under moderate wind conditions, the comprehensive impact of rainfall causes the wind speeds retrieved by the scatterometer to be higher than their actual values. The HY-2A scatterometer is a Ku-band, pencil-beam, conically scanning scatterometer. To correct the systematic error of the HY-2A scatterometer measurement in rainy conditions, a neural network model is proposed according to the characteristics of the backscatter coefficients measured by the HY-2A scatterometer in the presence of rain. With the neural network, the wind fields of the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data were used as the reference to correct the deviation in backscatter coefficients measured by the HY-2A scatterometer in rainy conditions, and the accuracy in wind speeds retrieved using the corrected backscatter coefficients was significantly improved. Compared with the cases of wind retrieval without rain effect correction, the wind speeds retrieved from the corrected backscatter coefficients by the neural network show a much lower systematic deviation, which indicates that the neural network can effectively remove the systematic deviation in the backscatter coefficients and the retrieved wind speeds caused by rain.

Rain Effect Frequency of Infiltration Rate and Infiltration Capacity in Common Soil: Laboratory Test with Rainfall Simulator

Analyzing the Influence of Rain Frequency Infiltration Rate and Infiltration Capacity in Common Soil Type (Laboratory Testing Study With Rainfall Simulator). Infiltration is the flow of water into the ground through the soil surface. This process is a very important part of the hydrological cycle and in the process of transferring rain into the flow of water in the soil before reaching the river. Infiltration (infiltration rate and capacity) is influenced by various variables, including soil type, slope inclination, density and type of vegetation, soil moisture content, and rainfall intensity. This study aims to determine the effect of rainfall frequency on the infiltration rate and infiltration capacity on common soil types. This research is a type of laboratory experimental research, using rainfall simulator tool. The soil used in this study is common soil type. Furthermore, artificial rain was provided with intensity I5, I15, and I25 and performed infiltration rate reading on the Drain Rainfall Simulator. The rate and capacity of infiltration in common soils increase proportionally to the increased intensity of rainfall, the higher the intensity of rainfall the higher the infiltration occurring at the same level of rain frequency. The rate and capacity of infiltration in common soils decrease proportionally to the increasing frequency of rain, the more the frequency of rain the smaller the infiltration occurring at the same level of rainfall intensity