Environmental radiation monitoring based gamma spectroscopy require a multichannel analyzer (MCA) which functions to record and analyze nuclear radiation spectrum data. There are currently many studies related to MCA based on field programmable gate array (FPGA). But, the scope of these published research is complex and fragmented. This systematic literature review (SLR) main objective to analyze research trends and emerging themes research of MCA based on FPGA for gamma spectroscopy that was developed during last 10 years. This review was conducted by selecting papers from leading journals in scientific databases namely ScienceDirect, IEEE Xplore and Scopus. For papers selection process, specific keyword strings used for each database and paper selecting using inclusion and exclusion criterion. Selection of papers resulted in 38 selected papers. During 10 last 10 years, This reseach become hot of topic research especially in Asia. This SLR proves that performance of MCA based FPGA is reliable and compatible with various of detector types. This MCA has been used for spectroscopy applications such as monitoring radiation, diagnostic medicine, industrial imaging and security screening. The implications of this study can used as reference for future research of development MCA based FPGA for enviromental radiation monitoring based gamma spectroscopy.
The cultivation of Chlorella DPK-01 in tubular photobioreactors (PBRs) with difference in time of audible sound exposure was done. The study aims to evaluate the effect of difference in time of audible sound exposure in tubular PBRs to the growth and lipid percentage of microalgae Chlorella DPK-01. This study was using three groups of Chlorella DPK-01 PBRs. One group was control group and not exposed to any sound (Control-PBR), one group was exposed to audible sound in the light (PBR-A), and another group was exposed to audible sound in the dark (PBR-B). Each group consists of three units of PBR. The audible sound (279.9 Hz sine wave) was played in the light for PBR-A and in the dark for PBR-B. The observation period was 14 days. The growth rate of Chlorella DPK-01 was 47.6% per day (Control-PBR), 0.44 per day (PBR-A), and 0.55 per day (PBR-B) respectively. Meanwhile, the lipid percentage of Chlorella DPK-01 was 16% (Control-PBR), 31% (PBR-A), and 11% (PBR-B) respectively. Therefore, exposing audible sound in the light and in the dark may differently affect the growth and lipid production of Chlorella DPK-01.
To improve the quality and quantity of meteorological data over Indonesia, Meteorology Climatology and Geophysics Agency of Indonesia (BMKG) is continuously developing automatic weather observations. BMKG has 63 units Automatic Weather Station (AWS) and 165 units Automatic Weather Observation System (AWOS) both inside and outside the BMKG Station environment. To make the control of sensor conditions easier, especially for temperature, pressure, relative humidity, and rainfall sensors, an additional system is needed to monitor and warn when problems occur with these sensors. The correlation among weather parameters data is the key to monitoring the sensor condition, these data are going to be trained and tested with the Artificial neural network (ANN) method. Then, the sensor condition (normal or error indicated) can be well detected based on AWS’s data. The quality improvement of automatic weather station data is expected to increase the utilization of the data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.