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The status of NORMs in natural environment adjacent to the Rooppur nuclear power plant of Bangladesh
Md Abu Haydar,Md Mehade Hasan,Imrose Jahan,Kanij Fatema,Md Idris Ali,Debasish Paul,Mayeen Uddin Khandaker 한국원자력학회 2021 Nuclear Engineering and Technology Vol.53 No.12
The Rooppur Nuclear Power Plant (RNPP), the first nuclear power plant in Bangladesh with a capacity of2.4 GWe, is under construction on the bank of the river Padma, at Rooppur in Bangladesh. Measurementof background radioactivity in the natural environment adjacent to RNPP finds great importance forfuture perspectives. Soil and sediment samples collected from upstream and downstream positions ofthe Padma River (adjacent to RNPP) were collected and analyzed by HPGe gamma-ray spectrometry forprimordial radionuclides. The average activity concentrations (in Bqkg 1) of 226Ra, 232Th and 40K radionuclides in soil samples were found to be 44.99 ± 3.89, 66.28 ± 6.55 and 553 ± 82.17 respectively. Respective values in sediment samples were found to be 44.59 ± 4.58, 67.64 ± 7.93, 782 ± 108. Relevantradiation hazard indices and dosimetric parameters were calculated and compared with the worldaverage data recommended by US-EPA. Analytical results show non-negligible radiation hazards to thesurrounding populace. Measured data will be useful to monitor any change of background radioactivityin the surrounding environment of RNPP following its operation for the generation of nuclear energ
Comparative Study of PSO-ANN in Estimating Traffic Accident Severity
Md. Ashikuzzaman,Wasim Akram,Md. Mydul Islam Anik,Taskeed Jabid,Mahamudul Hasan,Md. Sawkat Ali International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.8
Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.
OMICS approaches in cardiovascular diseases: a mini review
Sohag, Md. Mehadi Hasan,Raqib, Saleh Muhammed,Akhmad, Syaefudin Ali Korea Genome Organization 2021 Genomics & informatics Vol.19 No.2
Ranked in the topmost position among the deadliest diseases in the world, cardiovascular diseases (CVDs) are a global burden with alterations in heart and blood vessels. Early diagnostics and prognostics could be the best possible solution in CVD management. OMICS (genomics, proteomics, transcriptomics, and metabolomics) approaches could be able to tackle the challenges against CVDs. Genome-wide association studies along with next-generation sequencing with various computational biology tools could lead a new sight in early detection and possible therapeutics of CVDs. Human cardiac proteins are also characterized by mass spectrophotometry which could open the scope of proteomics approaches in CVD. Besides this, regulation of gene expression by transcriptomics approaches exhibits a new insight while metabolomics is the endpoint on the downstream of multi-omics approaches to confront CVDs from the early onset. Although a lot of challenges needed to overcome in CVD management, OMICS approaches are certainly a new prospect.
Quantitative Evaluation of Tool Wear in Cold Stamping of Ultra-High-Strength Steel Sheets
Ishat Raihan Jamil,Ali Muhit Mustaquim,Mahmudul Islam,Md Shajedul Hoque Thakur,Mohammad Nasim Hasan 대한금속ᆞ재료학회 2023 METALS AND MATERIALS International Vol.29 No.2
In our study, molecular dynamics (MD) simulations of laser powder bed fusion (LPBF) have been conducted on equimolarFeNiCr medium entropy alloy (MEA) powders. With the development of newer LPBF technologies capable of printing at themicroscale, an even deeper understanding of the underlying atomistic effects of the process parameters on the microstructuraland mechanical properties of the manufactured FeNiCr MEA products is required. In accordance with previous literature,the parameters of the LPBF process have been systematically varied, including layer resolution from 1 to 6, laser powerfrom 100 μW to 220 μW, bed temperature from 300 to 600 K, and laser scan speed from 0.5 Å/ps to 0.0625 Å/ps. Consistentwith prior macroscopic experimental findings, the atomistic results suggest that additive manufacturing using thinner layersimparts higher ultimate tensile strength (UTS) than fabricating with thicker layers. The latter, however, requires a shorterprocess time but induces keyhole defect formation if the laser-induced temperature is not sufficiently high enough. Increasingthe temperature proves useful in mitigating this problem. Enhancement of UTS for the multi-rowed powders has beenobserved by raising the substrate temperature to 600 K, slowing down the laser or by raising the power to 160 μW duringproduction. Beyond certain critical power, however, the UTS of the product diminishes due to the emergence of multiplevacancies. These results will help researchers to find a good balance between the production speed and strength of additivemanufactured products at the nanoscale.
Ishat Raihan Jamil,Ali Muhit Mustaquim,Mahmudul Islam,Md Shajedul Hoque Thakur,Mohammad Nasim Hasan 대한금속·재료학회 2023 METALS AND MATERIALS International Vol.29 No.3
In our study, molecular dynamics (MD) simulations of laser powder bed fusion (LPBF) have been conducted on equimolarFeNiCr medium entropy alloy (MEA) powders. With the development of newer LPBF technologies capable of printing at themicroscale, an even deeper understanding of the underlying atomistic effects of the process parameters on the microstructuraland mechanical properties of the manufactured FeNiCr MEA products is required. In accordance with previous literature,the parameters of the LPBF process have been systematically varied, including layer resolution from 1 to 6, laser powerfrom 100 μW to 220 μW, bed temperature from 300 to 600 K, and laser scan speed from 0.5 Å/ps to 0.0625 Å/ps. Consistentwith prior macroscopic experimental findings, the atomistic results suggest that additive manufacturing using thinner layersimparts higher ultimate tensile strength (UTS) than fabricating with thicker layers. The latter, however, requires a shorterprocess time but induces keyhole defect formation if the laser-induced temperature is not sufficiently high enough. Increasingthe temperature proves useful in mitigating this problem. Enhancement of UTS for the multi-rowed powders has beenobserved by raising the substrate temperature to 600 K, slowing down the laser or by raising the power to 160 μW duringproduction. Beyond certain critical power, however, the UTS of the product diminishes due to the emergence of multiplevacancies. These results will help researchers to find a good balance between the production speed and strength of additivemanufactured products at the nanoscale.