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Kabir, Ahmed Salahuddin,Bharti, Daizy,Shin, Mann Kyoon The Korean Society of Systematic Zoology 2018 Animal Systematics, Evolution and Diversity Vol.34 No.1
Two hypotrich ciliates, Australocirrus shii (Shi et al., 1997) Kumar & Foissner, 2015 and Afrokeronopsis aurea (Foissner & Stoeck, 2008) Foissner et al., 2010 isolated from freshwater habitats in Korea and were studied based on the specimens from live and after protargol impregnation. Australocirrus shii is redescribed based on morphology and 18S rRNA gene sequence, whereas Af. aurea is the first record for Korea. Main morphological features of the Korean population of Au. shii are as following: body size $100-200{\times}40-80{\mu}m$ in vivo; elongate to ellipsoidal or slightly elongate obovate, dorsoventrally flattened; transverse cirri arranged in (3+2) pattern, anterior pretransverse ventral cirrus distantly anterior of the first transverse cirrus; eight or nine dorsal kineties; and three caudal cirri. Main morphological features of the Korean population of Af. aurea are as following: body size $230-375{\times}70-145{\mu}m$ in vivo; shape elongate obovate or ellipsoidal, widest at the mid-body; undulating membranes in Australocirrus pattern with a buccal depression; and three caudal cirri. The Korean population of A. shii is similar in morphology with previous descriptions except for the presence of indentation at the posterior end in the Korean population. The Korean population of A. aurea is slightly shorter than the South African population and has slightly less marginal and mid-ventral cirri. The phylogenetic analysis of present two Korean hypotrichs and relevant species based on 18S rRNA gene sequences generated almost similar tree topologies compared with previous studies.
Ahmed Salahuddin Kabir,Daizy Bharti,신만균 한국동물분류학회 2018 Animal Systematics, Evolution and Diversity Vol.34 No.1
Two hypotrich ciliates, Australocirrus shii (Shi et al., 1997) Kumar & Foissner, 2015 and Afrokeronopsis aurea (Foissner & Stoeck, 2008) Foissner et al., 2010 isolated from freshwater habitats in Korea and were studied based on the specimens from live and after protargol impregnation. Australocirrus shii is redescribed based on morphology and 18S rRNA gene sequence, whereas Af. aurea is the first record for Korea. Main morphological features of the Korean population of Au. shii are as following: body size 100-200×40-80 μm in vivo; elongate to ellipsoidal or slightly elongate obovate, dorsoventrally flattened; transverse cirri arranged in (3+2) pattern, anterior pretransverse ventral cirrus distantly anterior of the first transverse cirrus; eight or nine dorsal kineties; and three caudal cirri. Main morphological features of the Korean population of Af. aurea are as following: body size 230-375×70-145 μm in vivo; shape elongate obovate or ellipsoidal, widest at the mid-body; undulating membranes in Australocirrus pattern with a buccal depression; and three caudal cirri. The Korean population of A. shii is similar in morphology with previous descriptions except for the presence of indentation at the posterior end in the Korean population. The Korean population of A. aurea is slightly shorter than the South African population and has slightly less marginal and mid-ventral cirri. The phylogenetic analysis of present two Korean hypotrichs and relevant species based on 18S rRNA gene sequences generated almost similar tree topologies compared with previous studies.
A New Optimized Localized Technique of CG Return Stroke Lightning Channel in Forest
Kabir, Homayun,Kanesan, Jeevan,Reza, Ahmed Wasif,Ramiah, Harikrishnan,Dimyati, Kaharudin The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
Localization of lightning strike point (LSP) in the forest is modeled to mitigate the forest fire damage. Though forest fire ignited by lightning rarely happens, its damage on the forest is grievousness. Therefore, predicting accurate location of LSP becomes crucial in order to control the forest fire. In this paper, we proposed a new hybrid localization algorithm by combining the received signal strength (RSS) and the received signal strength ratio (RSSR) to improve the accuracy by mitigating the environmental effect of lightning strike location in the forest. The proposed hybrid algorithm employs antenna theory (AT) model of cloud-to-ground (CG) return stroke lightning channel to forecast the location of the lightning strike. The obtained results show that the proposed hybrid algorithm achieves better location accuracy compared to the existing RSS method for predicting the lightning strike location considering additive white Gaussian noise (AWGN) environment.
A New Optimized Localized Technique of CG Return Stroke Lightning Channel in Forest
Homayun Kabir,Jeevan Kanesan,Ahmed Wasif Reza,Harikrishnan Ramiah,Kaharudin Dimyati 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
Localization of lightning strike point (LSP) in the forest is modeled to mitigate the forest fire damage. Though forest fire ignited by lightning rarely happens, its damage on the forest is grievousness. Therefore, predicting accurate location of LSP becomes crucial in order to control the forest fire. In this paper, we proposed a new hybrid localization algorithm by combining the received signal strength (RSS) and the received signal strength ratio (RSSR) to improve the accuracy by mitigating the environmental effect of lightning strike location in the forest. The proposed hybrid algorithm employs antenna theory (AT) model of cloud-to-ground (CG) return stroke lightning channel to forecast the location of the lightning strike. The obtained results show that the proposed hybrid algorithm achieves better location accuracy compared to the existing RSS method for predicting the lightning strike location considering additive white Gaussian noise (AWGN) environment.
An Economic Study on Small Scale Marine Fishing in Teknaf of Cox s Bazar District of Bangladesh
Nazma Akter,Kabir Ahmed,M. Serajul Islam,Seungmo Koo 한국외국어대학교 인도연구소 2009 남아시아연구 Vol.15 No.2
This study was designed to determine cost/return structures and economic efficiency of small scale marine fishing of the selected gears in Bangladesh. To achieve these objectives a total of 90 fishing units(firms) of which 30 gill net, 30 roke net and 30 set bag net fishing firms were selected. Data were collected from the boat owners and fishermen for the period of one year. The findings of the study revealed that the selected fishing gears were highly profitable. The annual profits of gillnet, roke net and set bag net were found to be Tk. 111,022, 75,525 and 147,241 for the selected gears. It is concluded that set bag net fishing was more profitable compared to the other two gears. Cobb Douglas production function analysis revealed ? that the most of the explanatory variables included in the model were statistically significant and had positive effect in increasing revenue from fishing business.
A Deep Learning Approach for Covid-19 Detection in Chest X-Rays
Sk. Shalauddin Kabir,Syed Galib,Hazrat Ali,Fee Faysal Ahmed,Mohammad Farhad Bulbul International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.3
The novel coronavirus 2019 is called COVID-19 has outspread swiftly worldwide. An early diagnosis is more important to control its quick spread. Medical imaging mechanics, chest calculated tomography or chest X-ray, are playing a vital character in the identification and testing of COVID-19 in this present epidemic. Chest X-ray is cost effective method for Covid-19 detection however the manual process of x-ray analysis is time consuming given that the number of infected individuals keep growing rapidly. For this reason, it is very important to develop an automated COVID-19 detection process to control this pandemic. In this study, we address the task of automatic detection of Covid-19 by using a popular deep learning model namely the VGG19 model. We used 1300 healthy and 1300 confirmed COVID-19 chest X-ray images in this experiment. We performed three experiments by freezing different blocks and layers of VGG19 and finally, we used a machine learning classifier SVM for detecting COVID-19. In every experiment, we used a five-fold cross-validation method to train and validated the model and finally achieved 98.1% overall classification accuracy. Experimental results show that our proposed method using the deep learning-based VGG19 model can be used as a tool to aid radiologists and play a crucial role in the timely diagnosis of Covid-19.
Mohammad Asadullah,Mohammad Shajahan Kabir,Mohammad Boshir Ahmed,Nadiah Abdul Razak,Nurul Suhada Abdur Rasid,Airin Aezzira 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.12
Activated carbons have been prepared from jute stick by both chemical and physical activation methods using zinc chloride and steam, respectively. They were characterized by evaluating surface area, iodine number, pore size distribution, and concentration of surface functional groups. The chemically activated carbon largely featured micropore structure,while the physically activated carbon mainly featured macropore structure. The specific surface area of chemically and physically activated carbons was 2,325 and 723 m2/g, while the iodine number was 2,105 and 815mg/g, respectively. The concentration of surface functional groups was determined by Boehm titration method, which suggested that different types of surface functional groups are randomly distributed on chemical activated carbons, while it is limited for physical activated carbon. The microporosity along with surface functional groups provided a unique property to chemically activated carbon to adsorb Methylene Blue dye to a large extent. The adsorption of dye was also affected by the adsorption parameters such as adsorption time, temperature and pH. Comparatively, higher temperature and pH significantly facilitated dye adsorption on chemically activated carbon.
LoRa-based video data transmission for real-time monitoring of pig farm
( Nasim Reza ),( Shahriar Ahmed ),( Sumaiya Islam ),( Shaha Nur Kabir ),( Minho Song ),( Gookhwan Kim ),( Sun-ok Chung ) 한국농업기계학회 2023 한국농업기계학회 학술발표논문집 Vol.28 No.1
This paper proposed a LoRa-based video data transmission system for real-time monitoring in a pig farm. This approach eliminates the need for complex and costly infrastructure, making it a cost-effective solution for real-time monitoring in pig farm. The system architecture included the Raspberry Pi 4B microcontroller, RGB cameras, LoRa transceivers, gateway, and cloud-based platform for data analysis and visualization. The video data was captured using the RGB cameras and stored into an external memory through the microcontroller. Then the video was segmented into small chunks and compressed as an H.265 codec, which reduced the size of the video data and made it easier to transmit using the LoRa. Each compressed video chunk was then sent by the LoRa transceiver with a low data rate and a low transmit power. This allows the transmission to reach long distances, while consuming very low power levels. At the receiving end, the video chunks were received by another LoRa transceiver and re-assembled into the original video stream. The system performance was evaluated through a series of tests, including transmission range, video quality, and power consumption. The results showed that the LoRa-based system could transmit video data over a long range (2 km) with low power consumption (less than 1 W), while maintaining good video quality (720p resolution). The findings showed a great potential for real-time monitoring in pig farms, providing valuable insights into the pigs behavior, health, and productivity.