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The Carbon Sequestration Potential of Forestry Sector: Bangladesh Context
Md. Shawkat Islam Sohel,Md. Parvez Rana,Mahbubul Alam,Sayma Akhter,Mohammed Alamgir 강원대학교 산림과학연구소 2009 Journal of Forest Science Vol.25 No.3
Forests potentially contribute to global climate change through their influence on the global carbon (C) cycle. The Kyoto Protocol provides for the involvement of developing countries in an atmospheric greenhouse gas reduction regime under its Clean Development Mechanism (CDM). Carbon credits are gained from reforestation and afforestation activities in developing countries. Bangladesh, a densely populated tropical country in South Asia, has a huge degraded forestland, which can be reforested by CDM projects. To realize the potential of the forestry sector in developing countries like Bangladesh for full-scale emission mitigation, the carbon sequestration potential should be integrated with the carbon trading system under the CDM of the Kyoto Protocol. This paper discusses the prospects of carbon trading in Bangladesh, in relation to the CDM, in the context of global warming.
Md. Mahbubul Islam,Nusrat Tasnim,Joong-Hwan Baek 한국정보통신학회 2021 2016 INTERNATIONAL CONFERENCE Vol.12 No.1
In this study, authors aimed to predict the gender of a customer with face mask to manage the customer data, targeted advertisement, and future of retail. Amid the COVID-19 pandemic situation, a customer must wear a face mask, avoid contacts with store staffs and should stay for short period of times while shopping. Smart store can meet the requirements by knowing the customer gender to find the right item. Predicting gender from faces with mask is a perplexing task due to two main reasons: 1) the lack of large benchmark datasets of masked faces, and 2) the deficiency of facial cues from the masked regions. Faces in the unconstraint environment have various orientations and occlusion degrees, where no less than one part of each face is occluded by mask. The traditional machine learning approaches are suffering in performance with the heterogeneity of the images in the non-benchmark dataset. This research proposes an automatic gender prediction system deploying deep learning networks; GoogleNet and ResNet50 those are pretrained with huge amount of image data. The extensive experiments demonstrate a noteworthy prediction accuracy (83%) even though the amount of available masked face data is very limited. Furthermore, this is the first work of gender prediction with the real masked face dataset heretofore.
Fingerprint Detection Using Canny Filter and DWT, a New Approach
Islam, Md. Imdadul,Begum, Nasima,Alam, Mahbubul,Amin, M.R. Korea Information Processing Society 2010 Journal of information processing systems Vol.6 No.4
This paper proposes two new methods to detect the fingerprints of different persons based on one-dimensional and two-dimensional discrete wavelet transformations (DWTs). Recent literature shows that fingerprint detection based on DWT requires less memory space compared to pattern recognition and moment-based image recognition techniques. In this study four statistical parameters - cross correlation co-efficient, skewness, kurtosis and convolution of the approximate coefficient of one-dimensional DWTs are used to evaluate the two methods involving fingerprints of the same person and those of different persons. Within the contexts of all statistical parameters in detection of fingerprints, our second method shows better results than that of the first method.
The Carbon Sequestration Potential of Forestry Sector: Bangladesh Context
Sohel, Md. Shawkat Islam,Rana, Md. Parvez,Alam, Mahbubul,Akhter, Sayma,Alamgir, Mohammed Institute of Forest Science 2009 Journal of Forest Science Vol.25 No.3
Forests potentially contribute to global climate change through their influence on the global carbon (C) cycle. The Kyoto Protocol provides for the involvement of developing countries in an atmospheric greenhouse gas reduction regime under its Clean Development Mechanism (CDM). Carbon credits are gained from reforestation and afforestation activities in developing countries. Bangladesh, a densely populated tropical country in South Asia, has a huge degraded forestland, which can be reforested by CDM projects. To realize the potential of the forestry sector in developing countries like Bangladesh for full-scale emission mitigation, the carbon sequestration potential should be integrated with the carbon trading system under the CDM of the Kyoto Protocol. This paper discusses the prospects of carbon trading in Bangladesh, in relation to the CDM, in the context of global warming.
( Sung-jun Park ),( Md Mahbubul Islam ),( Joong-hwan Baek ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.3
We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.
Saha, Tonmoy,Shufean, Md. Abu,Alam, Mahbubul,Islam, Md. Imdadul Korea Information Processing Society 2011 Journal of information processing systems Vol.7 No.4
WiMAX is intended for fourth generation wireless mobile communications where a group of users are provided with a connection and a fixed length queue. In present literature traffic of such network is analyzed based on the generator matrix of the Markov Arrival Process (MAP). In this paper a simple analytical technique of the two dimensional Markov chain is used to obtain the trajectory of the congestion of the network as a function of a traffic parameter. Finally, a two state phase dependent arrival process is considered to evaluate probability states. The entire analysis is kept independent of modulation and coding schemes.