Muhammad Mahbubur Rahman, Ph.D.

@article{DBLP:journals/corr/abs-1807-09842,

title = {Understanding and representing the semantics of large structured documents},

author = {Muhammad Mahbubur Rahman and Tim Finin},

url = {http://arxiv.org/abs/1807.09842},

year  = {2018},

date = {2018-01-01},

journal = {CoRR},

volume = {abs/1807.09842},

abstract = {Understanding large, structured documents like scholarly articles, requests for proposals or business reports is a complex and difficult task. It involves discovering a document’s overall purpose and subject(s), understanding the function and meaning of its sections and subsections, and extracting low level entities and facts about them. In this research, we present a deep learning-based document ontology to capture the general-purpose semantic structure and domain specific semantic concepts from a large number of academic articles and business documents. The ontology is able to describe different functional parts of a document, which can be used to enhance semantic indexing for a better understanding by human beings and machines. We evaluate our models through extensive experiments on datasets of scholarly articles from arXiv and Request for Proposal documents.},

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pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/corr/abs-1209-5345,

title = {Mining Social Data to Extract Intellectual Knowledge},

author = {Muhammad Mahbubur Rahman},

url = {http://arxiv.org/abs/1209.5345},

year  = {2012},

date = {2012-01-01},

journal = {CoRR},

volume = {abs/1209.5345},

abstract = {Social data mining is an interesting phenomenon which colligates different sources of social data to extract information. This information can be used in relationship prediction, decision making, pat-tern recognition, social mapping, responsibility distribution and many other applications. This paper presents a systematical data mining architecture to mine intellectual knowledge from social data. In this research, we use social networking site Facebook as primary data source. We collect different attributes such as about me, comments, wall post and age from Facebook as raw data and use advanced data mining approaches to excavate intellectual knowledge. We also analyze our mined knowledge with comparison for possible usages like as human behavior prediction, pattern recognition, job responsibility distribution, decision making and product promoting.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rahman,

title = {Realization of a Novel Fault Tolerant Reversible Full Adder Circuit in Nanotechnology},

author = {Md Islam and Muhammad Mahbubur Rahman and Zerina Begum and Mohd Hafiz},

year  = {2010},

date = {2010-01-01},

journal = {Int. Arab J. Inf. Technol.},

volume = {7},

pages = {317-323},

abstract = {In parity preserving reversible circuit, the parity of the input vector must match the parity of the output vector. It renders a wide class of circuit faults readily detectable at the circuit’s outputs. Thus, reversible logic circuits that are parity preserving will be beneficial to the development of fault tolerant systems in nanotechnology. This paper presents an efficient realization of well-known Toffoli gate using only two parity preserving reversible gates. The minimum number of garbage outputs and constant inputs required to synthesize a fault tolerant reversible full adder circuit has also been given. Finally, this paper presents a novel fault tolerant reversible full adder circuit and demonstrates its superiority with the existing counterparts.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{article,

title = {Low Cost Quantum Realization of Reversible Multiplier Circuit},

author = {Md Islam and Muhammad Mahbubur Rahman and Begum Z and Hafiz M.Z},

doi = {10.3923/itj.2009.208.213},

year  = {2009},

date = {2009-01-01},

journal = {Information Technology Journal},

volume = {8},

abstract = {Irreversible logic circuits dissipate heat for every bit of information that is lost. Information is lost when the input vector cannot be uniquely recovered from the output vector. Theoretically reversible logic dissipates zero power since the input vector of reversible circuit can be uniquely recovered from the output vector. Reversible computation has applications in digital signal processing, low power CMOS design, DNA computing and quantum computing. This study presents an overview of the well-known reversible gates and discuss about their quantum implementation. A new PFAG gate and its quantum implementation are presented. Finally, this study proposes a novel low-cost quantum realization of reversible multiplier circuit and compares its superiority with the existing counterparts.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}