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<title>School of Science and Engineering (SoSE)</title>
<link href="http://dspace.uiu.ac.bd/handle/52243/3" rel="alternate"/>
<subtitle/>
<id>http://dspace.uiu.ac.bd/handle/52243/3</id>
<updated>2026-04-19T08:54:14Z</updated>
<dc:date>2026-04-19T08:54:14Z</dc:date>
<entry>
<title>Securing E-Voting in Bangladesh: A Blockchain Based System</title>
<link href="http://dspace.uiu.ac.bd/handle/52243/3469" rel="alternate"/>
<author>
<name>Jahan, Nusrat</name>
</author>
<id>http://dspace.uiu.ac.bd/handle/52243/3469</id>
<updated>2026-04-18T06:41:24Z</updated>
<published>2026-01-24T00:00:00Z</published>
<summary type="text">Securing E-Voting in Bangladesh: A Blockchain Based System
Jahan, Nusrat
The electronic voting process brings a technological advancement to ballot casting.&#13;
It blends tradition with technology. The system presents digital capabilities which guarantee both improved security and efficiency in operations. Previous e-voting implementations frequently experience problems at present. Democratic systems receive criticism&#13;
because of their virtual weaknesses. The system permits security breaches while displaying minimal transparency while weakening vote privacy. This research investigates the&#13;
development of blockchain-enabled e-voting (BEV) as a solution for resolving the existing problems within voting systems. The project development targets improvements in&#13;
election security together with privacy systems and enhanced reliability features. Our system deploys blockchain essential attributes which include decentralization, transparency&#13;
and immutability. Research determines how BEV functions as an election technology in&#13;
Bangladesh. The report takes a confident stance to compare Bangladesh’s digital voting system with the digital voting pioneers of Estonia and Switzerland. The research&#13;
proves blockchain uses security protocols to preventVote alteration and duplication events.&#13;
Blockchain operates as an effective system to prevent accidental modifications in addition&#13;
to unauthorized alterations. The system helps authorize voter identification. At the&#13;
same time we fully recognize the critical need for actual field tests regarding this matter.&#13;
Bangladesh needs to address its infrastructure challenges along with raising standards&#13;
of voter privacy in its one-of-a-kind geographic setting. The research establishes that&#13;
blockchain technology establishes active and transparent digital election procedures which&#13;
provide security. The importance of future examination becomes crucial to solve both&#13;
technical problems and regulatory requirements with blockchain technology. These findings are meant to serve as practical guidance for Bangladeshi policy makers together with&#13;
other stakeholders. The researchers strive to enhance blockchain election functions and&#13;
develop secure trusted electronic voting infrastructure.
</summary>
<dc:date>2026-01-24T00:00:00Z</dc:date>
</entry>
<entry>
<title>Securing E-Voting in Bangladesh: A Blockchain Based System</title>
<link href="http://dspace.uiu.ac.bd/handle/52243/3468" rel="alternate"/>
<author>
<name>Jahan, Nusrat</name>
</author>
<id>http://dspace.uiu.ac.bd/handle/52243/3468</id>
<updated>2026-04-13T08:44:28Z</updated>
<published>2026-01-24T00:00:00Z</published>
<summary type="text">Securing E-Voting in Bangladesh: A Blockchain Based System
Jahan, Nusrat
The electronic voting process brings a technological advancement to ballot casting.&#13;
It blends tradition with technology. The system presents digital capabilities which guarantee both improved security and efficiency in operations. Previous e-voting implementations frequently experience problems at present. Democratic systems receive criticism&#13;
because of their virtual weaknesses. The system permits security breaches while displaying minimal transparency while weakening vote privacy. This research investigates the&#13;
development of blockchain-enabled e-voting (BEV) as a solution for resolving the existing problems within voting systems. The project development targets improvements in&#13;
election security together with privacy systems and enhanced reliability features. Our system deploys blockchain essential attributes which include decentralization, transparency&#13;
and immutability. Research determines how BEV functions as an election technology in&#13;
Bangladesh. The report takes a confident stance to compare Bangladesh’s digital voting system with the digital voting pioneers of Estonia and Switzerland. The research&#13;
proves blockchain uses security protocols to preventVote alteration and duplication events.&#13;
Blockchain operates as an effective system to prevent accidental modifications in addition&#13;
to unauthorized alterations. The system helps authorize voter identification. At the&#13;
same time we fully recognize the critical need for actual field tests regarding this matter.&#13;
Bangladesh needs to address its infrastructure challenges along with raising standards&#13;
of voter privacy in its one-of-a-kind geographic setting. The research establishes that&#13;
blockchain technology establishes active and transparent digital election procedures which&#13;
provide security. The importance of future examination becomes crucial to solve both&#13;
technical problems and regulatory requirements with blockchain technology. These findings are meant to serve as practical guidance for Bangladeshi policy makers together with&#13;
other stakeholders. The researchers strive to enhance blockchain election functions and&#13;
develop secure trusted electronic voting infrastructure.
</summary>
<dc:date>2026-01-24T00:00:00Z</dc:date>
</entry>
<entry>
<title>A Secure Spectrum Aware MAC layer protocol for Cognitive Radio Wireless Sensor Network.</title>
<link href="http://dspace.uiu.ac.bd/handle/52243/3408" rel="alternate"/>
<author>
<name>Hossain, Md Shamiun</name>
</author>
<id>http://dspace.uiu.ac.bd/handle/52243/3408</id>
<updated>2026-04-01T21:00:19Z</updated>
<published>2026-03-31T00:00:00Z</published>
<summary type="text">A Secure Spectrum Aware MAC layer protocol for Cognitive Radio Wireless Sensor Network.
Hossain, Md Shamiun
Persistent Secure Spectrum Aware MAC layer, scalability and load balancing are important&#13;
requirements for numerous ad-hoc sensor network. Secure Clustering sensor nodes&#13;
is an effective technique for achieving these goals. In this work, we present a secure,&#13;
spectrum-aware cross-layer MAC protocol designed for Cognitive Radio Ad Hoc Networks&#13;
(CRAHN), where cluster formation is defined maximum edge biclique problem, enhance&#13;
the security of the cluster formation process and ensure both a stable number of common&#13;
channels and robustness to varying spectrum availability. The clustering process concludes&#13;
in O(1) of iterations, independent of the network’s structure or scale. By carefully choosing&#13;
the secondary clustering parameter, the process can significantly reduce the hassle of&#13;
re-clustering. This thoughtful selection ensures that the workload is evenly spread across&#13;
the cluster heads, preventing any one cluster from becoming overloaded, and keeping the&#13;
network running smoothly and efficiently. Dynamic approach maintains a stable network&#13;
structure despite node mobility. These protocols focus on secure and efficient spectrum&#13;
sharing among nodes to enhance network performance. It also achieves fairly uniform&#13;
cluster head distribution across the network. The cluster-based architecture is designed&#13;
to be highly flexible, allowing it to build and adjust itself as needed. This dynamic nature&#13;
is supported by two key operations: Node-Move-In and Node-Move-Out. These operations&#13;
enable the network to easily integrate new nodes and remove existing ones, ensuring&#13;
that the system can adapt to changes and maintain optimal performance without manual&#13;
intervention. A pseudocode analysis focused on enhancing the security of the cluster&#13;
formation process is also applied in two topology management operations. Overall, the&#13;
time complexity for the Node-Move-In and Node-Move-Out algorithms is O(n), where n&#13;
represents the number of members in the cluster. This means that the algorithms handle a&#13;
number of operations proportional to the number of nodes involved, making them efficient&#13;
and scalable as the network grows.
</summary>
<dc:date>2026-03-31T00:00:00Z</dc:date>
</entry>
<entry>
<title>A Hybrid Approach to Bangla Regional Text Classification Using BERT Ensemble and Region-Specific Lexical Oversampling</title>
<link href="http://dspace.uiu.ac.bd/handle/52243/3393" rel="alternate"/>
<author>
<name>Sultana, Babe</name>
</author>
<id>http://dspace.uiu.ac.bd/handle/52243/3393</id>
<updated>2026-01-12T21:00:14Z</updated>
<published>2026-01-12T00:00:00Z</published>
<summary type="text">A Hybrid Approach to Bangla Regional Text Classification Using BERT Ensemble and Region-Specific Lexical Oversampling
Sultana, Babe
Regional text analysis reflects the lived realities of diverse communities by capturing&#13;
the linguistic richness and diversity present in various dialects. It bridges the gap between everyday regional usage and standardized language forms, thereby enhancing the&#13;
inclusivity of language technologies. In this paper, we focus on five regional dialects in&#13;
Bangladesh, namely Chittagong, Sylhet, Noakhali, Barishal, and Rangpur, using a dataset&#13;
of 4,218 text samples. The dataset is validated by five regional experts and categorized into&#13;
three tiers based on an assigned agreement criterion. Tier 1 represents a strictly filtered,&#13;
high-confidence subset and is used primarily for evaluation. A set of region-specific special&#13;
words, which belong exclusively to their respective regions and are validated by domain&#13;
experts, is introduced. These words are used in a linguistically informed oversampling&#13;
technique to balance the dataset in both experiments. In the first experiment, we demonstrate the effectiveness of the tiered dataset structure, where Tier 2 and Tier 3 (mediumand low-confidence subsets) are used for training, and Tier 1 (high-quality subset) is used&#13;
for testing. In this setting, BanglaBERT achieves the best individual performance with&#13;
67.45% accuracy and a weighted F1-score of 67.62%. In the second experiment, we focus exclusively on the Tier 1 dataset, applying a wide range of machine learning and deep&#13;
learning models to assess their effectiveness. The key contribution is a heterogeneous deep&#13;
ensemble technique that combines three BERT models, BanglaBERT, BUETBERT, and&#13;
DistilBERT, achieving an accuracy of 85.17% and a weighted F1-score of 84.84% on the&#13;
Tier 1 dataset.
CSE
</summary>
<dc:date>2026-01-12T00:00:00Z</dc:date>
</entry>
</feed>
