An integrated blockchain and IPFS-based solution for secure and efficient source code repository hosting using middleman approach.

Centralized version control systems (VCS) are vital for software development but pose risks of data loss and ownership disputes. While blockchain offers a decentralized alternative, existing solutions are often hindered by high latency, compromising the real-time collaboration essential for modern workflows. This study introduces a novel hybrid architecture combining the security of the Ethereum blockchain and the InterPlanetary File System (IPFS) with two key contributions: 1) Shamir's Secret Sharing (SSS) to create a trust-minimized model for key distribution, and 2) an authoritative-first, optimistic-fallback retrieval protocol utilizing a temporary middleware to decouple the user experience from blockchain confirmation delays.

Zero-shot performance analysis of large language models in sumrate maximization.

Large language models have revolutionized the field of natural language processing and are now becoming a one-stop solution to various tasks. In the field of Networking, LLMs can also play a major role when it comes to resource optimization and sharing. While Sumrate maximization has been a crucial factor for resource optimization in the networking domain, the optimal or sub-optimal algorithms it requires can be cumbersome to comprehend and implement.

CASL-W60: A word-level dataset for central African sign language recognition.

Sign language is a non-verbal discourse system used by people who are hard of hearing. It also carries cultural context and regional constructs, enabling meaningful communication and often preserving unique traditions. In the Central African region, local sign languages have distinct linguistic constructs but remain underrepresented in the literature, creating a significant gap in regional word-level datasets for machine learning practitioners.

Mapping drinking water contamination in Gazipur City restaurants using WQI and multivariate analysis.

Groundwater is a primary drinking water source in many regions of Bangladesh, necessitating continuous monitoring to ensure safety. This study evaluates groundwater quality in Gazipur City by analyzing 173 water samples collected in 2019 from restaurants across 18 zones. Fourteen physicochemical parameters, including pH, turbidity, total dissolved solids (TDS), electrical conductivity (EC), and major ions, were assessed.

Early diagnosis of autism across developmental stages through scalable and interpretable ensemble model.

Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition that challenges early diagnosis due to its diverse manifestations across different developmental stages. Timely and accurate detection is essential to enable interventions that significantly enhance developmental outcomes. This study introduces a robust and interpretable machine learning framework to diagnose ASD using questionnaire data.

Enhancing operational efficiency through overall equipment efficiency optimization and Kaizen initiatives.

This case study aims to investigate the causes of low efficiency in a carton production line by calculating Overall Equipment Effectiveness (OEE). A typical carton factory has been chosen for this study, which has two production lines, namely finished goods and corrugated boards. The define, measure, analyze, improve, and control approach is applied while implementing Six Sigma principles such as Kaizen, fishbone diagrams, and 5W+1H as its systematic procedure.

Enhancing hydrodynamic efficiency in Autonomous Underwater Vehicles (AUVs) utilizing adjoint method and proper orthogonal decomposition.

In recent years, there has been a significant need for high-performing and efficient Autonomous Underwater Vehicles (AUVs). This is primarily because of their use in offshore mineral exploitation and oceanographic research. While there have been notable breakthroughs in applying the adjoint technique to optimize air and land vehicles, there is still a deficiency in optimizing AUVs using the adjoint method.

Assessing the Risk of Antibiotic Resistance in Childhood Pneumonia: A Hospital-Based Study in Bangladesh.

Approximately two to three children die from pneumonia every hour, and pneumonia is the leading cause of hospitalization for children under five in Bangladesh. Bangladesh has adopted the Pocket Book guidelines by the World Health Organization (WHO) for hospital management of childhood pneumonia. These guidelines recommend the proper use of injectable antibiotic administration.

Urban water supply risks assessment under tropical climate.

The urban water supply system in tropical countries faces various physical risks, including pipe failures due to aging, material type, soil conditions, flooding, extreme weather events, and traffic loads. This study focuses on urban water supply risks for eight zones of Brunei-Muara district. A risk assessment using a data-driven matrix reveals Zones D2 and D6 as very high-risk areas, experiencing monthly average leaks of 880 and 471, respectively.

Digitize-HCD: A dataset for digitization of handwritten circuit diagrams.

Handwritten and legacy engineering diagrams are still commonly used in many industries and academic settings, but the lack of digitization limits their utility in modern workflows. While significant effort has been made to digitize handwritten content in other engineering domains, the digitization of handwritten circuit diagrams remains underexplored. Automating this process would enable the development of tools capable of converting handwritten circuit diagrams into machine-readable formats that can be instantly interpreted by circuit simulation software.

Towards automated recipe genre classification using semi-supervised learning.

Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In this study, we present a dataset named the "Assorted, Archetypal, and Annotated Two Million Extended (3A2M+) Cooking Recipe Dataset" that contains two million culinary recipes labeled in respective categories with extended named entities extracted from recipe descriptions.

Sustainable leachate treatment by integrating electrolysis with palm-shell activated carbon contactor for environmental protection.

The increasingly concerning issue of water pollution caused by untreated leachate necessitates the implementation of effective wastewater treatment methods. This study addresses the crucial issue of landfill leachate treatment through an innovative and environmentally friendly approach that integrates electrolysis with palm-shell activated carbon contactors. The efficacy of an integrated process for pollutants removal was assessed involving electrolysis with aluminum and iron electrodes, activated carbon contactors with varying bed depths, and the influence of salinity.

Efficiency of microbial desalination cells in treating wastewater, desalinating saltwater, and generating bioelectricity in Bangladesh.

Desalination ensures the provision of potable water to those living in coastal areas, thereby guaranteeing access to safe drinking water. Urbanization and industrialization pollute natural water sources with untreated and partially treated wastewater. International researchers have been searching for cost-effective and environmentally friendly solutions to the above-highlighted difficulties.

A semi-empirical relation based on temperature difference and filling ratio in a closed loop pulsating heat pipe: A numerical study.

A closed-loop pulsating heat pipe (CLPHP) is an attractive passive cooling system for electronic components. The design of CLPHP is challenging due to the complex nature of thermo-hydrodynamic coupling. This study investigates the heat transfer efficiency of a CLPHP using water as the working fluid.

Understanding the success factors of MOOCs' retention intention: A Necessary Condition Analysis.

This paper seeks to explore the influence of success factors, specifically motivation and course quality, on MOOC retention intention. Going beyond a mere examination of these motivational and quality factors, the study investigates students' motivation, considering needs, interests, course system, content, and service quality. Methodologically, a questionnaire survey was conducted, collecting data from 311 students enrolled in online courses.

Motion artifact contaminated multichannel EEG dataset.

Wearable EEG suffers from motion artifact contamination due to the subject's movement in an ambulatory environment. Signal processing techniques pose promising solutions for the detection and removal of motion artifacts from ambulatory EEG, but relevant open-access datasets are not available, which is detrimental to the development of wearable EEG applications. This article showcases open-access electroencephalography (EEG) recordings, while a subject is performing different upper-body, lower-body, and full-body movements.

Predicting removal of arsenic from groundwater by iron based filters using deep neural network models.

Arsenic (As) contamination in drinking water has been highlighted for its environmental significance and potential health implications. Iron-based filters are cost-effective and sustainable solutions for As removal from contaminated water. Applying Machine Learning (ML) models to investigate and optimize As removal using iron-based filters is limited.

Effect of triangular pits on the mechanical behavior of 2D MoTe: a molecular dynamics study.

Context: Among two-dimensional (2D) materials, transition metal dichalcogenides (TMDs) stand out for their remarkable electronic, optical, and chemical properties. Their atomic thinness also imparts flexibility, making them ideal for flexible and wearable devices. However, our understanding of the mechanical characteristics of molybdenum ditelluride (MoTe), particularly with defects such as pits, remains limited.

Investigating the synergistic effects of internal curing and pozzolanic activity in mortar utilizing clay-burnt brick fines.

This study investigates the combined effect of internal curing and pozzolanic activity in mortar through the incorporation of clay-burnt brick fines (CBBF) as a partial substitute for sand. Simultaneously, the study explores the degree of pozzolanic reactivity by replacing a part of cement with finer clay-burnt brick fines (CBBP, particle size <75 μm). These materials are sourced from waste materials generated during brick-chip production.

Comparison of RNN-LSTM, TFDF and stacking model approach for weather forecasting in Bangladesh using historical data from 1963 to 2022.

Forecasting the weather in an area characterized by erratic weather patterns and unpredictable climate change is a challenging endeavour. The weather is classified as a non-linear system since it is influenced by various factors that contribute to climate change, such as humidity, average temperature, sea level pressure, and rainfall. A reliable forecasting system is crucial in several industries, including transportation, agriculture, tourism, & development.

Sensitivity study on convective heat transfer in a driven cavity with star-shaped obstacle and hybrid nanofluid using response surface methodology.

Sensitivity analysis is significant for understanding and measuring the impact of various parameters and input variables on heat transfer phenomena. The main objective of the current work is to examine the sensitivity of a numerical analysis of mixed convection in a lid-driven square cavity with a magnetic field. The cavity also contains a heated, star-shaped obstacle and is filled with a hybrid nanofluid.

2DOF-PID-TD: A new hybrid control approach of load frequency control in an interconnected thermal-hydro power system.

The Load Frequency Control (LFC) scheme, with its primary aim being the maintenance of uniform frequency, has been a heavily researched topic for decades. Achieving a consistent frequency necessitates a delicate balance between load demand and power generation. Researchers strive to find an optimal solution within the LFC domain-one that can effectively withstand drastic load fluctuations.

Artificial Neural Network analysis on the effect of mixed convection in triangular-shaped geometry using water-based Al2O3 nanofluid.

The objective of the study is to investigate the fluid flow and heat transfer characteristics applying Artificial Neural Networks (ANN) analysis in triangular-shaped cavities for the analysis of magnetohydrodynamics (MHD) mixed convection with varying fluid velocity of water/Al2O3 nanofluid. No study has yet been conducted on this geometric configuration incorporating ANN analysis. Therefore, this study analyzes and predicts the complex interactions among fluid flow, heat transfer, and various influencing factors using ANN analysis.

Predicting students' satisfaction with academic services at a multicultural engineering university in Bangladesh: A multiple regression analysis.

This empirical study sought to determine the levels of satisfaction among engineering students enrolled at a multicultural international institution in Bangladesh with a reputation for excellence. An assortment of first- and fourth-year undergraduate students participated in the study by completing an online survey. The study focused on selected determinants namely; support services (SS), campus life (CL), economic factors (EF) and University corporate image (CI).