Volume 14 | Issue 5 |

 Abstract

In a National Highway Project, the engineer has to plan, design and construct either a network of new roads or road link. Once a highway is constructed, development takes along the adjoining land and subsequent changes in alignment highway is not a source of potential traffic hazard, but also causes a considerable increase in transportation cost and strain on drivers and the passengers. The Government of India had entrusted to the Authority the development, maintenance and management of Four / Six Laning of Ambaghat to Paijarwadi section of NH- 166 from Ch 67+140(existing km 69+072) to Ch. 112+340 (existing km 115+540),Length

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 Keywords

National Highway Development, NH-166, Hybrid Annuity Model (HAM), Design-Build-Operate-Transfer (DBOT), Highway Engineering, Road Widening (Four/Six Laning), Infrastructure Development, Traffic Management, Pavement Design, Transportation Engineering, Maharashtra Road Project Bottom Slab, Side Wall Construction, Top Slab.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Foundations are one of the most critical components of civil engineering structures, as they safely transfer structural loads to the underlying soil. The stability and durability of a structure largely depend on the bearing capacity and settlement characteristics of the supporting soil. Weak or poorly compacted soils may result in excessive settlement, instability, and structural failure. Therefore, improving the bearing capacity of soil has become an important aspect of geotechnical engineering.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Reinforced soil, bearing capacity, shallow footing, settlement, geogrid, soil stabilization, load-settlement behavior.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study presents a detailed analysis of quality control practices implemented in a Ready Mix Concrete (RMC) plant to achieve consistent production of high-performance concrete. Quality control plays a vital role in ensuring the strength, durability, workability, and overall reliability of concrete used in modern construction. The study covers the inspection and monitoring of raw materials, mix proportioning, batching operations, transportation, placement, and testing procedures for both fresh and hardened concrete. Standard quality assessment tests such as slump test, compressive strength test, and moisture content analysis were carried out to evaluate concrete performance and conformity with specified standards. The findings demonstrate that effective quality control measures significantly enhance concrete quality, minimize material wastage, improve operational efficiency, and ensure compliance with construction specifications. The study emphasizes the importance of systematic quality assurance practices in achieving durable, economical, and sustainable concrete production in RMC plants.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ready Mix Concrete (RMC), Quality Control, Quality Assurance, Compressive Strength, Workability, Slump Test, Concrete Durability, Mix Design, Batching Process, Sustainable Construction.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The electric folding bike is lightweight, compact, and easy to carry; it can withstand a load of 60 kg, travel at a speed of 20 kmph, and have a range of 50 km on a single charge.

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 Keywords

Design and Analysis of Folding Bike

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Runoff prediction is an essential component of hydrology and water resources engineering. Accurate estimation of runoff helps in designing drainage systems, flood forecasting, watershed management, irrigation planning, and hydraulic structure design. Conventional runoff estimation methods often require extensive field data, which may not always be available. Dimensional analysis provides a simplified and scientific approach for developing predictive relationships between runoff and influencing parameters using fundamental physical dimensions.

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 Keywords

socio-economic, physical dimensions, Buckingham ?-theorem, infiltration rate, slope, catchment area, soil characteristics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The solar photo-voltaic modules are generally employed in dusty environments e.g. tropical countries like India. The dust gets accumulated on the surface of the module and blocks the incident light from the sun. It reduces the power generation capacity of the module. The power output reduces as much as by 50% if the module is not cleaned for a month. The cleaning system designed cleans the module by Ardino control. The main objective is to remove the dust in the photo-voltaic modules to improving the power generating efficiency of the solar power generation system.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

photo-voltaic modules, ardino, power generation, dust particles

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Firefighting is a dangerous yet vital profession, and this research looks at how technology can help. A robot's primary function is to contain a fire before it spreads. Collaborating with firefighters, it could help lessen the likelihood of harm coming to victims. This project showcases the robot that fights fires. There are three main components to a robot's development: hardware, electronics, and programming. The castor wheel and two DC motors make up the robot's driving system. Water suction and spraying are made possible by a 12-volt DC pump. Motor for axial water spraying (SG90 servo).degrees Celsius 0-60A number of sensors can be connected to the Arduino Uno Board. The programming portion involved deriving the robot's movement from sensor input using the Arduino IDE language.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Robots, Fire fighters, castor, dc motors, servomotors, and arduino

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid growth of online transactions has significantly increased the risk of fraudulent activities, posing serious challenges to financial institutions and digital platforms. Fraud detection systems are essential for identifying and preventing unauthorized or suspicious transactions in real time. Traditional rule-based approaches often fail to detect evolving and complex fraud patterns, leading to the adoption of advanced techniques such as machine learning and data mining. This study focuses on developing an efficient fraud detection system that analyzes transaction data to identify anomalies and classify fraudulent behavior accurately. Various algorithms, including classification models and anomaly detection techniques, are utilized to improve detection accuracy while minimizing false positives. The proposed approach aims to enhance security, protect user data, and maintain trust in online transaction systems. Overall, this work highlights the importance of intelligent and adaptive fraud detection mechanisms in ensuring safe and reliable digital financial services.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Online Transaction Fraud, Fraud Detection, Machine Learning, Deep Learning,Hybrid Models, Anomaly Detection, Graph Neural Networks (GNN), Credit Card Fraud, Real-Time Detection, Explainable AI (XAI), Financial Technology (FinTech), Block chain Security.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the era of digital education, maintaining student engagement has become a pressing challenge. Traditional classroom methods for observing student attention are not viable in online settings. This paper presents Focus Plus, an intelligent system designed to detect learner distraction in real-time using webcam feeds. Utilizing computer vision techniques such as face detection, eye tracking, and head pose estimation, the system identifies whether a student is focused or distracted. The data is logged and visualized to generate reports that help instructors assess learner engagement. The implementation leverages Python with OpenCV and MediaPipe, providing a lightweight, real-time solution suitable for integration with existing learning platforms. Virtual reality (VR) can potentially enhance student engagement and memory retention in the classroom. However, distraction among participants in a VR-based classroom is a significant concern. Several factors, including mind wandering, external noise, stress, etc., can cause students to become internally and/or externally distracted while learning. To detect distractions, single or multi-modal features can be used. A single modality is found to be insufficient to detect both internal and external distractions, mainly because of individual variability. Using eye-tracking data and EEG data from the same participants, we can classify different forms of internal and external distractions while they are participating in an educational VR experience. We created an educational VR experience environment and added equipment to collect multi-modal data from participants. In order to classify the data collected from participants using various machine-learning methods, we used four different machine-learning models: k-nearest neighbors (kNN), Random Forest (RF), one-dimensional convolutional neural network-long short-term memory (1D-CNN-LSTM), and two-dimensional convolutional neural network (2D-CNN).In this work, we investigated multi- to classify participants' internal and external distraction states using the multi-modal features. We performed cross-subject, cross-session, and gender-based grouping tests to evaluate our models. We found that the RF classifier achieves the highest accuracy over 83% in the cross-subject test, around 68% to 78% in the cross-session test, and around 90% in the gender-based grouping test compared to other models. SHAP analysis of the extracted features illustrated greater contributions from the occipital and prefrontal regions of the brain, as well as gaze angle, gaze origin, and head rotation features from the eye tracking data.

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 Keywords

"Focus Plus: Detect Learner's Distraction by Web Camera in Distance Teaching"

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Centralized authentication systems suffer from security risks such as single points of failure, password theft, and privacy leakage. Blockchain-based authentication provides decentralization and trust but faces challenges related to performance, cost, and scalability. This paper presents the implementation of a secure authentication framework combining Zero-Knowledge Proofs (ZKPs) and Multi-Factor Authentication (MFA) to enhance privacy and security. ZKPs enable identity verification without revealing sensitive user data, while MFA strengthens resistance against common attacks. The proposed system utilizes off-chain computation with on-chain verification to reduce latency and gas costs. Experimental analysis demonstrates improved efficiency, security, and user experience. The framework is suitable for applications requiring high security such as banking, healthcare, and IoT systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Blockchain Authentication, Zero-Knowledge Proofs, Multi-Factor Authentication, Privacy Preservation, Off-chain Computation, Smart Contracts, Identity Verification.

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Creative Commons Attribution 4.0 and The Open Definition