Category Archives: Uncategorized

Authors: Sachin Kumar

Abstract: The Dual Role of Artificial Intelligence in Cyber Security: From Automated Defense to Adversarial Exploitation Abstract The rapid integration of Artificial Intelligence (AI) into the digital landscape has fundamentally transformed the field of cyber security. This paper examines the bidirectional impact of AI: its role as a powerful defensive mechanism capable of real-time threat detection and response, and its emergence as a sophisticated tool for adversarial exploitation. By analyzing Machine Learning (ML) models in intrusion detection, the rise of "Agentic" autonomous security systems, and the threats posed by adversarial ML and deepfakes, this study proposes a framework for AI-resilient security operations. The research concludes that while AI significantly enhances defensive capabilities, it also necessitates a new era of proactive, adaptive security strategies to counter AI-driven threats.

DOI: https://doi.org/10.5281/zenodo.19091390

 

Published by: vikaspatanker

Authors: Sachin Kumar

Abstract: Hardening the Core: Strategic Defense-in-Depth for Windows-Based Domain Controllers Abstract In the modern enterprise landscape, the Active Directory (AD) infrastructure and its constituent Domain Controllers (DCs) represent the "crown jewels" of organizational identity and access management. As the central repository for user credentials, group policies, and authorization data, a compromised Domain Controller grants an adversary virtually unlimited "keys to the kingdom." This paper provides a comprehensive analysis of the threat landscape targeting Windows-based Domain Controllers and proposes a robust, multi-layered defense-in-depth framework. By integrating administrative isolation, host-level hardening, network segmentation, and advanced monitoring, organizations can significantly reduce the attack surface. The study concludes with a strategic roadmap for implementing these defenses without compromising the high availability required for critical identity services.

DOI: https://doi.org/10.5281/zenodo.19091242

 

Published by: vikaspatanker

Authors: Ragul. M, Amna Saliha P I K, Dr. K. Brindha

Abstract: Digital health data grows fast. From patient files to scans, genes, fitness trackers, and billing logs – each piece adds up quick. Not just more information – but faster flows, messier formats. Yet within that chaos sit chances to do things differently. Hidden patterns start showing when tools can keep pace. Big data analytics steps into that role. Instead of static reports, it offers insights that shift as new facts arrive. Systems built on platforms like Hadoop or Spark handle loads regular software cannot. Cloud storage keeps the doors open for constant updates. Machine learning digs through noise to spot trends. Deep learning maps complex relationships in images or signals. Language parsers decode doctor notes once locked in freeform text. Five areas see clear change. One: guessing illness before symptoms show. Two: guiding long-term conditions day by day. Three: smoothing how hospitals run – from beds to staff shifts. Four: tracking drug effects after release. Five: treatments shaped around individual biology. Evidence comes from sifting 112 studies published between 2015 and 2024. Patterns emerge only when scale meets smart design. Raw power alone does nothing. It takes thoughtful layers – a stack where speed, structure, and smarts connect. Tests on standard collections like MIMIC-III, NIH Chest X-Ray, and eICU show accuracy between 87.6% and 94.1% for core predictions. Yet problems remain – privacy concerns linger just as much as biased models do. Different systems still struggle to work together while rules keep shifting. On top of that, new paths are forming: shared learning setups pop up alongside tools making AI clearer and analysis at the device level grows more common. For those working in health data, science, or hospital operations, this piece lays out how to grasp, judge, fit in big data methods where things never stay simple.

DOI: https://doi.org/10.5281/zenodo.19091089

 

Published by: vikaspatanker

Authors: Vikasini E, Daniya U, Mr.P. Jayasheelan, Guide Dr.P.Jayasheelan

Abstract: Paper registers and card systems for taking student and employee attendance are slow and full of mistakes. People can fake entries. Proxy marking is easy. Schools and workplaces need something more reliable and automatic to track who shows up. So we built an AI-powered smart attendance management system that uses facial recognition to record attendance in real time. The system is written in Python and uses OpenCV and the face recognition library. A SQLite database stores the structured data. A camera-enabled desktop app captures facial images. It matches people against a pre-registered face database and logs attendance with timestamps. No manual data entry. No easy way to mark attendance for someone else. The graphical interface uses Tkinter. Admins can manage records and run reports. They can also view attendance history. Tests show the system reaches high recognition accuracy under controlled lighting. It also cuts down administrative work a lot. This research shows how artificial intelligence and computer vision can be applied to institutional management systems to improve efficiency, reliability and accountability.

DOI: https://doi.org/10.5281/zenodo.19090670

 

Published by: vikaspatanker

Authors: Pratikbhai Patel

Abstract: The globalization of power systems with smart grid infrastructure has increased the demand of using high efficiency power conversion technologies that can incorporate into the national grids renewable energy sources, including solar and wind. This study focuses on the significance of a developed Pulse Width Modulation (PWM) methodology in streamlining the inverter efficiency, minimizing the harmonic distortion, and the grid stability. The research uses a systematic analysis methodology to assess converter topologies, modulation schemes, energy storage integration, electric vehicle mechanism, demand response scheme, and computational intelligence scheme under smart grid conditions. The results show that the optimised PWM methods have a significant drop in switching and conduction losses, thermal performance, and quality of voltage waveforms. These enhancements lead to the growth in the level of renewable penetration, system reliability, and low cost of operation. In addition, the study emphasizes the need to coordinate inverter efficiency standards, adaptive control, and digital grid coordination to facilitate sustainable development goals in the world. These findings validate that power electronic conversion systems that operate on high efficiency are critical enablers of resilience, scale and environmentally sustainable smart grid infrastructures globally.

DOI: https://doi.org/10.5281/zenodo.19088267

Published by: vikaspatanker

Authors: Dudekula Imam Khasim Vali, V.E.S.Mahendra Kumar

Abstract: The economy of all structures is being impacted by the current cost of building materials. It has a significant impact on the global environmental housing system. Conventional aggregates, such as gravel, and fine aggregate, such as sand in concrete, will be utilized for control. Robo sand (stone dust) will be used as fine aggregate to replace the sand in concrete, while natural material such as coconut shell will be researched as a coarse aggregate. In this study, sample specimens are prepared and tested using M25 grade concrete that has a combination of natural material coconut shell content as coarse aggregate in the proportions of 0%, 5%, 10%, 15%, 20%, and 25%, and Robo sand (stone dust) as fine aggregate with a complete 100% replacement of natural sand. for workability, compressive strength, split tensile strength and flexural strength for 7,14 and 28 days respectively and also showing the comparative results with Conventional M25 grade concrete. By this project investigation, concrete may be less dense, light weight concrete by coconut shells and good quality of concrete by Robo sand.

 

 

Published by: vikaspatanker

Authors: Eedara Venkata Hareesh, N.Sriaknth

Abstract: Building Information Modeling (BIM) has emerged as a transformative digital technology in the construction industry by enabling intelligent 3D modeling, improved collaboration, and efficient information management throughout the project lifecycle. However, successful project execution not only depends on accurate design representation but also requires effective project planning, scheduling, and resource control. Primavera P6 is widely recognized as a powerful project management software that supports detailed planning, time scheduling, cost estimation, and progress monitoring for complex construction projects. The integration of BIM with Primavera provides a highly efficient platform for developing realistic construction schedules, improving project visualization, and ensuring better decision-making during project execution.This study focuses on BIM-integrated project planning and scheduling using Primavera to enhance the effectiveness of construction project management. BIM models developed using software such as Revit are linked with Primavera schedules to establish a strong relationship between project activities and building components. This integration supports 4D planning, where the time dimension is combined with the 3D model to simulate construction sequencing and visualize the progress of project execution. Through BIM-based scheduling, construction stakeholders can identify logical activity sequences, detect clashes in time and space, and optimize the use of labor, materials, and equipment. The integrated approach improves coordination between architects, engineers, contractors, and project managers, thereby minimizing scheduling conflicts, reducing rework, and improving productivity.

 

 

Published by: vikaspatanker

Authors: Edara Nasarababu, G.Nagalakshimi

Abstract: Understanding the behaviour of bolstered concrete is vital for properly predicting future earthquake loading consequences on reinforced concrete systems and designing the structural gadget to undergo seismic pressures. Accurate seismic load consequences on the structural device are vital no longer just in multi-story buildings but additionally in usual residential constructions. This research examines the results of slab kinds at the performance of load-bearing systems in multi-tale reinforced concrete systems underneath seismic hundreds, in accordance with the modern-day Turkish Earthquake Code (TEC). This research conducts a comparative analysis of a flat slab gadget with 4 beam versions for a seven-story structure. The examine is conducted with pushover evaluation with the assistance of the ETABS software program application. The beam variations are labeled as follows: a structure with a completely flat slab (no beams), a shape with a flat slab and perimeter beams (apart from indoors beams), a shape with a flat slab and all beams, and a structure with a flat slab, whole beams, and brick walls. The examine findings, including base shear, storey drift, time period, and frequency, are tested for the G+8 building model.

DOI:

 

Published by: vikaspatanker

Authors: Guttikonda Venkateswara Reddy, M.Ashok

Abstract: The disposal of waste tyres has emerged as a significant environmental challenge due to their non-biodegradable nature, large volume generation, and associated fire and health hazards. In the context of sustainable infrastructure development, the utilization of waste tyre rubber in pavement base and sub-base layers presents a promising alternative for both waste management and performance enhancement of flexible pavements. This study investigates the feasibility, engineering behavior, and structural performance of pavement base and sub-base materials modified with waste tyre rubber in various forms such as shredded rubber, crumb rubber, and rubber chips. Laboratory experimental investigations were conducted to evaluate key geotechnical and mechanical properties including compaction characteristics, California Bearing Ratio (CBR), unconfined compressive strength (UCS), resilient modulus, permeability, and durability. The influence of rubber content on density, stiffness, deformation characteristics, and energy absorption capacity was systematically analyzed. Results indicate that controlled incorporation of waste tyre rubber improves ductility, fatigue resistance, and resistance to cracking while contributing to reduction in material brittleness. However, excessive rubber content leads to reduction in load-bearing capacity due to lower stiffness and density. The study identifies optimum rubber content ranges suitable for base and sub-base applications based on performance criteria. Environmental and economic benefits, including reduced landfill burden, conservation of natural aggregates, and lifecycle cost savings, are also discussed. The findings support the potential of waste tyre rubber as a sustainable geomaterial for pavement applications, contributing to circular economy principles and resilient road infrastructure.

 

 

Published by: vikaspatanker

Authors: Jonnala Adarsh Reddy, M.Ashok

Abstract: Sustainable pavement design has gained significant attention due to the increasing scarcity of natural aggregates and the environmental burden associated with construction activities. Construction and Demolition (C&D) waste offers a viable alternative material for pavement layers, promoting resource conservation and circular economy principles. This study investigates the feasibility of utilizing processed C&D waste in flexible pavement construction with an emphasis on structural performance, durability, and sustainability. The engineering properties of C&D waste aggregates, including gradation, strength, and stiffness characteristics, are evaluated and compared with conventional materials. Mechanistic–empirical design concepts are adopted to assess pavement response and long-term performance. Non-destructive evaluation techniques are considered to monitor in-service behavior and structural integrity of pavements incorporating recycled materials. Results indicate that, with proper processing and mix design, C&D waste can satisfactorily meet pavement design requirements. The use of C&D waste significantly reduces material costs, landfill disposal, and carbon footprint. This approach supports sustainable infrastructure development while maintaining acceptable performance standards. The findings provide practical guidance for integrating recycled materials into pavement design frameworks.

 

 

Published by: vikaspatanker