Authors: Sai Sandra, Niranjini Shibu

Abstract: The sustainable development goal-11 symbolizes the need for sustainable cities and communities in the forthcoming generation. It is necessary to built safe, resilient and greener environments in and around the habitats. The growing emphasis on sustainability in the construction industry has led to the exploration of biobased and eco-friendly materials. Among these, cork has gained significant attention due to its renewable nature, versatility, and exceptional physical properties. Derived from the bark of the cork oak tree, cork offers remarkable environmental, mechanical, and thermal advantages, making it a promising material for sustainable construction. This paper explores the origin, environmental significance, material properties, applications in the construction Industry and future potential of cork as a sustainable building material. By integrating cork into modern construction practices, the industry can substantially reduce the carbon emissions, safer communities and environmental footprint while enhancing the durability and efficiency of built environments.

DOI: https://doi.org/10.5281/zenodo.17519248

 

Published by: vikaspatanker

Authors: T. Sekar, A. Sangeetha

Abstract: The increased number of road accidents associated with violating two-wheeler helmet usage is very alarming and this situation demands the introduction of smart surveillance systems to maintain safety of the people. In this paper, we present the idea of a new system of helmet detection using deep learning algorithms and image processing to detect whether a person is not wearing a helmet automatically or not. The publicly available Kaggle Helmet Detection dataset that includes 7,500 images having annotations of bounding-boxes of helmet head, and person is used by the system. We transform the annotations to a binary classification task – Helmet and No Helmet and use the YOLOv5 object detection model because of its speed and accuracy of the inference. This was done by training the model using transfer learning and optimizing the model with data augmentation techniques to achieve cross generalization under different kinds of light and environmental conditions. Our system is tenable based on the results of experiments because it took into consideration a real-world scenario. The model based on the YOLOv5 had a generally high accuracy of 95.64%, precision of 94.32%, recall of 91.23% and an F1-score of 92.75. Real-time inference can also be done with the system as it can perform 24.56 ms/frame. This will fit it to be used in surveillance systems in a city environment. Also, Deep SORT tracking has been integrated to provide effective tracking without redundancy. This project will be useful in the development of intelligent traffic systems to automate the process of identifying non-helmets with high precision making it useful to law enforcement and citizen and driver safety on the road. It may be extended in the future to have modules of number plate recognition and fine imposing modules to be able to implement all the traffic rules.

Published by: vikaspatanker

Authors: Pushkar Chaudhari, Vaibhav Thakre, Tushar Chaudhari, Tanaya Bhaute, Dr.Rais Khan

Abstract: Port scanning is an essential technique in the arsenal of network security professionals, enabling the identification of active services and potential vulnerabilities on target systems. Despite advances in the field, traditional tools like Nmap and Masscan face limitations in usability, scan speed, resource efficiency, and integration capabilities. This paper presents the development and robust evaluation of an advanced port scanning tool built with Python, applying multi-threading and asynchronous techniques. Through comparative assessments, the proposed tool demonstrates compelling advantages in speed, resource efficiency, and cross-platform support, contributing to both practical and academic applications in cybersecurity.

Published by: vikaspatanker

Authors: M. Anbarasan, Dr. P. Guhan

Abstract: Fruit quality inspection plays a critical role in reducing post-harvest losses and ensuring consumer safety in the agricultural supply chain. Conventional manual inspection techniques are time-consuming, manual and ineffective on larger scales. To address these constraints, the paper introduces a model of identifying fruit quality using deep learning techniques that employ methods of digital image processing. The model exploits two-stage and evaluation procedure including classification and detection operation. We used pre-trained DenseNet networks with transfer learning to divide the fruits into three quality levels of Fresh, Overripe, and Spoiled quality. The method of image preprocessing normalization, filtering, and augmentation were used to increase the model robustness. The DenseNet model had an evaluation accuracy of 97.82%, which was higher as compared to SVM (89.53%) and Random Forest (90.21%) which are the conventional classifiers. Parallel to it, we also tested object detection models such as YOLOv8 to recognize and bound fruits with bounding boxes and label quality. YOLOv8 was revealed to be very fast with an average precision (mAP) of 96.1% and intersection over union (IoU) of 87.3%. It was also calculated that precision, recall, F1-score, and the time of inference were taken across 10 models. Findings confirm the efficiency of deep learning in automating the process of fruit quality determination to consequently deploy real-time applications in separating systems. The presented model is very flexible to other types of agricultural products and compatible with smart farming and automation processes that include retailing. Generally, this work fills the nexus between manual inspection and smart visual systems by making the fruit quality monitoring scalable, consistent, and efficient.

Published by: vikaspatanker

Authors: Kalaji L K, Thyagarajan K

Abstract: This paper presents a MATLAB/Simulink model of Photo Voltaic (PV) using Maximum Power Point Tracking (MPPT) technique and a converter. This model provide 200 V output from a 24 V input. The development of PV model, the integration of the MPPT with an average model of power electronics and the MATLAB implementation are described. The converter section consists of an isolated coupled inductor DC-DC converter. It has high gain. It consist of a dual-voltage doubler circuit. In addition, the energy in the coupled inductor leakage inductance can be recycled via a nondissipative snubber on the primary side. Thus, the system efficiency is improved. It completes the simulation of a PV energy conversion system.

DOI: https://doi.org/10.5281/zenodo.17510805

 

Published by: vikaspatanker

Authors: Mr. Ghanshyam Gajanan Lihankar, Prof. Snehal. V. Raut

Abstract: This research presents the design and development of a cybersecurity framework for AI-based personal assistants. These assistants, such as Alexa, Siri, and Google Assistant, are widely used for daily tasks but face growing risks from cyber threats and data breaches. The proposed system focuses on improving the security, privacy, and trust of AI assistants by identifying potential vulnerabilities and applying defense mechanisms. The paper explains the architecture, which includes threat detection, secure communication, user authentication, and data protection layers. This model ensures safe interaction, protects user information, and defends against unauthorized access or manipulation using advanced security techniques.

Published by: vikaspatanker

Authors: 1Mr. Rushi A. Jadhao, Prof. S. V. Athawale, Prof. S. V. Raut

Abstract: Brain-Computer Interfaces (BCIs) are fundamentally reshaping the landscape of human-machine interaction, rapidly emerging as an advanced generation of Natural User Interfaces (NUIs) that enable direct, non-muscular communication between the human brain and external apparatus. This paper systematically integrates BCI technology with established NUI principles, demonstrating how sophisticated neural control systems facilitate intuitive and natural data interaction within complex digital environments. The analysis encompasses recent technological milestones and practical uses, particularly within healthcare, communication restoration, and advanced assistive technologies, while simultaneously providing a critical evaluation of persistent operational, economic, and ethical challenges. A systemic review of contemporary technological trajectories, especially those anticipated for the 2024–2025 period, strongly suggests that BCIs are poised to become the quintessential example of an NUI, leveraging raw neural signals to permit effortless, volitional control over devices. Consequently, this study positions BCIs as potent, evolving technologies capable of enriching human functions and addressing neurological pathologies, a potential underpinned by stellar advancements in high-fidelity non-invasive EEG systems, Artificial Intelligence (AI)-enhanced signal processing, and integrated multimodal interfaces.

Published by: vikaspatanker

Authors: Manoj Parasa

Abstract: The convergence of artificial intelligence and SMART goal frameworks within SAP SuccessFactors has redefined performance management by embedding predictive and adaptive intelligence into the goal lifecycle. This study investigates how AI-augmented goal tracking enhances employee productivity, engagement, and organizational agility through data-driven insights. A mixed-methods design was applied, combining a functional prototype built on SAP SuccessFactors Performance and Goals with qualitative interviews from HR strategists and a quantitative evaluation of user data extracted from system simulations. Natural-language models, sentiment-analysis engines, and predictive dashboards were assessed for their ability to optimize goal alignment, forecast completion likelihood, and enable timely feedback interventions. Empirical results show that integrating AI into SMART frameworks increased goal completion rates by 22.8 percent, reduced review-cycle latency by 31 percent, and improved cross-team alignment consistency. The proposed framework demonstrates how adaptive machine-learning algorithms can transform reactive appraisals into continuous, evidence-based development processes. The paper concludes with a model for implementing AI-supported SMART goal systems within SAP SuccessFactors that balances efficiency with ethical governance, ensuring algorithmic transparency and equity in performance outcomes. These findings contribute to both academic literature and HR practice by establishing a scalable, ethically responsible architecture for next-generation performance management

DOI: http://doi.org/10.5281/zenodo.17500915

Published by: vikaspatanker

Authors: Milan Bhimani, Treesha Bacchuwar, Asst. Prof. Himanshu Tiwari, Sadap Bibi, Zinal Shah

Abstract: The rapid growth of digital platforms has transformed the way people discover and participate in local events. However, existing event discovery systems often focus on large-scale gatherings, neglecting hyperlocal activities rel- evant to smaller communities such as college campuses. This paper presents the design and development of a Hy- perlocal Event Finder System, a web-based platform that leverages geolocation and interest-based filtering to provide users with real-time access to nearby events. The system is built using a full-stack architecture with React.js for the frontend, Express.js and Node.js for the backend, and MongoDB as the database.It integrates user authenti- cation, event management, and recommendation features to deliver a seamless experience. Testing and evaluation demonstrate that the platform effectively addresses acces- sibility, scalability, and usability challenges, making it a promising solution for students and community members seeking context-specific event engagement. Future work will enhance personalization through advanced recommen- dation models and mobile application support.

Published by: vikaspatanker

Education is the major difference between the human and other species, this is the basic tool of knowledge transfer. Apart from basic knowledge information of some research is transfer by research articles. For this Journals are present that provides a repository for the people to save. Many of scholars or researcher search for the Free Academic Journals that provides free access to the readers so that knowledge is transfer to many relevant people who are looking for the same research area. This article help such scholar to get those journals such websites have following set of features:

Submit Your Paper  / Check Publication Charges

1. Journals archive section have list of articles check recent published articles and download the paper for free.

2. To generate revenue journals takes a small charges in name of publication or management.

3. Scholar should check the journal author section and search for the type of charges journal takes from the user. Some of journals who do not take any publication charges are unpaid journals but they work on subscription model where published article is download only for subscribed users.

4. Journals that do not show such information should be avoid for publication because they might charge after acceptance. Further charges of such journals are very high mostly depends on the country.

5. Always find that journal do regular publication in each volume issue this shows that journal is active and work for the author.

6. Some of publishers do not specify type of charges at submission and ask it once they send a acceptance email, so if possible then find the contact details of such publisher before publication of paper.

7. Any of journals that clearly specify the publication charges, contact number, provide various medium of publication are god publication house journals.

Many of Free Academic Journals that do publication and provide open access for free are either funded by government or some research organization always do very hard review. Publication in such journal tough for the beginners. So to develop a research profile author should go for the publication of journals who either take very less fees or very less subscription. Such journal should have good team as well so each published article have wider reach around the world.

Published by: vikaspatanker