Authors - Shabnam Praveen, Shubham Kumar, Tulika Roy, Sanskriti Sahu, Subhangi Raj, Ranjita Kumari Dash Abstract - The implementation and design of a covert communication channel that embeds hidden information within TCP/IP packet headers rather than within the actual payload of the packets is presented as a project. This is different than traditional embedding methods (steganography), which typically embed data into multime dia files, in that steganography in this case utilizes header fields that are not cur rently in use or can be modified so that TCP/IP packets can transmit hidden data. The fields that are used to transmit hidden data are the IP Identification Field, TCP Sequence Number, TCP Acknowledgment Number, and TCP Window Size. The sender module encodes and generates packets, and the receiver retrieves packets, extracts encoded bits, and reassembles data from the encoded bits found in the packets. The integrity of the data is verified using a checksum (SHA-256) and packet loss is reported. The lack of a payload will further enhance the stealth various data transmission methods may enjoy as it will circumvent conventional intrusion detection techniques (which primarily examine the payload data within packets). This project will demonstrate the ability to use this or similar covert communication channels to implement covert communication systems. In addi tion, covert communication channels can be used for different types of files and demonstrate the security and educational value of covert channel research in net work security.
Authors - Prajakta Shinkar, Madhuri Suryavanshi, Sakshi Satav, Mahima Thakre, Saisha Chaudhary Abstract - The contemporary academic and professional world requires smart systems of productivity that are not limited to the old task managers. The paper introduces an intelligent personal productivity assistant powered by AI that consists of generative AI, dynamical schedule, behavioral analytics, and gamification using a mobile-first structure. The system is based on a Flutter frontend and FastAPI backend and a hybrid AI architecture to create conversational tasks and understand their context. A burnout detection module is a behavioral module that analyzes workload trends, tasks owed and completion trends to give early risk alerts. A smart scheduling system aggressively plans on a daily basis with priority-based model, conflict resolution and Pomodoro-based segmentation. The proposed system combines conversational AI, predictive analytics, and motivational reinforcement to increase productivity and decrease cognitive load and help avoid burnout in managing tasks.
Authors - Ashvini Jadhav, Pankaj Chandre Abstract - The contemporary academic and professional world requires smart systems of productivity that are not limited to the old task managers. The paper introduces an intelligent personal productivity assistant powered by AI that consists of generative AI, dynamical schedule, behavioral analytics, and gamification using a mobile-first structure. The system is based on a Flutter frontend and FastAPI backend and a hybrid AI architecture to create conversational tasks and understand their context. A burnout detection module is a behavioral module that analyzes workload trends, tasks owed and completion trends to give early risk alerts. A smart scheduling system aggressively plans on a daily basis with priority-based model, conflict resolution and Pomodoro-based segmentation. The proposed system combines conversational AI, predictive analytics, and motivational reinforcement to increase productivity and decrease cognitive load and help avoid burnout in managing tasks.
Authors - NamUook, Kim, Gihwan Bong, Yoon Seok, Chang Abstract - The heterogeneity of data sources makes the design of traditional da ta ware-houses complex and time-consuming. Indeed, the data warehouse system must process structured, semi-structured, and unstructured sources. To over-come this challenge, we propose an interactive approach to data ware house design based on a federated ontology. The ontology serves as a unified conceptual layer that integrates heterogeneous data sources and facilitates the building of the data warehouse. Our approach allows decision-makers to in teractively select the subdomain of the federated ontology according to their needs and generate their data warehouse. The generation of the data ware-house in the constellation schema is automated using algorithms. It also ensures the maintenance of the data warehouse to take into account various changes in data and decision-makers' needs. The proposed methodology is summarized through architectures defined at each stage, each addressing a specific challenge. At the ontology construction level, it resolves issues related to data heterogeneity while enabling interoperability among multiple do-main ontologies. It also provides a complete scenario for the decision-maker to assist in the full construction of a data warehouse from an ontology. Finally, it facilitates querying the constructed data warehouse using requests ex-pressed by the decision-maker in natural language.
Authors - C Nitheeshwaran, M Saravanan, S Mukesh, K S Anuvarshini Abstract - The present study explores the online privacy concerns of young Indian consumers. Using the segmentation approach popularized by Dr Alan Wes-tin in the U.S., this study identifies the segments within Indian youth. This study is based on a survey conducted on a sample of Indian university students. Hierarchical and non-hierarchical cluster analysis techniques were applied to identify segments within young Indian consumers based on their privacy concerns. The study identified three consumer segments: highly concerned, moderately concerned, and less concerned based on online privacy concerns. The findings also reveal important differences among the three segments in terms of out-come variables such as perceived effectiveness of legal/regulatory policy, fabricating personal information, and software usage for protection. The results indicate an overall increased level of concern for online privacy among young Indian consumers. The results suggest similarities and dissimilarities with Westin’s approach. While previous research on online privacy has been chiefly based on the Western context, this study offers a window to look at the Eastern context by examining the privacy concerns of young Indian consumers, who have not been studied, and hence provides an important contribution to the existing literature.
Authors - Quang-Thinh Bui, Lan T.T. Tran Abstract - The digital transformation of the construction industry has intensified the demand for standardized methods of information exchange. Building Infor mation Modeling (BIM) has become a cornerstone of this transformation, ena bling interdisciplinary collaboration and improving data quality. However, recur ring challenges such as inconsistent data structures, unclear contractual require ments, and limited interoperability continue to hinder efficient project delivery. To address these issues, the Information Delivery Specification (IDS) was devel oped within the buildingSMART ecosystem as a computer-interpretable standard for defining and validating information requirements. Officially approved in June 2024, IDS bridges human-readable requirements with machine-interpretable val idation rules, positioning itself as both a contractual instrument and a technical validation tool. This study synthesizes insights from official IDS documentation and academic literature to provide a comprehensive evaluation of IDS’s role in the construction sector. The systematic literature review categorizes contributions into five the matic domains: standardization, application scenarios, systematic reviews, coun try and domain-specific studies, and methodological innovations. Findings high light IDS’s versatility across diverse applications, including acoustic assessment, accessibility compliance, railway projects, and energy simulation. At the same time, research gaps remain in areas such as national adaptation strategies, auto mated compliance checking through CI/CD pipelines, and methodological devel opment via linkage with the Level of Information Needs (LoIN). By integrating theoretical perspectives with practical case studies, this research demonstrates how IDS functions as both a technical standard and a methodolog ical framework. The study concludes that IDS has the potential to become a cor nerstone of digital construction practices, bridging regulatory requirements with automated validation in BIM workflows.
Authors - Anuja Kelkar, Pradnya Kardile, Aditi Dudhe, Prajakta Chaudhari, Meenal Kamlakar Abstract - In this paper we derive a new estimate of the channel bit rate. The estimates is a special transformation of the main EVT theorem that is particularly designed for use in telecommunication automated systesm meaning it’s robust to noise, computationally cheep, needs very few data points and no manual validation. Due to the EVT methodology we can evaluate if the bit rate can keep dropping indefinitely or if it has a guaranteed minimum value. The method is relatively fast because it uses Newton’s interpolation instead of hypothesis testing or regression.
Authors - Ankur Maurya, Shaurya Oberoi, Madhav Malhotra, Rakesh Chandra Joshi, Garima Aggarwal, Malay Kishore Dutta Abstract - Remote sensing imagery plays an important role in applications such as environmental monitoring, disaster management, urban planning and agricultural analysis. However, the spatial resolution of such imagery is often limited by sensor constraints, revisit frequency and acquisition cost. To address this challenge, this paper presents RCAN-RS, an enhanced Residual Channel Attention Network for remote sensing image super-resolution. The proposed model extends the RCAN framework through three targeted modifications: a dual-pooling channel attention mechanism, a spectral attention module and an edge enhancement module. These components are designed to improve detail reconstruction while preserving inter-channel consistency and sharp structural boundaries in remote sensing imagery. The model was trained and evaluated on the DOTA dataset un-der a 2× super-resolution setting from 256 × 256 to 512 × 512 pixels. Quantitative evaluation using both conventional image-quality metrics and remote-sensing-oriented measures shows that RCAN-RS achieves a mean PSNR of 34.42 dB, SSIM of 0.9398, Edge Preservation Index of 0.9524, ERGAS of 6.68 and UQI of 0.9846 on the test set. These results demonstrate the effectiveness of integrating attention-guided and edge-aware mechanisms for remote sensing image super-resolution.
Authors - Inuka Gajanayake, Gagani Kulathilaka, Guhanathan Poravi, Saadh Jawwadh Abstract - The swift growth of digital interfaces has facilitated manipulative design practices called dark patterns, which take advantage of cognitive biases to manipulate users and subvert informed decision-making. Though widespread across e-commerce, social media, and other areas, automated identification and empirical knowledge of user vulnerability are still in their infancy. This work introduces an end-to-end framework integrating a GenAI-augmented browser add-on for real-time detection of dark patterns with systematic estimation of user awareness and behavioral reactions. A new Pattern Vulnerability Index (PVI) measures the threat from individual patterns according to frequency, unawareness among users, and potential damage. Cross-platform analysis identified high-risk patterns like Discount Anchoring, Urgency, and cost-related manipulations to be frequently overlooked by users. Clustering identifies scenarios in which several deceptive patterns occur in co-presence, including checkout processes, promotional displays, and subscription pitfalls. The results highlight the moral significance of manipulative interface design and establish the capability of machine-based tools to promote user safeguard, sensitize, and guide regulation and design efforts. This study provides a basis for consumer-oriented solutions and future research towards more transparent and ethical online encounters.
Authors - Hiep. L. Thi Abstract - As a core pillar industry in China's economic transformation toward a service-oriented economy, the tourism industry plays an irreplaceable role in boosting domestic demand growth, optimizing regional industrial structures, and advancing high-quality economic development. The Dazu Rock Carvings in Chongqing, holding the dual top-tier qualifications of a World Cultural Heritage site and a National 5A Scenic Area, embody over 1,300 years of historical accumulation. With their unique cultural core of ‘Confucian-Buddhist-Taoist Syncretism’ and top-tier high-relief artistic craftsmanship, they stand as the pinnacle of Chinese stone carving art, boasting remarkable cultural tourism economic value and cultural inheritance value. However, for a long time, the Dazu Rock Carvings have been trapped in the dilemma of ‘high cultural value but low market recognition’—acclaimed but underrecognized in the market. Their visibility enhancement relies excessively on short-term hotspots, lacking a long-term support mechanism. Based on theories of culture-tourism integration, brand communication, and sustainable cultural heritage development, this paper employs literature review, data analysis, case comparison, and field research to accurately identify core pain points. It constructs a scientific and feasible new marketing path from six dimensions: innovative resource transformation, precise audience cultivation, diversified channel expansion, upgraded cross-border linkage, breakthrough international communication, and long-term institutional safeguards. This path aims to help the Dazu Rock Carvings transition from traffic-dependent development to value-driven development and, at the same time, provide practical references for similar cultural heritage scenic spots in China.
