Hack Hub is a campus-oriented web platform designed to streamline and centralize the management of hackathons, internships, and mentorship programs for students within educational institutions. In many colleges, information regarding technical events, internship opportunities, and mentorship programs is often scattered across multiple platforms such as emails, social media groups, and notice boards. This fragmented communication leads to missed opportunities, lack of awareness, and inefficient participation from students. To address these challenges, Hack Hub provides a unified digital solution that connects students, mentors, and administrators in a single platform. The Hack Hub system enables students to explore upcoming hackathons, apply for internships, and request mentorship support through an easy-to-use web interface. The platform allows administrators to create and manage events, publish internship opportunities, assign mentors, and monitor student participation effectively. Students can create profiles, browse opportunities, register for hackathons, submit internship applications, and communicate with mentors. The mentorship module helps students gain career guidance, technical knowledge, and project support from experienced mentors. The system also improves communication between users and ensures that all opportunities are organized and accessible. The application is developed using modern web technologies such as HTML, CSS, JavaScript, and React for building a responsive and interactive user interface. PHP is used as the backend technology to handle server-side processing, authentication, and business logic. MySQL database is used for storing user details, event information, internship postings, mentorship data, and application records. The integration of these technologies ensures efficient data management, secure user authentication, and smooth system performance. Hack Hub reduces manual work for administrators and provides a centralized platform for managing student opportunities. It improves student engagement, encourages participation in hackathons, enhances career development through internships, and promotes knowledge sharing through mentorship programs. The system is scalable, user-friendly, and can be extended with additional features such as notifications, AI-based recommendations, and mobile application support in the future.

Abstract Race conditions in web applications represent a persistent class of vulnerabilities that allow adversaries to bypass business logic through synchronized request bursts. While the transition from TCP-based HTTP/2 to UDP-based HTTP/3 (QUIC) introduces stochastic processing delays and independent stream delivery, the security implications of these protocol shifts remain under-explored. This work investigates the effectiveness of race condition exploits across modern transport protocols. Our experimental results demonstrate that while the user-space implementation of QUIC provides a resilience threshold against low-volume attacks, this protection is an artifact of scheduling jitter and is inherently fragile. We identify a critical concurrency threshold ( $$N=100$$ N = 100 ) where the density of a Single Datagram Attack (SDA) saturates the protocol parser, achieving an exploitation efficiency ( f ) that exceeds traditional HTTP/2 methods. However, we also identify a “smothering effect” unique to high-density bursts, where extreme transaction arrival rates trigger database-level lost updates that can paradoxically limit total economic impact. Furthermore, we show that infrastructure-level defenses, such as network pacing, are effectively neutralized by the reverse proxy’s de-multiplexing process. We conclude that protocol-level evolution does not mitigate application-layer concurrency risks; rather, it shifts the attack surface dynamics toward more efficient but higher-contention exploitation primitives.

This paper addresses the architectural design of a distributed web-based system for enterprise commodity flow management. Based on domain analysis, functional and non-functional requirements influencing the architectural decision are identified. A three-tier architectural model is proposed, consisting of a client presentation layer, a server-side business logic layer built on PHP, and a data storage layer powered by MySQL. To support geographically distributed operations, a data synchronization mechanism between the central node and remote branches is introduced, utilizing MySQL native replication and RESTful application programming interfaces. A comparative analysis of monolithic, three-tier, and microservice architectures is conducted using criteria of scalability, deployment cost, maintenance complexity, and fault tolerance. The findings indicate that for medium-sized enterprises with limited IT budgets, a three-tier architecture with distributed features achieves an acceptable trade-off between functionality and development effort.

ABSTRACT This paper presents AAMMOS (Autonomous Agentic Mainframe Modernization Operating System), a novel AI-powered framework for transforming legacy mainframe systems into cloud-native microservices. The system addresses the $3.3 trillion challenge of mainframe modernization by automating COBOL-to-Java transformation while preserving 100% business logic equivalence. Our approach combines six integrated modules: Protocol translation (EBCDIC↔UTF-8 conversion), Intelligent code generation (COBOL AST parsing), Distributed transaction orchestration (Saga pattern), Security mapping (RACF/ACF2 to OAuth2), Shadow validation (parallel execution with byte-level checking), and Cloud deployment automation (Docker/Kubernetes). Tested on a $1B+ daily transaction fund transfer system, AAMMOS achieved: 11-week transformation (vs. 24-36 months traditional), 50x performance improvement (8-24 hours → 200-500ms), 99.9996% code equivalence validation (1,347,892 test cases), and 4-6 microservices auto-generated from single 850-line COBOL program. Patent filed with India Patent Office (March 29, 2026). This research addresses a critical gap in enterprise modernization for financial institutions and large-scale legacy environments. Keywords: mainframe modernization, COBOL transformation, microservices, legacy systems, AI-powered code generation

With the rapid rise of social e-commerce, an increasing number of consumers now purchase goods through social community networks. However, substitution effects arising from limited inventories and stockouts can seriously impair demand forecasting accuracy. To address this challenge, we propose XAI-Sub, an interpretable demand forecasting framework that systematically incorporates domain knowledge via text mining and biclustering to improve both transparency and predictive performance. By aggregating sparse sales records into substitution-aware clusters and estimating scenario-specific substitution matrices using a novel alternating minimisation algorithm, XAI-Sub explicitly quantifies substitutive relationships while preserving interpretability. Validated on data from a large community group-buying (CGB) platform, our framework achieves a relative improvement of 38% in forecasting accuracy compared with conventional methods. The approach introduces three key advancements in explainable artificial intelligence (XAI): (1) domain-knowledge anchoring: text-derived semantic features anchor substitution patterns within business logic, facilitating human-AI alignment; (2) scenario-driven interpretability: biclustering decomposes demand dynamics into actionable substitution typologies; and (3) causal pathway visualisation: the substitution matrix serves as an interpretable interface, delineating demand redistribution pathways across clusters. This work demonstrates how formalising domain knowledge can bridge the ‘explanation gap’ in complex demand systems and provides CGB enterprises with practical tools to audit and exploit substitution mechanisms.

Abstract: In today’s rapidly growing digital world, community welfare activities still face major challenges due to the lack of structured and centralized systems. Although many people are willing to help others, there is often a gap between those who need support and those who can provide it. Existing methods such as social media posts, phone calls, and informal communication channels are widely used, but they are unorganized, difficult to track, and unreliable when the number of requests increases. These limitations lead to delayed responses, duplication of efforts, lack of transparency, and reduced trust among users. This paper presents CommunityConnect, a multi-role community support and welfare management platform designed to address these real-world challenges. The system provides a centralized digital environment where users, NGOs, volunteers, donors, and administrators can interact in a structured and coordinated manner. The core idea of the platform is to treat every welfare request not as a simple submission, but as a complete process that moves through multiple stages such as request creation, verification, acceptance or rejection, volunteer assignment, execution, tracking, and final closure. This workflow-based approach ensures that each request is properly managed, monitored, and completed with accountability. The platform is developed using modern web technologies to ensure performance, scalability, and usability. The frontend is built using React with Vite, providing a responsive and user-friendly interface. The backend is implemented using Node.js and Express, which handle business logic, request processing, and API communication. A MySQL database is used for structured data storage, enabling efficient management of users, requests, assignments, and system records. Secure authentication is implemented through email-based OTP verification and JWT-based session management, ensuring that only authorized users can access the system. Additional features such as media uploads, role-based access control, and integrated communication further enhance system functionality. The design and development of CommunityConnect are strongly supported by existing research in areas such as digital volunteering, nonprofit technology adoption, and civic engagement platforms. Previous studies highlight that digital platforms can improve participation and coordination, but most of them focus on specific aspects such as volunteer management or donation systems. They lack integration, workflow tracking, and multi-stakeholder coordination. CommunityConnect addresses this research gap by combining multiple functionalities into a single unified platform, enabling better coordination, transparency, and efficiency. The system has been successfully implemented and deployed on a live environment, demonstrating its real-world applicability. The results show that the platform is capable of improving communication between stakeholders, reducing response delays, increasing user participation, and ensuring better utilization of resources. By providing a structured and transparent workflow, CommunityConnect enhances trust and accountability in community welfare systems. Thus, CommunityConnect is not only a technical solution but also a socially impactful platform that leverages digital technology to strengthen community support mechanisms and improve the overall effectiveness of welfare activities in modern society. Keywords: Community Welfare, Digital Platform, Workflow Management, NGO Coordination, Volunteer Management, Role-Based Access Control, Request Lifecycle, Web Application, Transparency, Resource Sharing

This paper centers on open-secret vulnerabilities (OSVs), a kind of smart contract vulnerability that allows attackers to exploit the natural transparency feature of blockchains to gain illegal monetary profits from problematic smart contracts. Attackers can easily launch OSV attacks by leveraging publicly visible information from a smart contract to issue a profitable transaction without violating its business logic. This poses significant challenges in detecting OSVs. Despite the severe impacts of OSVs, there is no prior research work that systematically discusses OSVs (to the best of our knowledge). To fill this knowledge gap, this paper presents a formal definition of OSVs, and OSVHunter, the first-ever tool aiming to detect OSVs in smart contracts. The detection results show that OSVs are prevalent in real-world smart contracts. Some of these vulnerabilities are even concealed within highly popular Ethereum contracts, with individual contract valuations exceeding five hundred thousand U.S. dollars. These vulnerabilities appear in finance, gaming, gambling, etc. We hope this paper can arouse our community’s attention to the significance of OSVs and lay the technical foundation for future research.

The notion of managing multiple business models as a portfolio of different business models has captured the attention of both scholars and practitioners, reflecting a growing interest in how firms can pursue and manage different business objectives and drive growth. While previous research has explored how to manage existing business model portfolios, few studies have examined the processes involved in the creation of such portfolios. Drawing on a digital transformation initiative within a large manufacturing firm, this study offers an in-depth account of a business model portfolio expansion process as an incumbent B2B-firm add a new digital business model. By analyzing the incremental decoupling of the emerging business model from the existing, this study proposes a framework for business model expansion as a gradual, staged process of separation. It identifies three key mechanisms inherent in this: the gradual decoupling of the emerging business logic and its co-evolution with the structural separation of the organizations, the rapid sequencing of the stages in the process, and the critical role of external triggers. Overall, the study contributes to the literature on business model portfolios, while also advancing understanding of business model expansion and structural separation. • A gradual structural separation enables business model addition. • A co-evolving additional, digital logic supports portfolio expansion. • A rapid iteration between stages reduces conflicts and enables managerial initiatives. • External triggers are key for accelerating business model portfolio extension. • Outlines a stepwise decoupling process for managing the balance between an emerging business model and an existing portfolio.

Alan Turing's machine model of the universal machine model laid the theory and foundation of current computers, and layers can be regarded as an essence of computer science of current generation computers, averting the ubiquity of the universal computing; however, gradually, against Moore’s law and stepping into higher speed-computing needs, betraying the shortcomings of Turing’s model, are come up a new structure paradigm, namely specific domain architectures. Domain architecture is a style of software development which can extracts the complex business logic and build it out as a pure ‘domain model’, one that is independent of technical solutions. It is a bit like preparing an exact business blueprint of a software system: the software code may truly reflect business concepts and business rules. By defining clear boundaries and responsibilities, the domain architecture makes the system highly understandable, maintainable and capable of dynamically responding to changes in frequent business requirements. This article argues that people are entering a "post-Turing era", and people gradually turn from the pursuit of universality to pursuit of efficiency and accuracy. And that success of domain-specific architectures is no mere technology nor is it a new form rather than Turing’s form as represented by GPUs. Moreover, the future of computing will, sooner or later, be a heterogeneous era dominated by this new form.

In the past two decades, innovation has become the defining logic of business and policy. Every organisation now claims to innovate responsibly, sustainably, or ethically. Yet, when compared with established professions such as accounting, engineering, or project management, innovation management stands out for what it lacks: any formalised code of ethics. Innovation managers operate in spaces of uncertainty and asymmetrical power, often shaping technologies and systems long before society has understood their implications. The consequences of this ethical vacuum in Innovation Management (IM) are increasingly profound. The question, then, is no longer whether innovation should be ethical, but how ethics can be meaningfully institutionalised within innovation practice. This Letter proposes that innovation management urgently requires a formal code of ethics to guide conduct, clarify values, and legitimise the practice of innovation. It situates this argument within three long-standing ethical traditions that address the uncertainty of technological progress: the Precautionary Principle, which emphasises restraint in the face of risk; Anticipatory Ethics, which seeks to foresee moral challenges before they arise; and Responsible Innovation, which calls for alignment between technological progress and societal values. Together, these frameworks provide a robust theoretical foundation for the development of a hybrid model to provide ethical foresight into the evolving profession of innovation management.

This article critically analyzes the impacts of educational platformization and the financialization of teacher training in Brazil, linking these processes to the transformations of digital capitalism after 2008. From the field of critical agrarian education, it investigates how business logic and corporate governance models have redefined the role of public institutions, teachers, and curricula, especially through the actions of corporate foundations, EdTechs, and private organizations within public policies. Through a qualitative methodological approach, with an exploratory and analytical character, the text denounces the advance of an algorithmic pedagogy, guided by goals and indicators, which depoliticizes teaching work and empties its emancipatory dimension. In contrast to this trend, the text recovers the theoretical and political foundations of Latin American critical pedagogy, highlighting the legacy of Paulo Freire, the conception of the teacher as an organic intellectual, and the contributions of Southern epistemologies. It values the role of public universities and federal institutes as territories of resistance and affirms the importance of teacher training programs anchored in rural social movements, such as PRONERA and Saberes da Terra. It concludes that resisting platformization does not mean rejecting technology, but rather disputing its meanings and uses from a rooted, critical, and territorialized perspective. In times of deepening neoliberalism, training teachers committed to social and environmental justice also means training individuals of resistance and hope.

This study aims to analyze how the platformization of education has placed algorithmic governance at the center of the pedagogical, administrative, and evaluative management of schools. This has contributed to the control of narratives involving ethical, political, and social issues, through a business and neoconservative logic that reconfigures the structural way of teaching, learning, and managing education, and prioritizes the personalization of teaching based on financial-informational-digital capitalism. This scenario, often invisible to students, teachers, and administrators, has been observed in schools within the Paraná state public school system and poses challenges to public policies, which need to reconcile technological innovation, digital inclusion, and the protection of fundamental rights as ways to promote inclusion and plurality, rather than acting as mechanisms for controlling social narratives. The methodology is based on Historical Dialectical-Materialism, within the categories of “historical totality”, “contradiction”, and “hegemony”, with a qualitative nature of bibliographic typology and exploratory-documentary character, in order to analyze algorithmic governance in education in its technical, ethical, political, and social dimensions, highlighting data from the public school system of the state of Paraná. The results indicate the urgency of regulatory frameworks that ensure transparency, accountability, and social justice in the use of digital technologies applied to education.

In the context of increasingly complex data-driven decision-making, traditional analytical methods face significant challenges in handling heterogeneous data correlations and real-time computational responsiveness. By developing an Integrated Computational Business Analytics Framework (ICBAF), this research proposes a three-layer computational architecture comprising heterogeneous data representation, heuristic computational optimization, and online feedback loops, aiming to achieve a deep coupling of business logic and algorithmic reasoning. The findings indicate that by leveraging the topological representation capabilities of Graph Neural Networks (GNN) and the dynamic optimization mechanisms of real-time stream computing, this framework effectively resolves bottlenecks such as "data silos" and "decision lag," significantly enhancing decision precision in scenarios like intelligent marketing and smart operations. However, as the study primarily focuses on theoretical deduction and scenario-based simulations, it lacks rigorous empirical validation using large-scale, real-world industrial datasets. Consequently, its generalization capabilities under extreme noise and the cost-benefit ratio of computational resources require further verification in future research.

Despite the rise of the e-governance agenda in supporting local government operations, the involvement of higher education in promoting a collaborative extension initiative supporting such an agenda remains scarce in the literature, especially in rural communities with low digital literacy. Thus, this work details the development and implementation of the Cangbagsa Digital Barangay Information System (CDBIS), an academically driven extension solution that addresses inefficiencies in barangay (i.e., the Philippines’ smallest administrative unit) operations. Prior challenges included processing documents within 2–3 days, data inaccuracies, and limited service accessibility. This study aims to digitize local governance, improve efficiency, ensure data integrity, and create a scalable model for community innovation. The system was developed using a web-based, multi-tier architecture that integrates a user-friendly interface, role-based business logic, a centralized database, and secure server infrastructure to support efficient barangay data management and decision-making. The post-implementation evaluation uses the Updated DeLone and McLean Information System Success Model and a 22-item survey for system users, using a 7-point Likert scale. Data from the survey were analyzed through descriptive statistics and stepwise regression to identify predictors of user satisfaction. Respondents rated all constructs highly. Regression analysis shows System Quality as the strongest predictor of satisfaction (β=0.361), followed by Service (β=0.295) and Information Quality (β=0.287), explaining 65% of the variance. CDBIS significantly improved governance, reducing processing time by 75% and improving data accuracy by 88%. Sustaining success requires ongoing optimization, training, and user engagement. The system offers a replicable model for digital transformation in other rural communities.

The growth of capabilities of mobile devices allows them to host increasingly sophisticated applications. These capabilities have piqued interest in domains such as automotive, gaming, or 5G-based telecommunications, in use cases where hosting services in mobile devices is no longer a mere option, but has become a necessity due to stringent Quality of Service requirements. In this context, the emerging Hybrid Edge Cloud (HEC) paradigm provides an infrastructure for service execution in end devices. However, the highly dynamic and distributed nature of end devices makes the orchestration of services executed in them an open challenge; paramount to the operation of the system, as devices may often need to delegate services to other devices. We present the Collaborative Edge Cloud (CEC), an extension of HEC in which service orchestration and delegation are decoupled from a service’s business logic. Moreover, as a proof of concept of CEC, we also present the Pervasive Delegation of Services (PODS) platform, an implementation of CEC that allows services to be executed in end devices and orchestrated independently of their logic in an entirely decentralized way. Our evaluation shows that PODS, and thus CEC, improves the lifetime of collaborative services up to 4.9 × relative to other approaches.

Micro, small, and medium enterprises (MSMEs) in goat farming continue to encounter challenges in sales management, livestock data recording, and financial reporting due to reliance on manual processes. These issues often result in recording errors, data inconsistencies, and difficulties in routine business performance monitoring. This research designs and develops GoatPOS, a web-based Point of Sale (POS) system to facilitate goat sales management, ready-to-sell livestock inventory, financial reports, and customer data. Research methods encompass observation, interviews, and literature review, with system development following the Waterfall model. A client-server architecture is employed, utilizing Node.js for backend business logic and API services, alongside React.js for the interactive frontend interface. Findings demonstrate that GoatPOS enhances operational efficiency through transaction automation and real-time reporting, while bolstering data security via role-based access control. Thus, GoatPOS emerges as an information system solution promoting data-driven decision-making and the sustainability of goat farming enterprises.

With the widespread application of Internet of Things (IoT) technology in smart cities, its security issues have become increasingly prominent. Fuzzing, as an efficient automated vulnerability discovery technique, has been widely used in IoT security assessment. However, current research mostly focuses on general IoT environments or specific device types, lacking a systematic analysis of the complex, dynamic, and deeply integrated context of smart cities. This paper presents a review and integration of 42 representative IoT fuzzing studies published between 2021 and 2025, analyzed via an eight-dimensional analytical framework. It reveals significant gaps with reports on real-world attacks on the IoT systems between current research and the practical security needs of smart cities across three dimensions: device, protocol, and methodology. Based on this, this paper innovatively proposes: (1) an Observability-Complexity Based IoT Device Classification Model based on device observability and business logic complexity, providing a navigation chart for migrating testing capabilities across devices; (2) a technology migration framework based on protocol feature matching, facilitating rapid coverage of emerging and vertical protocols; (3) a methodological evolution path from “vulnerability mining” to “system resilience probing.” This research aims to promote the future role of IoT fuzzing in the assessment and assurance of smart city security resilience by providing structured analytical tools and clear research directions.

Retail investors in the Indian stock market often face significant losses due to a lack of structured, verified research and reliance on unverified “tips” circulated on social media. Existing platforms are either too expensive for beginners or lack accountability in their recommendations. This paper introduces StockPro, a comprehensive FinTech SaaS platform designed to democratize access to professional-grade stock research. Unlike traditional dashboards, StockPro utilizes a Layered Architecture to separate business logic from presentation, ensuring scalability and security. The system integrates real-time market data, a curated “Research Call” engine with lifecycle tracking, and a robust portfolio management system. Key technical contributions include a custom Role-Based Access Control (RBAC) system for analysts and users, and an automated Performance Tracking Module that verifies stock calls against live market data without human intervention

The integration of Artificial Intelligence (AI) into code quality analysis addresses the limitations of traditional manual and static analysis by leveraging machine learning (ML) and Large Language Models (LLMs) to identify syntax, semantic, and architectural issues. As of 2026, AI-driven tools have become foundational in Agile development, streamlining repetitive review tasks and enforcing consistent coding standards. While AI excels at rapid bug detection and security vulnerability identification, challenges remain in its ability to fully comprehend complex business logic and project-specific intent. Consequently, modern workflows emphasize a hybrid approach: "AI-assisted, human-verified". This strategy uses AI to handle the "repetitive 70%" of analysis, allowing human developers to focus on the remaining 30% of high-value, creative decision-making.

The rapid growth of online commerce has increased the demand for secure, scalable, and efficient-commerce platforms. This paper presents the design and development of a full-stack e-commerce website that enables customers to browse products, manage shopping carts, and complete secure online transactions. The system also provides administrative functionalities such as inventory management, order processing, and user management. A three-tier architecture consisting of frontend, backend, and database layers is adopted to ensure modularity and scalability. The frontend is developed using modern JavaScript frameworks to deliver a responsive user interface, while the backend uses Node.js and Express.js to handle business logic and authentication. Data is stored using MongoDB/MySQL. Security mechanisms such as JWT-based authentication, password hashing, HTTPS communication, and secure payment gateway integration are implemented. Experimental results demonstrate reliable real-time performance and high functional accuracy, making the system suitable for small and medium-scale enterprises.