Authors - Lucian Julio Felix da Costa, Claudio de Souza Baptista, Andre Luiz Firmino Alves Abstract - Auditing public procurement processes is essential to ensure transparency, accountability, and efficiency in the management of public funds. However, the increasing complexity of procurement procedures poses significant challenges for auditors, particularly regarding the timely detection of pricing irregularities. This paper presents a software tool for price comparison designed to support the identification of overpricing and underpricing in public works procurement. The proposed solution leverages semantic retrieval and historical price comparison techniques to analyze procurement data and integrate up-to-date market information. Additionally, the application provides interactive visualizations and semantic retrieval mechanisms to support auditors during procurement price analysis activities. The expected contribution of this study lies in improving the effectiveness and accuracy of procurement oversight, strengthening financial analysis processes, and contributing to the prevention and deterrence of fraudulent practices among bidders.
Authors - Vanderson dos Santos Araujo, Eliane Tamara Lima Oliveira, Pedro Manoel Hermínio Alves, Andre Luiz Firmino Alves, Claudio de Souza Baptista Abstract - Auditing public tenders requires analyzing lengthy documents to verify compliance with tender notices, a time-consuming task prone to human error. This article empirically evaluates the use of Large Language Models (LLMs) to assist with auditing tender notices. A total of 50 official tender notices and 736 audit instances were analyzed, comparing three context-provisioning strategies: expanded context windows, integrated file retrieval, and a custom Retrieval-Augmented Generation (RAG) pipeline. The results show that no single approach is superior across all scenarios. Models with long windows performed better at confirming explicit conformities, whereas retrieval-based strategies demonstrated greater sensitivity to potential non-conformities due to omissions. The analysis also indicates that the type of question strongly influences performance, especially for interpretive questions or those that rely on the absence of documentary evidence. As a key contribution, the study demonstrates that the effectiveness of AI-assisted auditing depends on the combination of the contextualization strategy, the quality of the retrieved context, and the formulation of the questions, reinforcing the role of LLMs as tools to support the auditor.
Authors - Ahmed Belgaid Abstract - Digital transformation has profoundly altered the organization of work and reinforced the importance of mastering digital tools for employability and productivity. In this context, this study highlights the challenges of digital accessibility for employees with visual impairments and its application through an analysis of the new WCAG standards. The aim of our analysis is to demonstrate that digital accessibility consists of guaranteeing an inclusive digital transformation; it is not limited to simply ac-quiring digital solutions or adapting existing ones. It is a comprehensive preparation process and an integrated approach involving various stakeholders within the company.
Authors - BENABDELLAH Nouhaila, CHRAIBI Abdeslam, BENRREZZOUQ Rhizlane Abstract - The importance of smart logistics dashboards as key tools for digital transformation in manufacturing companies is becoming more recognized. They enable real-time visibility, in-tegrate various data sources, and allow for analysis. However, there is limited research on how these dashboards affect decision quality and operational performance in emerging countries. This paper explores the impact of smart logistics dashboards on data-driven decision making (DDDM) and operational performance in Moroccan manufacturing firms. We conducted a quantitative survey among logistics and operations managers and examined a proposed concep-tual framework using PLS-SEM. The findings showed that the capabilities provided by smart dashboards significantly improve decision quality through better data integration and real-time analytics. Additionally, DDDM plays a key role in the relationship between smart dashboards and operational performance. These results are important for the field of smart logistics and digital transformation and have valuable practical implications for management in manufactur-ing firms in emerging countries.
Authors - Francisco Castro Murillo, Teresita de Jesus Alvarez Robles, Andres Sandoval Bringas, Monica Carreno Leon, Francisco Javier Alvarez Rodriguez Abstract - Web accessibility for visually impaired users remains a critical challenge in HCI. While technical compliance with WCAG is well-established, knowledge of User Experience (UX) evaluation methods tailored to non-visual interaction is fragmented. This paper presents a systematic mapping of the literature (2016–2026), analyzing 18 high-quality studies selected from 134 records retrieved from IEEE Xplore, ACM DL, SpringerLink, and ScienceDirect. Results show that user testing is the predominant method, often combined with standardized questionnaires like SUS and NASA-TLX. However, critical gaps persist: small sample sizes, inconsistent participant reporting, and a lack of metrics designed for non-visual interaction. This study contributes a taxonomy of visually impaired user profiles and identifies the technical requirements for building an inclusive web usability laboratory. By bridging the gap between technical auditing and real-world user satisfaction, this work provides a roadmap for the development of the MEUX LAB, ensuring more equitable digital evaluation environments.
Authors - Vikas Pandey, Sanasam Chanu Inunganbi Abstract - Plagiarism has become a serious problem in universities, research organizations, and professional workplaces, affecting academic integrity and the originality of work. While cloud-based detection tools are widely used, they share a fundamental problem that rarely gets discussed openly: every document is required to be submitted and handed over to a third-party server. For unpublished research, legal drafts, or any sensitive material, this trade-off is not acceptable. The proposed method, named ZERO, takes a different approach and runs entirely on the local machine, watching the clipboard quietly in the background and scoring text against a local TF-IDF corpus in under 200 milliseconds, with no uploads, no accounts, and no data leaving the device. An optional web scanning module is available when broader source coverage is needed. On top of the similarity score, ZERO provides a word-level risk heatmap, a sentence-by-sentence originality breakdown, a stylometric module called Writing DNA, and a scan history timeline. Testing on 60 hand-labelled samples showed that a recalibrated scoring curve brings the average score on original technical writing down from 34.7% to 9.8%, while keeping verbatim-copy detection at 95%. API credentials are stored in the OS keychain, and inter-process communication is locked to a strict channel whitelist, making the application well-suited for confidential and pre-publication work.
