Detecting Context Shifts in the Human Experience Using Multimodal Foundation Models

2025-05-04 · 1 citations

Detecting context shifts in human experience is critical for applications in cognitive modeling, human-AI interaction, and adaptive neurotechnology. However, formalizing and identifying these shifts in real-world settings remains challenging due to annotation inconsistencies, data sparsity, and the multimodal nature of human perception.

Revolutionizing Structural Damage Inspection in Infrastructure: The Role of Drones and 3D Scanning in Educational Innovation

2025-04-22

This paper presents the results of implementing innovative strategies using drones and 3D scanners in the specialization course Efficiency and Digitalization of Construction, aimed at undergraduate students of civil engineering and architecture. The course is offered as a specialization option among three alternatives in the penultimate semester of undergraduate programs in these fields: Sustainable Use of Water, Real Estate Intelligence, and Efficiency and Digitalization of Construction. It is delivered over an intensive 11 -week period, during which topics such as Structural Damage and Inspection Techniques, Structural Health Monitoring, Non-Destructive Testing, and Design for Durability are covered. In 2024, the course was attended by a group of 25 students from various campuses across the country. For the module on Structural Damage and Inspection Techniques, students engaged in traditional visual inspection activities of the campus stadium, identifying and qualitatively assessing damages using conventional management systems to evaluate damage severity. In contrast, a parallel activity was designed to implement advanced technologies, including 3D scanning with LiDAR and drones equipped with high-definition cameras, to identify and map damages. This technological approach enabled a quantitative and highly precise evaluation of damage severity through image analysis. When comparing these instructional strategies, incorporating technology and innovation into the cited module, students expressed, through end-of-course surveys, high motivation toward developing and researching technological solutions. They also recognized the importance of integrating high-precision technology into the evaluation and diagnosis of existing infrastructure. At the conclusion of the course activities, students and faculty prepared and submitted a technical report to campus administrators, detailing their findings and results. This report is expected to contribute to future maintenance and conservation projects, thus closing the cycle of specialization activities by observing the execution of physical interventions on the inspected stadium. Faculty members plan to continue these activities with the next cohort in the following academic year, allowing for the monitoring of damage progression and ensuring continuity in learning outcomes.

SPHERE CPS Enclave: A Reconfigurable Testbed for Industrial Control System Security Experimentation

2025-05-06

Cyber-physical systems (CPS) increasingly face security threats that can disrupt critical infrastructure operations. The SPHERE CPS enclave is a modular, remotely accessible industrial control system (ICS) testbed designed to support security experimentation on programmable logic controllers (PLCs), industrial networks, and digital twin simulations. It enables researchers to investigate cyber-physical attacks, anomaly detection, and intrusion resilience strategies. Unlike general cybersecurity testbeds, SPHERE's CPS enclave provides a configurable, realistic environment for studying adversarial scenarios that bridge cyber and physical domains. The infrastructure offers controlled, reproducible experiments with customizable network topologies and hardware-in-the-loop validation. This poster presents the design philosophy, community-driven experimental goals, and deployment considerations of the SPHERE CPS enclave, demonstrating its potential for advancing CPS security research.

ICSTracker: Backtracking Intrusions in Modern Industrial Control Systems

2025-06-23

Applying "provenance analysis" to industrial control systems (ICS) is challenging. Existing research struggles with recovering the physical semantics of controller logic, managing inconsistent state transitions, tracking cross-domain causality, and practical implementation. In this paper, we introduce ICS Tracker, a comprehensive approach that addresses these gaps by using digital twins to collect logs, automatically recovering physical semantics, reconstructing data dependencies, and linking controller operations to OS-level events. Tested on ten attack scenarios across two testbeds, ICSTracker outperforms previous methods, capturing all attack activities where earlier techniques missed 56%.

Lost in Tracking Translation: A Comprehensive Analysis of Visual SLAM in Human-Centered XR and IoT Ecosystems

ACM Transactions on Sensor Networks · 2025-12-12

Advances in tracking algorithms have enabled applications from steering autonomous vehicles to guiding robots to enhancing augmented reality experiences for users. However, these algorithms are application-specific and do not work across applications with different types of motion; even a tracking algorithm designed for a given application does not work in scenarios deviating from highly standard conditions. For example, a tracking algorithm designed for indoor robot navigation will not work for tracking the same robot in an outdoor environment. To demonstrate this problem, we evaluate the performance of the state-of-the-art tracking methods across various applications and scenarios. To inform our analysis, we first categorize environmental, locomotion-related, and algorithmic challenges faced by tracking algorithms. We quantitatively evaluate the performance using multiple tracking algorithms and representative datasets for a wide range of Internet of Things (IoT) and Extended Reality (XR) applications, including autonomous vehicles, drones, and humans. Our analysis shows that no tracking algorithm works across all applications and even in diverse scenarios within the same application. Ultimately, using the insights generated from our analysis, we discuss multiple approaches to improving the tracking performance using input data characterization, leveraging intermediate information, and output evaluation.

HyTwin: Hybrid Program Semantics for Digital Twin-Based Security Interventions in Industrial Control Systems

Lecture notes in computer science · 2025-01-01

PrivacyOracle: Configuring Sensor Privacy Firewalls with Large Language Models in Smart Built Environments

2024-05-23 · 6 citations

Modern smart buildings and environments rely on sensory infrastructure to capture and process information about their inhabitants. However, it remains challenging to ensure that this infrastructure complies with privacy norms, preferences, and regulations; individuals occupying smart environments are often occupied with their tasks, lack awareness of the surrounding sensing mechanisms, and are non-technical experts. This problem is only exacerbated by the increasing number of sensors being deployed in these environments, as well as services seeking to use their sensory data. As a result, individuals face an unmanageable number of privacy decisions, preventing them from effectively behaving as their own “privacy firewall” for filtering and managing the multitude of personal information flows. These decisions often require qualitative reasoning over privacy regulations, understanding privacy-sensitive contexts, and applying various privacy transformations when necessary We propose the use of Large Language Models (LLMs), which have demonstrated qualitative reasoning over social/legal norms, sensory data, and program synthesis, all of which are necessary for privacy firewalls. We present PrivacyOracle, a prototype system for configuring privacy firewalls on behalf of users using LLMs, enabling automated privacy decisions in smart built environments. Our evaluation shows that PrivacyOracle achieves up to $\mathbf{9 8 \%}$ accuracy in identifying privacy-sensitive states from sensor data, and demonstrates $\mathbf{7 5 \%}$ accuracy in measuring social acceptability of information flows.

Privacy Policies on the Fediverse: A Case Study of Mastodon Instances

Proceedings on Privacy Enhancing Technologies · 2024-07-06 · 2 citations

Free and open source social platform software has dramatically lowered the barrier to entry for anyone to set up and administer their own social network. This new population of social network administrators thus assume data management responsibilities for sociotechnical systems. Administrators have the power to customize this software, including data collection and data retention, potentially leading to radically different privacy policies. To better understand the characteristics — e.g., the variability, prohibitions, and permissions — of privacy policies on these new social networking platforms, we have conducted a case study of Mastodon. We performed a text analysis of 351 privacy policies and a survey of 104 Mastodon administrators. While most administrators used the default policy that ships with the Mastodon software, we observed that approximately ten percent of our sample tailored their privacy policies to their instances and that some administrators conflated codes of conduct with privacy policies. Our findings suggest the existing market-based individualistic frameworks for thinking about privacy policies do not adequately address this emerging community.

Administrative management and budget execution in a public university

SCIÉNDO · 2024-12-30

La ejecución presupuestal es un indicador importante para evaluar el uso de recursos y cumplimiento de metas de una organización. Por ello, el objetivo de esta investigación es determinar la relación entre la gestión administrativa y la ejecución presupuestal, en la Universidad Nacional José María Arguedas (UNAJMA), Perú, 2021. La técnica fue la encuesta, la cual se aplicó mediante dos cuestionarios a 130 trabajadores administrativos y los resultados se analizaron en SPSS, mediante la prueba no paramétrica Chi-cuadrado porque los datos tienen una distribución no normal. Como principal resultado, se determinó que la gestión administrativa y la ejecución presupuestal tienen un nivel regular y están significativamente relacionadas (p=0,000<0,05). Asimismo, se determinó que la planificación, organización, dirección y control, como dimensiones de la gestión administrativa, están relacionadas significativamente con la ejecución presupuestal, todas con una significancia p=0,000<0,05. Por lo tanto, se concluye que la gestión administrativa y todas sus dimensiones están significativamente relacionadas a la ejecución presupuestal, en dicha entidad.

Estimating the Risk of Failure in Government Auctions in Brazil

2024-11-17

O governo federal brasileiro realiza aproximadamente 63 mil pregões eletrônicos por ao ano, com despesas de cerca de R$190 bilhões. Agências de fiscalização enfrentam desafios para monitorar essas aquisições devido ao alto volume e custo. Este artigo propõe um modelo para classificar os pregões com base no risco de irregularidades. Os resultados obtidos indicam que o modelo de aprendizagem de máquina baseado no algoritmo XGBoost é eficaz na identificação de itens de pregão com maior risco de irregularidades graves, com um recall de 84% para a classe de interesse. O modelo tem o potencial de otimizar os recursos de fiscalização, direcionando os esforços para os pregões mais críticos, aumentando a probabilidade de detectar irregularidades e a expectativa de controle dos órgãos governamentais fiscalizados.