arXiv subjects

Luis López

Publications and source records attributed to Luis López.

6 recordsLinked to original sources

arXiv2026

Securing the Sandbox: A Rootless Containerized Framework for Process-Oriented Monitoring in Computer Graphics Education

Computer Science education fundamentally depends on intensive laboratory hours to foster true programming mastery and logical reasoning. However, the widespread adoption of Generative Artificial Intelligence (AI) has made it virtually impossible to distinguish authentic student effort from instant AI code synthesis by evaluating final submissions alone. To preserve pedagogical integrity, educators must enforce authentic coding discipline, guiding students through unassisted, iterative development cycles. While centralized environments like JupyterHub provide instructors with a platform to host and monitor the learning process step-by-step, they introduce severe operational vulnerabilities; because Jupyter environments inherently allow arbitrary shell command execution, they expose the underlying shared host to unauthorized system manipulation and lateral movement. This paper presents VISMATIC, a secure, low-cost framework designed to resolve this tension between process-oriented monitoring and infrastructure security. By pairing robust environment isolation with explicit user-interaction tracking at the API level, VISMATIC captures authentic programming behaviors without exposing the underlying host system. Evaluation from a pilot student cohort demonstrates that our macro-level behavioral metrics successfully flag statistical anomalies indicative of automated or off-platform workflows while preserving student anonymity, offering a scalable blueprint for safeguarding educational discipline in the AI era.

cs.CY↗

arXiv2025

An efficient GPU approach for designing 3D cultural heritage information systems

We propose a new architecture for 3D information systems that takes advantage of the inherent parallelism of the GPUs. This new solution structures information as thematic layers, allowing a level of detail independent of the resolution of the meshes. Previous proposals of layer based systems present issues, both in terms of performance and storage, due to the use of octrees to index information. In contrast, our approach employs two-dimensional textures, highly efficient in GPU, to store and index information. In this article we describe this architecture and detail the GPU algorithms required to edit these layers. Finally, we present a performance comparison of our approach against an octree based system.

cs.DC↗

arXiv2016

Resource location based on precomputed partial random walks in dynamic networks

The problem of finding a resource residing in a network node (the \emph{resource location problem}) is a challenge in complex networks due to aspects as network size, unknown network topology, and network dynamics. The problem is especially difficult if no requirements on the resource placement strategy or the network structure are to be imposed, assuming of course that keeping centralized resource information is not feasible or appropriate. Under these conditions, random algorithms are useful to search the network. A possible strategy for static networks, proposed in previous work, uses short random walks precomputed at each network node as partial walks to construct longer random walks with associated resource information. In this work, we adapt the previous mechanisms to dynamic networks, where resource instances may appear in, and disappear from, network nodes, and the nodes themselves may leave and join the network, resembling realistic scenarios. We analyze the resulting resource location mechanisms, providing expressions that accurately predict average search lengths, which are validated using simulation experiments. Reduction of average search lengths compared to simple random walk searches are found to be very large, even in the face of high network volatility. We also study the cost of the mechanisms, focusing on the overhead implied by the periodic recomputation of partial walks to refresh the information on resources, concluding that the proposed mechanisms behave efficiently and robustly in dynamic networks.

cs.NI↗

arXiv2014

Trend and Fractality Assessment of Mexico's Stock Exchange

The total value of domestic market capitalization of the Mexican Stock Exchange was calculated at 520 billion of dollars by the end of November 2013. To manage this system and make optimum capital investments, its dynamics needs to be predicted. However, randomness within the stock indexes makes forecasting a difficult task. To address this issue, in this work, trends and fractality were studied using GNU-R over the opening and closing prices indexes over the past 23 years. Returns, Kernel density estimation, autocorrelation function and R/S analysis and the Hurst exponent were used in this research. As a result, it was found that the Kernel estimation density and the autocorrelation function shown the presence of long-range memory effects. In a first approximation, the returns of closing prices seems to behave according to a Markovian random walk with a length of step size given by an alpha-stable random process. For extreme values, returns decay asymptotically as a power law with a characteristic exponent approximately equal to 2.5.

q-fin.ST↗

arXiv2013

Reducing Search Lengths with Locally Precomputed Partial Random Walks

Random walks can be used to search a complex networks for a desired resource. To reduce the number of hops necessary to find the resource, we propose a search mechanism based on building random walks connecting together partial walks that have been precomputed at each network node in an initial stage. The resources found in each partial walk are registered in its associated Bloom filter. Searches can then jump over partial nodes in which the resource is not located, significantly reducing search length. However, additional unnecessary hops come from false positives at the Bloom filters. The analytic model provided predicts the expected search length of this mechanism, the optimal size of the partial walks and the corresponding optimal (shortest) expected search length. Simulation experiments are used to validate these predictions and to assess the impact of the number of partial walks precomputed in each node.

cs.NI↗

arXiv2013

Improving Resource Location with Locally Precomputed Partial Random Walks

Random walks can be used to search complex networks for a desired resource. To reduce search lengths, we propose a mechanism based on building random walks connecting together partial walks (PW) previously computed at each network node. Resources found in each PW are registered. Searches can then jump over PWs where the resource is not located. However, we assume that perfect recording of resources may be costly, and hence, probabilistic structures like Bloom filters are used. Then, unnecessary hops may come from false positives at the Bloom filters. Two variations of this mechanism have been considered, depending on whether we first choose a PW in the current node and then check it for the resource, or we first check all PWs and then choose one. In addition, PWs can be either simple random walks or self-avoiding random walks. Analytical models are provided to predict expected search lengths and other magnitudes of the resulting four mechanisms. Simulation experiments validate these predictions and allow us to compare these techniques with simple random walk searches, finding very large reductions of expected search lengths.

cs.NI↗