arXiv subjects

Paulo Matias

Publications and source records attributed to Paulo Matias.

8 recordsLinked to original sources

arXiv2026

A Controlled Candidate-Set Benchmark for Offline Satellite-Security Plan Decomposition

Some security-development settings require local models that map an objective to an ordered, checkable plan. We present a low-rank decomposition adapter and release a case-disjoint corpus with 24 authored decompositions and 83 derived next-step examples across 24 satellite-security cases. To prevent reference-plan leakage, prompts contain one objective and eight shuffled SPARTA candidates. The evaluation candidate sets are constructed with oracle inclusion of every reference technique, so this study measures selection from a controlled set, not retrieval. On six fixed cases and five decoding seeds, mean scores vary across adapters and prompted Qwen2.5 baselines; a separate greedy check over three adapter training seeds shows non-negligible training variance. A 24-fold greedy leave-one-case-out control at the two compact sizes likewise shows tradeoffs: at 1.5B, adapter precision is 0.583 against 0.480 for two-shot prompting, while recall is 0.586 against 0.660. Case-resampling intervals for adapter precision relative to the strongest prompted baseline cross zero at 1.5B and 7B. The adapter is also substantially more format-compliant, which prevents attributing all score differences to selection. Autoregressive next-step accuracy is 0.08, 0.06, and 0.29 at 0.5B, 1.5B, and 7B. We therefore offer the formulation, leakage-controlled dataset, reproducibility package, and descriptive analysis as a proof of concept, not evidence of a reliable stand-alone decomposition system or a general adapter advantage. A separate diagnostic tests contract reuse.

cs.CR↗

arXiv2019

Telescope: an interactive tool for managing large scale analysis from mobile devices

In today's world of big data, computational analysis has become a key driver of biomedical research. Recent exponential growth in the volume of available omics data has reshaped the landscape of contemporary biology, creating demand for a continuous feedback loop that seamlessly integrates experimental biology techniques and bioinformatics tools. High-performance computational facilities are capable of processing considerable volumes of data, yet often lack an easy-to-use interface to guide the user in supervising and adjusting bioinformatics analysis in real-time. Here we report the development of Telescope, a novel interactive tool that interfaces with high-performance computational clusters to deliver an intuitive user interface for controlling and monitoring bioinformatics analyses in real-time. Telescope was designed to natively operate with a simple and straightforward interface using Web 2.0 technology compatible with most modern devices (e.g., tablets and personal smartphones). Telescope provides a modern and elegant solution to integrate computational analyses into the experimental environment of biomedical research. Additionally, it allows biomedical researchers to leverage the power of large computational facilities in a user-friendly manner. Telescope is freely available at https://github.com/Mangul-Lab-USC/telescope.

cs.DC↗

arXiv2019

NIZKCTF: A Non-Interactive Zero-Knowledge Capture the Flag Platform

Capture the Flag (CTF) competitions are increasingly important for the Brazilian cybersecurity community as education and professional tools. Unfortunately, CTF platforms may suffer from security issues, giving an unfair advantage to competitors. To mitigate this, we propose NIZKCTF, the first open-audit CTF platform based on non-interactive zero-knowledge proofs.

cs.CR↗

arXiv2017

Automated pulse discrimination of two freely-swimming weakly electric fish and analysis of their electrical behavior during a dominance contest

Electric fishes modulate their electric organ discharges with a remarkable variability. Some patterns can be easily identified, such as pulse rate changes, offs and chirps, which are often associated with important behavioral contexts, including aggression, hiding and mating. However, these behaviors are only observed when at least two fish are freely interacting. Although their electrical pulses can be easily recorded by non-invasive techniques, discriminating the emitter of each pulse is challenging when physically similar fish are allowed to freely move and interact. Here we optimized a custom-made software recently designed to identify the emitter of pulses by using automated chirp detection, adaptive threshold for pulse detection and slightly changing how the recorded signals are integrated. With these optimizations, we performed a quantitative analysis of the statistical changes throughout the dominance contest with respect to Inter Pulse Intervals, Chirps and Offs dyads of freely moving Gymnotus carapo. In all dyads, chirps were signatures of subsequent submission, even when they occurred early in the contest. Although offs were observed in both dominant and submissive fish, they were substantially more frequent in submissive individuals, in agreement with the idea from previous studies that offs are electric cues of submission. In general, after the dominance is established the submissive fish significantly changes its average pulse rate, while the pulse rate of the dominant remained unchanged. Additionally, no chirps or offs were observed when two fish were manually kept in direct physical contact, suggesting that these electric behaviors are not automatic responses to physical contact.

q-bio.QM↗

arXiv2015

Modular Acquisition and Stimulation System for Timestamp-Driven Neuroscience Experiments

Dedicated systems are fundamental for neuroscience experimental protocols that require timing determinism and synchronous stimuli generation. We developed a data acquisition and stimuli generator system for neuroscience research, optimized for recording timestamps from up to 6 spiking neurons and entirely specified in a high-level Hardware Description Language (HDL). Despite the logic complexity penalty of synthesizing from such a language, it was possible to implement our design in a low-cost small reconfigurable device. Under a modular framework, we explored two different memory arbitration schemes for our system, evaluating both their logic element usage and resilience to input activity bursts. One of them was designed with a decoupled and latency insensitive approach, allowing for easier code reuse, while the other adopted a centralized scheme, constructed specifically for our application. The usage of a high-level HDL allowed straightforward and stepwise code modifications to transform one architecture into the other. The achieved modularity is very useful for rapidly prototyping novel electronic instrumentation systems tailored to scientific research.

q-bio.QM↗

arXiv2015

An embedded system for real-time feedback neuroscience experiments

A complete data acquisition and signal output control system for synchronous stimuli generation, geared towards in vivo neuroscience experiments, was developed using the Terasic DE2i-150 board. All emotions and thoughts are an emergent property of the chemical and electrical activity of neurons. Most of these cells are regarded as excitable cells (spiking neurons), which produce temporally localized electric patterns (spikes). Researchers usually consider that only the instant of occurrence (timestamp) of these spikes encodes information. Registering neural activity evoked by stimuli demands timing determinism and data storage capabilities that cannot be met without dedicated hardware and a hard real-time operational system (RTOS). Indeed, research in neuroscience usually requires dedicated electronic instrumentation for studies in neural coding, brain machine interfaces and closed loop in vivo or in vitro experiments. We developed a complete embedded system solution consisting of a hardware/software co-design with the Intel Atom processor running a free RTOS and a FPGA communicating via a PCIe-to-Avalon bridge. Our system is capable of registering input event timestamps with 1μs precision and digitally generating stimuli output in hard real-time. The whole system is controlled by a Linux-based Graphical User Interface (GUI). Collected results are simultaneously saved in a local file and broadcasted wirelessly to mobile device web-browsers in an user-friendly graphic format, enhanced by HTML5 technology. The developed system is low-cost and highly configurable, enabling various neuroscience experimental setups, while the commercial off-the-shelf systems have low availability and are less flexible to adapt to specific experimental configurations.

q-bio.QM↗

arXiv2014

Representation of Evolutionary Algorithms in FPGA Cluster for Project of Large-Scale Networks

Many problems are related to network projects, such as electric distribution, telecommunication and others. Most of them can be represented by graphs, which manipulate thousands or millions of nodes, becoming almost an impossible task to obtain real-time solutions. Many efficient solutions use Evolutionary Algorithms (EA), where researches show that performance of EAs can be substantially raised by using an appropriate representation, such as the Node-Depth Encoding (NDE). The objective of this work was to partition an implementation on single-FPGA (Field-Programmable Gate Array) based on NDE from 512 nodes to a multi-FPGAs approach, expanding the system to 4096 nodes.

cs.DC↗

arXiv2014

Individual discrimination of freely swimming pulse-type electric fish from electrode array recordings

Pulse-type weakly electric fishes communicate through electrical discharges with a stereotyped waveform, varying solely the interval between pulses according to the information being transmitted. This simple codification mechanism is similar to the one found in various known neuronal circuits, which renders these animals as good models for the study of natural communication systems, allowing experiments involving behavioral and neuroethological aspects. Performing analysis of data collected from more than one freely swimming fish is a challenge since the detected electric organ discharge (EOD) patterns are dependent on each animal's position and orientation relative to the electrodes. However, since each fish emits a characteristic EOD waveform, computational tools can be employed to match each EOD to the respective fish. In this paper we describe a computational method able to recognize fish EODs from dyads using normalized feature vectors obtained by applying Fourier and dual-tree complex wavelet packet transforms. We employ support vector machines as classifiers, and a continuity constraint algorithm allows us to solve issues caused by overlapping EODs and signal saturation. Extensive validation procedures with Gymnotus sp. showed that EODs can be assigned correctly to each fish with only two errors per million discharges.

q-bio.QM↗