A Parametric Framework to Generate Visual Illusions Using Python

Visual illusions are fascinating phenomena that have been used and studied by artists and scientists for centuries, leading to important discoveries about the neurocognitive underpinnings of perception, consciousness, and neuropsychiatric disorders such as schizophrenia or autism. Surprisingly, despite their historical and theoretical importance as psychological stimuli, there is no dedicated software, nor consistent approach, to generate illusions in a systematic fashion. Instead, scientists have to craft them by hand in an idiosyncratic fashion, or use pre-made images not tailored for the specific needs of their studies. This, in turn, hinders the reproducibility of illusion-based research, narrowing possibilities for scientific breakthroughs and their applications. With the aim of addressing this gap, Pyllusion is a Python-based open-source software (freely available at https://github.com/RealityBending/Pyllusion ), that offers a framework to manipulate and generate illusions in a systematic way, compatible with different output formats such as image files (.png, .jpg, .tiff, etc.) or experimental software (such as PsychoPy).

Development of Virtual Simulation Experimental Software of Marine Platform Structure

Due to the harsh offshore exploitation environment, students are unable to conduct field investigation in offshore platforms. In this scenario, virtual simulation is an effective way to solve this problem. This paper introduces in detail a Virtual Simulation Experimental Software of Marine Platform Structure, which is closely integrated with the course content and engineering reality. Through the operation and learning of platform site selection, platform structure assembly, platform structure display, can realize the students' knowledge of platform structure composition mastery, and at the same time improve the students' participation and motivation. In addition, the system can automatically generate the experiment report and give the operation score reference to realize the teacher's quality control of the experiment course.

Wavelet Modeling of Control Stochastic Systems at Complex Shock Disturbances

This article is devoted to the development of methodological supports and experimental software tools for accuracy analysis and information processing in control stochastic systems (CStS) with complex shock disturbances (ShD) by means of wavelet Haar–Galerkin technologies. Basic new results include methods and algorithms of stochastic covariance analysis and modeling on the basis of the Galerkin method and wavelet expansion for linear, linear with parametric noises, and quasilinear CStS with ShD. Results are illustrated by an information-control system at ShD. New stochastic effects accumulation for systematic and random errors are detected and investigated.

A Descriptive 3D City Information Model Built From Infrastructure BIM

This study developed a descriptive 3D city information model (CIM) using only infrastructural building modeling tools to create maps, and analyzed the model according to needs identified in interviews with public-sector actors and a bibliometric analysis. The interviews assessed the challenges of implementing CIM in the Brazilian city of Curitiba, while the literature study determined that current academic production reflects the current reality, calling attention to relevant issues. The experimental software solution successfully created 3D informational modeling of cities for passive use as well as maps to support decision making, although it did not offer advanced parametric tools for urban analysis. Still, this model provides a flexible approach to overcoming the challenges reported by interviewees, which included financial limitations and organizational culture.

A descriptive 3D city information model built from infrastructure BIM

This study developed a descriptive 3D city information model (CIM) using only infrastructural building modeling tools to create maps, and analyzed the model according to needs identified in interviews with public-sector actors and a bibliometric analysis. The interviews assessed the challenges of implementing CIM in the Brazilian city of Curitiba, while the literature study determined that current academic production reflects the current reality, calling attention to relevant issues. The experimental software solution successfully created 3D informational modeling of cities for passive use as well as maps to support decision making, although it did not offer advanced parametric tools for urban analysis. Still, this model provides a flexible approach to overcoming the challenges reported by interviewees, which included financial limitations and organizational culture.

A study into the practice of reporting software engineering experiments

It has been argued that reporting software engineering experiments in a standardized way helps researchers find relevant information, understand how experiments were conducted and assess the validity of their results. Various guidelines have been proposed specifically for software engineering experiments. The benefits of such guidelines have often been emphasized, but the actual uptake and practice of reporting have not yet been investigated since the introduction of many of the more recent guidelines. In this research, we utilize a mixed-method study design including sequence analysis techniques for evaluating to which extent papers follow such guidelines. Our study focuses on the four most prominent software engineering journals and the time period from 2000 to 2020. Our results show that many experimental papers miss information suggested by guidelines, that no de facto standard sequence for reporting exists, and that many papers do not cite any guidelines. We discuss these findings and implications for the discipline of experimental software engineering focusing on the review process and the potential to refine and extend guidelines, among others, to account for theory explicitly.

Intelligent Malware - Trends and Possibilities

In recent months and years, with more and more computers and computer systems becoming the target of cyberattacks. These attacks are gaining strength and the sophistication of the approach in terms of how to attack. Attackers and Defenders are increasingly using artificial intelligence methods to maximize the success of their actions. For a successful defence, we must be able to anticipate future threats that may come. For these reasons, our research group is engaged in creating experimental software with artificial intelligence to test the possibilities and capabilities of such malware in the event of its deployment. This software has not only malware capabilities but also antimalware and can be used on both sides. This article introduces the reader to the main principles of our design, which can serve as a future platform for cyber defence systems.

Webcam-based online eye-tracking for behavioral research

Experiments are increasingly moving online (especially during the COVID epidemic). This poses a major challenge for researchers who rely on in-lab process-tracing techniques such as eye-tracking. Researchers in computer science have developed a web-based eye-tracking application (WebGazer) (Papoutsaki et al., 2016) but it has yet to see use in behavioral research. This is likely due to the extensive calibration and validation procedure (~50% of the study time) and low/inconsistent temporal resolution (Semmelmann & Weigelt, 2018), as well as the challenge of integrating it into standard experimental software. Here, we incorporate WebGazer with the most widely used JavaScript library among behavioral researchers (jsPsych) and adjust the procedure and code to reduce calibration/validation and dramatically improve the temporal resolution (from 100-1000 ms to 20-30 ms or better). We test our WebGazer/jsPsych combination with a decision-making study on Amazon MTurk. We find little degradation in spatial or temporal resolution over the course of the ~30-minute experiment. We replicate previous in-lab findings on the relationship between gaze dwell time and value-based choice. In summary, we provide an open-source, accessible, software template and tutorial for web-based eye-tracking in behavioral research that is sufficient to replicate in-lab studies with just a modest number of participants (N=38), and that is orders of magnitude faster than in-lab data collection. Moreover, we highlight that web-based eye-tracking is a useful tool for all behavioral researchers, as it can be used to ensure that study participants are humans and not machines.

A gateway between GitLab CI and DIRAC

GitLab’s Continuous Integration has proven to be an efficient tool to manage the lifecycle of experimental software. This has sparked interest in uses that exceed simple unit tests, and therefore require more resources, such as production data configuration and physics data analysis. The default GitLab CI runner software is not appropriate for such tasks, and we show that it is possible to use the GitLab API and modern container orchestration technologies to build a custom CI runner that integrates with DIRAC, the middleware used by the LHCb experiment to run its job on the Worldwide LHC Computing Grid. This system allows for excellent utilisation of computing resources while also providing additional flexibility for defining jobs and providing authentication.