This paper presents a new teaching tool with the goal of facilitating the learning of basic programming concepts among high school students and university freshmen. The tool incorporates a user-friendly visual interfa...
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ISBN:
(数字)9798350391084
ISBN:
(纸本)9798350391091
This paper presents a new teaching tool with the goal of facilitating the learning of basic programming concepts among high school students and university freshmen. The tool incorporates a user-friendly visual interface and robotics, expanding on the existing Fluxprog project. New features were implemented, such as variables, logical and mathematical operations, conditional structures, and loops, to motivate students to engage in challenges that promote logical thinking. This paper presents the design, implementation and evaluation of a programming teaching tool using a visual language based on flowcharts, with subsequent data collection through a questionnaire and analysis of preliminary results to evaluate the user's experience while interacting with the tool.
Software projects are affected by technical knowledge as well as the personality of the team. Such factors can reduce or increase the software quality and development speed. For successful task allocation, it is essen...
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ISBN:
(数字)9798350368833
ISBN:
(纸本)9798350368840
Software projects are affected by technical knowledge as well as the personality of the team. Such factors can reduce or increase the software quality and development speed. For successful task allocation, it is essential to consider the skills and profile of each developer, thus maximizing their productivity. In projects with large teams, task allocation can be challenging, and the help of tools can facilitate its execution. In this work, we propose an intelligent approach for allocating software development tasks suitable to the profile of developers. From the literature, we define the appropriate skills and technical profiles for a development team, and the assessment is based on the developer completing a questionnaire. We developed a recommendation system to suggest tasks to be allocated to developers, employing text processing techniques. For validation, 495 tasks were used from an actual project developing simulator software for military training. The recommended allocations were evaluated by the project developers and used to improve the system. Validations showed that the developed approach makes consistent and coherent task recommendations to developers according to the developer profile, as participants agree with the recommendation for 76% of tasks.
Penile cancer, although rare, has an increasing mortality rate in Brazil, highlighting the need for effective diagnostic methods. Artificial Intelligence (AI) in histopathological analysis can speed up and objectify d...
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Penile cancer, although rare, has an increasing mortality rate in Brazil, highlighting the need for effective diagnostic methods. Artificial Intelligence (AI) in histopathological analysis can speed up and objectify diagnosis, but designing an ideal architecture is challenging. In this study, we propose a neural architecture search (NAS) methodology for detecting penile cancer in digital histopathology images. We explored different configurations of stem blocks and the inclusion of attention mechanisms, highlighting specific preferences depending on the magnification of the images. The results showed that the NAS methodology enabled the discovery of more accurate and optimized architectures for this task, surpassing conventional models. The proposed models achieve 89.5% and 88.5% F1-Score for 40X and 100X magnification, respectively.
Vehicle-to-Everything (V2X) communication can considerably improve the efficiency and safety of autonomous driving and advanced driver-assistance systems (ADASs). However, V2X communication can be considerably degrade...
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ISBN:
(数字)9798350387414
ISBN:
(纸本)9798350387421
Vehicle-to-Everything (V2X) communication can considerably improve the efficiency and safety of autonomous driving and advanced driver-assistance systems (ADASs). However, V2X communication can be considerably degraded in the presence of cyberattacks, such as radio jamming. Traditionally, beamforming techniques can be applied to increase the signal-to-interference plus noise ratio (SINR). This paper evaluates broadband beamforming in the mmWave spectrum against radio jamming in V2X communication. The exploitation of the mm Wave spectrum in 5G-V2X communication has a natural advantage against radio jamming. First, attenuation is stronger in the mmWave spectrum in the range of 40 GHz or higher than in the traditional 5.9 GHz. Second, to generate broadband radio jamming, the radio jammer requires much more complex hardware and energy consumption. Third, by using broadband beamforming, broadband radio jamming can be considerably attenuated, limiting the degradation of the spectrum by the radio jamming. According to our numerical results, gains of close to 30 dB SINR can be achieved. We propose a broad-band beamforming technique based on the canonical polyadic decomposition via generalized eigenvalue decomposition (CPD-GEVD). The CPD-GEVD broadband beamforming outperforms state-of-the-art beamforming algorithms in most V2X scenarios presented in this paper.
Vehicle-to-Everything (V2X) communication has an essential role for enhancing safety, effi-ciency, and overall driving experience of autonomous driving. To meet the requirements of autonomous driving, V2X demands high...
Vehicle-to-Everything (V2X) communication has an essential role for enhancing safety, effi-ciency, and overall driving experience of autonomous driving. To meet the requirements of autonomous driving, V2X demands high data-rate connectivity, per-ceived zero-latency, and high reliability. These char-acteristics are inherently linked to future-generation mobile communication technologies, such as Beyond 5G (B5G) also known as 6G. However, current so-lutions for simulating 5G communications lack inte-gration between the user and control planes, making the simulation not reliable since the 5G control plane functionalities are not taken into account. In this sense, this paper proposes a first contribution towards to the platform called Beyond 5G Virtual Environment for Cy-bersecurity Testing in V2X Systems (B5GCyberTestV2X) by integrating the 5G control plane from Open5GS and UERANSIM into the Simu5G simulator. The inclusion of the control plane in 5G urban mobility simulations increases the security and reliability of the V2X commu-nication service. Therefore, in order to show the impact of the 5G control plane, we validate a simulation with a scenario in the presence of a spoofer transmitting false warning information. As shown in our simulation, the 5G control plane does not allow the connection of the spoofer into 5G network, making the cybersecurity tests of 5G-based V2X communication more realistic.
The use of private or consortium blockchains in organizations’ applications is growing. A relevant aspect of blockchains is the choice of consensus mechanism. This decision delimits which blockchain solutions are sui...
The use of private or consortium blockchains in organizations’ applications is growing. A relevant aspect of blockchains is the choice of consensus mechanism. This decision delimits which blockchain solutions are suitable for the private scenario. Once the consensus mechanism is chosen, more than one blockchain may be enabled. However, this decision making is not trivial and requires detailed experimental indicators about algorithms and blockchains performance. In this context, we provide a comprehensive performance analysis of the Raft consensus mechanism based on its implementation in Hyperledger Fabric and Ethereum blockchain solutions. We performed our experiments on an OpenStack private cloud using each blockchain developer’s default settings for virtual machines. Our findings show how the implementation of each solution can impact the application’s performance under certain conditions.
We study the impact in time and frequency domains of classical headers on quantum payloads in quantum wrapper networking. We identify and characterize in-fiber scattering processes that produce noise photons degrading...
Grid systems are large-scale platforms which consume a considerable amount of energy. Several efficient resource/power management strategies were proposed by the specialized literature. However, most of the proposed s...
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Classification algorithms have been extensively studied in many of the major scientific investigations in recent decades. Many of these algorithms are designed for supervised learning, which requires labeled instances...
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Precise measurements of chronic wound areas are very important for measuring the efficacy of different treatments, since it provides a clear picture of the chosen treatment evolution. The most used techniques still in...
Precise measurements of chronic wound areas are very important for measuring the efficacy of different treatments, since it provides a clear picture of the chosen treatment evolution. The most used techniques still in use for measuring the wound areas involve manual measuring, paper scales and/or acetate tracing, with each health professional possibly measuring the wounds in slightly different ways, specially when dealing with the wound's depth. Thus, it is common to observe inconsistent wound area estimations by different health workers on the same wounds. Moreover, the measuring process requires direct contact with the wound, increasing the contamination and infection risks, besides possibly causing discomfort for the patient. An alternative that has already been proved successful is the use of Structure from Motion (SfM) to recover three-dimensional representations of a wound's surface and estimate that area. In this work, we analyze the effectiveness of several widely used point descriptors (BRIEF, DRINK, FREAK, ORB, SIFT and SURF) in the SfM wound reconstruction task when applied to real images of realistic synthetic wounds made of latex placed on different areas of the body. The results showed that SIFT, SURF and DRINK produced better area estimates. Since the execution time is a factor, we selected DRINK as the standard descriptor for our system, since it is approximately 9.3 and 4.9 times faster than SIFT and SURF, respectively.
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