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Kazuki Koga and Kazuhiro Takemoto
Universal adversarial attacks, which hinder most deep neural network (DNN) tasks using only a single perturbation called universal adversarial perturbation (UAP), are a realistic security threat to the practical application of a DNN for medical imaging. ...
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Mario Andrés Muñoz and Michael Kirley
In this paper, we investigate how systemic errors due to random sampling impact on automated algorithm selection for bound-constrained, single-objective, continuous black-box optimization. We construct a machine learning-based algorithm selector, which u...
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Amy Vennos, Kiernan George and Alan Michaels
This paper explores the security of a single-stage residue number system (RNS) pseudorandom number generator (PRNG), which has previously been shown to provide extremely high-quality outputs when evaluated through available RNG statistical test suites or...
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Raz Lapid, Zvika Haramaty and Moshe Sipper
Deep neural networks (DNNs) are sensitive to adversarial data in a variety of scenarios, including the black-box scenario, where the attacker is only allowed to query the trained model and receive an output. Existing black-box methods for creating advers...
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Ryan Dieter Lang and Andries Petrus Engelbrecht
The choice of which objective functions, or benchmark problems, should be used to test an optimization algorithm is a crucial part of the algorithm selection framework. Benchmark suites that are often used in the literature have been shown to exhibit poo...
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Eko Supraptono, Arief Arfriandi, Sulus Ilhamti Rizqian
Pág. 46 - 56
Tourism is one of the methods to publish the beauty of nature or the uniqueness of culture in a region that spreads from the coast up to the mountains. The distribution and the access to tourist attractions require mobile application. In creating the app...
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Adel Younis and Zuomin Dong
The employment of conventional optimization procedures that must be repeatedly invoked during the optimization process in real-world engineering applications is hindered despite significant gains in computing power by computationally expensive models. As...
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Carlos Alejandro Perez Garcia, Marco Bovo, Daniele Torreggiani, Patrizia Tassinari and Stefano Benni
The escalating global population and climate change necessitate sustainable livestock production methods to meet rising food demand. Precision Livestock Farming (PLF) integrates information and communication technologies (ICT) to improve farming efficien...
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Alexey Vakhnin and Evgenii Sopov
Many modern real-valued optimization tasks use ?black-box? (BB) models for evaluating objective functions and they are high-dimensional and constrained. Using common classifications, we can identify them as constrained large-scale global optimization (cL...
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Alessandro Massaro
In the proposed paper, an artificial neural network (ANN) algorithm is applied to predict the electronic circuit outputs of voltage signals in Industry 4.0/5.0 scenarios. This approach is suitable to predict possible uncorrected behavior of control circu...
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Juan F. Gomez, Antonio R. Uguina, Javier Panadero and Angel A. Juan
The capacitated dispersion problem, which is a variant of the maximum diversity problem, aims to determine a set of elements within a network. These elements could symbolize, for instance, facilities in a supply chain or transmission nodes in a telecommu...
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Zi-Lu Ouyang, Zao-Jian Zou and Lu Zou
This paper aims to study the nonparametric modeling and control of ship steering motion. Firstly, the black box response model is derived based on the Nomoto model. Then, the establishment of a nonparametric response model and prediction of ship steering...
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Abel Garcia-Barrientos, David Torres-Uresti, Francisco R. Castillo-Soria, Ulises Pineda-Rico, Jose Antonio Hoyo-Montaño, Obed Perez-Cortes and Patricio Ordaz-Oliver
The design and implementation of a car?s black box system using a Raspberry Pi microcomputer and an Internet of things module is presented in this research. This system was built using a Raspberry Pi microcomputer and different sensors, including a GPS, ...
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Andreas Maniatopoulos, Paraskevi Alvanaki and Nikolaos Mitianoudis
The recent boom of artificial Neural Networks (NN) has shown that NN can provide viable solutions to a variety of problems. However, their complexity and the lack of efficient interpretation of NN architectures (commonly considered black box techniques) ...
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Ryan Feng, Yu Yao and Ella Atkins
Autonomous vehicles require fleet-wide data collection for continuous algorithm development and validation. The smart black box (SBB) intelligent event data recorder has been proposed as a system for prioritized high-bandwidth data capture. This paper ex...
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Ping Dong, Jianhua Cheng and Liqiang Liu
In this paper, a novel anti-jamming technique based on black box variational inference for INS/GNSS integration with time-varying measurement noise covariance matrices is presented. We proved that the time-varying measurement noise is more similar to the...
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Renato Bruni, Gianpiero Bianchi and Pasquale Papa
User requests to a customer service, also known as tickets, are essentially short texts in natural language. They should be grouped by topic to be answered efficiently. The effectiveness increases if this semantic categorization becomes automatic. We pur...
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Anna Feleki, Ioannis D. Apostolopoulos, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Nikolaos Papathanasiou, Dimitrios Apostolopoulos and Nikolaos Papandrianos
Myocardial Perfusion Imaging (MPI) has played a central role in the non-invasive identification of patients with Coronary Artery Disease (CAD). Clinical factors, such as recurrent diseases, predisposing factors, and diagnostic tests, also play a vital ro...
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Guglielmo Daddi, Nicolaus Notaristefano, Fabrizio Stesina and Sabrina Corpino
This work considers global path planning enabled by generative adversarial networks (GANs) on a 2D grid world. These networks can learn statistical relationships between obstacles, goals, states, and paths. Given a previously unseen combination of obstac...
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Muhammad Rifqi Maarif, R. Faiz Listyanda, Yong-Shin Kang and Muhammad Syafrudin
The analysis of influential machine parameters can be useful to plan and design a plastic injection molding process. However, current research in parameter analysis is mostly based on computer-aided engineering (CAE) or simulation which have been demonst...
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