Magnetic nanofibers are of great interest for applications like data transport and storage as well as in basic research. Especially bent nanofibers, which can unambiguously be produced by electrospinning, show a broad...
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Nowadays, novel construction materials, more efficient power supplies and advanced artificial intelligence algorithms allow one to use unmanned aerial vehicles (UAV) in various fields of life. One of the biggest event...
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ISBN:
(纸本)9781479987023
Nowadays, novel construction materials, more efficient power supplies and advanced artificial intelligence algorithms allow one to use unmanned aerial vehicles (UAV) in various fields of life. One of the biggest events promoting this idea is the Air Cargo Challenge (ACC) competition. In this paper the motivation for ACC participation and the overall procedure of CAD aided UAV design are presented. The nonlinear aircraft model as well as Computational Fluid Dynamic simulations are discussed. Finally, some details concerning designed UAV prototype are revealed.
Great disasters such as earthquakes can cause large disruptions in the normal lives of people, as well as human and material losses. Therefore, risk management measures are always necessary to reduce or avoid potentia...
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The use of Natural Language Processing Algorithms (NLP) for automation purposes in various applications is frequently encountered recently. Some research managed to identify the dominant emotion from a text using neur...
The use of Natural Language Processing Algorithms (NLP) for automation purposes in various applications is frequently encountered recently. Some research managed to identify the dominant emotion from a text using neural networks (ANN), Random Forest (RF) and Support Vectors Machines (SVM) while other studies classified documents with the aim of mechanizing the extraction process of *** paper presents a study on different Natural Language Processing Algorithms (NLP) used for automation of a virtual bookstore. The objective was the application of artificial intelligence algorithms to streamline the necessary processes of an online bookstore or library, taking into consideration the short descriptions and summaries of the books. The aim is to improve the results obtained by supervised algorithms using various techniques such as aggregating unsupervised classifications. In order to boost their understanding of natural language, GPT is used to enhance the dataset by adding additional context. Finally, some of the methods utilized in improving accuracy can be used to create a personalized recommendation system that suits each reader’s needs.
The main goal of the paper is to study the equilibria of a nonlinear system, proving the existence and uniqueness of an equilibrium point in the positive ortant. We also provide numerically tractable conditions (by us...
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In pattern identification, embedded Feature Selection (FS) determines a detailed data description and an efficient and accurate classification. Most Genetic Algorithm (GA) based optimization procedures tackle the mini...
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ISBN:
(纸本)9781665409773
In pattern identification, embedded Feature Selection (FS) determines a detailed data description and an efficient and accurate classification. Most Genetic Algorithm (GA) based optimization procedures tackle the minimization of a classifier's error rate. Independent of how feature selection procedures are configured, either in Single (SOO) or Multi-Objective Optimization (MOO) manners, the major problem with all classifiers is multidimensionality and quantity of redundant and noisy data recordings. This paper compares six GA-based optimizations as viable solutions for an accurate and efficient assessment of working memory load levels during arithmetic computations based on Electroencephalogram (EEG) data. An objective layout analysis of a randomly generated population motivates both SOO and MOO further explorations. The single objective error-based optimization, the aggregation of error, and the number of selected features illustrate the limitations of SOOs. The third SOO incorporates a fuzzy rejection mechanism for unnecessary features. The baseline for MOO comparison is Deb's NSGA. Two new MOO procedures for feature selection are proposed: a MOO Fuzzy Rejection of Irrelevant Features (MOO-FRIF) and a Fuzzy Progressive Deletion of Irrelevant Features (MOO-FPDIF). Both new MOO approaches gradually eliminate or discourage the EEG features that negatively influence the classifier. Two classifiers address the problem distinctively, namely Random Forests (RF) and a multi-class Support Vector Machine (SVM) with one vs. one comparison mechanism and RBF kernel.
This paper introduces the VibroWear architecture, a solution with a modular design at both hardware and software levels, that integrates an energy-aware engine in order to increase operational autonomy. By providing m...
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ISBN:
(数字)9781665485579
ISBN:
(纸本)9781665485586
This paper introduces the VibroWear architecture, a solution with a modular design at both hardware and software levels, that integrates an energy-aware engine in order to increase operational autonomy. By providing means of defining policies regarding energy consumption at module or I/O function level, the solution aims at adjusting the operational state of the modules (i.e. full, partial or decreased I/O activity, adjustable sample rates).
Coalition formation is an important aspect of multiagent systems because it enables agents to achieve goals more efficiently or goals they cannot accomplish individually. In this paper we consider an approximate metho...
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ISBN:
(纸本)9781479907342
Coalition formation is an important aspect of multiagent systems because it enables agents to achieve goals more efficiently or goals they cannot accomplish individually. In this paper we consider an approximate method based on neural networks to estimate two important values used for dividing the payoff of a coalition, namely the Shapley value and the nucleolus. We try several neural network topologies and different training algorithms and evaluate the behavior of an especially designed multiagent system when the payoff values are computed by exact and approximate methods.
Peer review represents the status-quo when it comes to evaluating research articles that are submitted to conferences and journals. The significance of a computer science article is given by the prestige of the public...
Peer review represents the status-quo when it comes to evaluating research articles that are submitted to conferences and journals. The significance of a computer science article is given by the prestige of the publication and is correlated with the inclusion in the ISI Web of Science *** paper discusses the issues of the current paper publication paradigm and proposes a decentralized approach to the paper dissemination and the peer review processes. On the one hand, decentralization and transparency are obtained by employing smart contracts, through blockchain technology. On the other hand, an optimization of the paper rating system is obtained by employing a system of expert badges, based on NFTs, which ensure that the peer review process is just and that only specialists in the fields associated to the contributed paper offer proficient feedback. Other proposed facets include the remuneration of reviewers, a method of allowing the proposed system to expand based on the community’s input, and a solution for allowing the organization of conferences.
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