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14th IEEE Malaysia International Conference on Communication, MICC 2019

作者： Altakhayneh, Walaa A. Ismail, Mahamod Altahrawi, Mohammed A. Abufoul, Mohammed K. Universiti Kebangsaan Malaysia Department of Electrical Electronic and Systems Engineering UKM Bangi Selangor43600 Malaysia University College of Applied Science Dept. of Computer Technology and Idustrial Professions 1415 Palestine

ISBN: (纸本)9781728147376

Wireless sensor network (WSN) is one of the huge advance in wireless communication because its ability to gather a lot of information about the surrounding area that is deployed there by the use of hundreds and thousands nodes in the network. The nodes are responsible to gather and relay the data between each other to the Base Station (BS). The main issue here to be into consideration is the life time of the nodes and the number of packets that nodes are able to transfer from one node to another. This means that the energy of nodes is the parameters that should be optimized to let WSN works for a long time with efficient manner. To satisfy this, routing and clustering mechanisms should be energy aware. Because of this;chosen an efficient routing protocol with addition to a powerful technique of clustering is very important. In this paper, a Genetic Low Energy Adaptive Clustering (G-LEACH) is evaluated in 100 uniformly distributed wireless sensor networks in term of number of alive nodes, energy consumption, number of cluster heads and packets delivery to cluster heads. The election of cluster head is achieved by using genetic optimization approach which can determine the efficient and useful cluster heads. The results show that G-LEACH presents some advantages over the LEACH algorithm since the stability zone of the G-LEACH is greater than the stability zone of LEACH by 358 rounds since the first node dies after 1544 rounds in G-LEACH. That's mean;the network's lifetime lives 61.7% longer with the use of G-LEACH instead of LEACH. Meanwhile, the cluster heads are increased by 10% above LEACH when using G-LEACH. © 2019 IEEE.

关键词： Genetic algorithms

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A black-box adversarial attack strategy with adjustable sparsity and generalizability for deep image classifiers

arXiv

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arXiv 2020年

作者： Ghosh, Arka Mullick, Sankha Subhra Datta, Shounak Das, Swagatam Das, Asit Kr. Mallipeddi, Rammohan Electronics and Communication Sciences Unit Indian Statistical Institute Kolkata India Electrical and Computer Engineering Dept. Duke University United States Dept. of Computer Science & Technology Indian Institute of Engineering Science & Technology Shibpur India College of IT Engineering Kyungpook National University Korea Republic of School of Engineering & Applied Sciences Bennett University Greater Noida India

Constructing adversarial perturbations for deep neural networks is an important direction of research. Crafting image-dependent adversarial perturbations using white-box feedback has hitherto been the norm for such adversarial attacks. However, black-box attacks are much more practical for real-world applications. Universal perturbations applicable across multiple images are gaining popularity due to their innate generalizability. There have also been efforts to restrict the perturbations to a few pixels in the image. This helps to retain visual similarity with the original images making such attacks hard to detect. This paper marks an important step that combines all these directions of research. We propose the DEceit algorithm for constructing effective universal pixel-restricted perturbations using only black-box feedback from the target network. We conduct empirical investigations using the ImageNet validation set on the state-of-the-art deep neural classifiers by varying the number of pixels to be perturbed from a meager 10 pixels to as high as all pixels in the image. We find that perturbing only about 10% of the pixels in an image using DEceit achieves a commendable and highly transferable Fooling Rate while retaining the visual quality. We further demonstrate that DEceit can be successfully applied to image-dependent attacks as well. In both sets of experiments, we outperform several state-of-the-art methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Pixels

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New Types of Neutrosophic Crisp Closed Sets

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Neutrosophic Sets and Systems 2020年 36卷 176-183页

作者： AL-Nafee, Ahmed B. Smarandache, Florentin Salama, A.A. Ministry of Education Open Educational College Math Dept. Babylon Iraq Deparment of Mathematics University of New Mexico705 Gurley AVE Gallup NM87301 United States Deparment of Mathematics and Computer Science Faculty of Science Port Said University Egypt

The neutrosophic sets were known since 1999, and because of their wide applications and their great flexibility to solve the problems, we used these the concepts to define a new types of neutrosophic crisp closed sets and limit points in neutrosophic crisp topological space, namly [neutrosophic crisp Gem sets and neutrosophic crisp Turig points ] respactvely, we stady their properties in details and join it with topological concepts. Finally we used [neutrosophic crisp Gem sets and neutrosophic crisp Turig points] to introduce of topological concepts as: neutrosophic crisp closed (open) sets, neutrosophic crisp closure, neutrosophic crisp interior, neutrosophic crisp extrior and neutrosophic crisp boundary which are fundamental for further reserch on neutrosophic crisp topology and will setrengthen the foundations of theory of neutrosophic topological spaces. © 2020. Neutrosophic Sets and Systems. All Rights Reserved.

关键词： Topology

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Two-hidden-layer feedforward networks are universal approximators: A constructive approach

arXiv

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arXiv 2019年

作者： Gonzalez-Diaz, Rocio Gutiérrez-Naranjo, Miguel A. Paluzo-Hidalgo, Eduardo Dept. of Applied Mathematics i University of Seville Dept. of Computer Science and Artificial Intelligence University of Seville

It is well known that Artificial Neural Networks are universal approximators. The classical result proves that, given a continuous function on a compact set on an n-dimensional space, then there exists a one-hidden-layer feedforward network which approximates the function. Such result proves the existence, but it does not provide a method for finding it. In this paper, a constructive approach to the proof of this property is given for the case of two-hidden-layer feedforward networks. This approach is based on an approximation of continuous functions by simplicial maps. Once a triangulation of the space is given, a concrete architecture and set of weights can be obtained. The quality of the approximation depends on the refinement of the covering of the space by simplicial complexes. Copyright © 2019, The Authors. All rights reserved.

关键词： Functions

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Exploiting linearity in dynamics solvers for the design of composable robotic manipulation architectures

Exploiting linearity in dynamics solvers for the design of c...

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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Sven Schneider Herman Bruyninckx Dept. of Computer Science Bonn-Rhein-Sieg University of Applied Sciences Germany

We investigate two major limiting factors in the design and implementation of modern dynamics solvers that interfere with their full utilization in versatile, manipulation-driven robotic software architectures. The first limitation originates from the design of those solvers which aims at computational efficiency while neglecting composability. Instead, we advocate to design the solvers in such a way that they exploit linearity in the equations of motion to fully decompose the state of a kinematic chain. This enables a versatile recomposition and more flexible applications. Secondly, we have observed that most implementations follow the programming principle of information hiding. Consequently, the internal state that is used to compute motion control commands is withheld from other parts of the software architecture. We tackle this problem by following a dataflow programming paradigm and separating the software's dataflow from the control flow. Thereafter, we demonstrate those two simple, yet effective strategies to overcome the limitations along various case studies.

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Noise analysis of Dual Halo Dual Dielectric Triple Material Surrounding Gate MOSFET for RF applications 3

Noise analysis of Dual Halo Dual Dielectric Triple Material ...

引用

3rd International Conference on Devices for Integrated Circuit, DevIC 2019

作者： Kumar, Prashant Gupta, Neeraj Gupta, Rashmi Sharma, Amit Dept. of Electronics Communication Engineering J.C. Bose University of Science Technology YMCA Faridabad121006 India Dept. of Electronics Communication Engineering Amity School of Engineering Technology Amity University Haryana Gurugram122413 India Dept. of Computer Science Engineering Amity School of Engineering Technology Amity University Haryana Gurugram122413 India Dept. of Mathematics Amity School of Applied Sciences Amity University Haryana Gurugram122413 India

ISBN: (纸本)9781538667224

In this paper, the noise performance of Dual Halo Dual Dielectric Triple Material Surrounding Gate (DH-DD-TM-SG) MOSFET has been investigated. The assessment of noise performance has been carried out in terms of noise figure, noise conductance and optimum impedance. These noise metrics reveal notable cutback in noise by virtue of dual dielectric and dual halo implants in DH-DD-TM-SG MOSFET in contrast to conventional Triple Material Surrounding Gate (TM-SG) MOSFET. It is scrutinized that noise figure is shrunk by 35.7% and optimum impedance is raised by 14.49% in DH-DD-TM-SG MOSFET than its counterpart, making it a suitable device for designing of low-noise amplifiers. © 2019 IEEE.

关键词： Noise figure

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Urban Intelligence: Toward the Digital Twin of Matera and Catania

Urban Intelligence: Toward the Digital Twin of Matera and Ca...

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Blockchain for Renewables Integration (BLORIN), Workshop on

作者： Giordana Castelli Amedeo Cesta Mario Ciampi Riccardo De Benedictis Giuseppe De Pietro Matteo Diez Giovanni Felici Roberto Malvezzi Barbara Masini Riccardo Pellegrini Andreas Scalas Giuseppe Stecca Lucanos Strambini Gabriella Tognola Paolo Ravazzani Emilio Fortunato Campana Engineering ICT and Technology for Energy and Transportation Dept. (DIITET) National Research Council (CNR) Rome Italy Institute of Cognitive Sciences and Technologies (ISTC) National Research Council (CNR) Rome Italy Institute for High Performance Computing and Networking (ICAR) National Research Council (CNR) Naples Italy Institute of Marine Engineering (INM) National Research Council (CNR) Rome Italy Institute for Systems Analysis and Computer Science (IASI) National Research Council (CNR) Rome Italy Engineering ICT and Technology for Energy and National Research Council (CNR) Rome Italy Institute of Electronics Computer and Telecommunication Engineering (IEIIT) National Research Council (CNR) Bologna Italy Institute for Applied Mathematics and Information Technologies (IMATI) National Research Council (CNR) Genoa Italy Institute for Systems Analysis and Computer Science “Antonio Ruberti” (IASI) National Research Council (CNR) Rome Italy Institute of Electronics Computer and Telecommunication Engineering (IEIIT) (CNR) Pisa Italy

ISBN: (纸本)9781665472500

The Urban Intelligence (UI) paradigm conceived by CNR consists of an ecosystem of digital technologies joined within a Digital Twin (DT) of the city aimed at improving the city governance towards goals addressed also by the UN Agenda 2030, such as urban environment, sustainability and resilience, wellbeing and quality of life, local development, and social inclusion. In particular, UI provides a set of candidate policies in complex scenarios, and supports policy makers and stakeholders in designing shared, evidence-based, and integrated solutions. UI is being applied for the first time to two Italian cities, Matera and Catania, paving the way for a deeper scientific framing of the paradigm, as well as for the technological development and testing of the core UI ecosystem in real-life situations. The paper introduces the UI key-concepts and components, illustrates the ongoing experimentations in these pilot cities related to the development of two DTs on parts of the urban areas, and presents some initial results.

关键词： Renewable energy sources Urban areas Ecosystems Lakes Digital twins Sensors Stakeholders

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Retrieval of Relevant Data for Measuring the Impact of Spaced-Repetition Algorithms on the Learning Success in Mobile Learning Games

Retrieval of Relevant Data for Measuring the Impact of Space...

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IEEE International Symposium on Multimedia

作者： Florian Schimanke Robert Mertens Bettina Sophie Huck Dept. of Computer Science HSW University of Applied Sciences Hameln Germany Dept. of Business Administration HSW University of Applied Sciences Hameln Germany

ISBN: (数字)9781728156064

ISBN: (纸本)9781728156071

This paper presents an approach on how to retrieve relevant data from a huge set of game-data in order to find evidence for the impact of using spaced-repetition algorithms on the learning success in a mobile learning game. After having collected approximately 12 million sets of playing data, the database needs to be preprocessed before analyzing it in order to filter out any data that is irrelevant or useless for our analysis or may even dilute its results. One structured and established way to do this is to follow the KDD process, which includes several consecutive steps of consolidating the available data, with preprocessing it being one of them. In order to be able to define the data were are looking for, we set up some proposals about how the relevant data should look like and how to retrieve it from our database.

关键词： Game based learning Mobile learning Spaced repetition SuperMemo Kdd Data retrieval Data mining e-learning information retrieval data mining retrieval Game theory order

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On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition

arXiv

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arXiv 2020年

作者： Cerisara, Christophe Král, Pavel Lenc, Ladislav LORIA-UMR7503 Nancy France Dept. of Computer Science & Engineering Faculty of Applied Sciences University of West Bohemia Plzeň Czech Republic NTIS - New Technologies for the Information Society Faculty of Applied Sciences University of West Bohemia Plzeň Czech Republic

Dialogue act recognition is an important component of a large number of natural language processing pipelines. Many research works have been carried out in this area, but relatively few investigate deep neural networks and word embeddings. This is surprising, given that both of these techniques have proven exceptionally good in most other language-related domains. We propose in this work a new deep neural network that explores recurrent models to capture word sequences within sentences, and further study the impact of pretrained word embeddings. We validate this model on three languages: English, French and Czech. The performance of the proposed approach is consistent across these languages and it is comparable to the state-of-the-art results in English. More importantly, we confirm that deep neural networks indeed outperform a Maximum Entropy classifier, which was expected. However, and this is more surprising, we also found that standard word2vec embeddings do not seem to bring valuable information for this task and the proposed model, whatever the size of the training corpus is. We thus further analyse the resulting embeddings and conclude that a possible explanation may be related to the mismatch between the type of lexical-semantic information captured by the word2vec embeddings, and the kind of relations between words that is the most useful for the dialogue act recognition task. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

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Correction to: LiDAR-Based Climate Change Imaging in Geoscience Using Spatio Extreme Fuzzy Gradient Model

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Remote Sensing in Earth Systems sciences 2025年第2期8卷 473-473页

作者： Krushnasamy, V. S. Al-Omari, Omaia Sundaram, Ajith Varghese, Issac K. Muniyandy, Elangovan Rao, M. V. A. L. Narasimha Dept. of EIE Dayananda Sagar College of Engineering Bangalore India Information Systems Department College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Amrita School of Business Amrita Vishwa Vidyapeetham Kochi India T A Pai Management Institute Manipal Academy of Higher Education Manipal India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of MBA Koneru Lakshmaiah Education Foundation Guntur India

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