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作者： Lloret-Climent, Miguel Nescolarde-Selva, Josué Antonio Mora-Mora, Higinio Signes-Pont, María Teresa Department of Applied Mathematics University of Alicante Alicante Spain Specialized Processors Architecture Laboratory Department of Computer Technology and Computation University of Alicante Alicante Spain

Graph theory is a fundamental tool in the study of economic issues, and input–output tables are one of the main examples. We use the interpretation of the labour market through networks to obtain a better understanding on its overall functioning. One benefit of the network perspective is that a large body of mathematics exists to help analyze many forms of networks models. If an economic system has obtained a suitable model, then it becomes possible to utilize relevant mathematical tools, such as graph theory, to better understand the way the labour market works. This interpretation allows us to employ the concepts of coverage, invariance, orbit and the structural functions supply–demand and competition and interpret them from the point of view of circular flow. In this paper, we aim to interpret the labour market through networks that are represented by graphs and where characteristic concepts of chaos theory such as cover, invariance and orbits interact with the concept circular flow. Finally, an example of this approach to labour markets is described, and some conclusions are drawn. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Chaos theory

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Geographic information science in the era of geospatial big data: A cyberspace perspective

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The Innovation 2022年第5期3卷 21-22页

作者： Xintao Liu Min Chen Christophe Claramunt Michael Batty Mei-Po Kwan Ahmad MSenousi Tao Cheng Josef Strobl Arzu Cöltekin John Wilson Temenoujka Bandrova Milan Konecny Paul MTorrens Fengyuan Zhang Li He Jinfeng Wang Carlo Ratti Olaf Kolditz Alexander Klippel Songnian Li Hui Lin Guonian Lu Department of Land Surveying and Geo-Informatics Hong Kong Polytechnic UniversityHong Kong SARKowloonChina Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China The French Naval Academy Research Institute 29240 Lanveoc-PoulmicFrance The Bartlett Centre for Advanced Spatial Analysis(CASA) University College London(UCL)WC1E 6BT LondonUK Institute of Space and Earth Information Science The Chinese University of Hong KongHong Kong SARShatin 999077China Department of Civil Engineering Cairo University12613 CairoEgypt SpaceTimeLab Department of CivilEnvironmental and Geomatic EngineeringUniversity College London(UCL)WC1E 6BT LondonUK Department of Geoinformatics University of Salzburg5020 SalzburgAustria Institute of Interactive Technologies(IIT) University of Applied Sciences and Arts Northwestern Switzerland FHNW5210 WindischSwitzerland Spatial Sciences Institute University of Southern CaliforniaLos AngelesCA 90007USA Laboratory on Cartography Department of Photogrammetry and CartographyUniversity of ArchitectureCivil Engineering and Geodesy1164 SofiaBulgaria Laboratory on Geoinformatics and Cartography Department of GeographyMasaryk University61137 BrnoCeskáRepublika Computer Science and Engineering Tandon School&Center for Urban Science+ProgressNew York UniversityNew YorkNY 10012USA School of Humanities and Social Science Xi’an Jiaotong UniversityXi’an 710049China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of SciencesBeijing 100101China Department of Urban Studies and Planning Massachusetts Institute of TechnologyCambridgeMA 02139USA Centre for Environmental Research Helmholtz Centre for Environmental Research-UFZ04318 LeipzigGermany Laboratory of Geo-information Science and Remote Sensing Wageningen University&ResearchWageningen 6708the Netherlands Department of Civil Engineering Toronto Metropolitan UniversityTorontoON M5B 2K3Canada School of Geography and Env

The advent of information and communication technology and the Internet of Things have led our society toward a digital *** proliferation of personal computers,smartphones,intelligent autonomous sensors,and pervasive network interactions with individuals have gradually shifted human activities from offline to online and from in person to *** transformation has brought a series of challenges in a variety of fields,such as the dilemma of placelessness,some aspects of timelessness(no time relevance),and the changing relevance of distance in the field of geographic information science(GIScience).In the last two decades,“cyber thinking”in GIScience has received significant attention from different *** instance,human activities in“cyberspace”need to be reconsidered when coupled with the geographic space to observe the first law of geography.

关键词： computer cyber instance

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Using Convolutional Neural Networks for Muon detection in WCD tank

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Journal of Physics: Conference Series 2020年第1期1603卷

作者： B.S. González R. Conceição B. Tomé M. Pimenta L.J. Herrera A. Guillen Computer Architecture and Technology Department University of Granada Granada Spain. LIP/IST Lisbon Portugal.

The aim of this paper is to study the possibility of improving the gamma/hadron discrimination in extensive air showers. For this purpose, the identification of hadronic extensive air showers is carried out by means of the detection of muons in water Cherenkov detectors (WCDs). Machine learning algorithms have proven to be useful in a wide variety of fields, and due to their outstanding performance in problems involving complex data, Convolutional Neural Networks (CNNs) have been used in the analysis of the signals measured by the WCDs. Taking simulated events, different approaches were proposed attending to the balance of the classes in the training stage. The results obtained are promising and show that machine learning algorithms provide a powerful tool for muon detection and gamma/hadron discrimination to be considered in future gamma-rays detectors like The Southern Wide-field Gamma-ray Observatory (SWGO) to be built in South America.

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Fungal electronics

arXiv

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arXiv 2021年

作者： Adamatzky, Andrew Ayres, Phil Beasley, Alexander E. Chiolerio, Alessandro Dehshibi, Mohammad M. Gandia, Antoni Albergati, Elena Mayne, Richard Nikolaidou, Anna Roberts, Nic Tegelaar, Martin Tsompanas, Michail-Antisthenis Phillips, Neil Wösten, Han A.B. Unconventional Computing Laboratory UWE Bristol United Kingdom The Centre for Information Technology and Architecture Royal Danish Academy Copenhagen Denmark Centre for Engineering Research University of Hertfordshire United Kingdom Center for Bioinspired Soft Robotics Istituto Italiano di Tecnologia Via Morego 30 Genova10163 Italy Department of Computer Science Multimedia and Telecommunications Universitat Oberta de Catalunya Barcelona Spain Institute for Plant Molecular and Cell Biology CSIC-UPV Valencia Spain Department of Design Politecnico di Milano Milan Italy MOGU S.r.l. Inarzo Italy Microbiology Department of Biology University of Utrecht Utrecht Netherlands

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as stand alone sensing and computing devices. Copyright © 2021, The Authors. All rights reserved.

关键词： Fungi

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The Biodiversity of Flora and Fauna in the Re-vegetation Area in the Post-Mining Area of Pongkor 4

The Biodiversity of Flora and Fauna in the Re-vegetation Are...

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4th International Symposium of Sustainable Landscape Development, ISSLD 2019

作者： Kusumoarto, A. Gunawan, A. Machfud Hikmat, A. Natural Resource and Environmental Management Science School of Post-Graduate IPB University Jl. Raya Pajajaran Bogor16143 Indonesia Faculty of Technic and Computer Science Indraprasta PGRI University Jl. Raya Nangka No. 58C RT.5/RW.5 Tanjung Barat Kota Jakarta Selatan Daerah Khusus Ibukota Jakarta12530 Indonesia Landscape Architecture Department IPB University Jl. Raya Darmaga Bogor16680 Indonesia AgroIndustrial Technology Department IPB University Jl.Raya Darmaga Bogor16680 Indonesia Conservation of Forest and Ecotourism Department IPB University Jl. Raya Darmaga Bogor16680 Indonesia

The Pongkor post-mining area is designated as one of the ecotourism areas in Bogor. This area has biodiversity of flora and fauna. This study aims to: (1) analysis the importance value index (IVI) of flora types;(2) analysis species richness index, species diversity index, and relative species abundance index;(3) analysis the beauty, the uniqueness and the rarity of the flora and fauna types. The method used in this research is quantitative descriptive. Based on the identification results, 185 species of flora are distributed in this region. During the rainy season, 15 species of herpetofauna were identified, 32 types of aves, and 4 types of mammals, while in the dry season 19 species of herpetofauna were identified, 23 types of aves, and 2 types of mammals. Based on the results of the analysis conducted on these flora and fauna, there are flora species that have high IVI values and some beautiful and unique flora species that are in the category of endangered species. Besides that, there are also fauna species which have a value of species richness index, species diversity index, and relative species abundance index, as well as some beautiful, unique, and fauna species that are in the category of endangered species. © Published under licence by IOP Publishing Ltd.

关键词： Biodiversity

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Reinforcement learning for channel coding: learned bit-flipping decoding

arXiv

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arXiv 2019年

作者： Carpi, Fabrizio Häger, Christian Martalò, Marco Raheli, Riccardo Pfister, Henry D. Department of Electrical and Computer Engineering New York University BrooklynNY United States Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Department of Engineering and Architecture University of Parma Parma Italy Department of Electrical and Computer Engineering Duke University DurhamNC United States

In this paper, we use reinforcement learning to find effective decoding strategies for binary linear codes. We start by reviewing several iterative decoding algorithms that involve a decision-making process at each step, including bit-flipping (BF) decoding, residual belief propagation, and anchor decoding. We then illustrate how such algorithms can be mapped to Markov decision processes allowing for data-driven learning of optimal decision strategies, rather than basing decisions on heuristics or intuition. As a case study, we consider BF decoding for both the binary symmetric and additive white Gaussian noise channel. Our results show that learned BF decoders can offer a range of performance–complexity trade-offs for the considered Reed–Muller and BCH codes, and achieve near-optimal performance in some cases. We also demonstrate learning convergence speed-ups when biasing the learning process towards correct decoding decisions, as opposed to relying only on random explorations and past knowledge. Copyright © 2019, The Authors. All rights reserved.

关键词： White noise

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Advanced forest fire risk mapping: Combining Sentinel-2 MSI data with hybrid machine learning in Similipal Biosphere Reserve

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Forest Ecology and Management 2025年 594卷

作者： Bilel Zerouali Celso Augusto Guimarães Santos Saleh Qaysi Richarde Marques da Silva Nassir Alarifi Nadjem Bailek Manoranjan Mishra Paolo Porto Youssef M. Youssef Laboratory of Architecture Cities and Environment Faculty of Civil Engineering and Architecture Department of Hydraulic Hassiba Benbouali University of Chlef B.P. 78C Ouled Fares 02180 Algeria Department of Civil and Environmental Engineering Federal University of Paraíba João Pessoa Paraíba 58051-900 Brazil Department of Geology & Geophysics College of Science King Saud University PO Box 2455 Riyadh 11451 Saudi Arabia Department of Geosciences Federal University of Paraíba João Pessoa Paraíba 58051-900 Brazil Laboratory of Mathematics Modeling and Applications Department of Mathematics and Computer Science Faculty of Sciences and Technology Ahmed Draia University of Adrar Adrar 01000 Algeria Department of Geography Fakir Mohan University Vyasa Vihar Nuapadhi Balasore Odisha 756089 India Dipartimento di Agraria University Mediterranea of Reggio Calabria Reggio Calabria 89122 Italy Geological and Geophysical Engineering Department Faculty of Petroleum and Mining Engineering Suez University Suez 43518 Egypt

Forests are among the most complex and invaluable ecosystems on Earth. This study applies machine learning (ML) models to predict forest fire probability in the Similipal Biosphere Reserve (India) using Sentinel-2 Multi-Spectral Instrument (MSI) data. The differenced Normalized Burn Ratio (dNBR ≥ 0.1) was used to identify burned areas, generating a dataset of 2000 points (1000 fire, 1000 non-fire) from ArcGIS tools and field surveys. The dataset was split into training (70 %) and testing (30 %) subsets to assess stacked hybrid ML models, including Random Forest (RF), RF-XGBoost, RF-LightGBM, RF-HGB, and RF-HGB-AdaBoost. Among these models, RF-HGB achieved the highest accuracy (0.75) and area under the curve (AUC) score (0.94) but had a high computational cost (427.28 s). RF-HGB-AdaBoost matched the AUC score (0.94) but had slightly lower accuracy (0.74) and the longest runtime (560.52 s). RF-XGBoost and RF-LightGBM provided a balance between performance and efficiency, with accuracies of 0.74 and 0.73, AUC scores of 0.94, and runtimes of 211.46 and 301.64 s, respectively. RF had the shortest runtime (152.63 s) but the lowest accuracy (0.629). Fire susceptibility mapping revealed that RF-HGB-AdaBoost classified the largest area (16.60 %, 924 km²) as High to Very High risk, followed by RF-XGBoost (16.26 %, 906 km²) and RF-LightGBM (15.95 %, 888 km²). Both RF-LightGBM and RF-XGBoost emphasized Moderate to High risk zones, covering 39.63 % and 39.13 % of the area, respectively. Rainfall was identified as the most influential factor using Gini feature importance. RF-HGB and RF-XGBoost, offering a balance between accuracy and computational efficiency, are recommended for strategic planning and real-time fire management. The findings provide critical insights for sustainable forest management and wildfire mitigation, supporting SDGs 13 and 15.

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Learned belief-propagation decoding with simple scaling and SNR adaptation

arXiv

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arXiv 2019年

作者： Lian, Mengke Carpi, Fabrizio Häger, Christian Pfister, Henry D. Department of Electrical and Computer Engineering Duke University DurhamNC United States Department of Engineering and Architecture University of Parma Parma Italy Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden

We consider the weighted belief-propagation (WBP) decoder recently proposed by Nachmani et al. where different weights are introduced for each Tanner graph edge and optimized using machine learning techniques. Our focus is on simple-scaling models that use the same weights across certain edges to reduce the storage and computational burden. The main contribution is to show that simple scaling with few parameters often achieves the same gain as the full parameterization. Moreover, several training improvements for WBP are proposed. For example, it is shown that minimizing average binary cross-entropy is suboptimal in general in terms of bit error rate (BER) and a new "soft-BER" loss is proposed which can lead to better performance. We also investigate parameter adapter networks (PANs) that learn the relation between the signal-to-noise ratio and the WBP parameters. As an example, for the (32, 16) Reed-Muller code with a highly redundant parity-check matrix, training a PAN with soft-BER loss gives near-maximum-likelihood performance assuming simple scaling with only three parameters. Copyright © 2019, The Authors. All rights reserved.

关键词： Belief propagation

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Dual-Band FSS Director using Inverted Interdigital Structure for LTE and WLAN

Dual-Band FSS Director using Inverted Interdigital Structure...

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International Symposium on Antennas and Propagation (ISAP)

作者： P. Chomtong T. Archevapanich P. Akkaraekthalin Department of Teacher Training in Electrical Engineering Rajamangala University of Technology Nonthaburi Thailand Faculty of Engineering and Architecture Rajamangala University of Technology Nonthaburi Thailand Department of Electrical and Computer Engineering King Mongkut’s University of Technology North Bangkok Thailand

This paper proposes a design of dual band FSS director using inverted interdigital technique on a microwave printed circuit board to achieve resonance frequencies at 1.8 GHz for LTE and 5.2 GHz for WLAN. Form the design method, the unit cell size can be reduced from λ/2 to λ/8 compared with the conventional structure caused by the slow wave effect in its structure. The FSS layer was formed by connecting 8×8 designed unit cells to be an array. The FSS layer acts as a director for dipole antennas at the frequencies of 1.8 GHz and 5.2 GHz. The simulation results show that the dipole antenna with the proposed FSS director has higher performances. The antenna gains were obviously improved with the gains of 2.61 dB at 1.8 GHz and 3.97 dB at 5.2 GHz higher than the conventional dipole antenna, which normally has a gain of about 2 dB. This proposed FSS structure can also be applied for other multiband antenna systems.

关键词： Frequency selective surfaces Dipole antennas Resonant frequency Gain Band-pass filters Directive antennas Wireless LAN

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Demo abstract: Towards IoT service deployments on edge community network microclouds

Demo abstract: Towards IoT service deployments on edge commu...

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2018 IEEE Conference on computer Communications Workshops, INFOCOM 2018

作者： Khan, Amin M. Freitag, Felix Vlassov, Vladimir Ha, Phuong Hoai Department of Computer Science UiT the Arctic University of Norway Tromsø Norway Department of Computer Architecture Universitat Politècnica de Catalunya Barcelona Spain KTH Royal Institute of Technology Stockholm Sweden Hitachi Vantara Corporation Lisbon Portugal

ISBN: (纸本)9781538659793

Internet of Things (IoT) services for personal devices and smart homes provided by commercial solutions are typically proprietary and closed. These services provide little control to the end users, for instance to take ownership of their data and enabling services, which hinders these solutions' wider acceptance. In this demo paper, we argue for an approach to deploy professional IoT services on user-controlled infrastructure at the network edge. The users would benefit from the ability to choose the most suitable service from different IoT service offerings, like the one which satisfies their privacy requirements, and third-party service providers could offer more tailored IoT services at customer premises. We conduct the demonstration on microclouds, which have been built with the Cloudy platform in the *** community network. The demonstration is conducted from the perspective of end users, who wish to deploy professional IoT data management and analytics services in volunteer microclouds. © 2018 IEEE.

关键词： Internet of things

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