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computer Vision and Fuzzy Logic for Sustainable Indonesian Fisheries

IOP Conference Series: Earth and Environmental Science 2020年第1期426卷

作者： Suryadiputra Liawatimena Wiedjaja Atmadja Bahtiar Saleh Abbas Agung Trisetyarso Antoni Wibowo Erland Barlian Lilik Tri Hardanto Adi Saputra Putri Sakinah Hery Purwoko Indra Zulardi Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Doctor Computer Science Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Management Department BINUS Business School - Doctor of Research in Management Bina Nusantara University Jakarta Indonesia 11480

Tuna fishing in Indonesia is excessive and if left unchecked, some types of tuna will become extinct within 3-10 years. There is an urgent need to help MMAF for producing more accurate fish catches data. This paper proposed a system that utilizes computer vision, fuzzy logic and Global Positioning System (GPS) for supporting a sustainableIndonesian fishery by recognizing and measuring fish length, determine fish age and where is the catch location. The system can help authority to manage sustainable fisheries management in Indonesia.

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Drones computer Vision using Deep Learning to Support Fishing Management in Indonesia

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IOP Conference Series: Earth and Environmental Science 2020年第1期426卷

作者： Suryadiputra Liawatimena Wiedjaja Atmadja Bahtiar Saleh Abbas Agung Trisetyarso Antoni Wibowo Erland Barlian Lilik Tri Hardanto Natassya Afdalena Triany Faisal Jaka Sulistiawan Albert Cahya Yojana Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Doctor Computer Science Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Management Department BINUS Business School - Doctor of Research in Management Bina Nusantara University Jakarta Indonesia 11480

It is necessary to study technical factors such as bait used, oceanographic conditions of fishing areas and skipjack tuna trade patterns (Katsuwonus pelamis) as well as other factors in Sulawesi Fisheries. Supporting data to study these technical factors need to be obtained so that it can be improved throughout the year as a skipjack fishing standard with weights taken by the skipjack weights. Therefore, drones and underwater drones with cameras with high-resolution video and images to be fed and processed by computer vision. These drones are operated via Huhate ships which are then used to test efficient technical factors as expected, can be used in determining the size, shape, and colour as well as the analysis of skipjack fish that are in the Fish Aggregating Devices (FADs or Rumpon) in order to manage the management of fisheries managed in Indonesia.

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The study of using big data analysis to detecting APT attack

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Journal of computers (Taiwan) 2019年第1期30卷 206-222页

作者： Liu, Chung-Hsin Chen, Wei-Hung Department of Information Engineering and Computer Science Chinese Culture University Taipei111 Taiwan Graduate Institute of R and D Master Program in Information Security Industry Chinese Culture University Taipei106 Taiwan

An advanced persistent threat (APT) is a deliberately slow-moving cyberattack that is applied to quietly compromise interconnected information systems without revealing itself. APTs often use a variety of attack methods to get unauthorized system access initially and then gradually spread throughout the network. In contrast to traditional attacks, they are not used to interrupt services but primarily to steal intellectual property, sensitive internal business and legal documents and other data. Once an attack is successful, then the system timely detection is of paramount importance to mitigate its impact and will prohibit APTs from further spreading. For the early detection APT threat, this study proposes a detection mechanism, using Big Data and Splunk analysis, then using data mining techniques to find malicious IP position. Through the experimental results, decision tree algorithm is used as the best prediction model, and in the predictive model, the detection rate increased to 99%. Finally, this study established an alert system, can achieve real-time threat detection APT effect. 2019 © computer Society of the Republic of China. All Rights Reserved.

关键词： Big data

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Electrically driven programmable phase-change meta-switch reaching 80% efficiency

arXiv

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arXiv 2021年

作者： Abdollahramezani, Sajjad Hemmatyar, Omid Taghinejad, Mohammad Taghinejad, Hossein Krasnok, Alex Eftekhar, Ali A. Teichrib, Christian Deshmukh, Sanchit El-Sayed, Mostafa Pop, Eric Wuttig, Matthias Alù, Andrea Cai, Wenshan Adibi, Ali School of Electrical and Computer Engineering Georgia Institute of Technology 778 Atlantic Drive NW AtlantaGA30332-0250 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical Engineering Precourt Institute for Energy Stanford University StanfordCA94305 United States Laser Dynamics Laboratory School of Chemistry and Biochemistry Georgia Institute of Technology AtlantaGA30332-0400 United States George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332-0405 United States Physikalisches Institut IA RWTH Aachen Sommerfeldstrasse 14 Aachen52074 Germany Physics Program Graduate Center City University of New York New YorkNY10016 United States School of Materials Science and Engineering Georgia Institute of Technology 801 Ferst Drive NW AtlantaGA30332-0295 United States

Despite recent advances in active metaoptics, efficient wide dynamic range combined with highspeed reconfigurable solutions is still elusive. Phase-change materials (PCMs) offer a compelling platform for metasurface optical elements, owing to the large index contrast and fast yet stable phase transition properties. Here, we experimentally demonstrate an in situ electrically driven reprogrammable metasurface by harnessing the unique properties of a phase-change chalcogenide alloy, Ge2Sb2Te5 (GST), in order to realize non-volatile, reversible, multilevel, fast, and pronounced optical modulation in the near-infrared spectral range. Co-optimized through a multiphysics analysis, we integrate an efficient heterostructure resistive microheater that indirectly heats and transforms the embedded GST film without compromising the optical performance of the metasurface even after several reversible phase transitions. A hybrid plasmonic-PCM meta-switch with a record eleven-fold change in the reectance (an absolute reectance contrast reaching 80%), unprecedented quasi-continuous spectral tuning over 250 nm, and operation speed that can potentially reach a few kHz is presented. Our work represents a significant step towards the development of fully integrable dynamic metasurfaces and their potential for beamforming applications. © 2021, CC BY.

关键词： Phase change materials

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Two-dimensional pentagonal material Penta-PdPSe: A first-principle study

arXiv

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arXiv 2021年

作者： Bafekry, Asadolah Fadlallah, M.M. Faraji, M. Shafique, A. Jappor, H.R. Abdolhoseini Sarsari, I. Ang, Yee Sin Ghergherehchi, M. Department of Radiation Application Shahid Beheshti University Tehran*** Iran Department of Physics Faculty of Science Benha University Benha13518 Egypt Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Department of Physics Lahore University of Management Sciences Lahore Pakistan Department of Physics College of Education for Pure Sciences University of Babylon Hilla Iraq Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Cluster Singapore University of Technology and Design Singapore487372 Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Low-symmetry Penta-PdPSe with intrinsic in-plane anisotropy synthesized successfully [P. Li et al., Adv. Mater., 2102541 (2021)]. Motivated by this experimental discovery, we investigate the structural, mechanical, electronic, optical and thermoelectric properties of PdPSe monolayer via density functional theory calculations. The phonon dispersion, molecular dynamics simulation, the cohesive energy mechanical properties of the penta-PdPSe monolayer is verified to confirm its stability. The phonon spectrum represents a striking gap between the high-frequency and the low-frequency optical branches and an out-of-plane flexure mode with a quadratic dispersion in the long-wavelength limit. The Poisson’s ratio indicates that penta-PdPSe is a brittle monolayer. The pendaPdPSe monolayer is an indirect semiconductor with bandgap of 1.40 (2.07) eV using PBE (HSE06) functional. Optical properties simulation suggests that PdPSe is capable of absorbing a substantial range of visible to ultraviolet light. Band alignment analysis also reveals the compatibility of PdPSe for water splitting photocatalysis application. By combining the electrical and thermal transport properties of PdPSe, we show that a high PF is achievable at room temperature, thus making PdPSe a candidate material for thermoelectric application. Our findings reveal the strong potential of penta-PdPSe monolayer for a wide array of applications, including optoelectronic, water splitting and thermoelectric device applications. © 2021, CC BY.

关键词： Monolayers

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Fast HEVC Transrating using Random Forests

Fast HEVC Transrating using Random Forests

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IEEE Visual Communications and Image Processing (VCIP)

作者： Mateus Grellert Tiago Oliveira Carlos Rafael Duarte Luis A. da Silva Cruz Graduate Program in Electronic and Computer Engineering Catholic University of Pelotas Brazil

ISBN: (纸本)9781538644591;9781538644584

This article describes a fast transrating solution for HEVC based on classification and machine learning techniques. Two classifiers are trained to predict the range of CTU quadtree depths that will be searched to find the best CTU partitioning. Three approaches are proposed for reducing the number of features used by the classifiers, two based on feature selection, and one based on feature transformation using autoencoders. A full transrating framework based on x265 is built for model training and evaluation. Experimental results using the x265 encoder show that an average 41.81% computational complexity reduction can be achieved at the cost of a tolerable 0.29% Bjontegaard-Delta bitrate, outperforming competing methods.

关键词： Feature extraction Training Bit rate Streaming media Transcoding Upper bound

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Back propagation neural network experiment on team matchmaking MOBA game 1

Back propagation neural network experiment on team matchmaki...

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1st International Conference on Information and Communications Technology, ICOIACT 2018

作者： Tanuar, Evawaty Abbas, Bahtiar Saleh Trisetyarso, Agung Kang, Chul-Ho Gaol, Ford Lumban Suparta, Wayan Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Electrical Engineering Sanata Dharma University Yogyakarta55282 Indonesia

ISBN: (纸本)9781538609545

Backpropagation is one of the famous method for learning, Implementing Backpropagation techniques in games is part of AI in game. This paper aim to analyzed the best team composition in a Moba Game type in learning using neural network. Mobile Legend: Bang Bang is one of MOBA game for mobile phone. In this experiment, the 2 hidden layers back-propagation neural network algorithm is used to analyze the Mobile Legend game. 5000 training steps was done to reach the stability. This also a way of learning to find the best composition in a team played. Research in area AI and game is very wide and open, a huge opportunity to be explore in future. The objective of this research is to produce the good combination of team which can be resulted in a greater winning chance. © 2018 IEEE.

关键词： Backpropagation

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Microchip-Based Structure Determination of Small Proteins Using Cryo-EM

SSRN

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SSRN 2020年

作者： Casasanta, Michael A. Jonaid, G.M. Kaylor, Liam Luqiu, William Y. Solares, Maria J. Schroen, Mariah L. Dearnaley, William J. Wilson, Jarad Dukes, Madeline J. Kelly, Deborah F. Department of Biomedical Engineering Pennsylvania State University University ParkPA16802 United States Materials Research Institute Pennsylvania State University University ParkPA16802 United States Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University ParkPA16802 United States Molecular Cellular and Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University ParkPA16802 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States RayBiotech Life Peachtree CornersGA30092 United States Applications Science Protochips Inc MorrisvilleNC27560 United States

Interest in cryo-Electron Microscopy (EM) imaging has skyrocketed in recent years due to its pristine views of macromolecules and materials. As advances in instrumentation and computing algorithms spurred this progress, there is renewed focus to address specimen-related challenges. Here we contribute a microchip-based toolkit to perform complementary structural and biochemical analysis on low molecular-weight proteins. As a model system, we used the SARS-CoV-2 nucleocapsid (N) protein (48 kDa) due to its stability and important role in therapeutic development. Cryo-EM structures of the N protein monomer revealed a flexible N-terminal “top hat” motif and a helical-rich C-terminal domain. To complement our structural findings, we engineered microchip-based immunoprecipitation assays that led to the discovery of the first antibody binding site on the N protein. The data also facilitated molecular modeling of a variety of pandemic and common cold-related coronavirus proteins. Such insights may guide future pandemic-preparedness protocols through immuno-engineering strategies to mitigate viral outbreaks. © 2020, The Authors. All rights reserved.

关键词： Proteins

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Reconfigurable Hyperbolic Polaritonics with Correlated Oxide Metasurfaces

Research Square

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Research Square 2021年

作者： Aghamiri, Neda Alsadat Hu, Guangwei Fali, Alireza Zhang, Zhen Li, Jiahan Balendhran, Sivacarendran Walia, Sumeet Sriram, Sharath Edgar, James H. Ramanathan, Shriram Alù, Andrea Abate, Yohannes Department of Physics and Astronomy University of Georgia AthensGA30602 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical and Computer Engineering National University of Singapore Kent Ridge Singapore117583 Singapore School of Materials Engineering Purdue University West LafayetteIN47907 United States Tim Taylor Department of Chemical Engineering Kansas State University ManhattanKN 66506 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia School of Engineering RMIT University MelbourneVIC Australia Functional Materials and Microsystems Research Group Micro Nano Research Facility RMIT University MelbourneVIC Australia ARC Centre of Excellence for Transformative Meta-Optical Systems RMIT University MelbourneVIC Australia Physics Program Graduate Center City University of New York New YorkNY10016 United States

Polaritons enable subwavelength confinement and highly anisotropic flows of light over a wide spectral range, holding the promise for applications in modern nanophotonic and optoelectronic devices. However, to fully realize their practical application potential, facile methods enabling nanoscale active control of polaritons are needed. Here, we introduce a hybrid polaritonic-oxide heterostructure platform consisting of van der Waals crystals, such as hexagonal boron nitride (hBN) or alpha-phase molybdenum trioxide (α-MoO3), transferred on nanoscale oxygen vacancy patterns on the surface of prototypical correlated perovskite oxide SmNiO3 (SNO). Using a combination of scanning probe microscopy and infrared nanoimaging techniques, we demonstrate nanoscale real-time reconfigurability of complex hyperbolic phonon polaritons patterned at the nanoscale with unmatched resolution. Hydrogenation and temperature modulation allow spatially localized conductivity modulation of SNO nanoscale patterns, enabling robust real-time modulation and nanoscale reconfiguration of hyperbolic polaritons. Our work paves the way towards nanoscale programmable metasurface engineering as a new paradigm for reconfigurable nanophotonic applications facilitated by a hybrid material platform exploiting extreme light-matter interactions in polaritonic systems. © 2021, CC BY.

关键词： Polariton

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Deep learning for classification and severity estimation of coffee leaf biotic stress

arXiv

引用

arXiv 2019年

作者： Esgario, José G. M. Krohling, Renato A. Ventura, José A. Federal University of Espìrito Santo Brazil PPGI - Graduate Program in Computer Science Production Engineering Department Incaper Rua Afonso Sarlo 160 Bento Ferreira Vitòria ES29052-010 Brazil

Biotic stress consists of damage to plants through other living organisms. Efficient control of biotic agents such as pests and pathogens (viruses, fungi, bacteria, etc.) is closely related to the concept of agricultural sustainability. Agricultural sustainability promotes the development of new technologies that allow the reduction of environmental impacts, greater accessibility to farmers and, consequently, increase on productivity. The use of computer vision with deep learning methods allows the early and correct identification of the stress-causing agent. So, corrective measures can be applied as soon as possible to mitigate the problem. The objective of this work is to design an effective and practical system capable of identifying and estimating the stress severity caused by biotic agents on coffee leaves. The proposed approach consists of a multi-task system based on convolutional neural networks. In addition, we have explored the use of data augmentation techniques to make the system more robust and accurate. The experimental results obtained for classification as well as for severity estimation indicate that the proposed system might be a suitable tool to assist both experts and farmers in the identification and quantification of biotic stresses in coffee plantations. Copyright © 2019, The Authors. All rights reserved.

关键词： Agriculture

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