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2nd International Congress on High-Performance Computing and Big Data Analysis, TopHPC 2019

作者： Yang, Gijoo Jin, Jeonggeun Kim, Dongho Joo, Hae-Jong Department of Information and Communication Engineering Dongguk University Seoul Korea Republic of Convergence Software Institute Dongguk University Seoul Korea Republic of Department of Computer Science and Engineering Dongguk University Seoul Korea Republic of

ISBN: (纸本)9783030334949

Developing chatbots that can recognize the emotions of users is a challenging problem of artificial intelligence. In order to build such a system, we need to define the emotion taxonomy to cover human-like feelings. Consequently, we need to prepare a large scale training data by using the defined emotion taxonomy. In this paper, we investigate methods of representing emotions and applying them in a deep neural network model that classifies the user’s emotion into many dimensions. We also take into account auditory signals of spoken language in addition to contextual information for classifying the emotions of users. Furthermore, we tackle the compositional negation of utterances which may cause misinterpretation of the emotion in the opposite direction. Our experiment shows that our model improves the performance of baseline models significantly. © 2019, Springer Nature Switzerland AG.

关键词： Taxonomies

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Vehicle to Everything (V2X) Communication Protocol by Using Vehicular AD-HOC Network

Vehicle to Everything (V2X) Communication Protocol by Using ...

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International Conference on Wavelet Active Media Technology and information Processing (ICWAMTIP)

作者： Muhammad Ahtsam Naeem Xiaolin Jia Muhammad Asim Saleem Wasif Akbar Afzaal Hussain Shahbaz Nazir Khwaja Mutahir Ahmad School of Computer Science and Technology Southwest University of Sciences and Technology China School of Information and Software Engineering University of Electronic Sciences and Technology of China (UESTC) School of Computer Science and Engineering University of Electronic Sciences and Technology of China (UESTC) Government College University Faisalabad Pakistan

ISBN: (数字)9781665405058

ISBN: (纸本)9781665405065

Incidents among road vehicles happen raised measures of wounds, passing rates, and vital cash related losses. Vehicle to everything updates road prosperity, traffic stream, Traffic adequacy, roadway security, and communication unflinching quality or decreases traffic blocking which impacts transportation. Vehicular Ad-hoc networks is a huge thought from the investigation organize and the vehicle business to improve the organizations of cooperate intelligent transportation system. The potential results of vehicle-to-vehicle, vehicle-to-structure, vehicle to cloud, vehicle to house, vehicle to network, vehicle to pedestrian correspondence showing, and PC entertainment will be shown. A quick generation of vehicular Ad-hoc masterminds is continuously required. In any case, this is nothing yet hard to achieve in light of the way that road traffic and framework correspondence test frameworks are amazing and normally creamer structures are required. One such a mutt approach, Vehicles in Network Simulation (Veins), melds the by and large used Simulation of Urban Mobility and the renowned discrete event multiplication state of Objective Modular Network Testbed in C++ (OMNET++).

关键词： Vehicle-to-everything Sensors Vehicular ad hoc networks Veins Magnetic sensors Computational modeling Protocols

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Full-blind delegating private quantum computation

arXiv

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arXiv 2020年

作者： Liu, Wen-Jie Chen, Zhen-Yu Liu, Jin-Suo Su, Zhao-Feng Chi, Lian-Hua Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China State Grid Electric Power Research Institute NARI Group Corporation Nanjing210003 China Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia Department of Computer Science and Information Technology La Trobe University VIC3086 Australia

The delegating private quantum computation (DQC) protocol with the universal quantum gate set {X, Z, H, P, R, CNOT} was firstly proposed by Broadbent et al., and then Tan et al. tried to put forward an half-blind DQC protocol (HDQC) with another universal set {H, P, CNOT, T}. However, the decryption circuit of Toffoli gate (i.e., T) is a little redundant, and Tan et al.'s protocol exists the information leak. In addition, both of these two protocols just focus on the blindness of data (i.e., the client's input and output), but do not consider the blindness of computation (i.e., the delegated quantum operation). For solving these problems, we propose a full-blind DQC protocol (FDQC) with quantum gate set {H, P, CNOT, T}, where the desirable delegated quantum operation, one of {H, P, CNOT, T}, is replaced by a fixed sequence (H, P, CZ, CNOT, T ) to make the computation blind, and the decryption circuit of Toffoli gate is also optimized. Analysis shows that our protocol can not only correctly perform any delegated quantum computation, but also holds the characteristics of data blindness and computation blindness. Copyright © 2020, The Authors. All rights reserved.

关键词： Eye protection

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Correction to: Feature selection via uncorrelated discriminant sparse regression for multimedia analysis

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Multimedia Tools and Applications 2022年第1期82卷 649-649页

作者： Guo, Shuangle Zhang, Jianguang Zhang, Wenting Song, Zhifei Meng, Chunmei The School of Information Engineering Binzhou University Binzhou China The College of Mathematics and Computer Science Hengshui University Hengshui China The School of Computer Science & Software Engineering Shenzhen University Shenzhen China The College Electronics & Information Engineering Hengshui University Hengshui China The Office of Academic Research Hengshui University Hengshui China The College of Continuing Education Hengshui University Hengshui China

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Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence

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FUTURE GENERATION computer SYSTEMS-THE INTERNATIONAL JOURNAL OF Escience 2022年 134卷 414-429页

作者： Ejarque, Jorge Badia, Rosa M. Albertin, Loic Aloisio, Giovanni Baglione, Enrico Becerra, Yolanda Boschert, Stefan Berlin, Julian R. D'Anca, Alessandro Elia, Donatello Exertier, Francois Fiore, Sandro Flich, Jose Folch, Arnau Gibbons, Steven J. Koldunov, Nikolay Lordan, Francesc Lorito, Stefano Lovholt, Finn Macias, Jorge Marozzo, Fabrizio Michelini, Alberto Monterrubio-Velasco, Marisol Pienkowska, Marta de la Puente, Josep Queralt, Anna Quintana-Orti, Enrique S. Rodriguez, Juan E. Romano, Fabrizio Rossi, Riccardo Rybicki, Jedrzej Kupczyk, Miroslaw Selva, Jacopo Talia, Domenico Tonini, Roberto Trunfio, Paolo Volpe, Manuela [a]Barcelona Supercomputing Center (BSC) Spain [b]Centre Internacional de Mètodes Numèrics a l’Enginyeria (CIMNE) Spain [c]Universitat Politècnica de Catalunya (UPC) Spain [d]Jülich Supercomputing Centre (JSC) Germany [e]Universitat Politècnica de València (UPV) Spain [f]Atos BDS R&D HPC & AI Software France [g]DtoK Lab Srl Italy [h]Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) Italy [i]Department of Information Engineering and Computer Science University of Trento Italy [j]Universidad de Málaga (UMA) Spain [k]Istituto Nazionale di Geofisica e Vulcanologia (INGV) Italy [l]Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung Germany [m]Consejo Superior Investigaciones Cientificas (CSIC) Spain [n]Eidgenössische Technische Hochschule (ETH) Zürich Switzerland [o]Siemens AG Germany [p]Norwegian Geotechnical Institute (NGI) Norway [q]Poznan Supercomputing and Networking Center (PSNC) Poland

The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the workflows but also from the type of computations they perform. While traditional HPC workflows target simulations and modelling of physical phenomena, current needs require in addition data analytics (DA) and artificial intelligence (AI) tasks. However, the development of these workflows is hampered by the lack of proper programming models and environments that support the integration of HPC, DA, and AI, as well as the lack of tools to easily deploy and execute the workflows in HPC systems. To progress in this direction, this paper presents use cases where complex workflows are required and investigates the main issues to be addressed for the HPC/DA/AI convergence. Based on this study, the paper identifies the challenges of a new workflow platform to manage complex workflows. Finally, it proposes a development approach for such a workflow platform addressing these challenges in two directions: first, by defining a software stack that provides the functionalities to manage these complex workflows;and second, by proposing the HPC Workflow as a Service (HPCWaaS) paradigm, which leverages the software stack to facilitate the reusability of complex workflows in federated HPC infrastructures. Proposals presented in this work are subject to study and development as part of the EuroHPC eFlows4HPC project. (C) 2022 Elsevier B.V. All rights reserved.

关键词： High performance computing Distributed computing Parallel programming HPC-DA-AI convergence Workflow development Workflow orchestration

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Design of a Cryptographically Secure Pseudo Random Number Generator with Grammatical Evolution

Research Square

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Research Square 2021年

作者： Ryan, Conor Kshirsagar, Meghana Vaidya, Gauri Cunningham, Andrew Sivaraman, R. Biocomputing and Developmental Systems Group Lero The Science Foundation Ireland Research Centre for Software Computer Science and Information System Department University of Limerick LimerickV94 T9PX Ireland Intel Research and Development Ireland Limited LeixlipW23 CX68 Ireland Department of Electronics Communication Engineering School of Electrical and Electronics Engineering Shanmugha Arts Science Technology and Research Academy Deemed to be University Thanjavur613401 India

This work investigates the potential of evolving an initial seed with Grammatical Evolution (GE), for the construction of cryptographically secure (CS) pseudo-random number generator (PRNG). We harness the flexibility of GE as an entropy source for returning initial seeds. The initial seeds returned by GE demonstrate an average entropy value of 7.920261600000001 which is extremely close to the ideal value of 8. The initial seed combined with our proposed approach, control_flow_incrementor, is used to construct both, GE-PRNG and GE-CSPRNG. The random numbers generated with CSPRNG meet the prescribed National Institute of Standards and Technology (NIST) SP800-22 requirements. Monte Carlo simulations established the efficacy of the PRNG. The experimental setup was designed to estimate the value for pi, in which 100,000,000 random numbers were generated by our system and which resulted in returning the value of pi to 3.146564000, with a precision up to six decimal digits. The random numbers by GE-PRNG were compared against those generated by Python’s rand() function for sampling. The sampling results, when measured for accuracy against twenty-nine real world regression datasets, showed that GE-PRNG had less error when compared to Python’s rand() against the ground truths in seventeen of those, while there was no discernible difference in the remaining twelve. © 2021, CC BY.

关键词： Monte Carlo methods

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Automatic segmentation of novel coronavirus pneumonia lesions in CT images utilizing deep-supervised ensemble learning network

arXiv

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arXiv 2021年

作者： Peng, Yuanyuan Zhang, Zixu Tu, Hongbin Li, Xiong School of Electrical and Automation Engineering East China Jiaotong University Nanchang China School of Computer Science Northwestern Polytechnical University Xi'an China Technique Center Hunan Great Wall Technology Information Company Limited Changsha China School of Software East China Jiaotong University Nanchang China

Background: The 2019 novel coronavirus disease (COVID-19) has been spread widely in the world, causing a huge threat to people's living environment. Objective: Under computed tomography (CT) imaging, the structure features of COVID-19 lesions are complicated and varied greatly in different cases. To accurately locate COVID-19 lesions and assist doctors to make the best diagnosis and treatment plan, a deep-supervised ensemble learning network is presented for COVID-19 lesion segmentation in CT images. Methods: Considering the fact that a large number of COVID-19 CT images and the corresponding lesion annotations are difficult to obtained, a transfer learning strategy is employed to make up for the shortcoming and alleviate the overfitting problem. Based on the reality that traditional single deep learning framework is difficult to extract complicated and varied COVID-19 lesion features effectively, which may cause some lesions to be undetected. To overcome the problem, a deepsupervised ensemble learning network is presented to combine with local and global features for COVID-19 lesion segmentation. Results: The performance of the proposed method was validated in experiments with a publicly available dataset. Compared with manual annotations, the proposed method acquired a high intersection over union (IoU) of 0.7279 and a low hausdorff distance (H) of 92.4604. Conclusion: A deep-supervised ensemble learning network was presented for coronavirus pneumonia lesion segmentation in CT images. The effectiveness of the proposed method was verified by visual inspection and quantitative evaluation. Experimental results indicated that the proposed method has a good performance in COVID-19 lesion segmentation. © 2021, CC BY.

关键词： computerized tomography

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Integrating Privacy Enhancing Techniques into Blockchains Using Sidechains

Integrating Privacy Enhancing Techniques into Blockchains Us...

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2019 IEEE Canadian Conference of Electrical and computer engineering, CCECE 2019

作者： Parizi, Reza M. Homayoun, Sajad Yazdinejad, Abbas Dehghantanha, Ali Choo, Kim-Kwang Raymond Department of Software Engineering and Game Development Kennesaw State University GA United States Department of Computer Engineering and Information Technology Shiraz University of Technology Shiraz Iran Faculty of Computer Engineering University of Isfahan Iran School of Computer Science University of Guelph ON Canada Department of Information Systems and Cyber Security University of Texas at San Antonio TX United States

ISBN: (纸本)9781728103198

Blockchains are turning into decentralized computing platforms and are getting worldwide recognition for their unique advantages. There is an emerging trend beyond payments that blockchains could enable a new breed of decentralized applications, and serve as the foundation for Internet's security infrastructure. The immutable nature of the blockchain makes it a winner on security and transparency;it is nearly inconceivable for ledgers to be altered in a way not instantly clear to every single user involved. However, most blockchains fall short in privacy aspects, particularly in data protection. Garlic Routing and Onion Routing are two of major Privacy Enhancing Techniques (PETs) which are popular for anonymization and security. Garlic Routing is a methodology using by I2P Anonymous Network to hide the identity of sender and receiver of data packets by bundling multiple messages into a layered encryption structure. The Onion Routing attempts to provide low-latency Internet-based connections that resist traffic analysis, deanonymization attack, eavesdropping, and other attacks both by outsiders (e.g. Internet routers) and insiders (Onion Routing servers themselves). As there are a few controversies over the rate of resistance of these two techniques to privacy attacks, we propose a PET-Enabled Sidechain (PETES) as a new privacy enhancing technique by integrating Garlic Routing and Onion Routing into a Garlic Onion Routing (GOR) framework suitable to the structure of blockchains. The preliminary proposed GOR aims to improve the privacy of transactions in blockchains via PETES structure. © 2019 IEEE.

关键词： Blockchain

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Implementation of Convolutional Neural Network Method for Classification of Diseases in Tomato Leaves 4

Implementation of Convolutional Neural Network Method for Cl...

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Widiyanto, Sigit Fitrianto, Rizqy Wardani, Dini Tri Department of Computer Science Gunadarma University Jakarta Indonesia Department of Software Engineering Gunadarma University Jakarta Indonesia Department of Information System Gunadarma University Jakarta Indonesia

ISBN: (纸本)9781728122076

Diseases in plants are a problem that often occurs in agriculture. The disease can be caused by pests or maintenance errors. This resulted in a decrease in agricultural production. The decline in production has resulted in a decline in economic yields produced by farmers. Diseases of tomato plants often appear on the leaves. Diseases of tomato leaves have various characteristics. This causes difficulty in identifying diseases automatically. This study aims to identify diseases in leaf images in full automatically without having to define the characteristics and process of segmentation. The method used in this study is Convolutional Neural Networks (CNN). In this study 5 types of leaf disease were used with each type of disease consisting of 1000 image data. This study has successfully identified disease in leaf images automatically with an accuracy of 96.60%. By using the method Confusion Matrix based on the results, it training can count four types of measurements, namely accuracy, precision, recall and F1-score by producing an average value of 98.00%. © 2019 IEEE.

关键词： Image recognition

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An Analysis of Utility for API Recommendation: Do the Matched Results Have the Same Efforts?

An Analysis of Utility for API Recommendation: Do the Matche...

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IEEE International Conference on software Quality, Reliability and Security (QRS)

作者： Huidan Li Rensong Xie Xianglong Kong Lulu Wang Bixin Li School of Computer Science and Engineering Southeast University China Key Laboratory of Safety-Critical Software (Nanjing University of Aeronautics and Astronautics) Ministry of Industry and Information Technology China

The following topics are dealt with: learning (artificial intelligence); program testing; program debugging; public domain software; software maintenance; software quality; security of data; neural nets; mobile comput... 详细信息

ISBN: (数字)9781728189130

ISBN: (纸本)9781728189147

关键词： Current measurement Conferences software quality Programming Reliability engineering software reliability Security

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