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Descriptive complexity of deterministic polylogarithmic time and space J. Comput. Syst. Sci. (IF 1.494) Pub Date : 2021-03-02 Flavio Ferrarotti; Senén González; José María Turull Torres; Jan Van den Bussche; Jonni Virtema
We propose logical characterizations of problems solvable in deterministic polylogarithmic time (PolylogTime) and polylogarithmic space (PolylogSpace). We introduce a novel two-sorted logic that separates the elements of the input domain from the bit positions needed to address these elements. We prove that the inflationary and partial fixed point variants of this logic capture PolylogTime and PolylogSpace
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Bidding mechanisms in graph games J. Comput. Syst. Sci. (IF 1.494) Pub Date : 2021-03-03 Guy Avni; Thomas A. Henzinger; Đorđe Žikelić
A graph game proceeds as follows: two players move a token through a graph to produce a finite or infinite path, which determines the payoff of the game. We study bidding games in which in each turn, an auction determines which player moves the token. Bidding games were largely studied in combination with two variants of first-price auctions called “Richman” and “poorman” bidding. We study taxman bidding
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Association rule-based malware classification using common subsequences of API calls Appl. Soft Comput. (IF 5.472) Pub Date : 2021-03-05 Gianni D’Angelo; Massimo Ficco; Francesco Palmieri
Emerging malware pose increasing challenges to detection systems as their variety and sophistication continue to increase. Malware developers use complex techniques to produce malware variants, by removing, replacing, and adding useless API calls to the code, which are specifically designed to evade detection mechanisms, as well as do not affect the original functionality of the malicious code involved
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Optimal fuzzy logic-based control strategy for lower limb rehabilitation exoskeleton Appl. Soft Comput. (IF 5.472) Pub Date : 2021-03-05 Richa Sharma; Prerna Gaur; Shaurya Bhatt; Deepak Joshi
In recent times, several control engineers have been working towards development of efficient rehabilitation exoskeletons for mobility impairments. This work aims at implementation of an optimal fuzzy logic-based control strategy for a lower limb exoskeleton application wherein the control parameters for the proposed control approach are obtained by a recently developed optimization technique named
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A novel model for data-driven smart sustainable cities of the future: the institutional transformations required for balancing and advancing the three goals of sustainability Energy Inform. Pub Date : 2021-03-05 Simon Elias Bibri
In recent years, it has become increasingly feasible to achieve important improvements of sustainability by integrating sustainable urbanism with smart urbanism thanks to the proven role and synergic potential of data-driven technologies. Indeed, the processes and practices of both of these approaches to urban planning and development are becoming highly responsive to a form of data-driven urbanism
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Unsplit-field higher-order nearly PML for arbitrary media in EM simulation J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-02 Jiang Haolin; Xie Yongjun; Wu Peiyu; Zhang Jianfeng; Niu Liqiang
An unsplit-field higher order nearly perfectly matched layer (NPML) based on the auxiliary differential equation approach is introduced in three-dimensional finite-difference timedomain lattices. The proposed scheme has the advantage of both the NPML scheme and the higher order concept in terms of the improved absorbing performance and considerable computational efficiency. By incorporating with the
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A deep learning-based binocular perception system J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-02 Sun Zhao; Ma Chao; Wang Liang; Meng Ran; Pei Shanshan
An obstacle perception system for intelligent vehicle is proposed. The proposed system combines the stereo version technique and the deep learning network model, and is applied to obstacle perception tasks in complex environment. In this paper, we provide a complete system design project, which includes the hardware parameters, software framework, algorithm principle, and optimization method. In addition
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STAP method based on atomic norm minimization with array amplitude-phase error calibration J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-02 Pang Xiaojiao; Zhao Yongbo; Cao Chenghu; Xu Baoqing; Hu Yili
In this paper, a space-time adaptive processing (STAP) method is proposed for the airborne radar with the array amplitude-phase error considered, which is based on atomic norm minimization (ANM). In the conventional ANM-based STAP method, the influence of the array amplitude-phase error is not considered and restrained, which inevitably causes performance deterioration. To solve this problem, the array
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Higher order implicit CNDG-PML algorithm for left-handed materials J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-02 Chen Yanfang; Wang Liwei
By incorporating the higher order concept, the piece-wise linear recursive convolution (PLRC) method and Crank-Nicolson Douglas-Gunn (CNDG) algorithm, the unconditionally stable complex frequency shifted nearly perfectly matched layer (CFS-NPML) is proposed to terminate the left-handed material (LHM) domain. The proposed scheme takes advantages of CFS-NPML formulation, the higher order concept PLRC
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Multiple interferences suppression with space-polarization null-decoupling for polarimetrie array J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Lu Yawei; Ma Jiazhi; Shi Longfei; Quan Yuan
The adaptive digital beamforming technique in the space-polarization domain suppresses the interference with forming the coupling nulls of space and polarization domain. When there is the interference in mainlobe, it will cause serious mainlobe distortion, that the target detection suffers from. To overcome this problem and make radar cope with the complex multiple interferences scenarios, we propose
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Fast and accurate covariance matrix reconstruction for adaptive beamforming using Gauss-Legendre quadrature J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-02 Liu Shuai; Zhang Xue; Yan Fenggang; Wang Jun; Jin Ming
Most of the reconstruction-based robust adaptive beamforming (RAB) algorithms require the covariance matrix reconstruction (CMR) by high-complexity integral computation. A Gauss-Legendre quadrature (GLQ) method with the highest algebraic precision in the interpolation-type quadrature is proposed to reduce the complexity. The interference angular sector in RAB is regarded as the GLQ integral range,
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Monopulse instantaneous 3D imaging for wideband radar system J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Li Yuhan; Qi Wei; Deng Zhenmiao; Fu Maozhong; Zhang Yunjian
To avoid the complicated motion compensation in interferometric inverse synthetic aperture (InISAR) and achieve realtime three-dimensional (3D) imaging, a novel approach for 3D imaging of the target only using a single echo is presented. This method is based on an isolated scatterer model assumption, thus the scatterers in the beam can be extracted individually. The radial range of each scatterer is
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An approach of motion compensation and ISAR imaging for micro-motion targets J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Wang Yong; Zhou Xingyu; Lu Xiaofei; Li Yajun
Inverse synthetic aperture radar (ISAR) imaging of the target with the non-rigid body is very important in the field of radar signal processing. In this paper, a motion compensation method combined with the preprocessing and global technique is proposed to reduce the influence of micro-motion components in the fast time domain, and the micro-Doppler (m-D) signal in the slow time domain is separated
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SAR image de-noising via grouping-based PCA and guided filter J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Fang Jing; Hu Shaohai; Ma Xiaole
A novel synthetic aperture radar (SAR) image de-noising method based on the local pixel grouping (LPG) principal component analysis (PCA) and guided filter is proposed. This method contains two steps. In the first step, we process the noisy image by coarse filters, which can suppress the speckle effectively. The original SAR image is transformed into the additive noise model by logarithmic transform
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Short-range clutter suppression method combining oblique projection and interpolation in airborne CFA radar J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Hu Yili; Zhao Yongbo; Pang Xiaojiao; Chen Sheng
The airborne conformai array (CFA) radar's clutter ridges are range-modulated, which result in a bias in the estimation of the clutter covariance matrix (CCM) of the cell under test (CUT), further, reducing the clutter suppression performance of the airborne CFA radar. The clutter ridges can be effectively compensated by the space-time separation interpolation (STS-INT) method, which costs less computation
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NSHV trajectory prediction algorithm based on aerodynamic acceleration EMD decomposition J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Li Fan; Xiong Jiajun; Lan Xuhui; Bi Hongkui; Chen Xin
Aiming at the problem of gliding near space hypersonic vehicle (NSHV) trajectory prediction, a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition (EMD) is proposed. The method analyzes the motion characteristics of the skipping gliding NSHV and verifies that the aerodynamic acceleration of the target has a relatively stable rule. On this basis, EMD is used to
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High-end equipment development task decomposition and scheme selection method J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Xu Xiangqian; Yang Kewei; Dou Yajie; Zhou Zhexuan; Chen Ziyi; Tan Yuejin
Decomposition of tasks and selection of optimal schemes are key procedures in high-end equipment development processes. However, such procedures are highly innovative, technology intensive, interdisciplinary, and multi-party engineering projects, making the decomposition and scheme selection more difficult and complicated than that in the development of ordinary equipment. In this study, we consider
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Evolutionary game analysis of problem processing mechanism in new collaboration J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Zhang Ming; Zhu Jianjun; Wang Hehua
This paper analyzes a problem processing mechanism in a new collaboration system between the main manufacturer and the supplier in the "main manufacturer-supplier" mode, which has been widely applied in the collaborative development management of the complex product. This paper adopts the collaboration theory, the evolutionary game theory and numerical simulation to analyze the decision-making mechanism
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A sparse algorithm for adaptive pruning least square support vector regression machine based on global representative point ranking J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Hu Lei; Yi Guoxing; Huang Chao
Least square support vector regression (LSSVR) is a method for function approximation, whose solutions are typically non-sparse, which limits its application especially in some occasions of fast prediction. In this paper, a sparse algorithm for adaptive pruning LSSVR algorithm based on global representative point ranking (GRPR-AP-LSSVR) is proposed. At first, the global representative point ranking
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Reactive scheduling of multiple EOSs under cloud uncertainties: Model and algorithms J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Wang Jianjiang; Hu Xuejun; He Chuan
Most earth observation satellites (EOSs) are low-orbit satellites equipped with optical sensors that cannot see through clouds. Hence, cloud coverage, high dynamics, and cloud uncertainties are important issues in the scheduling of EOSs. The proactive-reactive scheduling framework has been proven to be effective and efficient for the uncertain scheduling problem and has been extensively employed. Numerous
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Line-of-sight rates extraction of roll-pitch seeker under anti-infrared decoy state J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Li Yue; He Lei; Xia Qunli
In this paper, the method of extracting guidance information such as the line-of-sight (LOS) rates under the anti-infrared decoy state for the roll-pitch seeker is researched. Co-ordinate systems which are used to describe the angles transform are defined. The LOS angles reconstruction model of the roll-pitch seeker in inertial space is established. A Kalman filter model for extracting LOS rates of
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Open-loop and closed-loop Dα-type iterative learning control for fractional-order linear multi-agent systems with state-delays J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Li Bingqiang; Lan Tianyi; Zhao Yiyun; Lyu Shuaishuai
This study focuses on implementing consensus tracking using both open-loop and closed-loop Dα-type iterative learning control (ILC) schemes, for fractional-order multi-agent systems (FOMASs) with state-delays. The desired trajectory is constructed by introducing a virtual leader, and the fixed communication topology is considered and only a subset of followers can access the desired trajectory. For
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Constrained voting extreme learning machine and its application J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Min Mengcan; Chen Xiaofang; Xie Yongfang
Extreme learning machine (ELM) has been proved to be an effective pattern classification and regression learning mechanism by researchers. However, its good performance is based on a large number of hidden layer nodes. With the increase of the nodes in the hidden layers, the computation cost is greatly increased. In this paper, we propose a novel algorithm, named constrained voting extreme learning
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Enhanced two-loop model predictive control design for linear uncertain systems J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Mohammad-Ghassem Farajzadeh-Devin; Seyed Kamal Hosseini Sani
Model predictive controllers (MPC) with the two-loop scheme are successful approaches practically and can be classified into two main categories, tube-based MPC and MPC-based reference governors (RG). In this paper, an enhanced two-loop MPC design is proposed for a pre-stabilized system with the bounded uncertainty subject to the input and state constraints. The proposed method offers less conservatism
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Consensus of multi-vehicle cooperative attack with stochastic multi-hop time-varying delay and actuator fault J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Cai Guangbin; Zhao Yushan; Zhao Yang; Hu Changhua
A consensus-distributed fault-tolerant (CDFT) control law is proposed for a class of leader-following multi-vehicle cooperative attack (MVCA) systems in this paper. In particular, the switching communication topologies, stochastic multi-hop time-varying delays, and actuator faults are considered, which may lead to system performance degradation or on certain occasions even cause system instability
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Bayesian estimation of a power law process with incomplete data J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Hu Junming; Huang Hongzhong; Li Yanfeng
Due to the simplicity and flexibility of the power law process, it is widely used to model the failures of repairable systems. Although statistical inference on the parameters of the power law process has been well developed, numerous studies largely depend on complete failure data. A few methods on incomplete data are reported to process such data, but they are limited to their specific cases, especially
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Inspection interval optimization for aircraft composite structures with dent and delamination damage J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03 Cai Jing; Dai Dingqiang
The optimization of inspection intervals for composite structures has been proposed, but only one damage type, dent damage, has been addressed so far. The present study focuses on the two main damage types of dent and delamination, and a model for optimizing the inspection interval of composite structures is proposed to minimize the total maintenance cost on the premise that the probability of structure
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Call for papers J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03
Sensor arrays provide additional degree of freedom in the spatial domain compared to a single antenna, which, with the aid of advanced signal processing algorithms, can be exploited for interference suppression/beamforming, direction of arrival estimation, and target tracking and localization. While two prominent technologies in 5G/6G communication system, i.e., massive MIMO and millimeter (mm) wave
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Call for papers J. Syst. Eng. Electron. (IF 0.907) Pub Date : 2021-03-03
With the rapid development of new system radar, radar applications have been greatly extended from early military target seeking, tracking and fire control to civilian weather detection, terrain mapping and disaster monitoring. Landslide hazards could cause severe threats to human lives and properties worldwide every year. Surface deformations normally occur before the macro failure of natural and
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Computation-efficient 2-D DOA estimation algorithm with array motion strategy Digit. Signal Process. (IF 2.871) Pub Date : 2021-03-04 Penghui Ma; Jianfeng Li; Gaofeng Zhao; Xiaofei Zhang
Two-dimensional (2-D) direction of arrival (DOA) estimation exploiting interlaced uniform planar array (IUPA) motion is discussed in this paper, and a Discrete Fourier Transform cascading Taylor Expansion (DFT-TE) algorithm is proposed. Specifically, the proposed IUPA structure possesses larger inter-element spacing than traditional uniform planar array (UPA), and it can mitigate the mutual coupling
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An overview of deep reinforcement learning for spectrum sensing in cognitive radio networks Digit. Signal Process. (IF 2.871) Pub Date : 2021-03-05 Felix Obite; Aliyu D. Usman; Emmanuel Okafor
Deep reinforcement learning has recorded remarkable performance in diverse application areas of artificial intelligence: pattern recognition, robotics, object segmentation, recommendation-system, and gaming. In recent times, the applicability of deep learning to telecommunication technology is gradually attracting a lot of attention, especially in spectrum sensing, a core component in cognitive radio
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BCGAN: A CGAN-based over-sampling model using the boundary class for data balancing J. Supercomput. (IF 2.469) Pub Date : 2021-03-05 Minjae Son; Seungwon Jung; Seungmin Jung; Eenjun Hwang
A class imbalance problem occurs when a dataset is decomposed into one majority class and one minority class. This problem is critical in the machine learning domains because it induces bias in training machine learning models. One popular method to solve this problem is using a sampling technique to balance the class distribution by either under-sampling the majority class or over-sampling the minority
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Novel side pose classification model of stretching gestures using three-layer LSTM J. Supercomput. (IF 2.469) Pub Date : 2021-03-05 Boldmaa Solongontuya; Kyung Joo Cheoi; Mi-Hye Kim
In recent years, low back pain rehabilitation exercises have been widely performed for spine-related illnesses. To facilitate rehabilitation exercises, pose-based human action recognition technique is used to determine human movement from simple videos. Herein, we propose a new stretching side pose classification system using three-layer long short-term memory (LSTM) that can be used in rehabilitation
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Analysis of complications after transcatheter arterial chemoembolization based on deep learning J. Supercomput. (IF 2.469) Pub Date : 2021-03-05 Mengyan Xing; Zhonghua Ma; Hanfang Fu; Fang Jin; Jing Wang; Yujie Hua; Li Han
The aim of this exploration is to analyze the elements related to infections as well as neurological damage complications after transcatheter arterial chemoembolization (TACE) by computer information health analysis using deep learning. In this exploration, there were 80 primary liver cancer patients who were selected as the study subjects. After each patient was treated with TACE, analysis is made
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Heterogeneity-aware elastic scaling of streaming applications on cloud platforms J. Supercomput. (IF 2.469) Pub Date : 2021-03-05 Jyoti Sahni; Deo Prakash Vidyarthi
Rise of Big Data techniques has led to the requirement for low latency analysis of high-velocity continuous data streams in real time. Several solutions, including Stream Processing Systems (SPSs), have been developed to enable real-time distributed stream processing. However, emerging application scenarios such as smart cities and wearable assistance that involve highly variable data rates keep on
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Distributed intrusion detection scheme using dual-axis dimensionality reduction for Internet of things (IoT) J. Supercomput. (IF 2.469) Pub Date : 2021-03-05 Shashank Gavel; Ajay Singh Raghuvanshi; Sudarshan Tiwari
The immense growth in the cyber world has given birth to various types of cybercrimes in the Internet of things (IoT). Cybercrimes have breached the multiple levels of cybersecurity that is one of the major issues in the IoT networks. Due to the rise in IoT applications, both devices and services are prone to security attacks and intrusions. The intrusion breaches the data packet extracted from different
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A Routing Protocol for UAV-Assisted Vehicular Delay Tolerant Networks IEEE Open J. Comput. Soc. Pub Date : 2021-01-26 Zhaoyang Du; Celimuge Wu; Tsutomu Yoshinaga; Xianfu Chen; Xiaoyan Wang; Kok-Lim Alvin Yau; Yusheng Ji
Vehicular delay tolerant networks (VDTNs) enable information sharing among mobile nodes in scenarios where cellular base stations are unavailable and the connections between the mobile nodes are intermittent. While unmanned aerial vehicles (UAVs) have shown to improve the performance of VDTNs, existing routing protocols, such as PRoPHET, consider the encounter probability between mobile nodes only
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Instructions for Authors IEEE Open J. Comput. Soc. Pub Date : 2021-03-02
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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Author Correction: Sex-specific adipose tissue imprinting of regulatory T cells Nature (IF 42.778) Pub Date : 2021-03-05 Ajithkumar Vasanthakumar; David Chisanga; Jonas Blume; Renee Gloury; Kara Britt; Darren C. Henstridge; Yifan Zhan; Santiago Valle Torres; Sebastian Liene; Nicholas Collins; Enyuan Cao; Tom Sidwell; Chaoran Li; Raul German Spallanzani; Yang Liao; Paul A. Beavis; Thomas Gebhardt; Natalie Trevaskis; Stephen L. Nutt; Jeffrey D. Zajac; Rachel A. Davey; Mark A. Febbraio; Diane Mathis; Wei Shi; Axel Kallies
A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-2251-7
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Webcast: How to write a first-class paper Nature (IF 42.778) Pub Date : 2021-03-05 Jack Leeming
A scientific editor’s tips for writing titles and abstracts to boost the readership of your manuscripts.
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Coronapod: COVID's origins and the 'lab leak' theory Nature (IF 42.778) Pub Date : 2021-03-05 Benjamin Thompson; Noah Baker; Amy Maxmen
Hear the latest science from the coronavirus pandemic.
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Road map for domesticating multi-genome rice using gene editing Nature (IF 42.778) Pub Date : 2021-03-05 Diane R. Wang
Rapid domestication of wild polyploid rice.
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Nuclear energy, ten years after Fukushima Nature (IF 42.778) Pub Date : 2021-03-05 Aditi Verma; Ali Ahmad; Francesca Giovannini
Amid the urgent need to decarbonize, the industry that delivers one-tenth of global electricity must consult the public on reactor research, design, regulation, location and waste.
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Multitude of coronavirus variants found in the US — but the threat is unclear Nature (IF 42.778) Pub Date : 2021-03-05 Ewen Callaway
Ramped-up sequencing efforts are helping to identify mutations that might boost transmission or help a virus evade immune responses.
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Which are the best pandemic policies? Data trackers are trying to judge Nature (IF 42.778) Pub Date : 2021-03-05 Quirin Schiermeier
Thousands of scientists and volunteers have charted the way governments have responded to COVID-19.
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US health agency will invest $1 billion to investigate ‘long COVID’ Nature (IF 42.778) Pub Date : 2021-03-04 Nidhi Subbaraman
The National Institutes of Health will fund researchers to track people’s recovery, and will host a biospecimen bank.
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Daily briefing: Glow-in-the-dark shark is biggest bioluminescent vertebrate Nature (IF 42.778) Pub Date : 2021-03-04 Flora Graham
Kitefin shark is the biggest bioluminescent vertebrate known. Plus, Fortran wins vote as code that has most transformed research, and a call for funders to consider the unequal toll of the pandemic on scientists.
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Wanted Dead or Alive : Epistemic logic for impure simplicial complexes arXiv.cs.LO Pub Date : 2021-03-04 Hans van Ditmarsch
We propose a logic of knowledge for impure simplicial complexes. Impure simplicial complexes represent distributed systems under uncertainty over which processes are still active (are alive) and which processes have failed or crashed (are dead). Our work generalizes the logic of knowledge for pure simplicial complexes, where all processes are alive, by Goubault et al. Our logical semantics has a satisfaction
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Image-based Approximate DNA Storage System arXiv.cs.ET Pub Date : 2021-03-04 Bingzhe Li; Li Ou; David Du
Deoxyribonucleic Acid (DNA) as a storage medium with high density and long-term preservation properties can satisfy the requirement of archival storage for rapidly increased digital volume. The read and write processes of DNA storage are error-prone. Images widely used in social media have the properties of fault tolerance which are well fitted to the DNA storage. However, prior work simply investigated
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Experimental Body-input Three-stage DC offset Calibration Scheme for Memristive Crossbar arXiv.cs.ET Pub Date : 2021-03-03 Charanraj Mohan; L. A. Camuñas-Mesa; Elisa Vianello; Carlo Reita; José M. de la Rosa; Teresa Serrano-Gotarredona; Bernabé Linares-Barranco
Reading several ReRAMs simultaneously in a neuromorphic circuit increases power consumption and limits scalability. Applying small inference read pulses is a vain attempt when offset voltages of the read-out circuit are decisively more. This paper presents an experimental validation of a three-stage calibration scheme to calibrate the DC offset voltage across the rows of the memristive crossbar. The
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Alleviation of Temperature Variation Induced Accuracy Degradation in Ferroelectric FinFET Based Neural Network arXiv.cs.ET Pub Date : 2021-03-03 Sourav De; Yao-Jen Lee; Darsen D. Lu
This paper reports the impacts of temperature variation on the inference accuracy of pre-trained all-ferroelectric FinFET deep neural networks, along with plausible design techniques to abate these impacts. We adopted a pre-trained artificial neural network (NN) with 96.4% inference accuracy on the MNIST dataset as the baseline. As an aftermath of temperature change, the conductance drift of a programmed
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On the Complexity of Equilibrium Computation in First-Price Auctions arXiv.cs.GT Pub Date : 2021-03-04 Aris Filos-Ratsikas; Yiannis Giannakopoulos; Alexandros Hollender; Philip Lazos; Diogo Poças
We consider the problem of computing a (pure) Bayes-Nash equilibrium in the first-price auction with continuous value distributions and discrete bidding space. We prove that when bidders have independent subjective prior beliefs about the value distributions of the other bidders, computing an $\varepsilon$-equilibrium of the auction is PPAD-complete, and computing an exact equilibrium is FIXP-complete
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An Optimal Truthful Mechanism for the Online Weighted Bipartite Matching Problem arXiv.cs.GT Pub Date : 2021-03-04 Rebecca Reiffenhäuser
In the weighted bipartite matching problem, the goal is to find a maximum-weight matching in a bipartite graph with nonnegative edge weights. We consider its online version where the first vertex set is known beforehand, but vertices of the second set appear one after another. Vertices of the first set are interpreted as items, and those of the second set as bidders. On arrival, each bidder vertex
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One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning arXiv.cs.GT Pub Date : 2021-03-04 Avrim Blum; Nika Haghtalab; Richard Lanas Phillips; Han Shao
In recent years, federated learning has been embraced as an approach for bringing about collaboration across large populations of learning agents. However, little is known about how collaboration protocols should take agents' incentives into account when allocating individual resources for communal learning in order to maintain such collaborations. Inspired by game theoretic notions, this paper introduces
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Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers arXiv.cs.CE Pub Date : 2021-03-04 Agastya P. Bhati; Shunzhou Wan; Dario Alfè; Austin R. Clyde; Mathis Bode; Li Tan; Mikhail Titov; Andre Merzky; Matteo Turilli; Shantenu Jha; Roger R. Highfield; Walter Rocchia; Nicola Scafuri; Sauro Succi; Dieter Kranzlmüller; Gerald Mathias; David Wifling; Yann Donon; Alberto Di Meglio; Sofia Vallecorsa; Heng Ma; Anda Trifan; Arvind Ramanathan; Tom Brettin; Alexander Partin; Fangfang Xia; Xiaotan
The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods
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On the Complexity of Equilibrium Computation in First-Price Auctions arXiv.cs.CC Pub Date : 2021-03-04 Aris Filos-Ratsikas; Yiannis Giannakopoulos; Alexandros Hollender; Philip Lazos; Diogo Poças
We consider the problem of computing a (pure) Bayes-Nash equilibrium in the first-price auction with continuous value distributions and discrete bidding space. We prove that when bidders have independent subjective prior beliefs about the value distributions of the other bidders, computing an $\varepsilon$-equilibrium of the auction is PPAD-complete, and computing an exact equilibrium is FIXP-complete
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Consensus in Blockchain Systems with Low Network Throughput: A Systematic Mapping Study arXiv.cs.CC Pub Date : 2021-03-04 Henrik Knudsen; Jakob Svennevik Notland; Peter Halland Haro; Truls Bakkejord Ræder; Jingyue Li
Blockchain technologies originate from cryptocurrencies. Thus, most blockchain technologies assume an environment with a fast and stable network. However, in some blockchain-based systems, e.g., supply chain management (SCM) systems, some Internet of Things (IOT) nodes can only rely on the low-quality network sometimes to achieve consensus. Thus, it is critical to understand the applicability of existing
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Cryptomining makes noise: Detecting cryptojacking via Machine Learning Comput. Commun. (IF 2.816) Pub Date : 2021-02-26 Maurantonio Caprolu; Simone Raponi; Gabriele Oligeri; Roberto Di Pietro
Cryptojacking occurs when an adversary illicitly runs crypto-mining software over the devices of unaware users. This novel cybersecurity attack, that is emerging in both the literature and in the wild, has proved to be very effective given the simplicity of running a crypto-client into a target device. Several countermeasures have recently been proposed, with different features and performance, but
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Expressway traffic safety early warning system based on cloud architecture Comput. Commun. (IF 2.816) Pub Date : 2021-02-18 Yujia Tian; Dianliang Xiao; Lu Wang; Hong Chen
With the development of the society, highway traffic safety is gradually valued by the world. However, due to the complicated state of the highway roads, the faster road speeds and the different types of vehicles, the problem of highway safety warning is an extremely complex system engineering problem faced by the entire society. In view of the characteristics of the problem studied, this study firstly
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An improved OIF Elman neural network based on CSO algorithm and its applications Comput. Commun. (IF 2.816) Pub Date : 2021-02-13 Yufei Zhang; Jianping Zhao; Limin Wang; Honggang Wu; Ruihong Zhou; Jinglin Yu
In order to prevent air pollution and improve the living environment for residents, it is particularly important to carry out air quality forecasting. Air quality is affected by many factors, and showed significant non-linear features. Output–input feedback Elman (OIF Elman) neural network can effectively solve non-linear problems. However, the disadvantages of OIF Elman neural network are easy to
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