华语诗歌,在人类文明的历史长河中悠久、灿烂而辉煌。为了繁荣发展全球华语诗歌文化,增进同世界各国华语诗人的联系和交流,咏颂大爱精神以及人与自然和谐相处的人文情怀,《诗歌月刊》上半月刊联合深圳文宝文化公司举办一年一届的＂D C ...华语诗歌,在人类文明的历史长河中悠久、灿烂而辉煌。为了繁荣发展全球华语诗歌文化,增进同世界各国华语诗人的联系和交流,咏颂大爱精神以及人与自然和谐相处的人文情怀,《诗歌月刊》上半月刊联合深圳文宝文化公司举办一年一届的＂D C C杯＂国际华文诗歌大奖赛活动。展开更多
In this paper a system for automatic recognition of radar waveform is introduced. This technique is used in many spectrum management, surveillance, and cognitive radio and radar applications. For instance the transmit...In this paper a system for automatic recognition of radar waveform is introduced. This technique is used in many spectrum management, surveillance, and cognitive radio and radar applications. For instance the transmitted radar signal is coded into six codes based on pulse compression waveform such as linear frequency modulation (LFM), Frank code, P1, P2, P3 and P4 codes, the latter four are poly phase codes. The classification system is based on drawing Choi Willliams Distribution (CWD) picture and extracting features from it. In this study, various new types of features are extracted from CWD picture and then a pattern recognition method is used to recognize the spectrum. In fact, signals from CWD picture are defined using biometric techniques. We also employ false reject rate (FRR) and false accept rate (FAR) which are two types of fault measurement criteria that are deploy in biometric papers. Fairly good results are obtained for recognition of Signal to Noise Ratio (-11 dB).展开更多
Frequency Hopping Spread Spectrum (FHSS) system is often deployed to protect wireless communication from jamming or to preclude undesired reception of the signal. Such themes can only be achieved if the jammer or unde...Frequency Hopping Spread Spectrum (FHSS) system is often deployed to protect wireless communication from jamming or to preclude undesired reception of the signal. Such themes can only be achieved if the jammer or undesired receiver does not have the knowledge of the spreading code. For this reason, unencrypted M-sequences are a deficient choice for the spreading code when a high level of security is required. The primary objective of this paper is to analyze vulnerability of linear feedback shift register (LFSRs) codes. Then, a new method based on encryption algorithm applied over spreading codes, named hidden frequency hopping is proposed to improve the security of FHSS. The proposed encryption security algorithm is highly reliable, and can be applied to all existing data communication systems based on spread spectrum techniques. Since the multi-user detection is an inherent characteristic for FHSS, the multi-user interference must be studied carefully. Hence, a new method called optimum pair “key-input” selection is proposed which reduces interference below the desired constant threshold.展开更多
A multi-antenna multiple relay (MAMR) network is considered and a variation of two-hop zero-forcing amplify-forward relaying method is proposed. Deploying ZF method together with application of diagonal power allocati...A multi-antenna multiple relay (MAMR) network is considered and a variation of two-hop zero-forcing amplify-forward relaying method is proposed. Deploying ZF method together with application of diagonal power allocation matrices at the relays, it is shown that the overall MAMR network is simplified to M independent single antenna multiple relay (SAMR) networks, where M is the number of source and destination antennas. This enables to incorporate network beamforming proposed for SAMR networks. Accordingly, using the BER as the performance metric, we present simulation results to show the proposed approach outperforms the common ZF method addressed in the literature.展开更多
With the increasing of communication applications in recent years, the demand for radio spectral resources has increased significantly. Cognitive radio scenario was proposed to improve spectrum efficiency in wireless ...With the increasing of communication applications in recent years, the demand for radio spectral resources has increased significantly. Cognitive radio scenario was proposed to improve spectrum efficiency in wireless communication systems. In cognitive radio network, it is essential that control information is sent securely and reliably. Ensuring the trustworthiness of the transmitting of spectrum sensing information is important in the CR networks since spectrum sensing directly affects spectrum management and incumbent coexistence. In this paper, the first secondary link channel model is presented, then a secure LT Code is proposed to be compatible with presented channel model and acquires good QoS. As we may know, LT code overcomes packet loss when the channel of the SU is reclaimed by PU. In the new proposed combined encoding and ciphered block, a LT code matrix is used to generate a symmetric cryptographic key. Thus, less complexity observed in the processing computation. Besides, cryptographic key is not sent over the channel. As a result, an attacker has no way to eavesdrop the key unless he is prepared to consider all possible key combinations. This replaced block supplies secure controlling channel and increases spectrum efficiency too.展开更多
In this systems paper,we present MillenniumDB:a novel graph database engine that is modular,persistent,and open source.MillenniumDB is based on a graph data model,which we call domain graphs,that provides a simple abs...In this systems paper,we present MillenniumDB:a novel graph database engine that is modular,persistent,and open source.MillenniumDB is based on a graph data model,which we call domain graphs,that provides a simple abstraction upon which a variety of popular graph models can be supported,thus providing a flexible data management engine for diverse types of knowledge graph.The engine itself is founded on a combination of tried and tested techniques from relational data management,state-of-the-art algorithms for worst-case-optimal joins,as well as graph-specific algorithms for evaluating path queries.In this paper,we present the main design principles underlying MillenniumDB,describing the abstract graph model and query semantics supported,the concrete data model and query syntax implemented,as well as the storage,indexing,query planning and query evaluation techniques used.We evaluate MillenniumDB over real-world data and queries from the Wikidata knowledge graph,where we find that it outperforms other popular persistent graph database engines(including both enterprise and open source alternatives)that support similarqueryfeatures.展开更多
Parallel computing has become an important subject in the field of computer science and has proven to be critical when researching high performance solutions.The evolution of computer architectures(multi-core and many...Parallel computing has become an important subject in the field of computer science and has proven to be critical when researching high performance solutions.The evolution of computer architectures(multi-core and many-core)towards a higher number of cores can only confirm that parallelism is the method of choice for speeding up an algorithm.In the last decade,the graphics processing unit,or GPU,has gained an important place in the field of high performance computing(HPC)because of its low cost and massive parallel processing power.Super-computing has become,for the first time,available to anyone at the price of a desktop computer.In this paper,we survey the concept of parallel computing and especially GPU computing.Achieving efficient parallel algorithms for the GPU is not a trivial task,there are several technical restrictions that must be satisfied in order to achieve the expected performance.Some of these limitations are consequences of the underlying architecture of the GPU and the theoretical models behind it.Our goal is to present a set of theoretical and technical concepts that are often required to understand the GPU and its massive parallelism model.In particular,we show how this new technology can help the field of computational physics,especially when the problem is data-parallel.We present four examples of computational physics problems;n-body,collision detection,Potts model and cellular automata simulations.These examples well represent the kind of problems that are suitable for GPU computing.By understanding the GPU architecture and its massive parallelism programming model,one can overcome many of the technical limitations found along the way,design better GPU-based algorithms for computational physics problems and achieve speedups that can reach up to two orders of magnitude when compared to sequential implementations.展开更多
Empirical interatomic potentials require optimization of force field parameters to tune interatomic interactions to mimic ones obtained by quantum chemistry-based methods.The optimization of the parameters is complex ...Empirical interatomic potentials require optimization of force field parameters to tune interatomic interactions to mimic ones obtained by quantum chemistry-based methods.The optimization of the parameters is complex and requires the development of new techniques.Here,we propose an INitial-DEsign Enhanced Deep learning-based OPTimization(INDEEDopt)framework to accelerate and improve the quality of the ReaxFF parameterization.The procedure starts with a Latin Hypercube Design(LHD)algorithm that is used to explore the parameter landscape extensively.The LHD passes the information about explored regions to a deep learning model,which finds the minimum discrepancy regions and eliminates unfeasible regions,and constructs a more comprehensive understanding of physically meaningful parameter space.We demonstrate the procedure here for the parameterization of a nickel–chromium binary force field and a tungsten–sulfide–carbon–oxygen–hydrogen quinary force field.We show that INDEEDopt produces improved accuracies in shorter development time compared to the conventional optimization method.展开更多
Reproducible wafer-scale growth of two-dimensional(2D)materials using the Chemical Vapor Deposition(CVD)process with precise control over their properties is challenging due to a lack of understanding of the growth me...Reproducible wafer-scale growth of two-dimensional(2D)materials using the Chemical Vapor Deposition(CVD)process with precise control over their properties is challenging due to a lack of understanding of the growth mechanisms spanning over several length scales and sensitivity of the synthesis to subtle changes in growth conditions.A multiscale computational framework coupling Computational Fluid Dynamics(CFD),Phase-Field(PF),and reactive Molecular Dynamics(MD)was developed–called the CPM model–and experimentally verified.Correlation between theoretical predictions and thorough experimental measurements for a Metal-Organic CVD(MOCVD)-grown WSe_(2)model material revealed the full power of this computational approach.Large-area uniform 2D materials are synthesized via MOCVD,guided by computational analyses.The developed computational framework provides the foundation for guiding the synthesis of wafer-scale 2D materials with precise control over the coverage,morphology,and properties,a critical capability for fabricating electronic,optoelectronic,and quantum computing devices.展开更多
文摘In this paper a system for automatic recognition of radar waveform is introduced. This technique is used in many spectrum management, surveillance, and cognitive radio and radar applications. For instance the transmitted radar signal is coded into six codes based on pulse compression waveform such as linear frequency modulation (LFM), Frank code, P1, P2, P3 and P4 codes, the latter four are poly phase codes. The classification system is based on drawing Choi Willliams Distribution (CWD) picture and extracting features from it. In this study, various new types of features are extracted from CWD picture and then a pattern recognition method is used to recognize the spectrum. In fact, signals from CWD picture are defined using biometric techniques. We also employ false reject rate (FRR) and false accept rate (FAR) which are two types of fault measurement criteria that are deploy in biometric papers. Fairly good results are obtained for recognition of Signal to Noise Ratio (-11 dB).
文摘Frequency Hopping Spread Spectrum (FHSS) system is often deployed to protect wireless communication from jamming or to preclude undesired reception of the signal. Such themes can only be achieved if the jammer or undesired receiver does not have the knowledge of the spreading code. For this reason, unencrypted M-sequences are a deficient choice for the spreading code when a high level of security is required. The primary objective of this paper is to analyze vulnerability of linear feedback shift register (LFSRs) codes. Then, a new method based on encryption algorithm applied over spreading codes, named hidden frequency hopping is proposed to improve the security of FHSS. The proposed encryption security algorithm is highly reliable, and can be applied to all existing data communication systems based on spread spectrum techniques. Since the multi-user detection is an inherent characteristic for FHSS, the multi-user interference must be studied carefully. Hence, a new method called optimum pair “key-input” selection is proposed which reduces interference below the desired constant threshold.
文摘A multi-antenna multiple relay (MAMR) network is considered and a variation of two-hop zero-forcing amplify-forward relaying method is proposed. Deploying ZF method together with application of diagonal power allocation matrices at the relays, it is shown that the overall MAMR network is simplified to M independent single antenna multiple relay (SAMR) networks, where M is the number of source and destination antennas. This enables to incorporate network beamforming proposed for SAMR networks. Accordingly, using the BER as the performance metric, we present simulation results to show the proposed approach outperforms the common ZF method addressed in the literature.
文摘With the increasing of communication applications in recent years, the demand for radio spectral resources has increased significantly. Cognitive radio scenario was proposed to improve spectrum efficiency in wireless communication systems. In cognitive radio network, it is essential that control information is sent securely and reliably. Ensuring the trustworthiness of the transmitting of spectrum sensing information is important in the CR networks since spectrum sensing directly affects spectrum management and incumbent coexistence. In this paper, the first secondary link channel model is presented, then a secure LT Code is proposed to be compatible with presented channel model and acquires good QoS. As we may know, LT code overcomes packet loss when the channel of the SU is reclaimed by PU. In the new proposed combined encoding and ciphered block, a LT code matrix is used to generate a symmetric cryptographic key. Thus, less complexity observed in the processing computation. Besides, cryptographic key is not sent over the channel. As a result, an attacker has no way to eavesdrop the key unless he is prepared to consider all possible key combinations. This replaced block supplies secure controlling channel and increases spectrum efficiency too.
基金supported by ANID-Millennium Science Initiative Program-Code ICN17_002。
文摘In this systems paper,we present MillenniumDB:a novel graph database engine that is modular,persistent,and open source.MillenniumDB is based on a graph data model,which we call domain graphs,that provides a simple abstraction upon which a variety of popular graph models can be supported,thus providing a flexible data management engine for diverse types of knowledge graph.The engine itself is founded on a combination of tried and tested techniques from relational data management,state-of-the-art algorithms for worst-case-optimal joins,as well as graph-specific algorithms for evaluating path queries.In this paper,we present the main design principles underlying MillenniumDB,describing the abstract graph model and query semantics supported,the concrete data model and query syntax implemented,as well as the storage,indexing,query planning and query evaluation techniques used.We evaluate MillenniumDB over real-world data and queries from the Wikidata knowledge graph,where we find that it outperforms other popular persistent graph database engines(including both enterprise and open source alternatives)that support similarqueryfeatures.
基金supported by the The Young Teacher Research Capacity Advancement Program of Northwest Normal University(SKQ-NYB12009)Open Research Fund of the Beijing Key Lab of Applied Experimental Psychology and Science education programs in Gansu Province(GS[2013]GHBZ086)
基金supported by Fondecyt Project No.1120495.Finally,thanks to Renato Cerro for improving the English of this manuscript.
文摘Parallel computing has become an important subject in the field of computer science and has proven to be critical when researching high performance solutions.The evolution of computer architectures(multi-core and many-core)towards a higher number of cores can only confirm that parallelism is the method of choice for speeding up an algorithm.In the last decade,the graphics processing unit,or GPU,has gained an important place in the field of high performance computing(HPC)because of its low cost and massive parallel processing power.Super-computing has become,for the first time,available to anyone at the price of a desktop computer.In this paper,we survey the concept of parallel computing and especially GPU computing.Achieving efficient parallel algorithms for the GPU is not a trivial task,there are several technical restrictions that must be satisfied in order to achieve the expected performance.Some of these limitations are consequences of the underlying architecture of the GPU and the theoretical models behind it.Our goal is to present a set of theoretical and technical concepts that are often required to understand the GPU and its massive parallelism model.In particular,we show how this new technology can help the field of computational physics,especially when the problem is data-parallel.We present four examples of computational physics problems;n-body,collision detection,Potts model and cellular automata simulations.These examples well represent the kind of problems that are suitable for GPU computing.By understanding the GPU architecture and its massive parallelism programming model,one can overcome many of the technical limitations found along the way,design better GPU-based algorithms for computational physics problems and achieve speedups that can reach up to two orders of magnitude when compared to sequential implementations.
基金The authors acknowledge partial funding support from U.S.National Science Foundation under Award No.DMR-1842922,DMR-1842952,DMR-1539916,and MRI-1626251.
文摘Empirical interatomic potentials require optimization of force field parameters to tune interatomic interactions to mimic ones obtained by quantum chemistry-based methods.The optimization of the parameters is complex and requires the development of new techniques.Here,we propose an INitial-DEsign Enhanced Deep learning-based OPTimization(INDEEDopt)framework to accelerate and improve the quality of the ReaxFF parameterization.The procedure starts with a Latin Hypercube Design(LHD)algorithm that is used to explore the parameter landscape extensively.The LHD passes the information about explored regions to a deep learning model,which finds the minimum discrepancy regions and eliminates unfeasible regions,and constructs a more comprehensive understanding of physically meaningful parameter space.We demonstrate the procedure here for the parameterization of a nickel–chromium binary force field and a tungsten–sulfide–carbon–oxygen–hydrogen quinary force field.We show that INDEEDopt produces improved accuracies in shorter development time compared to the conventional optimization method.
基金This project is partly supported by the University of Alabama,the NSF-CAREER under the NSF cooperative agreement CBET-20426832D Crystal Consortium–Material Innovation Platform(2DCC-MIP)under NSF cooperative agreements DMR-1539916 and DMR-2039351+1 种基金the I/UCRC Center for Atomically Thin Multifunctional Coatings(ATOMIC)seed project SP001-17Y.Z.J.and L.Q.C.also acknowledge the generous support by the Hamer Foundation through a Hamer Professorship.
文摘Reproducible wafer-scale growth of two-dimensional(2D)materials using the Chemical Vapor Deposition(CVD)process with precise control over their properties is challenging due to a lack of understanding of the growth mechanisms spanning over several length scales and sensitivity of the synthesis to subtle changes in growth conditions.A multiscale computational framework coupling Computational Fluid Dynamics(CFD),Phase-Field(PF),and reactive Molecular Dynamics(MD)was developed–called the CPM model–and experimentally verified.Correlation between theoretical predictions and thorough experimental measurements for a Metal-Organic CVD(MOCVD)-grown WSe_(2)model material revealed the full power of this computational approach.Large-area uniform 2D materials are synthesized via MOCVD,guided by computational analyses.The developed computational framework provides the foundation for guiding the synthesis of wafer-scale 2D materials with precise control over the coverage,morphology,and properties,a critical capability for fabricating electronic,optoelectronic,and quantum computing devices.
