An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, clo...An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.展开更多
Software engineering is broadly discussed as falling far short of expectations. Data and examples are used to justify how software itself is often poor, how the engineering of software leaves much to be desired, and h...Software engineering is broadly discussed as falling far short of expectations. Data and examples are used to justify how software itself is often poor, how the engineering of software leaves much to be desired, and how research in software engineering has not made enough progress to help overcome these weaknesses. However, these data and examples are presented and interpreted in ways that are arguably imbalanced. This imbalance, usually taken at face value, may be distracting the field from making significant progress towards improving the effective engineering of software, a goal the entire community shares. Research dichotomies, which tend to pit one approach against another, often subtly hint that there is a best way to engineer software or a best way to perform research on software. This, too, may be distracting the field from important classes of progress.展开更多
Strategies for CADD vary depending on the extent of structural and other information available regarding the target (enzyme/receptor) and the ligands. Computer-aided drug design (CADD) is an exciting and diverse disci...Strategies for CADD vary depending on the extent of structural and other information available regarding the target (enzyme/receptor) and the ligands. Computer-aided drug design (CADD) is an exciting and diverse discipline where various aspects of applied and basic research merge and stimulate each other. In the early stage of a drug discovery process, researchers may be faced with little or no structure activity relationship (SAR) information. The process by which a new drug is brought to market stage is referred to by a number of names most commonly as the development chain or “pipeline” and consists of a number of distinct stages. To design a rational drug, we must firstly find out which proteins can be the drug targets in pathogenesis. In present review we reported a brief history of CADD, DNA as target, receptor theory, structure optimization, structure-based drug design, virtual high-throughput screening (vHTS), graph machines.展开更多
Due to 5G's stringent and uncertainty traffic requirements,open ecosystem would be one inevitable way to develop 5G.On the other hand,GPP based mobile communication becomes appealing recently attributed to its str...Due to 5G's stringent and uncertainty traffic requirements,open ecosystem would be one inevitable way to develop 5G.On the other hand,GPP based mobile communication becomes appealing recently attributed to its striking advantage in flexibility and re-configurability.In this paper,both the advantages and challenges of GPP platform are detailed analyzed.Furthermore,both GPP based software and hardware architectures for open 5G are presented and the performances of real-time signal processing and power consumption are also evaluated.The evaluation results indicate that turbo and power consumption may be another challengeable problem should be further solved to meet the requirements of realistic deployments.展开更多
Aiming at the problems of low prediction accuracy and weak generalization ability of current reliability prediction models,this paper proposes a hybrid multi-layer heterogeneous particle swarm optimization algorithm(H...Aiming at the problems of low prediction accuracy and weak generalization ability of current reliability prediction models,this paper proposes a hybrid multi-layer heterogeneous particle swarm optimization algorithm(HMHPSO)that can simultaneously optimize the structure and parameters of the GRU neural network.It first introduced a multi-layer heteromass particle swarm optimization(MHPSO)algorithm,which sets the population topology as a hierarchical structure and introduces the concept of attractors,so as to improve the update formula of particle speed,and enhance the information interaction ability between particles,increase the diversity of the groups,thereby improving the optimization ability of the algorithm.Then the HMHPSO used the quantum particle swarm optimization(QPSO)algorithm to determine the structure of the GRU,that is,the number of hidden nodes.Experimental results show that the algorithm can generate GRU neural networks with high generalization performance and low architecture complexity,and has better prediction accuracy in software reliability prediction.展开更多
基金Project(51274250)supported by the National Natural Science Foundation of ChinaProject(2012BAK09B02-05)supported by the National Key Technology R&D Program during the 12th Five-year Plan of China
文摘An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.
文摘Software engineering is broadly discussed as falling far short of expectations. Data and examples are used to justify how software itself is often poor, how the engineering of software leaves much to be desired, and how research in software engineering has not made enough progress to help overcome these weaknesses. However, these data and examples are presented and interpreted in ways that are arguably imbalanced. This imbalance, usually taken at face value, may be distracting the field from making significant progress towards improving the effective engineering of software, a goal the entire community shares. Research dichotomies, which tend to pit one approach against another, often subtly hint that there is a best way to engineer software or a best way to perform research on software. This, too, may be distracting the field from important classes of progress.
文摘Strategies for CADD vary depending on the extent of structural and other information available regarding the target (enzyme/receptor) and the ligands. Computer-aided drug design (CADD) is an exciting and diverse discipline where various aspects of applied and basic research merge and stimulate each other. In the early stage of a drug discovery process, researchers may be faced with little or no structure activity relationship (SAR) information. The process by which a new drug is brought to market stage is referred to by a number of names most commonly as the development chain or “pipeline” and consists of a number of distinct stages. To design a rational drug, we must firstly find out which proteins can be the drug targets in pathogenesis. In present review we reported a brief history of CADD, DNA as target, receptor theory, structure optimization, structure-based drug design, virtual high-throughput screening (vHTS), graph machines.
基金funded in part by National Natural Science Foundation of China(grant NO.61471347)National S&T Mayor Project of the Ministry of S&T of China(grant NO.2016ZX03001020-003)+1 种基金key program for international S&T Cooperation Program of China(grant NO.2014DFA11640)Shanghai Natural Science Foundation(grant NO.16ZR1435100)
文摘Due to 5G's stringent and uncertainty traffic requirements,open ecosystem would be one inevitable way to develop 5G.On the other hand,GPP based mobile communication becomes appealing recently attributed to its striking advantage in flexibility and re-configurability.In this paper,both the advantages and challenges of GPP platform are detailed analyzed.Furthermore,both GPP based software and hardware architectures for open 5G are presented and the performances of real-time signal processing and power consumption are also evaluated.The evaluation results indicate that turbo and power consumption may be another challengeable problem should be further solved to meet the requirements of realistic deployments.
文摘Aiming at the problems of low prediction accuracy and weak generalization ability of current reliability prediction models,this paper proposes a hybrid multi-layer heterogeneous particle swarm optimization algorithm(HMHPSO)that can simultaneously optimize the structure and parameters of the GRU neural network.It first introduced a multi-layer heteromass particle swarm optimization(MHPSO)algorithm,which sets the population topology as a hierarchical structure and introduces the concept of attractors,so as to improve the update formula of particle speed,and enhance the information interaction ability between particles,increase the diversity of the groups,thereby improving the optimization ability of the algorithm.Then the HMHPSO used the quantum particle swarm optimization(QPSO)algorithm to determine the structure of the GRU,that is,the number of hidden nodes.Experimental results show that the algorithm can generate GRU neural networks with high generalization performance and low architecture complexity,and has better prediction accuracy in software reliability prediction.
