The performance of proton exchange membrane fuel cells depends heavily on the oxygen reduction reaction(ORR)at the cathode,for which platinum-based catalysts are currently the standard.The high cost and limited availa...The performance of proton exchange membrane fuel cells depends heavily on the oxygen reduction reaction(ORR)at the cathode,for which platinum-based catalysts are currently the standard.The high cost and limited availability of platinum have driven the search for alternative catalysts.While FeN4 single-atom catalysts have shown promising potential,their ORR activity needs to be further enhanced.In contrast,dual-atom catalysts(DACs)offer not only higher metal loading but also the ability to break the ORR scaling relations.However,the diverse local structures and tunable coordination environments of DACs create a vast chemical space,making large-scale computational screening challenging.In this study,we developed a graph neural network(GNN)-based framework to predict the ORR activity of Fe-based DACs,effectively addressing the challenges posed by variations in local catalyst structures.Our model,trained on a dataset of 180 catalysts,accurately predicted the Gibbs free energy of ORR intermediates and overpotentials,and identified 32 DACs with superior catalytic activity compared to FeN4 SAC.This approach not only advances the design of high-performance DACs,but also offers a powerful computational tool that can significantly reduce the time and cost of catalyst development,thereby accelerating the commercialization of fuel cell technologies.展开更多
A systematic investigation is made on the problems which are related to the optimal control of the municipal water distribution network.A mathematical model of forecasting the water short term demand is proposed using...A systematic investigation is made on the problems which are related to the optimal control of the municipal water distribution network.A mathematical model of forecasting the water short term demand is proposed using the time series trigonometric function analysis method;the service discharge based macroscopic model of network performance is established using the network structuring method;a relatively satisfactory mathematical model for the optimal control of water distribution network is put forward in view of security and economy,and solved by the constrained mixed discrete variable complex arithmetic.The model is applied in many examples and the results are satisfactory.展开更多
A novel methodology is presented for simultaneously optimizing synthesis and cleaning schedule of flexible heat exchanger network(HEN)by genetic/simulated annealing algorithms(GA/SA).Through taking into account the ef...A novel methodology is presented for simultaneously optimizing synthesis and cleaning schedule of flexible heat exchanger network(HEN)by genetic/simulated annealing algorithms(GA/SA).Through taking into account the effect of fouling process on optimal network topology,a preliminary network structure possessing two-fold oversynthesis is obtained by means of pseudo-temperature enthalpy(T-H)diagram approach prior to simultaneous optimization.Thus,the computational complexity of this problem classified as NP(Non-deterministic Polynomial)-complete can be significantly reduced.The promising matches resulting from preliminary synthesis stage are further optimized in parallel with their heat exchange areas and cleaning schedule.In addition,a novel continu- ous time representation is introduced to subdivide the given time horizon into several variable-size intervals according to operating periods of heat exchangers,and then flexible HEN synthesis can be implemented in dynamic manner.A numerical example is provided to demonstrate that the presented strategy is feasible to decrease the total annual cost(TAC)and further improve network flexibility,but even more important,it may be applied to solve large-scale flexible HEN synthesis problems.展开更多
Two modes of regulating the water quality of experimental ponds in indoor raceway culture of Litopenaeus vannamei were evaluated using simple water treatment facilities. A self-made water purifying net, aeration stone...Two modes of regulating the water quality of experimental ponds in indoor raceway culture of Litopenaeus vannamei were evaluated using simple water treatment facilities. A self-made water purifying net, aeration stone, composite microbe preparation, and Ceratophyllum demersum were placed in the experimental ponds and the culture water was circulated along the raceway inside the pond using a paddle wheel aerator. In addition, the water quality in the experimental pond was improved by draining effluent from the pipeline at the bottom of ponds 7 and 8 (mode I) and exchanging the circulating water in pond 10 (mode Ⅱ) with the reservoir water in pond 9 using a pump and pipeline. The water quality in the experimental ponds was similar in response to regulation using mode Ⅰ or mode Ⅱ. Water quality parameters in the experimental ponds were controlled within a suitable range by simple facilities during culture period without using any chemical treatments. The rich content of dissolved oxygen was maintained by the circular flow and continuous aeration of the pond water. The respective average values of the main water parameters in experimental ponds 7 and 10 in response to regulation of the water quality using modes Ⅰ and Ⅱwere as follows: pH 8.17 and 7.99; DO 5.16 mg/L and 5.97 mg/L; CODMn18.45 and 12.61 mg/L; TAN (NH3-N) 0.854 mg/L (0.087 mg/L) and 0.427 mg/L (0.012 mg/L); NO2-N 0.489 mg/L and 0.337 mg/L. Moreover, the average body length and body weight of harvested shrimp of pond 7 and pond l0 were 7.56 cm and 8.99 cm, 5.10 g and 8.33 g, respectively. Furthermore, the survival rate, average biomass yield and average condition factor of the shrimp harvested were 70% and 60%, 2.54 kg/m2 and 2.14 kg/m2, and 0.675 g/cm and 0.927 g/cm, respectively. Linear equations describing the relationship between body length and culture time and cubic or power functions describing the relationship between body weight and body length were obtained based on evaluation of the growth data of shrimps throughout the culture period.展开更多
We presented a clock synchronization method that contained a clock adjusting algorithm and a frequency compensated clock to achieve precise synchronization among distributed clocks based on IEEE 1588 protocol.Further,...We presented a clock synchronization method that contained a clock adjusting algorithm and a frequency compensated clock to achieve precise synchronization among distributed clocks based on IEEE 1588 protocol.Further,we presented its application on Ethernet and implementation of the frequency compensated clock in a field programmable gate array(FPGA) as experiments.The results indicate that this method can support sub-microsecond synchronization with inexpensive standard crystal oscillators.展开更多
Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they ...Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.展开更多
A new analytical method using Back-Propagation (BP) artificial neural network and kinetic spectrophotometry for simultaneous determination of iron and magnesium in tap water, the Yellow River water and seawater is est...A new analytical method using Back-Propagation (BP) artificial neural network and kinetic spectrophotometry for simultaneous determination of iron and magnesium in tap water, the Yellow River water and seawater is established. By conditional experiments, the optimum analytical conditions and parameters are obtained. Levenberg-Marquart (L-M) algorithm is used for calculation in BP neural network. The topological structure of three-layer BP ANN network architecture is chosen as 15-16-2 (nodes). The initial value of gradient coefficient μ is fixed at 0.001 and the increase factor and reduction factor of μ take the default values of the system. The data are processed by computers with our own programs written in MATLAB 7.0. The relative standard deviation of the calculated results for iron and manganese is 2.30% and 2.67% respectively. The results of standard addition method show that for the tap water, the recoveries of iron and manganese are in the ranges of 98.0%-104.3% and 96.5%-104.5%, and the RSD is in the range of 0.23%-0.98%; for the Yellow River water (Lijin district of Shandong Province), the recoveries of iron and manganese are in the ranges of 96.0%-101.0% and 98.7%-104.2%, and the RSD is in the range of 0.13%-2.52%; for the seawater in Qingdao offshore, the recoveries of iron and manganese are in the ranges of 95.3%-104.8% and 95.3%-104.7%, and the RSD is in the range of 0.14%-2.66%. It is found that 21 common cations and anions do not interfere with the determination of iron and manganese under the optimum experimental conditions. This method exhibits good reproducibility and high accuracy in the determination of iron and manganese and can be used for the simultaneous determination of iron and manganese in tap water and natural water. By using the established ANN- catalytic spectrophotometric method, the iron and manganese concentrations of the surface seawater at 11 sites in Qingdao offshore are determined and the level distribution maps of iron and manganese are drawn.展开更多
Effects of vertex activity have been analyzed on a weighted evolving network.The network is characterized by the probability distribution of vertex strength,each edge weight and evolution of the strength of vertices w...Effects of vertex activity have been analyzed on a weighted evolving network.The network is characterized by the probability distribution of vertex strength,each edge weight and evolution of the strength of vertices with different vertex activities.The model exhibits self-organized criticality behavior.The probability distribution of avalanche size for different network sizes is also shown.In addition,there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities.展开更多
To improve the training efficiency and recommendation accuracy in cold-start interactive recommendation systems,a new graph structure called item similarity graph is proposed on the basis of real data from a public da...To improve the training efficiency and recommendation accuracy in cold-start interactive recommendation systems,a new graph structure called item similarity graph is proposed on the basis of real data from a public dataset.The proposed graph is built from collaborative interactions and a deep reinforcement learning-based graph-enhanced neural interactive collaborative filtering(GE-ICF)model.The GE-ICF framework is developed with a deep reinforcement learning framework and comprises an embedding propagation layer designed with graph neural networks.Extensive experiments are conducted to investigate the efficiency of the proposed graph structure and the superiority of the proposed GE-ICF framework.Results show that in cold-start interactive recommendation systems,the proposed item similarity graph performs well in data relationship modeling,with the training efficiency showing significant improvement.The proposed GE-ICF framework also demonstrates superiority in decision modeling,thereby increasing the recommendation accuracy remarkably.展开更多
In this paper, based on the characteristics of polar codes, a new decode-and-forward strategy called generalized partial information relaying protocol is proposed for degraded multiple-relay networks with orthogonal r...In this paper, based on the characteristics of polar codes, a new decode-and-forward strategy called generalized partial information relaying protocol is proposed for degraded multiple-relay networks with orthogonal receiver components(MRNORCs). In such a protocol, with the help of partial information from previous nodes, each relay node tries to recover the received source message and re-encodes part of the decoded message for transmission to satisfy the decoding requirements for the following relay node or the destination node. In order to construct practical polar codes, the nested structures are developed based on this protocol and the information sets corresponding to the partial messages forwarded are also calculated. The proposed scheme is proved to be capable of achieving the theoretical capacity of the degraded MRN-ORCs while still retains the low-complexity feature of polar codes. We perform simulations to testify the practicability of the proposed scheme and compare polar codes by using successive-cancellation list decoder(SCLD) with traditional low-density parity-check(LDPC) codes. The results show that the obtained polar codes provide significant gain.展开更多
As an analytical method, the effective-field theory (EFT) is used to study the dynamical response of the kinetic Ising model in the presence of a sinusoidal oscillating field. The effective-field equations of motion...As an analytical method, the effective-field theory (EFT) is used to study the dynamical response of the kinetic Ising model in the presence of a sinusoidal oscillating field. The effective-field equations of motion of the average magnetization are given for the honeycomb lattice (Z = 3). The Liapunov exponent A is calculated for discussing the stability of the magnetization and it is used to determine the phase boundary. In the field amplitude ho / ZJ-temperature T/ZJ plane, the phase boundary separating the dynamic ordered and the disordered phase has been drawn. In contrast to previous analytical results that predicted a tricritical point separating a dynamic phase boundary line of continuous and discontinuous transitions, we find that the transition is always continuous. There is inconsistency between our results and previous analytical results, because they do not introduce sufficiently strong fluctuations.展开更多
Based on the CNN-LSTM fusion deep neural network,this paper proposes a seismic velocity model building method that can simultaneously estimate the root mean square(RMS)velocity and interval velocity from the common-mi...Based on the CNN-LSTM fusion deep neural network,this paper proposes a seismic velocity model building method that can simultaneously estimate the root mean square(RMS)velocity and interval velocity from the common-midpoint(CMP)gather.In the proposed method,a convolutional neural network(CNN)Encoder and two long short-term memory networks(LSTMs)are used to extract spatial and temporal features from seismic signals,respectively,and a CNN Decoder is used to recover RMS velocity and interval velocity of underground media from various feature vectors.To address the problems of unstable gradients and easily fall into a local minimum in the deep neural network training process,we propose to use Kaiming normal initialization with zero negative slopes of rectifi ed units and to adjust the network learning process by optimizing the mean square error(MSE)loss function with the introduction of a freezing factor.The experiments on testing dataset show that CNN-LSTM fusion deep neural network can predict RMS velocity as well as interval velocity more accurately,and its inversion accuracy is superior to that of single neural network models.The predictions on the complex structures and Marmousi model are consistent with the true velocity variation trends,and the predictions on fi eld data can eff ectively correct the phase axis,improve the lateral continuity of phase axis and quality of stack section,indicating the eff ectiveness and decent generalization capability of the proposed method.展开更多
In order to evaluate the effects of mesh generation techniques and grid convergence on pump performance in centrifugal pump model, three widely used mesh styles including structured hexahedral, unstructured tetrahedra...In order to evaluate the effects of mesh generation techniques and grid convergence on pump performance in centrifugal pump model, three widely used mesh styles including structured hexahedral, unstructured tetrahedral and hybrid prismatic/tetrahedral meshes were generated for a centrifugal pump model. And quantitative grid convergence was assessed based on a grid convergence index(GCI), which accounts for the degree of grid refinement. The structured, unstructured or hybrid meshes are found to have certain difference for velocity distributions in impeller with the change of grid cell number. And the simulation results have errors to different degrees compared with experimental data. The GCI-value for structured meshes calculated is lower than that for the unstructured and hybrid meshes. Meanwhile, the structured meshes are observed to get more vortexes in impeller passage.Nevertheless, the hybrid meshes are found to have larger low-velocity area at outlet and more secondary vortexes at a specified location than structured meshes and unstructured meshes.展开更多
A riverhead is the demarcation point of continuous water channel and seasonal channel, which is characterized by a criti- cal flow that can support a continuous water body. In this study, the critical support dischar...A riverhead is the demarcation point of continuous water channel and seasonal channel, which is characterized by a criti- cal flow that can support a continuous water body. In this study, the critical support discharge (CSD) is defined as the critical steady flows required to form the origin of a stream. The CSD is used as the criterion to determine the beginning of the riverhead, which can be controlled by hydro-climate factors (e.g., annual precipitation, annual evaporation, or minimum stream flow in arid season). The CSD has a close correlation with the critical support/source area (CSA) that largely affects the density of the river network and the division of sub-watersheds. In general, river density may vary with regional meteorological and hydrological conditions that have to be considered in the analysis. In this paper, a new model referring to the relationship of CSA and CSD is proposed, which is based on the physical mechanism for the origin of riverheads. The feasibility of the model was verified using two watersheds (Duilongqu Basin of the Lhasa River and Beishuiqu Basin of the Nyangqu River) in Tibet Autonomous Region to calculate the CSA and extract river networks. A series of CSAs based on different CSDs in derived equation were tested by comparing the extracted river networks with the reference network obtained from a digitized map of river network at large scales. Comparison results of river networks derived from digital elevation model with real ones indicate that the CSD (equal to criterion of flow quantity (Qc)) are 0.0028 m3/s in Duilongqu and 0.0085 m3/s in Beishuiqu. Results show that the Qc can vary with hydro-climate conditions. The Qc is high in humid region and low in arid region, and the optimal Qo of 0.0085 m3/s in Beishuiqu Basin (humid region) is higher than 0.0028 m3/s in Duilongqu Basin (semi-arid region). The suggested method provides a new application approach that can be used to determine the Qo of a riverhead in complex geographical regions, which can also reflect the effect of hydro-climate change on rivers supply in different regions.展开更多
In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions (ff) in 2009. The authors built and trained 29 Elman neural net-...In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions (ff) in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data (1979-2008) from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System (GEOS)-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.展开更多
A modified evolution model of self-organized criticality on generalized Barabasi-Albert (GBA).scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behavi...A modified evolution model of self-organized criticality on generalized Barabasi-Albert (GBA).scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.展开更多
Using structured mesh to discretize the calculation region, the wind velocity and pressure distribution in front of the wind barrier under different embankment heights are investigated based on the Detached Eddy Simul...Using structured mesh to discretize the calculation region, the wind velocity and pressure distribution in front of the wind barrier under different embankment heights are investigated based on the Detached Eddy Simulation(DES) with standard SpalartAllmaras(SA) model. The Reynolds number is 4.0×105 in this calculation. The region is three-dimensional. Since the wind barrier and trains are almost invariable cross-sections, only 25 m along the track is modeled. The height of embankment ranges from 1 m to 5 m and the wind barrier is 3 m high. The results show that the wind speed changes obviously before the wind barrier on the horizontal plane, which is 4.5 m high above the track. The speed of wind reduces gradually while approaching the wind barrier. It reaches the minimum value at a distance about 5 m before the wind barrier, and increases dramatically afterwards. The speed of wind at this location is linear with the speed of far field. The train aerodynamic coefficients decrease sharply with the increment of the embankment height. And they take up the monotonicity. Meanwhile, when the height increases from 3 m to 5 m, they just change slightly. It is concluded that the optimum anemometer location is nearly 5 m in front of the wind barrier.展开更多
The fully connected Hopfield network is inferred based on observed magnetizations and pairwise correlations.We present the system in the glassy phase with low temperature and high memory load.We find that the inferenc...The fully connected Hopfield network is inferred based on observed magnetizations and pairwise correlations.We present the system in the glassy phase with low temperature and high memory load.We find that the inference error is very sensitive to the form of state sampling.When a single state is sampled to compute magnetizations and correlations,the inference error is almost indistinguishable irrespective of the sampled state.However,the error can be greatly reduced if the data is collected with state transitions.Our result holds for different disorder samples and accounts for the previously observed large fluctuations of inference error at low temperatures.展开更多
A new superstructure model of heat exchanger networks (HEN) with streamsplits based on rangers of streams supply temperatures and heat capacity flow rates is presented.The simultaneous optimal mathematical model of fl...A new superstructure model of heat exchanger networks (HEN) with streamsplits based on rangers of streams supply temperatures and heat capacity flow rates is presented.The simultaneous optimal mathematical model of flexible HEN synthesis is established too. Firstly,the streams with rangers of supply temperatures and/or the streams with the rangers of heat capacityflow rates are pretreated; Secondly, several rules are proposed to establish the superstructuremodel of HEN with splits and the simultaneous optimal mathematical model of flexible HEN; Thirdly,the improving genetic algorithm is applied to solve the mathematical model established at the secondstep effectively, and the original optimal structure of HEN based on the maximum operation limitingcondition can be obtained easily; Finally, the rules of heat exchange unit merged and the heat loadof heat exchanger relaxed are presented, the flexible configuration of HEN satisfied the operationcondition between the upper and down bounds of supply temperature and heat capacity flow rates canbe obtained based on the original optimal structure of HEN by means of these rules. A case studydemonstrates the method presented in this paper is effective展开更多
基金This work was supported by the National Natural Science Foundation of China(No.22473001)the Natural Science Funds for Distinguished Young Scholar of Anhui Province(1908085J08)the University An-nual Scientific Research Plan of Anhui Province(2022AH010013).
文摘The performance of proton exchange membrane fuel cells depends heavily on the oxygen reduction reaction(ORR)at the cathode,for which platinum-based catalysts are currently the standard.The high cost and limited availability of platinum have driven the search for alternative catalysts.While FeN4 single-atom catalysts have shown promising potential,their ORR activity needs to be further enhanced.In contrast,dual-atom catalysts(DACs)offer not only higher metal loading but also the ability to break the ORR scaling relations.However,the diverse local structures and tunable coordination environments of DACs create a vast chemical space,making large-scale computational screening challenging.In this study,we developed a graph neural network(GNN)-based framework to predict the ORR activity of Fe-based DACs,effectively addressing the challenges posed by variations in local catalyst structures.Our model,trained on a dataset of 180 catalysts,accurately predicted the Gibbs free energy of ORR intermediates and overpotentials,and identified 32 DACs with superior catalytic activity compared to FeN4 SAC.This approach not only advances the design of high-performance DACs,but also offers a powerful computational tool that can significantly reduce the time and cost of catalyst development,thereby accelerating the commercialization of fuel cell technologies.
基金Foundation for University Key Teacher by the Min-istry of Education
文摘A systematic investigation is made on the problems which are related to the optimal control of the municipal water distribution network.A mathematical model of forecasting the water short term demand is proposed using the time series trigonometric function analysis method;the service discharge based macroscopic model of network performance is established using the network structuring method;a relatively satisfactory mathematical model for the optimal control of water distribution network is put forward in view of security and economy,and solved by the constrained mixed discrete variable complex arithmetic.The model is applied in many examples and the results are satisfactory.
基金Supported by the National Natural Science Foundation of China (20976022) and Dalian University of Technology for Constructing Interdiscipline 'Energy+X'. ACKNOWLEDGEMENTS The authors gratefully acknowledge financial support from Lanzhou Petrochemical Company, PetroChina Company Limited.
文摘A novel methodology is presented for simultaneously optimizing synthesis and cleaning schedule of flexible heat exchanger network(HEN)by genetic/simulated annealing algorithms(GA/SA).Through taking into account the effect of fouling process on optimal network topology,a preliminary network structure possessing two-fold oversynthesis is obtained by means of pseudo-temperature enthalpy(T-H)diagram approach prior to simultaneous optimization.Thus,the computational complexity of this problem classified as NP(Non-deterministic Polynomial)-complete can be significantly reduced.The promising matches resulting from preliminary synthesis stage are further optimized in parallel with their heat exchange areas and cleaning schedule.In addition,a novel continu- ous time representation is introduced to subdivide the given time horizon into several variable-size intervals according to operating periods of heat exchangers,and then flexible HEN synthesis can be implemented in dynamic manner.A numerical example is provided to demonstrate that the presented strategy is feasible to decrease the total annual cost(TAC)and further improve network flexibility,but even more important,it may be applied to solve large-scale flexible HEN synthesis problems.
基金Supported by the Shanghai Commission of Science and Technology (No.063919112073919102)the Shanghai Agricultural Committee (No.2006,9-4)
文摘Two modes of regulating the water quality of experimental ponds in indoor raceway culture of Litopenaeus vannamei were evaluated using simple water treatment facilities. A self-made water purifying net, aeration stone, composite microbe preparation, and Ceratophyllum demersum were placed in the experimental ponds and the culture water was circulated along the raceway inside the pond using a paddle wheel aerator. In addition, the water quality in the experimental pond was improved by draining effluent from the pipeline at the bottom of ponds 7 and 8 (mode I) and exchanging the circulating water in pond 10 (mode Ⅱ) with the reservoir water in pond 9 using a pump and pipeline. The water quality in the experimental ponds was similar in response to regulation using mode Ⅰ or mode Ⅱ. Water quality parameters in the experimental ponds were controlled within a suitable range by simple facilities during culture period without using any chemical treatments. The rich content of dissolved oxygen was maintained by the circular flow and continuous aeration of the pond water. The respective average values of the main water parameters in experimental ponds 7 and 10 in response to regulation of the water quality using modes Ⅰ and Ⅱwere as follows: pH 8.17 and 7.99; DO 5.16 mg/L and 5.97 mg/L; CODMn18.45 and 12.61 mg/L; TAN (NH3-N) 0.854 mg/L (0.087 mg/L) and 0.427 mg/L (0.012 mg/L); NO2-N 0.489 mg/L and 0.337 mg/L. Moreover, the average body length and body weight of harvested shrimp of pond 7 and pond l0 were 7.56 cm and 8.99 cm, 5.10 g and 8.33 g, respectively. Furthermore, the survival rate, average biomass yield and average condition factor of the shrimp harvested were 70% and 60%, 2.54 kg/m2 and 2.14 kg/m2, and 0.675 g/cm and 0.927 g/cm, respectively. Linear equations describing the relationship between body length and culture time and cubic or power functions describing the relationship between body weight and body length were obtained based on evaluation of the growth data of shrimps throughout the culture period.
基金the Natural Science Foundation of Hubei (No.2006ABA065)
文摘We presented a clock synchronization method that contained a clock adjusting algorithm and a frequency compensated clock to achieve precise synchronization among distributed clocks based on IEEE 1588 protocol.Further,we presented its application on Ethernet and implementation of the frequency compensated clock in a field programmable gate array(FPGA) as experiments.The results indicate that this method can support sub-microsecond synchronization with inexpensive standard crystal oscillators.
基金Supported by the National Science and Technology Major Project (No.2011ZX03005-004-04)the National Grand Fundamental Research 973 Program of China (No.2011CB302-905)+2 种基金the National Natural Science Foundation of China (No.61170058,61272133,and 51274202)the Research Fund for the Doctoral Program of Higher Education of China (No.20103402110041)the Suzhou Fundamental Research Project (No.SYG201143)
文摘Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.
文摘A new analytical method using Back-Propagation (BP) artificial neural network and kinetic spectrophotometry for simultaneous determination of iron and magnesium in tap water, the Yellow River water and seawater is established. By conditional experiments, the optimum analytical conditions and parameters are obtained. Levenberg-Marquart (L-M) algorithm is used for calculation in BP neural network. The topological structure of three-layer BP ANN network architecture is chosen as 15-16-2 (nodes). The initial value of gradient coefficient μ is fixed at 0.001 and the increase factor and reduction factor of μ take the default values of the system. The data are processed by computers with our own programs written in MATLAB 7.0. The relative standard deviation of the calculated results for iron and manganese is 2.30% and 2.67% respectively. The results of standard addition method show that for the tap water, the recoveries of iron and manganese are in the ranges of 98.0%-104.3% and 96.5%-104.5%, and the RSD is in the range of 0.23%-0.98%; for the Yellow River water (Lijin district of Shandong Province), the recoveries of iron and manganese are in the ranges of 96.0%-101.0% and 98.7%-104.2%, and the RSD is in the range of 0.13%-2.52%; for the seawater in Qingdao offshore, the recoveries of iron and manganese are in the ranges of 95.3%-104.8% and 95.3%-104.7%, and the RSD is in the range of 0.14%-2.66%. It is found that 21 common cations and anions do not interfere with the determination of iron and manganese under the optimum experimental conditions. This method exhibits good reproducibility and high accuracy in the determination of iron and manganese and can be used for the simultaneous determination of iron and manganese in tap water and natural water. By using the established ANN- catalytic spectrophotometric method, the iron and manganese concentrations of the surface seawater at 11 sites in Qingdao offshore are determined and the level distribution maps of iron and manganese are drawn.
基金supported by National Natural Science Foundation of China under Grant No.10675060
文摘Effects of vertex activity have been analyzed on a weighted evolving network.The network is characterized by the probability distribution of vertex strength,each edge weight and evolution of the strength of vertices with different vertex activities.The model exhibits self-organized criticality behavior.The probability distribution of avalanche size for different network sizes is also shown.In addition,there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities.
基金The National Natural Science Foundation of China(No.62173251)the Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control,the Fundamental Research Funds for the Central Universities.
文摘To improve the training efficiency and recommendation accuracy in cold-start interactive recommendation systems,a new graph structure called item similarity graph is proposed on the basis of real data from a public dataset.The proposed graph is built from collaborative interactions and a deep reinforcement learning-based graph-enhanced neural interactive collaborative filtering(GE-ICF)model.The GE-ICF framework is developed with a deep reinforcement learning framework and comprises an embedding propagation layer designed with graph neural networks.Extensive experiments are conducted to investigate the efficiency of the proposed graph structure and the superiority of the proposed GE-ICF framework.Results show that in cold-start interactive recommendation systems,the proposed item similarity graph performs well in data relationship modeling,with the training efficiency showing significant improvement.The proposed GE-ICF framework also demonstrates superiority in decision modeling,thereby increasing the recommendation accuracy remarkably.
基金supported by the National Natural Science Foundation of China (No.41574137, 41304117)
文摘In this paper, based on the characteristics of polar codes, a new decode-and-forward strategy called generalized partial information relaying protocol is proposed for degraded multiple-relay networks with orthogonal receiver components(MRNORCs). In such a protocol, with the help of partial information from previous nodes, each relay node tries to recover the received source message and re-encodes part of the decoded message for transmission to satisfy the decoding requirements for the following relay node or the destination node. In order to construct practical polar codes, the nested structures are developed based on this protocol and the information sets corresponding to the partial messages forwarded are also calculated. The proposed scheme is proved to be capable of achieving the theoretical capacity of the degraded MRN-ORCs while still retains the low-complexity feature of polar codes. We perform simulations to testify the practicability of the proposed scheme and compare polar codes by using successive-cancellation list decoder(SCLD) with traditional low-density parity-check(LDPC) codes. The results show that the obtained polar codes provide significant gain.
文摘As an analytical method, the effective-field theory (EFT) is used to study the dynamical response of the kinetic Ising model in the presence of a sinusoidal oscillating field. The effective-field equations of motion of the average magnetization are given for the honeycomb lattice (Z = 3). The Liapunov exponent A is calculated for discussing the stability of the magnetization and it is used to determine the phase boundary. In the field amplitude ho / ZJ-temperature T/ZJ plane, the phase boundary separating the dynamic ordered and the disordered phase has been drawn. In contrast to previous analytical results that predicted a tricritical point separating a dynamic phase boundary line of continuous and discontinuous transitions, we find that the transition is always continuous. There is inconsistency between our results and previous analytical results, because they do not introduce sufficiently strong fluctuations.
基金financially supported by the Key Project of National Natural Science Foundation of China (No. 41930431)the Project of National Natural Science Foundation of China (Nos. 41904121, 41804133, and 41974116)Joint Guidance Project of Natural Science Foundation of Heilongjiang Province (No. LH2020D006)
文摘Based on the CNN-LSTM fusion deep neural network,this paper proposes a seismic velocity model building method that can simultaneously estimate the root mean square(RMS)velocity and interval velocity from the common-midpoint(CMP)gather.In the proposed method,a convolutional neural network(CNN)Encoder and two long short-term memory networks(LSTMs)are used to extract spatial and temporal features from seismic signals,respectively,and a CNN Decoder is used to recover RMS velocity and interval velocity of underground media from various feature vectors.To address the problems of unstable gradients and easily fall into a local minimum in the deep neural network training process,we propose to use Kaiming normal initialization with zero negative slopes of rectifi ed units and to adjust the network learning process by optimizing the mean square error(MSE)loss function with the introduction of a freezing factor.The experiments on testing dataset show that CNN-LSTM fusion deep neural network can predict RMS velocity as well as interval velocity more accurately,and its inversion accuracy is superior to that of single neural network models.The predictions on the complex structures and Marmousi model are consistent with the true velocity variation trends,and the predictions on fi eld data can eff ectively correct the phase axis,improve the lateral continuity of phase axis and quality of stack section,indicating the eff ectiveness and decent generalization capability of the proposed method.
基金Projects(51109095,51179075,51309119)supported by the National Natural Science Foundation of ChinaProject(BE2012131)supported by Science and Technology Support Program of Jiangsu Province,China
文摘In order to evaluate the effects of mesh generation techniques and grid convergence on pump performance in centrifugal pump model, three widely used mesh styles including structured hexahedral, unstructured tetrahedral and hybrid prismatic/tetrahedral meshes were generated for a centrifugal pump model. And quantitative grid convergence was assessed based on a grid convergence index(GCI), which accounts for the degree of grid refinement. The structured, unstructured or hybrid meshes are found to have certain difference for velocity distributions in impeller with the change of grid cell number. And the simulation results have errors to different degrees compared with experimental data. The GCI-value for structured meshes calculated is lower than that for the unstructured and hybrid meshes. Meanwhile, the structured meshes are observed to get more vortexes in impeller passage.Nevertheless, the hybrid meshes are found to have larger low-velocity area at outlet and more secondary vortexes at a specified location than structured meshes and unstructured meshes.
基金Under the auspices of National Natural Science Foundation of China(No.31070405)Knowledge Innovation Programs of Chinese Academy of Sciences(No.KZCX2-XB3-08)
文摘A riverhead is the demarcation point of continuous water channel and seasonal channel, which is characterized by a criti- cal flow that can support a continuous water body. In this study, the critical support discharge (CSD) is defined as the critical steady flows required to form the origin of a stream. The CSD is used as the criterion to determine the beginning of the riverhead, which can be controlled by hydro-climate factors (e.g., annual precipitation, annual evaporation, or minimum stream flow in arid season). The CSD has a close correlation with the critical support/source area (CSA) that largely affects the density of the river network and the division of sub-watersheds. In general, river density may vary with regional meteorological and hydrological conditions that have to be considered in the analysis. In this paper, a new model referring to the relationship of CSA and CSD is proposed, which is based on the physical mechanism for the origin of riverheads. The feasibility of the model was verified using two watersheds (Duilongqu Basin of the Lhasa River and Beishuiqu Basin of the Nyangqu River) in Tibet Autonomous Region to calculate the CSA and extract river networks. A series of CSAs based on different CSDs in derived equation were tested by comparing the extracted river networks with the reference network obtained from a digitized map of river network at large scales. Comparison results of river networks derived from digital elevation model with real ones indicate that the CSD (equal to criterion of flow quantity (Qc)) are 0.0028 m3/s in Duilongqu and 0.0085 m3/s in Beishuiqu. Results show that the Qc can vary with hydro-climate conditions. The Qc is high in humid region and low in arid region, and the optimal Qo of 0.0085 m3/s in Beishuiqu Basin (humid region) is higher than 0.0028 m3/s in Duilongqu Basin (semi-arid region). The suggested method provides a new application approach that can be used to determine the Qo of a riverhead in complex geographical regions, which can also reflect the effect of hydro-climate change on rivers supply in different regions.
基金supported by the Strategic Priority Research Program-Climate Change: Carbon Budget and Relevant Issues of the Chinese Academy of Sciences (Grant No. XDA05040000)the National Natural Science Foundation of China (Grant Nos. 41005023 and 41275046)
文摘In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions (ff) in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data (1979-2008) from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System (GEOS)-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.
基金The project supported by National Natural Science Foundation of China under Grant No. 90203008 and the Doctoral Foundation of Ministry of Education of China
文摘A modified evolution model of self-organized criticality on generalized Barabasi-Albert (GBA).scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.
基金Projects(51075401,U1334205)supported by the National Natural Science Foundation of ChinaProject(NCET-10-0833)supported by the New Century Excellent Talents in University,China+2 种基金Project supported by the Scholarship Award for Excellent Innovative Doctoral Student granted by Central South University,ChinaProject(2012T002-E)supported by the Science and Technology Research and Development Program of Ministry of Railway,ChinaProject(14JJ1003)supported by the Natural Science Foundation of Hunan Province,China
文摘Using structured mesh to discretize the calculation region, the wind velocity and pressure distribution in front of the wind barrier under different embankment heights are investigated based on the Detached Eddy Simulation(DES) with standard SpalartAllmaras(SA) model. The Reynolds number is 4.0×105 in this calculation. The region is three-dimensional. Since the wind barrier and trains are almost invariable cross-sections, only 25 m along the track is modeled. The height of embankment ranges from 1 m to 5 m and the wind barrier is 3 m high. The results show that the wind speed changes obviously before the wind barrier on the horizontal plane, which is 4.5 m high above the track. The speed of wind reduces gradually while approaching the wind barrier. It reaches the minimum value at a distance about 5 m before the wind barrier, and increases dramatically afterwards. The speed of wind at this location is linear with the speed of far field. The train aerodynamic coefficients decrease sharply with the increment of the embankment height. And they take up the monotonicity. Meanwhile, when the height increases from 3 m to 5 m, they just change slightly. It is concluded that the optimum anemometer location is nearly 5 m in front of the wind barrier.
基金Supported by the National Science Foundation of China under Grant Nos. 10774150,10834014the China 973-Program under Grant Nos. 2007CB935903 and HKUST605010
文摘The fully connected Hopfield network is inferred based on observed magnetizations and pairwise correlations.We present the system in the glassy phase with low temperature and high memory load.We find that the inference error is very sensitive to the form of state sampling.When a single state is sampled to compute magnetizations and correlations,the inference error is almost indistinguishable irrespective of the sampled state.However,the error can be greatly reduced if the data is collected with state transitions.Our result holds for different disorder samples and accounts for the previously observed large fluctuations of inference error at low temperatures.
基金Supported by the State Major Basic Research Department Program of China (No. G20000263) and the Deutsche Forschungs- gemeinschaft(DFG)(No. RO294/9).
文摘A new superstructure model of heat exchanger networks (HEN) with streamsplits based on rangers of streams supply temperatures and heat capacity flow rates is presented.The simultaneous optimal mathematical model of flexible HEN synthesis is established too. Firstly,the streams with rangers of supply temperatures and/or the streams with the rangers of heat capacityflow rates are pretreated; Secondly, several rules are proposed to establish the superstructuremodel of HEN with splits and the simultaneous optimal mathematical model of flexible HEN; Thirdly,the improving genetic algorithm is applied to solve the mathematical model established at the secondstep effectively, and the original optimal structure of HEN based on the maximum operation limitingcondition can be obtained easily; Finally, the rules of heat exchange unit merged and the heat loadof heat exchanger relaxed are presented, the flexible configuration of HEN satisfied the operationcondition between the upper and down bounds of supply temperature and heat capacity flow rates canbe obtained based on the original optimal structure of HEN by means of these rules. A case studydemonstrates the method presented in this paper is effective