Automatic pancreas segmentation plays a pivotal role in assisting physicians with diagnosing pancreatic diseases,facilitating treatment evaluations,and designing surgical plans.Due to the pancreas’s tiny size,signifi...Automatic pancreas segmentation plays a pivotal role in assisting physicians with diagnosing pancreatic diseases,facilitating treatment evaluations,and designing surgical plans.Due to the pancreas’s tiny size,significant variability in shape and location,and low contrast with surrounding tissues,achieving high segmentation accuracy remains challenging.To improve segmentation precision,we propose a novel network utilizing EfficientNetV2 and multi-branch structures for automatically segmenting the pancreas fromCT images.Firstly,an EfficientNetV2 encoder is employed to extract complex and multi-level features,enhancing the model’s ability to capture the pancreas’s intricate morphology.Then,a residual multi-branch dilated attention(RMDA)module is designed to suppress irrelevant background noise and highlight useful pancreatic features.And re-parameterization Visual Geometry Group(RepVGG)blocks with amulti-branch structure are introduced in the decoder to effectively integrate deep features and low-level details,improving segmentation accuracy.Furthermore,we apply re-parameterization to the model,reducing computations and parameters while accelerating inference and reducing memory usage.Our approach achieves average dice similarity coefficient(DSC)of 85.59%,intersection over union(IoU)of 75.03%,precision of 85.09%,and recall of 86.57%on the NIH pancreas dataset.Compared with other methods,our model has fewer parameters and faster inference speed,demonstrating its enormous potential in practical applications of pancreatic segmentation.展开更多
Based on the finite element-discrete element numerical method,a numerical model of fracture propagation in deflagration fracturing was established by considering the impact of stress wave,quasi-static pressure of expl...Based on the finite element-discrete element numerical method,a numerical model of fracture propagation in deflagration fracturing was established by considering the impact of stress wave,quasi-static pressure of explosive gas,and reflection of stress wave.The model was validated against the results of physical experiments.Taking the shale reservoirs of Silurian Longmaxi Formation in Luzhou area of the Sichuan Basin as an example,the effects of in-situ stress difference,natural fracture parameters,branch wellbore spacing,delay detonation time,and angle between branch wellbore and main wellbore on fracture propagation were identified.The results show that the fracture propagation morphology in deflagration fracturing is less affected by the in-situ stress difference when it is 5-15 MPa,and the tendency of fracture intersection between branch wellbores is significantly weakened when the in-situ stress difference reaches 20 MPa.The increase of natural fracture length promotes the fracture propagation along the natural fracture direction,while the increase of volumetric natural fracture density and angle limits the fracture propagation area and reduces the probability of fracture intersection between branch wells.The larger the branch wellbore spacing,the less probability of the fracture intersection between branch wells,allowing for the fracture propagation in multiple directions.Increasing the delay detonation time decreases the fracture spacing between branch wellbores.When the angle between the branch wellbore and the main wellbore is 45°and 90°,there is a tendency of fracture intersection between branch wellbores.展开更多
Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to ...Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to the inability to effectively capture global information from images,CNNs can easily lead to loss of contours and textures in segmentation results.Notice that the transformer model can effectively capture the properties of long-range dependencies in the image,and furthermore,combining the CNN and the transformer can effectively extract local details and global contextual features of the image.Motivated by this,we propose a multi-branch and multi-scale attention network(M2ANet)for medical image segmentation,whose architecture consists of three components.Specifically,in the first component,we construct an adaptive multi-branch patch module for parallel extraction of image features to reduce information loss caused by downsampling.In the second component,we apply residual block to the well-known convolutional block attention module to enhance the network’s ability to recognize important features of images and alleviate the phenomenon of gradient vanishing.In the third component,we design a multi-scale feature fusion module,in which we adopt adaptive average pooling and position encoding to enhance contextual features,and then multi-head attention is introduced to further enrich feature representation.Finally,we validate the effectiveness and feasibility of the proposed M2ANet method through comparative experiments on four benchmark medical image segmentation datasets,particularly in the context of preserving contours and textures.展开更多
To address the challenges of fault line identification and low detection accuracy of wave head in Fault Location(FL)research of distribution networks with complex topologies,this paper proposes an FL method of Multi-B...To address the challenges of fault line identification and low detection accuracy of wave head in Fault Location(FL)research of distribution networks with complex topologies,this paper proposes an FL method of Multi-Branch distribution line based on Maximal Overlap Discrete Wavelet Transform(MODWT)combined with the improved Teager Energy Operator(TEO).Firstly,the current and voltage Traveling Wave(TW)signals at the head of each line are extracted,and the fault-induced components are obtained to determine the fault line by analyzing the polarity of the mutation amount of fault voltage and current TWs.Subsequently,the fault discrimination mark is calculated based on the fault-induced line-mode current and the zero-mode voltage,with the fault type determined by comparing each mark’s value against the fault discrimination table,transforming the FL problem in complex topology into a single-line FL problem.Finally,the fault voltage TW is extracted fromthe fault line,and the wave head detection method based on MODWT combined with improved TEO is used to precisely identify the arrival instants of both the first TW wave head and its first reflection at each line terminal,and then the FL result is calculated by applying the double-ended TW ranging formula that removes the influence of wave velocity.Simulation results demonstrate that the proposed method accurately identifies the fault line and types of faults occurring and maintains the ranging accuracy within 0.5%under various fault scenarios.展开更多
The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-bran...The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.展开更多
Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges i...Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.展开更多
Carbazole-core multi-branched chromophores 9-ethyl- 3, 6-bis （ 2- { 4- [ 5- （4-tert-butyl-phenyl） - [ 1, 3, 4 ] oxadiazol-2-yl ] - phenyl }-vinyl） -carbazole（3） and 9-ethyl-3-（ 2- {4-[ 5-（4-tert-butyl- phenyl...Carbazole-core multi-branched chromophores 9-ethyl- 3, 6-bis （ 2- { 4- [ 5- （4-tert-butyl-phenyl） - [ 1, 3, 4 ] oxadiazol-2-yl ] - phenyl }-vinyl） -carbazole（3） and 9-ethyl-3-（ 2- {4-[ 5-（4-tert-butyl- phenyl） -[ 1, 3, 4 ] oxadiazol-2-yl ] -phenyl }-vinyl ） -carbazole （ 2 ） are synthesized through Wittig reaction and characterized by nuclear magnetic resonance（NMR）and infrared（IR）. The two- photon absorption properties of chromophores are investigated. These chromophores exhibit large two-photon absorption crosssections and strong blue two-photon excited fluorescence. The cooperative enhancement of two-photon absorption（TPA） in the multi-branched structures is observed. This enhancement is partly attributed to the electronic coupling between the branches. The electronic push-pull structures in the arm and their cooperative effects help the extended charge transfer for TPA.展开更多
In non-cooperative communication systems,wireless interference classification(WIC)is one of the most essential technologies.Recently,deep learning(DL)based WIC methods have been proposed.However,conventional DL-based ...In non-cooperative communication systems,wireless interference classification(WIC)is one of the most essential technologies.Recently,deep learning(DL)based WIC methods have been proposed.However,conventional DL-based WIC methods have high computational complexity and unsatisfactory accuracy,especially when the interference-tonoise ratio(INR)is low.To this end,we propose three effective approaches.Firstly,we introduce multibranch convolutional neural networks(CNNs)for interference recognition.The multi-branch CNN is constructed by repeating a layer that aggregates several transformations with the same topology,and it notably improves the recognition ability for WIC.Our design avoids the carefully crafted selection of each transformation.Unfortunately,multi-branch CNNs are computationally expensive and memory-inefficient.To this end,we further propose Low complexity multibranch networks(LCMN),which are mathematically equivalent to multi-branch CNNs but maintain low computing costs and efficient inference.Thirdly,we present novel loss function,which encourages networks to have consistent prediction probabilities for samples with high visual similarities,resulting in increasing recognition accuracy of LCMN.Experimental results demonstrate the proposed methods consistently boost the classification performance of WIC without substantially increasing computational overhead compared to traditional DL-based methods.展开更多
With the rapid development of deepfake technology,the authenticity of various types of fake synthetic content is increasing rapidly,which brings potential security threats to people’s daily life and social stability....With the rapid development of deepfake technology,the authenticity of various types of fake synthetic content is increasing rapidly,which brings potential security threats to people’s daily life and social stability.Currently,most algorithms define deepfake detection as a binary classification problem,i.e.,global features are first extracted using a backbone network and then fed into a binary classifier to discriminate true or false.However,the differences between real and fake samples are often subtle and local,and such global feature-based detection algorithms are not optimal in efficiency and accuracy.To this end,to enhance the extraction of forgery details in deep forgery samples,we propose a multi-branch deepfake detection algorithm based on fine-grained features from the perspective of fine-grained classification.First,to address the critical problem in locating discriminative feature regions in fine-grained classification tasks,we investigate a method for locating multiple different discriminative regions and design a lightweight feature localization module to obtain crucial feature representations by augmenting the most significant parts of the feature map.Second,using information complementation,we introduce a correlation-guided fusion module to enhance the discriminative feature information of different branches.Finally,we use the global attention module in the multi-branch model to improve the cross-dimensional interaction of spatial domain and channel domain information and increase the weights of crucial feature regions and feature channels.We conduct sufficient ablation experiments and comparative experiments.The experimental results show that the algorithm outperforms the detection accuracy and effectiveness on the FaceForensics++and Celeb-DF-v2 datasets compared with the representative detection algorithms in recent years,which can achieve better detection results.展开更多
To further clarify the proppant transport and placement law in multi-branched fractures induced by volume fracturing, proppant transport simulation experiments were performed with different fracture shapes, sand ratio...To further clarify the proppant transport and placement law in multi-branched fractures induced by volume fracturing, proppant transport simulation experiments were performed with different fracture shapes, sand ratios, branched fracture opening time and injection sequence of proppants in varied particle sizes. The results show that the settled proppant height increases and the placement length decreases in main fractures as the fracturing fluid diverts gradually to the branched fractures at different positions. The flow rate in branched fractures is the main factor affecting their filling. The diverion to branched fractures leads to low flow rate and poor filling of far-wellbore branched fractures. The inclined fracture wall exerts a frictional force on the proppant to slow its settlement, thus enhancing the vertical proppant distribution in the fracture. The increase of sand ratio can improve the filling of near-wellbore main fracture and far-wellbore branched fracture and also increase the settled proppant height in main fracture. Due to the limitation of fracture height, when the sand ratio increases to a certain level, the increment of fracture filling decreases. When branched fracture is always open(or extends continuously), the supporting effect on the branched fractures is the best, but the proppant placement length within the main fractures is shorter. The fractures support effect is better when it is first closed and then opened(or extends in late stage) than when it is first opened and then closed(or extends in early stage). Injecting proppants with different particle sizes in a specific sequence can improve the placement lengths of main fracture and branched fracture. Injection of proppants in an ascending order of particle size improves the near-wellbore fracture filling, to a better extent than that in a descending order of particle size.展开更多
As a highly efficient production method, the technique of multi-branch horizontal well is widely used in low permeability reservoirs, heavy oil reservoirs, shallow layer reservoirs and multi-layer reservoirs, because ...As a highly efficient production method, the technique of multi-branch horizontal well is widely used in low permeability reservoirs, heavy oil reservoirs, shallow layer reservoirs and multi-layer reservoirs, because it can significantly improve the productivity of a single well, inhibit coning and enhance oil recovery. Study on sweep efficiency and parameters optimization of multi-branch horizontal well is at the leading edge of research. Therefore, the study is important for enhancing oil recovery and integral exploitation benefit of oil fields. In many applications, streamline simulation shows particular advantages over finite-difference simulation. With the advantages of streamline simulation such as its ability to display paths of fluid flow and acceleration factor in simulation, the flooding process is more visual. The communication between wells and flooding area has been represented appropriately. This method has been applied to the XS9 reservoir in Daqing Oilfield. The production history of this reservoir is about 10 years. The reservoir is maintained above bubble point so that the simulation meets the slight compressibility assumption. New horizontal wells are drilled following this rule.展开更多
The multi-branched Husimi recursive lattice is extended to a virtual structure with fractional numbers of branches joined on one site. Although the lattice is undrawable in real space, the concept is consistent with r...The multi-branched Husimi recursive lattice is extended to a virtual structure with fractional numbers of branches joined on one site. Although the lattice is undrawable in real space, the concept is consistent with regular Husimi lattice. The Ising spins of antiferromagnetic interaction on such a set of lattices are calculated to check the critical temperatures(Tc) and ideal glass transition temperatures(Tk) variation with fractional branch numbers. Besides the similar results of two solutions representing the stable state(crystal) and metastable state(supercooled liquid)and indicating the phase transition temperatures, the phase transitions show a well-defined shift with branch number variation. Therefore the fractional branch number as a parameter can be used as an adjusting tool in constructing a recursive lattice model to describe real systems.展开更多
According to characteristic of hydroforming of parallel multi-branch tubes,multi-objective problems were transformed to single objective problem of relational grade comparison by grey system theory.Two different objec...According to characteristic of hydroforming of parallel multi-branch tubes,multi-objective problems were transformed to single objective problem of relational grade comparison by grey system theory.Two different objectives were selected,according to the principle that process parameters were optimal which of grey relational grade were maximum,the optimal loading parameters under different objective condition were obtained,and loading paths were optimized.The results indicated that parallel multi-branch tubes hydroformed under loading paths optimized by grey system theory could meet with the requirement that objective was optimal.And the optimal loading paths under different objectives were different,and the appropriate objective should be selected according to forming characteristic.展开更多
We investigate the fluorene-vinylene unit dependent photo-physical properties of multi- branched truxene based oligomers （Tr-OFVn, n=1-4） employing steady-state absorption and emission spectroscopy, transient absorp...We investigate the fluorene-vinylene unit dependent photo-physical properties of multi- branched truxene based oligomers （Tr-OFVn, n=1-4） employing steady-state absorption and emission spectroscopy, transient absorption spectroscopy, two-photon fluorescence, and z-scan technique. The results show that the increasing of fluorene-vinylene unit leads to a red-shift in the spectra of absorption and fluorescence, and shortens the excited state lifetime. Meanwhile, two-photon fluorescence efficiency and two-photon absorption cross section of truxene based oligolners gradually enhance in company with the extension of π- conjugated length. In addition, the values of two-photon absorption cross section modeled on the sum-over-state approach agree well with the experimental ones. The results indicate multi-branched truxene based oligomers bearing organic materials for two-photon applications.展开更多
In this work, the optical properties of fluorescent probes used for detection of biothiol were studied by employing time-dependent density functional theory. By calculating the single photon absorption and emission pr...In this work, the optical properties of fluorescent probes used for detection of biothiol were studied by employing time-dependent density functional theory. By calculating the single photon absorption and emission properties of probe Mol.1, Mol.2 and Mol.3 before and after reaction with cysteine and homocysteine, we have investigated the effect of carboncarbon triple bond and benzene ring on the properties of fluorescent probes. It is found that the oscillator strength of probe molecules increases gradually with the improvement of the structure of the electron donor triphenylamine and the addition of carbon-carbon triple bonds, and better properties of fluorescence probes have also been demonstrated. At the same time, the effect of different number of side branches on the molecular properties of the probe was also studied. The results showed that compared with single-branched molecule Z1 and tribranched probe Mol.3, two side probe molecules Z2 had higher oscillator strength and better detection effect. In addition, the new single-branched probe Mol.4 with the addition of carbon-carbon triple bonds and benzene rings has better probe properties and simpler structure than the tribranched probe Mol.3.展开更多
At present,the aeration-assisted cutting-carrying technology is faced with complexities in the drilling of CBM multi-branch horizontal wells.For example,the aerating pressure is hardly maintained,and the borehole inst...At present,the aeration-assisted cutting-carrying technology is faced with complexities in the drilling of CBM multi-branch horizontal wells.For example,the aerating pressure is hardly maintained,and the borehole instability may happen.In view of these prominent problems,the technology of double casing tubes&a binary cycle system suitable for CBM multi-branch horizontal wells was developed according to the Venturi principle by means of parasitic tube insufflation which is used for well control simulation system.Then,a multiphase flow finite element model was established for the fluid-cutting particle system in this drilling condition.This technology was tested in field.Double-casing tubes cementing is adopted in this technology and a jet generator is installed at the bottom of the inner casing.In the process of drilling,the drilling fluid injected through double intermediate casing annulus is converted by the jet generator into a high-efficiency steering water jet,which,together with the water jet generated by the bit nozzle,increases the fluid returning rate in the inner annulus space.It is indicated from simulation results that the cutting-carrying effect is the best when the included angle between the nozzle of the jet generator and the vertical direction is 30°.Besides,the influential laws of cutting size,primary cycle volume,accessory cycle volume and drilling velocity on hole cleaning are figured out.It is concluded that this technology increases the flow rate of drilling fluid in annulus space,the returning rate of drilling fluid significantly and the cutting-carrying capacity.It is currently one of the effective hole cleaning technologies for CBM multi-branch horizontal wells where fresh water is taken as the drilling fluid.展开更多
基金supported by the Science and Technology Innovation Programof Hunan Province(Grant No.2022RC1021)the Hunan Provincial Natural Science Foundation Project(Grant No.2023JJ60124)+1 种基金the Changsha Natural Science Foundation Project(Grant No.kq2202265)the key project of the Hunan Provincial of Education(Grant No.22A0255).
文摘Automatic pancreas segmentation plays a pivotal role in assisting physicians with diagnosing pancreatic diseases,facilitating treatment evaluations,and designing surgical plans.Due to the pancreas’s tiny size,significant variability in shape and location,and low contrast with surrounding tissues,achieving high segmentation accuracy remains challenging.To improve segmentation precision,we propose a novel network utilizing EfficientNetV2 and multi-branch structures for automatically segmenting the pancreas fromCT images.Firstly,an EfficientNetV2 encoder is employed to extract complex and multi-level features,enhancing the model’s ability to capture the pancreas’s intricate morphology.Then,a residual multi-branch dilated attention(RMDA)module is designed to suppress irrelevant background noise and highlight useful pancreatic features.And re-parameterization Visual Geometry Group(RepVGG)blocks with amulti-branch structure are introduced in the decoder to effectively integrate deep features and low-level details,improving segmentation accuracy.Furthermore,we apply re-parameterization to the model,reducing computations and parameters while accelerating inference and reducing memory usage.Our approach achieves average dice similarity coefficient(DSC)of 85.59%,intersection over union(IoU)of 75.03%,precision of 85.09%,and recall of 86.57%on the NIH pancreas dataset.Compared with other methods,our model has fewer parameters and faster inference speed,demonstrating its enormous potential in practical applications of pancreatic segmentation.
基金Supported by the National Natural Science Foundation of China(52374004)National Key R&D Program of China(2023YFF0614102,2023YFE0110900).
文摘Based on the finite element-discrete element numerical method,a numerical model of fracture propagation in deflagration fracturing was established by considering the impact of stress wave,quasi-static pressure of explosive gas,and reflection of stress wave.The model was validated against the results of physical experiments.Taking the shale reservoirs of Silurian Longmaxi Formation in Luzhou area of the Sichuan Basin as an example,the effects of in-situ stress difference,natural fracture parameters,branch wellbore spacing,delay detonation time,and angle between branch wellbore and main wellbore on fracture propagation were identified.The results show that the fracture propagation morphology in deflagration fracturing is less affected by the in-situ stress difference when it is 5-15 MPa,and the tendency of fracture intersection between branch wellbores is significantly weakened when the in-situ stress difference reaches 20 MPa.The increase of natural fracture length promotes the fracture propagation along the natural fracture direction,while the increase of volumetric natural fracture density and angle limits the fracture propagation area and reduces the probability of fracture intersection between branch wells.The larger the branch wellbore spacing,the less probability of the fracture intersection between branch wells,allowing for the fracture propagation in multiple directions.Increasing the delay detonation time decreases the fracture spacing between branch wellbores.When the angle between the branch wellbore and the main wellbore is 45°and 90°,there is a tendency of fracture intersection between branch wellbores.
基金supported by the Natural Science Foundation of the Anhui Higher Education Institutions of China(Grant Nos.2023AH040149 and 2024AH051915)the Anhui Provincial Natural Science Foundation(Grant No.2208085MF168)+1 种基金the Science and Technology Innovation Tackle Plan Project of Maanshan(Grant No.2024RGZN001)the Scientific Research Fund Project of Anhui Medical University(Grant No.2023xkj122).
文摘Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to the inability to effectively capture global information from images,CNNs can easily lead to loss of contours and textures in segmentation results.Notice that the transformer model can effectively capture the properties of long-range dependencies in the image,and furthermore,combining the CNN and the transformer can effectively extract local details and global contextual features of the image.Motivated by this,we propose a multi-branch and multi-scale attention network(M2ANet)for medical image segmentation,whose architecture consists of three components.Specifically,in the first component,we construct an adaptive multi-branch patch module for parallel extraction of image features to reduce information loss caused by downsampling.In the second component,we apply residual block to the well-known convolutional block attention module to enhance the network’s ability to recognize important features of images and alleviate the phenomenon of gradient vanishing.In the third component,we design a multi-scale feature fusion module,in which we adopt adaptive average pooling and position encoding to enhance contextual features,and then multi-head attention is introduced to further enrich feature representation.Finally,we validate the effectiveness and feasibility of the proposed M2ANet method through comparative experiments on four benchmark medical image segmentation datasets,particularly in the context of preserving contours and textures.
基金funded by the project of Guizhou Power Grid Co.,Ltd.Guiyang Power Supply Bureau(No.GZKJXM20232317).
文摘To address the challenges of fault line identification and low detection accuracy of wave head in Fault Location(FL)research of distribution networks with complex topologies,this paper proposes an FL method of Multi-Branch distribution line based on Maximal Overlap Discrete Wavelet Transform(MODWT)combined with the improved Teager Energy Operator(TEO).Firstly,the current and voltage Traveling Wave(TW)signals at the head of each line are extracted,and the fault-induced components are obtained to determine the fault line by analyzing the polarity of the mutation amount of fault voltage and current TWs.Subsequently,the fault discrimination mark is calculated based on the fault-induced line-mode current and the zero-mode voltage,with the fault type determined by comparing each mark’s value against the fault discrimination table,transforming the FL problem in complex topology into a single-line FL problem.Finally,the fault voltage TW is extracted fromthe fault line,and the wave head detection method based on MODWT combined with improved TEO is used to precisely identify the arrival instants of both the first TW wave head and its first reflection at each line terminal,and then the FL result is calculated by applying the double-ended TW ranging formula that removes the influence of wave velocity.Simulation results demonstrate that the proposed method accurately identifies the fault line and types of faults occurring and maintains the ranging accuracy within 0.5%under various fault scenarios.
基金This work was funded by the project of State Grid Hunan Electric Power Research Institute(No.SGHNDK00PWJS2210033).
文摘The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.
基金Double First-Class Innovation Research Project for People’s Public Security University of China(2023SYL08).
文摘Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.
基金The National Natural Science Foundation of China(No.60678042)the Natural Science Foundation of Jiangsu Province(No.BK2006553)the Pre-Research Project of the National Natural Science Foundation supported by Southeast University(No.9207041399)
文摘Carbazole-core multi-branched chromophores 9-ethyl- 3, 6-bis （ 2- { 4- [ 5- （4-tert-butyl-phenyl） - [ 1, 3, 4 ] oxadiazol-2-yl ] - phenyl }-vinyl） -carbazole（3） and 9-ethyl-3-（ 2- {4-[ 5-（4-tert-butyl- phenyl） -[ 1, 3, 4 ] oxadiazol-2-yl ] -phenyl }-vinyl ） -carbazole （ 2 ） are synthesized through Wittig reaction and characterized by nuclear magnetic resonance（NMR）and infrared（IR）. The two- photon absorption properties of chromophores are investigated. These chromophores exhibit large two-photon absorption crosssections and strong blue two-photon excited fluorescence. The cooperative enhancement of two-photon absorption（TPA） in the multi-branched structures is observed. This enhancement is partly attributed to the electronic coupling between the branches. The electronic push-pull structures in the arm and their cooperative effects help the extended charge transfer for TPA.
文摘In non-cooperative communication systems,wireless interference classification(WIC)is one of the most essential technologies.Recently,deep learning(DL)based WIC methods have been proposed.However,conventional DL-based WIC methods have high computational complexity and unsatisfactory accuracy,especially when the interference-tonoise ratio(INR)is low.To this end,we propose three effective approaches.Firstly,we introduce multibranch convolutional neural networks(CNNs)for interference recognition.The multi-branch CNN is constructed by repeating a layer that aggregates several transformations with the same topology,and it notably improves the recognition ability for WIC.Our design avoids the carefully crafted selection of each transformation.Unfortunately,multi-branch CNNs are computationally expensive and memory-inefficient.To this end,we further propose Low complexity multibranch networks(LCMN),which are mathematically equivalent to multi-branch CNNs but maintain low computing costs and efficient inference.Thirdly,we present novel loss function,which encourages networks to have consistent prediction probabilities for samples with high visual similarities,resulting in increasing recognition accuracy of LCMN.Experimental results demonstrate the proposed methods consistently boost the classification performance of WIC without substantially increasing computational overhead compared to traditional DL-based methods.
基金supported by the 2023 Open Project of Key Laboratory of Ministry of Public Security for Artificial Intelligence Security(RGZNAQ-2304)the Fundamental Research Funds for the Central Universities of PPSUC(2023JKF01ZK08).
文摘With the rapid development of deepfake technology,the authenticity of various types of fake synthetic content is increasing rapidly,which brings potential security threats to people’s daily life and social stability.Currently,most algorithms define deepfake detection as a binary classification problem,i.e.,global features are first extracted using a backbone network and then fed into a binary classifier to discriminate true or false.However,the differences between real and fake samples are often subtle and local,and such global feature-based detection algorithms are not optimal in efficiency and accuracy.To this end,to enhance the extraction of forgery details in deep forgery samples,we propose a multi-branch deepfake detection algorithm based on fine-grained features from the perspective of fine-grained classification.First,to address the critical problem in locating discriminative feature regions in fine-grained classification tasks,we investigate a method for locating multiple different discriminative regions and design a lightweight feature localization module to obtain crucial feature representations by augmenting the most significant parts of the feature map.Second,using information complementation,we introduce a correlation-guided fusion module to enhance the discriminative feature information of different branches.Finally,we use the global attention module in the multi-branch model to improve the cross-dimensional interaction of spatial domain and channel domain information and increase the weights of crucial feature regions and feature channels.We conduct sufficient ablation experiments and comparative experiments.The experimental results show that the algorithm outperforms the detection accuracy and effectiveness on the FaceForensics++and Celeb-DF-v2 datasets compared with the representative detection algorithms in recent years,which can achieve better detection results.
基金Supported by the National Natural Science Foundation of China (52074332,52204024)Outstanding Youth Foundation of Shandong Province (ZR2020YQ36)China Postdoctoral Science Foundation (M710225)。
文摘To further clarify the proppant transport and placement law in multi-branched fractures induced by volume fracturing, proppant transport simulation experiments were performed with different fracture shapes, sand ratios, branched fracture opening time and injection sequence of proppants in varied particle sizes. The results show that the settled proppant height increases and the placement length decreases in main fractures as the fracturing fluid diverts gradually to the branched fractures at different positions. The flow rate in branched fractures is the main factor affecting their filling. The diverion to branched fractures leads to low flow rate and poor filling of far-wellbore branched fractures. The inclined fracture wall exerts a frictional force on the proppant to slow its settlement, thus enhancing the vertical proppant distribution in the fracture. The increase of sand ratio can improve the filling of near-wellbore main fracture and far-wellbore branched fracture and also increase the settled proppant height in main fracture. Due to the limitation of fracture height, when the sand ratio increases to a certain level, the increment of fracture filling decreases. When branched fracture is always open(or extends continuously), the supporting effect on the branched fractures is the best, but the proppant placement length within the main fractures is shorter. The fractures support effect is better when it is first closed and then opened(or extends in late stage) than when it is first opened and then closed(or extends in early stage). Injecting proppants with different particle sizes in a specific sequence can improve the placement lengths of main fracture and branched fracture. Injection of proppants in an ascending order of particle size improves the near-wellbore fracture filling, to a better extent than that in a descending order of particle size.
文摘As a highly efficient production method, the technique of multi-branch horizontal well is widely used in low permeability reservoirs, heavy oil reservoirs, shallow layer reservoirs and multi-layer reservoirs, because it can significantly improve the productivity of a single well, inhibit coning and enhance oil recovery. Study on sweep efficiency and parameters optimization of multi-branch horizontal well is at the leading edge of research. Therefore, the study is important for enhancing oil recovery and integral exploitation benefit of oil fields. In many applications, streamline simulation shows particular advantages over finite-difference simulation. With the advantages of streamline simulation such as its ability to display paths of fluid flow and acceleration factor in simulation, the flooding process is more visual. The communication between wells and flooding area has been represented appropriately. This method has been applied to the XS9 reservoir in Daqing Oilfield. The production history of this reservoir is about 10 years. The reservoir is maintained above bubble point so that the simulation meets the slight compressibility assumption. New horizontal wells are drilled following this rule.
文摘The multi-branched Husimi recursive lattice is extended to a virtual structure with fractional numbers of branches joined on one site. Although the lattice is undrawable in real space, the concept is consistent with regular Husimi lattice. The Ising spins of antiferromagnetic interaction on such a set of lattices are calculated to check the critical temperatures(Tc) and ideal glass transition temperatures(Tk) variation with fractional branch numbers. Besides the similar results of two solutions representing the stable state(crystal) and metastable state(supercooled liquid)and indicating the phase transition temperatures, the phase transitions show a well-defined shift with branch number variation. Therefore the fractional branch number as a parameter can be used as an adjusting tool in constructing a recursive lattice model to describe real systems.
基金Sponsored by the National Natural Science Foundation of China(Grant No.U0934006)
文摘According to characteristic of hydroforming of parallel multi-branch tubes,multi-objective problems were transformed to single objective problem of relational grade comparison by grey system theory.Two different objectives were selected,according to the principle that process parameters were optimal which of grey relational grade were maximum,the optimal loading parameters under different objective condition were obtained,and loading paths were optimized.The results indicated that parallel multi-branch tubes hydroformed under loading paths optimized by grey system theory could meet with the requirement that objective was optimal.And the optimal loading paths under different objectives were different,and the appropriate objective should be selected according to forming characteristic.
文摘We investigate the fluorene-vinylene unit dependent photo-physical properties of multi- branched truxene based oligomers （Tr-OFVn, n=1-4） employing steady-state absorption and emission spectroscopy, transient absorption spectroscopy, two-photon fluorescence, and z-scan technique. The results show that the increasing of fluorene-vinylene unit leads to a red-shift in the spectra of absorption and fluorescence, and shortens the excited state lifetime. Meanwhile, two-photon fluorescence efficiency and two-photon absorption cross section of truxene based oligolners gradually enhance in company with the extension of π- conjugated length. In addition, the values of two-photon absorption cross section modeled on the sum-over-state approach agree well with the experimental ones. The results indicate multi-branched truxene based oligomers bearing organic materials for two-photon applications.
基金supported by the National Natural Science Foundation of China (No.11604185 and No.11804196)the Taishan Scholar Program of Shandong Province of China
文摘In this work, the optical properties of fluorescent probes used for detection of biothiol were studied by employing time-dependent density functional theory. By calculating the single photon absorption and emission properties of probe Mol.1, Mol.2 and Mol.3 before and after reaction with cysteine and homocysteine, we have investigated the effect of carboncarbon triple bond and benzene ring on the properties of fluorescent probes. It is found that the oscillator strength of probe molecules increases gradually with the improvement of the structure of the electron donor triphenylamine and the addition of carbon-carbon triple bonds, and better properties of fluorescence probes have also been demonstrated. At the same time, the effect of different number of side branches on the molecular properties of the probe was also studied. The results showed that compared with single-branched molecule Z1 and tribranched probe Mol.3, two side probe molecules Z2 had higher oscillator strength and better detection effect. In addition, the new single-branched probe Mol.4 with the addition of carbon-carbon triple bonds and benzene rings has better probe properties and simpler structure than the tribranched probe Mol.3.
基金supported by the National Science and Technology Major Project(No.2011ZX05061).
文摘At present,the aeration-assisted cutting-carrying technology is faced with complexities in the drilling of CBM multi-branch horizontal wells.For example,the aerating pressure is hardly maintained,and the borehole instability may happen.In view of these prominent problems,the technology of double casing tubes&a binary cycle system suitable for CBM multi-branch horizontal wells was developed according to the Venturi principle by means of parasitic tube insufflation which is used for well control simulation system.Then,a multiphase flow finite element model was established for the fluid-cutting particle system in this drilling condition.This technology was tested in field.Double-casing tubes cementing is adopted in this technology and a jet generator is installed at the bottom of the inner casing.In the process of drilling,the drilling fluid injected through double intermediate casing annulus is converted by the jet generator into a high-efficiency steering water jet,which,together with the water jet generated by the bit nozzle,increases the fluid returning rate in the inner annulus space.It is indicated from simulation results that the cutting-carrying effect is the best when the included angle between the nozzle of the jet generator and the vertical direction is 30°.Besides,the influential laws of cutting size,primary cycle volume,accessory cycle volume and drilling velocity on hole cleaning are figured out.It is concluded that this technology increases the flow rate of drilling fluid in annulus space,the returning rate of drilling fluid significantly and the cutting-carrying capacity.It is currently one of the effective hole cleaning technologies for CBM multi-branch horizontal wells where fresh water is taken as the drilling fluid.
