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Chinese Optics Letters 2024年第2期22卷 17-27页

作者： Nicola D'Ascenzo 胡文韬劳慧华越轩张博房磊奚道明郑睿邱奥 Emanuele Antonecchia 凌怡清刘雨晴李琰俞航肖鹏谢庆国 Wuhan National Laboratory for Optoelectronics Wuhan 430074China Biomedical Engineering Department Huazhong University of Science and TechnologyWuhan 430074China RAYQUANT Technology Co. Ltd.Ezhou 436044China RAYSOLUTION Healthcare Co. Ltd.Hefei 230000China RAYMEASURE Technology Co. Ltd.Suzhou 215000China RAYCAN Technology Co. Ltd.Suzhou 215000China College of Computer Science and software Engineering Shenzhen UniversityShenzhen 518060China

Modern scintillator-based radiation detectors require silicon photomultipliers(Si PMs)with photon detection efficiency higher than 40%at 420 nm,possibly extended to the vacuum ultraviolet(VUV)region,single-photon time resolution(SPTR)<100 ps,and dark count rate(DCR)<150 kcps/mm^(2).To enable single-photon time stamping,digital electronics and sensitive microcells need to be integrated in the same CMOS substrate,with a readout frame rate higher than 5 MHz for arrays extending over a total area up to 4 mm×4 mm.This is challenging due to the increasing doping concentrations at low CMOS scales,deep-level carrier generation in shallow trench isolation fabrication,and power consumption,among others.The advances at 350 and 110 nm CMOS nodes are benchmarked against available Si PMs obtained in CMOS and commercial customized technologies.The concept of digital multithreshold Si PMs with a single microcell readout is finally reported,proposing a possible direction toward fully digital scintillator-based radiation detectors.

关键词： silicon photomultiplier complementary metal-oxide semiconductor digital SiPM

Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

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Computers, Materials & Continua 2024年第5期79卷 2723-2741页

作者： Weijian Fan Ziwei Shi State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing100024China software Research Institute China United Network Communication Group Co.Ltd.Beijing100024China

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

关键词： Social media false information detection image aesthetic assessment cross-modal consistency

GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization

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Energy Engineering 2024年第4期121卷 1049-1065页

作者： Yingchao Li JianbinWang HaibinWang China Electric Power Research Institute State Grid Inner Mongolia Eastern Electric Power Co.Ltd.Hohhot010010China School of software Nanjing University of Information Science and TechnologyNanjing210044China

With the increasing demand for electrical services,wind farm layout optimization has been one of the biggest challenges that we have to deal with.Despite the promising performance of the heuristic algorithm on the route network design problem,the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored.In this paper,the wind farm layout optimization problem is defined.Then,a multi-objective algorithm based on Graph Neural Network(GNN)and Variable Neighborhood Search(VNS)algorithm is proposed.GNN provides the basis representations for the following search algorithm so that the expressiveness and search accuracy of the algorithm can be improved.The multi-objective VNS algorithm is put forward by combining it with the multi-objective optimization algorithm to solve the problem with multiple objectives.The proposed algorithm is applied to the 18-node simulation example to evaluate the feasibility and practicality of the developed optimization strategy.The experiment on the simulation example shows that the proposed algorithm yields a reduction of 6.1% in Point of Common Coupling(PCC)over the current state-of-the-art algorithm,which means that the proposed algorithm designs a layout that improves the quality of the power supply by 6.1%at the same cost.The ablation experiments show that the proposed algorithm improves the power quality by more than 8.6% and 7.8% compared to both the original VNS algorithm and the multi-objective VNS algorithm.

关键词： GNN representation learning variable neighborhood search multi-objective optimization wind farm layout point of common coupling

Influence of donor age on liver transplantation outcomes: A multivariate analysis and comparative study

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World Journal of Gastrointestinal Surgery 2024年第2期16卷 331-344页

作者： Miran Bezjak Ivan Stresec Branislav Kocman Stipislav Jadrijević Tajana Filipec Kanizaj Miro Antonijević Bojana Dalbelo Bašić Danko Mikulić Department of Surgery University Hospital MerkurZagreb 10000Croatia Department of Electronics MicroelectronicsComputer and Intelligent SystemsFaculty of Electrical Engineering and ComputingZagreb 10000Croatia Department of Gastroenterology University Hospital MerkurZagreb 10000Croatia Development of software Nanobit Ltd.Zagreb 10000Croatia

BACKGROUND The growing disparity between the rising demand for liver transplantation(LT)and the limited availability of donor organs has prompted a greater reliance on older liver grafts.Traditionally,utilizing livers from elderly donors has been associated with outcomes inferior to those achieved with grafts from younger donors.By accounting for additional risk factors,we hypothesize that the utili-zation of older liver grafts has a relatively minor impact on both patient survival and graft viability.AIM To evaluate the impact of donor age on LT outcomes using multivariate analysis and comparing young and elderly donor groups.METHODS In the period from April 2013 to December 2018,656 adult liver transplants were performed at the University Hospital Merkur.Several multivariate Cox propor-tional hazards models were developed to independently assess the significance of donor age.Donor age was treated as a continuous variable.The approach involved univariate and multivariate analysis,including variable selection and assessment of interactions and transformations.Additionally,to exemplify the similarity of using young and old donor liver grafts,the group of 87 recipients of elderly donor liver grafts(≥75 years)was compared to a group of 124 recipients of young liver grafts(≤45 years)from the dataset.Survival rates of the two groups were estimated using the Kaplan-Meier method and the log-rank test was used to test the differences between groups.RESULTS Using multivariate Cox analysis,we found no statistical significance in the role of donor age within the constructed models.Even when retained during the entire model development,the donor age's impact on survival remained insignificant and transformations and interactions yielded no substantial effects on survival.Consistent insigni-ficance and low coefficient values suggest that donor age does not impact patient survival in our dataset.Notably,there was no statistical evidence that the five developed models did not adhere to the proportional hazards assumption.When c

关键词： Liver transplantation Elderly donors Survival analysis Postoperative complications Cox proportional hazard models

FSS: algorithm and neural network accelerator for style transfer

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Science China(Information Sciences) 2024年第2期67卷 253-266页

作者： Yi LING Yujie HUANG Yujie CAI Zhaojie LI Mingyu WANG Wenhong LI Xiaoyang ZENG State Key Laboratory of ASIC & System Fudan University Shanghai Explore X Technology Co. Ltd.

Neural networks(NNs), owing to their impressive performance, have gradually begun to dominate multimedia processing. For resource-constrained and energy-sensitive mobile devices, an efficient NN accelerator is necessary. Style transfer is an important multimedia application. However, existing arbitrary style transfer networks are complex and not well supported by current NN accelerators, limiting their application on mobile devices. Moreover, the quality of style transfer needs improvement. Thus, we design the Fast Style system(FSS), where a novel algorithm and an NN accelerator are proposed for style transfer. In FSS, we first propose a novel arbitrary style transfer algorithm, Fast Style. We propose a light network that contributes to high quality and low computational complexity and a prior mechanism to avoid retraining when the style changes. Then, we redesign an NN accelerator for Fast Style by applying two improvements to the basic NVIDIA deep learning accelerator(NVDLA) architecture. First, a flexible dat FSM and wt FSM are redesigned to enable the original data path to perform other operations(including the GRAM operation)by software programming. Moreover, statistics and judgment logic are designed to utilize the continuity of a video stream and remove the data dependency in the instance normalization, which improves the accelerator performance by 18.6%. The experimental results demonstrate that the proposed Fast Style can achieve higher quality with a lower computational cost, making it more suitable for mobile devices. The proposed NN accelerator is implemented on the Xilinx VCU118 FPGA under a 180-MHz clock. Experimental results show that the accelerator can stylize 512×512-pixel video with 20 FPS, and the measured performance reaches up to 306.07 GOPS. The ASIC implementation in TSMC 28 nm achieves about 22 FPS in the case of a 720-p video.

关键词： neural network accelerator style transfer neural network deep learning

Towards accurate mapping of loess waterworn gully by integrating google earth imagery and DEM using deep learning

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International Soil and Water Conservation Research 2024年第1期12卷 13-28页

作者： Rong Chen Yi Zhou Zetao Wang Ying Li Fan Li Feng Yang School of Geography and Tourism Shaanxi Normal UniversityXi'an710119China National Experiment and Teaching Demonstration Center for Geography Xi'an710119China SuperMap software Co. Ltd.Beijing100015China School of Environmental Science and Engineering Southern University of Science and TechnologyShenzhen518055China

Accurate mapping of loess waterworn gully(LWG)is essential to further study gully erosion and geomorphological evolution for the Chinese Loess Plateau(CLP).Due to the vertical joint and collapsibility of loess,LWGs have the characteristics of zigzag and unique slope abruptness under synthetic action of hydraulic force and gravity.This forces existing LWG mapping methods to either focus on the improvement of mapping accuracy or center on the increase of mapping efficiency.However,simultaneously achieving accurate and efficient mapping of LWG is still in its infancy under complex topographic conditions.Here,we proposed a method that innovatively integrates the loess slope abruptness feature into an improved deep learning semantic segmentation framework for LWG mapping using 0.6 m Google imagery and 5 m DEM data.We selected four study areas representing typical loess landforms to test the performance of our method.The proposed method can achieve satisfactory mapping results,with the F1 score,mean Intersection-over-Union(mIoU),and overall accuracy of 90.5%,85.3%,and 92.3%,respectively.In addition,the proposed model also showed significant accuracy improvement by inputting additional topographic information(especially the slope of slope).Compared with existing algorithms(Random forests,original DeepLabV3+,and Unet),the proposed approach in this study achieved a better accuracy-efficiency trade-off.Overall,the method can ensure high accuracy and efficiency of the LWG mapping for different loess landform types and can be extended to study various loess gully mapping and water and soil conservation.

关键词： Loess waterworn gully Topographic information Mapping Deep learning Soil erosion Loess plateau

Numerical simulation analysis of wind field above pavement surface in different landforms by computational fluid dynamics approach

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第3期11卷 559-573页

作者： Jian Ouyang Zhao Jiang Leiyu Ye Jing Li Peng Cao School of Civil Engineering and Architecture Hainan University School of Transportation and Logistics Dalian University of Technology Hexagon Manufacturing Intelligence (Qingdao) Co. Ltd. China Tower Co. Ltd.Dalian Branch Faculty of Architecture Civil and Transportation Engineering Beijing University of Technology

The temperature and moisture of the pavement structure can be greatly influenced by the wind speed above pavement surface. The wind speed above pavement surface not only is dominated by the wind speed of atmosphere, but also it is highly related to the landform and buildings around road. However, currently there are no studies about the wind field above pavement surface in consideration of the effect of the landform and buildings. A simulation method, which is combined with geographic information system(GIS), wind data from meteorological observatory and computational fluid dynamics(CFD) software, is employed to study the effect of the landform and the wind speed of atmosphere on the wind field above pavement surface. Three cases are studied, including an urban road, a coastal road and a mountainous road. Furthermore, the wind field distribution above road surface in different wind directions was studied in our work. Results indicate that the wind field above pavement surface can be greatly affected by the landforms, buildings and wind direction. This simulation method can provide reliable results for the wind field above pavement surface. The maximum relative errors between simulated and measured wind speed can be less than 20% in the analysis of the three cases. It is recommended that the CFD simulation method is a good tool to accurately know the wind field above pavement surface.

关键词： Wind field above pavement surface Computational fluid dynamics Landforms Geographic information system Simulation

Synthesis,Style Editing,and Animation of 3D Cartoon Face

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Tsinghua Science and Technology 2024年第2期29卷 506-516页

作者： Ming Guo Feng Xu Shunfei Wang Zhibo Wang Ming Lu Xiufen Cui Xiao Ling School of software and BNRist Tsinghua UniversityBeijing 100084China Department of Multimedia and Smart Guangdong OPPO Mobile Telecommunications Corp.Ltd.Dongguan 523860China Intel Labs IntelBeijing 100089China

As a popular kind of stylized face,cartoon faces have rich application scenarios.It is challenging to create personalized 3D cartoon faces directly from 2D real photos.Besides,in order to adapt to more application scenarios,automatic style editing,and animation of cartoon faces is also a crucial problem that is urgently needed to be solved in the industry,but has not yet had a perfect solution.To solve this problem,we first propose“3D face cartoonizer”,which can generate high-quality 3D cartoon faces with texture when fed into 2D facial images.We contribute the first 3D cartoon face hybrid dataset and a new training strategy which first pretrains our network with low-quality triplets in a reconstruction-then-generation manner,and then finetunes it with high-quality triplets in an adversarial manner to fully leverage the hybrid dataset.Besides,we implement style editing for 3D cartoon faces based on k-means,which can be easily achieved without retrain the neural network.In addition,we propose a new cartoon faces'blendshape generation method,and based on this,realize the expression animation of 3D cartoon faces,enabling more practical applications.Our dataset and code will be released for future research.

关键词： cartoon 3D face animation computer graphics

An Efficient and Provably Secure SM2 Key-Insulated Signature Scheme for Industrial Internet of Things

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工程与科学中的计算机建模(英文) 2024年第1期138卷 903-915页

作者： Senshan Ouyang Xiang Liu Lei Liu Shangchao Wang Baichuan Shao Yang Zhao School of Mechanical Engineering Northwestern Polytechnical UniversityXi’anChina Department of Process and Information Technology Chengdu Aircraft Industrial(Group)Co.Ltd.ChengduChina School of Information and software Engineering The Network and Data Security Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina

With the continuous expansion of the Industrial Internet of Things(IIoT),more andmore organisations are placing large amounts of data in the cloud to reduce overheads.However,the channel between cloud servers and smart equipment is not trustworthy,so the issue of data authenticity needs to be addressed.The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems.Unfortunately,it still suffers from the problem of key exposure.In order to address this concern,this study first introduces a key-insulated scheme,SM2-KI-SIGN,based on the SM2 algorithm.This scheme boasts strong key insulation and secure keyupdates.Our scheme uses the elliptic curve algorithm,which is not only more efficient but also more suitable for IIoT-cloud environments.Finally,the security proof of SM2-KI-SIGN is given under the Elliptic Curve Discrete Logarithm(ECDL)assumption in the random oracle.

关键词： Key-insulated SM2 algorithm digital signature Industrial Internet of Things(IIoT) provable security

Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNNModel

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Energy Engineering 2024年第3期121卷 821-834页

作者： Qi Zhuang Dong Liu Zhuo Chen PetroChina Changqing Oilfield Company The Second Gas Production PlantXi’an710000China PetroChina Changqing Oilfield Company Safety and Environmental Supervision Department Co.Ltd.Xi’an710000China Sinopec Northwest Oilfield Company The Second Oil Production Plant Co.Ltd.Urumqi830016China

Oil and gas pipelines are affected by many factors,such as pipe wall thinning and pipeline rupture.Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management.Aiming at the shortcomings of the BP Neural Network(BPNN)model,such as low learning efficiency,sensitivity to initial weights,and easy falling into a local optimal state,an Improved Sparrow Search Algorithm(ISSA)is adopted to optimize the initial weights and thresholds of BPNN,and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established.Taking 61 sets of pipelines blasting test data as an example,the prediction model was built and predicted by MATLAB software,and compared with the BPNN model,GA-BPNN model,and SSA-BPNN model.The results show that the MAPE of the ISSA-BPNN model is 3.4177%,and the R2 is 0.9880,both of which are superior to its comparison model.Using the ISSA-BPNN model has high prediction accuracy and stability,and can provide support for pipeline inspection and maintenance.

关键词： Oil and gas pipeline corrosion defect failure pressure prediction sparrow search algorithm BP neural network logistic chaotic map