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software Defect Prediction Method Based on Stable Learning

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Computers, Materials & Continua 2024年第1期78卷 65-84页

作者： Xin Fan Jingen Mao Liangjue Lian Li Yu Wei Zheng Yun Ge College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing210012China School of software Nanchang Hangkong UniversityNanchang330029China software testing and Evaluation center Nanchang Hangkong UniversityNanchang330029China

The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and *** previous software defect prediction studies,transfer learning was effective in solving the problem of inconsistent project data ***,target projects often lack sufficient data,which affects the performance of the transfer learning *** addition,the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning *** address these problems,this article propose a software defect prediction method based on stable learning(SDP-SL)that combines code visualization techniques and residual *** method first transforms code files into code images using code visualization techniques and then constructs a defect prediction model based on these code *** the model training process,target project data are not required as prior *** the principles of stable learning,this paper dynamically adjusted the weights of source project samples to eliminate dependencies between features,thereby capturing the“invariance mechanism”within the *** approach explores the genuine relationship between code defect features and labels,thereby enhancing defect prediction *** evaluate the performance of SDP-SL,this article conducted comparative experiments on 10 open-source projects in the PROMISE *** experimental results demonstrated that in terms of the F-measure,the proposed SDP-SL method outperformed other within-project defect prediction methods by 2.11%-44.03%.In cross-project defect prediction,the SDP-SL method provided an improvement of 5.89%-25.46% in prediction performance compared to other cross-project defect prediction ***,SDP-SL can effectively enhance within-and cross-project defect predictions.

关键词： software defect prediction code visualization stable learning sample reweight residual network

Dynamic manipulation of multimodal emission in Er^(3+)-activated non-core-shell structure for optical thermometry and information security

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Rare Metals 2024年第4期43卷 1702-1712页

作者： Xuan Liu Zi-Xia Lin Yin-Biao Shi Xiao-Yan Wang Ming-Ye Ding Xiao-Fei Yang College of Science Nanjing Forestry UniversityNanjing210037China testing center Yangzhou UniversityYangzhou225009China

Regulating luminescent dynamics of lanthanide-based luminescent materials via external stimuli is of great significance in the fields of optical thermometry and high-level ***,it is still a huge challenge to realize multimodal emissions with tunable color outputs from a single activator in simple structures via smart dynamic control of photon transition ***,we present a mechanistic strategy to achieve multimodal luminescence of Er^(3+)activators with color-switchable outputs in a non-core-shell *** the control of excitation dynamics(λ_(ex)=980,808,1532,377 nm),the population among the intermediate en ergy levels of Er^(3+)and the interaction between Er^(3+)and Yb^(3+)could be precisely modulated through energy transfer and migration processes,leading to the generation of colortunable multimodal luminescence upon diverse excitation modes(non-steady-state,single-/dual-wavelength steady,thermal activation).Inspired by its special luminescent performance,the as-obtained material exhibits great potential in noncontact thermometry,multimodal anticounterfeiting,and high-capacity information encryption by performing a series of proof-of-concept *** findings might provide a conceptual model to modulate the luminescent dynamics in a simple-structured system for the generation of color-adjustable multimodal emissions,which is convenient for the development of advanced luminescent materials toward versatile cuttingedge applications.

关键词： Lanthanide ions Multimodal emission Upconversion Downshifting Anti-counterfeiting Luminescent thermometry

Extrusion-base d 3D-printe d“rolle d-up”composite scaffolds with hierarchical pore structure for bone growth and repair

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Journal of Materials Science & Technology 2024年第4期171卷 222-234页

作者： Yufan Li Li Chen Yijing Stehle Mingyue Lin Chenxin Wang Rui Zhang Min Huang Yubao Li Qin Zou Research center for Nano Biomaterials Analytical&Testing CenterSichuan UniversityChengdu 610064China Analytical&testing center Sichuan UniversityChengdu 610064China Department of mechanical engineering Union College807 Union St.SchenectadyNY 12308USA Sichuan Institute of Atomic Energy Chengdu 610101China

Three-dimensional(3D)bioprinting,specifically direct ink writing(DIW)capable of printing biologically active substances such as growth factors or drugs under low-temperature conditions,is an emerging di-rection in bone tissue ***,limited by the bio-ink mobility and the poor resolution of this printing technology,the lateral pores of current crisscross-stacked scaffolds printed through DIW tend to clog and are inimical to bone ***,it is critical to develop DIW printed biologi-cal scaffold structure with high mechanical strength,porosity,and biocompatibility ***,patterned polylactic acid(PLA)/polycaprolactone(PCL)/nano-hydroxyapatite(n-HA)based scaffold was printed through DIW technological and rolled-up for properties characterization,cytocompatibility test,and bone repair *** result not only shows that the hexagonal patterned scaffolds are me-chanically strong with porosity,but also demonstrated that the hierarchical pore structure formed during rolled-up has the potential to address the clogging problem and stimulates bone growth and repair.

关键词： Direct ink writing(DIW) Bone repair scaffold,Micro-CT Bio composites

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 769-786页

作者： Xiaojun Pu Jiaqi Zhu Yunkun Wu Chang Leng Zitong Bo Hongan Wang Institute of software Chinese Academy of Sciences BeijingChina Ecovacs Robotics Co. Ltd.SuzhouJiangsuChina Automotive software Innovation center ChongqingChina

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 ***,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal ***,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction *** DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency *** dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained ***,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained *** performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute *** results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of *** spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various *** conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.

关键词： adaptive COVID-19 forecasting dynamic intervention spatio-temporal graph neural networks

IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB

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Big Data Mining and Analytics 2024年第1期7卷 29-41页

作者： Pengyu Chen Wendi He Wenxuan Ma Xiangdong Huang Chen Wang School of software Tsinghua UniversityBeijing 100084China National Engineering Research center for Big Data software(NERCBDS) Tsinghua UniversityBeijing 100084China

There is a growing demand for time series data analysis in industry *** loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O *** User-Defined Functions(UDF)provided,computation for time series can be executed on Apache loTDB *** satisfy most of the common requirements in industrial time series analysis,we create a UDF library,loTDQ,on Apache *** library integrates stream computation functions on data quality analysis,data profiling,anomaly detection,data repairing,*** enables users to conduct a wide range of analyses,such as monitoring,error diagnosis,equipment reliability *** provides a framework for users to examine loT time series with data quality *** show that loTDQ keeps the same level of performance compared to mainstream alternatives,and shortens I/O consumption for Apache loTDB users.

关键词： industrial big data data quality data mining and analytics

A buffer overflow detection and defense method based on RiSC-V instruction set extension

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Cybersecurity 2024年第2期7卷 28-43页

作者： Chang Liu Yan-Jun Wu Jing-Zheng Wu Chen Zhao Intelligent software Research center Institute of SoftwareChinese Academy of SciencesBejingChina University of Chinese Academy of Sciences BeijingChina State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijingChina

Buffer overflow poses a serious threat to the memory security of modern operating *** overwrites the con-tents of other memory areas by breaking through the buffer capacity limit,destroys the system execution environ-ment,and provides implementation space for various system attacks such as program control flow *** makes it a wide range of harms.A variety of security technologies have been proposed to deal with system security problems including buffer *** example,No eXecute(NX for short)is a memory management technology commonly used in Harvard *** can refuse the execution of code which residing in a specific memory,and can effectively suppress the abnormal impact of buffer overflow on control ***,in recent years,it has also been used in the field of system security,deriving a series of solutions based on NX technology,such as ExecShield,DEP,StackGuard,***,these security solutions often rely too much on the processor archi-tecture so that the protection coverage is insufficient and the accuracy is *** in the emerging system architecture field represented by RiSC-V,there is still a lack of effective solutions for buffer overflow *** the continuous rapid development of the system architecture,it is urgent to develop defense methods that are applicable to different system application environments and oriented to all executable memory spaces to meet the needs of system security ***,we propose BOP,A new system memory security design method based on RISC-V extended instructions,to build a RISC-V buffer overflow detection and defense system and deal with the buffer overflow threat in *** to this method,NX technology can be combined with program control flow analysis,and Nx bit mechanism can be used to manage the executability of memory space,so as to achieve a more granular detection and defense of buffer overflow attacks that may occur in RISC-V system

关键词： RISc-V Operating system security Buffer overflow Control flow hijacking Nx bit Xibop

Numerical study on the blocking effect of skin on Flash-Ball Impact and damage assessment

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Defence Technology（防务技术） 2024年第3期33卷 532-545页

作者： Dihua Ouyang Chunwei Qin Xiaowen Qin Qiantao Zhang Xingyu Liu Xi'an University of Architecture and Technology Xi'an 710055China Analysis and testing center Xi'an University of Architecture and TechnologyXi'an 710055China Engineering University of PAP Xi'an 710086China

To explore the response law of non-lethal large-size kinetic energy projectiles to blunt attack on skin tissue,and to evaluate the skin injury characteristics of the attacked personnel and the use safety of kinetic energy *** on the LS-DYNA simulation software,a three-layer skin simulation model and a Flash-Ball rubber bullet model are established,and the force-time and deformation-time biomechanical corridors of the Flash-Ball rubber bullet impacting human skin tissue are *** corridor curve and the energy transfer and diffusion are analyzed and *** safety evaluation of the damage caused by the rubber bullet shooting a human body at different distances is carried out using the empirical formula of the penetration ***,the safe shooting distance is *** results show that the model used in the simulation has a good correlation with the experimental data,its biomechanical corridor characteristics are different from those of conventional vehicle impact and smallsize projectile response *** energy transfer and action time of medium and low-speed impact may cause greater *** fat layer is the largest energy absorption *** minimum safe shooting distance to ensure skin tissue from penetrating damage is 15.8 m,and the limit specific kinetic energy of skin damage is 7.88 J/cm^(2).This study can be extended to the study of biomechanical response law and safety evaluation under the impact of the same type of large kinetic energy projectile,which provides an important theoretical reference for the police to use large kinetic energy projectiles to conduct safe shooting in peacekeeping operations.

关键词： KIPs Blunt strike Biomechanical response Damage analysis

Effect of hot isostatic pressure on the microstructure and tensile properties of γ'-strengthened superalloy fabricated through induction-assisted directed energy deposition

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International Journal of Minerals,Metallurgy and Materials 2024年第5期31卷 1089-1097页

作者： Jianjun Xu Hanlin Ding Xin Lin Feng Liu Analytical&testing center Northwestern Polytechnical UniversityXi’an 710072China State Key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi’an 710072China

The microstructure characteristics and strengthening mechanism of Inconel738LC(IN-738LC) alloy prepared by using induction-assisted directed energy deposition(IDED) were elucidated through the investigation of samples subjected to IDED under 1050℃ preheating with and without hot isostatic pressing(HIP,1190℃,105 MPa,and 3 h).Results show that the as-deposited sample mainly consisted of epitaxial columnar crystals and inhomogeneously distributed γ’ phases in interdendritic and dendritic core *** HIP,grain morphology changed negligibly,whereas the size of the γ’ phase became increasingly *** further heat treatment(HT,1070℃,2 h + 845℃,24 h),the γ’ phase in the as-deposited and HIPed samples presented a bimodal size distribution,whereas that in the as-deposited sample showed a size that remained *** comparison of tensile properties revealed that the tensile strength and uniform elongation of the HIP + HTed sample increased by 5% and 46%,respectively,due to the synergistic deformation of bimodal γ’phases,especially large cubic γ’ ***,the relationship between phase transformations and plastic deformations in the IDEDed sample was discussed on the basis of generalized stability theory in terms of the trade-off between thermodynamics and kinetics.

关键词： directed energy deposition Ni-based superalloys high-temperature preheating hot isostatic pressing microstructure tensile properties

TSCND:Temporal Subsequence-Based Convolutional Network with Difference for Time Series Forecasting

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Computers, Materials & Continua 2024年第3期78卷 3665-3681页

作者： Haoran Huang Weiting Chen Zheming Fan MOE Research center of software/Hardware Co-Design Engineering East China Normal UniversityShanghai200062China

Time series forecasting plays an important role in various fields, such as energy, finance, transport, and weather. Temporal convolutional networks (TCNs) based on dilated causal convolution have been widely used in time series forecasting. However, two problems weaken the performance of TCNs. One is that in dilated casual convolution, causal convolution leads to the receptive fields of outputs being concentrated in the earlier part of the input sequence, whereas the recent input information will be severely lost. The other is that the distribution shift problem in time series has not been adequately solved. To address the first problem, we propose a subsequence-based dilated convolution method (SDC). By using multiple convolutional filters to convolve elements of neighboring subsequences, the method extracts temporal features from a growing receptive field via a growing subsequence rather than a single element. Ultimately, the receptive field of each output element can cover the whole input sequence. To address the second problem, we propose a difference and compensation method (DCM). The method reduces the discrepancies between and within the input sequences by difference operations and then compensates the outputs for the information lost due to difference operations. Based on SDC and DCM, we further construct a temporal subsequence-based convolutional network with difference (TSCND) for time series forecasting. The experimental results show that TSCND can reduce prediction mean squared error by 7.3% and save runtime, compared with state-of-the-art models and vanilla TCN.

关键词： Difference data prediction time series temporal convolutional network dilated convolution