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IEEE/ACM International Conference on Program Comprehension (ICPC)

作者： Hailin Huang Liuwen Cao Jiexin Wang Tianchen Yu Yi Cai School of Software Engineering South China University of Technology China Key Laboratory of Big Data and Intelligent Robot (SCUT) MOE of China China

ISBN: (数字)9798331502232

ISBN: (纸本)9798331502249

Large language models (LLMs) have revolutionized the field of programming for developers by automatically generating code based on natural language intent (NL intent). In numerous cases, LLMs can produce correct programs after several trials. As a result, a major challenge for this task is to select the most appropriate program from the multiple samples (also called code ranking) generated by LLMs. Recent popular approaches for code ranking involve the ranker-based methods, in which we train a ranker to classify the error in code using execution results (correct or error types) of code as supervised signals select the best program. However, existing rankerbased code ranking approaches rely on classification labels, which are highly sensitive to label distribution and show weak generalization ability to other distributions. In this paper, we introduce SACL-CR to address this challenge, a novel structureaware contrastive learning framework for code ranking. This approach effectively addresses the generalization issues of existing ranker-based methods by integrating both code sequence and structural information. Encoders trained with this method can effectively identify errors in code, enhancing the model's ability to differentiate between correct and incorrect code. Our research demonstrates that SACL-CR significantly enhances the pass@k accuracy of several code generation models, including CodeLlama and DeepseekCoder, on the HumanEval and MBPP datasets. The open-source code will be released at https://***/Iced-Americano2001/SACL-CR.

关键词： Codes Accuracy Large language models Natural languages Contrastive learning Programming

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Development of the high-strength ductile ferritic alloys via regulating the intragranular and grain boundary precipitation of G-phase

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Journal of Materials Science & Technology 2023年第5期136卷 180-199页

作者： Mujin Yang Chao Huang Jiajia Han Haichen Wu Yilu Zhao Tao Yang Shenbao Jin Chenglei Wang Zhou Li Ruiying Shu Cuiping Wang Huanming Lu Gang Sha Xingjun Liu School of Materials Science and Engineering Harbin Institute of TechnologyShenzhen 518055China Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen 518055China College of Materials and Fujian Provincial Key Laboratory of Materials Genome Xiamen UniversityXiamen 361005China Test Center Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo 315201China Department of Materials Science and Engineering City University of Hong KongHong KongChina Department of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyShenzhen 150001China Institute of Materials Genome and Big Data Harbin Institute of TechnologyShenzhen 518055China

A typical G-phase strengthened ferritic model alloy(1Ti:Fe-20Cr-3Ni-1Ti-3Si,wt.%)has been carefully studied using both advanced experimental(EBSD,TEM and APT)and theoretical(DFT)*** the classic“solid solution and aging”process,the superfine(Fe,Ni)_(2)TiSi-L2_(1)particles densely precipitate within the ferritic grain and subsequently transform into the(Ni,Fe)_(16)Ti_(6)Si_(7)-G *** the meanwhile,the elemental segregation at grain boundaries and the resulting precipitation of a large amount of the(Ni,Fe)_(16)Ti_(6)Si_(7)-G phase are also *** nanoscale microstructural evolutions result in a remarkable increase in hardness(100-300 HV)and severe *** the“cold rolling and aging”process is used,the brittle fracture is effectively suppressed without loss of nano-precipitation strengthening *** yield strength of 1700 MPa with 4%elongation at break is *** key improvement in mechanical properties is mainly attributed to the pre-cold rolling process which effectively avoids the dense precipitation of the G-phase at the grain *** findings could shed light on the further exploration of the precipitation site via optimal processing strategies.

关键词： G-phase Precipitation strengthening Grain boundary segregation Nano-precipitates

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Sub-Loc:predicting protein sub-mitochondrial localization based on sequence embedding

Sub-Loc:predicting protein sub-mitochondrial localization ba...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Wang, Xiaoting Wang, Juan Bian, Haodong Guo, Maozu Inner Mongolia University Ecological Big Data Engineering Research Center of the Ministry of Education School of Computer Science Hohhot China Beijing University of Civil Engineering and Architecture School of Electrical and Information Engineering Beijing100044 China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044 China

ISBN: (纸本)9781665468190

Mitochondria are subcellular organelles existing in most eukaryotic organisms. They have a pivotal role in lots of bio-chemical processes for cells. Proteins in different compartments of mitochondria have their transport routes. Locating proteins in mitochondria can provide a solid foundation for mitochondrial pathologies. So far, there have been several computational methods for solving the issue. However, their accuracy is so low that they do not identify the localization precisely. We develop an unsupervised learning model to represent mitochondrial proteins as n-dimensional vectors, called sequence embedding, which can learn the global and context information from mitochondrial proteins. We design a new model, called Sub-Loc, to predict the sub-mitochondrial localization of proteins using the SVM classifier and the sequence embedding method. The sequence embedding method and the Sub-Loc are tested by experiments. Experimental results show the sequence embedding method remarkably enhances the performance of prediction for sub-mitochondrial localization of proteins compared with other feature representations. The Sub-Loc outperforms other approaches for predicting sub-mitochondrial localization of proteins. © 2022 IEEE.

关键词： Support vector machines

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A novel numerical simulation of CO_(2) immiscible flooding coupled with viscosity and starting pressure gradient modeling in ultra-low permeability reservoir

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Frontiers of Earth Science 2023年第3期17卷 884-898页

作者： Jie CHI Binshan JU Jiabei WANG Xing ZHANG Wenbin CHEN Mengfei ZHANG School of Big Data and Fundamental Sciences Shandong Institute of Petroleum and Chemical TechnologyDongying 257061China School of Energy Resources China University of Geosciences(Beijing)Beijing 100083China Key Laboratory of Geological Evaluation and Development Engineering of Unconventional Natural Gas Energy Beijing 100083China School of Petroleum Engineering Chongqing University of Science&TechnologyChongqing 401331China Research Institute of Petroleum Engineering Technology Shengli Oilfield CompanySINOPECDongying 257000China

CO_(2) immiscible flooding is an environmentally-friendly and effective method to enhance oil recovery in ultra-low permeability reservoirs.A mathematical model of CO_(2) immiscible flooding was developed,considering the variation in crude oil viscosity and starting pressure gradient in ultra-low permeability reservoirs based on the non-Darcy percolation *** mathematical model and numerical simulator were developed in the C++language to simulate the effects of fluid viscosity,starting pressure gradient,and other physical parameters on the distribution of the oil pressure field,oil saturation field,gas saturation field,oil viscosity field,and oil *** results showed that the formation pressure and pressure propagation velocity in CO_(2) immiscible flooding were lower than the findings without considering the starting pressure *** formation oil content saturation and the crude oil formation viscosity were higher after the consideration of the starting pressure *** viscosity of crude oil considering the initiation pressure gradient during the formation was higher than that without this gradient,but the yield was lower than that *** novel mathematical models helped the characterization of seepage resistance,revealed the influence of fluid property changes on seepage,improved the mathematical model of oil seepage in immiscible flooding processes,and guided the improvement of crude oil recovery in immiscible flooding processes.

关键词： viscosity starting pressure gradient flow simulation CO_(2)immiscible flooding ultra-low permeability reservoir

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Observation-based sources evolution of non-methane hydrocarbons (NMHCs) in a megacity of China

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Journal of Environmental Sciences 2023年第2期124卷 794-805页

作者： Yarong Peng Hongli Wang Qian Wang Shengao Jing Jingyu An Yaqin Gao Cheng Huang Rusha Yan Haixia Dai Tiantao Cheng Qiang Zhang Meng Li Jianlin Hu Zhihao Shi Li Li Shengrong Lou Shikang Tao Qinyao Hu Jun Lu Changhong Chen Department of Environmental Science and Engineering Shanghai Key Laboratory of Atmospheric Particle Pollution and PreventionInstitute of Atmospheric SciencesFudan UniversityShanghai 200438China State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental SciencesShanghai 200233China Department of Atmospheric and Oceanic Sciences Institute of Atmospheric SciencesFudan UniversityShanghai 200438China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingTsinghua UniversityBeijing 100084China Big Data Institute for Carbon Emission and Environmental Pollution Fudan UniversityShanghai 200438China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China

Both concentrations and emissions of many air pollutants have been decreasing due to implement of control measures in China,in contrast to the fact that an increase in emissions of non-methane hydrocarbons(NMHCs)has been *** study employed seven years continuous NMHCsmeasurements and the related activities data of Shanghai,a megacity in China,to explore evolution of emissions and effectiveness of air pollution control *** mixing ratio of NMHCs showed no statistical interannual changes,of which their compositions exhibited marked *** resulted in a decreasing trend of ozone formation potential by 3.8%/year(p<0.05,the same below),which should be beneficial to ozone pollution mitigation as its production in Shanghai is in the NMHCs-limited *** alkanes,aromatics and acetylene changed by+3.7%/year,-5.9%/year and-7.4%/year,respectively,and alkenes showed no apparent *** sources were apportioned by a positive matrix factorization ***,vehicular emissions(-5.9%/year)and petrochemical industry emissions(-7.1%/year)decreased significantly,but the decrease slowed down;significant reduction in solvent usage(-9.0%/year)appeared after 2010;however,emissions of natural gas(+12.6%/year)and fuel evaporation(with an increasing fraction)became more *** inconsistency between observations and inventories was found in interannual trend and speciation as well as source contributions,emphasizing the need for further validation in NMHCs emission *** study confirms the effectiveness of measures targeting mobile and centralized emissions from industrial sources and reveals a need focusing on fugitive emissions,which provided new insights into future air policies in polluted region.

关键词： Characteristics Source apportionment Observation-based Interannual trend Shanghai

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Large-scale data archiving: At the interface of archive science and computer science

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data Science and Informetrics 2023年第3期3卷 1-17页

作者： Chaolemen Borjigin Qingwen Jin Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of ChinaBeijingChina School of Information Resource Management Renmin University of ChinaBeijingChina

Both computer science and archival science are concerned with archiving large-scale data,but they have different ***-scale data archiving in computer science focuses on technical aspects that can reduce the cost of data storage and improve the reliability and efficiency of big data *** weaknesses lie in inadequate and non-standardized *** in archival science focuses on the management aspects and neglects the necessary technical considerations,resulting in high storage and retention costs and poor ability to manage big ***,the integration of large-scale data archiving and archival theory can balance the existing research limitations of the two fields and propose two research topics for related research-archival management of big data and large-scale management of archived big data.

关键词： data archiving Archive Science Computer Science Large-scale data data storage

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Performance Analysis for Configured Active RIS-Aided Communication Systems

Performance Analysis for Configured Active RIS-Aided Communi...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Li, Longze Zhao, Haitao Ni, Yiyang Xu, Zhuoran Xun, Wei Xu, Bangning Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Wireless Communications Nanjing210003 China Jiangsu Second Normal University Nanjing Jiangsu Province Engineering Research Center of Basic Education Big Data Application 210003 China

ISBN: (纸本)9798350345384

The reconfigurable intelligent surface (RIS) is a crucial wireless channel control technology in 6G systems. Unlike traditional passive RIS (PRIS), active RIS (ARIS) can overcome the "multiplicative fading"effect. However, the configuration of the reflecting elements can significantly impact the system performance. In this paper, we focus on the ARIS equipped with uniform planar array (UPA) reflecting elements. We provide the ergodic achievable rate (EAR) for both unconfigured and configured ARIS system with closed-form. The effects of reflecting element area on the signal-to-noise ratio (SNR) are investigated, and a model selection scheme is proposed to determine whether to use ARIS or PRIS. Moreover, we analyze the average received power (ARP) and amplification power in ARIS. Based on the results of the analysis, a joint reflecting element area and quantity optimization scheme is proposed to improve system performance. The simulation results verify the accuracy of the analysis and highlight the superiority of the ARIS-assisted communication system. © 2023 IEEE.

关键词： Signal to noise ratio

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Exploring Heterogeneity and Uncertainty for Graph-based Cognitive Diagnosis Models in Intelligent Education

arXiv

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arXiv 2024年

作者： Shao, Pengyang Yang, Yonghui Gao, Chen Chen, Lei Zhang, Kun Zhuang, Chenyi Wu, Le Li, Yong Wang, Meng Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Anhui Hefei China BNRist Tsinghua University Beijing China Department of Electronic Engineering BNRist Tsinghua University Beijing China Ant Group Zhejiang Hangzhou China

Graph-based Cognitive Diagnosis (CD) has attracted much research interest due to its strong ability on inferring students’ proficiency levels on knowledge concepts. While graph-based CD models have demonstrated remarkable performance, we contend that they still cannot achieve optimal performance due to the neglect of edge heterogeneity and uncertainty. Edges involve both correct and incorrect response logs, indicating heterogeneity. Meanwhile, a response log can have uncertain semantic meanings, e.g., a correct log can indicate true mastery or fortunate guessing, and a wrong log can indicate a lack of understanding or a careless mistake. In this paper, we propose an Informative Semantic-aware Graph-based Cognitive Diagnosis model (ISG-CD), which focuses on how to utilize the heterogeneous graph in CD and minimize effects of uncertain edges. Specifically, to explore heterogeneity, we propose a semantic-aware graph neural networks based CD model. To minimize effects of edge uncertainty, we propose an Informative Edge Differentiation layer from an information bottleneck perspective, which suggests keeping a minimal yet sufficient reliable graph for CD in an unsupervised way. We formulate this process as maximizing mutual information between the reliable graph and response logs, while minimizing mutual information between the reliable graph and the original graph. After that, we prove that mutual information maximization can be theoretically converted to the classic binary cross entropy loss function, while minimizing mutual information can be realized by the Hilbert-Schmidt Independence Criterion. Finally, we adopt an alternating training strategy for optimizing learnable parameters of both the semantic-aware graph neural networks based CD model and the edge differentiation layer. Extensive experiments on three real-world datasets have demonstrated the effectiveness of ISG-CD. © 2024, CC BY.

关键词： knowledge graph

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Characterizing the Performance of Deep Learning Inference for Edge Video Analytics 9th

Characterizing the Performance of Deep Learning Inference fo...

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9th CCF Conference on big data, bigdata 2021

作者： Luo, Zhenxiao Wang, Xinglong Zhang, Yuxiao Wang, Zelong Hu, Miao Wu, Di School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou510006 China

ISBN: (纸本)9789811697081

Real-time video analytics is a killer application for edge computing, however, it has not been fully understood how much edge resource is required to support compute-intensive video analytics tasks at the edge. In this paper, we conduct an in-depth measurement study to unveil the resource requirement of deep learning (DL) inference for edge video analytics (EVA). We measure the DL inference time under various resource combinations, with different physical resources (e.g., processor types, core numbers, memory), video resolutions, and DL inference models. It is observed that the relationship between DL inference time and resource configuration is complicated, which cannot be captured by a simple model. Considering the coupling effects, we model the resource requirements of the DL inference by utilizing tensor factorization (TF) method. Our TF-based DL inference model can match well with the observations from field measurements. Different from previous models, our model is completely explainable and all the components have their physical meanings. Especially, it is possible to match the top three components extracted from the TF-based model with the practical DL functional layers, namely, convolutional layer, pooling layer, and fully-connected layer. The measurement results show that the top three components contribute approximately 50%, 25%, and 10% time for DL inference execution, which provides clear instruction on fine-grained DL task scheduling for edge video analytics applications. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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Backdoor Attacks on Bimodal Salient Object Detection with RGB-Thermal data 24

Backdoor Attacks on Bimodal Salient Object Detection with RG...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Yin, Wen Zhu, Bin Benjamin Xie, Yulai Zhou, Pan Feng, Dan School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Microsoft Corporation Beijing China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9798400706868

RGB-Thermal Salient Object Detection (RGBT-SOD) plays a critical role in complex scene recognition applications, such as autonomous driving. However, security research in this domain is still in its infancy. This paper presents the first backdoor attack on RGBT-SOD systems, generating saliency maps on triggered inputs that depict non-existent salient objects chosen by the attacker or falsely mark an entire image as fully salient or entirely non-salient. We uncover that triggers have an influence range for generating non-existent salient objects, supported by a theoretical analysis. Extensive experiments show the effectiveness of our attack in both digital and physical-world scenarios. Notably, our dual-modality backdoor attack achieves an Attack Success Rate (ASR) of 86.72% with only five pairs of poisoned images in model training. After investigating potential countermeasures, we find them inadequate in mitigating our attacks, highlighting the urgent need for robust defenses against sophisticated backdoor attacks in RGBT-SOD systems. © 2024 ACM.

关键词： Object detection

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