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共 2709 条记录，以下是41-50 订阅

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Accelerating High-Precision Vulnerability Detection in C Programs with parallel Graph Summarization 6

Accelerating High-Precision Vulnerability Detection in C Pro...

引用

6th international conference on Software Engineering and Computer Science, CSECS 2023

作者： Xu, Rulin Mao, Xiaoguang Xiao, Wei School of Computer NUDT Changsha China

ISBN: (纸本)9798350306378

C language programs are often subject to memory vulnerabilities, posing substantial security risks to software systems. Conventional detection techniques, rooted in static value-flow analysis, necessitate exhaustive searches across the entirety of value-flow graphs. this approach results in inefficient analyses of large-scale codes and presents difficulties in parallelization due to interdependent steps. In this study, we propose an innovative approach based on parallel graph summarization. this technique effectively transforms the computational bottleneck into a task that can be expedited in a parallel manner, leveraging multicore computation to significantly enhance the performance and scalability of vulnerability detection within $C$ programs. We segment the value-flow graph of the program into multiple subgraphs, extracting summaries of three pivotal types of information from each subgraph: path summaries, guard summaries, and behaviour summaries. these summaries significantly stream-line subsequent vulnerability detection analyses. Moreover, we implement a task-level parallel technique to accelerate the graph summary process in a multicore environment. Notably, empirical results reveal that our method, while ensuring accuracy, achieves 2.7X-6.1X speedup compared to serial algorithms. When assessed against prevalent open-source detection tools, our approach demonstrates superior trade-offs between accuracy and efficiency. In conclusion, this research presents an efficient and effective strategy for vulnerability detection in larze-scale C programs. © 2023 IEEE.

关键词： Static analysis

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A Novel Redundant Data Retrieval Model based on parallel Batch Algorithm 6

A Novel Redundant Data Retrieval Model based on Parallel Bat...

引用

6th international conference on Inventive Computation Technologies, ICICT 2023

作者： Wei, Cui Qingbo, Lu Na, Ding Eng Congli, Cui Zhengzhou Technical College Henan Zhengzhou450000 China UCSI University UCSI Heights No. 1 Jalan Menara Gading Kuala Lumpur Cheras56000 Malaysia Zhengzhou Electronic Information Engineering School Henan Zhengzhou450007 China

ISBN: (纸本)9798350398496

For the effective information retrieval models, traditional unsupervised cross-modal hashing methods try to learn hash functions from the underlying structure, distribution, and topological information of the data in order to preserve the original data spatial structure. Hence, to conduct more efficient analysis, this research study proposes a novel redundant data retrieval model based on parallel batch algorithm. Batch parallel proofreading is oriented to large-scale text offline proofreading scenarios, and has powerful computing power provided by the cluster computing. With this operation, the data will be preprocessed to better clean the row data. then, the hash model is integrated to consider the key as a divisor, the dividend as a maximum prime number p not greater than the length of the hash table m, and uses the remainder of the calculation result as the final hash function. Furthermore, the model is revised to construct the efficient data retrieval task. through testing, the performance of the proposed algorithm is proven to be efficient. © 2023 IEEE.

关键词： Hash functions

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Application of greedy algorithm and multi scale optimization algorithm in dynamic grid computing 6

Application of greedy algorithm and multi scale optimization...

引用

2023 IEEE 6th international conference on Information Systems and Computer Aided Education, ICISCAE 2023

作者： Xi, Bei'er Duan, Qinglin Dalian University of Technology Faculty of Vehicle Engineering and Mechanics Dalian China

ISBN: (纸本)9798350313444

Aiming at the high computational complexity of the traditional radial basis function (RBF), which is difficult to be applied effectively in large-scale computation, a method using greedy algorithm and multi-scale optimization algorithm is proposed to optimize the RBF. Based on RBF calculation method, this paper explores the application of greedy algorithm and multi-scale optimization algorithm in dynamic grid computing. Greedy algorithm improves computing efficiency and accuracy by selecting the best node, while multi-scale optimization algorithm improves computing speed and accuracy by dividing the grid into different scales. the effectiveness of greedy algorithm and multi-scale optimization algorithm to improve the efficiency and accuracy of dynamic grid computing is proved by an example. © 2023 IEEE.

关键词： Dynamic grid computing Greedy algorithm Multi-scale optimization algorithm Radial basis function

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A Numerical Model Oriented Large-scale parallel I/O Optimization Method 6

A Numerical Model Oriented Large-scale Parallel I/O Optimiza...

引用

6th international conference on Data Storage and Data Engineering, DSDE 2023

作者： Zhang, Lei Wu, Tao Zhou, Zheng Wang, Dong Chen, Xi School of Computer Science Chengdu University of Information Technology Chengdu China Tsinghua University Department of Earth System Science Beijing China College of Computer Southwest Minzu University Chengdu China

ISBN: (纸本)9798350333145

Numerical models usually contain a large number of data reading and writing, which generally takes a long time. At present, massively parallel technology has accelerated the speed of computing in model, but due to the limitation of computer I/O ability, the acceleration effect is limited, and there is a serious load imbalance during the model operation process, resulting in a waste of computing resources. To deal with that, this paper proposes a new I/O scheme, which can dynamically optimize task allocation during program operation, make full use of computing resources, and increase the mutual coverage of computing and I/O processes, so as to effectively shorten the model running time. Finally, the test in the earth simulator shows that the new I/O scheme improves the operation speed of the regional high-precision air pollution model by 25.45%. © 2023 IEEE.

关键词： Numerical models

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DGIC: A Distributed Graph Inference computing Framework Suitable For Encoder-Decoder GNN 2022

DGIC: A Distributed Graph Inference Computing Framework Suit...

引用

6th international conference on Innovation in Artificial Intelligence (ICIAI)

作者： Pan, Zeting Chang, Junsheng Natl Univ Def Technol Coll Comp Changsha Peoples R China

ISBN: (纸本)9781450395502

*A graph is a structure that can express the relationship between objects. the emergence of GNN enables deep learning to be applied in the field of graphs. However, most GNNs are trained offline and cannot be directly used in real-time monitoring scenarios such as financial risk control. In addition, due to the large scale of graph data, a single machine often cannot meet actual needs, and there are bottlenecks such as throughput performance. therefore, we propose a distributed graph inference computing framework, which can be applied to Encoder-Decoder GNN models. We complete the adaptation of the model by disassembling the graph data and using the extension storage and dynamic invocation mechanism to solve the model invocation problem. For inference performance, we implement dynamic graph construction through incremental composition and decouple the inference process to apply to different scenarios, so that GNNs conforming to the Encoder-Decoder style can be applied to the framework. A large number of experiments show that this method has good timeliness while improving the throughput upper limit, and can maintain the model effect of multi-tasking.

关键词： Graph inference Graph Neural Networks Distributed graph computing

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Cryptographic Reverse Firewall for Digital Signature in Fog computing 6

Cryptographic Reverse Firewall for Digital Signature in Fog ...

引用

6th international conference on Software Engineering and Computer Science, CSECS 2023

作者： Kang, Burong Lian, Huanhuan Zhou, Xuhua Zhou, Weniun Research Institute of China Telecom Corporation Limited Security Technology Research Division Shanghai China

ISBN: (纸本)9798350306378

Fog computing (FC) is introduced as an extended technique of cloud computing. FC makes it possible to compute straightly on the brim of the network. In FC application systems, authentication is an important security requirement when fog nodes communicate with other fog devices. Digital signature (DS) has been widely used in FC systems to provide the non-repudiation, authenticity along with data integrity. However, some latest research results demonstate that DS schemes may confront the algorithm substitution attack (ASA). that is, DS scheme would be implanted some covert backdoor information in algorithm implementation process by attackers. With the backdoor information attackers can recover the secret key of fog devices' users, which will result in privacy disclosure. To settle this matter, the notion of cryptographic reverse firewall (CRF) is proposed, which can re-randomize the inputs and outputs of the fog devices. Moreover, due to the limited storing and computing abilities of fog devices, the DS algorithms applied to FC systems should be resource-saving. In this paper, we simultaneously focus attention on addressing above two problems in fog computing and construct the CRFs for the Camenisch and Lysyanskaya DS scheme (CL signature) which is suitable to be applied in FC systems because of its high efficiency. © 2023 IEEE.

关键词： Fog computing

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Numerical Analysis of Synchronous Dislocation Scheduling Algorithm Optimization in Shared Cloud computing Environment

Numerical Analysis of Synchronous Dislocation Scheduling Alg...

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6th international conference on Intelligent computing and Control Systems, ICICCS 2022

作者： Lu, Xikui Tang, Shihua Henan Geology Mineral College Department of Surveying and Mapping Engineering Zhengzhou 450046 China Guilin University of Technology College of Geomatics and Geoinformation Guilin 541004 China

ISBN: (纸本)9781665410359

this paper studies the numerical analysis of the optimization of the synchronization misalignment scheduling algorithm under the shared cloud computing environment. First, the user submitted job is initialized, and then the job is inserted into the execution queue according to the appropriate strategy of the user synchronization misalignment scheduling algorithm. Establish multiple simultaneous multiple vacations Queuing model. the steady-state distribution of the system model is given by the quasi-birth-death process and the matrix geometric solution method, and the expressions of the average response time of the task and the average power of the system are derived. the test results show that in the case of multiple virtual machines, compared with Xen's Credit scheduling algorithm, the synchronization optimization scheduling system CCHybrid improves the performance of parallel loads by 15% to 50%, and the performance impact on non-parallel loads does not exceed 5%. © 2022 IEEE.

关键词： Cloud computing

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Galaxy Morphology Classification Based on VGG19 Deep Convolutional Neural Network 6

Galaxy Morphology Classification Based on VGG19 Deep Convolu...

引用

6th international conference on Advancements in computing, ICAC 2024

作者： Fernando, thrinith Rathnayake, Samadhi Dissanayaka, Kapila Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331517878

Galaxy morphology classification is crucial for understanding galaxy formation and evolution. Traditional methods for classifying galaxy morphologies are labour-intensive and require expert knowledge. Recent deep learning approaches simplify this process but often focus only on basic galaxy types, such as spiral, elliptical, and irregular, overlooking more complex or mixed morphologies. this study applied a transfer learning-based model for 10-class galaxy morphology classification using the Galaxy10 DECaLS dataset, which contains 17,736 images across 10 distinct galaxy types that diverge from the primary galaxy morphology types. the proposed classification model employed VGG19 as the base for feature extraction, supplemented by custom fully connected layers for classification. the approach included comprehensive data preprocessing, extensive data augmentation, the use of learning rate reduction and model checkpointing during training. A thorough evaluation using multiple metrics demonstrated significant improvements in classification performance, achieving 97.97% accuracy, 89.84% precision, 89.69% recall, an F1-score of 89.68%, and an area under the curve (AUC) of 0.98 on test data using macro-averaging. these findings confirmed the efficacy of deep learning models for automating galaxy morphology classification and underscored the benefits of transfer learning in achieving high accuracy. © 2024 IEEE.

关键词： Convolutional neural networks

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Adapting Speech Models for Stock Price Prediction 6

Adapting Speech Models for Stock Price Prediction

引用

6th international conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Voigt, Frederic Calero, Jose Alcarez Dahal, Keshav Wang, Qi Luck, Kai Von Stelldinger, Peer University of the West of Scotland United Kingdom Hamburg University of Applied Sciences Department of Computer Science Hamburg Germany University of the West of Scotland School of Computing Engineering & Physical Sciences Paisley United Kingdom

ISBN: (纸本)9798331505790

Large language models (LLMs) have demonstrated remarkable success in the field of natural language processing (NLP). Despite their origins in NLP, these algorithms possess the theoretical capability to process any data type represented in an NLP-like format. In this study, we use stock data to illustrate three methodologies for processing regression data with LLMs, employing tokenization and contextualized embeddings. By leveraging the well-known LLM algorithm Bidirectional Encoder Representations from Transformers (BERT) [1], we apply quantitative stock price prediction methodologies to predict stock prices and stock price movements, showcasing the versatility and potential of LLMs in financial data analysis. © 2024 IEEE.

关键词： Prediction models

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Research on Performance Enhancement of parallel computing in Intelligent Proofreading System 6th

Research on Performance Enhancement of Parallel Computing in...

引用

6th international conference on Innovative computing, IC 2023

作者： Guo, Zhishuai Zhang, Fucheng Neusoft Group Co. Ltd Liaoning Shenyang China

ISBN: (纸本)9789819920914

this paper describes the status quo of intelligent checking technology and the efficiency problems existing in the current checking system, and analyzes the reasons why the processing complexity of the checking system determines the time consuming of serial execution. through the introduction of parallel computing technology, the paper finds out the tasks suitable for multi-process and multi-thread in the checking system. through the reference of openMPI and Pthread, through multi-scene and multi-parameter experiments, the direction and method of parallel computing performance improvement and parameter value measures are obtained, and the parallel computing optimization strategy of the existing intelligent checking and checking system is proposed. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： FPMax Intelligent Proofreading parallel computing

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