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检索条件"任意字段=10th International Conference on Algorithms and Architectures for Parallel Processing"

共 2792 条记录，以下是341-350 订阅

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Research on Integrated Detection of SQL Injection Behavior Based on Text Features and Traffic Features 10th

Research on Integrated Detection of SQL Injection Behavior B...

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10th international conference on Computer Engineering and Networks, CENet 2020

作者： Li, Ming Liu, Bo Xing, Guangsheng Wang, Xiaodong Wang, Zhihui College of Intelligence Science and Technology National University of Defence Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Processing College of Computer Science and Technology National University of Defence Technology Changsha410073 China

ISBN: (纸本)9789811584619

With the rapid development of Internet technology, various network attack methods come out one after the other. SQL injection has become one of the most severe threats to Web applications and seriously threatens various Web application services and users data security. there are both traditional detection methods and emerging methods based on deep learning technology with higher detection accuracy for the detection of SQL injection. However, they are all for detecting a single statement and cannot determine the stage of the attack. To further improve the effect of SQL injection detection, this paper proposes an integrated detection framework for SQL injection behavior based on both text features and traffic features. We propose a SQL-LSTM model based on deep learning technology as the detection model at the text features level. Meanwhile, the features of the data traffic are merged. By this integrated method, the detection effect of SQL injection is further improved. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

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Proceedings of the 46th international conference on Very Large Data Bases, VLDB October 2019

Proceedings of the 46th International Conference on Very Lar...

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46th international conference on Very Large Data Bases, VLDB 2020

this proceedings contains 10 papers. the Proceedings of the VLDB Endowment (PVLDB) provides a high-quality publication service to the data management research community. this conference address a variety of traditional and novel data management challenges. this issue focuses on designing efficient algorithms and indexing structures for graph data and for databases with security constraints or frequent update requirements, exploring opportunities from novel hardware and architectures for data management and query processing, and supporting large scale data analytics, machine learning and other novel applications, etc. the key terms of this proceedings include model slicing, elastic inference cost, cross-chain deals, multicore architectures, MVCC systems, LINC, oblivious query processing, vacuum filters, snapshot isolation, hybrid workloads.

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Efficient algorithms for constrained clustering with side information 10th

Efficient algorithms for constrained clustering with side in...

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10th international Symposium on parallel architectures, algorithms and Programming, PAAP 2019

作者： Hao, Zhendong Guo, Longkun Yao, Pei Huang, Peihuang Peng, Huihong College of Mathematics and Computer Science Fuzhou University Fuzhou China College of Mathematics and Data Science Minjiang University Fuzhou China

Clustering as an unsupervised machine learning method has broad applications within the area of data science and natural language processing. In this paper, we use background knowledge or side information of the data as constraints to improve clustering accuracy. Following the representation method as in [15], we first format the side information as must-link set and cannot-link set. then we propose a constrained k-means algorithm for clustering the data. the key idea of our algorithm for clustering must-link data sets is to treat each set as a data with large volume, which is, to assign a set of must-link data as a whole to the center closest to its mass center. In contrast, the key for clustering cannot-link data set is to transform the assignment of the involved data points to the computation of a minimum weight perfect matching. At last, we carried out numerical simulation to evaluate our algorithms for constrained k-means on UCI datasets. the experimental results demonstrate that our method outperforms the previous constrained k-means as well as the classical k-means in both clustering accuracy and runtime. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Natural language processing systems

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Accelerating Nested Data parallelism: Preserving Regularity 26th

Accelerating Nested Data Parallelism: Preserving Regularity

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26th international conference on parallel and Distributed Computing (Euro-Par)

作者： van den Haak, Lars B. McDonell, Trevor L. Keller, Gabriele K. de Wolff, Ivo Gabe Eindhoven Univ Technol Eindhoven Netherlands Univ Utrecht Utrecht Netherlands

ISBN: (纸本)9783030576752;9783030576745

Irregular nested data-parallelism is a powerful programming model which enables the expression of a large class of parallel algorithms. However, it is notoriously difficult to compile such programs to efficient code for modern parallel architectures. Regular data-parallelism, on the other hand, is much easier to compile to efficient code, but too restricted to express some problems conveniently or in a manner to exploit the full parallelism. We extend the regular data-parallel programming model to allow for the parallel execution of array-level conditionals and iterations over irregular nested structures, and present two novel static analyses to optimise the code generated for these programs which reduces the costs of this more powerful irregular model. We present benchmarks to support our claim that these extensions are effective as well as feasible, as they enable to exploit the full parallelism of an important class of algorithms, and together with our optimisations lead to an improvement in absolute performance over an implementation limited to exploiting only regular parallelism.

关键词： Arrays GPGPU Nested data parallelism parallel functional programming

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5th international conference on Microelectronics, Electromagnetics and Telecommunication, ICMEET 2019

5th International Conference on Microelectronics, Electromag...

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5th international conference on Microelectronics, Electromagnetics and Telecommunication, ICMEET 2019

ISBN: (纸本)9789811538278

the proceedings contain 81 papers. the special focus in this conference is on Microelectronics, Electromagnetics and Telecommunication. the topics include: A Tapered Microstrip-Fed Steering-Shaped Super-Wideband Printed Monopole Antenna;High-throughput VLSI architectures for VLSI Signal processing;reform Initiatives for Electrical Distribution Utilities in Jharkhand, India;FPGA Performance Evaluation of Present Cipher Using LCC Key Generation for IoT Sensor Nodes;Performance Comparison Analysis of GTTPC and AHTPC Technique for WBAN with Mobile Scenario;Estimation of FSO Link Availability for Visakhapatnam Coastal Region;CPW-Fed Monopole Antenna for RCS Reduction in X-Band Applications;Performance Improvement of Solar PV Maximum Power Point Tracking Using Sliding Mode Control Algorithm;surfactant Effect on Bandgap and Crystallite Size of ZnO–TiO2–CeO2 Nanocomposites;TEC Variation Analysis During Near Peak Solar Year Activity Over Indian Subcontinent;a Review on Schemes for Interconnecting Microgrids of Urban Buildings;performance Analysis of Multiwalled Carbon Nanotube, Composite Multiwalled Carbon Nanotube, and Copper-Based Antenna in X-Band Applications;wideband Printed Antenna Design Techniques: A Comprehensive Study;comparison of Various algorithms for Side Lobe Level Reduction in 5G Antenna Arrays;analysis of Electromagnetic Shielding Effectiveness Properties of Al6061 Metal Matrix Composites at X-Band for Aerospace Applications;a Comprehensive Study and Evaluation of Recommender Systems;design, Simulation and Experimental Validation of Patch Antenna in S-Band Satellite Communication;performance Efficient Floating-Point Multiplication Using Unified Adder–Subtractor-Based Karatsuba Algorithm;Implementation of Program Page, Read Page and Block Erase Operations in NAND Flash Memory Controller;Design of Low Standby Power 10T SRAM Cell with Improved Write Margin;preface.

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processing in Memory Assisted MEC 3C Resource Allocation for Computation Offloading 20th

Processing in Memory Assisted MEC 3C Resource Allocation for...

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20th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Yang, Yang Chang, Xiaolin Jia, Ziye Han, Zhu Han, Zhen Beijing Jiaotong Univ Beijing Key Lab Secur & Privacy Intelligent Trans Beijing Peoples R China Xidian Univ Informat Sci Inst State Key Lab ISN Xian Peoples R China Univ Houston Dept Elect & Comp Engn Houston TX USA

ISBN: (纸本)9783030602451;9783030602444

the improvement of Internet of things (IoT) applications has led to a substantial increase in the number of multiple resources of computation, communication, and caching (3C). the fifth generation (5G) and multi-access edge computing (MEC) are promising to enhance the computation offloading of IoT applications with high performance and reliability. According to resource-consuming preferences, IoT applications can be divided into computation-hungry applications and memory-hungry applications. To deal with the computation-hungry applications, Graphics processing Units (GPUs) are increasingly used to process simple computation tasks. Meanwhile, the running of memory-hungry applications is accompanied by massive data transfers between processing core and memory. these transfers can result in significant energy and performance costs. processing in memory (PIM) is a computing paradigm that avoids most data movement costs by performing a part of the computations directly in the memory. In this paper, we focus on offloading computation tasks in MEC that require 3C resources with high efficiency and low energy consumption considering latency and resilience constraints in a PIM-assisted multi-core (PAMC) architecture of physical machines (PMs). We formulate an optimization problem to minimize the total weighted resource costs and energy consumption. We also present an algorithm based on the column generation to solve the problem. Simulation results demonstrate that the proposed PAMC architecture can achieve good results in terms of energy consumption and resources utilization in comparison with the traditional PMs' architecture with the same resources.

关键词： Column generation Computation offloading GPU Multi-access edge computing processing in memory

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10th Annual international conference on Biologically Inspired Cognitive architectures, BICA 2019

10th Annual International Conference on Biologically Inspire...

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10th Annual international conference on Biologically Inspired Cognitive architectures, BICA 2019

ISBN: (纸本)9783030257187

the proceedings contain 79 papers. the special focus in this conference is on Biologically Inspired Cognitive architectures. the topics include: Practical User and Entity Behavior Analytics Methods for Fraud Detection Systems in Online Banking: A Survey;significance of Emotional Context While Performing Semantic Tasks;the Semantic Complex Event processing Based on Metagraph Approach;deceptive Actions and Robot Collision Avoidance;a Cognitive Architecture for a Transportation Robotic System;reconfigurable Locomotion of Hexapod Robot Based on Inverse Kinematics;development of Text Data processing Pipeline for Scientific Systems;environment of Modeling Methods for Indicating Objects Based on Displaced Concepts;increasing of Semantic Sustainability in the Interaction of Information Processes;story-Centric View on the Mind;computational Model for Granulating of Objects in the Semantic Network to Enhance the Sustainability of Niche Concepts;metascience and Metacognition;dynamic Parameters of the Diffusion in Human Brain White Matter During Cognitive Tasks;Preliminary Results and Analysis Independent Core Observer Model (ICOM) Cognitive Architecture in a Mediated Artificial Super Intelligence (mASI) System;independent Core Observer Model Research Program Assumption Codex;human Brain Computer/Machine Interface System Feasibility Study for Independent Core Observer Model Based Artificial General Intelligence Collective Intelligence Systems;preliminary Mediated Artificial Superintelligence Study, Experimental Framework, and Definitions for an Independent Core Observer Model Cognitive Architecture-Based System;development of an Optimal Production Plan Using Fuzzy Logic Tools;internet Users Authentication via Artificial Intelligence;biologically Inspired Algorithm for Increasing the Number of Artificial Neurons;analysis of the Possibility of the Neural Network Implementation of the Viola-Jones Algorithm;semantics Beyond Language.

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parallel Graph Clustering Based on Minhash 10th

Parallel Graph Clustering Based on Minhash

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10th international conference on Computer Science and its Applications, CSA 2018 and the 13th KIPS international conference on Ubiquitous Information Technologies and Applications, CUTE 2018

作者： Kim, Byoungwook Chung, Jaehwa Gil, Joon-Min Shon, JinGon Department of Computer Engineering Dongguk University Gyeongju Korea Republic of Department of Computer Science Korea National Open University Seoul Korea Republic of School of Information Technology Engineering Catholic University of Daegu Daegu Korea Republic of

ISBN: (纸本)9789811393402

Graph clustering is a technique for grouping vertices having similar characteristics into the same cluster. It is widely used to analyze graph data and identify its characteristics. Recently, a large-capacity large-scale graph data is being generated in a variety of applications such as a social network service, a world wide web, and a telephone network. therefore, the importance of clustering technique for efficiently processing large capacity graph data is increasing. In this paper, we propose a clustering algorithm that efficiently generates clusters of large capacity graph data. Our proposed method efficiently estimates the similarity between clusters in the graph using Min-Hash and generates clusters according to the calculated similarity. In the experiment using real world data, we show the efficiency of the proposed method compared with the proposed method and existing graph clustering methods. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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Automatic generation and assessment of student assignments for parallel programming learning 10th

Automatic generation and assessment of student assignments f...

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10th international Symposium on parallel architectures, algorithms and Programming, PAAP 2019

作者： Luo, Zhenxiao Wang, Zelong Wu, Di Hei, Xiaojun Du, Yunfei School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou510006 China School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China National Supercomputer Center in Guangzhou Guangzhou China

the course of parallel programming is becoming more and more important for the education of students majoring in computer science. However, it is not easy to learn parallel programming well due to its high theory and practice requirements. In this paper, we design and implement an automatic assignment generation and assessment system to help students learn parallel programming. the assignments can be generated according to user behaviors and thus able to guide students to learn parallel programming step by step. Besides, it can automatically generate an overall assessment of student assignments by using fuzzy string matching, which provides an approximate reference score of objective questions. Subjective questions can be assessed directly by comparing the answer to the reference answer. this system also provides a friendly user interface for students to complete online assignments and let teachers manage their question database. In our teaching practice, students can learn parallel programming more effectively with the help of such an assignment generation and assessment system. © Springer Nature Singapore Pte Ltd. 2020.

关键词： parallel programming

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Study on the method of extracting diabetes history from unstructured chinese electronic medical record 10th

Study on the method of extracting diabetes history from unst...

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10th international Symposium on parallel architectures, algorithms and Programming, PAAP 2019

作者： Niu, Chengzhi Zhao, Xiaofan The First Affiliated Hospital of Zhengzhou University Beijing China People’s Public Security University of China Zhengzhou China

In this paper, based on the real electronic medical record data of the hospital, a customized method of rule-based learning and information extraction is designed, and three steps are adopted to realize the extraction of Chinese information: sampling and labeling. the medical history information of 600 electronic medical records (including current medical history, past history, personal history, family history, etc.) were randomly selected, and the information needed to be extracted (taking diabetes history as an example) was marked by the labeling platform developed in this study. According to the annotation results, the extraction template is summarized, and the extraction template can be directly used to extract the regular expression extraction rules, and these rules can be used to extract the actual information. the method of manual verification and automatic verification is used to verify the effectiveness of the method. By using the method of natural language processing and rule-based information extraction, an algorithm for extracting customized information from unstructured Chinese electronic medical record text data is designed and implemented. Aiming at the extraction of diabetes history in the hospital, the field verification of a single department has achieved good results. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Natural language processing systems

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