Proceedings of the 5th International Conference on Computer Science and Application Engineering最新文献_第9页

Automatic Recognition and Segmentation of Composite User Stories Based on Semantic Analysis 基于语义分析的复合用户故事自动识别与分割

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487089

Yufeng Ma, Yajie Dou, Mengru Wang, Yitong Wang, Miao Jiang, Yanjing Lu

{"title":"Automatic Recognition and Segmentation of Composite User Stories Based on Semantic Analysis","authors":"Yufeng Ma, Yajie Dou, Mengru Wang, Yitong Wang, Miao Jiang, Yanjing Lu","doi":"10.1145/3487075.3487089","DOIUrl":"https://doi.org/10.1145/3487075.3487089","url":null,"abstract":"User stories are often used in agile development to express user needs. Accurate and rapid understanding of user stories is critical to product development. One of the major obstacles to accurate and efficient story understanding is the ambiguity of story statement caused by the existence of compound user stories. Therefore, the understanding of user stories is crucial to product development. One aspect that hinders the efficiency of story understanding is compound user stories, especially in Chinese, so identifying compound stories in the early stages of development is a major goal of this article. This paper proposes a method for identifying and segmenting compound stories based on semantic analysis, which includes analyzing the structural and semantic features of compound stories, building a feature dictionary, and automatically recognizing compound stories based on HanLP. This paper takes the user story of a game live broadcast system as an example, and the research proves that the method proposed in this paper can well identify common compound user stories.","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"28 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133384325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HDBFuzzer–Target-oriented Hybrid Directed Binary Fuzzer hdbfuzzer -面向目标的混合定向二进制模糊器

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487124

Yingchao Yu, Xiaojun Qin, Shuitao Gan

{"title":"HDBFuzzer–Target-oriented Hybrid Directed Binary Fuzzer","authors":"Yingchao Yu, Xiaojun Qin, Shuitao Gan","doi":"10.1145/3487075.3487124","DOIUrl":"https://doi.org/10.1145/3487075.3487124","url":null,"abstract":"In this paper, we propose a target-oriented hybrid directed binary fuzzer (HDBFuzzer) to solve the vulnerability confirmation problem based on binary code similarity comparison. HDBFuzzer combines macro function level direction fuzzing and micro path-constraint directed solving. For some branches with simple or loose constraints, it still uses directed mutation of the directed fuzzing to penetrate while for some really hard-to-penetrate constraints, it resorts to guided concolic execution. At the same time, in order to improve the efficiency of constraint solving, we propose a constraint solving method based on “path abstraction”, which approximates the solution space by the linear expression and generates effective input utilizing the highly-effective sampling method towards the linear space. Then, under the guidance by the directed greybox fuzzing, HDBFuzzer can generate input that can quickly reach the vulnerable code region and finally crash the program under the test to confirm the vulnerability hidden in the binary program. We evaluate HDBFuzzer against AFLGo-B and QSYM on LAVA-M dataset and ten real-world programs, and the results show that HDBFuzzer is superior to AFLGo-B and QSYM on the bug discovery, bug reproduction and target reaching capabilities.","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129212866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Forecasting Port Container Throughput with Deep Learning Approach 基于深度学习方法的港口集装箱吞吐量预测

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487173

Fuxin Jiang, Gang Xie, Shouyang Wang

引用次数: 1

FCOSMask: Fully Convolutional One-Stage Face Mask Wearing Detection Based on MobileNetV3 FCOSMask:基于MobileNetV3的全卷积单阶段口罩佩戴检测

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487078

Yang Yu, Jie Lu, Chao Huang, Bo Xiao

引用次数: 0

Remaining Useful Life Prediction of Equipment Based on XGBoost 基于XGBoost的设备剩余使用寿命预测

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487134

Zhiyang Jia, Zhibo Xiao, Yijin Shi

引用次数: 1

Enriching Attributes from Knowledge Graph for Fine-grained Text-to-Image Synthesis 基于细粒度文本到图像合成的知识图属性丰富

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487155

Yonghua Zhu, Ning Ge, Jieyu Huang, Yunwen Zhu, Binghui Zheng, Wenjun Zhang

引用次数: 0

Prespecified-Time Control of Complex Networks Coupled with Nonlinear Dynamical Systems 非线性动力系统耦合复杂网络的预定时间控制

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487113

Juan Chen, Xinru Li, Ganbin Shen

引用次数: 0

Effective Indoor Fire Detection with Channel Shuffle Module 有效的室内火灾探测与频道洗牌模块

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487125

Hao Ge, Yichao Cao, Xiaobo Lu

引用次数: 0

Multimodal Emotion Recognition with Factorized Bilinear Pooling and Adversarial Learning 基于分解双线性池和对抗学习的多模态情绪识别

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487164

Haotian Miao, Yifei Zhang, Daling Wang, Shi Feng

{"title":"Multimodal Emotion Recognition with Factorized Bilinear Pooling and Adversarial Learning","authors":"Haotian Miao, Yifei Zhang, Daling Wang, Shi Feng","doi":"10.1145/3487075.3487164","DOIUrl":"https://doi.org/10.1145/3487075.3487164","url":null,"abstract":"With the fast development of social networks, the massive growth of the number of multimodal data such as images and texts allows people have higher demands for information processing from an emotional perspective. Emotion recognition requires a higher ability for the computer to simulate high-level visual perception understanding. However, existing methods often focus on the single-modality investigation. In this work, we propose a multimodal model based on factorized bilinear pooling (FBP) and adversarial learning for emotion recognition. In our model, a multimodal feature fusion network is proposed to encode the inter-modality features under the guidance of the FBP to help the visual and textual feature representation learn from each other interactively. Beyond that, we propose an adversarial network by introducing two discriminative classification tasks, emotion recognition and multimodal fusion prediction. Our entire method can be implemented end-to-end by using a deep neural network framework. Experimental results indicate that our proposed model achieves competitive performance on the extended FI dataset. Progressive results prove the ability of our model for emotion recognition against other single- and multi-modality works respectively.","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125187049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A 6G Oriented High-Throughput Satellite Communication Demodulation Method 一种面向6G高吞吐量卫星通信解调方法

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487140

Zhijie Mao, Guangen Wu, Lin Zhou

引用次数: 0