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2021 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems

作者： Yang, Jisan Jiang, Jie Tian, Lingfeng School of Instrumentation and Optoelectronic Engineering Beihang University No. 37 Xueyuan Road Beijing100191 China Precision Opto-mechatronics Technology Key Laboratory of Education Ministry Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beijing China

ISBN: (纸本)9781510655690

An airborne multiple-field-of-view (multi-FOV) star tracker operating inside the atmosphere has particular limitations in observation. It is necessary to optimize its structure parameters for improving its attitude determination and reliability in the working circumstances. In this paper, performance simulations for different multi-FOV structures are carried out. In the simulation design, the terrain occlusion, stellar atmospheric refraction, and atmospheric extinction are the main considerations. When conducting the simulation experiments, within the permitted attitude ranges, abundant random attitude of a star tracker was generated for performance testing, including three-axis attitude error and stellar detection probability. The results show that, with no refraction exists, when the tilt angle of the boresight of each FOV is at 40°~45°, regardless of which structural layout is adopted, both the attitude measurement accuracy and the stellar detect probability of single FOV is relatively high. With refraction exists, the tilt angles of the boresights are larger, the attitude measurement error is greater. For an airborne multi-FOV star tracker, a FOV with 0° tilt angle is necessary to promote its reliability. © 2022 SPIE.

关键词： Star trackers

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Forward engineering completeness for software by using requirements validation framework 31

Forward engineering completeness for software by using requi...

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31st International Conference on Software engineering and knowledge engineering, SEKE 2019

作者： Iqbal, Nayyar Sang, Jun Gao, Min Hu, Haibo Xiang, Hong Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing University Chongqing400044 China School of Big Data and Software Engineering Chongqing University Chongqing401331 China Department of Computer Science University of Agriculture Faisalabad Faisalabad38000 Pakistan

ISBN: (纸本)1891706489

In software development environment, software companies usually ignore the user requirements validation process in requirement gathering phase, which results in large number of modifications being required in the software maintenance phase to fulfill the customer requirements. Identification of accurate requirements from user stories and determining the effectiveness of work deliverable of software industry has always been a challenging task. In this paper, a new measurement approach for forward engineering completeness for software was introduced by using requirements validation framework. The forward engineering completeness for software was measured in two steps. In the first step, software component structure was developed in order to find the functional and nonfunctional requirements rejected by the customers in the requirement validation framework. In the second step, completeness of software from component-based development was determined in which the following parameters, such as functional, non-functional completeness attributes, were considered in the measurement process, and the unadopted attributes of the reuse code were also considered. Quality level for the attributes were assigned based upon the valuation of interior quality of the source code. Therefore, it resulted in the reduction of development time required for the software and the cost required for the software development was also reduced. A case study was incorporated in this research to explain the measurement process of forward engineering completeness. If the forward engineering code is satisfying the quality standards, then the code is in the completeness form. The attributes of code that negates to be used were considered as unadopted attributes. © 2019 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Computer software reusability

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CONSTRUCTURE: Benchmarking CONcept STRUCTUre REasoning for Multimodal Large Language Models

CONSTRUCTURE: Benchmarking CONcept STRUCTUre REasoning for M...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zha, Zhiwei Zhu, Xiangru Xu, Yuanyi Huang, Chenghua Liu, Jingping Li, Zhixu Wang, Xuwu Xiao, Yanghua Yang, Bei Xu, XiaoXiao Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China School of Information Science and Engineering East China University of Science and Technology China Alibaba Group China School of Information Renmin University of China China Renmin University of China China

ISBN: (纸本)9798891761681

Multimodal Large Language Models (MLLMs) have shown promising results in various tasks, but their ability to perceive the visual world with deep, hierarchical understanding similar to humans remains uncertain. To address this gap, we introduce CONSTRUCTURE, a novel concept-level benchmark to assess MLLMs' hierarchical concept understanding and reasoning abilities. Our goal is to evaluate MLLMs across four key aspects: 1) Understanding atomic concepts at different levels of abstraction;2) Performing upward abstraction reasoning across concepts;3) Achieving downward concretization reasoning across concepts;and 4) Conducting multi-hop reasoning between sibling or common ancestor concepts. Our findings indicate that even state-of-the-art multimodal models struggle with concept structure reasoning (e.g., GPT-4o averages a score of 62.1%). We summarize key findings of MLLMs in concept structure reasoning evaluation. Morever, we provide key insights from experiments using CoT prompting and fine-tuning to enhance their abilities. © 2024 Association for Computational Linguistics.

关键词： Abstracting

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MyWAL:performance optimization by removing redundant input/output stack in key-value store

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Frontiers of Information Technology & Electronic engineering 2023年第7期24卷 980-993页

作者： Xiao ZHANG Mengyu LI Michael NGULUBE Yonghao CHEN Yiping ZHAO School of Computer Science Northwestern Polytechnical UniversityXi'an 710072China MIIT Key Laboratory of Big Data Storage and Management Northwestern Polytechnical UniversityXi'an 710072China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical UniversityXi'an 710072China School of Software Northwestern Polytechnical UniversityXi'an 710072China

Based on a log-structured merge(LSM)tree,the key-value(KV)storage system can provide high reading performance and optimize random writing *** is widely used in modern data storage systems like e-commerce,online analytics,and real-time *** LSM tree stores new KV data in the memory and flushes to disk in *** prevent data loss in memory if there is an unexpected crash,RocksDB appends updating data in the write-ahead log(WAL)before updating the ***,synchronous WAL significantly reduces writing *** this paper,we present a new WAL mechanism named *** directly manages raw devices(or partitions)instead of saving data on a traditional file *** can avoid useless metadata updating and write data sequentially on *** results show that MyWAL can significantly improve the data writing performance of RocksDB compared to the traditional WAL for small KV data on solid-state disks(SSDs),as much as five to eight times *** non-volatile memory express soild-state drives(NVMe SSDs)and non-volatile memory(NVM),MyWAL can improve data writing performance by 10%–30%.Furthermore,the results of YCSB(Yahoo!Cloud Serving Benchmark)show that the latency decreased by 50%compared with SpanDB.

关键词： key-value(KV)store Log-structured merge(LSM)tree Non-volatile memory(NVM) Non-volatile memory express soild-state drive(NVMe SSD) Write-ahead log(WAL)

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Towards Efficient and Diverse Generative Model for Unconditional Human Motion Synthesis 24

Towards Efficient and Diverse Generative Model for Unconditi...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Yu, Hua Liu, Weiming Bai, Jiapeng Gui, Xu Hou, Yaqing Ong, Yewsoon Zhang, Qiang Key Laboratory of Social Computing and Cognitive Intelligence Ministry of Education School of Computer Science and Technology Dalian University of Technology Dalian China College of Computer Science Zhejiang University Hangzhou China National and Local Joint Engineering Laboratory of Computer Aided Design School of Software Engineering Dalian University Dalian China College of Computing and Data Science Nanyang Technological University Singapore Singapore Yonsei University Seoul Korea Republic of

ISBN: (纸本)9798400706868

Recent generative methods have revolutionized the way of human motion synthesis, such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Denoising Diffusion Probabilistic Models (DMs). These methods have gained significant attention in human motion fields. However, there are still challenges in unconditionally generating highly diverse human motions from a given distribution. To enhance the diversity of synthesized human motions, previous methods usually employ deep neural networks (DNNs) to train a transport map that transforms Gaussian noise distribution into real human motion distribution. According to Figalli's regularity theory, the optimal transport map computed by DNNs frequently exhibits discontinuities. This is due to the inherent limitation of DNNs in representing only continuous maps. Consequently, the generated human motions tend to heavily concentrate on densely populated regions of the data distribution, resulting in mode collapse or mode mixture. To address the issues, we propose an efficient method called MOOT for unconditional human motion synthesis. First, we utilize a reconstruction network based on GRU and transformer to map human motions to latent space. Next, we employ convex optimization to match the noise distribution with the latent space distribution of human motions through the Optimal Transport (OT) map. Then, we combine the extended OT map with the generator of reconstruction network to generate new human motions. Thereby overcoming the issues of mode collapse and mode mixture. MOOT generates a latent code distribution that is well-behaved and highly structured, providing a strong motion prior for various applications in the field of human motion. Through qualitative and quantitative experiments, MOOT achieves state-of-the-art results surpassing the latest methods, validating its superiority in unconditional human motion generation. © 2024 ACM.

关键词： Generative adversarial networks

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Object Detection Algorithm Based on Bimodal Feature Alignment 7th

Object Detection Algorithm Based on Bimodal Feature Alignme...

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Sun, Ying Hou, Zhiqiang Yang, Chen Ma, Sugang Fan, Jiulun School of Computer Science and Technology Xi’an University of Posts and Telecommunications Xi’an710121 China Key Laboratory of Network Data Analysis and Intelligent Processing of Shaanxi Province Xi’an710121 China School of Communications and Information Engineering Xi’an University of Posts and Telecommunications Xi’an710121 China

ISBN: (纸本)9783031476334

A dual-modal feature alignment based object detection algorithm is proposed for the full fusion of visible and infrared image features. First, we propose a two stream detection model. The algorithm supports simultaneous input of visible and infrared image pairs. Secondly, a gated fusion network is designed, consisting of a dual-modal feature alignment module and a feature fusion module. Medium-term fusion is used, which will be used as the middle layer of the dual-stream backbone network. In particular, the dual-mode feature alignment module extracts detailed information of the dual-mode aligned features by computing a multi-scale dual-mode aligned feature vector. The feature fusion module recalibrates the bimodal fused features and then multiplies them with the bimodal aligned features to achieve cross-modal fusion with joint enhancement of the lower and higher level features. We validate the performance of the proposed algorithm using both the publicly available KAIST pedestrian dataset and a self-built GIR dataset. On the KAIST dataset, the algorithm achieves an accuracy of 77.1%, which is 17.3% and 5.6% better than the accuracy of the benchmark algorithm YOLOv5-s for detecting visible and infrared images alone;on the self-built GIR dataset, the detection accuracy is 91%, which is 1.2% and 14.2% better than the benchmark algorithm for detecting visible and infrared images alone respectively. And the speed meets the real time requirements. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

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A calibration method of structural model for multi-FOV star tracker based on theodolite crosshair imaging

A calibration method of structural model for multi-FOV star ...

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2021 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems

作者： Tian, Lingfeng Jiang, Jie Yang, Jisan School of Instrumentation and Optoelectronic Engineering Beihang University No. 37 Xueyuan Road Beijing100191 China Precision Opto-mechatronics Technology Key Laboratory of Education Ministry Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beijing China

ISBN: (纸本)9781510655690

Compared with the traditional single field of view (FOV) star tracker, the multi-FOV star tracker has the advantages of equal measurement accuracy on three axes and better dynamic performance. The measurement accuracy of a multi-FOV star tracker is directly determined by the accuracy of the structural model. However, existing structural model calibration methods cannot be applied to the high precision multi-FOV star trackers with large size and weight. To solve this issue, a calibration method of the structural model for the multi-FOV star tracker based on theodolite crosshair imaging is proposed. An imaging model of theodolite crosshair in star tracker is established which elaborates the relationship between the theodolite angles and the star tracker images. Multiple theodolites are utilized to pair each FOV of the star tracker. In each pair, through collecting the angles measured by the theodolite and the images captured by the star tracker, the rotation between the theodolite frame and the star tracker FOV frame could be solved. Additionally, the rotations between theodolite frames are obtained by mutual collimation of theodolites. Finally, the structural model which contains the rotations between the different FOV frames is acquired by merging the above rotations. Structural model calibration experiments of a multi-FOV star tracker with a large size and weight have been conducted. The experimental result indicated that the mean star angular distance error between FOVs was less than 10 arcseconds. The accuracy of the calibration result met the practical requirements. The proposed method is free from the in uence of the size and weight of multi-FOV star trackers and maintains high calibration accuracy. © 2022 SPIE.

关键词： Stars

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Dual Templates Siamese Tracking 5th

Dual Templates Siamese Tracking

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5th Asian Conference on Pattern Recognition, ACPR 2019

作者： Hou, Zhiqiang Chen, Lilin Pu, Lei Institute of Computer Xi’an University of Posts and Telecommunications Xi’an710121 China Information and Navigation Institute of Air Force Engineering University Xi’an710077 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an University of Posts and Telecommunications Xi’an710121 China

ISBN: (纸本)9783030414030

In recent years, Siamese networks which is based on appearance similarity comparison strategy has attracted great attention in visual object tracking domain due to its balanced accuracy and speed. However, most Siamese networks based tracking algorithms have not considered template updates. The fixed template may cause tracking matching error and can even cause failure of object tracking. In view of this deficiency, we proposed an algorithm based on dual templates Siamese network using difference hash algorithm to determine the template update timing. First, we kept the initial frame target with stable response map score as the base template zr, using the difference hash algorithm to determine the dynamic template zt. We analyzed the candidate targets region and the two template matching results, meanwhile the result response maps were fused, which could ensure more accurate tracking results. The experiment results on the OTB-2013 and OTB-2015 and VOT2016 datasets showed that the proposed algorithm has achieved satisfactory result. © Springer Nature Switzerland AG 2020.

关键词： Template matching

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Self-knowledge Distillation for the Object Segmentation Based on Atrous Spatial Pyramid 5

Self-Knowledge Distillation for the Object Segmentation Base...

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2022 5th International Symposium on Big data and Applied Statistics, ISBDAS 2022

作者： Wang, Xiaobing Zheng, Yunfei Zhang, Xiongwei Cao, Tieyong Li, Chenming Wang, Xiulai Wang, Yong Fang, Zheng Wang, Yang Army Engineering University PLA Nanjing210016 China PLA Army Academy of Artillery and Air Defense Hefei230022 China Key Laboratory of Polarization Imaging Detection Technology Hefei230022 China Medical Information Data Room Jinling Hospital Nanjing210018 China

This paper presents an effective Self-knowledge Distillation (SKD) framework via Atrous Spatial Pyramid Structure (ASPS), which is able to enhance the performance of the object segmentation network without increasing network parameters. In the framework, a lightweight object segmentation network is constructed to achieve the pixel-level object segmentation efficiently. A SKD learning model, including the SKD representation structure based on ASPS and loss function, is proposed to transfer the knowledge in the ASPS into our object segmentation network and improve its generalization ability. The experimental results confirm that compared with recent typical object segmentation networks, our object segmentation network contains the fewest parameters but achieves better performance. Moreover, the proposed SKD method achieves the best performance-boosting compared with recent SKD methods © Published under licence by IOP Publishing Ltd.

关键词： Distillation

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A network anomaly monitoring method based on edge computing for CPS/IOT 2

A network anomaly monitoring method based on edge computing ...

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2nd IEEE International Conference on Industrial Internet Cloud, ICII 2019

作者： Cao, Zhiyong Cai, Xiaobo Li, Haipeng Huang, Wei Yang, Xiujuan Tao, Linli Zhang, Xi Wang, Huihui College of Animal Science and Technology Yunnan Agricultural University Kunming China College of Big Data Yunnan Agricultural University Kunming China Yunnan Provincial Key Laboratory of Animal Nutrition and Feed Science Kunming China Department of Engineering Jacksonville University Jacksonville United States

ISBN: (数字)9781728129778

ISBN: (纸本)9781728129778

In the large-scale IoT monitoring system, the cloud platform has been used as a remote data and control center. However, a large amount of data uploading and processing in the system brings great challenges to the cloud platform's bandwidth load and real-time feedback. Therefore, the paper proposed the framework of CPS/IoT monitoring system based on edge computing. On this basis, an anomaly detection method based on self-encoding neural network is proposed. The simulation data of the standardized pastures in Yunnan Province from 2017 to 2018 were used in the field. The simulation results show that the anomaly detection method based on self-encoding neural network can make full use of the spatial correlation of the collected data and accurately detect the anomaly data. © 2019 IEEE.

关键词： Edge computing

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