检索结果-内蒙古大学图书馆

arXiv 2021年

作者： Yan, Caixia Chang, Xiaojun Luo, Minnan Liu, Huan Zhang, Xiaoqin Zheng, Qinghua The Ministry of Education Key Lab of Intelligent Networks and Network Security National Engineering Lab for Big Data Analytics School of Electronic and Information Engineering Xi'an Jiaotong University Shaanxi710049 China The ReLER Lab AAAI Faculty of Engineering and Information Technology University of Technology Sydney Australia The College of Computer Science and Artificial Intelligence Wenzhou University China

Zero-shot object detection (ZSD), the task that extends conventional detection models to detecting objects from unseen categories, has emerged as a new challenge in computer vision. Most existing approaches tackle the ZSD task with a strict mapping-transfer strategy that may lead to suboptimal ZSD results: 1) the learning process of these models neglects the available semantic information on unseen classes, which can easily bias towards the seen categories;2) the original visual feature space is not well-structured for the ZSD task due to the lack of discriminative information. To address these issues, we develop a novel Semantics-Guided Contrastive Network for ZSD, named ContrastZSD, a detection framework that first brings contrastive learning mechanism into the realm of zero-shot detection. Particularly, ContrastZSD incorporates two semantics-guided contrastive learning subnets that contrast between region-category and region-region pairs respectively. The pairwise contrastive tasks take advantage of supervision signals derived from both the ground truth label and class similarity information. By performing supervised contrastive learning over those explicit semantic supervision, the model can learn more knowledge about unseen categories to avoid the bias problem to seen concepts, while optimizing the visual data structure to be more discriminative for better visual-semantic alignment. Extensive experiments are conducted on two popular benchmarks for ZSD, i.e., PASCAL VOC and MS COCO. Results show that our method outperforms the previous state-of-the-art on both ZSD and generalized ZSD tasks. © 2021, CC BY.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Generation of multi-channel short-pulse sources using nonlinear optical loop mirror based on photonic crystal fiber

Generation of multi-channel short-pulse sources using nonlin...

引用

OFC/NFOEC 2007 - Optical Fiber Communication and the National Fiber Optic Engineers Conference 2007

作者： Dong, Yi Li, Zhaohui Yu, Changyuan Wen, Yang Jing Wang, Yixin Lu, Chao Hu, Weisheng Cheng, Tee Hiang State Key Lab of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University 800 Dongchuan Rd. Shanghai 200240 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Institutes for Infocomm Research A STAR 21 Heng Mui Keng Terrace Singapore 119613 Singapore Dept. of Electrical and Computer Engineering National University of Singapore 4 Engineering Dr. 3 Singapore 117576 Singapore Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong Hong Kong

Fourteen C+L-band synchronized multi-channel short pulse sources are generated based on XPM and FWM effects in nonlinear optical loop mirror. Walk-off effect is reduced effectively by using 10m high nonlinear dispersi... 详细信息

ISBN: (纸本)1557528314

关键词： Optical systems

来源：评论

学校读者我要写书评

暂无评论

A delay guaranteed and services differentiated MAC protocol based on location and reservation in near-space

引用

Journal of Convergence Information Technology 2011年第2期6卷 120-130页

作者： Chen, Chen Gao, Xinbo Pei, Qingqi National Key Lab. of Integrated Service Networks Xidian Univ Xi'an 710071 China School of Electronic Engineering Xidian Univ Xi'an 710071 China Ministry of Edu. Key Lab. of Computer Network and Information Security Xidian Univ Xi'an 710071 China

With an ever-increasing interests and demands in Near-Space, more and more researchers have put their attentions on this field, leading to an emerging needs for modeling the 20-100km altitude space especially for broadband communications. Among the lots of works, Media Access Control (MAC) undoubtedly has chief importance and urgency with which communicating objects or nodes can effectively access to Near-Space. However, previous MAC designs mainly focus their attentions on service differentiation by application purposes without considering nodal mobility. In fact, access control for nodes with different mobility levels has significantly influences to MAC performance and is complex and difficult to be implemented together with present MAC protocols. In this paper, we first presented a location method for Near-Space vehicles such as airships and unmanned planes and then modeled the mobile networks infrastructure with mobility considered. For determining the vehicles joining/leaving events locally, we quantify the communication range with Received Signal Strength Indicator (RSSI) aid. Then, for better managing the nodes access to the Near-Space with aforementioned works, we designed a TDMA based reservation MAC protocol to guarantee the servicedelay and networks coverage with best efforts. Simulation results showed that our proposed model better fit for Near-Space mobile communication environments and presented a lower delay and higher coverage regarding to different mobility levels.

关键词： Medium access control

来源：评论

学校读者我要写书评

暂无评论

Hybrid relaying and jamming for secure two-way relay networks with passive eavesdroppers

Hybrid relaying and jamming for secure two-way relay network...

引用

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Hui-Ming Wang Xiang-Gen Xia Qinye Yin Pengcheng Mu School of Electronic and Information Engineering Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an Shaanxi P. R. China Department of Electrical and Computer Engineering Chonbuk National University Jeonju DE Korea

Exploiting the idea of cooperative communications is an efficient way to improve the physical-layer security of a wireless transmission in the presence of passive eavesdroppers. In this paper, we propose a hybrid cooperative relaying and jamming scheme to enhance the security of a two-way relay network, where some intermediate nodes help to relay the signal to the legitimate terminals via distributed beamforming and the others jam the eavesdropper simultaneously. In such a way, both two cooperative phases of the data transmission are protected. Subjected to the more practical per-node power constraint of each node and without the channel state information (CSI) of the eavesdropper, we propose a scheme to enhance the secrecy of the two terminals. It is shown that the problem can be transformed into a semidefinite programming (SDP) problem with an additional rank-1 constraint. We then develop a penalty function method and an iterative algorithm to solve such a problem efficiently, instead of the popular semi-definite relaxation (SDR) and randomization techniques proposed in the previous literatures. Simulations show that the proposed hybrid scheme greatly improves the security of the two-way relay networks.

关键词： Relays Jamming Security Noise Array signal processing Optimization Wireless communication

来源：评论

学校读者我要写书评

暂无评论

Hemispherical Massive MIMO Architecture for High-Altitude Platform Station (HAPS)

Hemispherical Massive MIMO Architecture for High-Altitude Pl...

引用

IEEE Conference on Wireless Communications and Networking

作者： Omid Abbasi Halim Yanikomeroglu Georges Kaddoum Department of Systems and Computer Engineering Non-Terrestrial Networks (NTN) Lab Carleton University Ottawa ON Canada Department of Electrical Engineering École de Technologie Supérieure (ETS) Université du Québec Montréal QC Canada

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

In this paper, we present a novel hemispherical antenna array (HAA) designed for High-Altitude Platform Stations (HAPS). Traditional rectangular antenna arrays for HAPS suffer from a significant limitation - their antenna elements are perpetually oriented downward, resulting in low gain for distant users. Meanwhile, cylindrical antenna arrays were introduced to mitigate this drawback, but they, in turn, exhibit a distinct problem: their antenna elements continually face the horizon, leading to suboptimal gain for users located beneath the HAPS. To address these challenges, we introduce the HAA. In the HAA configuration, antenna elements are strategically distributed across the surface of a hemisphere, ensuring that each user receives direct alignment with specific antenna elements, thereby maximizing the gain for all users. We derive the achievable data rates for users within this proposed scheme, employing an analog beamforming technique that leverages the steering vectors of the selected antenna elements for each user. We also formulate an op-timization problem focused on maximizing the minimum Signal-to-Interference-plus-Noise Ratio (SINR) for users. Additionally, we introduce an antenna selection algorithm based on the gains of the antenna elements. To further enhance system performance, we employ the Bisection method to determine the optimal power allocation for each user. Our simulation results substantiate the superior rate performance of the proposed HAA when compared to the conventional rectangular and cylindrical baseline arrays. The proposed approach demonstrates to reach sum data rates of up to 14 Gigabit/s. Furthermore, in contrast to the baseline schemes, the proposed scheme achieves more consistent spectral efficiencies across the entire coverage area.

关键词： Spectral efficiency Urban areas Receiving antennas Interference Bandwidth Vectors Resource management

来源：评论

学校读者我要写书评

暂无评论

Multi-task learning for object keypoints detection and classification

引用

Pattern Recognition Letters 2020年 130卷 182-188页

作者： Jie Xu Lin Zhao Shanshan Zhang Chen Gong Jian Yang PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education and Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China State Key Laboratory of Integrated Services Networks Xidian Univeristy Xi’an 710071 China

Object keypoints detection and classification are both central research topics in computer vision . Due to their wide range potential applications in the real world, substantial efforts have been taken to advance their performance. However, these two related tasks are mainly treated separately in previous works. We argue that keypoints detection and classification can be complementary tasks and beneficial to each other. Knowing the category of a object is able to reduce the searching space of keypoints detection models and facilitate more precise localization . On the other hand, having the knowledge of object keypoints can make classification models pay more attention on areas that are more associated with the object, which will inevitably promote classification accuracy . Embracing this observation, we propose to model keypoints detection and classification in a multi-task learning framework. Specifically, a multi-task deep network is designed and trained to conduct both tasks, where we devise the model structure delicately to carry out sufficient training of both tasks. Extensive experiments are set up on the AIFASHION DATASET and Human3.6M DATASET to validate our proposal, we show that our algorithm outperforms separate models trained individually on each task.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Robust Reinforcement Learning for Risk-Sensitive Linear Quadratic Gaussian Control

arXiv

引用

arXiv 2022年

作者： Cui, Leilei Başar, Tamer Jiang, Zhong-Ping The Control and Networks Lab Department of Electrical and Computer Engineering Tandon School of Engineering New York University BrooklynNY11201 United States The Coordinated Science Laboratory University of Illinois Urbana-Champaign UrbanaIL61801 United States

This paper proposes a novel robust reinforcement learning framework for discrete-time linear systems with model mismatch that may arise from the sim-to-real gap. A key strategy is to invoke advanced techniques from control theory. Using the formulation of the classical risk-sensitive linear quadratic Gaussian control, a dual-loop policy optimization algorithm is proposed to generate a robust optimal controller. The dual-loop policy optimization algorithm is shown to be globally and uniformly convergent, and robust against disturbances during the learning process. This robustness property is called small-disturbance input-to-state stability and guarantees that the proposed policy optimization algorithm converges to a small neighborhood of the optimal controller as long as the disturbance at each learning step is relatively small. In addition, when the system dynamics is unknown, a novel model-free off-policy policy optimization algorithm is proposed. Finally, numerical examples are provided to illustrate the proposed algorithm. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Unicode-proof Code Injection Attack on Windows CE- A Novel Approach of Evading Intrusion Detection System for Mobile Network

Unicode-proof Code Injection Attack on Windows CE- A Novel A...

引用

2011 IEEE 3rd International Conference on Communication Software and networks(2011第三届通信软件与网络国际会议 ICCSN2011)

作者： Yang Song Yuqing Zhang Yingfei Sun JingBo Yan National Computer Network Intrusion Protection Center Graduate University of Chinese Academy of Scie School of Information Science and Engineering Graduate University of Chinese Academy of Sciences Bei Key Lab of Computer Networks and Information Security of Ministry of Education Xidian University Xia

Code injection attack is a major way of spreading malware on network. The key section of code injection attack is a small piece of code, called shellcode, which performs unauthorized operations when it is injected into software as part of valid data. On Windows CE, input data are often encoded using Unicode before being processed. In such cases, shellcode should be built in a way that bypasses such encoding;that is, it should be Unicode-proof. Unicode-proof shellcode also has great advantage of evading instruction detection system. However, it is quite difficult to build Unicode-proof shellcode for the ARM architecture,.on which most embedded devices are developed, because the subset of instructions that can be used to write Unicode-proof shellcode is very limited. Moreover, the instruction cache in the ARM processor restricts the application of selfmodifying code, which is frequently used in shellcode writing. This novel research proposes an approach to *** Unicode-proof shellcode on Windows CE under these constraints. The approach applies to all versions of ARM processors and Windows CE, including systems evolved from Windows CE, such as Windows Mobile and Windows Phone. The shellcode is tested on three currently available devices.

关键词： Unicode-proof code injection Windows CE

来源：评论

学校读者我要写书评

暂无评论

Integrated Routing and Traffic Signal Control for CAVs via Reinforcement Learning Approach

Integrated Routing and Traffic Signal Control for CAVs via R...

引用

International Conference on Intelligent Transportation

作者： Jiho Park Guohui Zhang Chieh Wang Hong Wang Zhong-Ping Jiang Department of Electrical and Computer Engineering Control and Networks Lab Tandon School of Engineering New York University Brooklyn NY USA Department of Civil and Environmental Engineering University of Hawaii at Manoa Honolulu HI USA Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Incorporating Connected and Automated Vehicles (CAVs) into urban traffic networks presents opportunities and challenges for traffic management systems. This paper aims to develop an integrated routing and traffic signal control system designed explicitly for CAVs, utilizing a Reinforcement Learning (RL) approach. The objective is to enhance traffic flow and improve overall transportation efficiency in the controlled areas. We propose an innovative framework that employs the Deep Reinforcement Learning (DRL) algorithm, especially the Deep Q-network (DQN), to dynamically adjust the number of vehicles in the routes and the duration of traffic signals. Our simulation results demonstrate that a DQN agent successfully optimizes the number of vehicles in the routes and traffic signal timings of traffic signal controllers, eventually reducing total travel time. The study illustrates the potential usage of RL-based systems in managing routing and traffic signals for CAVs, offering a promising opportunity for future urban traffic management strategies.

关键词： Simulation Heuristic algorithms Transportation Routing Deep reinforcement learning Control systems Timing

来源：评论

学校读者我要写书评

暂无评论

Covert surveillance via proactive eavesdropping under channel uncertainty

arXiv

引用

arXiv 2020年

作者： Cheng, Zihao Si, Jiangbo Li, Zan Wang, Danyang Al-Dhahir, Naofal Integrated Service Networks Lab of Xidian University Xi'an710071 China University of Texas Dallas United States Department of Electrical and Computer Engineering University of Texas Dallas RichardsonTX75080 United States

Surveillance performance is studied for a wireless eavesdropping system, where a full-duplex legitimate monitor eavesdrops a suspicious link efficiently with the artificial noise (AN) assistance. Different from the existing work in the literature, the suspicious receiver in this paper is assumed to be capable of detecting the presence of AN. Once such receiver detects the AN, the suspicious user will stop transmission, which is harmful for the surveillance performance. Hence, to improve the surveillance performance, AN should be transmitted covertly with a low detection probability by the suspicious receiver. Under these assumptions, an optimization problem is formulated to maximize the eavesdropping non-outage probability under a covert constraint. Based on the detection ability at the suspicious receiver, a novel scheme is proposed to solve the optimization problem by iterative search. Moreover, we investigate the impact of both the suspicious link uncertainty and the jamming link uncertainty on the covert surveillance performance. Simulations are performed to verify the analyses. We show that the suspicious link uncertainty benefits the surveillance performance, while the jamming link uncertainty can degrade the surveillance performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Security systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：