检索结果-内蒙古大学图书馆

Tunable Rectification of Diffusion-Wave Fields by Spatiotemporal Metamaterials

Physical Review Letters 2022年第25期129卷 256601-256601页

作者： Jiaxin Li Zhanxiang Zhang Guoqiang Xu Haoran Sun Lizhou Dai Tianlong Li Cheng-Wei Qiu Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China

The diffusion process is the basis of many branches of science and engineering, and generally obeys reciprocity between two ports of a linear time-invariant medium. Recent research on classical wave dynamics has explored the spatiotemporal modulation to exhibit preferred directions in photons and plasmons. Here we report a distinct rectification effect on diffusion-wave fields by modulating the conductivity and observe nonreciprocal transport of charges. We experimentally create a spatiotemporal diffusion metamaterial, in which a mode transition to zero frequency is realized. A direct current component thereby emerges, showcasing a biased effect on the charge diffusion when the incident fundamental frequency is a multiple of the system modulation frequency. These results may find applications spanning a plethora of diffusive fields in general.

关键词： Diffusion Metamaterials Bloch-Floquet theorem

来源：评论

学校读者我要写书评

暂无评论

Goat Feeding Behavior Modeling and Monitoring Utilizing Livestock Wearable Device and Machine Learning Algorithm

Goat Feeding Behavior Modeling and Monitoring Utilizing Live...

引用

IEEE World Forum on Internet of Things (WF-IoT)

作者： Melchizedek Alipio Gianne Marcus Obusan Julianne Abbe Ong Samuel Perez Anton Luis Garces Miroslav Bures Department of Computer Science System Testing Intelligent Laboratory FEE Czech Technical University in Prague Prague 2 Czech Republic Department of Electronics and Computer Engineering De La Salle University Manila Philippines

ISBN: (数字)9798350311617

ISBN: (纸本)9798350311624

Goat farming shows potential as one of the so-lutions for providing quality livestock products in developing countries. Goat health is essential in determining the quality of goods obtained from the goat. Smart livestock farming has been a reliable solution to achieve high-yield and high-quality goat products. However, current smart livestock monitoring systems do not consider the feeding pattern and behavior of the animal as a factor in its overall health. Hence, this study aims to develop a system that effectively monitors the feeding behavior of the goat using wearable devices, machine learning, and a visualization interface. The wearable device consists of an accelerometer, gyrometer, and temperature sensors to monitor the goat's feeding behavior and movement. The data collected by the wearable device are wirelessly transmitted to a base station to build a sensor-based dataset. This dataset is used to generate a k-means clustering model to classify the feeding behavior of the goats. Results show that the system was able to classify the feeding behavior of the goat with an accuracy of 98.02 % and a reliability of 100% in comparison with the actual goat behavior on the farm. Lastly, a graphical user interface is developed to provide monitoring and other relevant information to help the farmers in grazing the goats.

关键词： Temperature sensors Temperature measurement Temperature distribution Animals Agriculture Reliability Wearable devices

来源：评论

学校读者我要写书评

暂无评论

Paired regions for shadow removal approach based on multi-features

引用

High Technology Letters 2023年第2期29卷 174-180页

作者：张之政 GUO Mingqiang WU Liang HUANG Ying CHEN Xueye Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034P.R.China National Engineering Research Center of Geographic Information System China University of GeosciencesWuhan 430074P.R.China School of Computer Science China University of GeosciencesWuhan 430074P.R.China Wuhan Zondy Cyber Technology Co. Ltd.Wuhan 430074P.R.China

The existence of shadow leads to the degradation of the image qualities and the defect of ground object *** removal is therefore an essential research topic in image processing *** biggest challenge of shadow removal is how to restore the content of shadow areas correctly while removing the shadow in the *** regions for shadow removal approach based on multi-features is proposed, in which shadow removal is only performed on related sunlit *** distance between regions is calculated to find the optimal paired regions with considering of multi-features(texture, gradient feature, etc.) *** in different scenes with peak signal-to-noise ratio(PSNR) and structural similarity(SSIM) evaluation indexes are chosen for *** results are shown with six existing comparison methods by visual and quantitative assessments, which verified that the proposed method shows excellent shadow removal effect, the brightness, color of the removed shadow area, and the surrounding non-shadow area can be naturally fused.

关键词： paired region feature distance texture peak signal-to-noise ratio(PSNR) structural similarity(SSIM)

来源：评论

学校读者我要写书评

暂无评论

DPFuzzer: Discovering Safety Critical Vulnerabilities for Drone Path Planners

DPFuzzer: Discovering Safety Critical Vulnerabilities for Dr...

引用

International Conference on Software engineering (ICSE)

作者： Yue Wang Chao Yang Xiaodong Zhang Yuwanqi Deng JianFeng Ma State Key Laboratory of Integrated Services Networks (ISN) Xidian University China Shaanxi Key Laboratory of Network and System Security Xidian University Xi'an China School of Cyber Engineering Xidian University China School of Computer Science and Technology Xidian University China

ISBN: (数字)9798331505691

ISBN: (纸本)9798331505707

State-of-the-art drone path planners enable drones to autonomously travel through obstacles in GPS-denied, uncharted, cluttered environments. However, our investigation shows that path planners fail to maneuver drones correctly in specific scenarios, leading to incidents such as collisions. To minimize such risks, drone path planners should be tested thoroughly against diverse scenarios before deployment. Existing research for testing drones to uncover safety-critical vulnerabilities is only focused on flight control programs and is limited in the capability to generate diverse obstacle scenarios for testing drone path planners. In this work, we propose DPFuzzer, an automated framework for testing drone path planners. DPFuzzer is an evolutionary algorithm (EA) based testing framework. It aims to uncover vulnerabilities in drone path planners by generating diverse critical scenarios that can trigger vulnerabilities. To better guide the critical scenario generation, we introduce Environmental Risk Factor (ERF), a metric we propose, to abstract potential safety threats of scenarios. We evaluate DPFuzzer on state-of-the-art drone path planners and the experimental result shows that DPFuzzer can effectively find diverse vulnerabilities. Additionally, we demonstrate that these vulnerabilities are exploitable in the real world.

关键词： Measurement Evolutionary computation Fuzzing Safety Scenario generation Fuels Drones Testing Software engineering Aerospace control

来源：评论

学校读者我要写书评

暂无评论

Parallelism or Fairness? How to Be Friendly for SSDs in Cloud Environments

Parallelism or Fairness? How to Be Friendly for SSDs in Clou...

引用

IEEE International Conference on Cluster Computing

作者： Yang Zhou Fang Wang Zhan Shi Dan Feng Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of data storage systems and Technology Ministry of Education of China Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350358711

ISBN: (纸本)9798350358728

Modern SSDs achieve low latency and high throughput by utilizing multiple levels of SSD parallelism. Fairness is also a critical design consideration in cloud environments and has inspired great interest in recent years to study it. However, we find that excessive striving for SSD parallelism can inadvertently harm the SSD fairness due to the striped data layout. We observe from our experimental analysis that some common access patterns in cloud loads (e.g., high-intensity I/O) are not addressed by SSD parallelism, which can affect both SSD parallelism and fairness. In this paper, we analyze two address mapping policies with orthogonal characteristics from SSD parallelism and fairness perspectives. Based on extensive experiments and observations, we schedule a hybrid address mapping policy to achieve fairness of SSDs in cloud environments by distinguishing different I/O access modes and cold/hot data, while ensuring SSD performance. Experimental results on the latest block-level I/O traces show that our approach significantly improves performance and fairness by up to 77.3% and 62.8%, respectively, over the previous schemes with negligible cost. Meanwhile, it can also reduce the write amplification by 23.5% to 33.5%.

关键词： Schedules Layout Interference Parallel processing Predictive models Throughput Data models Resource management Decision trees Low latency communication

来源：评论

学校读者我要写书评

暂无评论

Parameter-Efficient Multi-Modal Tuning for Salient Object Detection

SSRN

引用

SSRN 2025年

作者： Zhang, Zixuan Shi, Fan Jia, Chen Wang, Mianzhao Louis, Assale Adje Cheng, Xu Engineering Research Center of Learning-Based Intelligent System Ministry of Education Tianjin University of Technology Tianjin300384 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300384 China Yamoussoukro999063 Ivory Coast Smart Innovation Norway Norway

Salient object detection (SOD) is a key preprocessing step in various computer vision tasks, aiming to replicate the human visual system to identify the most significant objects or regions in images or videos. However, existing multi-modal SOD works introduce expensive fusion modules with a large number of parameters to integrate cues across modalities. This cannot effectively reduce the resource overhead required for computing devices. To address this issue, we propose a parameter-efficient multi-modal tuning method for salient object detection. Our method employs a hierarchical progressive encoder with a limited set of learnable parameters to capture aligned and intrinsic representations. Based on the encoder, we further introduce a learnable weighting parameter λ to exploit semantic understanding across different levels and patterns. Extensive experiments on 11 benchmark datasets with 32 state-of-the-art (SOTA) methods demonstrate the effectiveness of our method, which requires only 4.4M training parameters. © 2025, The Authors. All rights reserved.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Improved Multistep Model Predictive Control for Six-Step Operation of Traction PMSM Drives

Improved Multistep Model Predictive Control for Six-Step Ope...

引用

Workshop on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)

作者： Zhenyao Sun Shuai Xu Guangtong Ma Juri Jatskevich State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong University Chengdu China Department of Electrical and Computer Engineering The University of British Columbia Vancouver Canada

Model predictive control (MPC) has recently been considered for many permanent magnet synchronous machine (PMSM) drive applications. However, the conventional MPC lacks accurate current tracking and fast dynamic responses in the overmodulation region and the six-step operation, which limits its application areas. This paper proposes a six-step operation scheme based on MPC for PMSM drives in traction applications. The current trajectory long-horizon prediction and the average current-based objective function are introduced to determine the optimal switching instants. To enhance the method’s precision, a trapezoidal integration rule has been used in the prediction step. The voltage angle control principle is introduced to clamp the voltage vectors. The effectiveness of the proposed method has been validated by detailed studies. The proposed method is demonstrated to have excellent current tracking accuracy and fast dynamic response in six-step operation, which is an advantage over existing methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Realizing Emotional Interactions to Learn User Experience and Guide Energy Optimization for Mobile Architectures 22

Realizing Emotional Interactions to Learn User Experience an...

引用

Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture

作者： Xueliang Li Zhuobin Shi Junyang Chen Yepang Liu National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China College of Computer Science and Software Engineering Shenzhen University China Research Institute of Trustworthy Autonomous Systems Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation and Department of Computer Science and Engineering Southern University of Science and Technology China

ISBN: (纸本)9781665462723

In the age of AI, mobile architectures such as smartphones are still "cold machines"; machines do not feel. If the architecture is able to feel users' feelings and runtime user experience (UX), it will accordingly adapt performance/energy to find the optimal system-operating state that consumes the least energy to satisfy users. In this paper, we will utilize users' facial expressions (FEs) to learn their runtime UX. We know that FEs are the natural and direct way for humans to convey their emotions and feelings. Our study reveals that FEs also reflect UX. Our research for the first time quantifies the link between FEs and UX. Leveraging this link, the architecture will be able to use the front camera to see FEs and feel users' UX. Based on UX, the architecture can appropriately provision computing resources. We propose Vi-energy system to realize the above idea. Our evaluation shows that Vi-energy reduces energy consumption by 52.9% at maximum and secures UX.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need

arXiv

引用

arXiv 2024年

作者： Wang, Xianlong Li, Minghui Liu, Wei Zhang, Hangtao Hu, Shengshan Zhang, Yechao Zhou, Ziqi Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Hubei Engineering Research Center on Big Data Security Hubei Key Laboratory of Distributed System Security School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity information, unauthorized usage of this new type data has also become a serious concern. To address this, we propose the first integral unlearnable framework for 3D point clouds including two processes: (i) we propose an unlearnable data protection scheme, involving a class-wise setting established by a category-adaptive allocation strategy and multi-transformations assigned to samples;(ii) we propose a data restoration scheme that utilizes class-wise inverse matrix transformation, thus enabling authorized-only training for unlearnable data. This restoration process is a practical issue overlooked in most existing unlearnable literature, i.e., even authorized users struggle to gain knowledge from 3D unlearnable data. Both theoretical and empirical results (including 6 datasets, 16 models, and 2 tasks) demonstrate the effectiveness of our proposed unlearnable framework. Our code is available at https://***/CGCL-codes/UnlearnablePC Copyright © 2024, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MAGIC: detecting advanced persistent threats via masked graph representation learning 24

MAGIC: detecting advanced persistent threats via masked grap...

引用

Proceedings of the 33rd USENIX Conference on Security Symposium

作者： Zian Jia Yun Xiong Yuhong Nan Yao Zhang Jinjing Zhao Mi Wen Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China School of Software Engineering Sun Yat-sen University China National Key Laboratory of Science and Technology on Information System Security China Shanghai University of Electric Power China

ISBN: (纸本)9781939133441

Advance Persistent Threats (APTs), adopted by most delicate attackers, are becoming increasing common and pose great threat to various enterprises and institutions. Data provenance analysis on provenance graphs has emerged as a common approach in APT detection. However, previous works have exhibited several shortcomings: (1) requiring attack-containing data and a priori knowledge of APTs, (2) failing in extracting the rich contextual information buried within provenance graphs and (3) becoming impracticable due to their prohibitive computation overhead and memory *** this paper, we introduce MAGIC, a novel and flexible self-supervised APT detection approach capable of performing multi-granularity detection under different level of supervision. MAGIC leverages masked graph representation learning to model benign system entities and behaviors, performing efficient deep feature extraction and structure abstraction on provenance graphs. By ferreting out anomalous system behaviors via outlier detection methods, MAGIC is able to perform both system entity level and batched log level APT detection. MAGIC is specially designed to handle concept drift with a model adaption mechanism and successfully applies to universal conditions and detection scenarios. We evaluate MAGIC on three widely-used datasets, including both real-world and simulated attacks. Evaluation results indicate that MAGIC achieves promising detection results in all scenarios and shows enormous advantage over state-of-the-art APT detection approaches in performance overhead.

关键词：

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：