检索结果-内蒙古大学图书馆

Strategic Planning and Knowledge Management Approaches as input to remote area strategic plans: A Case study in Aru Islands Regency Maluku Province 8

Strategic Planning and Knowledge Management Approaches as in...

引用

8th International Conference on ICT for Smart Society, ICISS 2021

作者： Irena Gutandjala, Ilona Harso Supangkat, Suhono Lumban Gaol, Ford Rianti, Benny Bina Nusantara University BINUS Graduate Program-Computer Science Computer Science Department Jakarta11480 Indonesia Bandung Institute of Technology Smart City and Community Innovation Center School of Electrical and Informatics Engineering Bandung Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781665416979

Knowledge is an important asset in an organization. Aru Islands District is one of the districts in Maluku Province. The Government of Aru Islands District Maluku has a vision and mission as outlined in the Regional Strategic Plan or commonly referred to as RENSTRA. This vision and mission are an activity that requires a policy direction that is planned and integrated with the strategic environment of all related aspects. The strategic plan is then realized with the implementation of the government with regional autonomy which is the modern governance in realizing quality public services, fast, easy, fair and unlimited for the welfare and progress of the region. In this research will be used a strategic approach as input from the analysis with knowledge management and assessment of the condition of Aru district. © 2021 IEEE.

关键词： Strategic planning

来源：评论

学校读者我要写书评

暂无评论

Analysis of temporal structure of laser chaos by Allan variance

引用

Physical Review E 2023年第1期107卷 014211-014211页

作者： Naoki Asuke Nicolas Chauvet André Röhm Kazutaka Kanno Atsushi Uchida Tomoaki Niiyama Satoshi Sunada Ryoichi Horisaki Makoto Naruse Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Department of Information and Computer Sciences Saitama University 255 Shimo-Okubo Sakura-ku Saitama city Saitama 338-8570 Japan Faculty of Mechanical Engineering Institute of Science and Engineering Kanazawa University Kakuma Kanazawa city Ishikawa 920-1192 Japan

Allan variance has been widely utilized for evaluating the stability of the time series generated by atomic clocks and lasers, in time regimes ranging from short to extremely long. This multiscale examination capability of the Allan variance may also be beneficial in evaluating the chaotic oscillating dynamics of semiconductor lasers— not just for conventional phase stability analysis. In the present study, we demonstrated Allan variance analysis of the complex time series generated by a semiconductor laser with delayed feedback, including low-frequency fluctuations (LFFs), which exhibit both fast and slow dynamics. While the detection of LFFs is difficult with the conventional power spectrum analysis method in the low-frequency regime, the Allan variance approach clearly captured the appearance of multiple time-scale dynamics, such as LFFs. This study demonstrates that Allan variance can help in understanding and characterizing diverse laser dynamics, including LFFs, spanning a wide range of timescales.

关键词： Chaos

来源：评论

学校读者我要写书评

暂无评论

Experimental implementation of an efficient test of quantumness

引用

Physical Review A 2024年第1期109卷 012610-012610页

作者： Laura Lewis Daiwei Zhu Alexandru Gheorghiu Crystal Noel Or Katz Bahaa Harraz Qingfeng Wang Andrew Risinger Lei Feng Debopriyo Biswas Laird Egan Thomas Vidick Marko Cetina Christopher Monroe Institute for Quantum Information and Matter and Department of Computing and Mathematical Sciences California Institute of Technology Pasadena California 91125 USA Division of Physics Mathematics and Astronomy California Institute of Technology Pasadena California 91125 USA Joint Quantum Institute Departments of Physics and Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Joint Center for Quantum Information and Computer Science NIST/University of Maryland College Park Maryland 20742 USA IonQ Inc. College Park Maryland 20740 USA Departments of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Institute for Theoretical Studies ETH Zürich Zürich CH 8001 Switzerland Duke Quantum Center and Department of Physics Duke University Durham North Carolina 27708 USA Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA Chemical Physics Program and Institute for Physical Science and Technology University of Maryland College Park Maryland 20742 USA

A test of quantumness is a protocol where a classical user issues challenges to a quantum device to determine if it exhibits nonclassical behavior, under certain cryptographic assumptions. Recent attempts to implement such tests on current quantum computers rely on either interactive challenges with efficient verification or noninteractive challenges with inefficient (exponential time) verification. In this paper, we execute an efficient noninteractive test of quantumness on an ion-trap quantum computer. Our results significantly exceed the bound for a classical device's success.

关键词： Quantum cryptography Quantum information with trapped ions Quantum protocols Quantum verification

来源：评论

学校读者我要写书评

暂无评论

SODAR: Segmenting Objects by DynamicallyAggregating Neighboring Mask Representations

arXiv

引用

arXiv 2022年

作者： Wang, Tao Liew, Jun Hao Li, Yu Chen, Yunpeng Feng, Jiashi NUS Graduate School of Integrative Sciences and Engineering Institute of Data Science National University of Singapore Singapore The Department of Electrical and Computer Engineering National University of Singapore Singapore Institute of Computing Technology Chinese Academy of Science China YITU Technology Beijing100086 China

Recent state-of-the-art one-stage instance segmentation model SOLO divides the input image into a grid and directly predicts per grid cell object masks with fully-convolutional networks, yielding comparably good performance as traditional two-stage Mask R-CNN yet enjoying much simpler architecture and higher efficiency. We observe SOLO generates similar masks for an object at nearby grid cells, and these neighboring predictions can complement each other as some may better segment certain object part, most of which are however directly discarded by non-maximum-suppression. Motivated by the observed gap, we develop a novel learning-based aggregation method that improves upon SOLO by leveraging the rich neighboring information while maintaining the architectural efficiency. The resulting model is named SODAR. Unlike the original per grid cell object masks, SODAR is implicitly supervised to learn mask representations that encode geometric structure of nearby objects and complement adjacent representations with context. The aggregation method further includes two novel designs: 1) a mask interpolation mechanism that enables the model to generate much fewer mask representations by sharing neighboring representations among nearby grid cells, and thus saves computation and memory;2) a deformable neighbour sampling mechanism that allows the model to adaptively adjust neighbor sampling locations thus gathering mask representations with more relevant context and achieving higher performance. SODAR significantly improves the instance segmentation performance, e.g., it outperforms a SOLO model with ResNet-101 backbone by 2.2 AP on COCO test set, with only about 3% additional computation. We further show consistent performance gain with the SOLOv2 model. Code:https://***/advdfacd/AggMask. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Zero-Trust Empowered Decentralized Security Defense against Poisoning Attacks in SL-IoT: Joint Distance-Accuracy Detection Approach

Zero-Trust Empowered Decentralized Security Defense against ...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Rongxuan Song Jun Wu Qianqian Pan Muhammad Imran Niddal Naser Rebet Jones Christos Verikoukis Graduate School of Information Production and Systems Waseda University Japan Department of Computing and Mathematics Manchester Metropolitan University UK Institute of Innovation Science and Sustainsbility Federation University Australia College of Engineering Alfaisal University Riyadh Saudi Arabia Department of Computer Science Capitol Technology University USA University of Patras and Iquadrat Information Greece

Swarm learning (SL) exploits the blockchain to realize a federated and decentralized learning, which is very suitable for internet of things (IoT). Different from FL using central server to update global parameter, SL using edge node (header) to do that. However, poisoning attack is also an unresolved problem to SL. Because if header is malicious, it can pollute global parameter more easily than edge nodes. Moreover, there are following important limitations in existing defense schemes for FL, which cannot be used in SL directly. First, existing defense schemes focus on building a whitelist, which obstructs the decentralization because it can just provide decentralization in honest nodes instead of all of nodes. Second, existing schemes just consider poisoning attacks from edge nodes, they cannot defend attacks from header. Third, most existing schemes will let server execute the defense algorithm, but in SL, malicious header can return wrong defense results to deceive managers. To address above challenges, in this paper, we propose a protection system that leverages the concept of zero-trust architecture for SL, which achieves continuous risk calculation, analysis of learning behavior and abnormal parameter detection based on Manhattan distance and accuracy difference of parameters. We also evaluate the performance in the presence of random and customized malicious edge nodes. Experimental results demonstrate that our scheme can achieve higher accuracy than the other existing schemes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Efficient Maximum Euclidean Distance Transform Computation in Component Trees Using the Differential Image Foresting Transform

引用

Journal of Mathematical Imaging and Vision 2025年第3期67卷 1-23页

作者： Silva, Dennis J. Miranda, Paulo A. V. Alves, Wonder A. L. Hashimoto, Ronaldo F. Kosinka, Jiří Roerdink, Jos B. T. M. Institute of Mathematics and Statistics University of São Paulo R. do Matão 1010 SP São Paulo05508-090 Brazil Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Nijenborgh 9 Groningen9747 AG Netherlands Informatics and Knowledge Management Graduate Program Nove de Julho University R. Vergueiro 235/249 SP São Paulo01525-000 Brazil

The distance transform is a crucial technique in binary image processing, assigning the distance to the nearest contour to each foreground pixel. In this extended version of our previous work, we enhance our method for computing the maximum distance transform (DT) value, now utilizing the optimized differential image foresting transform (DIFT) and improved contour extraction processes. These advancements enable more efficient computation of the maximum DT value across all connected components of a grayscale image, significantly reducing computational time by intelligently reusing DIFT trees rooted at contour points (DIFT seeds). Our optimized algorithm now achieves processing speeds that are twice as fast as our previous differential method. The proposed attribute, maximum distance, which measures the thickness of objects within the image, has proven pivotal in different image processing approaches. We showcase this through detailed illustrations of attribute opening, extinction value filters, watershed, and ultimate attribute openings. © The Author(s) 2025.

关键词： Binary images

来源：评论

学校读者我要写书评

暂无评论

To Sharpen or not to Sharpen? On the Effect of Sharpening Filters Applied to Magnified Images 14

To Sharpen or not to Sharpen? On the Effect of Sharpening Fi...

引用

14th International Conference on Digital Image Processing, ICDIP 2022

作者： Emmendorfer, Leonardo R. de Olviveira, Vinicius Menezes Schein, Tatiana T. de Jesus, Junior C. Rodriguez, Bárbara D.A. Electrical Energy Processing Department Federal University of Santa Maria 97105-340 Brazil Center for Computational Science Federal University of Rio Grande 96201-900 Brazil Computational Modeling PhD Program Federal University of Rio Grande 96201-900 Brazil Computer Engineering Graduate Program Federal University of Rio Grande 96201-900 Brazil Institute of Mathematics Statistics and Physics Federal University of Rio Grande 96201-900 Brazil

ISBN: (纸本)9781510657564

Super-resolution algorithms aim to produce magnified high-resolution versions from low-resolution images. Some methods, however, are prone to generate blur during the process. Simple sharpening filters are adopted to alleviate this type of artifact. However, the actual effectiveness of this approach is not clear-cut in the literature. This work evaluates the effect of three simple sharpening filters on the quality of images obtained from super-resolution methods. Two metrics were considered in the evaluation: the Peak signal-to-noise ratio (PSNR) metric, and the Learned Perceptual Image Patch Similarity (LPIPS). One of the filters could consistently improve the LPIPS metric of magnified images from diverse benchmark sets on top of seven super-resolution methods. The increments obtained for the perceptual metric seem to occur due to the sharpening effect. Improvements on PSNR values were not as consistent. © 2022 SPIE.

关键词： Quality control

来源：评论

学校读者我要写书评

暂无评论

Characterizations of Second-order Nonlinear Optical Susceptibility for ϵ-phase Gallium Oxide

Characterizations of Second-order Nonlinear Optical Suscepti...

引用

2022 Compound Semiconductor Week, CSW 2022

作者： Zhou, Jingan Zhao, Xuan Xu, Rui Fu, Kai Li, Tao Xu, Mingfei He, Ziyi Robinson, Jacob T. Zhu, Hanyu Zhang, Xiaodong Zhao, Yuji Rice University Department of Electrical and Computer Engineering HoustonTX77005 United States Rice University Smalley-Curl Institute Applied Physics Graduate Program HoustonTX77005 United States Rice University Department of Materials Science and NanoEngineering HoustonTX77005 United States Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85287 United States Suzhou Institute of Nano-tech and Nano-bionics CAS Key Laboratory of Nanodevices and Applications Suzhou215123 China

ISBN: (数字)9781665453400

ISBN: (纸本)9781665453400

In this work, we report the second-order nonlinear optical susceptibility χ(2) for epsilon phase Gallium Oxide (ϵ-Ga2O3) thin film on sapphire. ϵ-Ga2O3 exhibits hexagonal P63mc space group symmetry, which is a non-centrosymmetric structure with non-zero second order susceptibility. By focusing a pulsed laser beam on to a polished ϵ-Ga2O3 thin film, we collected the generated second harmonic photons with an ultra-sensitive femtowatt photodetector, obtaining effective second-order nonlinear optical susceptibility of χ(2) = 4.89×10-3 pm/V at wavelength of 800 nm. Two different measurement systems collecting reflected and transmitted photons were applied separately to make the result more convincing. The wavelength dependence from 790 nm to 900 nm and polarization dependence from TM mode to TE mode were measured as well. These results will be helpful for the design and fabrication of Ga2O3 based integrated photonics platform in the infrared-visible spectral range. © 2022 IEEE.

关键词： Gallium compounds

来源：评论

学校读者我要写书评

暂无评论

GraCo: Granularity-Controllable Interactive Segmentation

GraCo: Granularity-Controllable Interactive Segmentation

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Yian Zhao Kehan Li Zesen Cheng Pengchong Qiao Xiawu Zheng Rongrong Ji Chang Liu Li Yuan Jie Chen School of Electronic and Computer Engineering Peking University Shenzhen China AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China Peng Cheng Laboratory Shenzhen China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Automation and BNRist Tsinghua University Beijing China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity out-put and multi-granularity output. The latter aims to allevi-ate the spatial ambiguity present in the former. However, the multi-granularity output pipeline suffers from limited interaction flexibility and produces redundant results. In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing ad-ditional parameters to input. This enhances the customization of the interactive system and eliminates redundancy while resolving ambiguity. Nevertheless, the exorbitant cost of annotating multi-granularity masks and the lack of avail-able datasets with granularity annotations make it difficult for models to acquire the necessary guidance to control out-put granularity. To address this problem, we design an any-granularity mask generator that exploits the semantic property of the pre-trained IS model to automatically gen-erate abundant mask-granularity pairs without requiring additional manual annotation. Based on these pairs, we propose a granularity-controllable learning strategy that efficiently imparts the granularity controllability to the IS model. Extensive experiments on intricate scenarios at ob-ject and part levels demonstrate that our GraCo has signifi-cant advantages over previous methods. This highlights the potential of GraCo to be a flexible annotation tool, capable of adapting to diverse segmentation scenarios. The project page: https://***/GraCo.

关键词： Image segmentation Adaptation models Annotations Interactive systems Pipelines Semantics Redundancy

来源：评论

学校读者我要写书评

暂无评论

Supplemental Information

arXiv

引用

arXiv 2025年

作者： Sunada, Satoshi Niiyama, Tomoaki Kanno, Kazutaka Nogami, Rin Röhm, André Awano, Takato Uchida, Atsushi Faculty of Mechanical Engineering Institute of Science and Engineering Kanazawa University Kakuma-machi Kanazawa Ishikawa920-1192 Japan Department of Information and Computer Sciences Saitama University 255 Shimo-Okubo Sakura-ku Saitama338-8570 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

The rapidly increasing computational demands for artificial intelligence (AI) have spurred the exploration of computing principles beyond conventional digital computers. Physical neural networks (PNNs) offer efficient neuromorphic information processing by harnessing the innate computational power of physical processes;however, training their weight parameters is computationally expensive. We propose a training approach for substantially reducing this training cost. Our training approach merges an optimal control method for continuous-time dynamical systems with a biologically plausible training method—direct feedback alignment. In addition to the reduction of training time, this approach achieves robust processing even under measurement errors and noise without requiring detailed system information. The effectiveness was numerically and experimentally verified in an optoelectronic delay system. Our approach significantly extends the range of physical systems practically usable as PNNs. Copyright © 2025, The Authors. All rights reserved.

关键词： Continuous time 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：