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Designs in finite metric spaces: A probabilistic approach

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arXiv 2021年

作者： Shi, Minjia Rioul, Olivier Solé, Patrick Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education School of Mathematical Sciences Anhui University Hefei230601 China Telecom ParisTech Palaiseau France I2M Aix-Marseille Univ. Centrale Marseille CNRS Marseille France

A finite metric space is called here distance degree regular if its distance degree sequence is the same for every vertex. A notion of designs in such spaces is introduced that generalizes that of designs in Q-polynomial distance-regular graphs. An approximation of their cumulative distribution function, based on the notion of Christoffel function in approximation theory is given. As an application we derive limit laws on the weight distributions of binary orthogonal arrays of strength going to infinity. An analogous result for combinatorial designs of strength going to infinity is *** Codes Primary 05E35, Secondary O5E20, 05E24 Copyright © 2021, The Authors. All rights reserved.

关键词： Orthogonal functions

Efficient Video Transformers with Spatial-Temporal Token Selection

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arXiv 2021年

作者： Wang, Junke Yang, Xitong Li, Hengduo Liu, Li Wu, Zuxuan Jiang, Yu-Gang Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University China Shanghai Collaborative Innovation Center on Intelligent Visual Computing China University of Maryland United States BirenTech Research

Video transformers have achieved impressive results on major video recognition benchmarks, which however suffer from high computational cost. In this paper, we present STTS, a token selection framework that dynamically selects a few informative tokens in both temporal and spatial dimensions conditioned on input video samples. Specifically, we formulate token selection as a ranking problem, which estimates the importance of each token through a lightweight scorer network and only those with top scores will be used for downstream evaluation. In the temporal dimension, we keep the frames that are most relevant to the action categories, while in the spatial dimension, we identify the most discriminative region in feature maps without affecting the spatial context used in a hierarchical way in most video transformers. Since the decision of token selection is non-differentiable, we employ a perturbed-maximum based differentiable Top-K operator for end-to-end training. We mainly conduct extensive experiments on Kinetics-400 with a recently introduced video transformer backbone, MViT. Our framework achieves similar results while requiring 20% less computation. We also demonstrate our approach is generic for different transformer architectures and video datasets. Code is available at https://***/wangjk666/STTS. Copyright © 2021, The Authors. All rights reserved.

关键词： Personnel training

APPLICATIONS OF KNOWLEDGE GRAPHS FOR THE FOOD SCIENCE AND INDUSTRY

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arXiv 2021年

作者： Min, Weiqing Liu, Chunlin Xu, Leyi Jiang, Shuqiang Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Soochow University Jiangsu Suzhou215021 China

The deployment of various networks (e.g., Internet of Things (IoT) and mobile networks), databases (e.g., nutrition tables and food compositional databases) and social media (e.g., Instagram and Twitter) generates huge amounts of food data, which present researchers with an unprecedented opportunity to study various problems and applications in the food science and industry via data-driven computational methods. However, these multi-source heterogeneous food data appear as information silos, leading to the difficulty in fully exploiting these food data. The knowledge graph provides a unified and standardized conceptual terminology in a structured form, and thus can effectively organize these food data to benefit various applications. In this review, we provide a brief introduction of knowledge graphs, and the evolution of food knowledge organization mainly from food ontology to food knowledge graphs. We then summarize seven representative applications of food knowledge graphs, such as new recipe development, diet-disease correlation discovery and personalized dietary recommendation. We also discuss future directions in this field, such as multimodal food knowledge graph construction and food knowledge graphs for human health. Copyright © 2021, The Authors. All rights reserved.

关键词： Ontology

PSpan: Mining frequent subnets of petri nets

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arXiv 2021年

作者： Lu, Ruqian Zhang, Shuhan Academy of Mathematics and Systems Science Key Lab of MADIS Chineses Academy Science China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China

This paper proposes for the first time an algorithm PSpan for mining frequent complete subnets from a set of Petri nets. We introduced the concept of complete subnets and the net graph representation. PSpan transforms Petri nets in net graphs and performs sub-net graph mining on them, then transforms the results back to frequent subnets. PSpan follows the pattern growth approach and has similar complexity like gSpan in graph mining. Experiments have been done to confirm PSpan's reliability and complexity. Besides C/E nets, it applies also to a set of other Petri net subclasses. Copyright © 2021, The Authors. All rights reserved.

关键词： Petri nets

Semi-Supervised Vision Transformers

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arXiv 2021年

作者： Weng, Zejia Yang, Xitong Li, Ang Wu, Zuxuan Jiang, Yu-Gang Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University China Shanghai Collaborative Innovation Center on Intelligent Visual Computing China Meta AI China Baidu Apollo China

We study the training of Vision Transformers for semi-supervised image classification. Transformers have recently demonstrated impressive performance on a multitude of supervised learning tasks. Surprisingly, we show Vision Transformers perform significantly worse than Convolutional Neural Networks when only a small set of labeled data is available. Inspired by this observation, we introduce a joint semi-supervised learning framework, Semiformer, which contains a transformer stream, a convolutional stream and a carefully designed fusion module for knowledge sharing between these streams. The convolutional stream is trained on limited labeled data and further used to generate pseudo labels to supervise the training of the transformer stream on unlabeled data. Extensive experiments on ImageNet demonstrate that Semiformer achieves 75.5% top-1 accuracy, outperforming the state-of-the-art by a clear margin. In addition, we show, among other things, Semiformer is a general framework that is compatible with most modern transformer and convolutional neural architectures. Code is available at https://***/wengzejia1/Semiformer. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

HTtext: A TextCNN-based pre-silicon detection for hardware Trojans

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HTtext: A TextCNN-based pre-silicon detection for hardware T...

IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yi Xu Zhenyi Chen Binhong Huang Ximeng Liu Chen Dong College of Computer and Data Science Fuzhou University Fuzhou China University of South Floride Tampa USA Key Lab of Information Security of Network Systems (Fuzhou University) Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University)

With the advent of the intelligence era, the usage and investment for chips have risen year by year, causing the demand for chip security. Machine learning (ML) analysis has made progress as a pre-silicon hardware Trojan (HT) detection technology. Whereas the performance of existing methods almost relies on the accuracy of multi-feature representation, moreover, it is difficult to extract features manually and easily cause unstable classifier performance (namely uncertainty). In this paper, an automatic feature extraction detecting model is first proposed, named HTtext, which generates simple path sentences from chip netlists and employs TextCNN, a deep learning algorithm, to distinguish HT circuits. The pre-training for TextCNN only uses the automatic single-feature calculation to avoid the uncertainty problem. Additionally, the model can obtain non-repetitive HT component information expression, which satisfies the stable detection performance. To measure the efficiency and balance of the model, the paper proposes the concept of the Stability Efficiency Index (SEI). In the experimental results for the benchmark netlists, not only the average accuracy (ACC) in TextCNN is as high as 99.26%, but also its SEI value ranks first in all comparison classifiers, which proves that the proposed HTtext model has high stability in generality.

关键词： Ports (computers) Semiconductor device measurement Uncertainty Stability criteria Feature extraction Hardware Circuit stability

Development of the ultra-high linearity flexible sensor using CMC/MXene-regulating conductive polymer strategy through resistance-capacitance hybrid response for pressure/temperature detection

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Journal of Colloid and Interface Science 2025年

作者： Xiaowen Zhu Yunong Zhao Ziyuan Zhou Aijuan Zhang Wuxue Ma Hanqing Liu Zihan Lin Shishun Yang Yuanyuan Fang Xiangjin Kong Yuxiu Zhongling Weiqiang Hong Qi Hong Xiaohui Guo Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Integrated Circuits Anhui University Hefei 230601 China State Key Laboratory of High-Performance Precision Manufacturing Dalian University of Technology Dalian 116024 China Key Laboratory for Micro/Nano Technology and System of Liaoning Province Dalian University of Technology Dalian 116024 China

Multifunctional temperature/pressure sensors have garnered significant research interest due to their broad applicability in wearable electronics and health monitoring. Nevertheless, most pressure sensors often exhibit pronounced nonlinear responses, primarily attributed to the pressure-dependent increase in compressive modulus. In this paper, we report a multifunctional sensor with ultra-high linearity pressure and well- temperature-sensing performance, fabricated via a facile dip-coating process. The hydrogen bonding interaction between carboxymethyl cellulose (CMC) and MXene effectively mitigates the self-stacking tendency of MXene (Ti 3 C 2 T x ) nanosheets. Subsequently, the CMC-modified MXene facilitates the conformational transition of PEDOT (Poly (3,4-ethylenedioxythiophene)) chains from benzoid to quinoid structures. This synergistic effect enables the fabrication of composites with enhanced electromechanical performance. Additionally, an innovative alternating current (AC) measurement is employed to investigate the potential resistance-capacitance hybrid response within the sensors. By optimizing preparation parameters, we achieve an ultra-high linearity (R 2  = 0.9943) across a broad detection range, alongside a well temperature sensitivity (−2.3575 %/°C). Proof-of-concept applications, including quilt slippage detection and pressure ulcer prevention, demonstrate the sensor's multifunctional capabilities. These findings highlight its potential for wearable medical devices and real-time health monitoring.

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LLR processing of Polar Codes in Concatenation Systems

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China Communications 2019年第9期16卷 201-208页

作者： Ya Meng Yi Fang Chuan Zhang Liping Li Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education of China Anhui UniversityHefei 230031China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China National Mobile Communications Research Laboratory Southeast UniversityNanjingChina

This paper studies the decoding performance of low-density parity-check(LDPC)codes in a serial concatenation system with polar codes employing the successive cancellation(SC)*** is known that the absolute incorrect log-likelihood ratio(LLR)values from the SC decoding can be very *** phenomenon dramatically deteriorates the error correcting performance of the outer LDPC *** this paper,the LLR values of polar codes are regulated by a log processing before being sent to the LDPC *** results show that the log processing is an efficient approach with a low optimization complexity compared with the existing procedures to improve the performance of the serial concatenation systems.

关键词： polar codes SC decoding LDPCcodes concatenation

Zero sum sets in abelian groups

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arXiv 2021年

作者： Shi, Minjia Krotov, Denis Li, Xiaoxiao Solé, Patrick Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematics Sciences Anhui University HefeiAnhui China Sobolev Institute of Mathematics Novosibirsk630090 Russia I2M CNRS Centrale Marseille University of Aix-Marseille Marseilles France

The distribution of cardinalities of zero-sum sets in abelian groups is completely determined. A summation involving the Möbius function is given for the general abelian group, while in many special cases, including the case of elementary abelian groups, solved earlier by Li and Wan, it has a compact form. The proof involves two different Möbius transforms, on positive integers and on set *** Codes 05A18, 05E40, 68P27 Copyright © 2021, The Authors. All rights reserved.

关键词： Group theory