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IEEE Conference on Decision and Control

作者： Hanzheng Zhang Zhaoyang Cheng Guanpu Chen Karl Henrik Johansson Shanghai Research Institute for Autonomous Intelligent Systems Tongji University Shanghai China Academy of Mathematics and System Science Chinese Academy of Science University of Chinese Academy of Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and the Digital Futures Stockholm Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We investigate the equilibrium stability and robustness in a class of moving target defense problems, in which players have both incomplete information and asymmetric cognition. We first establish a Bayesian Stackelberg game model for incomplete information and then employ a hypergame reformulation to address asymmetric cognition. With the core concept of the hyper Bayesian Nash equilibrium (HBNE), a condition for achieving both the strategic and cognitive stability in equilibria can be realized by solving linear equations. Moreover, to deal with players’ underlying perturbed knowledge, we study the equilibrium robustness by presenting a condition of robust HBNE under the given configuration. Experiments evaluate our theoretical results.

关键词： Games Nash equilibrium Stability analysis Robustness Mathematical models Cognition Bayes methods

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Machine Learning Techniques Using the Rapid Miner Tool for Solar Production Forecasting

Machine Learning Techniques Using the Rapid Miner Tool for S...

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Digital Age & Technological Advances for Sustainable Development (ICDATA), International Conference on

作者： Younes Ledmaoui Asmaa El Fahli Adila Elmaghraoui Mohamed El Aroussi Rachid Saadane Abdellah Chehri Laboratory Engineering system Hassania School of Public Works Casablanca Morocco Green Tech Institute (GTI) Mohammed VI Polytechnic University Benguerir Morocco Mathematics and Computer Science Kingston ON Canada

The Artificial Neural Network (ANN), Extreme Gradient Boosting (XGBOOST), Support Vector Machine (SVM), and Random Forest (RF) machine learning (ML) algorithms are used in this research to give a comparative study of solar energy production forecasting in Morocco. The models were developed, trained, and then assessed. In this paper, two metrics were employed to evaluate the models' performance: Mean absolute error (MAE), and root mean squared error (RMSE). The models' performances show that ANN is the most reliable predictive model for energy forecasting in similar scenarios.

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A Multichannel 14-Bit, 3-Msps/channel, Event-Driven Hybrid ADC with SAR/SS/TDC Architecture for Dark Matter Detection

A Multichannel 14-Bit, 3-Msps/channel, Event-Driven Hybrid A...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： C. Yu J. Cheng B. Yang Y. Qian W. Gao School of Computer Science Institute of Microelectronics Northwestern Polytechnical University Xi’an China Chinese Academy of Science Institute of Modern Physics Lanzhou China Ministry of Education Engineering Research Center of Embedded System Integrated Xi’an China

In the next-generation dark matter detection misssion, energy-efficient front-end electronics plays an importan role to construct space-bone radiation detector systems. A multichannel analog-to-digital converter (ADC) is required to digitize the analog signals from readout channels which is employed to read out the charges from a PMT detector with the plastic scintillator. The requirements of the ADC are listed below: the resolution of 14 bits; the sampling rate of larger than 3 Msps per channel, and the channel number of 16 (or more). In this paper, a novel hybrid ADC, which combines the techniques of successive approximate register (SAR) ADC, single-slope (SS) ramp ADC and time-to-digital converter (TDC) based on delay-locked loop (DLL), is proposed to meet the above performance constrains. A 5-bit SAR ADC, a 4-bit SS ADC and a 5-bit TDC are finally selected to construct a 14-bit converter under the tradeoff of resolution, speed and power dissipation. The advantage of this architecture lies in that it is easy to extended to multiple channels by the increase small power and area overhead in each channel. Both event-driven mode and continuous-conversion mode are realized for timing controlling and data readout. A four-channel prototype chip has been designed and fabricated in 0.18 μm CMOS process with 1.8/3.3 V power supply. A sampling rate of ~ 3.3 MS/s is achieved at the clock frequency of 100 MHz. Under the power consumption of 4 mW/channel, the differential nonlinearity (DNL) and the integral nonlinearity (INL) are simulated as -1/+0.7 LSB and -3 LSB/+2.8 LSB, respectively. The effective-number-of-bits (ENOB) is 12.7 bits and the signal-to-noise ratio (SNR) is 85.9 dB. The figure-of-merit (FOM) of 192.9 f J /conv.-step has been achieved.

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Integrating GPS and GSM Technologies for Enhanced Women’s Safety: A Fingerprint-Activated Device Approach

Integrating GPS and GSM Technologies for Enhanced Women’s S...

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Automation and Computation (AUTOCOM), International Conference on

作者： Kamred Udham Singh Varun Chaudhary Pradeep Kumar Sharma Pushpendra Kumar Neeraj Varshney Teekam Singh School of Computing Graphic Era Hill University Dehradun India IMS ENGINEERING COLLEGE Ghaziabad India Technical Architect HCL Technologies Noida UP Sr Software Engineer Scanno System Greater Noida Department of Computer Engineering & Applications GLA University Mathura UP India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun

The creation of a safety system that is based on GPS and is developed exclusively for the health and safety of women via the incorporation of novel elements in order to meet the rising concerns about crimes committed against women. The gadget is capable of contacting authorities, conveying the user’s position via SMS, and generating a loud noise to attract attention. It may be triggered in anticipation of potential danger and can be activated in the event that danger is imminent. In order to guarantee that only authorized users are able to activate the device, the system makes use of fingerprint recognition in a very unique way. Using technologies such as global positioning system (GPS), global system for mobile communications (GSM), and microcontrollers, this study makes a contribution to the continuing efforts to improve the safety of women via technological innovation. It provides a proactive approach to prevent violence against women and save lives. The research emphasizes the significance of combining hardware and software in order to provide a complete safety tool. It also illustrates the vital role that quick support plays and the potential of such gadgets to promote confidence among women in public places.

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Bayesian hypergame approach to equilibrium stability and robustness in moving target defense

arXiv

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arXiv 2024年

作者： Zhang, Hanzheng Cheng, Zhaoyang Chen, Guanpu Johansson, Karl Henrik Shanghai Research Institute for Autonomous Intelligent Systems Tongji University Shanghai China Academy of Mathematics and System Science Chinese Academy of Science University of Chinese Academy of Science Beijing China The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology The Digital Futures Stockholm Sweden

关键词： Nash equilibrium

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MMAGL: Multiobjective Multiview Attributed Graph Learning for Joint Clustering of Hyperspectral and LiDAR Data

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Zhang, Zijia Cai, Yaoming Gong, Wenyin Liu, Xiaobo Zeng, Cheng Yu, Gan Hubei University School of Artificial Intelligence Wuhan430078 China Hubei University Key Laboratory of Intelligent Sensing System and Security Ministry of Education Wuhan430078 China Zhongnan University of Economics and Law School of Information Engineering Wuhan430073 China China University of Geosciences School of Computer Science Wuhan430074 China China University of Geosciences School of Automation Wuhan430074 China Fuyang Normal University College of Information Engineering Fuyang236037 China

The joint clustering of multimodal remote sensing (RS) data represents a multiobjective optimization challenge involving conflicting modality-specific objectives and diverse regularization objectives. Current approaches to multiview subspace clustering (MVSC) often oversimplify this task by transforming it into a weighted single-objective optimization problem, neglecting the intricate interactions between objectives and leading to suboptimal subspace representations. The presence of quadratic decision variables in MVSC renders direct application on large-scale RS data impracticable using multiobjective evolutionary algorithms (MOEAs). To overcome this challenge, we propose a novel MVSC method termed multiobjective multiview attributed graph learning (MMAGL). Instead of optimizing every self-representation coefficient individually, our method transforms MVSC into a link prediction task over a sparse attributed graph that fuses different modalities. We incorporate superpixel-based sample reduction and proximity-based population coding, leveraging spatial and structural priors, respectively. This results in a significantly compressed decision space, enabling optimization with MOEAs. To fully exploit node attributes and the graph structure, we redefine self-representation using contrastive learning and introduce an efficient graph filtering (GF) through a generalized spectral graph convolution, enhancing clustering discriminability. The proposed MMAGL constitutes a hybrid and versatile framework, adaptable to any MOEA. Extensive experimental evaluations demonstrate that our MMAGL method surpasses the current state-of-the-art on multimodal RS benchmarks (e.g., with nearly 2% gain on Trento and 3% on Houston) on overall accuracy. © 2025 IEEE.

关键词： Proximity sensors

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A GLRT for estimating the number of correlated components in sample-poor mCCA

A GLRT for estimating the number of correlated components in...

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European Signal Processing Conference (EUSIPCO)

作者： Tanuj Hasija Timothy Marrinan Signal and System Theory Group Universität Paderborn Germany School of Electrical Engineering and Computer Science Oregon State University USA

ISBN: (数字)9789082797091

ISBN: (纸本)9781665467995

In many applications, components correlated across multiple data sets represent meaningful patterns and commonalities. Estimates of these patterns can be improved when the number of correlated components is known, but since data exploration often occurs in an unsupervised setting, the number of correlated components is generally not known. In this paper, we derive a generalized likelihood ratio test (GLRT) for estimating the number of components correlated across multiple data sets. In particular, we are concerned with the scenario where the number of available samples is small. As a result of the small sample support, correlation coefficients and other summary statistics are significantly overestimated by traditional methods. The proposed test combines linear dimensionality reduction with a GLRT based on a measure of multiset correlation referred as the generalized variance cost function (mCCA-GENVAR). By jointly estimating the rank of the dimensionality reduction and the number of correlated components, we are able to provide high-accuracy estimates in the challenging sample-poor setting. These advantages are illustrated in numerical experiments that compare and contrast the proposed method with existing techniques.

关键词： Dimensionality reduction Correlation coefficient Correlation Atmospheric measurements Europe Signal processing Particle measurements

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Optimal Action Strategy approach for Desert Crossing Based on Dynamic Programming

Optimal Action Strategy approach for Desert Crossing Based o...

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CQVIP Conference on Data Driven Intelligence and Innovation, CCDDII 2021

作者： Fan, Xingrong Meng, Dian Chongqing Engineering Laboratory for Detection Control and Integrated System Chongqing Technology and Business University Chongqing400067 China School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing400067 China

It is a novel but challenging task that simulated desert crossing strategy for the game players under the specified conditions. This study is aimed to develop an optimal action strategy approach for desert crossing based on dynamic programming. According to the game rules, a multi-stage decision optimization model was first established to maximize the remaining funds of players within given game time. Then, a simulation-based dynamic programming algorithm was designed to solve the optimization model, and the optimal action strategy was obtained by backtracking crossing routes. Finally, two experimental case studies with different initial conditions were used to validate the model. In comparison with the benchmark exhaustive search algorithm, the proposed approach has higher performance and efficiency. The case studies confirm that the method can obtain the optimal action strategy under different game maps and initial resources. © 2021 Elsevier B.V.. All rights reserved.

关键词： Dynamic programming

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoke Zhu Danyang Li Xiaopan Chen Fumin Qi Fan Zhang Xiao-Yuan Jing School of Computer and Information Engineering Henan University Kaifeng China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng China Department of System Operation National Supercomuting Center in Shenzhen Shenzhen China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China School of Computer Science Wuhan University Wuhan China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Facial image based kinship verification aims to decide whether there exists kinship between the given facial images. In practice, the cross-generation differences will cause adverse effects on kinship verification, which limits the performance. Therefore, how to mine the implied similarity from facial images with large cross-generation divergence is an important problem in kinship verification, which has not yet been well studied. In view of this, we propose a Similarity Mining via Implicit matching pattern LEarning (SMILE) approach for kinship verification. Specifically, SMILE mainly consists of two modules, including a Semi-coupled Multi-pattern Similarity Learning (SMSL) module and a Cross-Generation Feature Normalization (CGFN) module. The SMSL module is designed to learn multiple semi-coupled matching patterns for mining the implicit facial similarity information from different perspectives. The CGFN module aims to reduce the divergence between facial images of parent and child. Extensive experiments demonstrate that the proposed approach outperforms the existing state-of-the-art methods.

关键词： Pattern matching Similarity learning

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Flexible Pressure Sensor Constructed from Polyurethane Conductive Sponge Material

SSRN

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SSRN 2023年

作者： Dong, Liang Li, Chen Zhou, Youjun Zhao, Mengxi Song, Longgang Han, Peiying Zhang, Heng College of Mechanical & Electrical Engineering Shaanxi University of Science & Technology Xi’an710021 China School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory of Mechanical Manufacturing System Engineering Xi’an Jiaotong University Xi’an710054 China School of Mathematics & Computer Science Guangxi Science & Technology Normal University Laibin546199 China

As the main core component of wearable devices, flexible strain sensors have broad application prospects in health monitoring, motion monitoring, human-machine interface, rehabilitation, entertainment technology and other fields. In this paper, a rectangular sandwich sensor is constructed by using a conductive sponge. The gel modification improves the linearity of the sensor and increases the stress range. Through experiments, it can withstand more than 80% compressive strain, show 0.398 kPa-1 sensitivity in the range of 6~11 kPa, the maximum range is close to 40 kPa, the minimum detection limit is 20 Pa, good linearity and stability. A single entity performs some measurement of human activity signals, and 8 sensors are constructed into an interesting smart insole. © 2023, The Authors. All rights reserved.

关键词： Wearable sensors

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