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Ionic current model of the retinal photoreceptor and simulation analysis of the photoresponses

SYSTEMS AND computerS IN JAPAN 1996年第12期27卷 10-21页

作者： Usui, TOS Kamiyama, Y Faculty of Information Engineering Toyohashi University of Technology Shim Usui:graduated in 1974 with his Ph.D. degree in Computer Science from the University of California. He was appointed Research Associate at Nagoya University in 1974 a Lecturer at Toyohashi University of Technology in 1979 and an Associate Professor and then a Professor in 1986. He has been engaged in research on physiological information engineering and physiological engineering. He is the author of Basic Physwlqicul Signal Processing. He is a member of IEE Institute of Measurement and Automation Japan Institute of Information Processing Japan Institute of Medical Engineering Japan Institute of Physiology Japan Institute of Neural Science Japan Institute of Neural Networks Japan: and INNS. He is an IEEE fellow.

The fact that the reception of optical information by the retinal photoreceptor and the process of its transformation to the membrane voltage response are due to an interaction between the photocurrent from the outer segment and each ionic current in the inner segment has been confirmed by many physiological experiments. However, the properties of each ionic current in the photoreceptor have not been clear since no physiologically reliable model of the retinal photoreceptor has been constructed. This paper proposes a model of a retinal photoreceptor, which is a combination of the outer segment model (devised by Torre et al.) and the inner segment model (devised by the present authors). It has been confirmed that this model can accurately represent the electron physiological properties of a retinal photoreceptor. Using this model simulation, the relationship between the photocurrent and the photoresponse dynamics, and an oscillatory phenomena caused by a strong light flash have been analyzed. The results show that the dynamic and nonlinear response characteristics of a retinal photoreceptor are due to the interactions between the nonlinear ionic current in the inner segment and the mechanism of the intracellular calcium.

关键词： retinal photoreceptor photoresponse intracellular calcium mechanism simulation analysis

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Early detection of the advanced persistent threat attack using performance analysis of deep learning

arXiv

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arXiv 2020年

作者： Joloudari, Javad Hassannataj Haderbadi, Mojtaba Mashmool, Amir GhasemiGol, Mohammad Shahab, S. Mosavi, Amir Computer Engineering Department Faculty of Engineering University of Birjand Birjand Iran Department of Information Technology Mazandaran University of Science and Technology Babol Iran Institute of Research and Development Duy Tan University Da Nang550000 Viet Nam Future Technology Research Center College of Future National Yunlin University of Science and Technology 123 University Ro ad Section 3 Douliou Yunlin64002 Taiwan Institute of Automation Obuda University Budapest1034 Hungary School of Economics and Business Norwegian University of Life Sciences Ås1430 Norway Faculty of Civil Engineering Technische Universität Dresden Dresden01069 Germany Department of Informatics J. Selye University Komarno94501 Slovakia

One of the most common and important destructive attacks on the victim system is Advanced Persistent Threat (APT)-attack. The APT attacker can achieve his hostile goals by obtaining information and gaining financial benefits regarding the infrastructure of a network. One of the solutions to detect a secret APT attack is using network traffic. Due to the nature of the APT attack in terms of being on the network for a long time and the fact that the network may crash because of high traffic, it is difficult to detect this type of attack. Hence, in this study, machine learning methods such as C5.0 decision tree, Bayesian network and deep neural network are used for timely detection and classification of APT-attacks on the NSL-KDD dataset. Moreover, 10-fold cross validation method is used to experiment these models. As a result, the accuracy (ACC) of the C5.0 decision tree, Bayesian network and 6-layer deep learning models is obtained as 95.64%, 88.37% and 98.85%, respectively, and also, in terms of the important criterion of the false positive rate (FPR), the FPR value for the C5.0 decision tree, Bayesian network and 6-layer deep learning models is obtained as 2.56, 10.47 and 1.13, respectively. Other criterions such as sensitivity, specificity, accuracy, false negative rate and F-measure are also investigated for the models, and the experimental results show that the deep learning model with automatic multi-layered extraction of features has the best performance for timely detection of an APT-attack comparing to other classification models. Copyright © 2020, The Authors. All rights reserved.

关键词： Feature extraction

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2020年 1241 AISC卷 v-vi页

作者： Vittorini, Pierpaolo Di Mascio, Tania Tarantino, Laura Temperini, Marco Gennari, Rosella De la Prieta, Fernando Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Computer Science and Automation Control University of Salamanca Salamanca Spain

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8875卷

作者： Narasimha Murty, M. He, Xiangjian Raghavendra Rao, C. Weng, Paul Department of Computer Science and Automation Indian Institute of ScienceBangalore Bangalore India Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Department of Computer and Information Sciences University of Hyderabad Hyderabad India LIP6 University Pierre et Marie Curie Paris France

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Label Cluster Chains for Multi-Label Classification

arXiv

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arXiv 2024年

作者： Gatto, Elaine Cecília Nakano, Felipe Kenji Read, Jesse Ferrandin, Mauri Cerri, Ricardo Vens, Celine Department of Computer Science Federal University of São Carlos SP São Carlos13565-905 Brazil Faculty of Medicine Katholieke Universiteit Leuven West Flanders Kortrijk8500 Belgium École Polytechnique Polytechnic Institute of Paris Palaiseau Paris91120 France Department of Control Automation and Computing Engineering Federal University of Santa Catarina SC Blumenau89036-002 Brazil Institute of Mathematical and Computing Sciences University of São Paulo SP São Carlos13566-590 Brazil

Multi-label classification is a type of supervised machine learning that can simultaneously assign multiple labels to an instance. To solve this task, some methods divide the original problem into several sub-problems (local approach), others learn all labels at once (global approach), and others combine several classifiers (ensemble approach). Regardless of the approach used, exploring and learning label correlations is important to improve the classifier predictions. Ensemble of Classifier Chains (ECC) is a well-known multi-label method that considers label correlations and can achieve good overall performance on several multi-label datasets and evaluation measures. However, one of the challenges when working with ECC is the high dimensionality of the label space, which can impose limitations for fully-cascaded chains as the complexity increases regarding feature space expansion. To improve classifier chains, we propose a method to chain disjoint correlated label clusters obtained by applying a partition method in the label space. During the training phase, the ground truth labels of each cluster are used as new features for all of the following clusters. During the test phase, the predicted labels of clusters are used as new features for all the following clusters. Our proposal, called Label Cluster Chains for Multi-Label Classification (LCC-ML), uses multi-label Random Forests as base classifiers in each cluster, combining their predictions to obtain a final multi-label classification. Our proposal obtained better results compared to the original ECC. This shows that learning and chaining disjoint correlated label clusters can better explore and learn label correlations. © 2024, CC BY.

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Developing and validating measures for AI literacy tests: From self-reported to objective measures

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computers and Education: Artificial Intelligence 2024年 7卷

作者： Chiu, Thomas K.F. Chen, Yifan Yau, King Woon Chai, Ching-sing Meng, Helen King, Irwin Wong, Savio Yam, Yeung Department of Curriculum and Instruction Faculty of Education and Centre for Learning Sciences and Technologies And Centre for University and School Partnership the Chinese University of Hong Kong SAR ShatinNT Hong Kong Faculty of Engineering The Chinese University of Hong Kong SAR ShatinNT Hong Kong Faculty of Education The Chinese University of Hong Kong SAR ShatinNT Hong Kong Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong SAR ShatinNT Hong Kong Department of Computer Science & Engineering The Chinese University of Hong Kong SAR ShatinNT Hong Kong Department of Educational Psychology The Chinese University of Hong Kong SAR ShatinNT Hong Kong Department of Mechanical and Automation Engineering The Chinese University of Hong Kong SAR ShatinNT Hong Kong

The majority of AI literacy studies have designed and developed self-reported questionnaires to assess AI learning and understanding. These studies assessed students' perceived AI capability rather than AI literacy because self-perceptions are seldom an accurate account of true measures. International assessment programs that use objective measures to assess science, mathematical, digital, and computational literacy back up this argument. Furthermore, because AI education research is still in its infancy, the current definition of AI literacy in the literature may not meet the needs of young students. Therefore, this study aims to develop and validate an AI literacy test for school students within the interdisciplinary project known as AI4future. Engineering and education researchers created and selected 25 multiple-choice questions to accomplish this goal, and school teachers validated them while developing an AI curriculum for middle schools. 2390 students in grades 7 to 9 took the test. We used a Rasch model to investigate the discrimination, reliability, and validity of the items. The results showed that the model met the unidimensionality assumption and demonstrated a set of reliable and valid items. They indicate the quality of the test items. The test enables AI education researchers and practitioners to appropriately evaluate their AI-related education interventions. © 2024 The Authors

关键词： AI literacy Instrument K-12 education AI education Co-design process Measures

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High-frequency oscillations in the atmosphere above a sunspot umbra

arXiv

引用

arXiv 2018年

作者： Wang, Feng Deng, Hui Bo, L.I. Feng, Song Xianyong, B.A.I. Deng, Linhua Yang, Yunfei Zhike, X.U.E. Wang, Rui School of Physics and Electronic Engineering Guangzhou University Guangzhou510006 China Yunnan Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Shandong Provincial Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment Institute of Space Sciences Shandong University Weihai264209 China CAS Key Laboratory of Solar Activity National Astronomical Observatories Beijing100012 China Yunnan Observatories Chinese Academy of Sciences Kunming650216 China

We use high spatial and temporal resolution observations, simultaneously obtained with the New Vacuum Solar Telescope and Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory, to investigate the high-frequency oscillations above a sunspot umbra. A novel time–frequency analysis method, namely the synchrosqueezing transform (SST), is employed to represent their power spectra and to reconstruct the high-frequency signals at different solar atmospheric layers. A validation study with synthetic signals demonstrates that SST is capable to resolving weak signals even when their strength is comparable with the high-frequency noise. The power spectra, obtained from both SST and the Fourier transform, of the entire umbral region indicate that there are significant enhancements between 10 and 14 mHz (labeled as 12 mHz) at different atmospheric layers. Analyzing the spectrum of a photospheric region far away from the umbra demonstrates that this 12 mHz component exists only inside the umbra. The animation based on the reconstructed 12 mHz component in AIA 171 Å illustrates that an intermittently propagating wave first emerges near the footpoints of coronal fan structures, and then propagates outward along the structures. A time–distance diagram, coupled with a subsonic wave speed (∼ 49 km s−1), highlights the fact that these coronal perturbations are best described as upwardly propagating magnetoacoustic slow waves. Thus, we first reveal the high-frequency oscillations with a period around one minute in imaging observations at different height above an umbra, and these oscillations seem to be related to the umbral perturbations in the photosphere. Copyright © 2018, The Authors. All rights reserved.

关键词： Magnetohydrodynamics

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Reviewing continual learning from the perspective of human-level intelligence

arXiv

引用

arXiv 2021年

作者： Chang, Yifan Li, Wenbo Peng, Jian Tang, Bo Kang, Yu Lei, Yinjie Gui, Yuanmiao Zhu, Qing Liu, Yu Li, Haifeng The State Key Laboratory of Fire Science Department of Automation and Institute of Advanced Technology University of Science and Technology of China Hefei China Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China The Department of Electrical and Computer Engineering Mississippi State University United States College of Electronics and Information Engineering Sichuan University Chengdu China Faculty of Geosciences and Environmental Engineering The Southwest Jiaotong University Chengdu China Institute of Remote Sensing and Geographic Information System Peking Universit Beijing China School of Geosciences and Info-Physics Central South University South Lushan Road Changsha410083 China

Humans continual learning (CL) ability is closely related to Stability Versus Plasticity Dilemma that describes how humans achieve ongoing learning capacity and preservation for learned information. The notion of CL has always been present in artificial intelligence (AI) since its births. This paper proposes a comprehensive review of CL. Different from previous reviews that mainly focus on the catastrophic forgetting phenomenon in CL, this paper surveys CL from a more macroscopic perspective based on the Stability Versus Plasticity mechanism. Analogous to biological counterpart, "smart" AI agents are supposed to i) remember previously learned information (information retrospection);ii) infer on new information continuously (information prospection:);iii) transfer useful information (information transfer), to achieve high-level CL. According to the taxonomy, evaluation metrics, algorithms, applications as well as some open issues are then introduced. Our main contributions concern i) rechecking CL from the level of artificial general intelligence;ii) providing a detailed and extensive overview on CL topics;iii) presenting some novel ideas on the potential development of CL. © 2021, CC BY.

关键词： Petroleum reservoir evaluation

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C²F²: Cross-Task Cross-Domain Feature Fusion for Semi-Supervised Change Detection

引用

IEEE Geoscience and Remote Sensing Letters 2024年 21卷

作者： Dongjie Zhang Yuting Hong Xiaojie Qiu Li Dong Diqun Yan Chengbin Peng Faculty of Electrical Engineering and Computer Science and the Key Laboratory of Mobile Network Application Technology of Zhejiang Province Ningbo University Ningbo China Zhejiang Cowain Automation Technology Company Ltd. Ningbo China

Semi-supervised learning for change detection (CD), which significantly reduces the labor costs associated with data annotation, has recently garnered substantial attention. In this study, we propose to enhance traditional semi-supervised learning frameworks by leveraging cross-task cross-domain (CTCD) models, which generate complementary features that differ from standard hidden features. The procedure is as follows. First, the standard features obtained from a traditional encoding–decoding structure are fused with attention-augmented complementary features. Second, a secondary decoder maps the fused heterogeneous features into the label space to obtain high-quality pseudo-labels, offering more precise guidance for semi-supervised learning on traditional structures. This approach improves pseudo-labels by leveraging the strength of CTCD models, including large pretrained models, to enhance the semi-supervised learning process of domain-specific and task-specific models. Experimental results on benchmark datasets demonstrate that our proposed approach surpasses state-of-the-art methods.

关键词： Standards Feature extraction Decoding Training Accuracy Semisupervised learning Supervised learning

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HIGH-RISE BUILDINGS UNDER EARTHQUAKE EXCITATION: STABILIZATION USING SMC

引用

IFAC Proceedings Volumes 2006年第16期39卷 776-781页

作者： Georgi M. Dimirovski Jun Zhao Miomir K. Vukobratovic Dogus University Faculty of Engineering Dept. of Computer Engineering Acibadem Zeamet Sk. 21 Kadikoy TR-34722 Istanbul Rep. of Turkey Fax: ++90-216-327-9631 Tel: ++90-216-327-1104 SS Cyril and Methodius University Faculty of Electrical Engineering Rugjer Boskovic b.b. Karpos II MK-1000 Skopje Rep. of Macedonia Northestern University School of Information Science and Engineering Institute of Control Science Shenyang Liaoning CN-110004 P. R. of China Fax: ++86-24-8367-2273 Tel: ++86-24-2389-3000 Mihailo Pupin Institute Laboratory of Robotics & Automation Volgina 15 Karaburma 11000 F. R. Serbia and Montenegro Fax: ++381-11-2775-870 Tel: ++381-11-2774-236

The goal to control the dynamics of high-rise buildings either to ameliorate the damage or prevent their destruction when subject to an earthquake excitation has been subject of extensive research. All known control designs have advantages and disadvantages as well as operating limits. The application of sliding-mode control to controlling earthquake induced vibrations of a multi-story structural system as an active seismic compensation plus base isolation has been investigated. The performance has been compared to the one of traditional industrial controls, and relevant conclusions drawn. Simulation results, carried out using El Centro earthquake acceleration, have shown that the sliding mode control can decrease significantly displacements of the floors.

关键词： Earthquake sliding mode control structural systems vibration control

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