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检索条件"任意字段=2023 International Conference on Cognitive Computing and Complex Data, ICCD 2023"

共 712 条记录，以下是161-170 订阅

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Efficient MILP Decomposition in Quantum computing for ReLU Network Robustness 4

Efficient MILP Decomposition in Quantum Computing for ReLU N...

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4th IEEE international conference on Quantum computing and Engineering, QCE 2023

作者： Franco, Nicola Wollschläger, Tom Poggel, Benedikt Günnemann, Stephan Lorenz, Jeanette Miriam Fraunhofer Institute for Cognitive Systems Iks Munich Germany Technical Univ. of Munich Dept. of Computer Science Munich Data Science Institute Germany

ISBN: (纸本)9798350343236

Emerging quantum computing technologies, such as Noisy Intermediate-Scale Quantum (NISQ) devices, offer potential advancements in solving mathematical optimization problems. However, limitations in qubit availability, noise, and errors pose challenges for practical implementation. In this study, we examine two decomposition methods for Mixed-Integer Linear Programming (MILP) designed to reduce the original problem size and utilize available NISQ devices more efficiently. We concentrate on breaking down the original problem into smaller subproblems, which are then solved iteratively using a combined quantum-classical hardware approach. We conduct a detailed analysis for the decomposition of MILP with Benders and Dantzig-Wolfe methods. In our analysis, we show that the number of qubits required to solve Benders is exponentially large in the worst-case, while remains constant for Dantzig-Wolfe. Additionally, we leverage Dantzig-Wolfe decomposition on the use-case of certifying the robustness of ReLU networks. Our experimental results demonstrate that this approach can save up to 90% of qubits compared to existing methods on quantum annealing and gate-based quantum computers. © 2023 IEEE.

关键词： Qubits

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Fuzziness-Based Semi-Supervised Learning for Early Detection of Alzheimer's Disease using MRI data 26

Fuzziness-Based Semi-Supervised Learning for Early Detection...

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26th international conference on Computer and Information Technology, ICCIT 2023

作者： Bushra, Umme Habiba Priya, Fahmida Chowdhury Patwary, Muhammed J. A. International Islamic University Chittagong Department of Computer Science and Engineering Chattogram Bangladesh

ISBN: (纸本)9798350359015

Alzheimer's disease (AD) is a progressive neurodegenerative condition that erodes memory and cognitive abilities. It manifests as a gradual decline in cognitive functions, including memory loss, impaired decision-making and challenges in communication. As the disease advances, individuals may also experience changes in behavior and struggle with daily tasks. Detecting Alzheimer's in its early stages is crucial, as intervention can slow brain damage. However, diagnosing it can be complex, especially when symptoms are subtle and resemble normal aging. This study's focus is early AD detection, particularly identifying Mild cognitive Impairment (MCI), a challenging clinical diagnosis from MRI data. A novel approach is proposed where deep features extracted from two different CNN architectures and ORBbased features are combined through feature-level fusion. After performing feature-level fusion, a semi-supervised methodology are incorporated in the concept of fuzziness. The classification task is executed using a SVM classifier, yielding an accuracy of 94.39% for MCI vs CN (cognitively Normal) and 97.90% for AD vs CN. The proposed approach exhibits significant improvements in the classifier's performance compared to existing methods on the ADNI dataset. © 2023 IEEE.

关键词： Alzheimer's Disease Deep Learning Feature Level Fusion Fuzziness Machine Learning Semi-Supervised Learning

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Improving Quantal cognitive Hierarchy Model Through Iterative Population Learning 22

Improving Quantal Cognitive Hierarchy Model Through Iterativ...

引用

22nd international conference on Autonomous Agents and Multiagent Systems, AAMAS 2023

作者： Xu, Yuhong Cheng, Shih-Fen Chen, Xinyu School of Computing and Information Systems Singapore Management University Singapore

In this paper, we propose to enhance the state-of-the-art quantal cognitive hierarchy (QCH) model with iterative population learning (IPL) to estimate the empirical distribution of agents' reasoning levels and fit human agents' behavioral data. We apply our approach to a real-world dataset from the Swedish lowest unique positive integer (LUPI) game and show that our proposed approach outperforms the theoretical Poisson Nash equilibrium predictions and the QCH approach by 49.8% and 46.6% in Wasserstein distance respectively. Our approach also allows us to explicitly measure an agent's reasoning level distribution, which is not previously possible. © 2023 international Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Population statistics

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cognitive Defense Cyber Attack Prediction and Security Design in Machine Learning Model 6

Cognitive Defense Cyber Attack Prediction and Security Desig...

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6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Devadarshini, P.T. Chandrashekar, B. Pundir, Sumit Tiwari, Mohit Madala, Ravikiran Indhuma, E. Easwari Engineering College Department of Artificial Intelligence and Data Science TamilNadu Chennai India St. Martin's Engineering College Department of Computer Science and Engineering Kompalli Telangana Secunderabad India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India Network and Data Center Engineer Ph.D Information Technology University of Cumberlands DurhamNC United States St.Martln's Engineering College Department of Computer Science and Engineering Telangana Secunderabad India

ISBN: (纸本)9798350304480

Companies of all sizes in today's linked digital world are susceptible to cyber dangers. In this study, we provide a novel approach to cyber defence that integrates machine learning with cognitive defensive techniques to identify and prevent cyber attacks in their tracks. We built three ML models that use cognitive defensive strategies and other cutting-edge security measures like encryption and intrusion detection. A 95% accuracy rate was reached by our models, which is far greater than where things stand right now models. Our work has the potential to have a huge effect since the models we've developed may one day help businesses take a more preventative stance against cyber threats. Our findings may potentially be used to fields outside than cyber security. Overall, our study shows that machine learning and cognitive defense are useful for foreseeing and stopping cyber threats, and points the way toward fruitful future study in this area. © 2023 IEEE.

关键词： Accuracy Advanced security features cognitive defense Cyber security Cyber-attacks Encryption Intrusion detection Machine learning Prediction Prevention Proactive approach Threat landscape

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Policy-based Role and Access Modeling 12

Policy-based Role and Access Modeling

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12th IEEE international conference on Intelligent data Acquisition and Advanced computing Systems: Technology and Applications, IDAACS 2023

作者： Ayman, Noha Kiryakos, Mariam Sabty, Caroline El Bolock, Alia Abdennadher, Slim German International University Informatics and Computer Science Cairo Egypt Swansea University Swansea United Kingdom

ISBN: (纸本)9798350358056

In this paper, we present an approach based on Attribute Based Access Control (ABAC) and Risk Adaptive Access Control (RAdAC) to improve the reliability of the risk assessment and authorization process. The model has been designed to adapt to the complex and ever-changing nature of modern campus networks by incorporating location information. This added layer of risk assessment enhances the ABAC model by adding a level of authorization to it. © 2023 IEEE.

关键词： Attribute Based Access Control (ABAC) policy Risk Adaptive Access Control (RAdAC)

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Research on Autonomous Collision Avoidance Method of Typical General Aviation Aircraft Based on cognitive System 7th

Research on Autonomous Collision Avoidance Method of Typical...

引用

7th international conference on computing, Control and Industrial Engineering, CCIE 2023

作者： Zhang, Jie Bao, Xiyan Diao, Hanlou Nanjing Highway Development Center Jiangsu Nanjing210014 China Jiangsu Provincial Department of Transportation Jiangsu Nanjing210001 China China Design Group Jiangsu Nanjing210014 China

ISBN: (纸本)9789819927296

For the typical general aviation aircraft autonomous collision avoidance process, the collision avoidance rules for general aviation aircraft autonomous avoidance of fixed obstacles, random obstacles and other aircraft are established, and the general aviation aircraft autonomous collision avoidance algorithm based on the cognitive system is constructed. A complex low-altitude flight collision avoidance system built on Visual Studio 2013 is used to verify the behavior of typical general aviation aircrafts in avoiding fixed and random obstacles autonomously. Based on the idea of control variables and reinforcement learning, trend analysis and law summary of simulation data are performed. The relationship between the selection of autonomous avoidance methods for general aviation aircrafts and the obstacle distance is derived from the result analysis, which verifies the effectiveness of the typical autonomous avoidance methods for general aviation aircrafts proposed in this study. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Collision avoidance

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Trusted Channel Selection in cognitive Radio Network using VIKOR method 1

Trusted Channel Selection in Cognitive Radio Network using V...

引用

1st international conference on cognitive computing and Engineering Education, ICCCEE 2023

作者： Bhatia, Jitesh Kumar Mittal, Praveen GLA University Department of Computer Engineering Applications Mathura India

ISBN: (纸本)9798350332803

cognitive radio networks referred as CRNs use opportunistic spectrum access to improve the utilization of wireless resources. However, the selection of channels with high quality and trust is a critical issue in CRNs. This paper proposes a novel channel selection method using the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method to enhance the trustworthiness of CRNs. The VIKOR method is used to solve the multi-criteria decision-making problem by ranking alternatives and selecting the most appropriate channel for transmission. The channel selection process is based on various criteria such as channel availability, channel quality, channel reliability, and channel security. The paper discusses the problem of sensitivity regulation in multi-channel cognitive medium access. The availability probability of each channel is known, and the paper considers the situation where the probable channels are the equal modeled while independent when present, and not employing adaptive modulation, and instinctive sensitivity issues of the line sequence. The paper proves that the VIKOR method is a great way to optimize this process. The proposed method is particularly useful in avionics networks that require strict reliability and security requirements. The paper proposes a hardware layer reliable channel model that creates a reliable system with a reliable channel model. The layer of hardware is entrenched in hardware equipment via measurement of agents with control. This ensures reliable operation and system control in terms of volume. The channel model can monitor the data of this system, preventing intermediaries and malicious fraud attacks from compromising its security. The paper provides selection algorithms for wireless networks of ad-hoc with several priorities including multi functions for multiple task processes. The main objectives of the algorithms include effective performance with utilization of ideal resource through the balancing of load as well as

关键词： cognitive radio

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Construction of Index System of international Economic Cooperation Innovation Model in Digital Era-based on TIF Theory and DIKWP Model 25

Construction of Index System of International Economic Coope...

引用

25th IEEE international conferences on High Performance computing and Communications, 9th international conference on data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Shanqi, Zhan Tang, Fuliang Li, Yongmei Qiurong, Mei Zining, Lu Xing-Sen, Li Biyun, Zhang School of Software and Microelectronics Peking University Beijing China Dikwp Research Group School of Computer and Technology Hainan University China College of Engineering Peking University China Center of Chinese and Foreign Think Tanks China Beijing Financial Holdings Group China Research Institute of Extenics and Innovation Methods Guangdong University of Technology China China

ISBN: (纸本)9798350330014

With the deepening of globalization, international economic cooperation has become a key factor in promoting economic growth and development. However, the rapid changes and technological advances brought about by the digital age are changing the rules and methods of international economic cooperation. In this digital age, data is no longer just a resource, it is more like a new economic currency, and the development of information technology has made it easier to move data across borders, providing unprecedented opportunities for all kinds of economic activities. However, international economic cooperation in the digital age also comes with a series of challenges. data privacy and security issues are more prominent, the digital divide persists, and regulatory and legal issues become more complex. The issues of fairness, fairness, efficiency and dialectical openness of digital platforms have become major issues that attract the attention of all countries. Therefore, in these turbulent times, we need innovative methods and indicators to assess and guide international economic cooperation to ensure that it leads to sustainable, beneficial, and balanced growth that benefits everyone around the world. © 2023 IEEE.

关键词： Economics

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Testing Neurofeedback System for Studying cognitive Tests 3

Testing Neurofeedback System for Studying Cognitive Tests

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3rd international conference on Communication, computing and Digital Systems, C-CODE 2023

作者： Ali, Rukhsar National University of Computer and Emerging Sciences Dept. of Electrical Engineering Karachi Pakistan

ISBN: (纸本)9798350332391

The ongoing advancement in the multidisciplinary fields of engineering, neuroscience, microelectronics, bioengineering, and neurophysiology have decreased the gap among human and machine intelligence. Numerous techniques and methods have been produced for examination and grouping of bio-signals (i.e., one or two dimensional) both in time and frequency domain. The combination of signal processing with the surgical recording devices fills in as primary tool for the improvement of different biomedical applications. The research area has been very active and is continually improvising to build an efficient human-machine framework. Electroencephalography (EEG) is non-invasive and professional method to record the activity of brain in terms of electrical minute pulses. The development of EEG in the biomedical applications help in identifying various other problems related to human brain such as tumors, seizures, Alzheimer's malady, epilepsy, and different failures of human brain. The fundamental goal of this study is to obtain and analyze EEG signals by using a single electrode provided by NeuroSky MindWave Mobile, that electrode is placed on the frontal lobe (more specifically forehead). The headset provides the raw EEG signal, and the distinctive parameters of EEG from different subjects in order to study the relationship, while accurately categorizing these values which are displayed on the provided Graphics User Interface (GUI). After obtaining the data of subjects' different techniques are used to study the cognitive function of individuals, and we have observed the improvement in attentions shown by subjects after the neurofeedback training. © 2023 IEEE.

关键词： Electroencephalography

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Analysis of Students Performance in Flipped Classroom-based Vocational Education Using data Mining Tools 11

Analysis of Students Performance in Flipped Classroom-based ...

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11th IEEE international conference on Intelligent computing and Information Systems, ICICIS 2023

作者： Kamal Eldeen, Yousra O. Abdelraheem, Mohamed Soliman, Taysir Hassan A. Misr International Technological University IT Department Egyptian-German College of Technology Assiut Egypt Assiut University Electrical Engineering Department Assiut Egypt Assiut University Faculty of Computers and Information Information Science Department Assiut Egypt

ISBN: (纸本)9798350322101

This research investigates the impact of applying a Flipped Classroom Approach (FCA) in Vocational Education and proposes an improved approach that integrates cognitive Theory of Multimedia Learning (CTML) with flipped learning based on Revised Bloom's taxonomy. Educational data mining (EDM) using statistics and data analysis was applied to transform large educational raw data into useful and meaningful information. This information can be applied to gain insights into students and their learning environments, enhance teaching support, and optimize decision-making in educational systems. EDM was performed on the student activities recorded on online learning management system (Moodle) including, pre-class activities, attendance, and after-class assignments. A correlation analysis was performed to explore the relationship between their activities in Moodle and academic performance. Results show that students who followed the flipped learning strategy outperformed those who did not, and the video designed according to CTML had a positive impact on student outcomes. The study also revealed that after-class assignments had a significant influence on students' results, and that the students' final results could be predicted through their assignment performance. © 2023 IEEE.

关键词： Students

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