Artificial Intelligence for Communications and Networks : 4th EAI International Conference, AICON 2022, Hiroshima, Japan, November 30 - December 1, 2022, Proceedings

This book, AICON 2022, constitutes the post-conference proceedings of the 4 th EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2022, held in Hiroshima, Japan, in November 30- December 1, 2022. The 9 full papers and 4 short papers were carefully reviewed and selected from 36 submissions. The papers detail research in the areas of AI and communication systems related to intelligent systems and computational intelligence for communication and networks. They are organized in topical sections on AI and networks; machine learning; and evolutionary computation. Preface Organization Contents AI and Networks Cost-Aware Node Ranking Algorithm for Embedding Virtual Networks in Internet of Vehicles 1 Introduction 2 Related Work 3 Network Model and Problem Description 3.1 Virtual Network Assignment 3.2 Performance Metrics 4 Proposed Solution 4.1 Pre-processing Stage 4.2 Vehicle Ranking 4.3 Intermediate Node Cost 4.4 VNE-IoV Algorithm 5 Performance Evaluation 5.1 Simulation Setup 5.2 Vehicle Mobility Model 5.3 Evaluation Results 6 Conclusion and Future Work References Fault Diameter of Strong Product Graph of Two Paths 1 Introduction 2 Main Results 3 Model Comparison 4 Conclusions References Design and Implementation of SF Selection Based on Distance and SNR Using Autonomous Distributed Reinforcement Learning in LoRa Networks 1 Introduction 2 System Model and Problem Formulation 3 SF Parameter Selection for ToW-Dynamics 3.1 Multi-armed Bandit Problem 3.2 ToW-Dynamics Based SF Selection 4 Implementation and Performance Evaluation 5 Conclusion References Machine Learning QBRT: Bias and Rising Threshold Algorithm with Q-Learning 1 Introduction 2 Related Studies 2.1 Prior Work on Environment Non-stationarity and Scalability Issues 2.2 BRT Algorithm 2.3 Best-of-n Problem 2.4 Q Learning 3 Proposed Method 3.1 QBRT 3.2 Behavior of Swarms Implementing QBRT 4 Experiments 4.1 Experimental Environment 4.2 Experiment at THM with p=3,d=3 4.3 Experiment at THM with p=3,d=5 5 Conclusion References A Study on Effectiveness of BERT Models and Task-Conditioned Reasoning Strategy for Medical Visual Question Answering 1 Introduction 2 Related Work 2.1 VQA-RAD Dataset 2.2 CMSA-MTPT Framework 2.3 Task-Condition Reasoning Strategy 3 Our Framework 3.1 Overview 3.2 BERT Models as the Language Understanding Module 3.3 Setting of the Task-Conditioned Strategy 4 Experiments 4.1 Training ResNet Models 4.2 CMSA-MTPT with BERT Models 4.3 Task-Conditioned Reasoning CMSA-MTPT with BERT Models 4.4 A Clue for Interpretability in BERT Models 5 Conclusion References Deep Robust Neural Networks Inspired by Human Cognitive Bias Against Transfer-based Attacks 1 Introduction 2 Related Work 2.1 Adversarial Examples 2.2 Transfer-Based Attacks 2.3 Defense Against Transfer-Based Attacks 3 Proposed Method 3.1 Loosely Symmetric Neural Networks 3.2 LS-DNN Development 4 Experiments and Discussion 4.1 Methods 4.2 Conditions 4.3 Results 5 Conclusion and Future Work References Efficient Estimation of Cow's Location Using Machine Learning Based on Sensor Data 1 Introduction 2 Related Works 3 Methods 3.1 Data Acquisition 3.2 Data Preprocessing 3.3 Machine Learning Model 4 Results and Discussion 5 Conclusions References A Time Series Forecasting Method Using DBN and Adam Optimization 1 Introduction 2 DBN for Time Series Forecasting 2.1 RBM and Its Learning Rule 2.2 MLP and Its Learning Rule 2.3 Meta Parameter Optimization 3 Experiments and Analysis 3.1 Benchmark CATS 3.2 Results and Analysis of CATS Forecasting 3.3 Chaotic Time Series Data 3.4 Results and Analysis of Chaotic Time Series Forecasting 4 Conclusions References Unity-Bounded Function and Benchmark Design Specifications Targeted for Designing Typical Variable Digital Filters 1 Introduction 2 Typical Benchmark Specifications 2.1 Variable Lowpass Design Specification 2.2 Variable Highpass Design Specification 2.3 Variable Bandpass Design Specification 2.4 Variable Bandstop Design Specification 2.5 Variable Notch-Frequency Design Specification 3 Unity-Bounded Function 4 An Illustrative Example 5 Conclusion References Evolutionary Computation Proposal and Evaluation of a Course-Classification-Support System Emphasizing Communication with the Sub-committees Within the Committee of Validation and Examination for Degrees 1 Introduction 2 Degree-Awarding of NIAD-QE and the Course-Classification-Support System 3 The Course-Classification-Support System Using the Deep Learning 3.1 Preparation of Training Data and Previous Methods 3.2 Relationship with Related Works and Our Approach 3.3 Proposed Method 4 Results and Discussion 5 Conclusions References A Research of Infectivity Rate of Seasonal Influenza from Pre-infectious Person for Data Driven Simulation 1 Introduction 2 Proposed SEPIR Model 3 Epidemic Situations 3.1 Situation A 3.2 Situation B 3.3 Situation C 4 Parameters 4.1 Infectivity Rate 4.2 The Number of Susceptible Students 5 Near Decomposability 5.1 Definition 5.2 Rough Estimation 6 Discussion 7 Conclusion References Creating Trust Within Population of Evolutionary Computation in an Uncertain Environment Using Blockchain 1 Introduction 2 Usecases of Blockchain in Evolutionary Computation 3 Trust in Evolutionary Computation with Blockchain 4 System Architecture 5 Conclusion References Efficient Inductive Logic Programming Based on Particle Swarm Optimization 1 Introduction 2 Progol 3 Particle Swarm Optimization 4 PSO Based Progol 5 Experiments 6 Conclusions and Future Work References Author Index