다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Preface 1. Decision-Theoretic Foundations 1.1 Game Theory, Rationality, and Intelligence 1.2 Basic Concepts of Decision Theory 1.3 Axioms 1.4 The Expected-Utility Maximization Theorem 1.5 Equivalent Representations 1.6 Bayesian Conditional-Probability Systems 1.7 Limitations of the Bayesian Model 1.8 Domination 1.9 Proofs of the Domination Theorems Exercises 2. Basic Models 2.1 Games in Extensive Form 2.2 Strategic Form and the Normal Representation 2.3 Equivalence of Strategic-Form Games 2.4 Reduced Normal Representations 2.5 Elimination of Dominated Strategies 2.6 Multiagent Representations 2.7 Common Knowledge 2.8 Bayesian Games 2.9 Modeling Games with Incomplete Information Exercises 3. Equilibria of Strategic-Form Games 3.1 Domination and Ratonalizability 3.2 Nash Equilibrium 3.3 Computing Nash Equilibria 3.4 Significance of Nash Equilibria 3.5 The Focal-Point Effect 3.6 The Decision-Analytic Approach to Games 3.7 Evolution. Resistance. and Risk Dominance 3.8 Two-Person Zero-Sum Games 3.9 Bayesian Equilibria 3.10 Purification of Randomized Strategies in Equilibria 3.11 Auctions 3.12 Proof of Existence of Equilibrium 3.13 Infinite Strategy Sets Exercises 4. Sequential Equilibria of Extensive-Form Games 4.1 Mixed Strategies and Behavioral Strategies 4.2 Equilibria in Behavioral Strategies 4.3 Sequential Rationality at Information States with Positive Probability 4.4 Consistent Beliefs and Sequential Rationality at All Information States 4.5 Computing Sequential Equilibria 4.6 Subgame-Perfect Equilibria 4.7 Games with Perfect Information 4.8 Adding Chance Events with Small Probability 4.9 Forward Induction 4.10 Voting and Binary Agendas 4.11 Technical Proofs Exercises 5. Refinements of Equilibrium in Strategic Form 5.1 Introduction 5.2 Perfect Equilibria 5.3 Existence of Perfect and Sequential Equilibria 5.4 Proper Equilibria 5.5 Persistent Equilibria 5.6 Stable Sets 01 Equilibria 5.7 Generic Properties 5.8 Conclusions Exercises 6. Games with Communication 6.1 Contracts and Correlated Strategies 6.2 Correlated Equilibria 6.3 Bayesian Games with Communication 6.4 Bayesian Collective-Choice Problems and Bayesian Bargaining Problems 6.5 Trading Problems with Linear Utility 6.6 General Participation Constraints for Bayesian Games with Contracts 6.7 Sender-Receiver Games 6.8 Acceptable and Predominant Correlated Equilibria 6.9 Communication in Extensive-Form and Multistage Games Exercises Bibliographic Note 7. Repeated Games 7.1 The Repeated Prisoners Dilemma 7.2 A General Model of Repeated Garnet 7.3 Stationary Equilibria of Repeated Games with Complete State Information and Discounting 7.4 Repeated Games with Standard Information: Examples 7.5 General Feasibility Theorems for Standard Repeated Games 7.6 Finitely Repeated Games and the Role of Initial Doubt 7.7 Imperfect Observability of Moves 7.8 Repeated Wines in Large Decentralized Groups 7.9 Repeated Games with Incomplete Information 7.10 Continuous Time 7.11 Evolutionary Simulation of Repeated Games Exercises 8. Bargaining and Cooperation in Two-Person Games 8.1 Noncooperative Foundations of Cooperative Game Theory 8.2 Two-Person Bargaining Problems and the Nash Bargaining Solution 8.3 Interpersonal Comparisons of Weighted Utility 8.4 Transferable Utility 8.5 Rational Threats 8.6 Other Bargaining Solutions 8.7 An Alternating-Offer Bargaining Game 8.8 An Alternating-Offer Game with Incomplete Information 8.9 A Discrete Alternating-Offer Game 8.10 Renegotiation Exercises 9. Coalitions in Cooperative Games 9.1 Introduction to Coalitional Analysis 9.2 Characteristic Functions with Transferable Utility 9.3 The Core 9.4 The Shapkey Value 9.5 Values with Cooperation Structures 9.6 Other Solution Concepts 9.7 Colational Games with Nontransferable Utility 9.8 Cores without Transferable Utility 9.9 Values without Transferable Utility Exercises Bibliographic Note 10. Cooperation under Uncertainty 10.1 Introduction 10.2 Concepts of Efficiency 10.3 An Example 10.4 Ex Post Inefficiency and Subsequent Oilers 10.5 Computing Incentive-Efficient Mechanisms 10.6 Inscrutability and Durability 10.7 Mechanism Selection by an Informed Principal 10.8 Neutral Bargaining Solutions 10.9 Dynamic Matching Processes with Incomplete Information Exercises Bibliography Index

博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict

Data mining and analytics have played an important role in knowledge discovery and decision making/supports in the process industry over the past several decades. As a computational engine to data mining and analytics, machine learning serves as basic tools for information extraction, data pattern recognition and predictions. From the perspective of machine learning, this paper provides a review on existing data mining and analytics applications in the process industry over the past several decades. The state-of-the-art of data mining and analytics are reviewed through eight unsupervised learning and ten supervised learning algorithms, as well as the application status of semi-supervised learning algorithms. Several perspectives are highlighted and discussed for future researches on data mining and analytics in the process industry.

Data Mining and Analytics in the Process Industry: The Role of Machine Learning

Accurate health estimation and lifetime prediction of lithium-ion batteries are crucial for durable electric vehicles. Early detection of inadequate performance facilitates timely maintenance of battery systems. This reduces operational costs and prevents accidents and malfunctions. Recent advancements in “Big Data” analytics and related statistical/computational tools raised interest in data-driven battery health estimation. Here, we will review these in view of their feasibility and cost-effectiveness in dealing with battery health in real-world applications. We categorise these methods according to their underlying models/algorithms and discuss their advantages and limitations. In the final section we focus on challenges of real-time battery health management and discuss potential next-generation techniques. We are confident that this review will inform commercial technology choices and academic research agendas alike, thus boosting progress in data-driven battery health estimation and prediction on all technology readiness levels.

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Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review

In a typical Satellite-integrated Internet of Things (SIoT), the limited transmission rate of a sensor causes a stale in data freshness due to unavoidable time waiting for transmission. Moreover, due to the high bit error rate (BER) of the satellite-to-ground link, data freshness will be further exacerbated by frequent retransmissions. Generally, this issue is partially solved using a powerful compression scheme that can reduce the data volume. However, conventional compression schemes will necessitate a significant amount of time to accumulate constant data to a certain quantity, posing a difficult challenge. Therefore, this study proposes an age-optimal hybrid temporal-spatial generalized deduplication and automatic repeat request (HARQ-GD) protocol for the high-sampling data collection in SIoT, considering data compression, and transmission collaboratively. A novel Age of Information (AoI) metric is developed for timeliness evaluation over a two-hop end-to-end link of SIoT, which is optimized to design the proposed HARQ-GD protocol by considering the temporal and spatial correlations of sampled data with specific encoding/decoding algorithms and packet formats. The simulation results indicate that the proposed HARQ-GD protocol performs better performance than typical generalized deduplication (GD) and hybrid automatic repeat request with chase combing (HARQ-CC) schemes in reducing AoI, because of its fewer transmission times and higher compression rate.

Age-Optimal Hybrid Temporal-Spatial Generalized Deduplication and ARQ for Satellite-Integrated Internet of Things

The injection stretch blow moulding (ISBM) process is widely used to manufacture plastic bottles for the beverage and consumer goods industry. The majority of the production processes are open-loop systems, often suffering from high raw material and energy waste. In this paper, a heuristic based norm-optimal terminal iterative learning control (ILC) method is proposed to control the preform temperature profiles in the reheating process. The reheating process is a batch process, and ILC can achieve improved tracking performance in a fixed time interval. The terminal ILC (TILC) is a useful strategy when only the terminal temperature profile can be measured in a batch process like the preform reheating in ISBM. To balance the control performance and energy cost, a norm-optimal method is applied, leading to a proposal of the new norm-optimal TILC method in this paper. Heuristic methods including the swarm optimisation (PSO), differential evolution (DE) and teaching-learning based optimization (TLBO) are used to calculate the sequence of norm-optimal control inputs for this non-linear batch process. Simulation results confirm the efficacy of the proposed control strategy.

Heuristic Based Terminal Iterative Learning Control of ISBM Reheating Processes

Multi-system genetic algorithm for complex system optimization

Low orbit satellite constellation as a relay network provides a possible solution for remote real-time data gathering applications, in which freshness information updates will be forwarded via dynamical intersatellite links (ISLs). Modeling by a time-varying network, this article studies minimizing Age of Information (AoI) of delivering the data through a multihop path, in particular, focusing on the effect of frequent interruptions of ISLs. Subjected to two constraints of path and effective arrival rate, the minimizing AoI problem is formulated to find a pair of optimal transmission delay and arrival rate. In particular, the $\mathcal {H}$ -approximate optimal algorithm, called a latest update routing (LUR) algorithm, is proposed with a well-designed continuous time-varying graph. Using LUR, a set of paths can be obtained with degraded transmission delay that satisfies a given arrival rate. By screening all the arrival rates satisfying the effective constraint, the maximum rate and a corresponding path set that minimizes age can be found. The simulation results verified that a degraded average AoI can be obtained by the proposed path selection mechanism compared with the typical shortest delay path (SDP) strategy, minimum spanning tree (MST) strategy, and MAoIG. In particular, the numerical findings show that the proposed LUR reduces average AoI by a maximum of 12.66% compared with SDP, 75.28% compared with MST, and 69.3% compared with MAoIG, respectively, under different scenarios.

Age-Optimized Multihop Information Update Mechanism on the LEO Satellite Constellation via Continuous Time-Varying Graphs

In this paper, unit commitment and the scheduling problem of plug-in electric vehicles (PEV) under the condition of power grid feedback are jointly considered, formulating a many objective problem. The objectives involve economic and environmental impact, carbon emission as well as the user satisfaction. To solve this multi-objective problem, an improved MOEA/D algorithm is proposed where levy flight is integrated to improve the algorithm performance. The improved MOEA/D algorithm, NSGA-II algorithm and the traditional MOEA/D algorithm are compared. The experimental results show that the improved MOEA/D algorithm is comprehensive optimal in the multi-objective function, which shows the effectiveness of the improved algorithm. Moreover, the four objectives are comprehensively considered to balance the multiple factors in the application.

Zhile Yang

Papers

Age-Optimal Hybrid Temporal-Spatial Generalized Deduplication and ARQ for Satellite-Integrated Internet of Things

Heuristic Based Terminal Iterative Learning Control of ISBM Reheating Processes

Multi-system genetic algorithm for complex system optimization

Age-Optimized Multihop Information Update Mechanism on the LEO Satellite Constellation via Continuous Time-Varying Graphs

Multi-objective Optimization of Electric Vehicle and Unit Commitment Considering Users Satisfaction: An Improved MOEA/D Algorithm