Construction of adaptive particle swarm optimizers and optimization of parameters in switched dynamical systems

研究成果の概要 (和文) : 様々な問題に柔軟に適応できる粒子群最適化法(PSO)について考察し、3つの新しいPSOを提案した。(1)確定的な差分方程式に支配されるPSO。これは安定性解析や再現性のある動作制御に有利である。(2)粒子の動作を鈍感で接近粒子は衝突するPSO。これは複数解探索に有利である。(3)粒子間の結合にスイッチを導入したPSO。スイッチ頻度にを調節することにより、粒子間の疑似距離の制御や柔軟な粒子間の情報交換が可能である。また、パワーエレクトロニクスへの応用を検討し、スイッチング電源の制御信号最適化や、光電変換系の電源の最大電力点探索への応用の基礎となる成果を得た。研究成果の概要 (英文) : We have studied particle swarm optimizers(PSOs) with flexible adaptation function to various problems and have proposed three novel PSOs. (1) The PSO governed by a deterministic difference equation. It has advantages in analysis of stability and control of reproducible dynamics. (2) The PSO with insensitive particle movement and inter-near-particle collision. It is suitable for multi-solution problems. (3) The PSO with switched inter-particle connection. Adjusting the switching frequency, we can control inter-particle pseudo-distance and can realize flexible inter-particle communication. We have also studied applications to power electronics and have obtained basic results for applications to control signals optimization in switching power converters and to maximum power point search in photovoltaic systems

The state and illegality in Indonesia

The popular 1998 reformasi movement that brought down President Suharto’s regime demanded an end to illegal practices by state officials, from human rights abuse to nepotistic investments. Yet today, such practices have proven more resistant to reform than people had hoped. Many have said corruption in Indonesia is “entrenched”. We argue it is precisely this entrenched character that requires attention. What is state illegality entrenched in and how does it become entrenched? This involves The state and illegality in Indonesia studying actual cases. Our observations led us to rethink fundamental ideas about the nature of the state in Indonesia, especially regarding its socially embedded character. We conclude that illegal practices by state officials are not just aberrations to the state, they are the state. Almost invariably, illegality occurs as part of collective, patterned, organized and collaborative acts, linked to the competition for political power and access to state resources. While obviously excluding many without connections, corrupt behaviour also plays integrative and stabilizing functions. Especially at the lower end of the social ladder, it gets a lot of things done and is often considered legitimate. This book may be read as a defence of area studies approaches. Without the insights that grew from applying our area studies skills, we would still be constrained by highly stylised notions of the state, which bear little resemblance to the state’s actual workings. The struggle against corruption is a long-term political process. Instead of trying to depoliticize it, we believe the key to progress is greater popular participation. With contributions from Simon Butt, Robert Cribb, Howard Dick, Michele Ford, Jun Honna, Tim Lindsey, Lenore Lyons, John McCarthy, Ross McLeod, Marcus Mietzner, Jeremy Mulholland, Gerben Nooteboom, J Danang Widoyoko and Ian Wilson. This book is the result of a series of workshops supported, among others, by the Australian-Netherlands Research Collaboration (ANRC). “An intriguing [...] and thought-provoking volume on the nexus between the state and illegality. It treats illegality not as an abnormality, but as an integral aspect of statecraft and social life. The book advances theoretical discussions, embedding them in rich empirical material that sheds light on the ways in which people in different localities and sectors in Indonesia use, make sense of, and negotiate illegality. It will benefit students and scholars from various disciplines, seeking to explore the social meanings and functions of illegality in the everyday life of the nation.” Barak Kalir, University of Amsterda

Computational Optimizations for Machine Learning

The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity

Databook for human factors engineers. Volume 2 - Common formulas, metrics, definitions

Human factors engineering manual including mathematical formulas, nomographs, conversion tables, units of measurement, and nomenclature