Author：Kek,Megan Yih Chyn A.;Huijser,Henk

Abstract:© Springer Science+Business Media Singapore 2017. In this book we respond to a higher education environment that is on the verge of profound changes by imagining an evolving and agile problem-based learning ecology for learning. The goal of doing so is to humanise university education by pursuing innovative approaches to student learning, teaching, curricula, assessment, and professional learning, and to employ interdisciplinary methods that go far beyond institutional walls and include student development and support, curriculum sustainability, research and the scholarship of teaching and learning, as well as administration and leadership. An agile problem-based learning (PBL) ecology for learning deliberately blurs the boundaries between disciplines, between students and teachers, between students and employers, between employers and teachers, between academics and professional staff, between formal and informal learning, and between teaching and research. It is based on the recognition that all of these elements are interconnected and constantly evolving, rather than being discrete and static. Throughout this book, our central argument is that there is no single person who is responsible for educating students. Rather, it is everyone’s responsibility - teachers, students, employers, administrators, and wider social networks, inside and outside of the university. Agile PBL is about making connections, rather than erecting barriers. In summary, this book is not about maintaining comfort zones, but rather about becoming comfortable with discomfort. The actual implementation is beyond the scope of this book and we envisage that changing perceptions towards this vision will itself be a mammoth task. However, we believe that the alternative of leaving things as they are would ultimately prove untenable, and more distressingly, would leave a generation of students afraid to think, feel, and act for themselves, let alone being able to face the challenges of the 21st century.

Author：Han,Jiawen

Author：Shi, Yuhui

Abstract:Throughout time, scientists have looked to nature in order to understand and model solutions for complex real-world problems. In particular, the study of self-organizing entities, such as social insect populations, presents a new opportunity within the field of artificial intelligence. Emerging Research on Swarm Intelligence and Algorithm Optimization discusses current research analyzing how the collective behavior of decentralized systems in the natural world can be applied to intelligent system design. Discussing the application of swarm principles, optimization techniques, and key algorithms being used in the field, this publication serves as an essential reference for academicians, upper-level students, IT developers, and IT theorists. © 2015 by IGI Global. All rights reserved.

Author：Wu,Keping

Author：Phiri,Michael;Chen,Bing

Abstract:This brief started by looking at the changing context for national and international healthcare systems, before reviewing the healthcare premises information, guidance and tools that underlie the approach in which sustainability is to be seen as integrated with evidence-based design rather than as divorced and separate themes. However, to understand the role these aspects play, it is also essential to consider both the historical context and, in particular, the organisational structures of the different healthcare systems whether these are national or international. This chapter discusses emerging issues from the approach that adopts design for sustainability integrated with evidence-based design. The aim is to help decision-making within the area of healthcare premises, planning and design whether this is nationally or globally. The crucial emerging issues start with the problem of definitions of ‘Evidence’ and ‘Sustainability’ but include the debates surrounding several themes: Centralisation versus Decentralisation, the nature of Public versus Private Sector Involvement, National versus International Standards to Prescription versus Performance Standards. Addressing these issues has an important bearing on the development of design for sustainability and evidence-based design as science.

Author：Tadjouddine,Emmanuel M.

Abstract:It is hoped agent mediated e-commerce will be carried out as open systems of agents interoperating between different institutions, where different auction protocols may be in use. The authors argue that in order to put such a scenario to work, agents will need a method to automatically verify the properties of a previously unseen auction protocol. This, in turn poses the problem of automatically verifying desirable properties in order to trust a given auction mechanism. This challenge needs be addressed so that the business scenario of agent mediated e-commerce becomes a reality. In this chapter, the authors discuss salient opportunities for SMEs in addressing the issues of enabling software agents (e.g., PDAs, mobile phones) to connect to auction houses and verify desirable properties that need to hold before engaging any transactions. © 2011, IGI Global.

Author：Fischer,Thomas;Herr,Christiane M.

Abstract:Since it ascended in the mid-twentieth century on the basis of technical and scientific advances made during World War II, cybernetics has influenced design theory and research. It was appreciated by its originators primarily as a theoretical framework and as a common language to bridge disciplinary boundaries, but soon found more prominent applications in goal-oriented control engineering. Since around 1970, it developed a reflective, more philosophical, and less control-focused perspective referred to as second-order cybernetics. This perspective recognises circular causality, non-determinism, the subjective observer and other concepts avoided by natural science. In this way, it offers an approach to self-organising systems that negotiate their own goals in open-ended processes – in other words: design. As an introduction to design cybernetics, this chapter outlines the development of cybernetics from a technical engineering discipline to a design-philosophical perspective.

Author：Zhang,Yan Ming;Huang,Kaizhu;Geng,Guang Gang;Liu,Cheng Lin

Abstract:Despite the great success of graph-based transductive learning methods, most of them have serious problems in scalability and robustness. In this chapter, we propose an efficient and robust graph-based transductive classification method, called minimum tree cut (MTC), which is suitable for large scale data. Motivated from the sparse representation of graph, we approximate a graph by a spanning tree. Exploiting the simple structure, we develop a linear-time algorithm to label the tree such that the cut size of the tree is minimized. This significantly improves graph-based methods, which typically have a polynomial time complexity. Moreover, we theoretically and empirically show that the performance of MTC is robust to the graph construction, overcoming another big problem of traditional graph-based methods. Extensive experiments on public data sets and applications on text extraction fromimages demonstrate our method’s advantages in aspect of accuracy, speed, and robustness.

Author：Verdini,Giulio;Bina,Olivia;Chiles,Prue;Guerrieri,Pilar Maria;Mace,Alan;Nolf,Christian;Occhialini,Etra Connie;Pola,Anna Paola;Raffa,Paola

Abstract:This chapter intends to be both scientifically sound and narratively engaging, given the richness of the work done in Gagliato as experienced by the authors. As a matter of fact, besides the research done remotely, the authors gathered in Gagliato in July 2017 for a one-week participatory design workshop, getting to know the local context, talking with local people, materialising the focus groups implemented on site in future visions of sustainable development. Gagliato is a hilly town located in the province of Catanzaro in Calabria, overlooking the Ionian Sea. The chapter introduces a theoretical section regarding current debates on transdisciplinary research and the reason why Gagliato has been considered a suitable case to test it. The enabling conditions and potential barriers to achieve meaningful transdisciplinary outcomes and consequently tangible positive urban transformation of the experience of Gagliato will be discussed in relationship to the various phases of the project.

Author：Zhong,Sheng

Abstract:The chapter problematizes the nature of ‘culture’-led urban regeneration practices in Shanghai by differentiating between the intentions of regenerative efforts and the real outcomes of policy initiatives. Based on the case study of Shanghai Sculpture Space, the chapter reveals that Shanghai’s so-called ‘culture’- led urban regeneration program implemented through public-private partnership was actually propertyled. The biggest beneficiaries of the process were landed interests. The heavy involvement of the local state and government-linked institutions, however, did not result in the honoring of community sociocultural needs that a genuine culture-led urban regeneration project would require.

Author：Yang,Xin She;Chien,Su Fong;Ting,Tiew On

Abstract:All design problems in telecommunications can be formulated as optimization problems, and thus may be tackled by some optimization techniques. However, these problems can be extremely challenging due to the stringent time requirements, complex constraints, and a high number of design parameters. Solution methods tend to use conventional methods such as Lagrangian duality and fractional programming in combination with numerical solvers, while new trends tend to use evolutionary algorithms and swarm intelligence. This chapter provides a summary review of the bio-inspired optimization algorithms and their applications in telecommunications. We also discuss key issues in optimization and some active topics for further research.

Author：Nong,Jin;Chen,Yang

Abstract:This chapter aims at using an innovative method developed by Blouin et al. (Improved estimates of marginal tax rates: why they are needed, approach, and implications. Memo, 2008) to simulate 1041 China’s listed companies’ corporate marginal tax rate, and comparing the changes in marginal tax rate in the context of 2007 tax reform in China. After simulation and comparison, we find that the annual corporate marginal tax rate has greatly decreased after the new tax policy goes into effect. Besides, the tax effects on marginal tax rates vary with industry and across ownership.

Author：Kiddle,Rebecca;Kim,Joon Sik;Chen,Bing

Abstract:© 2016 Giulio Verdini, Yiwen Wang, Xiaonan Zhang and the contributors. To safeguard the overall quality of the development of urban and rural areas, as increasingly addressed in China’s strategic policy documents, there is an urgent need to provide a new vision for planning education, nurturing an interdisciplinary learning environment that can promote critical thinking as a basis for action or intervention. The urban and rural nexus highlights an area of particular tension as it works to house existing villagers alongside the rising middle classes keen for a more suburban/rural aspect (see Sturzacker and Law in this volume). This challenges planners to think beyond the scope of statutory systems and consider planning as an activity that professionals facilitate, rather than own or monopolize. The planning education system should, therefore, equip prospective planners with not only professional knowledge, but the capability to involve a range of stakeholders in more genuinely collaborative ways. On the urban fringe where very diverse social groups and needs meet, this ability to involve the range of stakeholders in decision-making processes is all the more important.

Author：Fang, Lei ; Guan, Sheng-Uei ; Zhang, Haofan

Abstract:Rule-based Genetic Algorithms (GAs) have been used in the application of pattern classification (Corcoran & Sen, 1994), but conventional GAs have weaknesses. First, the time spent on learning is long. Moreover, the classification accuracy achieved by a GA is not satisfactory. These drawbacks are due to existing undesirable features embedded in conventional GAs. The number of rules within the chromosome of a GA classifier is usually set and fixed before training and is not problem-dependent. Secondly, conventional approaches train the data in batch without considering whether decomposition solves the problem. Thirdly, when facing large-scale real-world problems, GAs cannot utilise resources efficiently, leading to premature convergence. Based on these observations, this paper develops a novel algorithmic framework that features automatic domain and task decomposition and problem-dependent chromosome length (rule number) selection to resolve these undesirable features. The proposed Recursive Learning of Genetic Algorithm with Task Decomposition and Varied Rule Set (RLGA) method is recursive and trains and evolves a team of learners using the concept of local fitness to decompose the original problem into sub-problems. RLGA performs better than GAs and other related solutions regarding training duration and generalization accuracy according to the experimental results. © 2013 by IGI Global. All rights reserved.

Author：Cheng, Shi ; Shi, Yuhui ; Qin, Quande

Abstract:Premature convergence occurs in swarm intelligence algorithms searching for optima. A swarm intelligence algorithm has two kinds of abilities exploration of new possibilities and exploitation of old certainties. The exploration ability means that an algorithm can explore more search places to increase the possibility that the algorithm can find good enough solutions. In contrast, the exploitation ability means that an algorithm focuses on the refinement of found promising areas. An algorithm should have a balance between exploration and exploitation, that is, the allocation of computational resources should be optimized to ensure that an algorithm can find good enough solutions effectively. The diversity measures the distribution of individuals' information. From the observation of the distribution and diversity change, the degree of exploration and exploitation can be obtained. Another issue in multiobjective is the solution metric. Pareto domination is utilized to compare two solutions; however, solutions are almost Pareto non-dominated for multiobjective problems with more than ten objectives. In this chapter, the authors analyze the population diversity of a particle swarm optimizer for solving both single objective and multiobjective problems. The population diversity of solutions is used to measure the goodness of a set of solutions. This metric may guide the search in problems with numerous objectives. Adaptive optimization algorithms can be designed through controlling the balance between exploration and exploitation. © 2015 by IGI Global. All rights reserved.

Author：Li,Peter Ping

Abstract:Most Eastern traditional philosophies, such as Taoism, from China, share a set of core themes that constitute a philosophy of wisdom (science-art integration), in contrast to Western philosophies with a focus on knowledge (science-art separation). This chapter argues that the epistemological system of yin-yang balancing is the root of Eastern culture traditions. Building on this theme, the chapter elaborates on the unique features of yin-yang balancing, in contrast to Aristotle's formal logic and Hegel's dialectics in the West. It is posited that yin-yang balancing is more sophisticated (rather than naïve) than all dialectical logic for paradox management, since it is the only system that can truly accommodate and appreciate paradox and has the potential to absorb all Western systems into a geocentric (East-meets-West) meta-system. The chapter concludes with an application of yin-yang balancing to the geocentric integration of the Eastern philosophy of wisdom with the Western philosophy of knowledge, toward a new geocentric meta-paradigm.

Author：Yang,Xin She;Chien,Su Fong;Ting,Tiew On

Abstract:Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and application as they relate to telecommunications and image processing, providing a complete resource that analyzes and discusses the latest and future trends in research directions. Written by recognized experts, this is a must-have guide for researchers, telecommunication engineers, computer scientists and PhD students.

Author：Harris,Geoffrey

Author：Westermann, Claudia

Abstract:The chapter considers second-order cybernetics as a framework that is accurately described as a poetics. An overview is provided on what it means to be in a world that is uncertain, e.g., how under conditions of limited understanding any activity is an activity that designs and constructs, and how designing objects, spaces, and situations relates to the (designed) meta-world of second-order cybernetics. If it cannot be determined whether the world is complex or not, to assume that the world is complex is a matter of choice linked to an attitude of generosity. The chapter highlights that it is this attitude, which makes designing an ethical challenge. Designers require a framework that is open, but one that supplies ethical guidance when ‘constructing’ something new. Relating second-order design thinking to insights in philosophy and aesthetics, the chapter argues that second-order cybernetics provides a response to this ethical challenge and essentially it entails a poetics of designing.

Author：Zhong,Guoqiang;Huang,Kaizhu

Abstract:Semi-supervised learning is an important area of machine learning. It deals with problems that involve a lot of unlabeled data and very scarce labeled data. The book focuses on state-of-the-art research on semi-supervised learning. In the first chapter, Weng, Dornaika and Jin introduce a graph construction algorithm named the constrained data self-representative graph construction (CSRGC). In the second chapter, to reduce the graph construction complexity, Zhang et al. use anchors that were a special subset chosen from the original data to construct the full graph, while randomness was injected into graphs to improve the classification accuracy and deal with the high dimensionality issue. In the third chapter, Dornaika et al. introduce a kernel version of the Flexible Manifold Embedding (KFME) algorithm. In the fourth chapter, Zhang et al. present an efficient and robust graph-based transductive classification method known as the minimum tree cut (MTC), for large scale applications. In the fifth chapter, Salazar, Safont and Vergara investigated the performance of semi-supervised learning methods in two-class classification problems with a scarce population of one of the classes. In the sixth chapter, by breaking the sample identically and independently distributed (i.i.d.) assumption, one novel framework called the field support vector machine (F-SVM) with both classification (F-SVC) and regression (F-SVR) purposes is introduced. In the seventh chapter, Gong employs the curriculum learning methodology by investigating the difficulty of classifying every unlabeled example. As a result, an optimized classification sequence was generated during the iterative propagations, and the unlabeled examples are logically classified from simple to difficult. In the eighth chapter, Tang combines semi-supervised learning with geo-tagged photo streams and concept detection to explore situation recognition. This book is suitable for university students (undergraduate or graduate) in computer science, statistics, electrical engineering, and anyone else who would potentially use machine learning algorithms; professors, who research artificial intelligence, pattern recognition, machine learning, data mining and related fields; and engineers, who apply machine learning models into their products.