A study of Beethoven’s Symphony No.5 c-minor Op.67 (Fate)\nused as standard teaching material in a junior high school music class

As part of junior high school music education in Japan, both standard singing teaching materials and standard listening teaching materials have been assigned according to successive Department of Education directives (1958, 1969, 1977, and 1989). However, these were not specified for the 1998 directive on teaching guidelines. For the 2008 guidelines, seven compositions by Japanese composers remain, but directives regarding standard listening teaching materials were not included. Among the previous directives (1977, 1989) Beethoven’s Symphony No.5 c-minor Op.67 (named ‘Fate’ in Japan) was assigned as part of the curriculum for both second grade students. This paper will attempt to examine the adequacy of descriptions of this Beethoven’s symphony in three textbooks assigned as part of music education in Japan

Supply network science: Emergence of a new perspective on a classical field.

Supply networks emerge as companies procure goods from one another to produce their own products. Due to a chronic lack of data, studies on these emergent structures have long focussed on local neighbourhoods, assuming simple, chain-like structures. However, studies conducted since 2001 have shown that supply chains are indeed complex networks that exhibit similar organisational patterns to other network types. In this paper, we present a critical review of theoretical and model based studies which conceptualise supply chains from a network science perspective, showing that empirical data do not always support theoretical models that were developed, and argue that different industrial settings may present different characteristics. Consequently, a need that arises is the development and reconciliation of interpretation across different supply network layers such as contractual relations, material flow, financial links, and co-patenting, as these different projections tend to remain in disciplinary siloes. Other gaps include a lack of null models that show whether the observed properties are meaningful, a lack of dynamical models that can inform how layers evolve and adopt to changes, and a lack of studies that investigate how local decisions enable emergent outcomes. We conclude by asking the network science community to help bridge these gaps by engaging with this important area of research

Human dynamics in the age of big data: a theory-data-driven approach

The revolution of information and communication technology (ICT) in the past two decades have transformed the world and people’s lives with the ways that knowledge is produced. With the advancements in location-aware technologies, a large volume of data so-called “big data” is now available through various sources to explore the world. This dissertation examines the potential use of such data in understanding human dynamics by focusing on both theory- and data-driven approaches. Specifically, human dynamics represented by communication and activities is linked to geographic concepts of space and place through social media data to set a research platform for effective use of social media as an information system. Three case studies covering these conceptual linkages are presented to (1) identify communication patterns on social media; (2) identify spatial patterns of activities in urban areas and detect events; and (3) explore urban mobility patterns. The first case study examines the use of and communication dynamics on Twitter during Hurricane Sandy utilizing survey and data analytics techniques. Twitter was identified as a valuable source of disaster-related information. Additionally, the results shed lights on the most significant information that can be derived from Twitter during disasters and the need for establishing bi-directional communications during such events to achieve an effective communication. The second case study examines the potential of Twitter in identifying activities and events and exploring movements during Hurricane Sandy utilizing both time-geographic information and qualitative social media text data. The study provides insights for enhancing situational awareness during natural disasters. The third case study examines the potential of Twitter in modeling commuting trip distribution in New York City. By integrating both traditional and social media data and utilizing machine learning techniques, the study identified Twitter as a valuable source for transportation modeling. Despite the limitations of social media such as the accuracy issue, there is tremendous opportunity for geographers to enrich their understanding of human dynamics in the world. However, we will need new research frameworks, which integrate geographic concepts with information systems theories to theorize the process. Furthermore, integrating various data sources is the key to future research and will need new computational approaches. Addressing these computational challenges, therefore, will be a crucial step to extend the frontier of big data knowledge from a geographic perspective. KEYWORDS: Big data, social media, Twitter, human dynamics, VGI, natural disasters, Hurricane Sandy, transportation modeling, machine learning, situational awareness, NYC, GI

IRGC Resource Guide on Resilience (Volume 2)

Volume 2 of the IRGC Resource Guide on Resilience provides an in-depth and pragmatic evaluation of concepts and methods for resilience-based approaches in contrast to risk-based approaches, as proposed and practised in different domains of science and practice. Adequate articulation of risk and resilience is key to ensure security in systems. The guide also considers possible drawbacks of resilience, such as if efforts to improve resilience diverts attention from core functions of risk management, or from the need to discourage inappropriate risk-seeking behaviour. Some of the papers in Volume 2 also discuss the relevance and role of resilience as a strategy to address the challenges posed by systemic risks that develop in complex adaptive systems (CAS). Such systems are interconnected, with the result that risks can cascade within and between systems. Resilience can help navigate dynamic changes in CAS, as those evolve in response to internal and external shocks and stresses