We analyze the betweenness centrality (BC) of nodes in large complex networks. In general, the BC is increasing with connectivity as a power law with an exponent $\eta$. We find that for trees or networks with a small loop density $\eta=2$ while a larger density of loops leads to $\eta<2$. For scale-free networks characterized by an exponent $\gamma$ which describes the connectivity distribution decay, the BC is also distributed according to a power law with a non universal exponent $\delta$. We show that this exponent $\delta$ must satisfy the exact bound $\delta\geq (\gamma+1)/2$. If the scale free network is a tree, then we have the equality $\delta=(\gamma+1)/2$.

Betweenness Centrality in Large Complex Networks

This thesis proposes an alternate paradigm for designing computers using continuoustime analog circuits. Digital computation sacrifices continuous degrees of freedom. A principled approach to recovering them is to view analog circuits as propagating probabilities in a message passing algorithm. Within this framework, analog continuous-time circuits can perform robust, programmable, high-speed, low-power, cost-effective, statistical signal processing. This methodology will have broad application to systems which can benefit from low-power, high-speed signal processing and offers the possibility of adaptable/programmable high-speed circuitry at frequencies where digital circuitry would be cost and power prohibitive. Many problems must be solved before the new design methodology can be shown to be useful in practice: Continuous-time signal processing is not well understood. Analog computational circuits known as “soft-gates” have been previously proposed, but a complementary set of analog memory circuits is still lacking. Analog circuits are usually tunable, rarely reconfigurable, but never programmable. The thesis develops an understanding of the convergence and synchronization of statistical signal processing algorithms in continuous time, and explores the use of linear and nonlinear circuits for analog memory. An exemplary embodiment called the Noise Lock Loop (NLL) using these design primitives is demonstrated to perform direct-sequence spread-spectrum acquisition and tracking functionality and promises order-of-magnitude wins over digital implementations. A building block for the construction of programmable analog gate arrays, the “soft-multiplexer” is also proposed. Thesis Supervisor: Neil Gershenfeld Title: Associate Professor

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Statistical Signal Processing

The tremendous growth in electronic data of universities creates the need to have some meaningful information extracted from these large volumes of data The advancement in the data mining field makes it possible to mine educational data in order to improve the quality of the educational processes This study, thus, uses data mining methods to study the performance of undergraduate students Two aspects of students' performance have been focused upon First, predicting students' academic achievement at the end of a four-year study programme Second, studying typical progressions and combining them with prediction results Two important groups of students have been identified: the low and high achieving students The results indicate that by focusing on a small number of courses that are indicators of particularly good or poor performance, it is possible to provide timely warning and support to low achieving students, and advice and opportunities to high performing students

Analyzing undergraduate students\' performance using educational data mining

The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and, indirectly, by raising new theoretical questions. Deferred acceptance algorithms are at the basis of a number of labor market clearinghouses around the world, and have recently been implemented in school choice systems in Boston and New York City. In addition, the study of markets that have failed in ways that can be fixed with centralized mechanisms has led to a deeper understanding of some of the tasks a marketplace needs to accomplish to perform well. In particular, marketplaces work well when they provide thickness to the market, help it deal with the congestion that thickness can bring, and make it safe for participants to act effectively on their preferences. Centralized clearinghouses organized around the deferred acceptance algorithm can have these properties, and this has sometimes allowed failed markets to be reorganized.

Deferred Acceptance Algorithms: History, Theory, Practice, and Open Questions

The impact of heavy traffic on forest soils: A review

Swiss Federal Institute of Technology (ETH)

Rural transportation networks are highly susceptible to geohazards such as earthquakes and landslides. Indirect losses can be severe because the breakdown of a transportation network aggravates rescue, supply, and other recovery activities. The operations and logistics of rural networks that are under seismic risks must be managed using the limited resources specifically in developing countries. We propose a methodology to evaluate road recovery strategies for restoring connectivity after blockages due to earthquakes and earthquake-triggered landslides. This paper gives insight into the recovery process, which can be used by decision-makers for enhancing resilience and supplying immediate relief to rural areas. The proposed framework has four steps: 1) identification of strategies for increasing recovery performance, 2) determination of graph-based metrics to represent network connectivity, 3) applying topology-based and Monte Carlo simulations to each strategy, and 4) analysis of recovery times to compare these resilience-enhancement strategies. The methodology was tested using a case study from Sindhupalchok District, Nepal, a region that was severely affected by the Gorkha earthquake in 2015. The closed road segments and recovery times were determined through field surveys with locals and governmental authorities, and by investigating the intensity of earthquake-triggered landslides. Our results showed that the proposed approach provides information about the recovery behavior of road networks and simplifies the evaluation process. It is robust enough to extend and assess decision-makers’ preferences for improving resilience.

https://publikationen.bibliothek.kit.edu/1000085592/16835876

Framework for improving the resilience and recovery of transportation networks under geohazard risks

Rapid urbanisation worldwide has created a host of fundamental challenges, which in conjunction with natural or man-made disasters, now threaten the resilience of communities, cities, and mega-cities. Consider the first challenge of climate change which has undermined the fundamental assumptions used to design the engineered systems that currently define the critical functionalities of cities today, and for tomorrow will demand innovative paradigms and new assumptions for designing resilient cities of the future. Another challenge concerns the damages directly or indirectly associated with natural and man-made disasters. These damages are expected to escalate as long as the value at risk continues to increase. And then there is the challenge of surging connectivity within and between critical infrastructure systems which has left such systems interdependent and vulnerable to cascading failures and regime shifts which foment ill-defined changes in system functionality. Changes that include but are not limited to emergent disruptions of critical services, system damages and even system-wide failures. The purpose of this chapter is to propose a framework for understanding and assessing critical infrastructure system resilience, to introduce a vision of resilient governance, and to propose a framework for harnessing knowledge transfer and continuous learning as required of policymakers seeking to elucidate and promote best practices that shape desired behaviour from individuals, social systems, stakeholders and communities.

Infrastructure Resilience Assessment, Management and Governance – State and Perspectives

Transportation networks daily provide accessibility and crucial services to societies. However, they must also maintain an acceptable level of service to critical infrastructures in the case of disruptions, especially during natural disasters. We have developed a method for assessing the resilience of transportation network topology when exposed to environmental hazards. This approach integrates graph theory with stress testing methodology and involves five basic steps: (1) establishment of a scenario set that covers a range of seismic damage potential in the network, (2) assessment of resilience using various graph-based metrics, (3) topology-based simulations, (4) evaluation of changes in graph-based metrics, and (5) examination of resilience in terms of spatial distribution of critical nodes and the entire network topology. Our case study was from the city of Kathmandu in Nepal, where the earthquake on April 25, 2015, followed by a major aftershock on May 12, 2015, led to numerous casualties and caused significant damage. Therefore, it is a good example for demonstrating and validating the developed methodology. The results presented here indicate that the proposed approach is quite efficient and accurate in assisting stakeholders when evaluating the resilience of transportation networks based on their topology.

Integration of stress testing with graph theory to assess the resilience of urban road networks under seismic hazards

Nacrtak The forest operations engineering and management community has been facing the problem of improving its scientific visibility, realigning its research efforts to the future challenges, and of strengthening its self-confidence. The paper aims at exploring the paradigms that shaped the development of forest operations as a scientific discipline, sketching a vision how forest operations could look like in 2020, establishing a common understanding for future of the discipline, and discussing the major challenges ahead. The investigation identified five periods of steady state development (paradigms) and developed a vision of network-based forest operations systems, built of »self-organizing« cells. It then discusses the challenges that we will probably been faced with in the fields of »harvesting and transportation engineering«, »forest operations management«, »forest ergonomics«, and »forest operations ecology«. The study intended to trigger a broad discussion on the future directions of forest operations engineering and management, and to build a basis for a redesign of cor- responding curricula in higher education.

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Hans Rudolf Heinimann

Papers

Swiss Federal Institute of Technology (ETH)

Framework for improving the resilience and recovery of transportation networks under geohazard risks

Infrastructure Resilience Assessment, Management and Governance – State and Perspectives

Integration of stress testing with graph theory to assess the resilience of urban road networks under seismic hazards

Forest operations engineering and management – the ways behind and ahead of a scientific discipline