On technology emergence and pattern detection in aggregate innovative activity

Theories of General Purpose Technologies (GPT) introduced heterogeneity in the world of technological change in order to explain fluctuations in economic growth, productivity paradoxes, or technological clusters. The first part of this thesis addresses in detail a GPT\u27s emergence, presenting a new theoretical model that focuses on pervasiveness character of a GPT emphasizing knowledge network characteristics. Each new product in the economy is a result of a combination of technologies forming a complex network structure of technological inter-dependencies, where a general knowledge emerges as a result of knowledge spillovers, coordination of innovative efforts among economic agents, dynamics of expected profits, and the structure of knowledge base. The model demonstrates similar network characteristics when compared to empirical networks of products and technologies as well as explains clustering of innovations in time, change of technological paradigms and mechanism leading to a technological lock-in. It is argued that robotics and especially new developments in service robotics can be considered as a potential GPT. Employing a machine learning technique, namely Support Vector Machine, the second part of this thesis introduces a methodology for identification of service robotics patents within databases. The result is a novel possibility to allocate patents which reduces expert bias regarding vested interests on lexical query methods, avoids problems with citational approaches, and facilitates evolutionary changes. Resulting patents are geographically localized and analyzed, being a proxy for knowledge production in service robotics. The last part of the thesis focuses on a general detection of emergent patterns in micro data. Firstly, a method for statistical identification of clusters of innovative activity is applied to service robotics patents and all German R&D data. A micro-geographic approach identifies spatial localization or dispersion by comparing observable spatial distance patterns between R&D establishments to counter-factual simulations. Findings demonstrate the localization of the knowledge production in service robotics as well as the share of localized German industries in production being higher than in services. Secondly, employing a new methodology based on Markov chain simulations it is assessed whether the number of sustained superior employment growth performing firms in four European economies is different from what would be expected by chance. A mixed evidence of presence and absence of factors determining firm dynamics is found

Secondary Instabilities of Surface Waves on Viscous Fluids in the Faraday Instability

Secondary instabilities of Faraday waves show three regimes: (1) As seen previously, low-viscosity (nu) fluids destabilize first into squares. At higher driving accelerations a, squares show low-frequency modulations corresponding to the motion of phase defects, while theory predicts a stationary transverse amplitude modulation (TAM). (2) High-nu fluids destabilize first to stripes. Stripes then show an oscillatory TAM whose frequency is incommensurate with the driving frequency. At higher a, the TAM undergoes a phase instability. At still higher a, edge dislocations form and fluid droplets are ejected. (3) Intermediate-nu fluids show a complex coexistence of squares and stripes, as well as stationary and oscillatory TAM instabilities of the stripes.Comment: REVTEX, with 3 separate uuencoded figures, to appear in Europhys. Let

Pervasive enough? General purpose technologies as an emergent property

We propose a novel model of knowledge discovery shedding light on the emergence of General Purpose Technologies (GPTs), the process which has been largely neglected in the literature on technological change. We demonstrate that GPTs emerge only when certain conditions with regard to the following techno-economic factors are met: knowledge diffusion, coordination on technological trajectories and volatility in the rank of expected returns on products. Furthermore, our model provides intuitive explanation for technological lock-ins, S-shaped curves of technology adoption, temporal clustering of innovations in time and replicates distinct features of empirical networks of relatedness among technologies and products

On the Origin of Traveling Pulses in Bistable Systems

The interaction between a pair of Bloch fronts forming a traveling domain in a bistable medium is studied. A parameter range beyond the nonequilibrium Ising-Bloch bifurcation is found where traveling domains collapse. Only beyond a second threshold the repulsive front interactions become strong enough to balance attractive interactions and asymmetries in front speeds, and form stable traveling pulses. The analysis is carried out for the forced complex Ginzburg-Landau equation. Similar qualitative behavior is found in the bistable FitzHugh-Nagumo model.Comment: 5 pages, RevTeX. Aric Hagberg: http://t7.lanl.gov/People/Aric/; Ehud Meron:http://www.bgu.ac.il/BIDR/research/staff/meron.htm

A Phase Front Instability in Periodically Forced Oscillatory Systems

Multiplicity of phase states within frequency locked bands in periodically forced oscillatory systems may give rise to front structures separating states with different phases. A new front instability is found within bands where $\omega_{forcing}/\omega_{system}=2n$ ($n>1$). Stationary fronts shifting the oscillation phase by $\pi$ lose stability below a critical forcing strength and decompose into $n$ traveling fronts each shifting the phase by $\pi/n$. The instability designates a transition from stationary two-phase patterns to traveling $n$-phase patterns

Local estimates for entropy densities in coupled map lattices

We present a method to derive an upper bound for the entropy density of coupled map lattices with local interactions from local observations. To do this, we use an embedding technique being a combination of time delay and spatial embedding. This embedding allows us to identify the local character of the equations of motion. Based on this method we present an approximate estimate of the entropy density by the correlation integral.Comment: 4 pages, 5 figures include

HHT-based Analysis of ECG Signals of Patients with Borderline Mental Disorders

This paper describes a solution for borderline mental disorders detection. This approach is based on the ECG processing by Hilbert-Huang Transformation. The described approach allows to develop an additional module for mental disorders diagnostic systems. The research is based on the fact that in the conditions of borderline mental disorders there are changes in patients' heart function. Detection of significant ECG informative parameters is based on the effective and accurate measurement of amplitude, time, frequency and energy parameters of the ECG signal. A verified and registered database of 780 ECG signals of patients with borderline mental disorders and healthy people is used. The proposed method is described and the results are shown. The errors of the method with current sampling do not exceed 4%. The developed approach using volumetric spectral surfaces has showed a high probability of determining the period of occurrence of psycho-traumatic situations in various patients using the ECG

Aberrant Splicing of the Senataxin Gene in a Patient with Ataxia with Oculomotor Apraxia Type 2

Ataxia with oculomotor apraxia type 2 (AOA2) is caused by a diversity of mutations within the coding region of the senataxin gene. Recently, rare noncoding senataxin mutations affecting RNA processing have been identified in AOA2. Here, we report the case of an 18-year-old woman, with classic clinical features of AOA2, who was found to harbor a mutation within senataxin intron 16. This mutation disrupts the local 5′ splice site architecture via a novel intronic frameshift mechanism, causing skipping of exon 16 with predicted disruption of the conserved DNA/RNA helicase domain. RNA processing mutations expand the growing complexity of pathogenic senataxin mutations

A patent search strategy based on machine learning for the emerging field of service robotics

Emerging technologies are in the core focus of supra-national innovation policies. These strongly rely on credible data bases for being effective and efficient. However, since emerging technologies are not yet part of any official industry, patent or trademark classification systems, delineating boundaries to measure their early development stage is a nontrivial task. This paper is aimed to present a methodology to automatically classify patents as concerning service robots. We introduce a synergy of a traditional technology identification process, namely keyword extraction and verification by an expert community, with a machine learning algorithm. The result is a novel possibility to allocate patents which (1) reduces expert bias regarding vested interests on lexical query methods, (2) avoids problems with citational approaches, and (3) facilitates evolutionary changes. Based upon a small core set of worldwide service robotics patent applications we derive apt n-gram frequency vectors and train a support vector machine (SVM), relying only on titles, abstracts and IPC categorization of each document. Altering the utilized Kernel functions and respective parameters we reach a recall level of 83% and precision level of 85%

Proximity and Collaboration in German Nanotechnology Network

The processes of the establishment and facilitation of inter-organizational collaboration in German nanotechnology network are differently influenced by proximity dimentions. Collaborations are very important for newly emerging technologies such as nanotechnology. With this master thesis we focus on howgeographical, organizational and technological proximities influence collaboration activities in nanotechnology. We base the analyses on publication data for the last three years. We were able to show which of these dimensions play a role in establishing and facilitatingcollaborations using methods of regression analysis. While geographical and technological proximity directlyaffect both of these processes, organizational is only affecting the establishment of collaborations. We explain why proximity and collaboration are related in such ways. Based on that we offer management and policy recommendations.Management of TechnologyEconomics of InnovationTechnology, Policy and Managemen