Accuracy and stability analysis of path loss exponent measurement for localization in wireless sensor network

In wireless sensor network localization, path loss model is often used to provide a conversion between distance and received signal strength (RSS). Path loss exponent is one of the main environmental parameters for path loss model to characterize the rate of conversion. Therefore, the accuracy of path loss exponent directly influences the results of RSS-to-distance conversion. When the conversion requires distance estimation from RSS value, small error of measured path loss exponent could lead to large error of the conversion output. To improve the localization results, the approaches of measuring accurate parameters from different environments have become important. Different approaches provide different measurement stabilities, depending on the performance and robustness of the approach. This paper presents four calibration approaches to provide measurements of path loss exponent based on measurement arrangement and transmitter/receiver node’s allocation. These include one-line measurement, online-update spread locations measurement, online-update small-to big rectangular measurement, and online-update big-to-small rectangular measurement. The first two are general approaches, and the last two are our newly proposed approaches. Based on our research experiments, a comparison is presented among the four approaches in terms of accuracy and stability. The results show that both online-update rectangular measurements have better stability of measurements. For accuracy of measurement, online-update big-to-small rectangular measurement provides the best result after convergence

Advancement in Source Estimation Techniques Using Broadband Regional Seismograms

One important constraint on source retrieval from regional seismograms comes from the amplitude difference between various phases (such as Pnl/surface wave, SV/SH). Because the misfit errors used in some waveform inversions are normalized by the data and synthetics, the amplitude information in the data has not been fully utilized. In this article, we modify the "cut and paste" source estimation technique (Zhao and Helmberger, 1994) by removing this type of normalization. It is shown that the modified method increases the stability and resolution of inversion. When multiple stations at different distance ranges are used, a distance scaling factor is introduced to compensate for the amplitude decay with distance. By applying the technique to the TERRAscope data, we have determined source mechanisms and depths of 335 southern Californian events with M_L ≧ 3.5. The amplitude decays with distance are r^(1.13) for Pnl, r^(0.55) for Love waves, and r^(0.74) for Rayleigh waves. In contrast to generally shallow source depths reported by the southern California short period network, the depth distribution from waveform inversion shows a strong peak around 12 km with few earthquakes occurring above 5 km and below 20 km

Innovation Effects and Origins of Ego-Network Stability: The Hidden Dimension of Social Capital

University of Minnesota Ph.D. dissertation. 2018. Major: Business Administration. Advisor: Akbar Zaheer. 1 computer file (PDF); 190 pages.Much research has shown that firms’ ego-network configurations, i.e., structural holes or network closure, help them achieve superior innovation outcomes. However, little is known about how overall ego-network stability affects innovation. In this two-part dissertation, I first argue that in the alliance network context the stability is detrimental for the focal firm’s innovation performance. Moreover, firms are affected differentially by the stability depending on whether they span structural holes and on whether their inventive activities are geographically concentrated. Spanning structural holes mitigates the negative effect of ego-network stability whereas the geographic concentration of firms’ inventive activities further worsens the negative relationship. Next, I develop propositions about the origins of firms’ ego-network stability. I limit my theorizing in this case to structural hole stability or the stability of open structures only, with special focus on the embeddedness of alliance brokerage structures in geographic and network community space. I argue that the stability of network structures increases with the geographic distance between member firms. In contrast, I hypothesize that member firms’ location in different network communities has a negative effect on the stability of networks. I empirically test my propositions regarding the (ego-network) stability-performance relationship using 198 biopharmaceutical firms headquartered in the U.S. over a 21-year period from 1985 to 2005. My estimation sample for testing the origins of structural hole stability comprises of 329 broker and 680 alter firms over 1985-2005, yielding 61,495 triad-year observations in the global pharmaceutical industry context. I find support for my ideas. I contribute theoretically by highlighting the importance of network stability, a salient but lost dimension of social capital, for the focal firm’s performance. My work has practical implications in terms of network rewiring and maintenance

PMU-Based Estimation of Dynamic State Jacobian Matrix

In this paper, a hybrid measurement- and model-based method is proposed which can estimate the dynamic state Jacobian matrix in near real-time. The proposed method is computationally efficient and robust to the variation of network topology. A numerical example is given to show that the proposed method is able to provide good estimation for the dynamic state Jacobian matrix and is superior to the model-based method under undetectable network topology change. The proposed method may also help identify big discrepancy in the assumed network model.Comment: IEEE International Conference on Circuits and Systems (ISCAS) 201