The Nose

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The Moe Politics in Year, Hare, Affair

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Effects of overconfidence on decision making

This thesis aims to explore the effect of overconfidence on people's decision making. To approach this topic, a standard binary detection problem is considered, and its associated individual decision rule and decision fusion rule are derived. Following an axiomatic and empirical approach, a variant of the Prelec function from cumulative prospect theory is then developed to model the effect of overconfidence as a function of level of training. Next, the probability of detection after decision fusion is derived, and a combinatorial optimization is considered which aims to select a subgroup of people/agents to maximize the overall probability of detection.Ope

Binary microlensing with plasma environment -- Star and planet

Galactic microlensing has been widely used to study the star and planet. The stellar wind plays an important role in the formation, environment and habitability of the planet. In this work we study a binary microlensing system including the stellar wind, i.e. a star with plasma environment plus a planet. Plasma surrounding the main lens causes chromatic deflection of the light rays, in addition to the gravitational one. As a result, such a lensing system can generate complicated caustics which depends on the different lensing parameters. In this work we study the magnification curves for different traces of the background source and compare the transitions of the formation of ``hill and hole'' in the magnification curves. We find that the plasma will cause extra caustic, shrink the central caustics generated by the star and push the caustic by the planet outwards. Observations and modelling of binary microlensing curves with taking plasma effect into account can provide a potential method to study plasma environment of the stars. In case of a high plasma density of the stellar wind, the plasma lensing effects will be observable in the sub-mm band.Comment: 11 pages, submitted, comments welcom

Enhanced 6D Measurement by Integrating an Inertial Measurement Unit (IMU) with a 6D Sensor Unit of a Laser Tracker

Six-degree-of-freedom (6D) sensors enhance the measurement capability of traditional three-degree-of-freedom (3D) laser trackers. However, the classical 6D measurement techniques still have shortcomings in actual use, such as the problem of line of sight and relatively low data acquisition rate. The proposed approach by integrating an Inertial Measurement Unit (IMU) with a 6D sensor unit of a laser tracker is effective to overcome these limitations. The error is corrected by the combination of a Kalman filter and a backward smoothing algorithm. The Kalman filter only works when the 6D sensor's data is being sent through, while the backward smoothing algorithm works during the whole process. The experiments are performed to compare the error in three positions and three rotational orientations between the proposed method and the Kalman filter and evaluate the effects of different rates and IMU frequencies on the algorithm. The simulations are also performed to estimate the maximum outage time. The results verify that the proposed method can solve the problem of line of sight and low data acquisition rate effectively.</p

In vivo terahertz imaging to evaluate scar treatment strategies : silicone gel sheeting

Silicone gel sheeting (SGS) is widely used for scar treatment; however, studies showing its interaction with skin and efficacy of scar treatment are still lacking. THz light is non-ionizing and highly sensitive to changes in water content and thus skin hydration. In this work, we use in-vivo THz imaging to monitor how SGS affects the THz response of human skin during occlusion, and the associated THz reflectivity and refractive index changes are presented. We find that SGS effectively hydrates the skin beneath it, with minimal lateral effects beyond the sheeting. Our work demonstrates that THz imaging is able to detect the subtle hydration changes on the surface of human skin caused by SGS, and it has the potential to be used to evaluate different scar treatment strategies

Multivariate Time Series Density Clustering Algorithm Using Shapelet Space

Multivariate time series clustering has become an important research topic in the task of time series analysis. Compared with univariate time series, the research of multivariate time series is more complex and difficult. Although many clustering algorithms for multivariate time series have been proposed, these algorithms still have difficulties in solving the accuracy and interpretation at the same time. Firstly, most of the current work does not consider the length redundancy and variable correlation of multivariable time series, resulting in large errors in the final similarity matrix. Secondly, the data are commonly used in the clustering process with the division paradigm, when the numerical space presents a complex distribution, this idea does not perform well, and it does not have the explanatory power of each variable and space. To address the above problems, this paper proposes a multivariate time series adaptive weight density clustering algorithm using Shapelet (high information-rich continuous subsequence) space (MDCS). This algorithm firstly performs a Shapelet search for each variable, and obtains its own Shapelet space through an adaptive strategy. Then, it weights the numerical distribution generated by each variable to obtain a similarity matrix that is more consistent with the characteristics of data distribution. Finally, the data are finally allocated using the shared nearest neighbor density peak clustering algorithm with improved density calculation and secondary allocation. Experimental results on several real datasets demonstrate that MDCS has better clustering results compared with current state-of-the-art clustering algorithms, with an average increase of 0.344 and 0.09 in the normalized mutual information and Rand index, balancing performance and interpretability

THz in vivo measurements : the effects of pressure on skin reflectivity

Terahertz (THz) light is non-ionizing and highly sensitive to subtle changes in water concentration which can be indicative of disease. The short THz penetration depth in bio-samples restricts in vivo measurements to be in a reflection geometry and the sample is often placed onto an imaging window. Upon contacting the imaging window, occlusion and compression of the skin affect the THz response. If not appropriately controlled, this could cause misleading results. In this work, we investigate and quantify how the applied pressure affects the THz response of skin and employ a stratified model to help understand the mechanisms at play. This work will enable future THz studies to have a more rigorous experimental protocol, which in turn will facilitate research in various potential biomedical applications under investigation

A robust protocol for in vivo THz skin measurements

This work presents an experimental setup to control the way in which pressure interferes with the repeatability of in vivo THz skin measurements. By integrating a pressure sensor circuit into our THz system, it is possible to identify which measurements were taken within a previously specified pressure range. The live response of the pressure sensor helps to acquire data within the desired pressure leading to greater consistency of data between measurements. Additionally, a protocol is proposed to help achieve repeatable results and to remove the effects of the natural variation of the skin through the course of the day. This technique has been shown to be able to quantify the changes induced in the skin following the application of a moisturising skin product and shows the measured result to be significantly different from natural skin variation. This research therefore prepares the way for further studies on the effectiveness of different skin products using in vivo THz measurements