Multiple Imputation Using Gaussian Copulas

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use method for generating multiple imputations using a Gaussian copula. The Gaussian copula for multiple imputation (Hoff, 2007) allows scholars to attain estimation results that have good coverage and small bias. The use of copulas to model the dependence among variables will enable researchers to construct valid joint distributions of the data, even without knowledge of the actual underlying marginal distributions. Multiple imputations are then generated by drawing observations from the resulting posterior joint distribution and replacing the missing values. Using simulated and observational data from published social science research, we compare imputation via Gaussian copulas with two other widely used imputation methods: MICE and Amelia II. Our results suggest that the Gaussian copula approach has a slightly smaller bias, higher coverage rates, and narrower confidence intervals compared to the other methods. This is especially true when the variables with missing data are not normally distributed. These results, combined with theoretical guarantees and ease-of-use suggest that the approach examined provides an attractive alternative for applied researchers undertaking multiple imputations

The Nature of Surface Oxides on Corrosion-Resistant Nickel Alloy Covered by Alkaline Water

A nickel alloy with high chrome and molybdenum content was found to form a highly resistive and passive oxide layer. The donor density and mobility of ions in the oxide layer has been determined as a function of the electrical potential when alkaline water layers are on the alloy surface in order to account for the relative inertness of the nickel alloy in corrosive environments

HoneyPAKEs

We combine two security mechanisms: using a Password-based Authenticated Key Establishment (PAKE) protocol to protect the password for access control and the Honeywords construction of Juels and Rivest to detect loss of password files. The resulting construction combines the properties of both mechanisms: ensuring that the password is intrinsically protected by the PAKE protocol during transmission and the Honeywords mechanisms for detecting attempts to exploit a compromised password file. Our constructions lead very naturally to two factor type protocols. An enhanced version of our protocol further provides protection against a compromised login server by ensuring that it does not learn the index to the true password

On the security of consumer wearable devices in the Internet of Things

Miniaturization of computer hardware and the demand for network capable devices has resulted in the emergence of a new class of technology called wearable computing. Wearable devices have many purposes like lifestyle support, health monitoring, fitness monitoring, entertainment, industrial uses, and gaming. Wearable devices are hurriedly being marketed in an attempt to capture an emerging market. Owing to this, some devices do not adequately address the need for security. To enable virtualization and connectivity wearable devices sense and transmit data, therefore it is essential that the device, its data and the user are protected. In this paper the use of novel Integrated Circuit Metric (ICMetric) technology for the provision of security in wearable devices has been suggested. ICMetric technology uses the features of a device to generate an identification which is then used for the provision of cryptographic services. This paper explores how a device ICMetric can be generated by using the accelerometer and gyroscope sensor. Since wearable devices often operate in a group setting the work also focuses on generating a group identification which is then used to deliver services like authentication, confidentiality, secure admission and symmetric key generation. Experiment and simulation results prove that the scheme offers high levels of security without compromising on resource demands

An Approach to the Bio-Inspired Control of Self-reconfigurable Robots

Self-reconfigurable robots are robots built by modules which can move in relationship to each other. This ability of changing its physical form provides the robots a high level of adaptability and robustness. Given an initial configuration and a goal configuration of the robot, the problem of self-regulation consists on finding a sequence of module moves that will reconfigure the robot from the initial configuration to the goal configuration. In this paper, we use a bio-inspired method for studying this problem which combines a cluster-flow locomotion based on cellular automata together with a decentralized local representation of the spatial geometry based on membrane computing ideas. A promising 3D software simulation and a 2D hardware experiment are also presented.National Natural Science Foundation of China No. 6167313

Highly Sensitive Fluorescence Probe Based on Functional SBA-15 for Selective Detection of Hg2+

An inorganic–organic hybrid fluorescence chemosensor (DA/SBA-15) was prepared by covalent immobilization of a dansylamide derivative into the channels of mesoporous silica material SBA-15 via (3-aminopropyl)triethoxysilane (APTES) groups. The primary hexagonally ordered mesoporous structure of SBA-15 was preserved after the grafting procedure. Fluorescence characterization shows that the obtained inorganic–organic hybrid composite is highly selective and sensitive to Hg2+ detection, suggesting the possibility for real-time qualitative or quantitative detection of Hg2+ and the convenience for potential application in toxicology and environmental science