The adsorption, storage and release of nitric oxide using ion exchanged zeolites

Zeolites exchanged with transition metal cations Co2+, Mn2+, Zn2+ and Cu2+ are capable of storing and delivering a large quantity of nitric oxide in a range of 1.2-2.7 mmolg(-1). The metal ion exchange impacts the pore volumes of zeolite FAU more significantly than LTA. The storage of NO mainly involves coordination of NO to metal cation sites. By exposing zeolites to a moisture atmosphere, the stored nitric oxide can be released. The NO release takes more than 2 hours for the NO concentration decreasing below similar to 5ppb in outlet gas. Its release rate can be controlled by tailoring zeolite frameworks and optimising release conditions.

Local materials for building houses: laterite valorization in Africa

This paper presents the preliminary results of geological and geomechanical studies on the laterite stone exploited at Dano quarry in Burkina Faso. The field work described the geological structure of quarry sites and their environment to determine the rocks alteration and the links between the bedrock and lateritic material. Physic-mechanical properties have been studied for assessing the potentiality of this material for lightweight housing, to be completed with thermal and environmental considerations. Some social and economic evaluations are in progress in order to foster its utilization under local conditions.

Low-rank representation based action recognition

Human action recognition is an important problem in computer vision, which has been applied to many applications. However, how to learn an accurate and discriminative representation of videos based on the features extracted from videos still remains to be a challenging problem. In this paper, we propose a novel method named low-rank representation based action recognition to recognize human actions. Given a dictionary, low-rank representation aims at finding the lowestrank representation of all data, which can capture the global data structures. According to its characteristics, low-rank representation is robust against noises. Experimental results demonstrate the effectiveness of the proposed approach on several publicly available datasets.

Channel measurements of device–to–device communications in an urban outdoor environment

In this paper, the results of radio channel measurements between two hypothetical cellular handsets in an outdoor urban environment are reported. The device-to-device channel measurements were made at 868 MHz and investigated a number of different everyday usage scenarios such as the devices being held at the user's heads, placed in a pocket while one of the users rotated or both moved randomly. It was found that shadowing of the main signal path caused by the human body will be an important factor in future device-to-device communications at this frequency. The recently proposed shadowed κ-μ fading model was used to characterize these channels and shown to provide a good description of the measured data.

Improved Physical Layer Secure Wireless Communications using a Directional Modulation Enhanced Retrodirective Array

Unlike the mathematical encryption and decryption adopted in the classical cryptographic technology at the higher protocol layers, it is shown that characteristics intrinsic to the physical layer, such as wireless channel propagation, can be exploited to lock useful information. This information then can be automatically unlocked using real time analog RF means. In this paper retrodirective array, RDA, technology for spatial encryption in the multipath environment is for the first time combined with the directional modulation, DM, method normally associated with free space secure physical layer communications. We show that the RDA can be made to operate more securely by borrowing DM concepts and that the DM enhanced RDA arrangement is suitable for use in a multipath environment.

Conceptual Design and Workspace Analysis of an Exechon-inspired Parallel Kinematic Machine

Inspired by the commercial application of the Exechon machine, this paper proposed a novel parallel kinematic machine (PKM) named Exe-Variant. By exchanging the sequence of kinematic pairs in each limb of the Exechon machine, the Exe-Variant PKM claims an arrangement of 2UPR/1SPR topology and consists of two identical UPR limbs and one SPR limb. The inverse kinematics of the 2UPR/1SPR parallel mechanism was firstly analyzed based on which a conceptual design of the Exe-Variant was carried out. Then an algorithm of reachable workspace searching for the Exe-Variant and the Exchon was proposed. Finally, the workspaces of two example systems of the Exechon and the Exe-Variant with approximate dimensions were numerically simulated and compared. The comparison shows that the Exe-Variant possesses a competitive workspace with the Exechon machine, indicating it can be used as a promising reconfigurable module in a hybrid 5-DOF machine tool system.

An Ambiguity Aversion Framework of Security Game under Ambiguities

Security is a critical concern around the world. Since resources for security are always limited, lots of interest have arisen in using game theory to handle security resource allocation problems. However, most of the existing work does not address adequately how a defender chooses his optimal strategy in a game with absent, inaccurate, uncertain, and even ambiguous strategy profiles' payoffs. To address this issue, we propose a general framework of security games under ambiguities based on Dempster-Shafer theory and the ambiguity aversion principle of minimax regret. Then, we reveal some properties of this framework. Also, we present two methods to reduce the influence of complete ignorance. Our investigation shows that this new framework is better in handling security resource allocation problems under ambiguities.

Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.