Conducting and Superconducting BEDT-TTF Based Synmetals

The synthesis, crystal structures and band electronic structures of BEDT-TTF based synmetals are discussed, where BEDT-TTF is bis(ethylenedithio)-tetrathiofulvalene here abbreviated to “ET”. The electrical properties of ET:X salts above their phase transitions are either 1D [for (ET)₂X, where X⁻ = ICl₂⁻, AuBr₂⁻, Au(CN)₂⁻ and Ag(CN)₂⁻], 2D metallic [for (ET)₂X, where X⁻ = I₃⁻, AuI₂⁻, IBr₂⁻ and I₂Br⁻] or 3D metallic [for (ET)Ag₄(CN)₅]. The β-(ET)₂X (X⁻ = I₃⁻, AuI₂⁻ and IBr₂⁻) salts become ambient pressure organic superconductors at 1,4 K (or ∼ 8 K under pressure), 5.0 K, and 2.8 K, respectively. The variation of critical temperatures of this series of β-(ET)₂X salts are correlated to the respective changes in unit cell volume or in the density of electronic states at the Fermi level.     

RBS/channeling studies on the heteroepitaxially grown Y2O3 film on Si(100)

The heteroepitaxially grown yttrium oxide layer by an ionized cluster beam (ICB) on a Si(100) substrate was investigated by Rutherford backscattering spectrometry (RBS)/channeling. The channeling minimum value (χ_min) of the Y₂O₃ layer on Si(100) is 0.28, and this is the smallest value among those reported. From the channeling polar plots, it is found that Y₂O₃ film grown on Si(100) oriented with (110) direction and has a double domain structure. The 110 axis of Y₂O₃ layer is exactly parallel to the 100 axis of the Si substrate. It is also observed that the interface region of Y₂O₃ film has more crystalline defects than the surface region.     

Angle densities and recognition of 3D objects

Recognition of 3D objects using computer vision is complicated by the fact that geometric features vary with view orientation. An important factor in designing recognition algorithms in such situations is understanding the variation of certain critical features such as angles. In this paper we derive the two dimensional joint density function of two angles in a scene given an isotropic view orientation and an orthographic projection. The analytic expression for the densities are useful in determining statistical decision rules to recognize surfaces and objects. Experiments to evaluate the usefulness of the proposed methods are reported     

Facial landmarks detection using improved active shape model on android platform

Detection of facial feature is fundamental for applications such as security, biometrics, 3D face modeling and personal authentication. Active Shape Model (ASM) is one of the most popular local texture models for face detection. This paper presents an issue related to face detection based on ASM, and proposes an efficient extraction algorithm for facial landmarks suitable for use on mobile devices. We modifies the original ASM to improve its performance with three changes; (1) Improving the initialization model using the center of the eyes by using a feature map of color information, (2) Constructing modified model definition and fitting more landmarks than the classical ASM, and (3) Extending and building a 2-D profile model for detecting faces in input image. The proposed method is evaluated on dataset containing over 700 images of faces, and experimental results reveal that the proposed algorithm exhibited a significant improvement of over 10.2 % in average success ratio, compared to the classic ASM, clearly outperforming on success rate and computing time.     

Edge Metric Dimension of Honeycomb and Hexagonal Networks for IoT

Wireless Sensor Network (WSN) is considered to be one of the fundamental technologies employed in the Internet of things (IoT); hence, enabling diverse applications for carrying out real-time observations. Robot navigation in such networks was the main motivation for the introduction of the concept of landmarks. A robot can identify its own location by sending signals to obtain the distances between itself and the landmarks. Considering networks to be a type of graph, this concept was redefined as metric dimension of a graph which is the minimum number of nodes needed to identify all the nodes of the graph. This idea was extended to the concept of edge metric dimension of a graph G, which is the minimum number of nodes needed in a graph to uniquely identify each edge of the network. Regular plane networks can be easily constructed by repeating regular polygons. This design is of extreme importance as it yields high overall performance; hence, it can be used in various networking and IoT domains. The honeycomb and the hexagonal networks are two such popular mesh-derived parallel networks. In this paper, it is proved that the minimum landmarks required for the honeycomb network HC(n), and the hexagonal network HX(n) are 3 and 6 respectively. The bounds for the landmarks required for the hex-derived network HDN1(n) are also proposed.     

Hermite variational implicit surface reconstruction

We propose a new technique for reconstructing surfaces from a large set of unorganized 3D data points and their associated normal vectors. The surface is represented as the zero level set of an implicit vol-ume model which fits the data points and normal constraints. Compared with variational implicit sur-faces,we make use of surface normal vectors at data points directly in the implicit model and avoid of introducing manufactured off-surface points. Given n surface point/normal pairs,the proposed method only needs to solve an n×n positive definite linear system. It allows fitting large datasets effectively and robustly. We demonstrate the performance of the proposed method with both globally supported and compactly supported radial basis functions on several datasets.