An SNS-based model for finding collaborative partners

This paper proposes a model, Recommendation of Appropriate Partners (RAP), used on a Social Networking Service (SNS) for locating appropriate “helpers” for users based on individual users’ Chain of Friends (CoF) relationships. Using the RAP model, individual users can participate in a collaborative online community in remote locations, whereby helpers are willing to help other users solve their tasks/problems, and it is intended that both the users and helpers gain knowledge from these interactive online sessions. An example of the RAP-based system was implemented to invite Program Committee members to an international conference. The system was evaluated and the experimental results show that our model is very effective for discovering collaboration partners and finding users with similar interests in order to create communities for providing future and longer-term helping exchange.

     

A variational formulation for fingerprint orientation modeling

Orientation pattern is an important feature for characterizing fingerprint and plays critical roles in fingerprint recognition and fingerprint classification. This paper proposes a framework for modeling the fingerprint orientation field based on the variational principle, where the orientation pattern can be estimated through solving the associated Euler–Lagrange equation. Compared with existing methods, our proposed method has the following features. Firstly, it does not require any prior information about the structure of the acquired fingerprint, such as location of singular point(s). Secondly, it explicitly provides freedom for modeling the singularity in the orientation field. Thirdly, it has less number of parameters. Comparison has been made with respect to state-of-the-arts in fingerprint orientation modeling in terms of modeling accuracy, fingerprint enhancement and singular point detection. Advantages of the proposed method are demonstrated.     

Efficient screen-space approach to high-quality multiscale ambient occlusion

We present a new screen-space ambient occlusion (SSAO) algorithm that improves on the state-of-the-art SSAO methods in both performance and quality. Our method computes ambient occlusion (AO) values at multiple image resolutions and combines them to obtain the final, high-resolution AO value for each image pixel. It produces high-quality AO that includes both high-frequency shadows due to nearby, occluding geometry and low-frequency shadows due to distant geometry. Our approach only needs to use very small sampling kernels at every resolution, thereby achieving high performance without resorting to random sampling. As a consequence, our results do not suffer from noise and excessive blur, which are common of other SSAO methods. Therefore, our method also avoids the expensive, final blur pass commonly used in other SSAO methods. The use of multiple resolutions also helps reduce errors that are caused by SSAO’s inherent lack of visibility checking. Temporal incoherence caused by using coarse resolutions is solved with an optional temporal filtering pass. Our method produces results that are closer to ray-traced solutions than those of any existing SSAO methods, while running at similar or higher frame rates than the fastest ones.     

Explicit solution of DMZ equation in nonlinear filtering via solution of ODEs

In this note, we develop a real-time and accurate solution for nonlinear filtering problems based on the Gaussian distribution. Specifically, we present an explicit solution of the Duncan-Mortensen-Zakai (DMZ) equation of the Yau filtering system, which includes the linear filtering system and exact filtering system. The solution is given in terms of a solution of a system of ordinary differential equations. In particular, our method can be implemented in hardware. The complexity of our algorithms is the same as those of Kalman-Bucy filters in the case of linear filtering systems.     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

Quantitative Measurements of the Critical Impeller Speed for Solid‐Liquid Suspensions

A quantitative methodology for particle suspension assessment is presented. A new parameter, f_mov/tot, the ratio of the mean number of moving particles to the total number of particles, is introduced to evaluate the minimum speed required to just suspend solids. This approach is tested to investigate the impact of impeller clearance on the minimum impeller speed, N_js, in a vessel when using a radial flow Rushton turbine. Flow patterns and power numbers obtained experimentally and computationally support the suspension findings. Image analysis is an appropriate method for determining N_js. Lowering the impeller clearance reduces the speed required for particle suspension with a change of flow pattern from a radial discharge with two loops to a single loop scouring the vessel base. The power number also falls markedly at the two‐to‐one loop transition as does the strain rate near the base.