4-[(5-Chloro-3-methyl-1-phenyl-1H-pyrazol-4-yl)methyl­idene­amino]-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one

In the mol­ecule of the title compound, C22H20ClN5O, the atoms of the two pyrazole rings and the –C=N– group which joins them are essentially coplanar, with an r.m.s. deviation of 0.054 (2) Å. The phenyl rings form dihedral angles of 41.24 (5) and 55.53 (5)° with this plane. The crystal structure is stabilized by weak inter­molecular π–π inter­actions, with centroid-to-centroid distances of 3.6179 (13) Å between the imidazole rings

Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach

The proliferation of highly capable mobile devices such as smartphones and tablets has significantly increased the demand for wireless access. Software defined network (SDN) at edge is viewed as one promising technology to simplify the traffic offloading process for current wireless networks. In this paper, we investigate the incentive problem in SDN-at-edge of how to motivate a third party access points (APs) such as WiFi and smallcells to offload traffic for the central base stations (BSs). The APs will only admit the traffic from the BS under the precondition that their own traffic demand is satisfied. Under the information asymmetry that the APs know more about own traffic demands, the BS needs to distribute the payment in accordance with the APs' idle capacity to maintain a compatible incentive. First, we apply a contract-theoretic approach to model and analyze the service trading between the BS and APs. Furthermore, other two incentive mechanisms: optimal discrimination contract and linear pricing contract are introduced to serve as the comparisons of the anti adverse selection contract. Finally, the simulation results show that the contract can effectively incentivize APs' participation and offload the cellular network traffic. Furthermore, the anti adverse selection contract achieves the optimal outcome under the information asymmetry scenario.Comment: 10 pages, 9 figure

In-the-wild Facial Expression Recognition in Extreme Poses

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.Comment: Published on ICGIP201

Synthesis of dental resins using diatomite and nano-sized SiO2 and TiO2

AbstractThe mechanical properties of dental composites were improved by porous diatomite and nano-sized silica (OX-50) used as co-fillers. The resin composites, filled with silanized OX-50 and silanized diatomite (40:60wt/wt), presented the best flexural strength (133.1MPa), elastic modulus (9.5GPa) and Vickers microhardness (104.0HV). Besides these, TiO2 nanoparticles were introduced to tune the dental resin composites colours which were valued by the CIE-Lab system. The colour parameters (L⁎, a⁎, b⁎) showed that the colour changes of resin composites could be perceived obviously, when 300–400nm TiO2 particles were introduced as fillers. The resin composite, filled with 0.5wt% TiO2, exhibited both clear discolouration (ΔE⁎=3.22) and high mechanical strength. Using scanning electron microscope (SEM) equipped with an energy dispersive X-ray (EDX), the titanium elemental mapping results indicated that the TiO2 particles were distributed evenly in the prepared dental composites