Optimized Blind Control Method to Minimize Heating, Cooling and Lighting Energy

AbstractEnergy saving has become a hot issue all over the world. To minimize the energy use in buildings, the cooperative control coupled with heating, cooling, lighting and blind control system was proposed in this study. The blind condition is optimized to minimize the total energy of heating, cooling and lighting.In this study, the control behaviors and energy saving effect of the proposed system were evaluated by field measurement. The results show that the proposed control system reduces the cooling energy demand by about 40.8% and 19.6% of the lighting energy compared to the conventional control system with maintaining the same thermal comfort level. The total energy saving rate reached 29.7%

Probing the messenger of supersymmetry breaking by the muon anomalous magnetic moment

Motivated by the recently measured muon's anomalous magnetic moment $a_{\mu}$, we examine the supersymmetry contribution to $a_{\mu}$ in various mediation models of supersymmetry breaking which lead to predictive flavor conserving soft parameters at high energy scale. The studied models include dilaton/modulus-mediated models in heterotic string/$M$ theory, gauge-mediated model, no-scale or gaugino-mediated model, and also the minimal and deflected anomaly-mediated models. For each model, the range of $a^{SUSY}_{\mu}$ allowed by other experimental constraints, e.g. b --> s\gamma and the collider bounds on superparticle masses, is obtained together with the corresponding parameter region of the model. Gauge-mediated models with low messenger scale can give any $a^{SUSY}_{\mu}$ within the $2\sigma$ bound. In many other models, b --> s\gamma favors $a^{SUSY}_{\mu}$ smaller than either the $-1\sigma$ value ($26\times 10^{-10}$) or the central value ($42\times 10^{-10}$).Comment: RevTeX, 29 pages, 14 eps figures, figure for deflected anomaly mediation is corrected, reference adde

Ferromagnetically coupled magnetic impurities in a quantum point contact

We investigate the ground and excited states of interacting electrons in a quantum point contact using exact diagonalization method. We find that strongly localized states in the point contact appear when a new conductance channel opens due to momentum mismatch. These localized states form magnetic impurity states which are stable in a finite regime of chemical potential and excitation energy. Interestingly, these magnetic impurities have ferromagnetic coupling, which shed light on the experimentally observed puzzling coexistence of Kondo correlation and spin filtering in a quantum point contact

The CDF dijet excess and Z'_{cs} coupled to the second generation quarks

Recently the CDF collaboration has reported the excess in the dijet invariant-mass distribution of the Wjj events, corresponding to a significance of 3.2 standard deviations. Considering the lack of similar excesses in the $\gamma jj$ and $Z jj$ events yet, we propose a new Z' model: Z' couples only to the second generation quarks. Single production of \zsc as well as associated production with $W,\gamma, Z$ are mainly from the sea quarks. Only $W Z'$ production has additional contribution from one valence quark and one sea quark, which is allowed by CKM mixing. We found that if the new gauge coupling is large enough, marginally permitted by perturbativity, this new model can explain the observed CDF $Wjj$ anomaly as well as the lack of \gm jj and $Z jj$ anomalies. Vanishing coupling of Z'-b-b protects this model from the constraint of p pbar ->WH -> l\nu b \bar{b}.Comment: references adde

Combining Local Appearance and Holistic View: Dual-Source Deep Neural Networks for Human Pose Estimation

We propose a new learning-based method for estimating 2D human pose from a single image, using Dual-Source Deep Convolutional Neural Networks (DS-CNN). Recently, many methods have been developed to estimate human pose by using pose priors that are estimated from physiologically inspired graphical models or learned from a holistic perspective. In this paper, we propose to integrate both the local (body) part appearance and the holistic view of each local part for more accurate human pose estimation. Specifically, the proposed DS-CNN takes a set of image patches (category-independent object proposals for training and multi-scale sliding windows for testing) as the input and then learns the appearance of each local part by considering their holistic views in the full body. Using DS-CNN, we achieve both joint detection, which determines whether an image patch contains a body joint, and joint localization, which finds the exact location of the joint in the image patch. Finally, we develop an algorithm to combine these joint detection/localization results from all the image patches for estimating the human pose. The experimental results show the effectiveness of the proposed method by comparing to the state-of-the-art human-pose estimation methods based on pose priors that are estimated from physiologically inspired graphical models or learned from a holistic perspective.Comment: CVPR 201