Magnetism and Mott Transition: A Slave-rotor Study

Motivated by the debate of spin-density-wave (SDW) versus local-moment (LM) picture in the iron-based superconducting (FeSC) materials, we consider a two-band orbital-symmetric Hubbard model in which there is robust Fermi surface nesting at $(\pi,0)$. We obtain the phase diagram of such system by a mean-field slave-rotor approach, in which the Fermi surface nesting and the SDW order are explicitly taken into account via a natural separation of scale between the Hund's coupling and the Coulomb interaction. We find that for a sizable range of Hund's coupling the Mott transition acquires a strong first-order character, but there also exists a small range of stronger Hund's coupling in which an enhancement of magnetization can be observed on the SDW side. We interpret the former scenario as one in which a sharp distinction can be drawn between LM and the SDW picture, and the latter scenario as one in which signs of LM physics begin to develop in the metallic phase. It is tempting to suggest that some FeSC materials are in the vicinity of the latter scenario.Comment: 7 pages, 5 figures; v2: Added discussions on anisotropy in renormalized hopping, clarifications and discussions with regard to orbital order, new inset in Fig. 3(d), expanded and revised bibliography, plus other minor revisions. Accepted to PR

Automatically Designing CNN Architectures for Medical Image Segmentation

Deep neural network architectures have traditionally been designed and explored with human expertise in a long-lasting trial-and-error process. This process requires huge amount of time, expertise, and resources. To address this tedious problem, we propose a novel algorithm to optimally find hyperparameters of a deep network architecture automatically. We specifically focus on designing neural architectures for medical image segmentation task. Our proposed method is based on a policy gradient reinforcement learning for which the reward function is assigned a segmentation evaluation utility (i.e., dice index). We show the efficacy of the proposed method with its low computational cost in comparison with the state-of-the-art medical image segmentation networks. We also present a new architecture design, a densely connected encoder-decoder CNN, as a strong baseline architecture to apply the proposed hyperparameter search algorithm. We apply the proposed algorithm to each layer of the baseline architectures. As an application, we train the proposed system on cine cardiac MR images from Automated Cardiac Diagnosis Challenge (ACDC) MICCAI 2017. Starting from a baseline segmentation architecture, the resulting network architecture obtains the state-of-the-art results in accuracy without performing any trial-and-error based architecture design approaches or close supervision of the hyperparameters changes.Comment: Accepted to Machine Learning in Medical Imaging (MLMI 2018

How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?

Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU) systems. In particular, MUDiv allows for scheduling among users in order to eliminate the negative effects of unfavorable channel fading conditions of some users on the system performance. Scheduling, however, consumes energy (e.g., for making users' channel state information available to the scheduler). This extra usage of energy, which could potentially be used for data transmission, can be very wasteful, especially if the number of users is large. In this paper, we answer the question of how much MUDiv is required for energy limited MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling algorithms which aim at maximizing the MUDiv gain. Toward this end, we introduce a new realistic energy model which accounts for scheduling energy and describes the distribution of the total energy between scheduling and data transmission stages. Using the fact that such energy distribution can be controlled by varying the number of active users, we optimize this number by either (i) minimizing the overall system bit error rate (BER) for a fixed total energy of all users in the system or (ii) minimizing the total energy of all users for fixed BER requirements. We find that for a fixed number of available users, the achievable MUDiv gain can be improved by activating only a subset of users. Using asymptotic analysis and numerical simulations, we show that our approach benefits from MUDiv gains higher than that achievable by generic greedy access algorithm, which is the optimal scheduling method for energy unlimited systems.Comment: 28 pages, 9 figures, submitted to IEEE Trans. Signal Processing in Oct. 200

Contribution of b→sggb \to sgg through the QCD anomaly in exclusive decays B±→(η′,η)(K±,K∗±)B^{\pm}\to (\eta^{\prime},\eta)(K^{\pm}, K^{*\pm}) and B0→(η′,η)(K0,K∗0)B^{0}\to (\eta^{\prime},\eta)(K^{0},K^{*0})

We compute the decay rates for the exclusive decays $B^{\pm} \to (\eta^{\prime},\eta) (K^{\pm}, K^{*\pm})$ and $B^{0}\to (\eta^{\prime},\eta) (K^{0}, K^{*0})$ in a QCD-improved factorization framework by including the contribution from the process $b\to sgg \to s (\eta^{\prime}, \eta)$ through the QCD anomaly. This method provides an alternative estimate of the contribution $b \to s c\bar{c} \to s(\eta,\eta^\prime)$ to these decays as compared to the one using the intrinsic charm content of the $\eta^{\prime}$ and $\eta$ mesons determined through the decays $J/\psi \to (\eta,\eta^\prime ,\eta_c) \gamma$. The resulting branching ratios are compared with the CLEO data on $B^{\pm} \to \eta^{\prime} K^{\pm}$ and $B^{0} \to \eta^{\prime} K^{0}$ and predictions are made for the rest.Comment: 16 pages including 4 postscript figures; uses epsfig. The most recent branching ratios from CLEO, ref. [5], are taken into account. The theory part is unchange

Thermal stress analysis of space shuttle orbiter subjected to reentry aerodynamic heating

A structural performance and resizing (SPAR) finite-element computer program and NASA structural analysis (NASTRAN) finite-element computer programs were used in the thermal stress analysis of the space shuttle orbiter subjected to reentry aerodynamic heating. A SPAR structural model was set up for the entire left wing of the orbiter, and NASTRAN structural models were set up for: (1) a wing segment located at midspan of the orbiter left wing, and (2) a fuselage segment located at midfuselage. The thermal stress distributions in the orbiter structure were obtained and the critical high thermal stress regions were identified. It was found that the thermal stresses induced in the orbiter structure during reentry were relatively low. The thermal stress predictions from the whole wing model were considered to be more accurate than those from the wing segment model because the former accounts for temperature and stress effects throughout the entire wing

OBOME - Ontology based opinion mining in UBIPOL

Ontologies have a special role in the UBIPOL system, they help to structure the policy related context, provide conceptualization for policy domain and use in the opinion mining process. In this work we presented a system called Ontology Based Opinion Mining Engine (OBOME) for analyzing a domain-specific opinion corpus by first assisting the user with the creation of a domain ontology from the corpus. We determined the polarity of opinion on the various domain aspects. In the former step, the policy domain aspect has are identified (namely which policy category is represented by the concept). This identification is supported by the policy modelling ontology, which describe the most important policy – related classes and structure. Then the most informative documents from the corpus are extracted and asked the user to create a set of aspects and related keywords using these documents. In the latter step, we used the corpus specific ontology to model the domain and extracted aspect-polarity associations using grammatical dependencies between words. Later, summarized results are shown to the user to analyze and store. Finally, in an offline process policy modeling ontology is updated