Real photons produced from photoproduction in pppp collisions

We calculate the production of real photons originating from the photoproduction in relativistic $pp$ collisions. The Weizs$\ddot{\mathrm{a}}$cker-Williams approximation in the photoproduction is considered. Numerical results agree with the experimental data from Relativistic Heavy Ion Collider (RHIC) and Large Hadron Collider (LHC). We find that the modification of the photoproduction is more prominent in large transverse momentum region.Comment: 2 figure

Dynamic Thermal and Power Management: From Computers to Buildings

Thermal and power management have become increasingly important for both computing and physical systems. Computing systems from real-time embedded systems to data centers require effective thermal and power management to prevent overheating and save energy. In the mean time, as a major consumer of energy buildings face challenges to reduce the energy consumption for air conditioning while maintaining comfort of occupants. In this dissertation we investigate dynamic thermal and power management for computer systems and buildings. (1) We present thermal control under utilization bound (TCUB), a novel control-theoretic thermal management algorithm designed for single core real-time embedded systems. A salient feature of TCUB is to maintain both desired processor temperature and real-time performance. (2) To address unique challenges posed by multicore processors, we develop the real-time multicore thermal control (RT-MTC) algorithm. RT-MTC employs a feedback control loop to enforce the desired temperature and CPU utilization of the multicore platform via dynamic frequency and voltage scaling. (3) We research dynamic thermal management for real-time services running on server clusters. We develop the control-theoretic thermal balancing (CTB) to dynamically balance temperature of servers via distributing clients\u27 service requests to servers. Next, (4) we propose CloudPowerCap, a power cap management system for virtualized cloud computing infrastructure. The novelty of CloudPowerCap lies in an integrated approach to coordinate power budget management and resource management in a cloud computing environment. Finally we expand our research to physical environment by exploring several fundamental problems of thermal and power management on buildings. We analyze spatial and temporal data acquired from an real-world auditorium instrumented by a multi-modal sensor network. We propose a data mining technique to determine the appropriate number and location of temperature sensors for estimating the spatiotemporal temperature distribution of the auditorium. Furthermore, we explore the potential energy savings that can be achieved through occupancy-based HVAC scheduling based on real occupancy data of the auditorium

Semantic Graph for Zero-Shot Learning

Zero-shot learning aims to classify visual objects without any training data via knowledge transfer between seen and unseen classes. This is typically achieved by exploring a semantic embedding space where the seen and unseen classes can be related. Previous works differ in what embedding space is used and how different classes and a test image can be related. In this paper, we utilize the annotation-free semantic word space for the former and focus on solving the latter issue of modeling relatedness. Specifically, in contrast to previous work which ignores the semantic relationships between seen classes and focus merely on those between seen and unseen classes, in this paper a novel approach based on a semantic graph is proposed to represent the relationships between all the seen and unseen class in a semantic word space. Based on this semantic graph, we design a special absorbing Markov chain process, in which each unseen class is viewed as an absorbing state. After incorporating one test image into the semantic graph, the absorbing probabilities from the test data to each unseen class can be effectively computed; and zero-shot classification can be achieved by finding the class label with the highest absorbing probability. The proposed model has a closed-form solution which is linear with respect to the number of test images. We demonstrate the effectiveness and computational efficiency of the proposed method over the state-of-the-arts on the AwA (animals with attributes) dataset.Comment: 9 pages, 5 figure