Hvac Supply Air Optimization Using Evolutionary Algorithms

Heating, ventilation, and air-conditioning account for a vast majority of energy consumption in the residential and commercial sectors. Intelligent energy management control system (EMCS) in buildings offers an excellent means of reducing energy consumption in heating, ventilation, and air-conditioning (HVAC) systems while maintaining or improving indoor environmental conditions. This can be achieved through the use of computational intelligence and optimization. This project proposes and evaluates a model-based optimization process for HVAC systems using an evolutionary algorithm. The process can be integrated into the EMCS to perform several intelligent functions and achieve optimal whole-system performance. The proposed process addresses the requirements of the latest ASHRAE Standard 62.1. A whole building simulation energy software is used to generate the sub hourly load. The simulations are performed to test the process and determine the potential energy savings achieved. In addition, simulations were conducted at peak load on July 15th and partial load on April 10th to observe the effects of genetic algorithm (GA). Through artificial intelligence utilization, the energy consumption can be better managed. Building controls are like living organisms which can be treated much like evolutionary biology during programming. The single-objective GA optimization and modernized ventilation codes have demonstrated that total energy consumed by the HVAC system can be reduced by 30.6% for the air side distribution

Hvac Supply Air Optimization Using Evolutionary Algorithms

Heating, ventilation, and air-conditioning account for a vast majority of energy consumption in the residential and commercial sectors. Intelligent energy management control system (EMCS) in buildings offers an excellent means of reducing energy consumption in heating, ventilation, and air-conditioning (HVAC) systems while maintaining or improving indoor environmental conditions. This can be achieved through the use of computational intelligence and optimization. This project proposes and evaluates a model-based optimization process for HVAC systems using an evolutionary algorithm. The process can be integrated into the EMCS to perform several intelligent functions and achieve optimal whole-system performance. The proposed process addresses the requirements of the latest ASHRAE Standard 62.1. A whole building simulation energy software is used to generate the sub hourly load. The simulations are performed to test the process and determine the potential energy savings achieved. In addition, simulations were conducted at peak load on July 15th and partial load on April 10th to observe the effects of genetic algorithm (GA). Through artificial intelligence utilization, the energy consumption can be better managed. Building controls are like living organisms which can be treated much like evolutionary biology during programming. The single-objective GA optimization and modernized ventilation codes have demonstrated that total energy consumed by the HVAC system can be reduced by 30.6% for the air side distribution

Power Optimization With BLER Constraint for Wireless Fronthauls in C-RAN

Cloud radio access network (C-RAN) is a novel architecture for future mobile networks to sustain the exponential traffic growth thanks to the exploitation of centralized processing. In C-RAN, one data processing center or baseband unit (BBU) communicates with users via distributed remote radio heads (RRHs), which are connected to the BBU via high capacity, low latency fronthaul links. In this letter, we study C-RAN with wireless fronthauls due to their flexibility in deployment and management. First, a tight upper bound of the system block error rate (BLER) is derived in closed-form expression via union bound analysis. Based on the derived bound, adaptive transmission schemes are proposed. Particularly, two practical power optimizations based on the BLER and pair-wise error probability (PEP) are proposed to minimize the consumed energy at the RRHs while satisfying the predefined quality of service (QoS) constraint. The premise of the proposed schemes originates from practical scenarios where most applications tolerate a certain QoS, e.g., a nonzero BLER. The effectiveness of the proposed schemes is demonstrated via intensive simulations

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

CMB-HD: an Ultra-Deep, High-Resolution Millimeter-Wave Survey over Half the Sky

A millimeter-wave survey over half the sky, that spans frequencies in the range of 30 to 350 gigahertz, and that is both an order of magnitude deeper and of higher-resolution than currently funded surveys would yield an enormous gain in understanding of both fundamental physics and astrophysics. By providing such a deep, high-resolution millimeter-wave survey (about 0.5 microK-arcminutes noise and 15 arcseconds resolution at 150 gigahertz), CMB-HD (Cosmic Microwave Background - Henry Draper catalog entry) will enable major advances. It will allow 1) the use of gravitational lensing of the primordial microwave background to map the distribution of matter on small scales (k approximately equal to 10 h per megaparsec), which probes dark matter particle properties. It will also allow 2) measurements of the thermal and kinetic Sunyaev-Zeldovich effects on small scales to map the gas density and gas pressure profiles of halos over a wide field, which probes galaxy evolution and cluster astrophysics. In addition, CMB-HD would allow us to cross critical thresholds in fundamental physics: 3) ruling out or detecting any new, light (less than 0.1 electronvolts), thermal particles, which could potentially be the dark matter, and 4) testing a wide class of multi-field models that could explain an epoch of inflation in the early Universe. Such a survey would also 5) monitor the transient sky by mapping the full observing region every few days, which opens a new window on gamma-ray bursts, novae, fast radio bursts, and variable active galactic nuclei. Moreover, CMB-HD would 6) provide a census of planets, dwarf planets, and asteroids in the outer Solar System, and 7) enable the detection of exo-Oort clouds around other solar systems, shedding light on planet formation. The combination of CMB-HD with contemporary ground and space-based experiments will also provide powerful synergies. CMB-HD will deliver this survey in 5 years of observing 20,000 square degrees, using two new 30-meter-class off-axis cross-Dragone telescopes to be located at Cerro Toco in the Atacama Desert. The telescopes will field about 2.4 million detectors (600,000 pixels) in total. The CMB-HD survey will be made publicly available, with usability and accessibility a priority

Basic Atomic Physics

Contains reports on five research projects.Joint Services Electronics Program Grant DAAH04-95-1-0038National Science Foundation Grant PHY 92-21489U.S. Navy - Office of Naval Research Grant N00014-90-J-1322National Science Foundation Grant PHY95-14795Charles S. Draper Laboratory Contract DL-H-484775U.S. Army Research Office Contract DAAH04-94-G-0170U.S. Army Research Office Contract DAAH04-95-1-0533U.S. Navy - Office of Naval Research Contract N00014-89-J-1207U.S. Navy - Office of Naval Research Contract N000014-96-1-0432David and Lucile Packard Foundation Grant 96-5158National Science Foundation Grant PHY95-01984U.S. Army - Office of ResearchU.S. Navy - Office of Naval Research Contract N00014-96-1-0485U.S. Navy - Office of Naval Research AASERT N00014-94-1-080