The Prospects for Hybrid Electric Vehicles, 2005-2020: Results of a Delphi Study

The introduction of Toyota's hybrid electric vehicle (HEV), the Prius, in Japan has generated considerable interest in HEV technology among US automotive experts. In a follow-up survey to Argonne National Laboratory's two-stage Delphi Study on electric and hybrid electric vehicles (EVs and HEVs) during 1994-1996, Argonne researchers gathered the latest opinions of automotive experts on the future ''top-selling'' HEV attributes and costs. The experts predicted that HEVs would have a spark-ignition gasoline engine as a power plant in 2005 and a fuel cell power plant by 2020. The projected 2020 fuel shares were about equal for gasoline and hydrogen, with methanol a distant third. In 2020, HEVs are predicted to have series-drive, moderate battery-alone range and cost significantly more than conventional vehicles (CVs). The HEV is projected to cost 66% more than a $20,000 CV initially and 33% more by 2020. Survey respondents view batteries as the component that contributes the most to the HEV cost increment. The mean projection for battery-alone range is 49 km in 2005, 70 km in 2010, and 92 km in 2020. Responding to a question relating to their personal vision of the most desirable HEV and its likely characteristics when introduced in the US market in the next decade, the experts predicted their ''vision'' HEV to have attributes very similar to those of the ''top-selling'' HEV. However, the ''vision'' HEV would cost significantly less. The experts projected attributes of three leading batteries for HEVs and projected acceleration times on battery power alone. The resulting battery packs are evaluated, and their initial and replacement costs are analyzed. These and several other opinions are summarized

Privacy Preservation using T-Closeness with Numerical Attributes

Data mining is a process that is used to retrieve the knowledgeable data from the large dataset. Information imparting around two associations will be basic done a large number requisition zones. As people are uploading their personal data over the internet, however the data collection and data distribution may lead to disclosure of their privacy. So, preserving the privacy of the sensitive data is the challenging task in data mining. Many organizations or hospitals are analyzing the medical data to predict the disease or symptoms of disease. So, before sharing data to other organization need to protect the patient personal data and for that need privacy preservation. In the recent year�s privacy preserving data mining has being received a large amount of attention in the research area. To achieve the expected goal various methods have been proposed. In this paper, to achieve this goal a pre-processing technique i.e. k-means clustering along with anonymization technique i.e. k-anonymization and t-closeness and done analysis which techniques achieves more information gain

The Evolutionary History Of Parthenogenetic Cnemidophorus Lemniscatus (Sauria: Teiidae). Ii. Maternal Origin And Age Inferred From Mitochondrial Dna Analyses

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137476/1/evo03814.pd

Estimates of daily oxygen consumption, carbon dioxide and methane emissions, and heat production for beef and dairy cattle using spot gas sampling

A simulation study was conducted to examine accuracy of estimating daily O2 consumption, CO2 and CH4 emissions, and heat production (HP) using a spot sampling technique and to determine optimal spot sampling frequency (FQ). Data were obtained from 3 experiments where daily O2 consumption, emissions of CO2 and CH4, and HP were measured using indirect calorimetry (respiration chamber or headbox system). Experiment 1 used 8 beef heifers (ad libitum feeding; gaseous exchanges measured every 30 min over 3 d in respiration chambers); Experiment 2 used 56 lactating Holstein-Friesian cows (restricted feeding; gaseous exchanges measured every 12 min over 3 d in respiration chambers); Experiment 3 used 12 lactating Jersey cows (ad libitum feeding; gaseous exchanges measured every hour for 1 d using headbox style chambers). Within experiment, averages of all measurements (FQALL) and averages of measurements selected at time points with 12, 8, 6, or 4 spot sampling FQ (i.e., sampling every 2, 3, 4, and 6 h in a 24-h cycle, respectively; FQ12, FQ8, FQ6, and FQ4, respectively) were compared. Within study a mixed model was used to compare gaseous exchanges and HP among FQALL, FQ12, FQ8, FQ6, and FQ4, and an interaction of dietary treatment by FQ was examined. A regression model was used to evaluate accuracy of spot sampling within study [i.e., FQALL (observed) vs. FQ12, FQ8, FQ6, or FQ4 (estimated)]. No interaction of diet by FQ was observed for any variables except for CH4 production in experiment 1. No FQ effect was observed for gaseous exchanges and HP except in experiment 2 where CO2 production was less (5,411 vs. 5,563 L/d) for FQ4 compared with FQALL, FQ12, and FQ8. A regression analysis between FQALL and each FQ within study showed that slopes and intercepts became farther from 1 and 0, respectively, for almost all variables as FQ decreased. Most variables for FQ12 and FQ8 had root mean square prediction error (RMSPE) less than 10% of the mean and concordance correlation coefficient (CCC) greater than 0.80, and RMSPE increased and CCC decreased as FQ decreased. When a regression analysis was conducted with combined data from the 3 experiments (mixed model with study as a random effect), results agreed with those from the analysis for the individual studies. Prediction errors increased and CCC decreased as FQ decreased. Generally, all the estimates from FQ12, FQ8, FQ6, and FQ4 had RMSPE less than 10% of the means and CCC greater than 0.90 except for FQ6 and FQ4 for O2 consumption and CH4 production. In conclusion, the spot sampling simulation with 3 indirect calorimetry experiments indicated that FQ of at least 8 samples (every 3 h in a 24-h cycle) was required to estimate daily O2 consumption, CO2 and CH4 production, and HP and to detect changes in those in response to dietary treatments. This sampling FQ may be considered when using techniques that measure spot gas exchanges such as the GreenFeed and face mask systems

Self-supervised generative adverrsarial network for depth estimation in laparoscopic images

Dense depth estimation and 3D reconstruction of a surgical scene are crucial steps in computer assisted surgery. Recent work has shown that depth estimation from a stereo image pair could be solved with convolutional neural networks. However, most recent depth estimation models were trained on datasets with per-pixel ground truth. Such data is especially rare for laparoscopic imaging, making it hard to apply supervised depth estimation to real surgical applications. To overcome this limitation, we propose SADepth, a new self-supervised depth estimation method based on Generative Adversarial Networks. It consists of an encoder-decoder generator and a discriminator to incorporate geometry constraints during training. Multi-scale outputs from the generator help to solve the local minima caused by the photometric reprojection loss, while the adversarial learning improves the framework generation quality. Extensive experiments on two public datasets show that SADepth outperforms recent state-of-the-art unsupervised methods by a large margin, and reduces the gap between supervised and unsupervised depth estimation in laparoscopic images

Analysis of major trends in U.S. commercial trucking, 1977-2002.

This report focuses on various major long-range (1977-2002) and intermediate-range (1982-2002) U.S. commercial trucking trends. The primary sources of data for this period were the U.S. Bureau of the Census Vehicle Inventory and Use Survey and Truck Inventory and Use Survey. In addition, selected 1977-2002 data from the U.S. Department of Energy/Energy Information Administration and from the U.S. Department of Transportation/Federal Highway Administration's Highway Statistics were used. The report analyzes (1) overall gasoline and diesel fuel consumption patterns by passenger vehicles and trucks and (2) the population changes and fuels used by all commercial truck classes by selected truck type (single unit or combination), during specified time periods, with cargo-hauling commercial trucks given special emphasis. It also assesses trends in selected vehicle miles traveled, gallons per vehicle miles traveled, and gallons per cargo ton-mile traveled, as well as the effect of cargo tons per truck on fuel consumption. In addition, the report examines long-range trends for related factors (e.g., long-haul mileages driven by heavy trucks) and their impacts on reducing fuel consumption per cargo-ton-mile and the relative shares of total commercial fuel use among truck classes. It identifies the effects of these trends on U.S. petroleum consumption. The report also discusses basic engineering design and performance, national legislation on interstate highway construction, national demographic trends (e.g., suburbanization), and changes in U.S. corporate operations requirements, and it highlights their impacts on both the long-distance hauling and shorter-distance urban and suburban delivery markets of the commercial trucking industry

A non-degenerate optical parametric oscillator as a high-flux source for quantum lithography

We investigate the use of a non-degenerate parametric oscillator (NDPO) as a source for quantum lithography, for which the light can have high-flux and strong non-classical features. This builds on the proposal of Boto, et al. [A. N. Boto, et al., PRL (85), 2733 (2000)], for etching simple patterns on multi-photon absorbing materials with sub-Rayleigh resolution, using special two-mode entangled states of light. An NDPO has two outgoing modes differentiated by polarization or direction of propagation, but sharing the same optical frequency. We derive analytical expressions for the multi-photon absorption rates when the NDPO is operated below, near, and above its threshold. The resulting interference patterns are characterized by an effective wavelength half that for the illuminating modes. We compare our results with those for the case of a high-gain optical amplifier source, and discuss the relative merit of the NDPO

Random matrix ensemble with random two-body interactions in presence of a mean-field for spin one boson systems

For $m$ number of bosons, carrying spin ($S$=1) degree of freedom, in $\Omega$ number of single particle orbitals, each triply degenerate, we introduce and analyze embedded Gaussian orthogonal ensemble of random matrices generated by random two-body interactions that are spin (S) scalar [BEGOE(2)-$S1$]. The embedding algebra is $U(3) \supset G \supset G1 \otimes SO(3)$ with SO(3) generating spin $S$. A method for constructing the ensembles in fixed-($m$, $S$) space has been developed. Numerical calculations show that the form of the fixed-($m$, $S$) density of states is close to Gaussian and level fluctuations follow GOE. Propagation formulas for the fixed-($m$, $S$) space energy centroids and spectral variances are derived for a general one plus two-body Hamiltonian preserving spin. In addition to these, we also introduce two different pairing symmetry algebras in the space defined by BEGOE(2)-$S1$ and the structure of ground states is studied for each paring symmetry.Comment: 22 pages, 6 figure

Electric and hybrid electric vehicles: A technology assessment based on a two-stage Delphi study

To address the uncertainty regarding future costs and operating attributes of electric and hybrid electric vehicles, a two stage, worldwide Delphi study was conducted. Expert opinions on vehicle attributes, current state of the technology, possible advancements, costs, and market penetration potential were sought for the years 2000, 2010, and 2020. Opinions related to such critical components as batteries, electric drive systems, and hybrid vehicle engines, as well as their respective technical and economic viabilities, were also obtained. This report contains descriptions of the survey methodology, analytical approach, and results of the analysis of survey data, together with a summary of other factors that will influence the degree of market success of electric and hybrid electric vehicle technologies. Responses by industry participants, the largest fraction among all the participating groups, are compared with the overall responses. An evaluation of changes between the two Delphi stages is also summarized. An analysis of battery replacement costs for various types is summarized, and variable operating costs for electric and hybrid vehicles are compared with those of conventional vehicles. A market penetration analysis is summarized, in which projected market shares from the survey are compared with predictions of shares on the basis of two market share projection models that use the cost and physical attributes provided by the survey. Finally, projections of market shares beyond the year 2020 are developed by use of constrained logit models of market shares, statistically fitted to the survey data