946 resultados para Search, Right of.
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Translation of: Sur la visite des vaisseaux neutres sous convoi.
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Sabin 69691.
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Errata inserted after title page.
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This manual summarizes the roadside tree and brush control methods used by all of Iowa's 99 counties. It is based on interviews conducted in Spring 2002 with county engineers, roadside managers and others. The target audience of this manual is the novice county engineer or roadside manager. Iowa law is nearly silent on roadside tree and brush control, so individual counties have been left to decide on the level of control they want to achieve and maintain. Different solutions have been developed but the goal of every county remains the same: to provide safe roads for the traveling public. Counties in eastern and southern Iowa appear to face the greatest brush control challenge. Most control efforts can be divided into two categories: mechanical and chemical. Mechanical control includes cutting tools and supporting equipment. A chain saw is the most widely used cutting tool. Tractor mounted boom mowers and brush cutters are used to prune miles of brush but have significant safety and aesthetic limitations and boom mowers are easily broken by inexperienced operators. The advent of tree shears and hydraulic thumbs offer unprecedented versatility. Bulldozers are often considered a method of last resort since they reduce large areas to bare ground. Any chipper that violently grabs brush should not be used. Chemical control is the application of herbicide to different parts of a plant: foliar spray is applied to leaves; basal bark spray is applied to the tree trunk; a cut stump treatment is applied to the cambium ring of a cut surface. There is reluctance by many to apply herbicide into the air due to drift concerns. One-third of Iowa counties do not use foliar spray. By contrast, several accepted control methods are directed toward the ground. Freshly cut stumps should be treated to prevent resprouting. Basal bark spray is highly effective in sensitive areas such as near houses. Interest in chemical control is slowly increasing as herbicides and application methods are refined. Fall burning, a third, distinctly separate technique is underused as a brush control method and can be effective if timed correctly. In all, control methods tend to reflect agricultural patterns in a county. The use of chain saws and foliar sprays tends to increase in counties where row crops predominate, and boom mowing tends to increase in counties where grassland predominates. For counties with light to moderate roadside brush, rotational maintenance is the key to effective control. The most comprehensive approach to control is to implement an integrated roadside vegetation management (IRVM) program. An IRVM program is usually directed by a Roadside Manager whose duties may be shared with another position. Funding for control programs comes from the Rural Services Basic portion of a county's budget. The average annual county brush control budget is about $76,000. That figure is thought not to include shared expenses such as fuel and buildings. Start up costs for an IRVM program are less if an existing control program is converted. In addition, IRVM budgets from three different northeastern Iowa counties are offered for comparison in this manual. The manual also includes a chapter on temporary traffic control in rural work zones, a summary of the Iowa Code as it relates to brush control, and rules on avoiding seasonal disturbance of the endangered Indiana bat. Appendices summarize survey and forest cover data, an equipment inventory, sample forms for record keeping, a sample brush control policy, a few legal opinions, a literature search, and a glossary.
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"A transcript of lectures and discussions relative to the law of search and seizures and its effect on law enforcement, conducted by the U.S. Attorney's Office of the District of Columbia in cooperation with the Metropolitan Police Department, Washington, D.C."
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The image reconstruction using the EIT (Electrical Impedance Tomography) technique is a nonlinear and ill-posed inverse problem which demands a powerful direct or iterative method. A typical approach for solving the problem is to minimize an error functional using an iterative method. In this case, an initial solution close enough to the global minimum is mandatory to ensure the convergence to the correct minimum in an appropriate time interval. The aim of this paper is to present a new, simple and low cost technique (quadrant-searching) to reduce the search space and consequently to obtain an initial solution of the inverse problem of EIT. This technique calculates the error functional for four different contrast distributions placing a large prospective inclusion in the four quadrants of the domain. Comparing the four values of the error functional it is possible to get conclusions about the internal electric contrast. For this purpose, initially we performed tests to assess the accuracy of the BEM (Boundary Element Method) when applied to the direct problem of the EIT and to verify the behavior of error functional surface in the search space. Finally, numerical tests have been performed to verify the new technique.
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This paper advances a highly tractable model with search theoretic foundations for money and neoclassical growth. In the model, manufacturingand commerce are distinct and separate activities. In manufacturing,goods are efficiently produced combining capital and labor. In commerce,goods are exchanged in bilateral meetings. The model is applied to studythe effects of inßation on capital accumulation and welfare. With realisticparameters, inflation has large negative effects on welfare even though itraises capital and output. In contrast, with cash-in-advance, a deviceinformally motivated with bilateral trading, inflation depresses capitaland output and has a negligible effect on welfare.
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The Attorney General’s Consumer Protection Division receives hundreds of calls and consumer complaints every year. Follow these tips to avoid unexpected expense and disappointments. This record is about:Consumer “Private Right of Action” -- What Consumers Need to Know
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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.
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Includes bibliography