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Data collections

In addition to the data in Table 11.1, it is necessary to gather other information so that a complete analysis of performance can be conducted.2 [Pg.238]

Antisealant What product is being used, what is the dosage, and how is the dosage controlled Is flow proportional control being used  [Pg.239]

Particle monitors Particle monitors can be used to follow changes in the nature of the suspended solids in the feed water and throughout the pretreatment system. Do the monitors indicate a change in the number of particles of a given size This could indicate a change in source water quality or in the efficiency of the pretreatment. [Pg.239]

Input Data Raw water Feed Permeate Reject [Pg.286]

Already in an early stage of a project, starting to collect data of the physical (subsoil, bathymetry, waves, currents, wind) and environmental setting of the proposed reclamation site and borrow area is important. This information is not only required to support the feasibility study, but it will in later stages also be helpful to better plan successive site investigations. Some studies, like an Environmental Impact Assessment (EIA), may require much time to complete and should be started as soon as possible to avoid interference with the overall project planning. [Pg.14]

This implies that activities such as the determination of the referenee condition (existing situation before start of the reclamation works) have to commence in the project initiation phase. [Pg.15]

Data collection includes desk studies, field work and laboratory testing. During the project initiation phase the main focus will usually be on desk studies and pre-hminary field and laboratory operations. [Pg.15]

To proceed with a design, the designer must first assemble all the relevant facts and data required. For process design this will include information on possible processes, equipment performance, and physical property data. This stage can be one of the most time consuming, and frustrating, aspects of design. Sources of process information and physical properties are reviewed in Chapter 8. [Pg.3]

The national standards are also sources of design methods and data they are also design constraints. [Pg.3]

The constraints, particularly the external constraints, should be identified early in the design process. [Pg.3]

The HGCA glossary describes this as the gathering of information on fields and crops in digital form by sensors, in addition to data collected manually or visually . Even the data collected manually or visually need to be entered digitally eventually, so that they can be used by the software. [Pg.239]

In all cases it is important to understand that the technology must be used in conjunction with other data, such as field history, weather records and geology maps. Ground tmthing is also important - RGB images may hint at a compaction problem but the farmer will still have to dig a hole to confirm this  [Pg.240]

The survey was sent to 446 employees overall in four firms (see Table 21 for distribution between firms). The data collection phase lasted one month for each firm and took place in 2011. After two weeks, a reminder was sent to the employees. 173 responses could be collected, which yielded an overall response rate of 38,8%. Of these responses, 24 were discarded, as they were not filled out to a sufficient degree. This left 149 valid answers for the anafysis. These 149 responses were full responses with no missing data in the focal constructs of the study. Some of the questions, which were sensible (e.g job satisfaction) were optional, and were not provided by all of the respondents. [Pg.126]

The full response rate is rather high. Yet 1 used the procedure suggested by Armstrong and Overton (19773 lo check. If the population of non-respondents was different from the respondents. I split my samples into half into early respondents and late respondents for each firm. I then used t-test to compare the samples. As there were no significant differences for each construct Qevel of significance 5%), 1 assume that there is no bias due to non-respondents. [Pg.127]

All of the main constructs employed in this study were constructs that have been used in literature before and have shown good psychometric properties, i.e. high reliability and validity (Nunnally and Bernstein 1994). As this work is located at the intersection of user innovation and organizational behavior, both of these research fields were analyzed to choose appropriate measurement instruments. With respect to the [Pg.127]

The indexing procedure we have just discussed has provided us with information on the unit cell, and thus the Bravais lattiee. Taking the symmetry of the diffraction pattern, the so-called Laue group (Table 10.1), into account, we ean now determine whieh reflections have to be measured, and which reflections are equivalent by symmetry. For instance. Table 10.1 shows that for the triclinic system the Laue group is 1, i.e. the diffraction pattern is centrosymmetrie and only half the reflections have to be examined for a monoclinie crystal the Laue group is 2/m, i.e. the diffraction pattern has two elements of two-fold symmetry and consequently only a quarter of the reflections are needed. In the monochnic case we have to measure all [Pg.337]

The first step is to collect pertinent information to the process, including a process flow sheet, produet information and completion of a typical questionnaire, as shown in Table 2. [Pg.563]

Knowledge of the most critical aspect of the process can guide the sometimes difficult selection process. For example, the requirement of a very dry product with strict impurity levels suggests a filtering centrifuge. A product with a feed rate of 150 gpm, without wash requirements, would lead us to a continuous sedimentation centrifuge. [Pg.563]

A simple Buchner funnel test will indicate fast, medium or slow filtration. Slow filtering materials that have inordinate quantities of particles passing the filter paper will be submicron and difficult to capture in a filtering system. Therefore, a sedimentation centrifuge should be considered. [Pg.563]

A phenomenon called cake cracking can occur and will be evident in this simple test. Not all materials exhibit this. It depends upon the surface tension of the product and its tendency to shrink as dewatering occurs. Amorphous, thixotropic materials will exhibit this more than rigid solids. [Pg.563]

Cake compressibility is the ability of a cake to reduce its volume, i.e., porosity, when stress is applied. The resulting cake will display an increase in hydraulic resistance. This is not necessarily caused by an average change in porosity, as a porosity gradient can occur by the redistribution of the solid material. Rigid granular particles tend to be incompressible and filter well even with thick cakes. Materials that are easily deformed such as amorphous or thixotropic materials will respond well to mechanical pressure or operation with thin cakes. (See Ch. 6 on Cake Compressibility.) [Pg.565]

Twenty-six interviews were corrducted from April through June 2007. Irrterviews lasted from 50 to 90 min (typically 80-90 rrrin), and each was tape recorded. Interviews were organized as in-depth, serrri-stractured corrversahons in which the [Pg.382]

Sampling frame Demographics included Rank/positions included [Pg.383]

Academic Male, female currently working across the country (inside and outside of Tunis) Tenured faculty, untenured faculty, visiting faculty from France, USA university founders/directors research group and lab directors directors of studies preparatory high school directors faculty with and without international experience, either studying and/or working abroad (USA, France, Germany, Canada) deans [Pg.383]

Government Male based in Tunis Industry liaisons, trade association directors, national utilities directors, ministry officials [Pg.383]

Industry Male, female Tunis Industry advisors for apprenticed students technical managers company associate directors CEOs practicing engineering project directors (subdiscipline of construction) [Pg.383]

As mentioned in Section 5.1, SIMS is a highly diverse micro-analytical technique, possibly the most diverse. This diversity, even noted when restricting the discussion to commercially available instruments, covers the capabilities provided and the freedom in instrumental parameters available. As an example, almost all commercially available SIMS instruments contain two or more primary ion guns and are aU able to collect secondary ion spectra in either the positive or the negative polarities. In addition, there are almost always multiple signals from which to choose from for following a specific element or molecule. In some cases, these may be summed. In short, one or more of the following may be collected  [Pg.215]

Atomic positive or negative secondary ions. These are collected when best sensitivity/detection limits are required. Note There also exist element-specific methodologies with some examples including the collection of dimer ions, i.e. SiN when Nitrogen in Silicon is of interest, the use of O2 leak conditions for increasing the sensitivity/detection limits for metal ions, etc. [Pg.215]

Cs cluster secondary ions (MCs where M represents some electropositive element, or MCs2 where M represents some electronegative element). This is used when the matrix effects present need to be minimized, albeit at the cost of sensitivity/detection limits. Note Cs primary ion impact is required [Pg.215]

Molecular positive or negative secondary ions representative of the molecular distributions of interest. Cationized positive secondary ions (the cation can be Hydrogen, a specific F row transition metal, or some alkali metal) may also be recorded as these can resirlt in improved sensitivity/detection limits [Pg.215]

In some cases, there does not appear any clear systematics to the choice of the conditions or the secondary ions used. This is partially a result of the diverse community that utilizes SIMS and the channel by which the respective methodologies were developed. In any case, much of this information is available in journal publications and/or in texts specific to the area of application. Some texts from the various areas in which SIMS is commonly applied include Wilson et al. 1986 Riviere and Myhra 2009 Fayek et al. 2009 Mahoney 2013. Note As the appUcation of SIMS to the Biosciences is rapidly expanding/changing, the reader is also advised to access the most recent literature for the latest methodologies, many of which are sample specific. [Pg.215]

We first focus on criteria developed from feedback-control theory. Efficient control requires a reliable measurement and feedback of performance. Reliability is here defined as the extent to which repeated measurements give the same results. A reliable reporting and counting of accidents is important if the frequency of accidents (number of accidents per one milHon hours of work) is used as a measure of the SHE performance of the company or department in qnestion. Another example has to do with whether different investigators who look into the same accident will come up with the same results concerning causal factors (intra-observer reliability). [Pg.137]

The documented facts about accident risks must be accurate in relation to the factual circumstances. Reliable documentation is not necessarily accurate. We may have systematic errors due to some common misconception of the nature of accidents. Or our data may be contaminated by extraneous factors such as rumours or direct manipulation. [Pg.137]

The requirement for adequate coverage comes from Ashby s law of requisite variety. To exercise efficient control, we must receive data on the different technical, organisational and human factors that affect the risk of accidents and are controllable through management decisions. It also means that data collection must be flexible enough to handle unexpected threats and changes. [Pg.137]


Gmehling, J., and U. Onken "Vapor-Liquid Equilibrium Data Collection," DECHEMA Chemistry Data Ser., Vol. 1 (1-10), Frankfurt, 1977. [Pg.8]

Comprehensive data collection for more than 6000 binary and multicomponent mixtures at moderate pressures. Data correlation and consistency tests are given for each data set. [Pg.8]

The prediction of the size and permeability of the aquifer is usually difficult, since there is typically little data collected in the water column exploration and appraisal wells are usually targeted at locating oil. Hence the prediction of aquifer response often remains a major uncertainty during reservoir development planning. In order to see the reaction of an aquifer, it is necessary to produce from the oil column, and measure the response in terms of reservoir pressure and fluid contact movement use is made of the material balance technique to determine the contribution to pressure support made by the aquifer. Typically 5% of the STOMP must be produced to measure the response this may take a number of years. [Pg.191]

The same general comments hold as for Unit 3. Figure 7 provides an example of the AE monitoring data collected from 19.06.97 to 16.07.97, in terms of the main plant parameters vs time (fig. 7a), as well as of the AE RMS values (fig. 7b). [Pg.78]

A new one-dimensional mierowave imaging approaeh based on suecessive reeonstruetion of dielectrie interfaees is described. The reconstruction is obtained using the complex reflection coefficient data collected over some standard waveguide band. The problem is considered in terms of the optical path length to ensure better convergence of the iterative procedure. Then, the reverse coordinate transformation to the final profile is applied. The method is valid for highly contrasted discontinuous profiles and shows low sensitivity to the practical measurement error. Some numerical examples are presented. [Pg.127]

There is a two-step process to predict the detectable detail - object diameter diagram. The optimal data collection parameter settings to maximise SNRAproj for the defect to the surrounding material - Optimal... [Pg.213]

There are some theoretical developments and practical implementations of methods, allowing to solve 3D reconstruction problem. They differ on their technical characteristics, scheme of data collecting and processing, qualitative results of the obtained images. [Pg.216]

In Dynamic Spatial Reconstructor at the expense of use 2D matrix of detectors there was the opportunity to use a divergent cone beam of source emission. This system had a number of lacks. In particular the number of projections is rigidly limited by the number of x-ray sources. The dispersion of source emission results in errors of data collected.. However the system confirmed basic advantages of application of conic beams and 2D matrices of detectors for collecting information about 3D object. [Pg.217]

Note some particularities of new USCT method. At first, data collection and search of areas with anomalous (inhomogeneous)SD of acoustic parameters (velocities of spreading of US waves) is joined. As a sought image, on which anomalies is revealed, it is offered total image B (r), which practically is the low frequency copy of restored fimction g(f). As PMF SD of... [Pg.251]

Another feature is a repositioning program (Repos.exe) which is used for the purpose of correcting positioning data collected when scanning on a pipe elbow or when scanning is performed with the microphone collar mounted on the elbow itself... [Pg.864]

An experienced inspection engineer will attempt to identify the characteristics of a given structure to determine potential. specific critical damage mechanisms. No individual major concrete structure can be adequately analysed by simple mass-accumulation of data and using criteria, which are based on standard codes. This does not mean that either data-collection or available criteria are not useful, but they should be exercised with care and flexibility and the procedures for inspection customised for the given structure. [Pg.997]

It is clear from our discussion of contact angle hysteresis that there is some degree of variability in reported contact angle values. The data collected in Table X-2, therefore, are intended mainly as a guide to the type of behavior to be expected. The older data comprise mainly results for refractory and relatively polar solids, while newer data are for polymeric surfaces. [Pg.364]

Figure C3.1.2. Stopped-flow apparatus with motor-driven syringes. Syringe plungers force tire reactants A and B tlirough a mixing chamber into a spectral cell. Kinetic data collection begins when tire effluent syringe plunger is pushed out to contact an activation switch, about a millisecond after tire initiation of mixing. (Adapted from Pilling M J and Seakins P W 1995 Reaction Kinetics (Oxford Oxford University Press)... Figure C3.1.2. Stopped-flow apparatus with motor-driven syringes. Syringe plungers force tire reactants A and B tlirough a mixing chamber into a spectral cell. Kinetic data collection begins when tire effluent syringe plunger is pushed out to contact an activation switch, about a millisecond after tire initiation of mixing. (Adapted from Pilling M J and Seakins P W 1995 Reaction Kinetics (Oxford Oxford University Press)...
Figure C3.2.4. Plot of the log of photocurrent against number of methyl units in a alkylsilane based monolayer self-assembled on a n silicon electrode. The electrode is immersed in a solution witli an electron donor. Best fits of experimental data collected at different light intensities ( ) 0.3 mW cm ( ) 0.05 mW cm. From [10]. Figure C3.2.4. Plot of the log of photocurrent against number of methyl units in a alkylsilane based monolayer self-assembled on a n silicon electrode. The electrode is immersed in a solution witli an electron donor. Best fits of experimental data collected at different light intensities ( ) 0.3 mW cm ( ) 0.05 mW cm. From [10].
A rn uleculur dynam ics si in illation can li ave tli rcc distinct time and teiTi pcratii re periods h eating, simulation (niri). an d eoolin g. If yon wan t to meast re equilibrium properties of a molectilar system. yon can divide til e sitn 11 lation period into two parts equilibration and data collection. ... [Pg.73]

In many molecular dynamics simulations, equilibration is a separate step that precedes data collection. Equilibration is generally necessary lo avoid introducing artifacts during the healing step an d to en su re th at the trajectory is aciii ally sim u laiin g eq u i librium properties. The period required for equilibration depends on the property of Interest and the molecular system. It may take about 100 ps for the system to approach equilibrium, but some properties are fairly stable after 1 0-20 ps. Suggested tim es range from. 5 ps to nearly 100 ps for medium-si/ed proteins. [Pg.74]

Th e sim u lation or run tim e m eludes time for the system lo equilibrate at Ibe simulation temperature plus tbe time for data collection, while the trajectory evolves. Simulation timesdepend on the time scale of tbc property you are investigating. [Pg.88]

HyperChem run s the molecular dynain ics trajectory, averaging and analyzing a trajectory and creating the Cartesian coordinates and velocities, fhe period for reporting these coordinates and velocities is th e data collection period. At-2. It is a m iiltiplc of the basic time step. At = ii At], and is also referred to as a data step. The value 1I2 is set in the Molecular Dynamics options dialog box. [Pg.318]

At, etc. The Snapshot period is specified 111 the Snapshot dialog bo by n, data steps, i.e. as a ni ii Itiple of the data collection period, At4 = n4 i3t2. [Pg.319]

TlyperCi hem updates the screen diirin g a trajectory at regular in ter-vals so yon can visiiali/e the irajectory. Since this screen update may slow down a trajectory If it occurs too frequently, yon c.an specify the duration of the Screen Refresh period At.,. The screen updates at ilines tQ, Iq + Atj, to + 2Atj, etc. The Screen Refresh period is specified in the Molecular Dynamics options dialog box by n 5 data steps, i.e. as a m iiliiplc of the data collection period, At5 = n 5 At2-... [Pg.319]

To reach equilibrium temperature quickly before starting the equilibration phase of a simulation (see Equilibration and Data Collection on page 74). [Pg.72]

Amolecular dynamics simulation can have three distinct time and temperature periods heating, simulation (run), and cooling. If you want to measure equilibrium properties of a molecular system, you can divide the simulation period into two parts equilibration and data collection. [Pg.73]


See other pages where Data collections is mentioned: [Pg.65]    [Pg.208]    [Pg.210]    [Pg.210]    [Pg.252]    [Pg.1382]    [Pg.1590]    [Pg.1629]    [Pg.1635]    [Pg.1806]    [Pg.1859]    [Pg.2829]    [Pg.2956]    [Pg.228]    [Pg.275]    [Pg.72]    [Pg.74]    [Pg.318]    [Pg.318]    [Pg.24]    [Pg.118]    [Pg.565]    [Pg.74]    [Pg.318]    [Pg.318]   
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An Overview of Data Collection Systems

Ancillary data collection

Automated data collection

Automatic Measurement and Data Collection

Automatic data collection

Biological Sample Preparation and Modes of Data Collection

Booklists special data collections

COLLECTION AND ANALYSIS OF RATE DATA

COLLECTION OF KINETIC DATA

Carbides data collection

Case studies high resolution data collection

Circular dichroism data collection

Clinical trials data collection

Clinical trials data collection/management

Clinical trials documentation data collection

Collect Good Data

Collect Online Data for the Whole Operation Cycle

Collect Supply Chain Network Data

Collect and Analyze Historical Data (Timeline)

Collecting Data The Case Report Form

Collecting Safety-Related Data

Collection and evaluation of data

Collection incident data

Collection of Field and Laboratory Data

Collection of accident and incident data

Collection of data

Collection of rate data

Collections of critically evaluated data

Conductivity data collection

Continuous scan data collection

Criteria for collecting kinetic data

Crystal data collection

Crystal structure analysis data collection

Crystallography data collection

Cultural factors data collection

DECHEMA data collection

DECHEMA vapor—liquid equilibrium data collection

DECHEMA vapour-liquid equilibrium data collection

DECHEMA-vapour-liquid data collection

Data Collection During Drilling

Data Collection and Computer Treatment

Data Collection and Interpretation

Data Collection and Management

Data collection (see Chapter

Data collection accuracy required

Data collection analysis and reporting

Data collection and analysis

Data collection and processing

Data collection and reporting system

Data collection centring crystals

Data collection change analysis

Data collection checklist developed from

Data collection chemical processing industry

Data collection defined

Data collection definitions

Data collection design approach

Data collection detector delay

Data collection diffraction

Data collection evaluation

Data collection for dredgeability assessment

Data collection for quality assessment

Data collection for quantity assessment

Data collection form

Data collection forms design

Data collection from crystals

Data collection generally

Data collection high-throughput

Data collection image plate detectors

Data collection in the borrow area

Data collection incident reporting systems

Data collection information provided

Data collection interpretation

Data collection major incident analysis

Data collection methodologies

Data collection methods

Data collection monochromatic

Data collection multiple-factor approach

Data collection multiple-wavelength anomalous

Data collection near miss reporting system

Data collection on a conventional X-ray source with an area detector (including tabulated cases) and relationship to synchrotron radiation

Data collection organizational factors

Data collection overview

Data collection passive approaches

Data collection phase

Data collection primary monitoring variables

Data collection procedures

Data collection protocol

Data collection reporting form design

Data collection ribosome

Data collection root cause analysis system

Data collection scale

Data collection software tools

Data collection soil mapping

Data collection step

Data collection subjects

Data collection system

Data collection system types

Data collection system, laser

Data collection systems, generally

Data collection terms Links

Data collection virus

Data collection virus crystals

Data collection weather

Data collection with integrity

Data collection yield mapping

Data collection yield monitors

Data collection, catalyst performance

Data collection, catalyst performance testing

Data collection, hard material propertie

Data collection, liquid-solid interfaces

Data collection, protein crystallography

Data collection, quantum mechanics

Data collection, reduction, and analysis

Data collection, speed

Data collection/analysis

Data collection/analysis pilot plant

Data collection/analysis quality control

Data collection/analysis safety

Data collection/analysis types

Data collection/retrieval systems

Databases trial data collection

Density data collection

Detectors data collection

Differential scanning calorimetry data collection

Diffraction methods data collection

Diffraction pattern data collection

Diffraction patterns data collection from

Direct data collection

Document analysis, data collection

Electric data collection

Electronic data collection

Enable processes data collection management

Enthalpy data collection

Equilibration and Data Collection

Ethical issues data collection

Example of Data Collection, Evaluation, and Processing

Existing chemicals data collection

Exposure time, data collection

FTIR, attenuated total reflectance data collection

Feedback data collection

Filters and barriers in data collection

Fluorescence spectroscopy data collection

Forms for Collecting Data

Gender data collection

Hazard assessment data collection

High data collection

Impact evaluation data collection

Implementation and data collection

Implementation, data collection system

Infrared data collection

Internal systems for collecting and analysing incident data

Interviews, data collection

Interviews, data collection qualitative research

Lattice data collection

Life cycle assessment data collection

Life-cycle inventory data collection

Liquid data collection

Low temperature data collection

Lysozyme data collection

Manage Data Collection

Mass spectrometry data collection

Material data collection

Mechanical data collection

Melting data collection

Methods for collecting near miss data

Monitoring data collection system

Near miss reporting system data collection systems

Neutron reflection data collection

Nitrides data collection

Nuclear Electronics and Data Collection

Nuclear magnetic resonance data collection

PS Collection Data

Patient data collection

Pharmacokinetic data, collection

Phases I— data collection

Physical data collection

Plant data collection

Practical approach to experimental impedance data collection and analysis

Production data collection

Pulse Fourier transform spectrometer data collection

Purposes of collecting and analysing near miss data

Qualitative research designs data collection

Quality control data collection forms

Quantitative human reliability data collection system

Questionnaire Development and Data Collection

Questionnaires data collection

Radiation data collection

Rate data collection and analysis

Reporting form design, data collection methods

Resistivity data collection

Retrieval methods, data collection

Safety data collection

Sampling and data collection

Services utilization data, collection

Short wavelength data collection

Single crystals data collection

Site-directed mutagenesis data collection

Skill 1.3. Observation and Data Collection

Skill 1.4 Understanding procedures for collecting and interpreting data to minimize bias

Solubility equilibrium data collection

Space groups data collection

Spectral data collection

Spectroscopic databases data collections

Stage 3 Collect data

Statistical data collection

Statistical process control data collection

Step data collection sequence

Step scan data collection

Storage methods, data collection

Structure dereplication data collection

Supply chain network data collection

Surveillance systems data collection

Symmetry and the strategy of collecting data

Synchrotron data collection

Synchrotrons data collection from

The Data Collection Period

Thermal data collection

Time-array detection data collection

Transmission electron microscopy data collection

Transportation issues data collection

Types of Data Collected

Types of Data Collection Systems

Understanding the FDA Data Collection Process

Validation data collection

What type of data should be collected

X-ray crystallography data collection

X-ray data collection

X-ray diffraction data collecting

Young data collection

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