scholarly journals STUDI PERAMBATAN KESALAHAN SISTEMATIS LUAS LAHAN PARKIR KAMPUS MENGGUNAKAN PENDEKATAN LUAS SEGITIGA SEMBARANG

2019 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Hendro Supratikno ◽  
David Premana
Keyword(s):  
Systematic Error ◽  
Error Propagation ◽  
Measurement Data ◽  
Systematic Errors ◽  
Random Errors ◽  
Land Area ◽  
Parking Lots ◽  
Parking Lot ◽  
Data Error ◽  
Definition Of

Parking is a condition of not moving a vehicle that is temporary because it was abandoned by the driver. Included in the definition of parking is every vehicle that stops at certain places whether stated by traffic signs or not, and not solely for the benefit of raising and / or lowering people and / or goods.Campus 3 Lumajang State Community Academy has facilities and infrastructure prepared by the Lumajang Regency government. However, the parking lots provided cannot accommodate vehicles optimally because of the ratio of the number of vehicles and the area of the parking area that is not appropriate. This is because the area of the parking lot is not analyzed by data error when measuring.Each measurement data is assumed to have errors both systematic errors, random errors, and large errors (blunders), so that in the measurement of parking lots certainly there are errors. From this the authors intend to conduct research to find out how the propagation of systematic errors and the large systematic errors of the area of campus parking lot 3 Lumajang Community Academy.The methods used in this study include preparing materials and tools, making land sketches, decomposing them, determining distances using theodolite, determining land area equations, and finding systematic error propagation. So that the final goal in this study is to find large systematic errors in the parking area of Campus 3 of the Lumajang State Community Academy

scholarly journals Towards space based verification of CO<sub>2</sub> emissions from strong localized sources: fossil fuel power plant emissions as seen by a CarbonSat constellation

2011 ◽  
Vol 4 (4) ◽  
pp. 5147-5182
Author(s):  
V. A. Velazco ◽  
M. Buchwitz ◽  
H. Bovensmann ◽  
M. Reuter ◽  
O. Schneising ◽  
...  
Keyword(s):  
Power Plant ◽  
Systematic Error ◽  
Co2 Emissions ◽  
Power Plants ◽  
Fossil Fuel ◽  
Systematic Errors ◽  
Random Errors ◽  
Power Plant Emissions ◽  
Global Coverage ◽  
Plant Emissions

Abstract. Carbon dioxide (CO2) is the most important man-made greenhouse gas (GHG) that cause global warming. With electricity generation through fossil-fuel power plants now as the economic sector with the largest source of CO2, power plant emissions monitoring has become more important than ever in the fight against global warming. In a previous study done by Bovensmann et al. (2010), random and systematic errors of power plant CO2 emissions have been quantified using a single overpass from a proposed CarbonSat instrument. In this study, we quantify errors of power plant annual emission estimates from a hypothetical CarbonSat and constellations of several CarbonSats while taking into account that power plant CO2 emissions are time-dependent. Our focus is on estimating systematic errors arising from the sparse temporal sampling as well as random errors that are primarily dependent on wind speeds. We used hourly emissions data from the US Environmental Protection Agency (EPA) combined with assimilated and re-analyzed meteorological fields from the National Centers of Environmental Prediction (NCEP). CarbonSat orbits were simulated as a sun-synchronous low-earth orbiting satellite (LEO) with an 828-km orbit height, local time ascending node (LTAN) of 13:30 (01:30 p.m.) and achieves global coverage after 5 days. We show, that despite the variability of the power plant emissions and the limited satellite overpasses, one CarbonSat can verify reported US annual CO2 emissions from large power plants (≥5 Mt CO2 yr−1) with a systematic error of less than ~4.9 % for 50 % of all the power plants. For 90 % of all the power plants, the systematic error was less than ~12.4 %. We additionally investigated two different satellite configurations using a combination of 5 CarbonSats. One achieves global coverage everyday but only samples the targets at fixed local times. The other configuration samples the targets five times at two-hour intervals approximately every 6th day but only achieves global coverage after 5 days. From the statistical analyses, we found, as expected, that the random errors improve by approximately a factor of two if 5 satellites are used. On the other hand, more satellites do not result in a large reduction of the systematic error. The systematic error is somewhat smaller for the CarbonSat constellation configuration achieving global coverage everyday. Finally, we recommend the CarbonSat constellation configuration that achieves daily global coverage.

Systematic Errors in the Four Vertical Algorithms in Normal and Handicapped Populations

1975 ◽  
Vol 6 (4) ◽  
pp. 202-220 ◽  
Author(s):  
L. S. Cox
Keyword(s):  
Systematic Error ◽  
Systematic Errors ◽  
Random Errors ◽  
Computational Process ◽  
Middle Income ◽  
Adequate Knowledge ◽  
Basic Facts ◽  
One Year ◽  
Computational Skill ◽  
Computational Processes

In a two-year study, frequencies and descriptions of systematic errors in four algorithms in arithmetic were studied in upper-middle income regular and special education classrooms involving 744 children. Children were screened for adequate knowledge of basic facts and for receiving prior instruction on the computational processes. Systematic errors contained a recurring incorrect computational process and were differentiated from careless errors and random errors. Errors were studied within levels of computational skill for each algorithm. Results showed that 5-6% of the children made systematic errors in the addition, multiplication, and division algorithms. The figure was 13% for the subtraction algorithm. One year later 23% of the children were making either the identical systematic error or another systematic error.

scholarly journals Towards space based verification of CO<sub>2</sub> emissions from strong localized sources: fossil fuel power plant emissions as seen by a CarbonSat constellation

2011 ◽  
Vol 4 (12) ◽  
pp. 2809-2822 ◽  
Author(s):  
V. A. Velazco ◽  
M. Buchwitz ◽  
H. Bovensmann ◽  
M. Reuter ◽  
O. Schneising ◽  
...  
Keyword(s):  
Power Plant ◽  
Systematic Error ◽  
Co2 Emissions ◽  
Power Plants ◽  
Fossil Fuel ◽  
Systematic Errors ◽  
Random Errors ◽  
Power Plant Emissions ◽  
Global Coverage ◽  
Plant Emissions

Abstract. Carbon dioxide (CO2) is the most important man-made greenhouse gas (GHG) that cause global warming. With electricity generation through fossil-fuel power plants now being the economic sector with the largest source of CO2, power plant emissions monitoring has become more important than ever in the fight against global warming. In a previous study done by Bovensmann et al. (2010), random and systematic errors of power plant CO2 emissions have been quantified using a single overpass from a proposed CarbonSat instrument. In this study, we quantify errors of power plant annual emission estimates from a hypothetical CarbonSat and constellations of several CarbonSats while taking into account that power plant CO2 emissions are time-dependent. Our focus is on estimating systematic errors arising from the sparse temporal sampling as well as random errors that are primarily dependent on wind speeds. We used hourly emissions data from the US Environmental Protection Agency (EPA) combined with assimilated and re-analyzed meteorological fields from the National Centers of Environmental Prediction (NCEP). CarbonSat orbits were simulated as a sun-synchronous low-earth orbiting satellite (LEO) with an 828-km orbit height, local time ascending node (LTAN) of 13:30 (01:30 p.m. LT) and achieves global coverage after 5 days. We show, that despite the variability of the power plant emissions and the limited satellite overpasses, one CarbonSat has the potential to verify reported US annual CO2 emissions from large power plants (≥5 Mt CO2 yr−1) with a systematic error of less than ~4.9% and a random error of less than ~6.7% for 50% of all the power plants. For 90% of all the power plants, the systematic error was less than ~12.4% and the random error was less than ~13%. We additionally investigated two different satellite configurations using a combination of 5 CarbonSats. One achieves global coverage everyday but only samples the targets at fixed local times. The other configuration samples the targets five times at two-hour intervals approximately every 6th day but only achieves global coverage after 5 days. From the statistical analyses, we found, as expected, that the random errors improve by approximately a factor of two if 5 satellites are used. On the other hand, more satellites do not result in a large reduction of the systematic error. The systematic error is somewhat smaller for the CarbonSat constellation configuration achieving global coverage everyday. Therefore, we recommend the CarbonSat constellation configuration that achieves daily global coverage.

Statistics and parallaxes

1978 ◽  
Vol 48 ◽  
pp. 7-29
Author(s):  
T. E. Lutz
Keyword(s):  
Experimental Design ◽  
Statistical Methods ◽  
Review Paper ◽  
Systematic Errors ◽  
Past Experience ◽  
Random Errors ◽  
Trigonometric Parallaxes ◽  
Systematic And Random Errors

This review paper deals with the use of statistical methods to evaluate systematic and random errors associated with trigonometric parallaxes. First, systematic errors which arise when using trigonometric parallaxes to calibrate luminosity systems are discussed. Next, determination of the external errors of parallax measurement are reviewed. Observatory corrections are discussed. Schilt’s point, that as the causes of these systematic differences between observatories are not known the computed corrections can not be applied appropriately, is emphasized. However, modern parallax work is sufficiently accurate that it is necessary to determine observatory corrections if full use is to be made of the potential precision of the data. To this end, it is suggested that a prior experimental design is required. Past experience has shown that accidental overlap of observing programs will not suffice to determine observatory corrections which are meaningful.

A Preliminary Study on Saving Parking Lot

2011 ◽  
Vol 368-373 ◽  
pp. 3628-3631
Author(s):  
Jun Liu ◽  
Wei Xian Zhang
Keyword(s):  
Sustainable Development ◽  
Large Area ◽  
The Sustainable Development ◽  
Parking Lots ◽  
Wide Range ◽  
Parking Lot ◽  
Preliminary Study

Along with the development of society and the popularity of private cars, more and more parking lots are to be needed. Consequently, large sized parking lots will be built in many cities. But the traditional parking lots were paved by a large area of concrete. So much concrete will be bound to create heat pollution. Meanwhile, a large area of parking lot occupies mass openspace. The existing parking lots lead to a waste of resources. This paper introduces a new term of saving parking lot and presents some key principles that stem from a wide range of contributions. The newfashioned parking lot may also give rise to the sustainable development.

Establishing inherent uncertainty in the shifts determined by volumetric imaging

2017 ◽  
Vol 16 (3) ◽  
pp. 258-264
Author(s):  
Upendra Kumar Giri ◽  
Anirudh Pradhan
Keyword(s):  
Linear Accelerator ◽  
Systematic Errors ◽  
Cone Beam ◽  
Random Errors ◽  
Mean Values ◽  
Volumetric Imaging ◽  
X Ray ◽  
Image Quality Control ◽  
The Mean ◽  
Six Degree Of Freedom

AbstractObjectiveThis study was conducted for establishing inherent uncertainty in the shift determination by X-ray volumetric imaging (XVI) and calculating margins due to this inherent uncertainty using van Herk formula.Material and methodsThe study was performed on the XVI which was cone-beam computed tomography integrated with the Elekta AxesseTM linear accelerator machine having six degree of freedom enabled HexaPOD couch. Penta-Guide phantom was used for inherent translational and rotational shift determination by repeated imaging. The process was repeated 20 times a day without moving the phantom for 30 consecutive working days. The measured shifts were used for margins calculation using van Herk formula.ResultsThe mean standard deviations were calculated as 0·05, 0·05, 0·06 mm in the three translational (x, y and z) and 0·05°, 0·05°, 0·05° in the three rotational axes (about x, y, z). Paired sample t-test was performed between the mean values of translational shifts (x, y, z) and rotational shifts. The systematic errors were found to be 0·03, 0·04 and 0·03 mm while the random errors were 0·05, 0·06 and 0·06 mm in the lateral, cranio-caudal and anterio-posterior directions, respectively. For the rotational shifts, the systematic errors were 0·02, 0·03 and 0·03 and the random errors were 0·06, 0·05 and 0·05 in the pitch, roll and yaw directions, respectively.ConclusionOur study concluded that there was an inherent uncertainty associated with the XVI tools, on the basis of these six-dimensional shifts, margins were calculated and recorded as a baseline for the quality assurance (QA) programme for XVI imaging tools by checking its reproducibility once in a year or after any major maintenance in hardware or upgradation in software. Although the shift determined was of the order of submillimetre order, still that shift had great significance for the image quality control of the XVI tools. Every departments practicing quality radiotherapy with such imaging tools should establish their own baseline value of inherent shifts and margins during the commissioning and must use an important QA protocol for the tools.

Study on Location Planning of Regional Parking

2012 ◽  
Vol 178-181 ◽  
pp. 1748-1752
Author(s):  
Xin Jie Zhang
Keyword(s):  
Location Planning ◽  
Chinese Cities ◽  
Parking Lots ◽  
Parking Lot ◽  
The City

Parking difficulty is being a highlighted problem in nowadays' cities. As a reality of planning of parking lots in Chinese cities are later than other countries, and also parking lot planning are based on city blueprint and needs of parking places, as well as limit of making parking lot plan, we can make a model on planning and choosing parking lot fields to find the most suitable scheme. Thus it can bring the greatest benefit to the whole area in the city, and also make a reference to planning of the parking lot construction in area.

scholarly journals Energy Trading with Electric Vehicles in Smart Campus Parking Lots

2018 ◽  
Vol 8 (10) ◽  
pp. 1749 ◽  
Author(s):  
Mohamed Ahmed ◽  
Young-Chon Kim
Keyword(s):  
Electric Vehicles ◽  
Market Mechanism ◽  
University Campus ◽  
Energy Trading ◽  
Control Center ◽  
Parking Lots ◽  
Electric Vehicle Charging ◽  
Parking Lot ◽  
Demand Information ◽  
Knapsack Algorithm

Energy trading with electric vehicles provides opportunities to eliminate the high peak demand for electric vehicle charging while providing cost saving and profits for all participants. This work aims to design a framework for local energy trading with electric vehicles in smart parking lots where electric vehicles are able to exchange energy through buying and selling prices. The proposed architecture consists of four layers: the parking energy layer, data acquisition layer, communication network layer, and market layer. Electric vehicles are classified into three different types: seller electric vehicles (SEVs) with an excess of energy in the battery, buyer electric vehicles (BEVs) with lack of energy in the battery, and idle electric vehicles (IEVs). The parking lot control center (PLCC) plays a major role in collecting all available offer/demand information among parked electric vehicles. We propose a market mechanism based on the Knapsack Algorithm (KPA) to maximize the PLCC profit. Two cases are considered: electric vehicles as energy sellers and the PLCC as an energy buyer, and electric vehicles as energy buyers and the PLCC as an energy seller. A realistic parking pattern of a parking lot on a university campus is considered as a case study. Different scenarios are investigated with respect to the number of electric vehicles and amount of energy trading. The proposed market mechanism outperforms the conventional scheme in view of costs and profits.

scholarly journals Calculating Point Cloud Object Volume Using Co-Opposite-Direction Slicing Method

2019 ◽  
Author(s):  
Bin Li ◽  
Xiaowei Bi ◽  
Cheng Peng ◽  
Yong Chen ◽  
Xiaofa Zhao ◽  
...  
Keyword(s):  
Full Advantage ◽  
Opposite Direction ◽  
Point Cloud ◽  
Systematic Errors ◽  
Random Errors ◽  
Improved Method ◽  
Cone Model ◽  
Slicing Method

Although the Slicing Method (SM) is effective for calculating the volume of point cloud objects (PCOs), it is restricted in terms of applicability and practicability because of a certain contingency and directional defects. The Co-Opposite-Direction Slicing Method (CODSM) proposed in this paper is an improved method for calculating PCO volume by increasing parallel (co-opposite-direction) observation and considering the two-way mean as the result. This method takes full advantage of the mutual offsetting of random errors and the compensation of systematic directional errors, which can effectively overcome (or mitigate) the effect of random errors and reduce the effect of systematic errors in SM. In this paper, two typical objects, a cone model and a stone lion base, are the examples for calculating PCO volume using CODSM. The results show that CODSM has all the inherent advantages of SM and effectively weakens the volatility of random errors and the directionality of systematic errors from SM. Therefore, CODSM is a robust configuration upgrade of SM.

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