• The Korean Journal of Nuclear Medicine Technology
• /
• v.27 no.1
• /
• pp.36-41
• /
• 2023

Purpose The long-term trend of extrinsic uniformity by type of gamma camera was analyzed, and the factors affecting uniformity were investigated. Based on this, the purpose was to predict the life of the gamma camera, pay attention to factors that affect uniformity, and obtain better quality images. Materials and methods Four of the gamma cameras in operation at a senior general hospital in Seoul were selected and the trend of extrinsic uniformity from the first operation date to the present was analyzed. In order to minimize various factors affecting uniformity, a detailed analysis was conducted by calculating the monthly and annual average of the uniformity values. Results Two Symbia E gamma cameras from SIEMENS, one Symbia Evo Excel gamma camera, and one Symbia Intevo16 gamma camera were selected and analyzed. The uniformity of Symbia E₁ (2012 warehousing) changed unevenly, and the uniformity of Symbia E₂ (2014 warehousing) changed according to the replacement cycle of ⁵⁷Co sheet sources. The uniformity of Symbia Evo Excel (received in 2017) and Symbia Intevo 16 (received in 2017) was constant compared to Symbia E. Conclusion The extrinsic uniformity of the gamma camera gradually increased over time. However, there was a difference in uniformity for each type of gamma camera, and there was a change in uniformity in which the cause could not be accurately identified. In order to improve the quality of the image, it is necessary to periodically check changes in uniformity and minimize factors that affect uniformity.

• Communications of the Korean Mathematical Society
• /
• v.15 no.2
• /
• pp.371-378
• /
• 2000

In this paper, we investigate frames that admit a unique uniformity and characterize the completely regular frames which admit a unique uniformity.

• Honam Mathematical Journal
• /
• v.40 no.1
• /
• pp.27-46
• /
• 2018

In this paper, (E, L)-preproximity and uniformity spaces in matriod theory as a generalized to a classical proximity and Uniformity spaces introduced by Csaszar [1] is introduced. Recently, Shi [17]-[18] introduced a new approach to the fuzzification of matroids.Here introduce (E, L)-preproximity and uniformity spaces, Uniformity and strong uniformity on (E, L)-fuzzifying matroid space, Not only study the properties of this new notions, but it has been generated (E, L)-fuzzifying matroid Space from (E, L)-preproximity and uniformity spaces. Next to introduced (E, L)-preproximity continuous in (E, L)-fuzzifying matroid space and used it in more properties. Finally we solve combinatorial optimizations problem via (E, L)-fuzzifying matroid space.

• Journal of the Ergonomics Society of Korea
• /
• v.20 no.2
• /
• pp.59-70
• /
• 2001

White uniformity is one of the important inspection factors determining the image quality of CRT screen. In the full white pattern, white uniformity means the degree of uniform distribution of white color across the whole screen. To elicit the sensitivity factors affecting the decision of the white uniformity quality, experiments in which participants were confronted with 6 evaluation points embedded in 3 measurement groups on a CRT screen were conducted to gather the psychophysical data that are the level of white uniformity subjects perceived and CA100 produced. These data were used to develop a modified CIE1976 equation for calculating white uniformity. Performance comparison between the original CIE1976 equation and the modified equation was conducted in terms of accuracy test and magnitude estimation. It was concluded the modified equation is more sensitive in the change of white uniformity, compared to the original CIE1976 equation.

• Journal of ILASS-Korea
• /
• v.24 no.3
• /
• pp.122-129
• /
• 2019

Flow uniformity in aftertreatment system is an important factor in determining uniform catalytic reaction and filtration. In this study, variety types of DOC-DPF system design were analyzed to increase flow uniformity. For this analysis, ANSYS Fluent was used with porous media setup for DOC and DPF. Turbulent flow was modeled by standard $k-{\varepsilon}$ model excepting porous media. Uniformity index was utilized to evaluate the flow uniformity quantitatively. Reference design showed low velocity region because two large vortex were generated before baffle. When radius of DOC-DPF system was increased, exhaust pressure acting on the inlet decreases and velocity distribution was shifted to one side. When inlet pipe was set to axial center of DOC-DPF system velocity distribution was symmetric. However, flow was not dissipated until the front end of DOC and showed higher uniformity index. When the volume of DOC was reduced while fixed volume of entire DOC-DPF system and baffle plate is located downstream of the DOC-DPF system, there was improvement in uniformity index.

• Journal of the Optical Society of Korea
• /
• v.17 no.2
• /
• pp.213-218
• /
• 2013

Although infrared focal plane array (IRFPA) detectors have been commonly used, non-uniformity correction (NUC) remains an important problem in the infrared imaging realm. Non-uniformity severely degrades image quality and affects radiometric accuracy in infrared imaging applications. Residual non-uniformity (RNU) significantly affects the detection range of infrared surveillance and reconnaissance systems. More effort should be exerted to improve IRFPA uniformity. A novel NUC method that considers the surrounding temperature variation compensation is proposed based on the binary nonlinear non-uniformity theory model. The implementing procedure is described in detail. This approach simultaneously corrects response nonlinearity and compensates for the influence of surrounding temperature shift. Both qualitative evaluation and quantitative test comparison are performed among several correction technologies. The experimental result shows that the residual non-uniformity, which is corrected by the proposed method, is steady at approximately 0.02 percentage points within the target temperature range of 283 K to 373 K. Real-time imaging shows that the proposed method improves image quality better than traditional techniques.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.1
• /
• pp.67-74
• /
• 2018

In this paper, we propose an efficient scene based non-uniformity correction algorithm which performs the offset correction using the uniform obtained from input scenes for Infrared camera. In general, pixel outputs of a infrared detector can not be uniform. Therefore, the non-uniformity correction procedure need to be performed to make the image outputs uniform. A typical non-uniformity correction method uses a black body at the laboratory to obtain the output of the infrared detector's pixels for two temperatures, HOT and COLD, and calculates the non-uniformity correction parameters. However, output characteristics of the Infrared detector changes while the Infrared camera is operated, the fixed pattern noise of the Infrared detector and dead pixels are generated. To remove the noise, the offset correction is generally performed. The offset correction procedure usually need the additional device such as a thermo-electric cooler, shutter, or non-uniformity correction lens. Therefore, we introduce a general scene based non-uniformity correction technique without additional equipment, and then we propose an improved non-uniformity correction algorithm based on image to solve the problem of the existing technique.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.19 no.2
• /
• pp.87-92
• /
• 2015

Purpose When the patients takes myocardial perfusion SPECT using $^{201}Tl$, the operator gives the patients an injection of $^{201}Tl$. But the uniformity correction map in SPECT uses $^{99m}Tc$ uniformity correction map. Thus, we want to compare the image quality when it uses $^{99m}Tc$ uniformity correction map and when it uses $^{201}Tl$ uniformity correction map. Materials and Methods Phantom study is performed. We take the data by Asan medical center daily QC condition with flood phantom including $^{201}Tl$ 21.3 kBq/mL. After postprocessing with this data, we analyze CFOV integral uniformity(I.U) and differential uniformity(D.U). And we take the data with Jaszczak ECT Phantom by American college of radiology accreditation program instruction including $^{201}Tl$ 33.4 kBq/mL. After post processing with this data, we analyze spatial Resolution, Integral Uniformity(I.U), coefficient of variation(C.V) and Contrast with Interactive data language program. Results In the flood phantom test, when it uses $^{99m}Tc$ uniformity correction map, Flood I.U is 3.6% and D.U is 3.0%. When it uses $^{201}Tl$ uniformity correction map, Flood I.U is 3.8% and D.U is 2.1%. The flood I.U is worsen about 5%, but the D.U is improved about 30% inversely. In the Jaszczak ECT phantom test, when it uses $^{99m}Tc$ uniformity correction map, SPECT I.U, C.V and contrast is 13.99%, 4.89% and 0.69. When it uses $^{201}Tl$ uniformity correction map, SPECT I.U, C.V and contrast is 11.37%, 4.79% and 0.78. All of data are improved about 18%, 2%, 13% The spatial resolution was no significant changes. Conclusion In the flood phantom test, Flood I.U is worsen but Flood D.U is improved. Therefore, it's uncertain that an image quality is improved with flood phantom test. On the other hand, SPECT I.U, C.V, Contrast are improved about 18%, 2%, 13% in the Jaszczak ECT phantom test. This study has limitations that we can't take all variables into account and study with two phantoms. We need think about things that it has a good effect when doctors decipher the nuclear medicine image and it's possible to improve the image quality using the uniformity correction map of other radionuclides other than $^{99m}Tc$, $^{201}Tl$ when we make other nuclear medicine examinations.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.28 no.1
• /
• pp.35-41
• /
• 2016

With the assumption that the performance of a catalyst is guaranteed and that the performance of an SCR reactor is influenced by the uniformity of fluid flow into the catalyst, this study carried out a numerical analysis of flow uniformity, which is an important design factor in SCR reactors. CFD was used to grasp flow uniformity and flow characteristics inside the SCR reactor. As for the flow uniformity, analysis was carried out on the velocity and direction of the fluid flowing into the front of the first SCR reactor. Numerical analysis was carried out in terms of the area ratios of the mixing evaporator to the catalyst for 500 PS SCR, 1 : 1.9, 1 : 3.1, 1 : 4.5, and 1 : 7.0. The results showed that the larger the area ratio, the smaller the flow uniformity. On the basis of these results, the flow uniformity of the modified SCR reactor is 77%. A guidevane was installed to improve flow uniformity, and attempts were made to grasp the flow uniformity based on the shape of the guide vane. The shape of the guide vane was cylindrical, and numerical analysis was carried out for cases with two cylinders and three cylinders. As a result of the numerical analysis, it was found that while there was no great difference between 82.7% with two cylinders and 81.7% with three cylinders, the effects of the installation of the guide vane on the improvement of flow uniformity were indisputable.

• Proceedings of the KSME Conference
• /
• 2007.05b
• /
• pp.2512-2517
• /
• 2007

Effect of natural convention for hot plate surface temperature uniformity was studied by experiments that were adjusted height of chamber and temperature difference. The hot plate chamber is composed of the hot plate and the upper heater and adiabatic vertical wall. The hot plate diameter is 220mm and maintains temperature at $150^{\circ}C$. Flow pattern compares with surface temperature and confirms that natural convection affects on temperature uniformity of hot plate surface. In case, temperature non-uniformity of hot plate surface is due to heater pattern, lots of weak and small flow cells more improve temperature uniformity than stronger flow cells or non-developing flow cell. Improve temperature uniformity $1.2^{\circ}C$ when developing weak and small flow cells.