• Journal of Communications and Networks
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• v.11 no.1
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• pp.42-46
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• 2009

Superimposed training (SIT) design for estimating of time-varying multipath channels is investigated for mobile orthogonal frequency division multiplexing (OFDM) systems. The design of optimum SIT consists of two parts: The optimal SIT sequence is derived by minimizing the channel estimates' mean square error (MSE); the optimal power allocation between training and information data is developed by maximizing the averaged signal to interference plus noise ratio (SINR) under the condition of equal powered paths. The theoretical analysis is verified by simulations. For the metric of the averaged SINR against signal to noise ratio (SNR), the theoretical result matches the simulation result perfectly. In contrast to an interpolated frequency-multiplexing training (FMT) scheme or an SIT scheme with random pilot sequence, the SIT scheme with proposed optimal sequence achieves higher SINR. The analytical solution of the optimal power allocation is demonstrated by the simulation as well.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1224-1227
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• 2009

When evaluating the quality of images and displays, it is important to combine the characteristics as perceived by the human visual system and measured by equipment using subjective and objective methods, respectively. In the case of objective methods, the quality of a display is measured using colorimetric or radiometric devices according to existing standards covering the color temperature, gamut size, gamma characteristic, and device characterization. Meanwhile, subjective methods assess the quality of an image using the human visual system based on a comparison with a reference or counterpart using such metrics as the sharpness, noise, contrast, saturation, and color accuracy. Objective and subjective methods are usually used together in comparison, as ultimately it is observers watching images on a display. In addition to existing objective methods, a new image quality metric is also introduced as regards the JPEG compression ratio that is reflected in the relationship between the gamut size and the color fidelity in CIELAB color space.

• Korean Journal of Optics and Photonics
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• v.11 no.2
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• pp.85-90
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• 2000

The image quality of CRT displays is descnbed by the physical characteristics such as luminance, contrast, address ability, viewing distance, and so on. However, the final evaluation of rmage quality is deteITIlllled by not phYSICal data, but subjective perceived Image quality. Therefore the correlation is compared the score of subjective image qualIty accompli~hed by several persons with calculated SQRI (SQuate Root Integral) value uSlllg 4 kInds of CRT monitors. And the influence of tile physical chatac1eristics for subjective Image quality is analyzed on the basis of the validity of SQRI method as a metric for the evaluation of subjective image quality. ality.

• Nutritional Sciences
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• v.2 no.2
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• pp.93-101
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• 1999

The aim of this study was to investigate influence of body build on body composition, energy metabolic state and insulin concentration of blood. 29 male athletes and 36 male non-athletic students were recruited for the study. Anthropometry including chest depth and breadth, fat mass, fat fee mass, tricep skinfold thickness were measured. fasting glucose, lactate, triglyceride, fee fatty acid, and insulin concentration in serum were measured . Body build was assessed using metric index, which calculated by regression equations of Mohr and Greil. The athletic and non-athletic students were allocated to 3 body build, that is leptomorph, mesomorph, and pyknomorph. Resting metabolic rate was calculated. Respiratory quotient was determined through ratio of measured VO$_2$, and V$CO_2$. Most non-athletes have a leptomorphic body build, in contrast to athletes mesomorphic type. The body build type influenced body composition differently between non-athletic group and athletic group. Weight, body mass index, body fat mass and fat mass proportion (%), and fat-free mass increased from leptomorph to pyknormorph in non-athletic group. Pyknormorphic athletes have a significant higher body mass index, fat mass, fat free mass than other body build type. Serum glucose, triglyceride, lactate, insulin showed significant differences only in non-athletic group between leptomorph and mesomorph. RMR increased significantly from leptomorph to mesomorph in non-athletes. There was no significant difference of RQ among 3 body build types in both athletes and non-athletes. This study gives a coherent data on body build and body composition for athletes and non-athletes students. The influence of body builds on energy metabolic status of serum was different between athletes and non-athletes.

• Advances in concrete construction
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• v.17 no.2
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• pp.93-110
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• 2024

The process of concrete production consumes an immense volume of water, with approximately one billion metric tons of freshwater being utilized for tasks such as aggregate washing, fresh concrete production, and concrete curing. The accessibility of clean water for the public is hindered by the limited availability of water resources, primarily due to the rapid expansion of industries such as tanneries, stone quarries, and concrete manufacturing. These industries not only consume substantial amounts of freshwater but also generate significant volumes of various types of waste. Therefore, the use of fresh water in concrete production should be minimized. Few studies have reviewed the production of concrete using wastewater to derive practical and applicable findings for the industry. Thus, this study thoroughly explores the physical and chemical effects of wastewater on concrete, examining aspects like durability, hardened properties, and rheological characteristics. It identifies key factors that can compromise concrete properties when exposed to wastewater. The scarcity of research on integrating wastewater into concrete production underscores the urgent necessity for innovative approaches and methodologies in this field. While the inclusion of wash water typically reduces the workability of fresh concrete, it often enhances its compressive strength. Notably, significant improvements have been observed when using tertiary processed wastewater, wash water, polyvinyl alcohol-based wash water (PVAW), and reclaimed water in the concrete mixing process. The application of tertiary treatment to wastewater resulted in a notable enhancement of compressive strength, showing increases of up to 7%. In contrast, wastewater treated through secondary methods experienced a decline in strength ranging from 9% to 18% over a period of six months. However, the use of reclaimed wastewater demonstrated an improvement in strength by 8% to 17%, depending on the concentration level ranging from 25% to 100%. In contrast, the utilization of secondary processed wastewater and industrial water has a minimal impact on the concrete's strength.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.483-501
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• 2012

The purpose of this study was to apply a multi-metric model of Lentic Ecosystem Health Assessments(LEHA) for environmental impact assessments of Cheongpyung Reservoir during 2005 - 2006 and assessed the ecological model values. The ecosystem model of LEHA was composed of eleven metrics such as biological parameters($B_p$), physical parameters($P_p$), and chemical parameters($C_p$), and determined the rank of ecological health by the criteria. The variables of $B_p$ were metrics of % sensitive species($M_2$, NMS) and insectivore species($M_5$, % $I_n$), which decrease as the water quality degradates, and these metric values were low as 1.5% and 32.4%, respectively. In contrast, the proportions of tolerant species and omnivore species as the other $B_p$ parameters were 43% and 62%, respectively, which indicate a degradation and disturbance of the ecosystem. Riparian vegetation coverage($M_9$, % $V_c$) as a variable of $P_p$, were higher in the 2nd than 1st survey, and decreased toward the dam site from the headwaters. This was due to a habitat simplification(modifications) by frequent bottom dredging of sand and rocks. The variables of $C_p$ were two metrics of specific conductivity($M_{10}$, $C_I$) as an indicator of ionic contents(cations and anions) and the Trophic State Index(TSI) based on chlorophyll-a($M_{11}$, $TSI_{CHL}$) as an indicator of trophic state. These metric values of $C_p$ had high temporal variations, but low spatial variations on the main axis of the reservoir along with the ecological health of a good condition. The environmental impact assessments using the LEHA multi-metric model indicated that the model values of LEHA averaged 30.7 in 1st survey(fair - poor condition) vs. 28 in 2nd survey(poor condition), indicating a temporal variation of the ecological health. The model values of LEHA showed a minimum(28) in the lacustrine zone(S5) and ranged from 29 to 30 in the other locations sampled, indicating a low longitudinal variation. Overall, environmental impact assessments, based on LEHA model, suggest that chemical water quality conditions were in good, but biological conditions were disturbed due to habitat modifications by frequent dredgings in the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• International Journal of High-Rise Buildings
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• v.8 no.2
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• pp.117-123
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• 2019

Tall buildings are prone to wind-induced vibrations due to their slenderness whereby peak structural accelerations may be higher than the recommended maximum value. The common countermeasure is the installation of a tuned mass damper (TMD) near the highest occupied floor. Due to the extremely large modal mass of tall buildings and because of the narrow to broad band type of wind excitation the TMD mass may become inacceptable large - in extreme cases up to 2000 metric tons. It is therefore a need to develop more efficient TMD concepts which provide the same damping to the building but with reduced mass. The adaptive TMD concept described in this paper represents a solution to this problem. Frequency and damping of the adaptive TMD are controlled in real-time by semi-active oil dampers according to the actual structural acceleration. The resulting enhanced TMD efficiency allows reducing its mass by up to 20% compared to the classical passive TMD. The adaptive TMD system is fully fail-safe thanks to a smart valve system of the semi-active oil dampers. In contrast to active TMD solutions the adaptive TMD is unconditionally stable and its power consumption on the order of 1 kW is negligible small as controllable oil dampers are semi-active devices. The adaptive TMD with reduced mass, stable behavior and lowest power consumption is therefore a preferable and cost saving damping tool for tall buildings.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.53-61
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• 2021

Distribution of fish community depends largely on environmental disturbance such as habitat change. In this study, we evaluated the impact of environmental variables and microhabitat patch types on fish distribution in Yudeung Stream at 15 sites between early May and late June 2019. We used non-metric multidimensional scaling to examine the distribution patterns of fish in each site. Gnathopogon strigatus, Squalidus gracilis majimae, Zacco koreanus, and Zacco platypus were associated with riffle and boulder areas, whereas Iksookimia koreensis, Acheilognathus koreensis, Coreoleuciscus splendidus, Sarcocheilichthys nigripinnis morii, and Odontobutis interrupta were associated with large shallow areas. In contrast, Cyprinus carpio, Carassius auratus, Lepomis macrochirus, and Micropterus salmoides were found at downstream sites associated with large pool areas, sandy/clay-bottomed areas, and vegetated areas. On the basis of these results, we suggest that microhabitat patch types are important in determining the diversity and abundance of fish communities, since a mosaic of different microhabitats supports diverse fish species. As such, microhabitat patches are key components of freshwater stream ecosystem heterogeneity, and a suitable patch composition in stream construction or restoration schemes will support ecologically healthy food webs.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4591-4596
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• 2023

Single-photon emission computed tomography SPECT image reconstruction methods have a significant influence on image quality, with filtered back projection (FBP) and ordered subset expectation maximization (OSEM) being the most commonly used methods. In this study, we proposed newly-designed adaptive non-blind deconvolution with a structural similarity (SSIM) index that can take advantage of the FBP and OSEM image reconstruction methods. After acquiring brain SPECT images, the proposed image was obtained using an algorithm that applied the SSIM metric, defined by predicting the distribution and amount of blurring. As a result of the contrast to noise ratio (CNR) and coefficient of variation evaluation (COV), the resulting image of the proposed algorithm showed a similar trend in spatial resolution to that of FBP, while obtaining values similar to those of OSEM. In addition, we confirmed that the CNR and COV values of the proposed algorithm improved by approximately 1.69 and 1.59 times, respectively, compared with those of the algorithm involving an inappropriate deblurring process. To summarize, we proposed a new type of algorithm that combines the advantages of SPECT image reconstruction techniques and is expected to be applicable in various fields.