• Journal of the Society of Disaster Information
• /
• v.20 no.1
• /
• pp.20-31
• /
• 2024

Purpose: Research and development of high-strength concrete enables high-rise buildings and reduces the self-weight of the structure by reducing the cross-section, thereby reducing the thickness of beams and slabs to build more floors. A large effective space can be secured and the amount of reinforcement and concrete used to designate the base surface can be reduced. Method: In terms of field construction and quality, the effect of reducing the occurrence of drying shrinkage can be confirmed by studying the combination of low water bonding ratio and minimizing bleeding on the concrete surface. Result: The ease of site construction was confirmed due to the high self-charging property due to the increased fluidity by using high-performance water reducing agents, and the advantage of shortening the time to remove the formwork by expressing the early strength of concrete was confirmed. These experimental results show that the field application of ultra-high-strength concrete with a design standard strength of 100 MPa or higher can be expanded in high-rise buildings. Through this study, we experimented and evaluated whether ultra-high-strength concrete with a strength of 130 MPa or higher, considering the applicability of high-rise buildings with more than 120 floors in Korea, could be applied in the field. Conclusion: This study found the optimal mixing ratio studied by various methods of indoor basic experiments to confirm the applicability of ultra-high strength, produced 130MPa ultra-high strength concrete at a ready-mixed concrete factory similar to the real size, and tested the applicability of concrete to the fluidity and strength expression and hydration heat.

• Journal of Space Technology and Applications
• /
• v.4 no.1
• /
• pp.1-11
• /
• 2024

Korea Astronomy and Space Science Institute (KASI) developed an satellite laser ranging (SLR) system for tracking space objects using ultra-pulsed lasers. For the safe operation of SLR system, aircraft surveillance radar system (ASRS) was developed to prevent human damage from high power laser transmitted from the SLR system. The ASRS consists of the radar hardware subsystem (RHS) and main control subsystem (MCS), in order to detect flying objects in the direction of laser propagation and then stop immediately the laser transmission. The RHS transmits the radio frequency (RF) pulse signals and receives the returned signals, while the MCS analyzes the characteristics of received signals and distinguishes the existence of flying objects. If the flying objects are determined to be existed, the MCS sends the command signal to the laser controller in SLR system to pause the laser firing. In this study, we address the interface and operational scenarios of ASRS, including the design of RHS and MCS. It was demonstrated in the aircraft experiments that the ASRS could detect an aircraft and then stop transmitting high power laser successfully.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.7
• /
• pp.335-347
• /
• 2024

Open-vocabulary 3D point cloud instance segmentation (OV-3DIS) is a challenging visual task to segment a 3D scene point cloud into object instances of both base and novel classes. In this paper, we propose a novel model Open3DME for OV-3DIS to address important design issues and overcome limitations of the existing approaches. First, in order to improve the quality of class-agnostic 3D masks, our model makes use of T3DIS, an advanced Transformer-based 3D point cloud instance segmentation model, as mask proposal module. Second, in order to obtain semantically text-aligned visual features of each point cloud segment, our model extracts both 2D and 3D features from the point cloud and the corresponding multi-view RGB images by using pretrained CLIP and OpenSeg encoders respectively. Last, to effectively make use of both 2D and 3D visual features of each point cloud segment during label assignment, our model adopts a unique feature ensemble method. To validate our model, we conducted both quantitative and qualitative experiments on ScanNet-V2 benchmark dataset, demonstrating significant performance gains.

• Journal of Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.39-70
• /
• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.29 no.6
• /
• pp.327-340
• /
• 2017

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2016. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of flow, heat and mass transfer, the reduction of pollutant exhaust gas, cooling and heating, the renewable energy system and the flow around buildings. CFD schemes were used more for all research areas. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results of the long-term performance variation of the plate-type enthalpy exchange element made of paper, design optimization of an extruded-type cooling structure for reducing the weight of LED street lights, and hot plate welding of thermoplastic elastomer packing. In the area of pool boiling and condensing, the heat transfer characteristics of a finned-tube heat exchanger in a PCM (phase change material) thermal energy storage system, influence of flow boiling heat transfer on fouling phenomenon in nanofluids, and PCM at the simultaneous charging and discharging condition were studied. In the area of industrial heat exchangers, one-dimensional flow network model and porous-media model, and R245fa in a plate-shell heat exchanger were studied. (3) Various studies were published in the categories of refrigeration cycle, alternative refrigeration/energy system, system control. In the refrigeration cycle category, subjects include mobile cold storage heat exchanger, compressor reliability, indirect refrigeration system with $CO_2$ as secondary fluid, heat pump for fuel-cell vehicle, heat recovery from hybrid drier and heat exchangers with two-port and flat tubes. In the alternative refrigeration/energy system category, subjects include membrane module for dehumidification refrigeration, desiccant-assisted low-temperature drying, regenerative evaporative cooler and ejector-assisted multi-stage evaporation. In the system control category, subjects include multi-refrigeration system control, emergency cooling of data center and variable-speed compressor control. (4) In building mechanical system research fields, fifteenth studies were reported for achieving effective design of the mechanical systems, and also for maximizing the energy efficiency of buildings. The topics of the studies included energy performance, HVAC system, ventilation, renewable energies, etc. Proposed designs, performance tests using numerical methods and experiments provide useful information and key data which could be help for improving the energy efficiency of the buildings. (5) The field of architectural environment was mostly focused on indoor environment and building energy. The main researches of indoor environment were related to the analyses of indoor thermal environments controlled by portable cooler, the effects of outdoor wind pressure in airflow at high-rise buildings, window air tightness related to the filling piece shapes, stack effect in core type's office building and the development of a movable drawer-type light shelf with adjustable depth of the reflector. The subjects of building energy were worked on the energy consumption analysis in office building, the prediction of exit air temperature of horizontal geothermal heat exchanger, LS-SVM based modeling of hot water supply load for district heating system, the energy saving effect of ERV system using night purge control method and the effect of strengthened insulation level to the building heating and cooling load.

• Science of Emotion and Sensibility
• /
• v.19 no.3
• /
• pp.103-120
• /
• 2016

This study investigated how video playback styles affect viewers' emotional responses to a video and then suggested emotion assessment tool for playback-edited videos. The study involved two in-lab experiments. In the first experiment, observers were asked to express their feelings while watching videos in both original playback and articulated playback simultaneously. By controlling the speed, direction, and continuity, total of twelve playback styles were created. Each of the twelve playback styles were applied to five kinds of original videos that contains happy, anger, sad, relaxed, and neutral emotion. Thirty college students participated and more than 3,800 words were collected. The collected words were comprised of 899 kinds of emotion terms, and these emotion terms were classified into 52 emotion categories. The second experiment was conducted to develop proper emotion assessment tool for playback-edited video. Total of 38 emotion terms, which were extracted from 899 emotion terms, were employed from the first experiment and used as a scales (given in Korean and scored on a 5-point Likert scale) to assess the affective quality of pre-made video materials. The total of eleven pre-made commercial videos which applied different playback styles were collected. The videos were transformed to initial (un-edited) condition, and participants were evaluated pre-made videos by comparing initial condition videos simultaneously. Thirty college students evaluated playback-edited video in the second study. Based on the judgements, four factors were extracted through the factor analysis, and they were labelled "Happy", "Sad", "Reflective" and "Weird (funny and at the same time weird)." Differently from conventional emotion framework, the positivity and negativity of the valence dimension were independently treated, while the arousal aspect was marginally recognized. With four factors from the second experiment, finally emotion assessment tool for playback-edited video was proposed. The practical value and application of emotion assessment tool were also discussed.

• Journal of Bio-Environment Control
• /
• v.16 no.3
• /
• pp.210-216
• /
• 2007

A study was conducted to find mechanism and spray characteristics of a mini-sprinkler with downward spray to develop a new design type to be able to prevent drop water. The experiments were executed in a plastic greenhouse to minimize the effect of the wind. Data was collected at five different operation pressures and at 4 different raiser heights. Spray characteristics of the sprinkler such as effective radius, effective area, mean application depth, absolute maximum application depth, effective maximum application depth and coefficient of variation were determined. In order to analyze the mechanism and packing supporter of sprinkler, the numerical simulation using ABAQUS was performed. The optimum pressure for preventing drop water was determined.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.241-254
• /
• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• KSBB Journal
• /
• v.25 no.2
• /
• pp.142-154
• /
• 2010

The protein-bound innerpolysaccharides (IPS) produced by suspended mycelial cultures of Inonotus obliquus have promising potentials as an effective antidiabetic as well as an immunostimulating agents. To enhance IPS production, intensive strain improvement process should be carried out using large amount of UV-mutated protoplasts. During the whole strain-screening process, the stage of solid growth-culture was found to be the most time-requiring step, thus preventing rapid screening of high-yielding producers. In order to reduce the cell growth period in the solid growth-stage, therefore, solid growth-medium was optimized using the statistical methods such as (i) Plackett-Burman and fractional factorial designs (FFD) for selecting positive medium components, and (ii) steepest ascent (SAM) and response surface (RSM) methods for determining optimum concentrations of the selected components. By adopting the medium composition recommended by the SAM experiment, significantly higher growth rate was obtained in the solid growth-cultures, as represented by about 41% larger diameter of the cell growth circle and higher mycelial density. Sequential optimization process performed using the RSM experiments finally recommended the medium composition as follows: glucose 25.61g/L, brown rice 12.53 g/L, soytone peptone 12.53 g/L, $MgSO_4$ 5.53 g/L, and agar 20 g/L. It should be noted that this composition was almost similar to the medium combinations determined by the SAM experiment, demonstrating that the SAM was very helpful in finding out the final optimum concentrations. Through the use of this optimized medium, the period for the solid growth-culture could be successfully reduced to about 8 days from the previous 15~20 days, thus enabling large and mass screening of high producers in a relatively short period.

• Asian-Australasian Journal of Animal Sciences
• /
• v.24 no.8
• /
• pp.1164-1172
• /
• 2011

Two experiments were conducted to evaluate the efficacy of Trichoderma reesei derived phytase for pigs fed diets with fixed calcium to total phosphorus ratios (1.5:1). In Exp. 1, 280 weaned pigs (initial BW of $10.32{\pm}1.94$ kg) were allocated to one of five dietary treatments on the basis of weight and gender in a randomized complete block design. Treatments were the low phosphorus (0.6% Ca, 0.4% total P and 0.23% available P) diets supplemented with 0, 250, 1,000, or 2,000 FTU phytase/kg of diet and a positive control diet (PC; 0.85% Ca, 0.58% total P and 0.37% available P). The treatments were applied to seven pens with eight pigs per pen, half male and half female. In Exp. 2, six barrows fitted with ileal T-cannula (initial BW = $35.1{\pm}1.6$ kg) were assigned to three dietary treatments with a double $3{\times}3$ Latin square design. The dietary treatments were the low-phosphorus diet (0.53% Ca, 0.34% total P and 0.14% available P), the low phosphorus diet plus 1,000 FTU phytase/kg and a positive control diet (0.77% Ca, 0.50% total P and 0.30% available P). In Exp. 1, there were linear increases (p<0.01) in weight gain, phosphorus absorption, bone strength, calcium and phosphorus content of fat-free dried bone and plasma phosphorus concentrations with increasing dose rate of phytase. The performance of pigs fed the diets with 250, 1,000, or 2,000 FTU of phytase/kg did not differ from pigs fed the PC diet. Pigs fed diets with 1,000 or 2,000 FTU of phytase/kg did not differ from pigs fed the PC diet in bone characteristics. The apparent digestibility of dry matter, crude protein, ash and energy was not affected by dietary treatment. However, pigs fed the PC diet excreted more fecal phosphorus (g/d, p<0.01) and fecal phosphorus per BW gain (g/kg) than pigs fed the diets with phytase. Phytase linearly decreased (p<0.01) fecal phosphorus excreted per BW gain (g/kg), plasma calcium concentration as well as plasma and bone alkaline phosphatase activity. In Exp. 2, phytase supplementation in the low-P diet increased (p<0.05) the apparent ileal digestibility (AID) of Ca, P, leucine, lysine, phenylalanine, alanine and cysteine, tended to AID of crude protein, isoleucine, threonine, asparagine and serine. In conclusion, the novel phytase originated from Trichoderma reesei is effective in releasing Ca, P, and amino acids from corn soy based diet for pigs.