Behavior Analysis of Concrete Structure under Blast Loading : (I) Experiment Procedures (폭발하중을 받는 콘크리트 구조물의 실험적 거동분석 : (I) 실험수행절차)
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- KSCE Journal of Civil and Environmental Engineering Research
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- v.29 no.5A
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- pp.557-564
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- 2009
In recent years, there have been numerous explosion-related accidents due to military and terrorist activities. Such incidents caused not only damages to structures but also human casualties, especially in urban areas. To protect structures and save human lives against explosion accidents, better understanding of the explosion effect on structures is needed. In an explosion, the blast overpressure is applied to concrete structures as an impulsive load of extremely short duration with very high pressure and heat. Generally, concrete is known to have a relatively high blast resistance compared to other construction materials. However, information and test results related to the blast experiment of internal and external have been limited due to military and national security reasons. Therefore, in this paper, to evaluate blast effect on reinforced have concrete structure and its protective performance, blast tests are carried out with
Experiments were conducted to investigate rice varietal response to low water and air temperatures at different growth stages from 1975 to 1980 in a phytotron in Suweon and in a cold water nursery in Chooncheon. Germination ability, seedling growth, sterility of laspikelets, panicle exertion, discoloration of leaves, and delay of heading of recently developed indica/japonica cross(I/J), japonica, and indica varieties at low air temperature or cold water were compared to those at normal temperature or natural conditions. The results are summarized as follows: 1. Practically acceptable germination rate of 70% was obtained in 10 days after initiation of germination test at 15\circ_C for japonica varieties, but 15 days for IxJ varieties. Varietal differences in germination ability at suboptimal temperature was greatest at 16\circ_C for 6 days. 2. Cold injury of rice seedlings was most severe at the 3.0-and 3.5-leaf stage and it was reduced as growth stage advanced. A significant positive correlation was observed between cold injury at 3-leaf stage and 6-leaf stage. 3. At day/night temperatures of 15/10\circ_C seedlings of both japonica and I/J varieties were dead in 42 days. At 20/15\circ_C japonica varieties produced tillers actively, but tillering of I/J varieties was retarded a little. At 25/15\circ_C, both japonica and I/J varieties produced tillers most actively. Increase in plant height was proportional to the increase in all varieties. 4. In I/J varieties the number of differentiated panicle rachis branches and spikelets was reduced at a day-night temperature of 20-15\circ_C compared to 25-20 or 30-25\circ_C, but not in japonica varieties although panicle exertion was retarded at 20-15\circ_C. The number of spikelets was not correlated with the number of primary rachis branches, but positively correlated with that of secondary rachis branches. 5. Heading of rice varieties treated with 15\circ_C air temperature at meiotic stage was delayed compared to that at tillering stage by 1-3 days and heading was delayed as duration of low temperature treatment increased. 6. At cold water treatment of 17\circ_C from tillering to heading stage, heading of japonica, I/J, and cold tolerant indica varieties was delayed 2-6, 3-9, and 4-5 days, respectively, Growth stage sensitive to delay of heading delay at water treatment were tillering stage, meiotic stage, and booting tage in that order, delay of heading was greater in indica corssed japonica(Suweon 264), japonica(Suweon 235), and cold tolerant indica(Lengkwang) varieties in that order. Delay of heading due to cold water treatment was positively correlated with culm length reduction and spikelet sterility. 7. Elongation of culms and exertion of panicles of rice varieties treated with low air temperature 17\circ_C. Culm length reduction rate of tall varieties was lower than that of short statured varieties at low temperature. Panicle exertion was most severaly retarded with low temperature treatment at heading stage. Generally, retardation of panicle exertion of 1/1 varieties was more severe than that of japonica varieties at low temperature. There was a positive correlation between panicle exertion and culm length at low temperature. 8. The number of panicles was increased with cold water treatment at tillering stage, but reduced at meiotic stage. As time of cold water treatment was conducted at earlier growth stage, culm length was shorter and panicle exertion poorer. 9. Sterility of all rice varieties was negligible at 17\circ_C for three days but 30.3-85.2% of strility was observed for nine-day treatment at 17\circ_C. Among the tested varieties, sterility of Suweon 264 and Milyang 42 was highest and that of Suweon 290 and Suweon 287 was lowest. The most sensitive growth stage to low temperature induced sterility was from 15 to 5 days before heading. There was positive correlation between sterility of rice plants treated with low temperature at meiotic and heading stage. 10. Percentage of spikelet sterility was greatest at cold water treatment at meiotic stage (auricle distance -15~-10cm) and it was higher in 1/1 (Suweon 264, Joseng tongil), japonica (Nongbaek, Towada), and cold tolerance indica(Lengkwang) varieties in the order. Level of cold water and position of young-ear affected on the sterility of varieties at meiotic stage; percentage of spikelet sterility of variety, Lengkwang, of which young-ear was located above the cold water level was high, but that of short statured variety, Suweon 264, of which young-ear was located in the cold water was lower. 11. Percentage of ripened grains was not reducted at 15\circ_C air temperature for three days at full heading stage in all varieties. However, at six-day low temperature treatment Suweon 287, Suweon 264 showed percentage of ripended grains lower than 60%, but at nine-day low temperature treatment all varieties showed percentage of ripened grains lower than 60%. Low temperature treatment of 17\circ_C from 10 days after heading for 20 days did not affect on the ripening of all varieties. 12. Uptake of nitrogen, phosphorous, potassium, calcium, and magnesium in whole plants was higher at average air temperature of 25\circ_C, but concentration of the elements was lower compared to those at 19\circ_C. However, both total uptake and concentration of manganese were higher at 19\circ_C compared to 25\circ_C. 13. Higher application of nitrogen, phosphorus, silicate, and compost increased yield of rice due to increased number of panicles and spike let fertility in cold water irrigated paddy.
Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.
In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.
Purpose : To analyze the eyeglasses supply system for ametropic soldiers in ROK military. Methods : We investigated and analyzed the supply system of eyeglasses for the ametropic soldiers provided by the Korean military. The refractive powers and corrected visual acuity were measured for 37 ametropic soldiers who wear insert glasses for ballistic protective and gas-masks supplied by the military based on their habitual prescriptions. Full correction of refractive error was prescribed for subjects having less than 1.0 of distance visual acuity, and comparison was held for inspecting the changes in corrected visual acuity. Suggestions were provided for solving the issues regarding current supplying system, and this study investigated the applicabilities for utilizing professional optometric manpower. Results : The new glasses supplied by army for ametropic soldiers were duplicated from the glasses they worn when entering the army. The spherical equivalent refractive powers of the conventional, ballistic protective and gas-mask insert glasses supplied for 37 ametropic soldiers were
Energetic mesoscale eddies in the East Sea (ES) associated with strong mesoscale variability impacting circulation and environments were statistically characterized by analyzing satellite altimeter data collected during 1993-2017 and in-situ data obtained from four cruises conducted between 2015 and 2017. A total of 1,008 mesoscale eddies were detected, tracked, and identified and then classified into 27 groups characterized by mean lifetime (L, day), amplitude (H, m), radius (R, km), intensity per unit area (EI,
Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.
To obtain basic information on the Korean local corn lines a total of 57 lines were selected from 1,000 Korean local collection at Chungnam National University, classified by principal component analysis, and genetic nature was investigated. The results are summarized as follows. 1. There were a great variation in mean values of plant characters of the lines. The mean values of plant characters except for density of kernels varied with types of crossing. All characters except. for tasselling dates were reduced in magnitude when selfed, while those characters were increased when topcrossed. 2. The correlation coefficients among characters studied ranged front 0.99 to -0.59. The correlation coefficients among characters were not greatly changed depending upon types of crosses. 3. In order to classify the lines more effectively, selected 12 plant characters were used to classify 57 local lines by principal component analysis. The first four component could explain 86.4%, 83.4% and 81.1% of the total variations in sibbed lines, selfed lines and topcrossed lines, respectively. 4. Contribution of characters to principal component was high at upper principal components and low at lower principal components. 5. Biological meaning of the principal component and plant types corresponding to the each principal component were explained clearly by the correlation coefficient between principal components and characters. The first principal component appeared to correspond to the size of plant and ear. The second principal component appeared to correspond to the degree of differentiation in organs and the duration of vegetative growing period. But biological meaning of the third and fourth principal components was not clear. 6. The lines were classified into 4 lineal groups by the taxonomic distance. Group I included 52 lines which was 91.2% of total lines, group II 3 lines, group III 1 lines and group IV I lines, respectively. Four groups could be characterized as follows : Group I : early maturity, short-culmed, medium height plant, small ears, medium kernels and medium yielding. Group II : late maturity, medium height plant, small ears, small kernels, prolific ears and higher yielding. Group III : medium maturity, tall-culmed, small ears, small kernels and low yielding. Group IV : medium maturity, tall-calmed, large ears, one ear plant and me yielding. 7. The inbreeding depression varied with plant characters and lines. The characters such as yield, kernel weight per ear, ear weight and plant height showed great degree of inbreeding depression. Group I showed high inbreeding depression in such characters as 100 kernel weight, leaf number, plant height and days to tasselling, while group II showed high inbreeding depression in other plant characters. 8. Heterosis of plant characters varied also with lines. The ear weight, kernel weight per ear, yield, 100 kernel weight, and plant height were some of the plant characters showing high heterosis. Group II showed high values of heterosis in such characters as ear length, ear diameter, ear weight, kernel weight per ear, 100 kernel weight, and leaf length, while group I was high in heterosis in other plant characters. 9. The degree of homozgosity was highest in ear weight (79.1%) and lowest in ear number per plant (-21%). Group II showed higher degree of homozygosity than group I. 10. Correlation coefficients between characters of ribbed and topcrossed lines were positive for all characters. Highly significant. correlation coefficients between ribbed and topcrossed lines were obtained especially for characters such as ear number per plant, plant height, leaf length and yield per plot.
Thecodiplosis japonesis is sweeping the Pinus densiflora forests from south-west to north-east direction, destroying almost all the aged large trees as well as even the young ones. The front line of infestation is moving slowly but ceaselessly norhwards as a long bottle front. Estimation is that more than 40 percent of the area of P. densiflora forest has been damaged already, however some individuals could escapes from the damage and contribute to restore the site to the previous vegetation composition. When the stands were attacked by this insect, the drastic openings of the upper story of tree canopy formed by exclusively P. densiflora are usually resulted and some environmental factors such as light, temperature, litter accumulation, soil moisture and offers were naturally modified. With these changes after insect invasion, as the time passes, phytosociologic changes of the vegetation are gradually proceeding. If we select the forest according to four categories concerning the history of the insect outbreak, namely, non-attacked (healthy forest), recently damaged (the outbreak occured about 1-2 years ago), severely damaged (occured 5-6 years ago), damage prolonged (occured 10 years ago) and restored (occured about 20 years ago), any directional changes of vegetation composition could be traced these in line with four progressive stages. To elucidate these changes, three survey districts; (1) "Gongju" where the damage was severe and it was outbroken in 1977, (2) "Buyeo" where damage prolonged and (3) "Gochang" as restored, were set, (See Tab. 1). All these were located in the south temperate forest zone which was delimited mainly due to the temporature factor and generally accepted without any opposition at present. In view of temperature, the amount and distribution of precipitation and various soil factor, the overall homogeneity of environmental conditions between survey districts might be accepted. However this did not mean that small changes of edaphic and topographic conditions and microclimates can induce any alteration of vegetation patterns. Again four survey plots were set in each district and inter plot distance was 3 to 4 km. And again four subplots were set within a survey plot. The size of a subplot was
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70