• Title/Summary/Keyword: Open Data Performance

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Analysis on the Ventilation Performance of Single-span Tomato Greenhouse with Roof Windows (천창을 설치한 토마토 재배 단동 온실의 환기성능 분석)

  • Nam, Sang-Woon;Kim, Young-Shik;Both, Arend-Jan
    • Journal of Bio-Environment Control
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    • v.20 no.2
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    • pp.78-82
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    • 2011
  • Ventilation rates, inside and outside weather data were measured in a arch-shape single-span plastic greenhouse growing tomatoes. On the roof of the experimental greenhouse, round windows which have a diameter of 0.6 m were installed at intervals of 8m. It showed that the number of air changes in this greenhouse were average 0.17 volumes per minute and in the range of 0.02 to 0.32 volumes per minute. These air changes are insufficient to meet the recommended ventilation rate for commercial greenhouses, and it is estimated that interval of 6 m is appropriate for spring or fall season. For summer season, it is necessary to narrow the space or to enlarge the open area of roof windows. Using the heat balance model, the evapotranspiration coefficients of greenhouse tomatoes were estimated from experimental ventilation data, overall heat transfer and solar radiation. It showed that the evapotranspiration coefficients were average 0.62 and in the 0.39 to 0.85 range. We suggest applying 0.6 as the evapotranspiration coefficient in design of ventilation for the single-span tomato greenhouses.

Intercomparison of Chamber Methods for Soil Respiration Measurement in a Phytotron System (식물 환경 조절 시스템에서의 토양 호흡 관측 챔버법의 비교 실험)

  • Chae Namyi;Kim Rae-Hyun;Hwang Taehee;Suh Sang-Uk;Lee Jae-Seok;Son Yowhan;Lee Dowon;Kim Joon
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.7 no.1
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    • pp.107-114
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    • 2005
  • Soil CO₂ emission is one of the primary components in carbon balance of terrestrial ecosystems. In soil CO₂ flux measurements, chamber method is currently the most common technique. Prior to compare or synthesize the data collected from different chamber methods, potential biases must be quantified for each measurement system. We have conducted an intercomparison experiment among four closed dynamic chamber systems and an automatic open-closed chamber system in a temperature-controlled phytotron. Due to the disturbed CO₂ concentrations inside the phytotron during the measurements with closed dynamic chambers and the changes in soil water content, the interpretation of the data was difficult to quantify the biases of individual methods. However, the experiment provided not only valuable information on the performance characteristics of the five instruments to varying soil temperature and CO₂ concentration but also useful insights for better designs and strategy for future intercomparison in a controlled environment.

The Effect of Academic Stress and ASE(Attitude-Social Influence-Self Efficacy) Model Factors on Academic Persistence of Online University Students (원격대학 학습자의 학업스트레스와 ASE 모델 요인이 학업지속의도에 미치는 영향)

  • Lee, Da Ye;Seo, Young Sook;Kim, Young Im
    • The Journal of the Korea Contents Association
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    • v.18 no.10
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    • pp.453-463
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    • 2018
  • An analysis including ASE model accessing based on the intention of behavior performance of online university students is a new approach to improve academic persistence considering the characteristics of students with extensive personal variables, a uniqueness of learning environment. This study aimed to identify the relationship between ASE model including academic stress and academic persistence, and the effect of these factors on academic persistence of online university students. Data were collected from 181 sophomores in K open university from March to June, 2018. Frequency analysis, ${\chi}^2-test$, t-test, F-test, Pearson's correlation analysis, and multiple regression analysis used for data analysis. For factors affecting academic persistence, academic stress (${\beta}=-.16$, p=.016), online learning attitude (${\beta}=.44$, p<.001), and social support among social influential factors (${\beta}=.16$, p=.045) were statistically significant and the prediction model of academic persistence showed 29% explanation power (F=15.76, p<.001). To enhance academic persistence of online university students, it is needed to develop programs to reduce academic stress, improve attitude toward online learning, and improve social support.

Evaluation of Travel Time Prediction Reliability on Highway Using DSRC Data (DSRC 기반 고속도로 통행 소요시간 예측정보 신뢰성 평가)

  • Han, Daechul;Kim, Joohyon;Kim, Seoungbum
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.4
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    • pp.86-98
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    • 2018
  • Since 2015, the Korea Expressway Corporation has provided predicted travel time information, which is reproduced from DSRC systems over the extended expressway network in Korea. When it is open for public information, it helps travelers decide optimal routes while minimizing traffic congestions and travel cost. Although, sutiable evaluations to investigate the reliability of travel time forecast information have not been conducted so far. First of all, this study seeks to find out a measure of effectiveness to evaluate the reliability of travel time forecast via various literatures. Secondly, using the performance measurement, this study evaluates concurrent travel time forecast information in highway quantitatively and examines the forecast error by exploratory data analysis. It appears that most of highway lines provided reliable forecast information. However, we found significant over/under-forecast on a few links within several long lines and it turns out that such minor errors reduce overall reliability in travel time forecast of the corresponding highway lines. This study would help to build a priority for quality control of the travel time forecast information system, and highlight the importance of performing periodic and sustainable management for travel time forecast information.

Comparative study on production, reproduction and functional traits between Fleckvieh and Braunvieh cattle

  • Cziszter, Ludovic-Toma;Ilie, Daniela-Elena;Neamt, Radu-Ionel;Neciu, Florin-Cristian;Saplacan, Silviu-Ilie;Gavojdian, Dinu
    • Asian-Australasian Journal of Animal Sciences
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    • v.30 no.5
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    • pp.666-671
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    • 2017
  • Objective: Aim of the current comparative study was to evaluate production outputs, reproduction efficiency and functional traits in dual-purpose Fleckvieh and Braunvieh cows, reared under temperate European conditions. Methods: A data-set from 414 Fleckvieh and 42 Braunvieh cows and 799 lactations was analysed. ID tag number, milk yield per milking session, number of steps/interval and milk conductivity were recorded and collected daily using AfiMilk 3.076 A-DU software (Afimilk Ltd., Kibbutz, Israel). Production and milk quality data were taken from the results of the official performance recordings and the reproductive outputs of cows were recorded by the research stations veterinarians. Comparisons between the two genotypes were carried out using the one way analysis of variance protocol, with categorical factor being considered the breed of cows. All the statistical inferences were carried out using Statistica software (StatSoft Inc., Tulsa, OK, USA). Results: Fleckvieh cows significantly outperformed ($p{\leq}0.05$) the Braunvieh herd, with average milk yields of $5,252.1{\pm}35.79kg$ and $4,897.6{\pm}128.94kg$, respectively. Age at first calving was significantly ($p{\leq}0.01$) influenced by the breed, with Fleckvieh heifers being more precocious ($32.8{\pm}0.29mo$) compared to those of Braunvieh breed ($35.7{\pm}0.84mo$). Reproduction efficiency as defined by the number of inseminations per gestation, calving interval, dystocia, days dry and days open, was not influenced by genotype (p>0.05). Incidences of sub-clinical mastitis, clinical mastitis, lameness and abortions were not influenced by the breed factor (p>0.05). Stay-ability of cows was significantly ($p{\leq}0.001$) influenced by genotype, with Braunvieh cows having an average age at culling of $117.88{\pm}11.78$ months compared to $90.88{\pm}2.89$ months in Fleckvieh. Conclusion: Overall, results have shown that genotype significantly influenced milk yield, age at first calving and longevity.

Hand Held the distance measurement of platform on GPS (GPS기반 Hand Held Type 거리 측정기)

  • 박지훈;김영길
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.864-867
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    • 2003
  • GPS (Global Positioning System) made by the Department of Defense in U.S.A is positioning system to use satellite and initially it has been used only for the military forces but open to civilian in about 1987. This system has widely been used for not only surveying land, but also car navigation on the street and means to build up the data of the GIS. With GPS, recently our country is accelerating to make imbeded system and also the study on imbeded system is well under way. For example, Car navigation and the construction of the Seokang bridge between Willson Arch at Han river by using DGPS were evaluated as successful model to lead accurate location with the precision of the cm. The examples of the project performance with GPS has gradually been extended to the each department organization of the local and central government. for the example, It is true that BIS(Bus Information System) is widely spreading out. In addition, the study on the Distribution Maintenance System is expected to be well in progress to take advantage of GPS based on the data base of the NGIS(National Geography Institute System) of the NGI(National Geography Institute). This paper shows that we embodied not only the large imbeded system for car and finding the location in Korean Land Corporation but also the protype of the kinematics Wrist Held which is easily portable to pedestrian, climber and marathon runner.

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Design of a Deep Neural Network Model for Image Caption Generation (이미지 캡션 생성을 위한 심층 신경망 모델의 설계)

  • Kim, Dongha;Kim, Incheol
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.4
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    • pp.203-210
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    • 2017
  • In this paper, we propose an effective neural network model for image caption generation and model transfer. This model is a kind of multi-modal recurrent neural network models. It consists of five distinct layers: a convolution neural network layer for extracting visual information from images, an embedding layer for converting each word into a low dimensional feature, a recurrent neural network layer for learning caption sentence structure, and a multi-modal layer for combining visual and language information. In this model, the recurrent neural network layer is constructed by LSTM units, which are well known to be effective for learning and transferring sequence patterns. Moreover, this model has a unique structure in which the output of the convolution neural network layer is linked not only to the input of the initial state of the recurrent neural network layer but also to the input of the multimodal layer, in order to make use of visual information extracted from the image at each recurrent step for generating the corresponding textual caption. Through various comparative experiments using open data sets such as Flickr8k, Flickr30k, and MSCOCO, we demonstrated the proposed multimodal recurrent neural network model has high performance in terms of caption accuracy and model transfer effect.

Modeling the Flushing Effect of Multi-purpose Weir Operation on Algae Removal in Yeongsan River (영산강 다기능보 운영에 따른 플러싱 및 조류 배제 효과 모델링)

  • Chong, Sun-a;Yi, Hye-suk;Hwang, Hyun-sik;Kim, Ho-joon
    • Journal of Korean Society of Environmental Engineers
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    • v.37 no.10
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    • pp.563-572
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    • 2015
  • The purpose of this study was to model the effect of flushing discharge on algae removal by multi-purpose weir operation in Yeongsan River (Seungchon Weir) using a 3-dimensional (3D) model. The chlorophyceae Eudorina sp. formed bloom in May 2013. Flushing discharge was conducted in two different ways for algal bloom reduction. To elucidate the spatial variability, a high-resolution 3D model, ELCOM-CAEDYM, was used to simulate the spatial variations of water quality and chl-a over a month. The results showed that ELCOM-CAEDYM could reproduce highly spatially resolved field data at low cost, and showed very good performance in simulating the pattern of algal bloom occurrence. The effect of each flushing discharge operation was analyzed with the results of modeling. The results of case 1, flushing discharge using an open movable weir, showed that the algal bloom between the Seochang Bridge and the Hwangryong River junction is rapidly flushed after operating the movable weir, but the residual algae remained in the weir pool as the discharge decreased. However, the results of case 2, fixed weir overflow with a small hydropower stop, showed that most of the algae was removed after flushing discharge and the effect of algae removal was much bigger than that in case 1, as per modeling results and observed data.

Implementation of a Static Analyzer for Detecting the PHP File Inclusion Vulnerabilities (PHP 파일 삽입 취약성 검사를 위한 정적 분석기의 구현)

  • Ahn, Joon-Seon;Lim, Seong-Chae
    • The KIPS Transactions:PartA
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    • v.18A no.5
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    • pp.193-204
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    • 2011
  • Since web applications are accessed by anonymous users via web, more security risks are imposed on those applications. In particular, because security vulnerabilities caused by insecure source codes cannot be properly handled by the system-level security system such as the intrusion detection system, it is necessary to eliminate such problems in advance. In this paper, to enhance the security of web applications, we develop a static analyzer for detecting the well-known security vulnerability of PHP file inclusion vulnerability. Using a semantic based static analysis, our vulnerability analyzer guarantees the soundness of the vulnerability detection and imposes no runtime overhead, differently from the other approaches such as the penetration test method and the application firewall method. For this end, our analyzer adopts abstract interpretation framework and uses an abstract analysis domain designed for the detection of the target vulnerability in PHP programs. Thus, our analyzer can efficiently analyze complicated data-flow relations in PHP programs caused by extensive usage of string data. The analysis results can be browsed using a JAVA GUI tool and the memory states and variable values at vulnerable program points can also be checked. To show the correctness and practicability of our analyzer, we analyzed the source codes of open PHP applications using the analyzer. Our experimental results show that our analyzer has practical performance in analysis capability and execution time.

An Overloaded Vehicle Identifying System based on Object Detection Model (객체 인식 모델을 활용한 적재불량 화물차 탐지 시스템 개발)

  • Jung, Woojin;Park, Yongju;Park, Jinuk;Kim, Chang-il
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.562-565
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    • 2022
  • Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. However, this irregular weight distribution is not possible to be recognized with the current weight measurement system for vehicles on roads. To address this limitation, we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles from the CCTV, black box, and hand-held camera point of view. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data. From the result, we believe that public big data can be utilized more efficiently and applied to the development of an object detection-based overloaded vehicle detection model.

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