• Title/Summary/Keyword: Software-as-a-service

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Soil Moisture Estimation Using KOMPSAT-3 and KOMPSAT-5 SAR Images and Its Validation: A Case Study of Western Area in Jeju Island (KOMPSAT-3와 KOMPSAT-5 SAR 영상을 이용한 토양수분 산정과 결과 검증: 제주 서부지역 사례 연구)

  • Jihyun Lee;Hayoung Lee;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1185-1193
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    • 2023
  • The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

An Update-Efficient, Disk-Based Inverted Index Structure for Keyword Search on Data Streams (데이터 스트림에 대한 키워드 검색을 위한, 효율적인 갱신이 가능한 디스크 기반 역색인 구조)

  • Park, Eun Ju;Lee, Ki Yong
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.4
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    • pp.171-180
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    • 2016
  • As social networking services such as twitter become increasingly popular, data streams are widely prevalent these days. In order to search data accumulated from data streams efficiently, the use of an index structure is essential. In this paper, we propose an update-efficient, disk-based inverted index structure for efficient keyword search on data streams. When new data arrive at the data stream, the index needs to be updated to incorporate the new data. The traditional inverted index is very inefficient to update in terms of disk I/O, because all index data stored in the disk need to be read and written to the disk each time the index is updated. To solve this problem, we divide the whole inverted index into a sequence of inverted indices with exponentially increasing size. When new data arrives, it is first inserted into the smallest index and, later, the small indices are merged with the larger indices, which leads to a small amortize update cost for each new data. Furthermore, when indices stored in the disk are merged with each other, we minimize the disk I/O cost incurred for the merge operation, resulting in an even smaller update cost. Through various experiments, we compare the update efficiency of the proposed index structure with the previous one, and show the performance advantage of the proposed structure in terms of the update cost.

Analysis of Status and Trend in Software Education : Focused on Educational Technology Survey(2014 - 2016) (초·중등 SW 교육 현황 및 추이 분석 : 교육정보화 실태조사(2014-2016)을 중심으로)

  • Yoon, Ilkyu;Kim, Hansung
    • Journal of The Korean Association of Information Education
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    • v.22 no.1
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    • pp.71-80
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    • 2018
  • The purpose of this study is to analyze objectively the current state of preparation of SW education in Korea based on the survey of educational technology of elementary and secondary school which is investigated periodically every year. For this purpose, we extracted indicators related to SW education from educational technology level indicators such as human, material, and utilization and analyzed the change in the level of domestic educational technology level from 2014 to 2016. The main results of this study are as follows. Firstly, the ratio of teachers who have informatics teacher certificates among middle school informatics teacher is continuously decreasing from 2014(71%) to 2016(54%), and the number of information and the number of informatics teachers moving from informatics subject to other subjects is steadily increasing. On the other hand, there is a paradoxical situation in which the total number of teachers in informatics subject is continuously increasing for three years. Secondly, the total amount of ICT related budgets for elementary and secondary schools has been steadily decreasing since 2014. Thirdly, The ratio of informatics(computer) related creative activities in elementary schools dropped to 87.7% in 2015 and 84.6% in 2016. Also, the ratio of informatics subject operating school in middle school is gradually decreasing from 34.8% in 2014, 30.8% in 2015, and 28.2% in 2016. Based on the results of this analysis, this study suggested a method for stable settlement of SW education in elementary and secondary public education field.

Geographical Name Denoising by Machine Learning of Event Detection Based on Twitter (트위터 기반 이벤트 탐지에서의 기계학습을 통한 지명 노이즈제거)

  • Woo, Seungmin;Hwang, Byung-Yeon
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.10
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    • pp.447-454
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    • 2015
  • This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

Genetic parameters of calving ease using sire-maternal grandsire model in Korean Holsteins

  • Alam, Mahboob;Dang, Chang Gwon;Choi, Tae Jeong;Choy, Yun Ho;Lee, Jae Gu;Cho, Kwang Hyeon
    • Asian-Australasian Journal of Animal Sciences
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    • v.30 no.9
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    • pp.1225-1233
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    • 2017
  • Objective: Calving ease (CE) is a complex reproductive trait of economic importance in dairy cattle. This study was aimed to investigate the genetic merits of CE for Holsteins in Korea. Methods: A total of 297,614 field records of CE, from 2000 to 2015, from first parity Holstein heifers were recorded initially. After necessary data pruning such as age at first calving (18 to 42 mo), gestation length, and presence of sire information, final datasets for CE consisted of 147,526 and 132,080 records for service sire calving ease (SCE) and daughter calving ease (DCE) evaluations, respectively. The CE categories were ordered and scores ranged from CE1 to CE5 (CE1, easy; CE2, slight assistance; CE3, moderate assistance; CE4, difficult calving; CE5, extreme difficulty calving). A linear transformation of CE score was obtained on each category using Snell procedure, and a scaling factor was applied to attain the spread between 0 (CE5) and 100% (CE1). A sire-maternal grandsire model analysis was performed using ASREML 3.0 software package. Results: The estimated direct heritability ($h^2$) from SCE and DCE evaluations were $0.11{\pm}0.01$ and $0.08{\pm}0.01$, respectively. Maternal $h^2$ estimates were $0.05{\pm}0.02$ and $0.04{\pm}0.01$ from SCE and DCE approaches, respectively. Estimates of genetic correlations between direct and maternal genetic components were $-0.68{\pm}0.09$ (SCE) and $-0.71{\pm}0.09$ (DCE). The average direct genetic effect increased over time, whereas average maternal effect was low and consistent. The estimated direct predicted transmitting ability (PTA) was desirable and increasing over time, but the maternal PTA was undesirable and decreasing. Conclusion: The evidence on sufficient genetic variances in this study could reflect a possible selection improvement over time regarding ease of calving. It is expected that the estimated genetic parameters could be a valuable resource to formulate sire selection and breeding plans which would be directed towards the reduction of calving difficulty in Korean Holsteins.

Leased Line Traffic Prediction Using a Recurrent Deep Neural Network Model (순환 심층 신경망 모델을 이용한 전용회선 트래픽 예측)

  • Lee, In-Gyu;Song, Mi-Hwa
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.10
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    • pp.391-398
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    • 2021
  • Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.

An Efficient Top-k Query Processing Algorithm over Encrypted Outsourced-Data in the Cloud (아웃소싱 암호화 데이터에 대한 효율적인 Top-k 질의 처리 알고리즘)

  • Kim, Jong Wook;Suh, Young-Kyoon
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.12
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    • pp.543-548
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    • 2015
  • Recently top-k query processing has been extremely important along with the explosion of data produced by a variety of applications. Top-k queries return the best k results ordered by a user-provided monotone scoring function. As cloud computing service has been getting more popular than ever, a hot attention has been paid to cloud-based data outsourcing in which clients' data are stored and managed by the cloud. The cloud-based data outsourcing, though, exposes a critical secuity concern of sensitive data, resulting in the misuse of unauthorized users. Hence it is essential to encrypt sensitive data before outsourcing the data to the cloud. However, there has been little attention to efficient top-k processing on the encrypted cloud data. In this paper we propose a novel top-k processing algorithm that can efficiently process a large amount of encrypted data in the cloud. The main idea of the algorithm is to prune unpromising intermediate results at the early phase without decrypting the encrypted data by leveraging an order-preserving encrypted technique. Experiment results show that the proposed top-k processing algorithm significantly reduces the overhead of client systems from 10X to 10000X.

Trends and Future Direction of the Clinical Decision Support System in Traditional Korean Medicine

  • Sung, Hyung-Kyung;Jung, Boyung;Kim, Kyeong Han;Sung, Soo-Hyun;Sung, Angela-Dong-Min;Park, Jang-Kyung
    • Journal of Pharmacopuncture
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    • v.22 no.4
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    • pp.260-268
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    • 2019
  • Objectives: The Clinical Decision Support System (CDSS), which analyzes and uses electronic health records (EHR) for medical care, pursues patient-centered medical care. It is necessary to establish the CDSS in Korean medical services for objectification and standardization. For this purpose, analyses were performed on the points to be followed for CDSS implementation with a focus on herbal medicine prescription. Methods: To establish the CDSS in the prescription of Traditional Korean Medicine, the current prescription practices of Traditional Korean Medicine doctors were analyzed. We also analyzed whether the prescription support function of the electronic chart was implemented. A questionnaire survey was conducted querying Traditional Korean Medicine doctors working at Traditional Korean Medicine clinics and hospitals, to investigate their desired CDSS functions, and their perceived effects on herbal medicine prescription. The implementation of the CDSS among the audit software developers used by the Korean medical doctors was examined. Results: On average, 41.2% of Traditional Korean Medicine doctors working in Traditional Korean Medicine clinics manipulated 1 to 4 herbs, and 31.2% adjusted 4 to 7 herbs. On average, 52.5% of Traditional Korean Medicine doctors working in Traditional Korean Medicine hospitals adjusted 1 to 4 herbs, and 35.5% adjusted 4 to 7 herbs. Questioning the desired prescription support function in the electronic medical record system, the Traditional Korean Medicine doctors working at Korean medicine clinics desired information on 'medicine name, meridian entry, flavor of medicinals, nature of medicinals, efficacy,' 'herb combination information' and 'search engine by efficacy of prescription.' The doctors also desired compounding contraindications (eighteen antagonisms, nineteen incompatibilities) and other contraindicatory prescriptions, 'medicine information' and 'prescription analysis information through basic constitution analyses.' The implementation of prescription support function varied by clinics and hospitals. Conclusion: In order to implement and utilize the CDSS in a medical service, clinical information must be generated and managed in a standardized form. For this purpose, standardization of terminology, coding of prescriptions using a combination of herbal medicines, and unification such as the preparation method and the weights and measures should be integrated.

Soil Erosion Assessment Tool - Water Erosion Prediction Project (WEPP) (토양 침식 예측 모델 - Water Erosion Prediction Project (WEPP))

  • Kim, Min-Kyeong;Park, Seong-Jin;Choi, Chul-Man;Ko, Byong-Gu;Lee, Jong-Sik;Flanagan, D.C.
    • Korean Journal of Soil Science and Fertilizer
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    • v.41 no.4
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    • pp.235-238
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    • 2008
  • The Water Erosion Prediction Project (WEPP) was initiated in August 1985 to develop new generation water erosion prediction technology for federal agencies involved in soil and water conservation and environmental planning and assessment. Developed by USDA-ARS as a replacement for empirical erosion prediction technologies, the WEPP model simulates many of the physical processes important in soil erosion, including infiltration, runoff, raindrop detachment, flow detachment, sediment transport, deposition, plant growth and residue decomposition. The WEPP included an extensive field experimental program conducted on cropland, rangeland, and disturbed forest sites to obtain data required to parameterize and test the model. A large team effort at numerous research locations, ARS laboratories, and cooperating land-grant universities was needed to develop this state-of-the-art simulation model. The WEPP model is used for hillslope applications or on small watersheds. Because it is physically based, the model has been successfully used in the evaluation of important natural resources issues throughout the United State and in several other countries. Recent model enhancements include a graphical Windows interface and integration of WEPP with GIS software. A combined wind and water erosion prediction system with easily accessible databases and a common interface is planned for the future.

The Automation Model of Ransomware Analysis and Detection Pattern (랜섬웨어 분석 및 탐지패턴 자동화 모델에 관한 연구)

  • Lee, Hoo-Ki;Seong, Jong-Hyuk;Kim, Yu-Cheon;Kim, Jong-Bae;Gim, Gwang-Yong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.8
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    • pp.1581-1588
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    • 2017
  • Recently, circulating ransomware is becoming intelligent and sophisticated through a spreading new viruses and variants, targeted spreading using social engineering attack, malvertising that circulate a large quantity of ransomware by hacking advertising server, or RaaS(Ransomware-as-a- Service), from the existing attack way that encrypt the files and demand money. In particular, it makes it difficult to track down attackers by bypassing security solutions, disabling parameter checking via file encryption, and attacking target-based ransomware with APT(Advanced Persistent Threat) attacks. For remove the threat of ransomware, various detection techniques are developed, but, it is very hard to respond to new and varietal ransomware. Accordingly, in this paper, find out a making Signature-based Detection Patterns and problems, and present a pattern automation model of ransomware detecting for responding to ransomware more actively. This study is expected to be applicable to various forms in enterprise or public security control center.