• Journal of Korea Water Resources Association
• /
• v.57 no.3
• /
• pp.151-164
• /
• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.40 no.1
• /
• pp.23-33
• /
• 2012

In this study, how much users of Hannamkeumbuk Keumbuk Mountains are aware of Baekdaegan and its attached mountain chains, a traditional geographic system, according to Sangyungpyo and basic data like the degree of awareness and use-behaviors, etc. have been studied. In addition, the environmental value of Hannamkeumbuk Keumbuk Mountains separating the central and the southern part of Korea among attached mountain ranges, secondary mountain chains, which act as an ecosystem buffer in the Baekdudaegan Range, has been estimated at the current amount of currency. In the questions of the perception of the traditional classification standard of mountain chains and Baekdudaegan, more than 70% of respondents answered that they had heard of or known them but 66.8% werenot aware of Hannamkeumbuk Keumbuk Mountains. While the awareness for Baekdudaegan is high, the perception of its attached mountain chains was very poor. DBDC responder system and CVM, which is used widely for the value estimate method of environment goods, were used. As the result, an additional benefit got when a person visits Hannamkeumbuk Keumbuk mountains was estimated as 5,813 won. It could find out that this amount was very low compared with 51,984 won, average visit cost. It judged that the reason was that damage of environmental conditions, the monotony of the trails and progress of indiscriminate environmental destruction, etc. The results of this study will offer a new perspective on public relations activities and resource conservation of Baekdudaegan and its attached mountain chains and estimate perceptions and efficient services for visitors to HannamKeumbuk Keumbuk Mountains. This study will act as data for basic planning and management to increase the mountains' value and to preserve them. Further studies are needed to make a frame of work division and management with various organizations so that the management of Hannamkeumbuk-Keumbuk Mountains may be properly established and their value may been hanced.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.329-352
• /
• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Tuberculosis and Respiratory Diseases
• /
• v.60 no.2
• /
• pp.194-204
• /
• 2006

Background : Even though tuberculosis (TB) is still a major public concern in Korea, there is little data on the management of TB patients and its outcomes in the private sector. This study evaluated the status of TB treatment in the private sector. Methods : Sixteen-hundred-sixty-six TB patients who were notified in a private university hospital from 2001 to 2002 were enrolled in this study. The patients were divided into pulmonary ($TB_P$), extrapulmonary ($TB_E$), and combined ($TB_{P+E}$) groups, and were also divided into initial and retreatment groups. The clinical characteristics, diagnostic methods, treatment regimens, and outcomes were analyzed and compared. Results : The mean age of the 1,666 patients was 48.9 years and the male-to-female ratio was 1.3:1. The number of patients in the initial and retreatment groups of $TB_P$, and those of ($TB_E+TB_{P+E}$) were 809, 276, 480, 101, respectively. A bacteriological study was performed in 92.0% of cases, and a positive culture was confirmed in 58.1% and 31.7% of patients with TBP and ($TB_E+TB_{P+E}$), respectively (p<0.05). The AFB smear was positive in 45.4 % of the $TB_P$ patients. PCR was carried out in 60.4% of the ($TB_E+TB_{P+E}$) group. The MDR was detected in 14.0% of isolates. Overall, the treatment completion, default, and death rates were 70.2%, 13.5% and 1.9%, respectively. Conclusion : Even though the management of TB patients in a private hospital was satisfactory in terms of the national guidelines, the high default rate was is still a problem. Efforts to decrease the default rate either independently or in cooperation with the public sector will be needed.

• Journal of KIISE:Databases
• /
• v.31 no.5
• /
• pp.553-566
• /
• 2004

Some of the current main research areas involving techniques related to XML consist of storing XML documents, optimizing the query, and indexing. As such we may focus on the set of documents that are composed of various structures, but that are not shared with common structure such as the same DTD or XML Schema. In the case, it is essential to analyze structural similarities and differences among many documents. For example, when the documents from the Web or EDMS (Electronic Document Management System) are required to be merged or classified, it is very important to find the common structure for the process of handling documents. In this paper, we transformed sequential pattern mining algorithms(1) to extract maximal similar paths between two XML documents. Experiments with XML documents show that our transformed sequential pattern mining algorithms can exactly find common structures and maximal similar paths between them. For analyzing experimental results, similarity metrics based on maximal similar paths can exactly classify the types of XML documents.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.8C
• /
• pp.1025-1033
• /
• 2004

This paper covers the detection of covert direct sequence spread spectrum signal without the PN(Pseudo Noise) code information. Due to its low probability of interception, the difficulty of spectrum surveillance increases. Detection parameters are the signal existence of given bandwidth, the length of spreading sequence used by transmitter, and the identification of spreading code for detected chip length. The triple correlation function(TCF) value which is one of the higher order statistical signal processing techniques can be used to detect spread spectrum signal without a prior knowledge, but, it has weakness that TCF results depend on the spread data sequence in actual application. This paper proposes the new scheme that not only overcomes the weakness but also presents better performance than the traditional TCF scheme. The performance comparison of conventional TCF with proposed technique shows that the triple correlation estimator(TCE) has better detection capability.

• Journal of KIISE:Computing Practices and Letters
• /
• v.13 no.7
• /
• pp.462-475
• /
• 2007

The Embedded system provides human-centric services in many fields of education, information, industry and service, and monitoring programs have been variously developed for managing, controlling and testing for these embedded systems. Currently, many kernel trace toolkits are being used for monitoring. These trace toolkits are so complicate that we present $ETT^{plus}$, our simple and explicit embedded kernel trace toolkit, for embedded systems and describe the transmission method for trace data between the embedded target system and the host system. $ETT^{plus}$ provides the solution to solve the problems such as the difficult kernel patch and file system dependency in existing kernel trace toolkits like LTT. Furthermore, we present the experimental results about embedded system performance evaluations such as system call execute time or network data transmission time by using $ETT^{plus}$.

• Journal of KIISE:Software and Applications
• /
• v.26 no.8
• /
• pp.955-963
• /
• 1999

다단계 보안 실시간 데이타베이스 시스템은 데이타베이스의 일관성 유지와 실시간 요구인 마감시간의 만족, 그리고 기밀성을 띤 데이타가 노출될 수 있는 비밀채널(covert-channel)의 방지라는 요구사항을 모두 만족해야 한다. 기존의 SRT-2PL(Secure Real-Time 2 Phase Locking)은 원본과 복사본으로 데이타 객체를 분리시켜 다른 등급간에 불간섭(non-interference)을 유지하여 비밀채널의 방지를 가능하게 하였으나, 복사본이 모든 데이타 객체에 대해 항상 존재하므로 메모리의 낭비가 있을 수 있고, 복사본의 갱신을 위한 갱신 큐의 관리에 따르는 오버헤드와 그에 따른 예측성 결여라는 문제점을 갖고 있다. 이를 개선하기 위하여 본 논문에서는 다단계 보안 실시간 데이타베이스 시스템의 요구사항을 모두 만족하는 동적 복사 프로토콜을 제안한다. 동적 복사 프로토콜은 로킹 기법을 기초로 동작하고, 트랜잭션의 작업에 따라 동적으로 복사본을 생성하고 삭제한다. 모의 실험 결과 제안한 동적 복사 프로토콜은 비밀채널을 방지하고 동적인 복사본의 생성으로 SRT-2PL의 단점인 메모리 낭비를 줄일 수 있으며, 예측성을 높여 마감시간 오류율을 감소시켰다.Abstract Concurrency control of real-time secure database system must satisfy not only logical data consistency but also timing constraints and security requirements associated with transactions. These conflicting natures between timing constraints and security requirements are often resolved by maintaining several versions(or secondary copies) on the same data items. In this paper, we propose a new lock-based concurrency control protocol, Dynamic Copy Security Protocol, ensuring both two conflicting requirements. Our protocol aims for reducing the storage overhead of maintaining secondary copies and minimizing the processing overhead of update history. Main idea of our protocol is to keep a secondary copy only when it is needed to resolve the conflicting read/write operations in real time secure database systems. For doing this, a secondary copy is dynamically created and removed during a transaction's read/write operations according to our protocol. We have also examined the performance characteristics of our protocol through simulation under different workloads while comparing the existing real time security protocol. The results show that our protocol consumed less storage and decreased the missing deadline transactions.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.2
• /
• pp.103-112
• /
• 2012

We demonstrate the preliminary results of ship detection application using synthetic aperture radar (SAR) and automatic identification system (AIS) together. Multi-frequency and multi-temporal SAR images such as TerraSAR-X and Cosmo-SkyMed (X-band), and Radarsat-2 (C-band) are acquired over the West Sea in South Korea. In order to compare with SAR data, we also collected an AIS data. The SAR data are pre-processed considering by the characteristics of scattering mechanism as for sea surface. We proposed the "Adaptive Threshold Algorithm" for classification ship efficiently. The analyses using the combination of the SAR and AIS data with time series will be very useful to ship detection or tracing of the ship.

• The Journal of Society for e-Business Studies
• /
• v.21 no.1
• /
• pp.1-14
• /
• 2016

This research proposes a method that aims to evaluate the risk levels of websites based on exposure risks of privacy information. The proposed method considers two aspects as follows. First, we define the risk levels of each privacy information according to its own inherent risk. Second, we calculate the visiting probability of a webpage to measure the expected of the actual exposure of privacy information on that webpage. In this research, we implemented an system to prove that automatically collects websites and calculates their risk levels. For the experiments, we used a real world dataset consisting of a total of websites for 4 categories such as university, bank, central government agency, and education. The experiment results show that the websites in the bank category are relatively well managed, while the others are needed to cope with the exposure of privacy information. Finally, the proposed method in this research is expected to be further utilized in establishing a priority-based approach to alleviate of the privacy information exposure problems.