• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• 한국습지학회지
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• 제25권4호
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• pp.306-314
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• 2023

하천퇴적물은 유역내 다양한 오염원으로부터 발생하는 중금속, 유기물 등 오염물질의 수용체일 뿐만 아니라 수질 오염 및 수생태 악영향을 유발할 수 있는 2차적 오염원이기에 중요한 관리대상이라고 할 수 있다. 오염된 하천퇴적물의 효과적인 관리를 위해서는 오염원에 대한 식별과 이와 연계된 관리대책의 수립이 우선되어야 한다. 본 연구는 하천퇴적물내 측정된 다양한 이화학적 오염항목 분포 특성에 기반하여 퇴적물의 주요 오염원을 식별하기 위한 방법으로서 기계학습모델의 적용성을 평가하였다. 기계학습 모델의 성능 평가를 위해 전국 4대강 수계내 주요 폐금속광산 및 산업단지 인근에서 수집된 총 356개의 하천퇴적물에 대한 중금속 10개 항목(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, Al)과 토양항목 3개(모래, 실트, 점토 비율) 수질항목 5개(함수율, 강열감량, 총유기탄소, 총질소, 총인)를 포함한 총 18개 오염항목에 대한 분석자료를 활용하였다. 기계학습 분류 모델로서 선형판별분석(linear discriminant analysis, LDA)과 서포트벡터머신(support vector machine, SVM) 분류기를 사용하여 폐금속광산('광산')과 산업단지('산단') 인근에서의 하천퇴적물 시료의 분류 성능을 평가한 결과, 채취 지점 및 시기별 4가지 경우(비강우시 광산, 강우시 광산, 비강우시 산단, 및 강우시 산단)에 대한 퇴적물 시료의 분류 성능이 우수하였으며, 특히 비선형 모델인 SVM(88.1%)이 선형모델인 LDA(79.5%) 보다 퇴적물을 분류하는데 있어 보다 우수한 성능을 나타냈다. SVM 앙상블 기반 비배타적 다중라벨분류기 모델을 이용하여 각 시료채취 지점 상류 유역 1km 반경 내 지배적인 토지이용 및 오염원을 다중 타겟값으로 다중분류 예측을 수행한 결과, 폐금속광산과 산업단지의 분류는 비교적 높은 정확도로 수행하였으나, 도시와 농업지역 등 다른 비점오염원에 대한 분류정확도는 56~60%범위로 비교적 낮게 나타났다. 이는 다중라벨 분류모델의 복잡성에 비해 데이터셋의 크기가 상대적으로 작아서 발생한 과적합에 기인한 것으로 향후 보다 많은 측정자료가 확보될 경우 기계학습 모델을 적용한 오염원 분류의 정확도를 보다 향상시킬 수 있을 것으로 판단된다.

• Journal of Biosystems Engineering
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• 제42권4호
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• pp.350-357
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• 2017

Purpose: In-situ monitoring of water quality is fundamental to most environmental applications. The high cost and long delays of conventional laboratory methods used to determine water quality, including on-site sampling and chemical analysis, have limited their use in efficiently managing water sources while preventing environmental pollution. The objective of this study was to develop an on-site water monitoring system consisting mainly of an Arduino board and a sensor array of multiple ion selective electrodes (ISEs) to measure the concentration of $NO_3$ ions. Methods: The developed system includes a combination of three ISEs, double-junction reference electrode, solution container, sampling system consisting of three pumps and solenoid valves, signal processing circuit, and an Arduino board for data acquisition and system control. Prior to each sample measurement, a two-point normalization method was applied for a sensitivity adjustment followed by an offset adjustment to minimize the potential drift that could occur during continuous measurement and standardize the response of multiple electrodes. To investigate its utility in on-site nitrate monitoring, the prototype was tested in a facility where drinking water was collected from a water supply source. Results: Differences in the electric potentials of the $NO_3$ ISEs between 10 and $100mg{\cdot}L^{-1}$ $NO_3$ concentration levels were nearly constant with negative sensitivities of 58 to 62 mV during the period of sample measurement, which is representative of a stable electrode response. The $NO_3$ concentrations determined by the ISEs were almost comparable to those obtained with standard instruments within 15% relative errors. Conclusions: The use of the developed on-site nitrate monitoring system based on automatic sampling and two-point normalization was feasible for detecting abrupt changes in nitrate concentration at various water supply sites, showing a maximum difference of $4.2mg{\cdot}L^{-1}$ from an actual concentration of $14mg{\cdot}L^{-1}$.

• Environmental Analysis Health and Toxicology
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• 제16권4호
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• pp.161-170
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• 2001

In aqueous ecosystems, the level of toxicity is highly responsive dependant to multiple variables, including rainfall, sunlight, pH, adhesion, etc. Because Korea has particularly distinct wet and dry seasons, the toxicity of pollutants in rivers or streams is dependant on the sampling season and time. In order to examine the effects of rainfall on toxicity, sediment samples were collected from five sites along the Keumho river. It was found that Microtox toxicity levels were generally higher during the dry season than the wet season. It indicated that river pollutants are carried off more quickly by the water during the wet season. As a result, it was recommended that the point sources of pollutants of the Keumho river would be placed between KH3 (Paldalgyo) and KH4(Keumhogyo), KH4(Keumhogyo) and KH5(Dasa).

• 한국작물학회:학술대회논문집
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• 한국작물학회 2005년도 국제학술회의
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Nuclear Engineering and Technology
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• 제49권4호
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• pp.787-791
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• 2017

Americium-beryllium (Am-Be; n, ${\gamma}$) is a neutron emitting source used in various research fields such as chemistry, physics, geology, archaeology, medicine, and environmental monitoring, as well as in the forensic sciences. It is a mobile source of neutron activity (20 Ci), yielding a small thermal neutron flux that is water moderated. The aim of this study is to develop a model to increase the neutron thermal flux of a source such as Am-Be. This study achieved multiple advantageous results: primarily, it will help us perform neutron activation analysis. Next, it will give us the opportunity to produce radio-elements with short half-lives. Am-Be single and multisource (5 sources) experiments were performed within an irradiation facility with a paraffin moderator. The resulting models mainly increase the thermal neutron flux compared to the traditional method with water moderator.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.591-595
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• 2010

Conventional methods of model evaluation usually rely only on model performance based on a comparison of simulated variables to corresponding observations. However, this type of model evaluation has been criticized because of its insufficient consideration of the various uncertainty sources involved in modeling processes. This study aims to propose an extended model evaluation method using multiple assesment indices (MAIs) that consider not only the model performance but also the model structure and parameter uncertainties in rainfall-runoff modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250m, 500m, and 1km digital elevation models) were developed and assessed by three MAIs for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. In addition, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. Numerous parameter sets could lead to indistinguishable hydrographs. This result supports that while making a model complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty. The proposed model evaluation process can provide an effective guideline for identifying a reliable hydrologic model.

• 한국습지학회지
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• 제21권2호
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• pp.102-113
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• 2019

조석에 따른 마산만의 수질의 차이를 파악하기 위하여 2016년 초여름(6월)과 여름(7, 8월)의 대조기 1 조석주기 내의 만조와 간조시에 6개의 조사정점에서 slack-tide sampling을 실시하였다. 조사된 모든 수질성분들의 혼합 상태는 SAL과의 사이의 상관관계를 통하여 잘 설명되고 있다. 초여름과 여름철 공통적으로 하천수 유입 물질인 TURB, DSi, NNN은 주로 보존성 혼합을, 내부증감 물질인 SS, COD, AMN, $H_2S$는 주로 비보존성 혼합을 나타내었다. 보존성 혼합은 만조와 간조의 수질 사이에 좋은 선형 관계를 나타내었고, 비보존성 혼합은 양자가 각기 다른 변동 양상을 나타내었다. 요인분석을 통하여 만조와 간조의 농도차의 시공간적 변화에 주요한 잠재변수들을 확인할 수 있었다. 초여름의 경우는 갈수기로서 외부유입 물질(allochthonous inputs)이 적으므로 농도차 변화에 주도적으로 영향을 미치는 오염원이 없이 조석, 유역으로부터 자연유입, 내부증감 등의 영향이 복합적으로 작용하여 4개의 요인(VF1~4)에 고루 분포되어 나타났다. 반면에 여름철의 경우는 하천수의 영향을 받는 ST-1에서 큰 농도차를 나타내는 지표들은 VF1 요인에 집중적으로 포함되어 나타났고, 그 밖에 내부 증감을 나타내는 지표들로 극명히 구분되어 나타났다. 실제로 항상 안정된 상태의 하구는 존재하지 않는다. Flushing time의 변화 등에 의하여 혼합양상은 항상 변할 수 있고, 여기에 내부증감으로 end-members의 조건이 변함에 따라 농도차의 발생은 불가피하다. 그러므로 하구의 수질을 조사할 때 평균적인 수질 자료를 확보하기 위한 시료 채취 방법을 항상 강구할 필요가 있다.

• Journal of Information Science Theory and Practice
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• 제7권4호
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• 상하수도학회지
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• 제28권2호
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• pp.235-248
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• 2014

The widespread occurrence of dissolved endocrine disrupting compounds(EDCs) and pharmaceutical active compounds(PhACs) in water sources is of concern due to their adverse effects. To remove these chemicals, adsorption of EDCs/PhACs on granular activated carbon(GAC) was investigated, and bisphenol A, carbamazepine, diclofenac, ibuprofen, and sulfamethoxazole were selected as commonly occurring EDCs/PhACs in the aquatic environment. Various adsorption isotherms were applied to evaluate compatability with each adsorption in the condition of single-solute. Removal difference between individual and competitive adsorption were investigated from the physicochemical properties of each adsorbate. Hydrophobicity interaction was the main adsorption mechanism in the single-solute adsorption with order of maximum adsorption capacity as bisphenol A > carbamazepine > sulfamethoxazole > diclofenac > ibuprofen, while both hydrophobicity and molecular size play significant roles in competitive adsorption. Adsorption kinetic was also controled by hydrophobicity of each adsorbate resulting in higher hydrophobicity allowed faster adsorption on available adsorption site on GAC. EDCs/PhACs adsorption on GAC was determined as an endothermic reaction resulting in better adsorption at higher temperature ($40^{\circ}C$) than lower temperature ($10^{\circ}C$).