• Journal of Pharmacopuncture
• /
• v.20 no.2
• /
• pp.89-92
• /
• 2017

Aconitum Heterophyllum (A. Heterophyllum) is an indigenous medicinal plant of India and belongs to the family Ranunculaceae. A. Heterophyllum is known to possess a number of therapeutic effects. For very ancient times, this plant has been used in some formulations in the traditional healing system of India, i.e., Ayurveda. It is reported to have use in treating patients with urinary infections, diarrhea, and inflammation. It also has been used as an expectorant and for the promotion of hepatoprotective activity. The chemical studies of the plant have revealed that various parts of the plant contain alkaloids, carbohydrates, proteins and amino acids, saponins, glycosides, quinones, flavonoids, terpenoids, etc. In the present study, a comprehensive phytochemistry and pharmacognosy, as well as the medicinal properties, of A. Heterophyllum are discussed. Scientific information on the plant was collected from various sources, such as electronic sources (Google scholar, Pubmed) and some old classical text books of Ayurveda and Ethnopharmacology. The study also presents a review of the literature on A. Heterophyllum, as well as the primary pharmacological and other important findings on this medicine. This review article should provide useful information to and be a valuable tool for new researchers who are initiating studies on the plant A. Heterophyllum.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.7
• /
• pp.2116-2124
• /
• 2000

In this paper we propose combustion control of refuse incineration plant using fuzzy model and genetic algorithm. At first fuzzy modelling is performed to obtain fuzzy model of the refuse incineration plant and obtained fuzzy model predicts outputs of the plant when inputs are given. Fuzzy model ca be used to obtain control strategy, and train and enhance operators' skill by simulating the plant. Then genetic algorithms search and find out optimal control inputs over all possible solutions in respect to desired outputs and these are inserted to plant. In order to testify proposed control method, computer simulation was carried out. As a result, ISE of fuzzy model of refuse incineration plant is 0.015 and ITAE of control by proposed method, 352 which is better than that by manual operation.

• Journal of Computational Design and Engineering
• /
• v.1 no.1
• /
• pp.13-26
• /
• 2014

Recently, renovations of plant equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scanned data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing plant has an enormous amount of points, captures intricate objects, and includes a high noise level, so the manual reconstruction of a 3D model is very time-consuming and costly. Among plant equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser-scanned data of plant equipment. The straight portion of pipes, connecting parts, and connection relationship of the piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations of pipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, and junctions, respectively.

• Journal of Pharmacopuncture
• /
• v.25 no.3
• /
• pp.199-208
• /
• 2022

Objectives: In recent decades, the trend for treating diabetes mellitus (DM) has shifted toward alternative medicines that are obtained from plant sources. Existing literature suggests that phenolic compounds derived from plants possess promising health-promoting properties. This study aimed to discuss the role of plant-derived phenolic compounds in the effective treatment and management of diabetes. Methods: Information about plant secondary metabolites, phenolic compounds, and their role in the treatment and management of diabetes was collected from different databases, such as Pubmed, ScienceDirect, Scopus, and Google Scholar. Keywords like secondary metabolites, phenolic compounds, simple phenol, flavonoids, lignans, stilbenes, and diabetes were searched. Research and review articles with relevant information were included in the study. Results: Anti-diabetic studies of the four major classes of phenolic compounds were included in this review. The plant-derived phenolic compounds were reported to have potent anti-diabetic activities. However, each class of phenolic compounds was found to behave differently according to various mechanisms. Conclusion: The obtained results suggest that phenolic compounds derived from natural sources display promising anti-diabetic activities. Based on the available information, it can be concluded that phenolic compounds obtained from various natural sources play key roles in the treatment and management of diabetes.

• Journal of Cadastre & Land InformatiX
• /
• v.48 no.1
• /
• pp.5-14
• /
• 2018

Recently the construction of solar plant showed a steady growth in influence of renewable energy policy. It is very important to determine the optimal location and aspect of solar panel using analyzed data of solar radiation to solar plant area beforehand. This study analyzed solar radiation in solar plant area using DEM acquired from UAV geospatial information. Mean solar radiation of 2017 was calculated as $1,474,466W/m^2$ and total solar radiation of 2017 considering solar plant area showed $33,639MW/m^2$ on analyzed result. It is important to analyze monthly solar radiation in aspect of maintenance works of solar plant. Monthly solar radiation of May to July was calculated over $160,000W/m^2$ and that of January to February and November to December showed under $80,000W/m^2$ in monthly solar radiation analysis of solar plant area. Also this study compared with solar radiation being calculated from UAV geospatial information and that of National Institute of Meteorological Sciences. And mean solar radiation of study area showed a little high in comparison with whole country data of National Institute of Meteorological Sciences, because the 93.7% of study area was composed of south aspect. Therefore this study can be applied to calculate solar radiation in new developed solar plant area very quickly using UAV.

• The Plant Pathology Journal
• /
• v.17 no.6
• /
• pp.370.4-370
• /
• 2001

• Journal of the Korean Data and Information Science Society
• /
• v.9 no.1
• /
• pp.57-62
• /
• 1998

The minimum number of samples for the measurement of plant characteristics of major crops were calculated from the data obtained from the field experiments on rice, barley, wheat, soybean and sweet potato conducted by Kyungpuk Rural Development Administration.

• Journal of the Korean Society of Safety
• /
• v.35 no.1
• /
• pp.25-33
• /
• 2020

In most plant layout optimization researches, MILP(Mixed Integer Linear Programming) problems, in which the objective function includes the costs of pipelines connecting process equipment and cost associated with safety issues, have been employed. Based on these MILP problems, various optimization solvers have been applied to investigate the optimal solutions. To consider safety issues on the objective function of MILP problems together, the accurate information about the impact and the frequency of potential accidents in a plant should be required to evaluate the safety issues. However, it is really impossible to obtain accurate information about potential accidents and this limitation may reduce the reliability of a plant layout problem. Moreover, in real industries such as plant engineering companies, the plant layout is previously fixed and the considerations of various safety instruments and systems have been performed to guarantee the plant safety. To reflect these situations, the two step optimization problems have been designed in this study. The first MILP model aims to minimize the costs of pipelines and the land size as complying sufficient spaces for the maintenance and safety. After the plant layout is determined by the first MILP model, the optimal locations of blast walls have been investigated to maximize the mitigation impacts of blast walls. The particle swarm optimization technique, which is one of the representative sampling approaches, is employed throughout the consideration of the characteristics of MILP models in this study. The ethylene oxide plant is tested to verify the efficacy of the proposed model.

• Journal of Convergence for Information Technology
• /
• v.7 no.1
• /
• pp.49-54
• /
• 2017

In this paper, we propose a system that can provide a environment for plant cultivation in connection with LED plant factories and enable users to participate in plant cultivation remotely to engage in personal hobbies. The proposed system can monitor the growth conditions of plants through various sensors and remotely adjust the cultivation environment required for plant growth through the Arduino system, so that users can feel the satisfaction of plant cultivation and harvesting as a hobby. On the other hand, we suggest a mutual benefit structure for plant factory and users by securing a certain amount of income source to factory, by paying the idle space to the individual online. This paper demonstrates the feasibility of the proposed system by making the prototype of the remote plant cultivation consignment system using the Arduino and Android application(App.), and contributes to popularize the LED plant factories and expand the business area in future.

• Journal of the Korea Society for Simulation
• /
• v.17 no.4
• /
• pp.1-9
• /
• 2008

Proposed in the paper is an automated procedure to construct a plant model for PLC simulation. Since PLC programs only contain the control logic without the information on the plant model, it is necessary to build the corresponding plant model to perform simulation. Conventionally, a plant model for PLC simulation has been constructed manually, and it requires much efforts as well as the in-depth knowledge of simulation. As a remedy for the problem, we propose an automated procedure to generate a plant model from the symbol table of a PLC program. To do so, we propose a naming rule for PLC symbols so that the symbol names include enough information on the plant model. By analyzing such symbol names, we extract a plant model automatically. The proposed methodology has been implemented, and test runs were made.