• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.04a
• /
• pp.576-579
• /
• 2011

Wireless sensor network are widely all over different fields. Because of its distinguished characteristics, we must take account of the factor of energy consumed when designing routing protocol. Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors sends data from the CH (Cluster Head) and then to the BS (Base Station). BCDCP works well in a smallscale network however is not preferred in a large scale network since it uses much energy for long distance wireless communication. TBRP can be used for large scale network, but it weakness lies on the fact that the nodedry out of energy easily since it uses multi-hops transmission data to the Base Station. Here, we proposed a routing protocol. A Cluster Based Energy Efficient Tree Routing Protocol (CETRP) in Wireless Sensor Networks (WSNs) to prolong network life time through the balanced energy consumption. CETRP selects Cluster Head of cluster tree shape and uses maximum two hops data transmission to the Cluster Head in every level. We show CETRP outperforms BCDCP and TBRP with several experiments.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.2
• /
• pp.157-168
• /
• 2009

In this paper, a photovoltaic system is designed with a step up chopper and single phase PWM(Pulse Width Modulation) voltage source inverter. Where proposed Synchronous signal and control signal was processed by one-chip microprocessor for stable modulation. The step up chopper operates in continuous mode by adjusting the duty ratio so that the photovoltaic system tracks the maximum power point of solar cell without any influence on the variation of insolation and temperature because solar cell has typical voltage and current dropping character. The single phase PWM voltage source the inverter using inverter consists of complex type of electric power converter to compensate for the defect, that is, solar cell cannot be developed continuously by connecting with the source of electric power for ordinary use. It can cause the effect of saving electric power. from 10 to 20[%]. The single phase PWM voltage source inverter operates in situation that its output voltage is in same phase with the utility voltage. In order to enhance the efficiency of photovoltaic cells, photovoltaic positioning system using sensor and microprocessor was design so that the fixed type of photovoltaic cells and photovoltaic positioning system were compared. In result, photovoltaic positioning system can improved 5% than fixed type of photovoltaic cells. In addition, I connected extra power to the system through operating the system voltage and inverter power in a synchronized way by extracting the system voltage so that the phase of the system and the phase of single-phase inverter of PWM voltage type can be synchronized. And, It controlled in order to provide stable pier to the load and the system through maintaining high lurer factor and low output power of harmonics.

• Journal of Appropriate Technology
• /
• v.5 no.2
• /
• pp.70-81
• /
• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.

• Journal of Environmental Impact Assessment
• /
• v.32 no.3
• /
• pp.157-165
• /
• 2023

In Korea, a major contaminant of farmland soils in the vicinity of abandoned mines is arsenic, for which the general soil reclamation method is contaminated soil stabilization and cover the stabilized soil with clean soil at a thickness of 40 cm. In a previous pot experiment study we confirmed the feasibility of a lower thickness (20 cm) of covering soil for such reclamation in abandoned coal mines, where arsenic contamination levels are generally lower than in metal mines. In this subsequent study a field experiment including rice plant cultivation in field test plots was conducted. For over 4 months, the transfer of arsenic from the contaminated soil to the unpolished rice grains was reduced by 44% when a clean soil covering with a thickness of 20 cm was applied. The maximum decrease (56%) was shown when the stabilization process was performed before the covering. These results reveal a lower thickness of clean soil covering has a high feasibility and it can increase cost-efficiency in the reclamation of an abandoned coal mine.

• Resources Recycling
• /
• v.32 no.3
• /
• pp.3-8
• /
• 2023

This study discussed production, demand, and future prospects of rubidium, which is an alkali group metal that is highly reactive to various media and requires carefulness in handling, but no significant environmental hazard of rubidium has been reported yet. Rubidium is used in various fields such as optoelectronic equipment, biomedical, and chemical industries. Because of difficulty in production as well as limited demand, the transaction price of rubidium is relatively high, but its detail information such as market status and potential growth is uncertain. However, if the mass production of versatile ultra-high-performance equipment such as quantum computers and the necessity of rubidium use in the equipment are confirmed, there is a possibility that the rubidium market will expand in the future. Rubidium is often found together with lithium, beryllium, and cesium, and may be present in granite containing minerals such as lepidolite and pollucite, as well as in seawater and industrial waste. Several technologies such as acid leaching, roasting, solvent extraction, and adsorption are used to recover rubidium. The maximum recovery efficiency of the rubidium from the sources and the processing above is generally high, but, in many practices, rubidium is not the main recovery target, and therefore the actual recovery effects should depend on presence of other valuable components or impurities, together with recovery costs, energy consumption, environmental issues, etc. In conclusion, although the current production and consumption of rubidium are limited, with consideration of the possible market fluctuations according to the emergence of large-scale demand sources, etc., further investigations by related institutions should be necessary.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.4C
• /
• pp.145-151
• /
• 2009

In general, a drilled shaft embedded in weathered rock has a large load bearing capacity. Therefore, most of the load tests are performed only up to the load level that confirms the pile design load capacity, and stopped much before the ultimate load of the pile is attained. If a reliable ultimate load value can be extracted from the premature load test data, it will be possible to greatly improve economic efficiency as well as pile design quality. The main purpose of this study is to propose a method for judging the reliability of the ultimate load of piles that is obtained from extrapolated load test data. To this aim, ten static load test data of load-displacement curves were obtained from testing of piles to their failures from 3 different field sites. For each load-displacement curve, loading was assumed as 25%, 50%, 60%, 70%, 80%, and 90% of the actual pile bearing capacity. The limited known data were then extrapolated using the hyperbolic function, and the ultimate capacity was re-determined for each extrapolated data by the Davisson method (1972). Statistical analysis was performed on the reliability of the re-evaluated ultimate loads. The results showed that if the ratio of the maximum-available displacement to the predicted displacement exceeds 0.6, the extrapolated ultimate load may be regarded as reliable, having less than a conservative 20% error on average. The applicability of the proposed method of judgment was also verified with static load test data of driven piles.

• Smart Media Journal
• /
• v.12 no.10
• /
• pp.63-70
• /
• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.10
• /
• pp.123-132
• /
• 2023

Git's commit messages manage the history of source changes during project progress or operation. By utilizing this historical data, project risks and project status can be identified, thereby reducing costs and improving time efficiency. A lot of research related to this is in progress, and among these research areas, there is research that classifies commit messages as a type of software maintenance. Among published studies, the maximum classification accuracy is reported to be 95%. In this paper, we began research with the purpose of utilizing solutions using the commit classification model, and conducted research to remove the limitation that the model with the highest accuracy among existing studies can only be applied to programs written in the JAVA language. To this end, we designed and implemented an additional step to standardize source change data into natural language using GPT. This text explains the process of extracting commit messages and source change data from Git, standardizing the source change data with GPT, and the learning process using the DistilBERT model. As a result of verification, an accuracy of 91% was measured. The proposed model was implemented and verified to ensure accuracy and to be able to classify without being dependent on a specific program. In the future, we plan to study a classification model using Bard and a management tool model helpful to the project using the proposed classification model.

• Journal of Environmental Science International
• /
• v.32 no.12
• /
• pp.899-914
• /
• 2023

Various seeding materials for cloud seeding are being used, and sodium chloride powder is one of them, which is commonly used. This study analyzed the experimental results of multi-aircraft cloud seeding in connection with Republic of Korea Air Force (CN235) and KMA/NIMS(Korea Meteorological Administration/National Institute of Meteorological Sciences) Atmospheric Research Aircraft. Powdered sodium chloride was used in CN235 for the first time in South Korea. The analysis of the cloud particle size distributions and radar reflectivity before and after cloud seeding showed that the growth efficiency of powdery seeding material in the cloud is slightly higher than that of hygroscopic flare composition in the distribution of number concentrations by cloud aerosol particle diameter (10 ~ 1000 ㎛). Considering the radar reflectivity, precipitation, and numerical model simulation, the enhanced precipitation due to cloud seeding was calculated to be a maximum of 3.7 mm for 6 hours. The simulated seeding effect area was about 3,695 km², which corresponds to 13,634,550 tons of water. In the precipitation component analysis, as a direct verification method, the ion equivalent concentrations (Na⁺, Cl^-, Ca²⁺) of the seeding material at the Bukgangneung site were found to be about 1000 times higher than those of other non-affected areas between about 1 and 2 hours after seeding. This study suggests the possibility of continuous multi-aircraft cloud seeding experiments to accumulate and increase the amount of precipitation enhancement.

• The Journal of Engineering Geology
• /
• v.33 no.4
• /
• pp.627-638
• /
• 2023

This study aimed to evaluate the spatial variability of downstream river flow resulting from the operation of the Gimcheon Buhang Dam in the Gamcheon watershed. The dam's effects on flood reduction during the flood season and on increasing streamflow during the dry season-two main functions of multipurpose dams-were quantitatively analyzed. Streamflow data from 2013 to 2021 for the study waterhsed were simulated on a daily basis using SWAT-K (Soil and Water Assessment Tool - Korea) model. Comparison of the simulated and observed values found goodness of fit values of 0.75 or higher for both the coefficient of determination and the Nash-Sutcliffe model efficiency coefficient. The spatial analysis of the dam's effect on flood reduction focused on the annual maximum flood: rates of flood reduction at the four stations ranged from 8.5% to 25.0%. The evaluation of streamflow increase during times of low flow focused on flow duration curves: in particular, compared to the case without an upstream dam, the average low flow at the four sites increased from 33% to 198%.