• Bulletin of the Korean Chemical Society
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• v.17 no.3
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• pp.257-262
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• 1996

p-(2-Vinyloxyethoxy)benzylidenemalononitrile 2 and methyl p-(2-vinyloxyethoxy)benzylidenecyanoacetate 3 was prepared by the condensation of p-(2-vinyloxyethoxy)benzaldehyde 1 with malononitrile or methyl cyanoacetate, respectively. Vinyl ether monomers 2 and 3 polymerized quantitatively with radical initiators in γ-butyrolactone solution at 65 ℃. The trisubstituted terminal double bond participated in the vinyl polymerization and radical polymerization of 2 and 3 led to swelling polymers 4 and 5 that were not soluble in common solvents due to cross-linking. Under the same polymerization conditions ethylvinyl ether polymerized well with model compounds of p-methoxybenzylidenemalononitrile 6 and methyl p-methoxybenzylidenecyanoacetate 7, respectively, to give 1:1 alternating copolymers 8 and 9 in high yields. Polymers 4 and 5 showed a thermal stability up to 300 ℃ without any characteristic Tg peaks in DSC thermograms. Alternating copolymers 8 and 9 were soluble in common solvents such as acetone and DMSO, and the inherent viscosities of the polymers were in the range of 0.36-0.74 dL/g. Films cast from acetone solution were cloudy and tough and Tg values obtained from DSC thermograms were in the range of 59-60 ℃.

• Bulletin of the Korean Chemical Society
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• v.18 no.3
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• pp.318-323
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• 1997

ο-(2-Vinyloxyethoxy)benzylidenemalononitrile (3a) and methyl ο-(2-vinyloxyethoxy)-benzylidenecyanoacetate (3b), m-(2-vinyloxyethoxy)benzylidenemalononitrile (4a), and methyl m-(2-vinyloxyethoxy)benzylidenecyanoacetate (4b) were prepared by the condensation of ο-(2-vinyloxyethoxy)benzaldehyde (1) and m-(2-vinyloxyethoxy)benzaldehyde (2) with malononitrile or methyl cyanoacetate, respectively. Bifunctional vinyl ether monomers 3a and 3b polymerized quantitatively with radical initiators in γ-butyrolactone solution at 65 ℃, while meta-isomers 4a and 4b gave lower yields of polymers under the same conditions. The polymers 5-6 obtained from the monomers 3-4 were insoluble in common solvents due to cross-linking. Under the same polymerization conditions ethyl vinyl ether polymerized well with model compounds ο-methoxybenzylidenemalononitrile 7a, methyl ο-methoxybenzylidenecyanoacetate 7b, m-methoxybenzylidenemalononitrile 8a, and methyl m-methoxybenzylidenecyanoacetate 8b, respectively, to give 1:1 alternating copolymers 9-10 in high yields. Cross-linked polymers 5-6 showed a thermal stability up to 300 ℃, and showed a double phase degradation pattern in their TGA thermograms. Polymers 5-6 showed broad endothermic bands around 75-110 ℃ without any characteristic Tg peaks in DSC thermograms. Alternating copolymers 9-10, except copolymer 9b were soluble in common organic solvents. The inherent viscosities of polymer 9-10 were in the range of 0.35-0.62 dL/g. Polymer films cast from acetone solution were cloudy and tough and Tg values obtained from DSC thermograms were in the range of 118-165 ℃.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1195-1200
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• 2020

The DOM (: Digital Optical Method), which measures the turbidity of chimney smoke, is a method of calculating the turbidity by setting the area to be measured and the contrast area using a low-cost digital camera that can be easily obtained. However, it is difficult to measure clouds and white smoke in a cloudy sky. In this paper, we develop a background sky type model that can represent the background sky and classify the type by periodically photographing it with a digital camera to solve this problem. In addition, based on the model, we develop a filter to optimize white smoke image and prove its excellence through experiments.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.245-254
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• 2022

Sensor dataset for autonomous driving is one of the essential components as the deep learning approaches are widely used. However, most driving datasets are focused on typical environments such as sunny or cloudy. In addition, most datasets deal with color images and lidar. In this paper, we propose a driving dataset with multi-spectral images and lidar in adverse weather conditions such as snowy, rainy, smoky, and dusty. The proposed data acquisition system has 4 types of cameras (color, near-infrared, shortwave, thermal), 1 lidar, 2 radars, and a navigation sensor. Our dataset is the first dataset that handles multi-spectral cameras in adverse weather conditions. The Proposed dataset is annotated as 2D semantic labels, 3D semantic labels, and 2D/3D bounding boxes. Many tasks are available on our dataset, for example, object detection and driveable region detection. We also present some experimental results on the adverse weather dataset.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.491-500
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• 2024

In hopes of resolving the issue of poor quality of information input for teaching spoken English online, the study creates an English teaching assistance model based on a recognition algorithm named dynamic time warping (DTW) and relies on automated voice recognition technology. In hopes of improving the algorithm's efficiency, the study modifies the speech signal's time-domain properties during the pre-processing stage and enhances the algorithm's performance in terms of computational effort and storage space. Finally, a simulation experiment is employed to evaluate the model application's efficacy. The study's revised DTW model, which achieves recognition rates of above 95% for all phonetic symbols and tops the list for cloudy consonant recognition with rates of 98.5%, 98.8%, and 98.7% throughout the three tests, respectively, is demonstrated by the study's findings. The enhanced model for DTW voice recognition also presents higher efficiency and requires less time for training and testing. The DTW model's KS value, which is the highest among the models analyzed in the KS value analysis, is 0.63. Among the comparative models, the model also presents the lowest curve position for both test functions. This shows that the upgraded DTW model features superior voice recognition capabilities, which could significantly improve online English education and lead to better teaching outcomes.

• Corrosion Science and Technology
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• v.7 no.2
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• pp.119-124
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• 2008

Steel is generally not corrosion resistant to water with formation of non protective rusts on its surface. Rusts are composed of iron oxides such as $Fe_3O_4$, $\alpha-$, $\beta-$, $\gamma-$and ${\delta}-FeOOH$. However, steel, particularly weathering steel containing small amounts of Cu, Ni and Cr etc., shows good corrosion resistance against rural, industrial or marine environment. Its corrosion rate is exceedingly small as compared with that of carbon steel. According to the exposure test results undertaken in outdoor environments, the atmospheric corrosion rate for weathering steel is only 1 mm for a century. Atmospheric corrosion for steels proceeds under alternate dry and wet conditions. Dry condition is encountered on steel surface on fine or cloudy days, and wet condition is on rainy or snowy days. The reason why weathering steel shows superior atmospheric corrosion resistance is due to formation of corrosion protective rusts on its surface under very thin water layer. The protective rusts are usually composed of two layer rusts; the upper layer is ${\gamma}-FeOOH$ termed as lepidocrocite, and inner layer is nano-particle ${\alpha}-FeOOH$ termed as goethite. This paper is aimed at elucidating the atmospheric corrosion mechanism for steel in comparison with corrosion in bulky water environment by use of empirical data.The summary is as follows: 1. No corrosion protective rusts are formed on steel in bulky water. 2. Atmospheric corrosion for steel is the corrosion under wetting and drying conditions. Corrosion and passivation occur alternately on steel surface. Steel, particularly weathering steel with small amounts of alloying elements such as Cu, Ni and Cr etc. enhances forming corrosion protective rusts by passivation.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.99-105
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• 2017

In this paper, we propose to design and implement the database management system for analyzing vehicle accidents through utilizing integration of the public big data. And the paper aims to provide valuable information for recognizing seriousness of the vehicle accidents and various circumstances at the accident time, and to utilize the produced information for the insurance company policies as well as government policies. For analysis of the vehicle accidents the system utilizes the integrated big data of National Indicator System, the Meteorological Office, National Statistical Office, Korea Insurance Development Institute, Road Traffic Authority, Ministry of Land, Infrastructure and Transport as well as the National Police Agency, which differentiates this system from the previous systems. The system consists of data at the accident time including weather conditions, vehicle models, age, sex, insurance amount etc., by which the database system users are able to obtain the integral information about vehicle accidents. The result shows that the vehicle accidents occur more frequently in the clear weather conditions, in the vehicle to vehicle conditions and in crosswalk & crossway. Also, it shows that the accidents in the cloudy weather leads more seriously to injury and death than in the clear weather. As well, the vehicle accident information produced by the system can be utilized to effectively prevent drivers from dangerous accidents.

• Journal of the Korean Solar Energy Society
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• v.36 no.6
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• pp.37-46
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• 2016

In this study, long-term global illuminance data for 19 selected cities are calculated from modeled solar radiation data, AEER's TMY2. Perez model in Daysim daylight simulation tool is used for the solar radiation to illuminance conversion. And then, daylight availability in an unit office space is evaluated for the 19 cities. For this evaluation, various daylight performance indices are reviewed since static daylight performance index such as daylight factor (DF) and annual average global illuminance value is not suitable for actual performance evaluation in terms of visual comfort and light energy saving of a space. This study evaluated daylighting performance of prototypical office space module by introducing DA (daylight autonomy) and UDI (Useful Daylight Illuminance) index for major cities of Korea. Result shows that there is upto 18% of illuminance level difference with annual average global illuminance data, but if we consider useful daylight in a space the illuminance level difference among the cities are only within 5%. This means that for sustainable building design especially in daylight design, amount of annual global illuminance is not important factor even in cloudy cities. Daylight design and daylight harvesting system would return similar energy saving impact regardless of building location.

• Journal of Environmental Health Sciences
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• v.29 no.1
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• pp.51-61
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• 2003

Pollution purification using titanium dioxide (TiO$_2$) photocatalyst has attracted a great deal of attention with increasing number of relent environmental problems. Currently, the application of TiO$_2$ photocatalyst has been focused on purification and treatment of waste water. However. the use of conventional TiO$_2$ powder photocatalyst results in disadvantage of stirring during the reaction and of separation after the reaction. And the usage of artificial UV lamp has made the cost of photocatalyst treatment system high. Consequently, we herein studied the pilot-scale design to aid in optimization of the energy-saving process for more through development and reactor design by solar light/UV lamp/ TiO$_2$system. In this study, we manufactured the TiO$_2$sol by sol-gel method. According to analysis by XRD, SEM and TEM, characterization of TiO$_2$ sol were nano-size (5-6 nm) and anatase type. Inorganic binder (SiO$_2$) was added to TiO$_2$ lot to be coated for support strongly, and support of ceramic bead was used to lower separation rate that of glass bead The influences were studied of various experimental parameters such as TiO$_2$ quantity, pH, flow rate. additives, pollutants concentration, climate condition and reflection plate by means of reaction time of the main chararteristics of the obtained materials. In water treatment system, variable realtor as solar light/ or UV lamp according to climate condition such as sunny and cloudy days treated the phenol and E-coli(Escherichia coli) effectively.