• Resources Recycling
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• v.23 no.2
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• pp.3-16
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• 2014

Car exhaust $CO_2$ gas reduction and fuel efficiency of the car lighter for the current era is a big challenge. The developments of high-performance Nd magnets, Li-ion secondary battery and exhaust gas purification performance of PGM catalysts used in the lightweight EV and HEV are activated. Country in order to improve the car lighter and function that use the resources of rare metals are ubiquitous imported from China because of export supply control, as soaring prices have unstable supply and demand. Compared to the emissions from the next-generation automotive recycling, waste scarce resources need to be. This study investigated the recycling technology analysis and development of the information technology, or delivered to the researchers by giving national car industry aims to contribute to the development. Findings, pulmonary high-performance motor vehicle emissions in the exhaust gas purification PGM Catalysts, Li-ion battery and Nd magnets recycling technology, such as pre- and post-processing techniques to classify technology, pre-urban mining technology mechanical separation by screening techniques under development, the study and post-processing technology has, pyro and hydro metallurgical smelting technology is established. Waste Recycling in terms of economic efficiency of mechanical components for the intensive study of screening techniques is needed.

• Clean Technology
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• v.22 no.2
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• pp.96-105
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• 2016

VOCs emissions from industries cause the air pollution and odor. In the industrial facilities, the existing odor treatment techniques have limits and problems. In this study, the optimum essential oil and metal oxide selected by screening test. lavender oil, cypress oil and TiO₂ were determined by deodorant materials and those were blended by 5%, 45%, 10%, respectively. In addition, the result of batch type experiments depending on the dilution rate, injection, rate, temperature showed that the optimum condition of deodorant is 6 mL of injection rate, and 200 times of dilution rate and the removal efficiency increased in proportion with temperature. In addition, the activation energy was calculated from the rate equation, which appeared in the 3-4 times lower than conventional deodorants.

• Journal of Life Science
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• v.33 no.7
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• pp.531-537
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• 2023

Intracellular and axonal transport is mediated by microtubule-dependent motor proteins, such as kinesins and cytoplasmic dynein. Kinesin moves along the microtubule to the positive end of the microtubule, while dynein moves to the negative end of the microtubule. Kinesin-1 was first identified as a kinesin superfamily protein (KIF) that functions in the intracellular transport of various cargoes, including organelles, neurotransmitter receptors, and mRNA-protein complexes, through interactions between the carboxyl (C)-terminal domain and the cargo. It interacts with other cargoes, but the adapter/scaffold proteins that mediate between kinesin-1 and the cargo have yet to be fully identified. In this study, a yeast two-hybrid screen was used to identify adapter proteins that interact with the C-terminal region of KIF5A. We found an association between the C-terminal region of KIF5A and the cyclin-dependent kinase 2-associated protein 1 (CDK2AP1), originally identified in malignant hamster oral keratinocytes. CDK2AP1 bound to the C-terminal region of KIF5A and did not interact with KIF3A (the motor of kinesin-2), KIF5B, KIF5C, and kinesin light chain 1 (KLC1). The C-terminal region of CDK2AP1 is essential for its interaction with KIF5A. When co-expressed in HEK-293T cells, CDK2AP1 and kinesin-1 co-immunoprecipitated and co-localized in the cells. These results suggest that the KIF5A-CDK2AP1 interaction serves as an adapter protein connecting kinesin-1 and the cargo when kinesin-1 transports cargo in cells.

• Journal of Technology Innovation
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• v.26 no.3
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• pp.37-68
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• 2018

Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.