Abstract: One embodiment of the present invention provides an ecotoxicity monitoring device using Aliivibrio fischeri, and an ecotoxicity monitoring method using the same. The ecotoxicity monitoring device includes a reaction tank module, an Aliivibrio fischeri culture unit, a diluted water supply unit, a sample supply unit, an optical measurement unit, a control unit and an analysis unit, wherein the analysis unit is configured to calculate a correction coefficient based on the initial light quantity value of a reference reaction tank measured through the optical measurement unit and the final light quantity value measured after a predetermined time has elapsed, and calculate the corrected light quantity values of a sample reaction tank and a dilution reaction tank based on the calculated correction coefficient.

Abstract: The present invention relates to a solid oxide fuel cell (SOFC) system in which ammonia is applied and, more specifically, to: an ammonia-based SOFC system which is mobile and in which heating element temperature rise allowing a COx-free and NOx-free eco-friendly system is applied; and an operation method therefor.

Abstract: The present invention relates to a solid oxide fuel cell (SOPC) system in which ammonia is applied and, more specifically, to: an ammonia-based SOFC system which is mobile and in which heating element temperature rise allowing a COx-free and NOx-free eco-friendly system is applied; and an operation method therefor.

Abstract: A detection device includes a substrate, first electrodes formed on a first surface of the substrate, a responsive layer, and second electrodes formed on a first surface of the responsive layer, each of the second electrodes are capacitively coupled to one of the first electrodes and each second electrode is connected to a power supply to provide driving power.

Abstract: Disclosed are a method and apparatus for estimating lithofacies by learning well logs. The method includes a model formation step of forming lithofacies estimation model to output lithofacies corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having lithofacies corresponding to measured depth as answers, and lithofacies estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which lithofacies are to be estimated, the values being arranged corresponding to measured depth, to the lithofacies estimation model to estimate lithofacies corresponding to measured depth.

Abstract: Disclosed are a method and apparatus for estimating S-wave velocities by learning well logs, whereby the method includes a model formation step of forming an S-wave estimation model to output S-wave velocities corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having S-wave velocities corresponding to measured depth as answers, and an S-wave velocity estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which S-wave velocities are to be estimated, the values being arranged corresponding to measured depth, to the S-wave estimation model to estimate S-wave velocities corresponding to measured depth.

Abstract: Provided is a drug hypersensitivity prevention system. A drug hypersensitivity prevention system according to an embodiment of the present application may comprise: a first fluid storage unit 10; a second fluid storage unit 20; a control device 30 including a first pump 31 installed in a discharge line connected to the first fluid storage unit 10 so as to control an amount of a first fluid discharged from the first fluid storage unit 10, and a second pump 32 installed in a discharge line connected to the second fluid storage unit 20 so as to control an amount of a second fluid discharged from the second fluid storage unit 20; a mixing unit 40 in which the first fluid discharged from the first fluid storage unit 10 and the second fluid discharged from the second fluid storage unit 20 are mixed; a pouch 50 connected to the mixing unit 40; and a catheter 60 connected to the mixing unit 40.

Abstract: Disclosed are a method and apparatus for estimating S-wave velocities by learning well logs, whereby the method includes a model formation step of forming an S-wave estimation model to output S-wave velocities corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having S-wave velocities corresponding to measured depth as answers, and an S-wave velocity estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which S-wave velocities are to be estimated, the values being arranged corresponding to measured depth, to the S-wave estimation model to estimate S-wave velocities corresponding to measured depth.

Abstract: Disclosed are a method and apparatus for estimating S-wave velocities by learning well logs, whereby the method includes a model formation step of forming an S-wave estimation model to output S-wave velocities corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having S-wave velocities corresponding to measured depth as answers, and an S-wave velocity estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which S-wave velocities are to be estimated, the values being arranged corresponding to measured depth, to the S-wave estimation model to estimate S-wave velocities corresponding to measured depth.

Abstract: A detection device includes a substrate, first electrodes formed on a first surface of the substrate, a responsive layer, and second electrodes formed on a first surface of the responsive layer, each of the second electrodes are capacitively coupled to one of the first electrodes and each second electrode is connected to a power supply to provide driving power.

Abstract: Disclosed are a method and apparatus for estimating S-wave velocities by learning well logs, whereby the method includes a model formation step of forming an S-wave estimation model to output S-wave velocities corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having S-wave velocities corresponding to measured depth as answers, and an S-wave velocity estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which S-wave velocities are to be estimated, the values being arranged corresponding to measured depth, to the S-wave estimation model to estimate S-wave velocities corresponding to measured depth.

Abstract: Disclosed are a method and apparatus for estimating S-wave velocities by learning well logs, whereby the method includes a model formation step of forming an S-wave estimation model to output S-wave velocities corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having S-wave velocities corresponding to measured depth as answers, and an S-wave velocity estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which S-wave velocities are to be estimated, the values being arranged corresponding to measured depth, to the S-wave estimation model to estimate S-wave velocities corresponding to measured depth.

Abstract: The present invention relates to a composition for diagnosing bone metastasis of cancer, a method for providing information needed for diagnosis of bone metastasis of cancer using same, a method for providing information needed for monitoring responses to treatment of bone metastasis of cancer using same, and a method for screening a therapeutic agent for bone metastasis of cancer using same. The composition for diagnosing bone metastasis of cancer of the present invention has the effect of effectively diagnosing bone metastasis of cancer at an early stage.

Abstract: The present invention relates to a method of preparing ultra-pure silicon carbide in which a super-porous spherical silica aerogel is used as a silica raw material. By preparing the silica aerogel particles using low-cost water glass, a reaction area with respect to a carbon raw material is increased to enable low-temperature synthesis of silicon carbide, the size and shape of silicon carbide powder may be uniformly controlled to prepare ultra-pure silicon carbide, and economic efficiency and productivity of the silicon carbide synthesis may be improved. Thus, it is expected that the silicon carbide powder prepared by the preparation method of the present invention may be provided as an optimized raw material for the preparation of silicon carbide sintered body and single crystal (ingot).

Abstract: Disclosed are a method and apparatus for estimating lithofacies by learning well logs. The method includes a model formation step of forming lithofacies estimation model to output lithofacies corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having lithofacies corresponding to measured depth as answers, and lithofacies estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which lithofacies are to be estimated, the values being arranged corresponding to measured depth, to the lithofacies estimation model to estimate lithofacies corresponding to measured depth.

Abstract: Disclosed are a method and apparatus for estimating S-wave velocities by learning well logs, whereby the method includes a model formation step of forming an S-wave estimation model to output S-wave velocities corresponding to measured depth when the well logs are input based on train data sets including train data having values of multiple factors included in the well logs, the values being arranged corresponding to measured depth, and label data having S-wave velocities corresponding to measured depth as answers, and an S-wave velocity estimation step of inputting unseen data having values of multiple factors included in well logs acquired from a well at which S-wave velocities are to be estimated, the values being arranged corresponding to measured depth, to the S-wave estimation model to estimate S-wave velocities corresponding to measured depth.

Abstract: The invention relates to a soft starter (10) for connecting at least one main circuit (12, 14, 16), each of which includes a bypass circuit (20) having a semiconductor switch (22). Said soft starter (10) comprises a control unit (40) for actuating the bypass circuit (20), and the control unit (40) is equipped with a control signal input (44). According to the invention, the control unit (40) has a separate safety signal input (42).

Abstract: The present disclosure provides an aerogel-containing composition including an aerogel, a water-soluble binder, a foaming agent, and a mixture of water and a polar organic solvent as a solvent, and an insulation blanket prepared using the same. In the aerogel-containing composition, the aerogel is uniformly dispersed in the composition, and when preparing a blanket, an insulation blanket having low thermal conductivity and flexibility of low density is prepared without concern of shrinkage of the substrate for a blanket and detachment of the aerogel during a drying process.

Abstract: The present disclosure provides an aerogel-containing composition including an aerogel, a water-soluble binder, a foaming agent, and a mixture of water and a polar organic solvent as a solvent, and an insulation blanket prepared using the same. In the aerogel-containing composition, the aerogel is uniformly dispersed in the composition, and when preparing a blanket, an insulation blanket having low thermal conductivity and flexibility of low density is prepared without concern of shrinkage of the substrate for a blanket and detachment of the aerogel during a drying process.

Abstract: The present disclosure provides an aerogel-containing composition including an aerogel, a water-soluble binder, a foaming agent, and a mixture of water and a polar organic solvent as a solvent, and an insulation blanket prepared using the same. In the aerogel-containing composition, the aerogel is uniformly dispersed in the composition, and when preparing a blanket, an insulation blanket having low thermal conductivity and flexibility of low density is prepared without concern of shrinkage of the substrate for a blanket and detachment of the aerogel during a drying process.