According to one embodiment of the present invention, there is provided a hydrogen extraction reactor, comprising a chamber including an inner space; a reaction unit which is provided to pass through the inside of the chamber and where an endothermic reaction for hydrogen extraction occurs; a heating unit which is provided to be spaced apart from the reaction unit inside the chamber and transfers heat to the inside of the chamber; and a heat transfer material which is provided between the reaction unit and the heating unit in the chamber, wherein the heat transfer material undergoes a phase transition between a gas phase and a liquid phase according to the entry and exit of heat from the heating unit or the reaction unit.

According to one embodiment of the present invention, there is provided a hydrogen extraction reactor, comprising a chamber including an inner space; a reaction unit which is provided to pass through the inside of the chamber and where an endothermic reaction for hydrogen extraction occurs; a heating unit which is provided to be spaced apart from the reaction unit inside the chamber and transfers heat to the inside of the chamber; and a heat transfer material which is provided between the reaction unit and the heating unit in the chamber, wherein the heat transfer material undergoes a phase transition between a gas phase and a liquid phase according to the entry and exit of heat from the heating unit or the reaction unit.

A method for identifying, classifying, and sending notification of an electric arc furnace's (EAF) anomalies to improve the EAF efficiency. The method includes the steps of establishing baseline state measurements of the EAF, receiving new state measurements of the EAF and statistically testing the new state measurements against the baseline state measurements. The method further includes the steps of identifying as an anomaly a failed statistical test, classifying the identified anomaly and sending notification of the classified anomaly to a configurable list of recipients.

A method for identifying, classifying, and sending notification of an electric arc furnace's (EAF) anomalies to improve the EAF efficiency. The method includes the steps of establishing baseline state measurements of the EAF, receiving new state measurements of the EAF and statistically testing the new state measurements against the baseline state measurements. The method further includes the steps of identifying as an anomaly a failed statistical test, classifying the identified anomaly and sending notification of the classified anomaly to a configurable list of recipients.

According to one embodiment of the present invention, there is provided a hydrogen extraction reactor, comprising a chamber including an inner space; a reaction unit which is provided to pass through the inside of the chamber and where an endothermic reaction for hydrogen extraction occurs; a heating unit which is provided to be spaced apart from the reaction unit inside the chamber and transfers heat to the inside of the chamber; and a heat transfer material which is provided between the reaction unit and the heating unit in the chamber, wherein the heat transfer material undergoes a phase transition between a gas phase and a liquid phase according to the entry and exit of heat from the heating unit or the reaction unit.

According to one embodiment of the present invention, there is provided a hydrogen extraction reactor, comprising a chamber including an inner space; a reaction unit which is provided to pass through the inside of the chamber and where an endothermic reaction for hydrogen extraction occurs; a heating unit which is provided to be spaced apart from the reaction unit inside the chamber and transfers heat to the inside of the chamber; and a heat transfer material which is provided between the reaction unit and the heating unit in the chamber, wherein the heat transfer material undergoes a phase transition between a gas phase and a liquid phase according to the entry and exit of heat from the heating unit or the reaction unit.

An image processing apparatus includes a sub-image generation unit, a luminance ratio map generation unit, and an electric heating wire pattern estimation unit. The sub-image generation unit generates sub-images by dividing a first image in a lateral direction. The first image is one of a left image and a right image that are captured by a stereo camera through a windshield provided with an electric heating wire. The luminance ratio map generation unit sequentially selects one of the sub-images and generates map data based on the selected sub-image and a second image. The map data indicates a ratio between luminance values. The second image is another of the left image and the right image. The electric heating wire pattern estimation unit performs an estimation of a wiring pattern of the electric heating wire based on the map data regarding each of the sub-images.

An image processing apparatus includes a sub-image generation unit, a luminance ratio map generation unit, and an electric heating wire pattern estimation unit. The sub-image generation unit generates sub-images by dividing a first image in a lateral direction. The first image is one of a left image and a right image that are captured by a stereo camera through a windshield provided with an electric heating wire. The luminance ratio map generation unit sequentially selects one of the sub-images and generates map data based on the selected sub-image and a second image. The map data indicates a ratio between luminance values. The second image is another of the left image and the right image. The electric heating wire pattern estimation unit performs an estimation of a wiring pattern of the electric heating wire based on the map data regarding each of the sub-images.

A method for identifying, classifying, and sending notification of an electric arc furnace's (EAF) anomalies to improve the EAF efficiency. The method includes the steps of establishing baseline state measurements of the EAF, receiving new state measurements of the EAF and statistically testing the new state measurements against the baseline state measurements. The method further includes the steps of identifying as an anomaly a failed statistical test, classifying the identified anomaly and sending notification of the classified anomaly to a configurable list of recipients.

A method for identifying, classifying, and sending notification of an electric arc furnace's (EAF) anomalies to improve the EAF efficiency. The method includes the steps of establishing baseline state measurements of the EAF, receiving new state measurements of the EAF and statistically testing the new state measurements against the baseline state measurements. The method further includes the steps of identifying as an anomaly a failed statistical test, classifying the identified anomaly and sending notification of the classified anomaly to a configurable list of recipients.