Abstract: One embodiment discloses a DC-DC converter which, in a solar-related energy storage system, cuts-off the over-discharging of a battery, and a control method thereof. Specifically, disclosed are a DC-DC converter which protects a battery by appropriately switching between a sleep mode which minimizes battery consumption by maintaining only minimized functions and a cut-off mode which prevents the battery from over-discharging by physically cutting off a circuit connected to the battery, and a control method thereof. Also, an embodiment discloses a DC-DC converter or reverse wiring protection device for between a solar panel and a battery.

Abstract: A semiconductor device includes a substrate. A first channel pattern is disposed on the substrate. The first channel pattern includes a first side and a second side opposite to each other in a first direction. A first gate electrode is disposed on the first side of the first channel pattern. A first source/drain electrode is disposed on the first side of the first channel pattern. A second source/drain electrode is disposed on the second side of the first channel pattern. The first gate electrode overlaps the second source/drain electrode in the first direction.

Abstract: An arc lamp includes an arc tube configured to receive a reaction gas therein, and an anode and a cathode disposed opposite one another within the arc tube and configured to generate an electrical arc. The anode includes an anode head portion extending inwardly from an end portion of the arc tube, and an anode tip portion bonded to the anode head portion and comprising a trench extending in a top surface along a peripheral region of the anode tip portion.

Abstract: An arc lamp includes an arc tube configured to receive a reaction gas therein, and an anode and a cathode disposed opposite one another within the arc tube and configured to generate an electrical arc. The anode includes an anode head portion extending inwardly from an end portion of the arc tube, and an anode tip portion bonded to the anode head portion and comprising a trench extending in a top surface along a peripheral region of the anode tip portion.

Abstract: A method and apparatus for providing a mouse right click function in a touch screen terminal are provided. The method includes detecting occurrence of a first touch, detecting occurrence of a second touch in a status where the first touch is maintained, and displaying an option menu including a plurality of functions on a screen.

Abstract: Disclosed herein is a separate learning system and method using a two-layered neural network having target values for hidden nodes. The separate learning system of the present invention includes an input layer for receiving training data from a user, and including at least one input node. A hidden layer includes at least one hidden node. A first connection weight unit connects the input layer to the hidden layer, and changes a weight between the input node and the hidden node. An output layer outputs training data that has been completely learned. The second connection weight unit connects the hidden layer to the output layer, changing a weight between the output and the hidden node, and calculates a target value for the hidden node, based on a current error for the output node.

Abstract: Disclosed herein is a separate learning system and method using a two-layered neural network having target values for hidden nodes. The separate learning system of the present invention includes an input layer for receiving training data from a user, and including at least one input node. A hidden layer includes at least one hidden node. A first connection weight unit connects the input layer to the hidden layer, and changes a weight between the input node and the hidden node. An output layer outputs training data that has been completely learned. The second connection weight unit connects the hidden layer to the output layer, changing a weight between the output and the hidden node, and calculates a target value for the hidden node, based on a current error for the output node.

Abstract: Disclosed herein is a separate learning system and method using a two-layered neural network having target values for hidden nodes. The separate learning system of the present invention includes an input layer for receiving training data from a user, and including at least one input node. A hidden layer includes at least one hidden node. A first connection weight unit connects the input layer to the hidden layer, and changes a weight between the input node and the hidden node. An output layer outputs training data that has been completely learned. The second connection weight unit connects the hidden layer to the output layer, changing a weight between the output and the hidden node, and calculates a target value for the hidden node, based on a current error for the output node.

Abstract: Disclosed herein is a dynamic update cube and hybrid query search method for range-sum queries. The present invention relates to a hybrid query search method, which provides a precise answer or an approximate answer with respect to On-Line Analytic Processing (OLAP) queries by using a delta (?)-tree, which has a multidimensional index structure and a prefix-sum cube, so as to effectively support range-sum queries widely used in opinion decisions in enterprises. In the dynamic update cube and hybrid query search method for range-sum queries, a prefixed-sum cube is dense and the dynamic update cube is sparse, such that whenever a data cube changes, the prefixed sum cube is not directly updated and instead, the changes of the data cube are stored in a ?-Tree and the ?-Tree is managed.

Abstract: Disclosed herein is an apparatus and method for hyper-rectangle based multidimensional data segmentation and clustering. The segmentation apparatus has threshold calculation means, segment generation means, geometric condition determination means, segment merging means, and segment updating means. The threshold calculation means inputs a multidimensional sequence Si and the minimum number of points per segment minPts, and calculates bounding threshold values for a volume and an edge. The segment generation means initialize a segment set and an outlier set to empty sets and generates a current segment using a first point of the sequence Si. The geometric condition determination means determines whether a next point of the sequence Si satisfies a geometric condition using the bounding threshold values for the volume and the edge. The segment merging means merges the next point of the sequence Si into the current segment if geometric condition is satisfied.

Abstract: Disclosed herein is an apparatus and method for similarity searches using hyper-rectangle based multidimensional data segmentation. The similarity search apparatus has MBR generation means, first sequence pruning means, second sequence pruning means, and subsequence finding means. The MBR generation means segments a multidimensional data sequence to be partitioned into subsequences, and represents each subsequence by each Minimum Bounding Rectangle (MBR), such that sets of MBRs are generated from the multidimensional data sequence, and the MBR sets are stored in a database. The first sequence pruning means prunes irrelevant data sequences using a distance Dmbr between MBRs extracted from an inputted query sequence and the MBR sets stored in the database in a multidimensional Euclidean space.

Abstract: Disclosed herein is a dynamic update cube and hybrid query search method for range-sum queries. The present invention relates to a hybrid query search method, which provides a precise answer or an approximate answer with respect to On-Line Analytic Processing (OLAP) queries by using a delta (&Dgr;)-tree, which has a multidimensional index structure and a prefix-sum cube, so as to effectively support range-sum queries widely used in opinion decisions in enterprises. In the dynamic update cube and hybrid query search method for range-sum queries, a prefixed-sum cube is dense and the dynamic update cube is sparse, such that whenever a data cube changes, the prefixed sum cube is not directly updated and instead, the changes of the data cube are stored in a &Dgr;-Tree and the &Dgr;-Tree is managed.

Abstract: Disclosed is a multi-dimensional selectivity estimation method using compressed histogram information which the database query optimizer in a database management system uses to find the most efficient execution plan among all possible plans. The method includes the several steps to generate a large number of small-sized multi-dimensional histogram buckets, sampling DCT coefficients which have high values with high probability, compressing information from the multi-dimensional histogram buckets using a multi-dimensional discrete cosine transform(DCT) and storing compressed information, and estimating the query selectivity by using compressed and stored histogram information as the statistics.