Abstract: Disclosed are an aluminum alloy for a die casting and a method of producing an aluminum alloy casting product. The aluminum alloy may include silicon (Si) in an amount of about 7.5 to 9.5 wt %; magnesium (Mg) in an amount of about 2.5 to 3.5 wt %; iron (Fe) in an amount of about 0.5 to 1.0 wt %; manganese (Mn) in an amount of about 0.1 to 0.6 wt %; and aluminum (Al) constituting the remaining balance of the aluminum alloy, all the wt % are based on the total weight of the aluminum alloy.

Abstract: Disclosed are a magnesium die casting alloy, and an alloy composition for improving thermal conductivity and electrical conductivity. A magnesium die casting alloy includes an amount of about 0.5 to 2.0 wt % of aluminum (Al) and the balance magnesium (Mg), based on the total weight of the magnesium die casting alloy. Accordingly, an alloy, which has high thermal conductivity and electrical conductivity as compared to a conventional AZ91D magnesium alloy, is obtained.

Abstract: An electronic device is provided. The electronic device includes a receiving circuit configured to wirelessly receive power and output AC power, a rectifying circuit configured to rectify the AC power from the receiving circuit, wherein the rectifying circuit may include a first P-MOSFET configured to transfer a positive amplitude of power to an output terminal of the rectifying circuit while the AC power has the positive amplitude and to prevent transferring a negative amplitude of power to the output terminal of the rectifying circuit while the AC power has the negative amplitude, and a forward loss compensating circuit connected with the first P-MOSFET configured to reduce a threshold voltage of the first P-MOSFET while the AC power has the positive amplitude.

Abstract: Disclosed are an aluminum alloy for die casting that has excellent thermal conductivity and corrosion resistance, which can be used for parts requiring heat dissipation and high corrosion resistance, and a method of producing a cast aluminum alloy using the same. Provided is an aluminum alloy for die casting that may include an amount of about 8.5 to 10.5 wt % of silicon (Si); an amount of about 3.6 to 5.5 wt % of magnesium (Mg); an amount of about 0.3 to 1.0 wt % of iron (Fe); an amount of about 0.1 to 1.0 wt % of manganese (Mn); and the balance of aluminum (Al) and inevitable impurities, all the wt % are based on the total weight of the aluminum alloy.

Abstract: An aluminum alloy, comprising: 4.0 to 10.0 weight % silicon (Si), 0.1 to 4.0 weight % magnesium (Mg), 0.1 to 1.0 weight % chromium (Cr), 0.05 to 1.0 weight % zinc (Zn), 0.05 to 1.0 weight % manganese (Mn), 0.01 to 1.0 weight % titanium (Ti), 0.001 to 0.5 weight % tin (Sn), and 81.5 to 95.689 weight % aluminum and at least one impurity.

Abstract: Disclosed are a magnesium die casting alloy, and an alloy composition for improving thermal conductivity and electrical conductivity. A magnesium die casting alloy includes an amount of about 0.5 to 2.0 wt % of aluminum (Al) and the balance magnesium (Mg), based on the total weight of the magnesium die casting alloy. Accordingly, an alloy, which has high thermal conductivity and electrical conductivity as compared to a conventional AZ91D magnesium alloy, is obtained.

Abstract: Disclosed are an aluminum alloy for a die casting and a method of producing an aluminum alloy casting product. The aluminum alloy may include silicon (Si) in an amount of about 7.5 to 9.5 wt %; magnesium (Mg) in an amount of about 2.5 to 3.5 wt %; iron (Fe) in an amount of about 0.5 to 1.0 wt %; manganese (Mn) in an amount of about 0.1 to 0.6 wt %; and aluminum (Al) constituting the remaining balance of the aluminum alloy, all the wt % are based on the total weight of the aluminum alloy.

Abstract: A high-strength aluminum alloy for die casting having excellent corrosion resistance and thermal conductivity includes, based on the total weight of the alloy, 5 to 7 wt % of silicon (Si), 0.1 to 1.0 wt % of iron (Fe), 0.1 to 3.0 wt % of magnesium (Mg), 0.1 to 1.0 wt % of nickel (Ni), 0.15 to 0.45 wt % of titanium (Ti), 1.0 to 3.0 wt % of tin (Sn), and the remainder aluminum (Al).

Abstract: An aluminum alloy, comprising: 4.0 to 10.0 weight % silicon (Si), 0.1 to 4.0 weight % magnesium (Mg), 0.1 to 1.0 weight % chromium (Cr), 0.05 to 1.0 weight % zinc (Zn), 0.05 to 1.0 weight % manganese (Mn), 0.01 to 1.0 weight % titanium (Ti), 0.001 to 0.5 weight % tin (Sn), and 81.5 to 95.689 weight % aluminum and at least one impurity.

Abstract: Graph embedding is incorporated into nonnegative matrix factorization, NMF, while using the original formulation of graph embedding. Negative values are permitted in the definition of graph embedding without violating the nonnegative requirement of NMF. The factorized matrices of NMF are found by an iterative process.

Abstract: Supervised kernel nonnegative matrix factorization generates a descriptive part-based representation of data, based on the concept of kernel nonnegative matrix factorization (kernel NMF) aided by the discriminative concept of graph embedding. An iterative procedure that optimizes suggested formulation based on Pareto optimization is presented. The present formulation removes any dependence on combined optimization schemes.

Abstract: Supervised nonnegative matrix factorization (SNMF) generates a descriptive part-based representation of data, based on the concept of nonnegative matrix factorization (NMF) aided by the discriminative concept of graph embedding. An iterative procedure that optimizes suggested formulation based on Pareto optimization is presented. The present formulation removes any dependence on combined optimization schemes. Analytical and empirical evidence is presented to show that SNMF has advantages over popular subspace learning techniques as well as current state-of-the-art techniques.

Abstract: Supervised nonnegative matrix factorization (SNMF) generates a descriptive part-based representation of data, based on the concept of nonnegative matrix factorization (NMF) aided by the discriminative concept of graph embedding. An iterative procedure that optimizes suggested formulation based on Pareto optimization is presented. The present formulation removes any dependence on combined optimization schemes. Analytical and empirical evidence is presented to show that SNMF has advantages over popular subspace learning techniques as well as current state-of-the-art techniques.

Abstract: Supervised kernel nonnegative matrix factorization generates a descriptive part-based representation of data, based on the concept of kernel nonnegative matrix factorization (kernel NMF) aided by the discriminative concept of graph embedding. An iterative procedure that optimizes suggested formulation based on Pareto optimization is presented. The present formulation removes any dependence on combined optimization schemes.

Abstract: Graph embedding is incorporated into nonnegative matrix factorization, NMF, while using the original formulation of graph embedding. Negative values are permitted in the definition of graph embedding without violating the nonnegative requirement of NMF. The factorized matrices of NMF are found by an iterative process.

Abstract: A separating plate for polymer electrolyte membrane fuel cell and a method for manufacturing the same is provided. Preferred separating plates for polymer electrolyte membrane fuel cell are capable of being light weight and corrosion resistant, as well as being economical to produce and exhibit good physical properties. Preferred separating plates are produced with compositions comprising graphite and phenolic resin.

Abstract: Disclosed are a manufacturing method of a separator for a fuel cell, comprising a preforming step for forming a preform of the separator and a main forming step for form the separator with the preform; and a separator manufactured thereby.