Abstract: Provided are an apparatus and method for forgery prevention of digital information. The apparatus for forgery prevention of digital information includes: a digital information obtaining unit configured to obtain digital information in real time; a seed value generator configured to generate a seed value carrying characteristics of the digital information obtained using the digital information obtaining unit; an information piece generator configured to divide the digital information obtained using the digital information obtaining unit, into continuous information pieces with a sequence; and a hash value generator configured to generate a hash value of a first information piece from the seed value and the first information piece and generate a hash value of a subsequent information piece by using a hash value of a previous information piece and the subsequent information piece as inputs.

Abstract: Disclosed are an unmanned aerial vehicle (UAV) having a buoyancy apparatus and an attitude control method thereof, in which the buoyancy apparatus is coupled to the UAV to reduce the energy consumption of rotors such that the time of staying in the air is extended, enabling a long flight, and in which the buoyancy apparatus absorbs the impact energy and reduces the falling speed to thereby ensure sufficient safety for the UAV.

Abstract: Disclosed are a method of transmitting image data having a hybrid resolution and a method of generating a hybrid-resolution image. A main region of an original image is transmitted as a high-resolution image and the remaining regions are transmitted as a low-resolution background image. Accordingly, an amount of data to be transmitted is able to be reduced.

Abstract: A sound source separating apparatus may include: a housing; a plurality of microphones positioned on the housing; a plurality of sound guides positioned on the housing to be adjacent to the plurality of microphones, and configured to guide sound to the plurality of microphones and to generate a difference between a plurality of sound information respectively arriving at the plurality of microphones according to a direction of a sound source; and a processor configured to separate the sound source according to the direction of the sound source based on the plurality of sound information received by the plurality of microphones.

Abstract: Provided are an apparatus and method for forgery prevention of digital information. The apparatus for forgery prevention of digital information includes: a digital information obtaining unit configured to obtain digital information in real time; a seed value generator configured to generate a seed value carrying characteristics of the digital information obtained using the digital information obtaining unit; an information piece generator configured to divide the digital information obtained using the digital information obtaining unit, into continuous information pieces with a sequence; and a hash value generator configured to generate a hash value of a first information piece from the seed value and the first information piece and generate a hash value of a subsequent information piece by using a hash value of a previous information piece and the subsequent information piece as inputs.

Abstract: A sound source separating apparatus may include: a housing; a plurality of microphones positioned on the housing; a plurality of sound guides positioned on the housing to be adjacent to the plurality of microphones, and configured to guide sound to the plurality of microphones and to generate a difference between a plurality of sound information respectively arriving at the plurality of microphones according to a direction of a sound source; and a processor configured to separate the sound source according to the direction of the sound source based on the plurality of sound information received by the plurality of microphones.

Abstract: Disclosed are an unmanned aerial vehicle (UAV) having a buoyancy apparatus and an attitude control method thereof, in which the buoyancy apparatus is coupled to the UAV to reduce the energy consumption of rotors such that the time of staying in the air is extended, enabling a long flight, and in which the buoyancy apparatus absorbs the impact energy and reduces the falling speed to thereby ensure sufficient safety for the UAV.

Abstract: In a method for simulating fluid flow using Tsallis entropy and Rényi entropy, the method includes a space defining step, a state determining step, a flow effect generating step, and a state renewal step. In the space defining step, a simulation space having lattices is defined. In the state determining step, a space occupation state is determined by objects, a fluid state, and a probability distribution state of a particle with respect to a velocity of the particle, for nodes of the lattices of the simulation space. In the flow effect generating step, a flow effect for nodes of the lattices of the simulation space is generated by using a collision rule, as a probability distribution of a particle with respect to a velocity of the particle, which is obtained by satisfying a condition at which Tsallis divergence between the collision rule itself and a reference collision rule which is obtained under a given condition has an extremal value.

Abstract: A method for simulating fluid flow includes: discretizing a space in which a fluid flows into a regular lattice; assuming that fluid particles repetitively move and collide in the lattice; deriving a univariate polynomial equation by comparing the n-th (n is a non-negative integer) order momentum of velocity between the Maxwell-Boltzmann distribution and the discretized Maxwell-Boltzmann distribution; calculating the weight coefficients corresponding to the discrete velocities of the fluid particles based on the univariate polynomial equation; and deriving a lattice Boltzmann model using the weight coefficients. A lattice Boltzmann model with superior stability and accuracy may be derived easily.

Abstract: A method for simulating fluid flow includes: discretizing a space in which a fluid flows into a regular lattice; assuming that fluid particles repetitively move and collide in the lattice; deriving a univariate polynomial equation by comparing the n-th (n is a non-negative integer) order momentum of velocity between the Maxwell-Boltzmann distribution and the discretized Maxwell-Boltzmann distribution; calculating the weight coefficients corresponding to the discrete velocities of the fluid particles based on the univariate polynomial equation; and deriving a lattice Boltzmann model using the weight coefficients. A lattice Boltzmann model with superior stability and accuracy may be derived easily.