Abstract:
본 발명은 살균된 민들레에 누룩균( Asperillus oryzae )을 접종한 후, 발효시켜 민들레 발효물을 제조하는 단계(A); 및 상기 민들레 발효물을 열수추출하여 민들레 발효추출물을 수득하는 단계(B); 를 포함하는 과정으로부터 수득되는 민들레 발효추출물을 유효성분으로 함유하는 간 보호용 조성물에 관한 것이다.
Abstract:
A method for performing a design of clustering in a wireless sensor network comprises the following steps: understanding characteristics of multiple nodes included in the wireless sensor network, determining a solution indicating whether each of the multiple nodes is a cluster header using a harmony search algorithm; calculating an evaluation value of the determined solution using an average of energy consumed by each of the multiple nodes and a deviation of residual energy of each of the nodes; updating the solution in the harmony search algorithm according to the evaluation value; and performing a design of clustering in the wireless sensor network using the updated solution.
Abstract:
PURPOSE: A clustering optimal design method at a wireless sensor network using ants algorithm is provided to minimize the distance between a sink node and a cluster nodes and each cluster node and sensor nodes. CONSTITUTION: A cluster head selection probability of being connected to the sink node is calculated according to pheromone and preference through the ant algorithm(S110). The cluster head according to the calculated selection probability is selected, and a value interlinked to the cluster head which most nears from each sensor node creates(S120). The suitability is evaluated for all ants(S130). Amount of the pheromone representing the extent, in which the sensor node is a headed cluster, is controlled(S140,S150,S160). It is processed a pheromone control of mediation through the maximum-minimum strategy for deciding the minimum value and maximum value of the accumulation pheromone amount(S180).
Abstract:
무선 센서 네트워크에서 클러스터링(Clustering) 설계를 수행하는 방법은 상기 무선 센서 네트워크에 포함되는 복수의 노드들의 특성을 파악하는 단계; 하모니 서치 알고리즘을 이용하여 상기 복수의 노드들 각각이 클러스터 헤드인지 여부를 나타내는 해를 결정하는 단계; 상기 복수의 노드들 각각이 소모하는 에너지의 평균 및 상기 복수의 노드들 각각에 남아있는 에너지 사이의 편차를 이용하여 상기 결정된 해에 대한 평가값을 계산하는 단계; 상기 평가값에 따라 상기 하모니 서치 알고리즘에서, 상기 해를 업데이트하는 단계; 및 상기 업데이트된 해를 이용하여 상기 무선 센서 네트워크를 클러스터링 설계를 수행하는 단계를 포함한다.
Abstract:
A biogeographical optimization method for grid computing scheduling comprises the steps of: identifying the processing speed of each of a plurality of nodes included in a grid network and the length of each of a plurality of tasks; setting an objective function for minimizing a total makespan related to a point of time when all of the tasks are completed by the nodes on the assumption that each of the plurality of tasks is assigned to one node; arbitrarily extracting initial habitats, used for a biogeographical optimization technique, as initial solutions; and assigning the plurality of tasks to the plurality of nodes by updating the initial habitats so that the objective function can be optimized according to the biogeographical optimization technique. [Reference numerals] (510) Compute a habitat suitability index; (520) Extract immigration/emigration rates and a mutation rate; (530) Apply immigration/emigration; (540) Apply mutation; (550) Update a habitat; (560) Determine whether to end; (AA) End