2017년까지 정부는 사회적기업 3천개를 육성하고 사회적기업에 10만명을 고용하려는 계획을 가지고 있다. 우리나라의 사회적기업은 2007년 사회적기업 육성법이 제정된 이래 본격적으로 육성을 시작, 2015 년 현재 1400여개의 가파른 양적 성장을 기록하였다. 하지만 양적 성장은 이루었지만 여전히 대다수 사회적기업이 그 경제적․사회적 목적에 맞는 자립을 이루어내지 못하고 정부에 대한 높은 의존을 하고 있는 점과 규모의 영세성이 해결해야 할 문제점으로 남아있다. 이에 내실화를 이루고 안정적인 사회적기업의 정착을 위해 사회적기업을 위한 생태계 조성에 또 하나 의 토대가 될 수 있는 상생모델의 제시를 통해 앞으로의 발전방향을 모색해보고자 하였다. 본 연구에서는 행복나래(주)의 사회적기업 지원에 대한 성과분석을 바탕으로 사회적기업의 안정적 생태계 조성을 위한 또 하나의 방안으로서 모범적 상생모델과 앞으로의 발전방향에 대해 제시하였다.

In this paper, we proposed the model of wireless communication for ACTS using DSRC and the DSRC system for T/C. The proposed wireless communication model is how to join with DSRC and other wireless communication in port. The DSRC system for T/C is the first application to the unit of port Facilities Automation on stacking area. The DSRC system is communicated between OBE and RSE using 5.8Hz ISM band frequency. The previous works of DSRC applications are gate automation. In these cases, the road trackers are difficult to obtain information of the port in the stacking area. So we used the DSRC for the wireless communication for the port Facilities Automation. Using DSRC, the load trackers obtain more information in the port and contacts to ITS on back-roads of port. The proposed communication system is serviced to reelection of port statistics.

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

Todays, the efficient management of container has not been realized in container terminal, because of the excessive quantity of container transported and manual system. For the efficient and automated management of container in terminal, the automated container identifier recognition system in terminal is a significant problem. However, the identifier recognition rate is decreased owing to the difficulty of image preprocessing caused the refraction of container surface, the change of weather and the damaged identifier characters. Therefore, this paper proposes more accurate system for container identifier recognition as suggestion of LSPRD(Line-Scan Proper Region Detection) for stronger preprocessing against external noisy element and MBP(Momentum Back-Propagation) neural network to recognize the identifier.