Earticle

본 연구는 디지털노동 플랫폼 알고리즘, 플랫폼노동 특유성과 수행 간의 관계를 현상적으로 살펴보고자 함에 목적이 있다. 국내 배달 플랫폼 기업의 관계자와 배달 라이더를 대상으로 인터뷰를 진행하였으며, 근거이론방법을 활용하여 주요 개념들을 도출하고 이들 간 연관 관계를 제시하였다. 본 연구의 결과는 디지털 플랫폼노동 현상의 원리를 제안하고 있다는 점에 학문적 의의가 있으며, 플랫폼노동에 대한 인식 개선과 대안 마련 측면에서 실무적 시사점이 있다.

An early warning system was developed to help identify stock status as early as possible. For performance to improve, there needs to be a feature to predict the amount of stock that must be provided and a feature to estimate when to buy goods. This research was conducted to improve the inventory early warning system and optimize the Reminder Block's performance in minimum stock settings. The models used in this study are the single exponential smoothing (SES) method for prediction and the economic order quantity (EOQ) model for determining the quantity. The research was conducted by analyzing the Reminder Block in the early warning system, identifying data needs, and implementing the SES and EOQ mathematical models into the Reminder Block. This research proposes a new Reminder Block that has been added to the SES and EOQ models. It is hoped that this study will help in obtaining accurate information about the time and quantity of repurchases for efficient inventory management.

To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

The SCM is that Supply Chain Network is Promptly and Voluntarily Optimized in Unstable Market Change Environment. The Cash flow Efficiency of Hole Supply Chain Network is Improved by Changing the Information and Changing the Foundation of Business Processes. The Role of WMS has been Changing Importantly with the Introduction of SCM. WMS Needed to Change to the Information Center in Order to Change Information in Real Time and the WMS of Information Storing in Order to Support an Idea Decision. This Development was Defined about the Importance of WMS in SCM Environment. The Criterion of Valuation is Normally Measured Time between Taking a Order Receive and Bringing the Items to Customer. The Decreasing Move Time of Order Picker in Warehouse is Directly Influence to the Job Execution. So, this Research is Defined about the Optimized Route of Order Picker and Suggests Algorithm. To do this, Past Algorithm is Studied. It's Easy to Introduce and this Study is Looking for Method about the Noticing of Order Picker. The Algorithm will Improve to be Adapt to Standard Process System.

해를 거듭할수록 증가하는 고속도로 연장과 함께 전체 고속도로 유지보수 비용은 급증하는 추세에 있다. 제한된 유지보수 예산으로 전체 고속도로망을 효율적으로 유지관리하기 저해 포장관리시스템 (PMS, Pavement Management System)의 운영은 필수적이라 할 수 있다.본 연구는 PMS의 핵심기능인 보수 우선순위 및 공법결정 논리를 개발하여 실무자들의 PMS 활용도를 높이기 위한 연구로서, 실무자들이 친숙하게 사용할 수 있도록 PMS의 기본기능에 충실하여 쉽게 운영 기능한 시스템을 구성 하는데 역점을 두었다. PMS의 주 논리인 보수우선순위 및 보수공법결정에 관련된 각 항목들의 criteria는 기술자의 판단에 의해서 쉽게 수정할 수 있도록 하여 좀더 유연한 운영을 할 수 있도록 하였고, 보수공법 결정에 있어서도 기계적인 알고리즘께 의한 보수공법결정체계의 경직성을 보완하기 위해, 제시된 보수공법의 적절성을 PMS운영자가 직접 확인하고 필요시 현장실사 또는 정밀조사를 통해 보수공법을 조정할 수 있도록 하였다. 도로 일반현황조회에 있어서는 운영자가 쉽게 포장의 상태를 파악할 수 있도록 HGIS와의 연계를 통해 현황조회 기능을 강화하였다. 고속도로 PMS의 전산화는 각 고속도로 포장과 관련된 모든 정보에 대한 데이터베이스를 기반으로 하여 실무자들이 쉽게 이해하고 편리하게 사용하는데 중점을 두어 개발하였으며 정량화된 객관적인 정보를 실무자에게 제공하여 포장을 효율적으로 관리할 수 있도록 하였다.

Maintenance cost for managing the whole network of Expressway system in Korea increases rapidly with the increase of the total length of the system. Implementation of the Pavement Management System(PMS) is essential for efficient management of the Expressway with a limited budget. The purpose of this study is to develop the main algorithm of PMS for Korea Expressway System and to associate the algorithm with database and the Highway Geographic Information System(HGIS) recently developed. Emphasis is laid on developing the algorithm as easy as possible, so that the users can use the PMS without practical difficulty. PMS is not the decision maker, but just a supporting system for the user. The algorithm is designed in such a way that the users can modify the decision criteria if necessary. The user is the one who makes the final decision of the priority and the maintenance alternatives. The users can also inquire the current condition of the whole Expressway network in detail by association of the database and the algorithm with HGIS.

Purpose: The purpose of this study was to develop an algorithm for preventing and managing of pressure ulcer and to verify the its appropriateness. Methods: The first step was development of a pre-algorithm through a literature review and expert opinion. The second step was to establish content validity by submitting the algorithm questionnaires about the content to 12 experts. The third step was the revision of the algorithm. The fourth and last step was to establish the clinical validity of the algorithm with 25 experienced nurses. Results: For the ease of the practitioner the algorithm for prevention and the management of pressure ulcers was confined to one page depicting the main algorithm pathway and seven stepwise guidelines. The guidelines included skin care of pressure ulcer prevention, mechanical loading care, support surface care , reposition care of pressure ulcer, and Stages II, III and IV explanations along with debridement/wound irrigation and infection control. Most of all algorithm courses chosen more than 80% of agreement by expert index of content validity. The usefulness,appropriateness, and convenience of the algorithm were demonstrated through clinical validity with intensive care unit and ward nurses. Conclusion: The algorithm will improve the quality of pressure ulcer nursing care as it provides a model for decision making for clinical nurses as well as providing consistent and integrated nursing care for patients with pressure ulcer throughout an institution.

본 연구는 지역사회 내에 거주하는 재가 아동의 신체적, 심리적, 사회․환경적 상황을 종합적으로 평가하여 그에 적합한 서비스를 제공하기 위한 욕구 중심의 사정도구를 개발하고, 개발된 도구를 활용하여 재가 아동 482명의 사정 데이터를 수집한 후 데이터마이닝의 의사결정 나무분석 기법을 활용하여 욕구에 적합한 서비스제공을 위한 욕구 추출 알고리즘을 구성하였다. 본 연구는 2007년 3월부터 2009년 3월까지 약 2년에 걸쳐 이루어졌으며, 크게 사정도구 개발과 개발된 도구를 활용한 욕구추출 과정으로 나뉠 수 있다. 도구개발은 문헌고찰을 통하여 기본적인 틀을 구성하였고, 포커스집단과 전문가들을 통하여 사정도구의 주관적 호소와 욕구 문항을 개발하였으며, 도구의 타당도를 확인하기 위해 통계적인 검증과정을 거쳤다. 검증결과 본 도구의 내적 신뢰도의 평균은 .867이었고 이 도구를 활용하여 아동 사례관리의 욕구추출 알고리즘을 제시하였다. 본 연구의 결과로 제시한 사정도구와 알고리즘은 재가 아동의 객관적 욕구를 사정하고 확인함으로써 체계적인 사례관리를 수행하는 자료로 활용될 수 있다.

The study aims to develop a assessment tool to provide the in-home child in a local community with appropriate services in consideration of physical, emotional, social and environmental circumstances. After collection of assesment data of 482 in-home child through use of the tool, a desire-extracting algorithm was developed to provide a service to real needs through the use of decision tree analysis on data mining. The study was conducted for to years from march 2007 through march 2009, and it is divided into development of an assessment tool and extraction of real needs through the use of the tool. The basic framework of the development of the tool was established through the examination of related literature, the subjective satisfaction of the assessment tool and items were developed through the use of a focus group and experts, and verification was implemented through the use of statistics to confirm the validity of the tool. As a result of the verification, the tool secured following reliability α = .867. In addition, real needs-extraction algorithm was established through the use of the assessment tool, and the algorithm according each desire was suggested. The assessment tool and algorithm suggested as a result of the study can be used as data to conduct systematic management of examples through the confirmation of objective desire of in-home child.

본 연구는 시설에 거주하는 노인들의 신체적, 심리적, 사회ㆍ환경적 상황을 종합적으로 평가하여 그에 적합한 서비스를 제공하기 위한 욕구 중심의 사정도구를 개발하고, 개발된 도구를 활용하여 시설노인 612명의 사정 데이터를 수집한 후 데이터마이닝의 의사결정 나무분석 기법을 활용하여 욕구에 적합한 서비스제공을 위한 욕구 추출 알고리즘을 구성하였다. 본 연구는 2006년 4월부터 9월까지 6개월간 걸쳐 이루어졌으며, 크게 사정도구 개발과 개발된 도구를 활용한 욕구추출 과정으로 나뉠 수 있다. 도구개발은 문헌고찰을 통하여 기본적인 틀을 구성하였고, 포커스집단과 전문가들을 통하여 사정도구의 주관적 호소와 욕구 문항을 개발하였으며, 도구의 타당도를 확인하기 위해 통계적인 검증과정을 거쳤다. 검증결과 본 도구는 <표 2>와<표 3>의 결과처럼 타당도와 신뢰도를 확보하였으며, 이 도구를 활용하여 욕구추출 알고리즘 요약을 <표 7>과 같이 제시하였다. 본 연구의 결과로 제시한 사정도구와 알고리즘은 시설노인의 객관적 욕구를 사정하고 확인함으로써 체계적인 사례관리를 수행하는 자료로 활용될 수 있다.

The study aims to develop a assessment tool to provide the elderly in nursing-home with appropriate services in consideration of physical, emotional, social and environmental circumstances. After collection of assesment data of 612 the elderly in nursing-home through use of the tool, a desire-extracting algorithm was developed to provide a service to real needs through the use of decision tree analysis on data mining. The study was conducted for Six months from April 2006 through september 2006, and it is divided into development of an assessment tool and extraction of real needs through the use of the tool. The basic framework of the development of the tool was established through the examination of related literature, the subjective satisfaction of the assessment tool and items were developed through the use of a focus group and experts, and verification was implemented through the use of statistics to confirm the validity of the tool. As a result of the verification, the tool secured following validity and credibility as seen in <Table 2> and <Table 3>. In addition, real needs-extraction algorithm was established through the use of the assessment tool, and the algorithm according each desire was suggested as seen in <Tables 7> The assessment tool and algorithm suggested as a result of the study can be used as data to conduct systematic management of examples through the confirmation of objective desire of in nursing-home.

IEEE 802.11e standardized the EDCA mechanism to support the priority based QoS. And the virtual collision handler schedules the transmission time of each MAC frame using the internal back-off window according to the access category(AC). This can provides the differentiated QoS to real-time services at the medium traffic load condition. However, the transmission delay of MAC frame for real-time services may be increased as the traffic load of best effort service increases. It becomes more critical when the real-time service uses a compressed mode video codec such as moving picture experts group(MPEG) 4 codec. That is because each frame has the different importance. That is, the I-frame has more information as compared with the P- and the B-frame. In this paper, we proposed a buffer management algorithm based on the frame importance and the delay bound. The proposed algorithm is consisted of the traffic regulator based on the dual token bucket algorithm and the active queue management algorithm. The traffic regulator reduces the transmission rate of lower AC until that the virtual collision handler can transmit an I-frame. And the active queue management discards frame based on the importance of each frame and the delay bound of head of line(HoL) frame when the channel resource is insufficient.

무선 모바일 네트워크 환경에서 노드 이동성은 에너지 소모를 가중화시킨다. 본 논문에서는 노드 이동성으로 인한 에너지 소모를 줄이고, 클러스터 멤버 노드의 수명 주기를 연장시키기 위하여 클러스터 기반의 노드 관리 알고리즘 (CNMA: Cluster-based Node Management Algorithm)을 제안한다. 제안된 CNMA 알고리즘은 클러스터 내에서 클러스터 헤더 노드와 멤버 노드들의 이동성을 추적하고 이들의 관계를 주기적으로 모니터링함으로써 에너지 잔량을 분석한다. 그리고 노드들의 상태 전이 과정을 분석하여 클러스터링 분할과 병합을 수행한다. 본 연구의 목적은 노드 이동성으로 발생된 에너지 소모를 최소화하기 위한 것이다. 시뮬레이션 결과를 통하여 제안된 알고리즘이 이동성으로 인한 에너지 소모를 효율적으로 제어할 수 있음을 보이며, 에너지 수명 주기가 향상됨을 보인다.

The node mobility in the wireless mobile network environment increases the energy consumption. This paper proposes a CNMA (cluster-based node management algorithm) to reduce the energy consumption caused by node mobility, and to prolong the life cycle for cluster member nodes. The proposed CNMA traces the mobility for nodes between cluster header and member, and it analyses the energy capacity as monitoring periodically their relationship. So, it makes a division and merges by analysing the state transition for nodes. This paper is to reduce the energy consumption due to the node mobility. The simulation results show that the proposed CNMA can efficiently control the energy consumption caused by mobility, and it can improve the energy cycle.

보건의료데이터의 질적 수준을 향상시키기 위해서는 데이터 질 관리 알고리즘을 개발할 필요성이 있다. 이 에 본 연구에서는 질환의 유병률, 입원율이 높은 고혈압 환자의 당뇨질환 동반에 관련된 데이터 질 관리 알고리즘을 개발하고자 하였다. 이를 위해 2011년, 2012년 퇴원손상심층조사 자료 중 고혈압 환자 61,199건을 추출하여 분석대 상으로 하였다. 데이터 마이닝의 대화식 의사결정나무 방법과 Outlier Detection 방법론을 통해 데이터 질 관리 알고 리즘 개발한 결과 고혈압 환자가 당뇨병을 동반상병으로 가지는데 영향을 미치는 요인으로는 성별, 연령, 당뇨병성 사구체 장애, 당뇨병성 망막병증. 당병성 다발성 신경병증 등이 있었다. 의사결정나무 결과에 따라 당뇨병을 동반상 병으로 가질 확률 값이 80% 이상이거나, 20% 이하인 집단을 Outlier(극단치)로 정의하고, 고혈압 환자의 당뇨 동반 에 대한 극단치를 가지는 6개 집단을 발견하였다. 이와 같이 Outlier(극단치) 집단에 포함되는 실제 데이터를 확인하 여 데이터의 질적 수준을 향상 시킬 필요가 있다.

There is a need to develop a data quality management algorithm in order to improve the quality of health care data. In this study, we developed a data quality control algorithms associated diseases related to diabetes in patients with hypertension. To make a data quality algorithm, we extracted hypertension patients from 2011 and 2012 discharge damage survey data. As the result of developing Data quality management algorithm, significant factors in hypertension patients with diabetes are gender, age, Glomerular disorders in diabetes mellitus, Diabetic retinopathy, Diabetic polyneuropathy, Closed [percutaneous] [needle] biopsy of kidney. Depending on the decision tree results, we defined Outlier which was probability values associated with a patient having diabetes corporal with hypertension or more than 80%, or not more than 20%, and found six groups with extreme values for diabetes accompanying hypertension patients. Thus there is a need to check the actual data contained in the Outlier(extreme value) groups to improve the quality of the data.

도서관 사서의 수많은 업무 중 도서 정리 업무는 사서가 일일이 정리해야 하는 일이기 때문에, 투입되는 인적·시간적 비용이 크다. 이러한 문제를 해결하기 위해 최근 인공지능 기술을 접목한 도서 정리 로봇에 관한 관심이 증가하고 있다. 본 연구에서는 도서 정리 로봇에 적용할 수 있는 다중경유지 최단 경로 알고리즘인 K-ACO 알고리즘을 제안한다. 제안하는 K-ACO 알고리즘은 하나의 로봇이 아니라 여러 대의 로봇을 가정하고 있다. 또한, K-ACO는 개미 알고리즘을 개선하여 K개의 군집을 만들고 각 군집 별 최단 경로를 제공해준다. 본 논문에서는 제안한 알고리즘의 성능 분석을 도서 정리 시간의 관점에서 실시하였다. 제안한 알고리즘인 K-ACO 알고리즘을 한 대학교 도서관에 적용하여 현재 도서 정리 알고리즘과 비교해 보았다. 시뮬레이션을 통해 제안하는 알고리즘은 도서 정리 업무를 치우치지 않고 공평하게 배분하여 궁극적으로 전체 일이 끝나는 시간을 확연히 줄일 수 있음을 알 수 있었다. 본 연구 결과를 통하여 제안한 알고리즘의 적용으로 도서 정리에 필요한 인적·시간적 비용을 절감하여 도서관 내 양질의 서비스 향상을 기대한다.

Among the numerous duties of a librarian in a library, the work of arranging books is a job that the librarian has to do one by one. Thus, the cost of labor and time is large. In order to solve this problem, the interest in book-arranging robots based on artificial intelligence has recently increased. In this paper, we propose the K-ACO algorithm, which is the shortest path algorithm for multi-stops that can be applied to the library book arrangement robots. The proposed K-ACO algorithm assumes multiple robots rather than one robot. In addition, the K-ACO improves the ANT algorithm to create K clusters and provides the shortest path for each cluster. In this paper, the performance analysis of the proposed algorithm was carried out from the perspective of book arrangement time. The proposed algorithm, the K-ACO algorithm, was applied to a university library and compared with the current book arrangement algorithm. Through the simulation, we found that the proposed algorithm can allocate fairly, without biasing the work of arranging books, and ultimately significantly reduce the time to complete the entire work. Through the results of this study, we expect to improve quality services in the library by reducing the labor and time costs required for arranging books.

This paper considers a coordinated scheduling problem between multi-suppliers and an manufacture. When the supplier has insufficient inventory to meet the manufacture's order, the supplier may use the expedited production and the expedited transportation. In this case, we consider a scheduling problem to minimize the total cost of suppliers and manufacture. We suggest an population management genetic algorithm with local search and crossover (GALPC). By the computational experiments comparing with general genetic algorithm, the objective value of GALPC is reduced by 8% and the calculation time of GALPC is reduced by 70%.

Climate change and global warming carbon reduction efforts are being spread around the world. Republic of Korea in 2013, also in accordance with the Kyoto Protocol carbon reduction is likely to include mandatory targets. To counteract this policy of our government's green growth as a growth engine of the future are presented. To this end, the city's energy in the city to fix the problem, "Low Carbon, Green City" paradigm has been suggested. "Low Carbon, Green City" in order to implement to reduce energy consumption and carbon emissions, it is widely used in the existing building at the level of energy savings as much larger units, the city-wide energy reduction measures that it has become. City-wide planning and managing the energy in the city and use renewable energy to actively introduce efficiencies that are anticipated to be very large. To do this is to develop an algorithm for it is the goal of this study

Currently, it needs an introduction of the electric differential pricing for contribution to the stability of the power supply. And the renewable energy system is dramatically spreading to solve the lack of electricity power and save the electric charge. Therefore, the energy integrated management system is required that can be in consideration of the differential pricing and control renewable energy devices easily. In this paper, we present the integrated management system architecture of renewable energy and energy saving algorithm. The proposed system and algorithm can provide more economic benefit to residential customers.

차량과 같이 넓은 범위를 이동하는 환경에서 무선 인터넷 서비스를 사용할 때, 불필요하게 발생하는 핸드오버는 서비스 품질 저하의 주된 요인이다. 본 논문에서는 차량이 일정한 이동패턴을 갖고 있을 때, 핸드오버 빈도를 줄일 수 있는 방안을 제시한다. 차량의 이동 패턴을 Discrete-Time Markov Chain (DTMC)으로 모델링하고, AdaBoost 기법을 이용하여, 각 셀 내의 체류시간과 평균 신호의 세기를 저장하고 분석하여 핸드오버 시, 적합한 목적지 셀을 정하도록 한다. 제안한 방안의 검증을 위해, 서울 시내버스 노선들을 기반으로 성능 평가를 수행하였으며, 결과로 기존의 핸드오버 기법보다 핸드오버의 빈도를 줄이며, 평균 처리율 (throughput)은 비슷한 레벨로 유지할 수 있었다.

Redundant handovers cause degraded quality of service to passengers in vehicle. This paper proposes a handover scheme suitable for users traveling in vehicles, which enables continuous learning of the handover process using a discrete-time Markov chain (DTMC). Through AdaBoost machine learning algorithm, the proposed handover scheme avoids unnecessary handover trials when a short dwell time in a target cell is expected or when the target cell is an intermediate cell through which the vehicle quickly passes. Simulation results show that the proposed scheme reduces the number of handover occurrences and maintains adequate throughput.

Today, the management environments of intelligence firm are changing the way of production planning and logistics management, and are changing the process of supply chain management system. This paper shows the development of information system software for intelligence enterprises is used in supply chain management for robot engineering industry. Specifically, supply chain management system in this paper has been developed to analyze the impact of multi plant and multi distribution environment, showing the process analysis and system development of hierarchical assembly manufacturing industry. In this paper we consider a production planning and distribution management system of intelligence firm in the supply chain. We focus on a capacitated production resource and distribution volume allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using a genetic algorithm to solve it efficiently. This method makes it possible for the population to reach the feasible approximate solution easily. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solution converge to the feasible approximate solution quickly.

기존의 건물에 사용되는 에너지 감소 기술은 에너지 절약을 위해 꾸준히 발전되어 왔으나 이는 건축물 개개소의 단위 혹은 집합주택, 단지 규모의 건물군까지만 해당되는 사항으로서 전체 도시의 탄소 배출량 및 에너지 소비량 저감에는 한계가 있다. 따라서 탄소 배출량 및 에너지 소비량이 적은 저탄소 녹색도시를 구현하기 위해서는 탄소 배출량이 적은 신재생에너지를 이용한 에너지 플랜트를 건설하는 등 에너지 인프라를 구축하고 이를 효율적으로 운영하여 도시 차원의 에너지 소비량 및 탄소 배출량을 저감해야만 한다. 본 논문에서는 신도시계획에 있어서 신재생에너지 플랜트의 종류, 위치, 용량 등을 선정하고 이들 플랜트로부터의 열·전력의 공급을 효율적으로 통합관리·운영하기 위해 개발되고 있는 도시 에너지 통합관리‧운영시스템을 운영하기 위한 U-EMS의 알고리즘을 개발하였다.

Energy-saving technologies used in existing buildings for energy reduction have been developing steadily. However, it applies only unit buildings, places, housing or building groups, so there is a limit to realize low-carbon emissions and reduction of energy consumption in a entire city. Therefore, to realize a low-carbon green city which is low carbon emissions and energy consumption construct the energy infrastructure like energy plants using the renewable energy and ect. And it is operating efficiency that reduce the energy consumption and carbon emission in the city level. In this study, We developed the U-EMS algorithm for operating energy management and operation of the city which is being developed to operate city energy's integrated management·operating system that is being developed to supply efficiency of heat·electricity from the renewable plant is selected when the new city planning.