Earticle

이 연구는 교무분장 과정에서 교사의 능력뿐만 아니라 업무 선호를 고려하는 것이 중요하다는 전제하에, 단위학교 내 업무 선호의 양상과 선호 차원 및 예측요인을 실증적으로 탐색하는 데 목적이 있다. 서울교원종단연구 2020의 5차년도(2025년) 데이터를 활용하였으며, 업무 선호의 2차원 유형화 분석 모형을 설정한 후 탐색적 요인분석 및 다중회귀분석 등을 수행하였다. 먼저, 단위학교 내 업무에 대한 선호는 이질적인 것으로 나타났다. 학교급에 따라 전반적으로 선호도가 높은 업무 일지라도 교사 개인 간 선호의 편차가 존재하며, 기피 업무에 대해서도 일부는 선호를 보이는 것으로 확인되었다. 다음으로, 단위학교 내 업무에 대한 선호는 교사 특성에 따라 차이가 있다. 학교급별로 29개 업무를 소수의 선호 차원으로 요약한 결과, 전반적으로 “교무 및 학사 행정”과 “학생 활동 및 생활 지원”의 2개 차원으로 업무 선호를 인식하는 것으로 확인되었다. 이후 업무 선호 차원에 대한 예측요인 분석 결과는 비교적 학교급별로 유사한 패턴이 관찰되었다. 교무 및 학사 행정 차원의 업무 선호는 교육연한, 전입 여부와 과목, 학생 활동 및 생활 지원 차원의 업무 선호는 교직경력, 성별과 과목이 주요 예측요인으로 확인되었다. 마지막으로, 교무분장 과정에서 평균적인 선호를 넘어 개인별 선호의 이질성을 고려할 필요가 있으며, 교사의 능력과 선호를 함께 반영할 수 있는 교무분장 운영 방향을 제언하였다.

This study aims to empirically explore the patterns, dimensions, and predictive factors of task preferences within individual schools, based on the premise that considering teachers' preferences alongside their abilities is crucial in the process of assigning school tasks. It utilizes data from the 5th wave (2025) of the Seoul Educational Longitudinal Study of Teacher 2020. After establishing a two-dimensional typology framework for task preferences, exploratory factor analysis and multiple regression analysis were conducted. First, preferences for tasks within schools were found to be heterogeneous. Even for tasks generally preferred across school levels, significant variation in preferences existed among individual teachers. Furthermore, some teachers exhibited preferences for tasks that were otherwise avoided. Second, preferences for tasks within schools differed based on teacher characteristics. After reducing and categorizing preferences for 29 tasks by school level, preferences were generally recognized as two dimensions: “Academic Affairs and Administrative Support” and “Student Activities and Life Support.” Third, subsequent analysis of predictive factors for task preference dimensions showed relatively similar patterns across school levels. For task preferences in the “Academic Affairs and Administrative Support”, educational attainment, transfer status, and subjects were identified as key predictors. For preferences in the “Student Activities and Life Support”, years of teaching, gender, and subjects were the main predictors. Finally, it was suggested that the process of assigning school tasks requires attention to individual preferences beyond average tendencies. There is a need to consider directions for assigning school tasks that appropriately account for both teachers' abilities and preferences, including preference heterogeneity.

EA의 업무를 수행하기 위해 마련해 놓은 지식 체계인 업무 참조 모델(Business Reference Model)은 대부분 범주 별로 계층형 구조화 되어 있으며, 해당 조직의 목표를 달성하고 업무 수행능력 의 개선을 지원한다. 이를 통해 조직의 효율성을 높이고 조직 업무의 예외적 돌발성을 최소화하고 업 무간의 연계성 강화를 통해 개별 업무절차를 직관적이고 단순하게 변화시키고, 이로써 조직 내적으로 효율성 향상에 기여할 수 있다. EA에는 현재 BOK(Body of Knowledge)가 정의되어 존재하지만, 이 들을 업무의 할당과 그 평가에 사용하기 위한 시스템이 미비한 상태이다. 본 연구에서는 계층적 유사 도에 근거한 업무 할당 및 평가체계를 제공하고, 이를 통해 기존에는 정성적으로 이루어지던 업무의 정의와 할당 및 평가체계에 수치적 엄밀성을 도입하여 정량화된 명확한 평가가 가능하도록 하고, 이 것이 되먹임 되어 BOK체계 자체가 재평가되고 성숙될 수 있는 방법론을 제안하였다.

BRM (Business Reference Model) is constructed for enhancing the performance of the EA (Enterprise Architecture) tasks with respect to categories defined as a knowledge hierarchy. It aims to accomplish the organizational purposes by which it progresses enactment of the tasks. Furthermore, it simplifies the definition of the EA tasks and improves the effectiveness of them mainly due to reducing redundancy and reinforcing in-between connectivity of the tasks. By doing these, the internal organization performance can be exceedingly amended. In EA, there usually exists a hierarchically structured BOK (Body of Knowledge). The utilization of BOK such as the coordination for task assignment and the corresponding assessment cannot properly be consummated. In the paper, we introduce a distance measure for the categorical data based on the hierarchical knowledge so that the EA task assignment and assessment method can effectively prepared, and the BRM per se can be matured by the feedback of the BOK.

One of the geometrical k-cut problem applications is the task assignment in homogeneous networks where processors are homogeneous and some of them have unique or special functionalities. Though the problem is NP-hard in general, there are polynomial-time optimal algorithms if the topology graphs representing networks have regular properties such as tree and general array. We showed that the O(n3k) time complexity of existing algorithms for the task assignment problems can be enhanced to O(n3logk) in cases of linear array, binary tree, and general array by using the results of [3, 5]. This paper also proposed a new kind of topology graphs on which the geometrical k-cut problem can be solved in polynomial time. The time complexity of the algorithm is O(n3k), where n is the number of nodes in a k-terminal graph, with the Goldberg-Tarjan’s network flow algorithm.

For multi- multi-unmanned aerial vehicle (UAV) air combat decision problems, this paper proposes a multi-UAV task allocation method based on cloud model. Firstly, we analyses air combat situation advantage of random and fuzzy information. The cloud model is applied to multi-UAV task allocation. We establish air combat superiority index model based on cloud model. And then through comprehensive cloud generation algorithm, we establish combat situation advantages of comprehensive cloud model based on cloud model and present multi-UAV task assignment method based on comprehensive cloud model. Finally, the simulation verification indicate: To evaluate air combat advantage using cloud model, we can get precise and credible combat situation advantage, thus, we get more scientific and reliable multi-UAV task assignment.

In view of collaborative development environment web services supplier in ability, cost, time supplier relations and component relevance information under uncertainty problems. The fuzzy multi-objective task assignment model of web services are built in a collaborative development environment. Using α cut sets and extension principle to simplify the fuzzy multi-objective assignment mode, we get the solution of simplified assignment model via the Genetic and simulated-annealing algorithm. In view of the model solution sets are fuzzy and uncertain membership function, a new centroid defuzzification method is used for the model solution. Thus the optimization allocation of component supplier’s fuzzy task is realized in collaborative development environment. Finally, the simulation results verify the feasibility of the proposed method, which can ensure the suppliers’ tasking in successive software project in collaborative development environment.

The project deployment diagram, which is used to uniformly describe the process and resource of virtual enterprise is established aiming at how to choose virtual enterprise partner of time-cost tradeoff and set task-resource assignment graph as scheduling model, the iterative heuristic algorithm is adopted based on relative cost-effectiveness to solve. The production of virtual partner and transportation time and cost are taken into account in algorithm, which may ensure deadline constraint as well as effectively cut down overall cost. Such algorithm applying to resource distribution and a vast amount of simulative tests proved that this method is able to effectively cut down the operation time of obtaining prioritization scheme.

Selection of a suitable task from the extensively available large set of tasks is an intricate job for the developers in crowdsourcing software development (CSD). Besides, it is also a tiring and a time-consuming job for the platform to evaluate thousands of tasks submitted by developers. Previous studies stated that managerial and technical aspects have prime importance in bringing success for software development projects, however, these two aspects can be more effective and conducive if combined with human aspects. The main purpose of this paper is to present a conceptual framework for task assignment model for future research on the basis of personality types, that will provide a basic structure for CSD workers to find suitable tasks and also a platform to assign the task directly. This will also match their personality and task. Because personality is an internal force which whittles the behavior of developers. Consequently, this research presented a Task Assignment Model (TAM) from a developers point of view, moreover, it will also provide an opportunity to the platform to assign a task to CSD workers according to their personality types directly.

In this paper, a study on task assignment strategies for a complex real-time network system is presented. Firstly, two task assignment strategies are proposed to improve previous strategies. The proposed strategies assign tasks with meeting end-to-end real-time constraints, and also with optimizing system utilization through period modulation of the tasks. Consequently, the strategies aim at the optimizationto optimize of system performance with while still meeting real-time constraints. The proposed task assignment strategies are devised using the genetic algorithmswith heuristic real-time constraints in the generation of new populations. The strategies are differentiated by the optimization method of the two objectives-meeting end-to-end real-time constraints and optimizing system utilization: the first one has sequential genetic algorithm routines for the objectives, and the second one has one multiple objective genetic algorithm routine to find a Pareto solution. Secondly, the performances of the proposed strategies and a well-known existing task assignment strategy using the BnB(Branch and Bound) optimization are compared with one other through some simulation tests. Through the comparison of the simulation results, the most adequate task assignment strategies are proposed for some as system requirements-: the optimization of system utilization, the maximization of running tasktasks, and the minimization of the number of network node nodesnumber for a network system.

Load balancing is the major benefit of any distributed system. To facilitate this advantage, task duplication and migration methodologies are employed. As this paper deals with dependent tasks (DAG), we used duplication. Task duplication reduces the overall schedule length of DAG along-with load balancing. This paper proposes a new task duplication algorithm at the time of tasks assignment on various processors. With the intention of conducting proposed algorithm performance computation; simulation has been done on the Netbeans IDE. The mesh topology of a distributed system is simulated at this juncture. For task duplication, overall schedule length of DAG is the main parameter that decides the performance of a proposed duplication algorithm. After obtaining the results we compared our performance with arbitrary task assignment, CAWF and HEFT-TD algorithms. Additionally, we also compared the complexity of the proposed algorithm with the Duplication Based Bottom Up scheduling (DBUS) and Heterogeneous Earliest Finish Time with Task Duplication (HEFT-TD).

We suggest a distributed framework for task assignment in the computer-controlled shop floor where each of the resource agents and part agents acts like an independent profit maker. The job allocation problem is formulated as a linear programming problem. The LP formulation is analyzed to provide a rationale for the distributed task assignment procedure. We suggest an auction based negotiation procedure including a price-based bid construction and a price revising mechanism. The performance of the suggested procedure is compared with those of an LP formulation and conventional dispatching procedures by simulation experiments.

The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitive environment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the task and win rewards. Task searching and assigning are very important aspects of the CSD environment because tasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on the platform are very difficult and time-consuming process for both the developer and platform. However, there are many other problems that are affecting CSD quality and reliability of CSD workers to assign the task which include the required knowledge, large participation, time complexity and incentive motivations. In order to attract the right person for the right task, the execution of action plans will help the CSD platform as well the CSD worker for the best matching with their tasks. This study formalized the task assignment method by utilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefined conditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planning to provide the best possible solution to matching the CSD worker with their personality type.

Task assignments of multiple unmanned aerial vehicles (UAVs) are examined. The phrase "task assignment" comprises the decision making procedures of a UAV group. In this study, an on-line decentralized task assignment algorithm is proposed for an autonomous UAV group. The proposed method is divided into two stages: an order optimization stage and a communications and negotiation stage. A genetic algorithm and negotiation strategy based on one-to-one communication is adopted for each stage. Through the proposed algorithm, decentralized task assignments can be applied to dynamic environments in which sensing range and communication are limited. The performance of the proposed algorithm is verified by performing numerical simulations.

Background: Occupational health and safety (OHS) is a significant interest of all governments to prevent workplace hazards. Although appropriate legislation and regulations are essentials for the protection of workers, they are solely not enough. Application of them in practice should be secured by an efficient inspection system. Fundamental components of an inspection system are inspectors and their audit tasks. Maintaining the fair balanced task assignment among inspectors strictly enhances the efficiency of the overall system. Methods: This study proposes a two-phased goal programming approach for OHS inspectors' task assignments and presents a case study. Results: The solution approach gives the balanced assignment of inspectors to the workplaces in different cities of the country in the planning period. The obtained schedule takes into account the distances covered by the work places and the number of the workplaces' employees to be audited and pays attention to the human factors by considering the preferences of the inspectors. The comparisons between the obtained optimal schedule and the implemented one that is produced manually show that the approach not only maintains the technical requirements of the problem, but also provides social and physical balance to the task assignment. Conclusion: Both the approach and the application study are expected to offer fruitful inspirations in the area of safety management and policy and they provide a good guide for social policy and organizational aspects in the field of OHS inspectors' task assignment.

In recent years, distributed control systems(DCS) using fieldbus such as CAN have been being applied to process systems but it is very difficult to design the DCS in order to guarantee the given end-to-end constraints such as precedence constraints, time constraints, and periods and priorities of tasks and messages. This paper presents a scheduling method to guarantee the given end-to-end constraints. The presented scheduling method is the integrated one considering both tasks executed in each node and messages transmitted via the network and is designed to be applied to a general DCS that has multiple loops with several types of constraints, where each loop consists of ...

하둡 맵리듀스(MapReduce)는 사용자가 요청한 잡을 하둡 클러스터에서 효과적으로 병렬 분산 처리하기 위한 프레임워크이다. 맵리듀스의 태스크 스케쥴러는 사용자의 잡 태스크들을 여러 노드에 할당하기 위한 기법이다. 하지만, 기존의 스케쥴러는 노드의 가용 상태에 따라 규모가 동적으로 변화하는 하둡 클러스터를 고려하지 않음으로써 클러스터의 자원을 충분히 활용하지 못하는 문제가 있다. 본 논문에서는 노드의 가용성을 고려하여 잡 태스크를 효과적으로 할당함으로써 하둡 클러스터의 활용성을 높이는 태스크 할당 정책을 제시한다.

Hadoop MapReduce is a processing framework in which users' job can be efficiently processed in parallel and distributed ways on the Hadoop cluster. MapReduce task schedulers are used to select target nodes and assigns user's tasks to them. Previous schedulers cannot fully utilize resources of Hadoop cluster because they does not consider dynamic characteristics of cluster based on nodes' availability. To increase utilization of Hadoop cluster, this paper proposes a novel task assignment policy for MapReduce that assigns a job tasks to dynamic cluster efficiently by considering availability of each node.

병원 응급실의 환자 과밀 현상이 점점 더 심해지고 있는 상황이다. 본 연구에서는 응급실의 치료 서비스 수준 및 시스템 효율을 개선하는 방안의 일환으로 간호사에게 치료 테스크를 할당하는 규칙을 개발하고자 한다. 제시하는 규칙에서는 매 치료 테스크 할당 시에 4개 속성 즉 1)태스크의 수행시간, 2)치료 요청 후의 흐른 시간, 3)모든 치료가 다 끝날 때까지의 총 남은 시간, 4)남은 치료단계의 개수를 동시에 고려한다. 각 치료 치료태스크의 기준별 긴급도를 계산하고, 기준별 중요도를 반영한 전체긴급도 값을 계산한 후 이 값이 가장 큰 태스크에 간호사를 할당한다. 컴퓨터 시뮬레이션을 통하여 M 병원 응급실의 간략화 모형을 대상으로 기존규칙과 비교실험을 수행하였다. 환자가 응급실에 머문 평균시간 및 단위시간 동안 처리한 환자 수를 평가기준으로 실험한 결과 제시한 규칙이 두 기준 모두에서 우수한 성능을 보였다.

Overcrowding in an Emergency Department (ED) of hospital is a common phenomenon. To improve the service quality and system performance of the ED, a task assignment rule for the Registered Nurses (RNs) is proposed in this paper. At each task assignment point, the rule prioritizes all treatment requests based on the urgency which is determined by the multiple attributes such as accomplishment time of treatment task, elapsed time of treatment request, total remain time to patient discharge, and number of remain treatments. The values of partial urgency with a single criterion are determined and then overall urgency is computed to find the most urgent one among current requests with the importance weights assigned to the criteria. Through computer simulation, the performance of the proposed rule is compared with current rule in terms of the length of stay and system throughput in a simplified ED system of the hospital M.

In this paper, the task assignment strategy considering communication delay and the priority of distributed tasks is proposed for the real-time network system in order to maximize the utilization of the system. For the task assignment strategy, the relationship among priority of tasks in network nodes, the calculation time of each task, and the end-to-end response time including the network delay is formulated firstly. Then, the task assignment strategy using the genetic algorithm is proposed to optimize the utilization of the system considering the LCM(Least Common Multiple) period. The effectiveness of proposed strategy is proven by the simulation for estimating the performance such as the utilization and the response time of the system in case of changing the number of tasks and the number of network nodes.

최상의 에이전트-작업 할당을 결정하는 문제는 조합 최적화(combinatorial optimization)의 대표적인 문제이자 NP-난해(NP-hard)임이 알려져 있다. 본 연구에서는 에이전트와 작업의 할당 시 결정되는 작업 수행 확률(completion probability)이 불확실한 상황에서의 문제를 다룬다. 에이전트나 작업 내부의 요인 혹은 시스템 외적인 요소로 인한 작업 수행 확률은 고정적이기보다 불확실성을 갖는 것이 일반적이다. 불확실성을 고려하지 않은 할당 결정은 변동성이 있는 현실 상황에서 효과적이지 않은 결정이 될 수 있다. 작업 수행 확률의 불확실성을 수학적으로 반영하기 위해 본 연 구에서는 추계적 계획법(stochastic programming)을 활용한 수리 모형을 제시한다. 본 연구에서는 효율적으로 문제를 풀기 위해 표본 평균 근사법(sample average approximation)을 활용한 알고리즘을 제안한다. 본 문제 해결 방법론을 이용해 효과적인 할당 결정과 상한값과 하한값을 구할 수 있고, 결과의 성능을 확인하기 위해 최적 격차(optimality gap)와 분산을 실험을 통해 제시한다. 이를 통해 알고리즘으로 구한 할당 결정의 우수성 및 강건성을 보인다.

The optimal assignment problem between agents and tasks is known as one of the representative problems of combinatorial optimization and an NP-hard problem. This paper covers multi agent-multi task assignment problems with uncertain completion probability. The completion probabilities are generally uncertain due to endogenous (agent or task) or exogenous factors in the system. Assignment decisions without considering uncertainty can be ineffective in a real situation that has volatility. To consider uncertain completion probability mathematically, a mathematical formulation with stochastic programming is illustrated. We also present an algorithm by using the sample average approximation method to solve the problem efficiently. The algorithm can obtain an assignment decision and the upper and lower bounds of the assignment problem. Through numerical experiments, we present the optimality gap and the variance of the gap to confirm the performances of the results. This shows the excellence and robustness of the assignment decisions obtained by the algorithm in the problem with uncertainty.

본 연구는 고등학교 남학생 400명을 대상으로, 가상의 직장 상황을 주고 남성의 온정적 성차별주의 지지도가 여성직장인의 업무 배치에 어떤 영향을 줄 수 있는지 검증해 보았다. 그 결과, 온정적 성차별주의 지지도가 높은 남학생들일수록 도전적인 업무에는 여성을 배치하지 않으려 했고, 여성적인 업무에 여성을 배치하는 데는 더 동의하고 있었다. 온정적 성차별주의는 여성을 약한 존재로 보며 여성에 대한 전통적인 고정관념을 가지고 있다. 그래서 온정적 성차별주의를 지지하는남학생일수록 여성을 보호해야 한다는 생각에 여성에게 힘든 업무를 주지 않고, 여성에게 적합하다고 여겨지는 업무를 맡기려고 한 것으로 보인다. 하지만 온정적 성차별주의자 남성들의 이런 행동은 여성들의 능력 개발과 직업적 성취를 어렵게 만든다. 따라서 직장 내 성차별을 근절하고 진정한 남녀평등을 실현하기 위해서는 사회과에서 학생들에게 온정적 성차별주의에 대해 가르쳐야 한다. 이때는 온정적 성차별주의가 왜 해로운지 구체적으로 알려주는 일이 중요하다. 그리고 사회과는 특히 남학생들이 온정적 성차별주의를 거부하고 성평등을 실천하도록 도울 수 있는 효과적인 지도 방안을 모색해야 한다.

In this study, 400 male high school students participated in the investigation to verify how the support from benevolent sexism of men affects assignment of female coworkers in a given hypothetical occupational situation. The results showed that male students with greater support level of benevolent sexism avoided assigning female workers to challenging tasks and agreed more on assigning female workers to tasks typically considered fitting more for women. Benevolent sexism perceives women as weak individuals and carries traditional stereotypes of women. Thus, male students that supported benevolent sexism seemed not to assign women with difficult tasks and rather gave them with tasks they considered to be appropriate for women. However, such behavior of men exhibiting benevolent sexism makes it difficult for women to develop their skillsets and attain professional achievements. Therefore, in order to eradicate sexism in the workplace and achieve true gender equality, it is required to educate students on benevolent sexism in social studies. In educating students on why benevolent sexism could be negative, it is critical to teach in detail. Furthermore, in social studies education, it is required to find effective ways of guidance to help male students reject benevolent sexism and practice gender equality.

역할기반 접근통제(RBAC, Role-Based Access Control)의 개념은 접근통제의 전통적인 강제적 접근통제(MAC, Mandatory Access Control) 및 임의적 접근통제(DAC, Discretionary Access Control)의 대안으로서 많은 관심을 집중시키고 있다. 그러나 역할기반 접근통제를 워크 플로우 시스템에 그대로 적용할 경우에 의무 분리가 복잡해지고, 의무분리를 통해 상호 배타적인 역할을 가지지 못하게 했을 때 서로 관계없는 워크 플로우를 동시에 처리 못하게 되는 문제점이 발생할 수 있다. 이것을 해결하기 위하여 기업 환경의 특성으로 고려한 과업 역할기반 접근제어 모델(TRBAC: Task Role Based Access Control)이 제안되었다. 본 논문에서는 TRBAC의 워크 플로우 과업 관리를 위하여 과업(Task)을 역할(Role)에 할당하는 과업 - 역할할당(TRA)모델을 제안하고 이를 구현한다.