• 정보교육학회논문지
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• 제20권6호
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• pp.629-644
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• 2016

본 연구는 웹기반 복합적 과제에서 전체과제 계열화 방법이 전문성 향상에 미치는 영향을 규명하는 것을 목적으로 한다. 이를 위해 전체과제 계열화 방법을 단순 제시, 눈덩이 강조변화, 전체 강조변화로 구별하였으며, 93명의 대학생이 실험에 참가하였다. 연구결과에 따르면, 인지부하에서 전체과제 계열화 방법 간 유의한 차이가 나타났지만, 사후검정 결과 단순 제시 집단과 눈덩이 강조변화 집단 간에는 유의한 차이가 나타나지 않았다. 이에 따라 복합적 과제는 실제의 과제를 다루어 각 요소들의 높은 상호작용성을 가지고 있지만 부분을 강조하되 전체를 함께 조망할 수 있는 눈덩이 강조변화 방식의 제공은 학습자의 메타인지를 지원해줄 수 있어 인지과부하를 일으키지 않는다는 것을 확인할 수 있었다. 학습전이를 살펴본 결과 전체과제 계열화 방법에 따라 집단 간 유의한 차이가 나타났다. 이는 전체과제 계열화를 사용할지라도 그 안에서 전체과제 계열화의 단점인 연습부족을 보완하기 위해 눈덩이 강조변화 방식을 통해 계열화 하였을 때 복합적 과제에 대한 이해도를 높여 실제 문제해결 과제에서 질 높은 결과물을 구성하여 초보자의 전문성을 향상 시킬 수 있음을 시사했다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• 정보처리학회논문지B
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• 제8B권6호
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• pp.601-608
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• 2001

The automated assignment of multiple tasks to executing agents is a key problem in the area of multi-agent systems. In many domains, significant savings can be achieved by reallocating tasks among agents with different costs for handling tasks. The automation of task reallocation among self-interested agents requires that the individual agents use a common negotiation protocol that prescribes how they have to interact in order to come to an agreement on "who does what". In this paper, we introduce the multi-agent Traveling Salesman Problem(TSP) as an example of task reallocation problem, and suggest the Vickery auction as an interagent negotiation protocol for solving this problem. In general, auction-based protocols show several advantageous features: they are easily implementable, they enforce an efficient assignment process, and they guarantce an agreement even in scenarios in which the agents possess only very little domain-specific Knowledge. Furthermore Vickrey auctions have the additional advantage that each interested agent bids only once and that the dominant strategy is to bid one′s true valuation. In order to apply this market-based protocol into task reallocation among self-interested agents, we define the profit of each agent, the goal of negotiation, tasks to be traded out through auctions, the bidding strategy, and the sequence of auctions. Through several experiments with sample multi-agent TSPs, we show that the task allocation can improve monotonically at each step and then finally an optimal task allocation can be found with this protocol.

• 영어어문교육
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• 제12권3호
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• pp.123-145
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• 2006

The purpose of this study is to propose an efficient vocabulary assessment model in task-based language learning and to verify the viability of this assessment model. Bachman and Palmer (1996) pointed out the fact that many language tests focus on just one of the areas of language knowledge. However, researchers suggested that it is necessary to acknowledge the needs of several analytic scales, which can provide separate ratings for different components of the language ability to be tested. Although there were many studies which tried to evaluate the various aspects of vocabulary ability, most of them measured only one or two factors. Based on previous research, this study proposed an assessment model of general construct of vocabulary ability and tried to measure vocabulary ability in four separate areas. The subjects were two classes of university level Korean EFL students. They participated in small group discussion via synchronous CMC. One class used a lexically focused task, which was proposed by Kim and Jeong (2006) and the other class used a non-lexically focused task. The results showed that the students with a lexically focused task significantly outperformed those with a non-lexically focused task in overall vocabulary ability as well as four subdivisions of vocabulary ability. In conclusion, the assessment model of separate ratings is a viable measure of vocabulary ability and this can provide elaborate interpretation of vocabulary ability.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.308-310
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• 2022

With the rise of the Al wave, task-oriented dialogue systems have become one of the popular research directions in academia and industry. Currently, task-oriented dialogue systems mainly adopt pipelined form, which mainly includes natural language understanding, dialogue state decision making, dialogue state tracking and natural language generation. However, pipelining is prone to error propagation, so many task-oriented dialogue systems in the market are only for single-round dialogues. Usually single- domain dialogues have relatively accurate semantic understanding, while they tend to perform poorly on multi-domain, multi-round dialogue datasets. To solve these issues, we developed a paddle-based multi-domain task-oriented Chinese dialogue system. It is based on NEZHA-base pre-training model and CrossWOZ dataset, and uses intention recognition module, dichotomous slot recognition module and NER recognition module to do DST and generate replies based on rules. Experiments show that the dialogue system not only makes good use of the context, but also effectively addresses long-term dependencies. In our approach, the DST of dialogue tracking state is improved, and our DST can identify multiple slotted key-value pairs involved in the discourse, which eliminates the need for manual tagging and thus greatly saves manpower.

• 한국과학교육학회지
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• 제16권1호
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• pp.87-96
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• 1996

In this study, students' performances on the reasoning tasks dealing with physical situations were analyzed. Through these analysis, the influences of students' preconceptions and logical abilities in reasoning process were described. For this study, 97 high school students were randomly selected. Among them, the number of the students who changed their misconceptions is 62% for the first task(force acting on the upward moving body), and 25% for the second task(force acting on the body when it is on the top of its motion). The students who show the premise-based response changed their conceptions in both of the tasks are more than those who responded in the idea based responses. The index of the influence of prior knowledge, ${\alpha}$ is 33% for the first task, and 67% for the second task, and ${\beta}$ is 41% for the first task, and 17% for the second task. When students performed the reasoning tasks about force and motion, the misconcepts frequently influenced their performances. But for the first task, the precentage of students who changed their concepts is about 62%. It shows the possibility that if the task is simple and appropriate, students can change their concepts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• 한국IT서비스학회지
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• 제12권1호
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• pp.309-321
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• 2013

In current complex nature of management with task-structures, a method to reach the enterprise's informationalization success is not common. To satisfy these various requirement, improving the usability of information technology (IT) is a key factor which defining the level of organizational requirement first. Imposing an IT-solution which has excess service of the organization's previous task-environment, procedure and scope is not effective to SME-level unit, which unit could not have a formal organization structure and task structure. SME level informationalization will be success if each function realizes easier on the task-employee's viewpoint. Achieving this objective, a solution provider or department must reflect their work characteristics of nature which has least level of work performing resistance. It is most useful system for SME level unit, if a provider develops single programs which based on task activities, and each program can configure network-linking.

• 제어로봇시스템학회논문지
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• 제18권4호
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• pp.302-307
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• 2012

Real-time systems perform periodic tasks and real-time aperiodic tasks such as alarm processing. Especially the periodic tasks included in control systems such as robots have precedence relationships among them. This paper proposes a new scheduling algorithm based on topological sort and residual time. The precedence relationships among periodic tasks are translated to the priorities of the tasks using topological sort algorithm. During the execution of the system the proposed scheduling algorithm decides on whether or not a newly arrived real-time aperiodic task is accepted based on residual time whenever the aperiodic task such as alarm is arrived. The proposed algorithm is validated using examples.