• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.31-48
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• 2023

The popularization of smart devices and subsequent optimization of their sensing capacity has resulted in a novel mobile crowdsensing (MCS) pattern, which employs smart devices as sensing nodes by recruiting users to develop a sensing network for multiple-task performance. This technique has garnered much scholarly interest in terms of sensing range, cost, and integration. The MCS is prevalent in various fields, including environmental monitoring, noise monitoring, and road monitoring. A complete MCS life cycle entails task allocation, data collection, and data aggregation. Regardless, specific drawbacks remain unresolved in this study despite extensive research on this life cycle. This article mainly summarizes single-task, multi-task allocation, and space-time multi-task allocation at the task allocation stage. Meanwhile, the quality, safety, and efficiency of data collection are discussed at the data collection stage. Edge computing, which provides a novel development idea to derive data from the MCS system, is also highlighted. Furthermore, data aggregation security and quality are summarized at the data aggregation stage. The novel development of multi-modal data aggregation is also outlined following the diversity of data obtained from MCS. Overall, this article summarizes the three aspects of the MCS life cycle, analyzes the issues underlying this study, and offers developmental directions for future scholars' reference.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.621-630
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• 2018

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.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.89-100
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• 2022

With the advancement in the Internet of things Technology (IoT) cloud computing, billions of physical devices have been interconnected for sharing and collecting data in different applications. Despite many advancements, some latency - specific application in the real world is not feasible due to existing constraints of IoT devices and distance between cloud and IoT devices. In order to address issues of latency sensitive applications, fog computing has been developed that involves the availability of computing and storage resources at the edge of the network near the IoT devices. However, fog computing suffers from many limitations such as heterogeneity, storage capabilities, processing capability, memory limitations etc. Therefore, it requires an adequate task scheduling method for utilizing computing resources optimally at the fog layer. This work presents a comprehensive review of different task scheduling methods in fog computing. It analyses different task scheduling methods developed for a fog computing environment in multiple dimensions and compares them to highlight the advantages and disadvantages of methods. Finally, it presents promising research directions for fellow researchers in the fog computing environment.

• Fire Science and Engineering
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• v.33 no.5
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• pp.130-139
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• 2019

This study identified the level of task stress experienced by fire protection system management workers and analyzed the effects of task stress on job satisfaction and proposed future response. First, task stress according to background cause showed differences in relation to age, position, monthly salary, total career, license, and task, but there was no difference in relation to academic background. Second, of the sub-parameters of stress, physical environment, task demand, organizational system, lack of reward, and workplace culture have negative effects on job satisfaction as stress increases, while interpersonal relation conflict and job insecurity do not have any effect. In the future, it will be necessary to investigate the empirical causes of work overload and to study organization-level stress relief measures.

• Journal of the Ergonomics Society of Korea
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• v.33 no.1
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• pp.27-37
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• 2014

Objective: This study aims to improve human performance by analyzing the operators' tasks and providing input data on the composition of future SMART operators. Background: SMART is a nuclear reactor for export which needs operators who can satisfy both safety and economic feasibility. Therefore, this study is fundamental research on the composition of operators and this research analyzed SMART tasks in terms of human safety performance. Method: After analyzing 10 SMART EOG in hierarchical task analysis, this study classified task performance types according to task requirements of NUREG-0711 (Rev.3). Results: This study found the task frequency of SMART EOG and 12 operating task types. Conclusion: This study expects that human performance can be improved by analyzing the personal errors, which have the highest task frequency among 12 operating task types. Application: The results of this study can be applied as base data when licensing needs to be acquired.

• Journal of Korean Library and Information Science Society
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• v.43 no.1
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• pp.99-122
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• 2012

This study deals with the user task that is the goal of development of RDA (Resource Description & Access), an international standard for future bibliographic description. RDA seeks to implement the user task based on FRBR-FRAD model. User task could be composed of two areas: (1) find, identify, select, and obtain of bibliographic resources in information seeking and (2) find, identify, clarify, and understand of entities related to resources (i.e., person, family, corporate, concept, etc.). This research analyzes how the resource is defined with entity, attributes, and relationship in RDA based on the conceptual model of FRBR-FRAD. And this finally shows the ways of supporting user task in RDA.

• English Language & Literature Teaching
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• v.12 no.4
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• pp.253-276
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• 2006

The purpose of this study is to compare and analyze the aspects of task-based materials in high school English textbooks for first year students in Korea. Based on the theoretical backgrounds for designing communicative tasks and the basic contents of the 7th national curriculum for English, a total of six different qualitative evaluation categories of task-based materials are constructed. The six categories include input data, settings, activity types, language skills, activity themes, and communicative functions. The results of the data analysis showed that the regulations of the 7th national English curriculum, which were aimed at improving the students' communicative abilities, were properly reflected in the materials of task-based activities of all textbooks. On the other hand, a few problems were found in some textbooks: too many individual tasks; being out of proportion in presenting task types and themes; non-systematic introduction of language skills, etc. To conclude, a few suggestions are made to provide some meaningful considerations for the text material developers in order to produce better textbooks in the future: task goals and rationale that encourage the learner's positive motivation; authenticity of input data based on the real-world context; a collaborative learning environment that enhances communicative interaction; a proportional representation of the various activity types including creative problem-solving procedures; systematic introduction of integrated language skills, etc.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1208-1218
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• 2022

In the medical field, artificial intelligence has been used in various ways with many developments. However, most artificial intelligence technologies are developed so that one model can perform only one task, which is a limitation in designing the complex reading process of doctors with artificial intelligence. Multi-task learning is an optimal way to overcome the limitations of single-task learning methods. Multi-task learning can create a model that is efficient and advantageous for generalization by simultaneously integrating various tasks into one model. This study investigated the concepts, types, and similar concepts as multi-task learning, and examined the status and future possibilities of multi-task learning in the medical research.

• The Journal of Industrial Distribution & Business
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• v.13 no.5
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• pp.27-40
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• 2022

Purpose: Research on job crafting has thus far focused on how alter job demand and resources behaviors relate to employee task performance. However, job crafting behaviors do not necessarily have an impact only on task performance, but also on employees' contextual performance, a phenomenon that has little research in job crafting research. Therefore, this study aims to investigate the effect of job crafting on task performance or contextual performance and the mediating effect of work engagement between them in the Chinese context. Research design, data and methodology: In order to achieve the above research goals and test the proposed hypotheses, we used a cross-sectional design and a self-administered questionnaire to collect quantitative data from September 8, 2021 to September 27, 2021 among knowledge workers in Shandong Province various financial companies and finally analyzed 211 questionnaires. Descriptive statistics and research model analysis were performed using SPSS 25.0 Version and AMOS 27.0 Version to test the developed hypotheses. Results: The results are as follows; firstly, the study showed that job crafting of employees had a significant positive impact on task performance and contextual performance. Secondly, the higher job crafting of employees, the higher their work engagement. Thirdly, this study showed that work engagement of employees had a positive impact on task performance and contextual performance. Fourthly, we predicted and found that work engagement of employees had a positive mediating effect between job crafting and task performance and a positive mediating effect between job crafting and contextual performance. Overall, this study showed that the proactive job crafting behaviors of employees enhance their engagement for their work, which in turn improves task performance and contextual performance. Conclusions: This paper develops job crafting research by exploring the positive impact of job crafting on employees' task performance or contextual performance through their work engagement. It also proposes that both job crafting behaviors and work engagement are important approaches to improve employees' task performance or contextual performance. Practical implications for organizations, such as increasing employee' work engagement, as well as the limitations and suggestions are concluded for the future research directions.