• Title/Summary/Keyword: Learning Management Services

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Lessons Learned from Institutionalization of ML (Machine Learning) Supported HR Services in the Existence of Multiple Institutional Logics

  • Gyeung-min Kim;Heesun Kim
    • Asia pacific journal of information systems
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    • v.33 no.4
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    • pp.1171-1187
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    • 2023
  • This study explores how an organization has successfully implemented ML-supported HR services to resolve high employee turnover problems in the IT sector. The empirical setting of the research is where contradicting institutional logics exist among technical, HR, and business groups regarding the ML model development and use of the model predictions in HR services. Institutional framework is used to identify the roles of organizational actors and the legitimacy structures in the organizational environments that can shape or constrain the ML led organizational changes. In institutional theories, technology adoption and organizational change are not only constrained by organizational context, but also fostered through organizational actors' roles and efforts to increase the legitimacy for the change. This research found that when multiple contradicting institutional logics exist, legitimizing the establishment of an enabling environment for multiple logics to reconcile and for the project to move forward is critical. Industry-wide conditions, previous experiences with the pilot ML project, forming a TFT with clearly defined roles and responsibilities, and relevant KPIs are found to legitimize the HR team and the business division to collaborate with the technical personnel to launch ML-supported HR services.

Real-time RL-based 5G Network Slicing Design and Traffic Model Distribution: Implementation for V2X and eMBB Services

  • WeiJian Zhou;Azharul Islam;KyungHi Chang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.9
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    • pp.2573-2589
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    • 2023
  • As 5G mobile systems carry multiple services and applications, numerous user, and application types with varying quality of service requirements inside a single physical network infrastructure are the primary problem in constructing 5G networks. Radio Access Network (RAN) slicing is introduced as a way to solve these challenges. This research focuses on optimizing RAN slices within a singular physical cell for vehicle-to-everything (V2X) and enhanced mobile broadband (eMBB) UEs, highlighting the importance of adept resource management and allocation for the evolving landscape of 5G services. We put forth two unique strategies: one being offline network slicing, also referred to as standard network slicing, and the other being Online reinforcement learning (RL) network slicing. Both strategies aim to maximize network efficiency by gathering network model characteristics and augmenting radio resources for eMBB and V2X UEs. When compared to traditional network slicing, RL network slicing shows greater performance in the allocation and utilization of UE resources. These steps are taken to adapt to fluctuating traffic loads using RL strategies, with the ultimate objective of bolstering the efficiency of generic 5G services.

Resource Metric Refining Module for AIOps Learning Data in Kubernetes Microservice

  • Jonghwan Park;Jaegi Son;Dongmin Kim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.6
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    • pp.1545-1559
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    • 2023
  • In the cloud environment, microservices are implemented through Kubernetes, and these services can be expanded or reduced through the autoscaling function under Kubernetes, depending on the service request or resource usage. However, the increase in the number of nodes or distributed microservices in Kubernetes and the unpredictable autoscaling function make it very difficult for system administrators to conduct operations. Artificial Intelligence for IT Operations (AIOps) supports resource management for cloud services through AI and has attracted attention as a solution to these problems. For example, after the AI model learns the metric or log data collected in the microservice units, failures can be inferred by predicting the resources in future data. However, it is difficult to construct data sets for generating learning models because many microservices used for autoscaling generate different metrics or logs in the same timestamp. In this study, we propose a cloud data refining module and structure that collects metric or log data in a microservice environment implemented by Kubernetes; and arranges it into computing resources corresponding to each service so that AI models can learn and analogize service-specific failures. We obtained Kubernetes-based AIOps learning data through this module, and after learning the built dataset through the AI model, we verified the prediction result through the differences between the obtained and actual data.

A Study on Analysis of Current Status and Improvement Suggestions for Massive Open Online Courses (온라인 공개 강좌 MOOC의 현황 분석 및 개선안 연구)

  • Bae, Ye-Sun;Jun, Woo-Chun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.12
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    • pp.3005-3012
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    • 2014
  • Massive Open Online Courses(MOOC), originally started from United States, have recently received a great deal of attention all over the world. MOOC means free online courses that anyone can attend anytime. In Korea, KERIS(Korea Education and Research Information Service) and some universities provide various MOOC services. The purpose of this paper is to present current status and improvement suggestions of MOOC. We first introduce the formal definition and history of MOOC, then discuss current status of MOOC services in Korea and other countries. We finally present improvement suggestions that include induction of active participation for universities, value creation for campus, development of revenue model, providing motivation to students for finishing courses, development of LMS(Learning Management System), securing well-trained lecturers, translation of lecture materials, ensuring quality of authentification system of MOOC services.

A Study on Development Strategies for Artificial Intelligence-Based Personalized Mathematics Learning Services (인공지능 기반 개인 맞춤 수학학습 서비스 개발 방향에 관한 연구)

  • Joo-eun Hyun;Chi-geun Lee;Daehwan Lee;Youngseok Lee;Dukhoi Koo
    • Journal of Practical Engineering Education
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    • v.15 no.3
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    • pp.605-614
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    • 2023
  • In In the era of digital transition, AI-based personalized services are emerging in the field of education. This research aims to examine the development strategies for implementing AI-based learning services in school. Focusing on AI-based math learning service "Math Cell" developed by i-Scream Edu, this study surveyed the functional requirements from the perspective of an educator. The results were analyzed for importance and suitability using IPA, and expert opinions were surveyed to explore specific development directions for the service. Consequently, importance in all areas such as diagnosis, learning, evaluation, and management averaged 4.82 and performance averaged 4.56, showing excellent results in most questions, and in particular, importance was higher than performance. Among certain detailed functions, concept learning, customized task presentation, evaluation result analysis function, dashboard-related functions, and learning materials in the dashboard were not intuitive for students to understand and had to be supplemented. This study provides meaningful insights by summarizing expert opinions on AI-based personalized mathematics learning services, thereby contributing to the exploration of the development strategies for "Math Cell".

Health Care Reform in OECD and It's Lessons (OECD 국가를 중심으로 한 의료개혁 동향과 교훈)

  • Lee, Kyu-Sik;Kim, Ju-Kyeong
    • Korea Journal of Hospital Management
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    • v.9 no.3
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    • pp.18-48
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    • 2004
  • Health policies in many countries have come under critical scrutiny in recent years. This is because of increasing national health expenditures. Also many persons in health sector have been the perception that resources allocated to health services are not always deployed in an optimal fashion. And they believe that the scope of resources in health services is limited, there is need to search for ways of using existing resources more efficiently. A further concern has been the desire to ensure access to healthcare of various groups on an equitable basis. In some European countries this has been linked to a wish to enhance patient choice and to make service providers more responsive to consumers, while Korea integrated health insurance funds into single fund in 2000. Many European countries are under considerable pressure to review and restructure their health care systems. There are several reasons of pressure to reform. There are demographic changes, pattern of disease change, advances in medical sciences will also give rise to new demands within the health services, public expectations of health services are rising as those who use services demand higher standards of care. These circumstances require the change of health care delivery system based on hierarchical regionalism, which was basis of health care delivery since 1920s. Korea is also under similarly pressure to restructure our own health care systems. We will have good learning from OECD experiences. In this paper we reviewed and compared among OECD countries' various experiences.

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A Study of On-line Education on Training Effectiveness (온라인(on-line) 교육훈련의 효과성에 관한 연구)

  • 남기찬;임효창;황국재
    • Journal of the Korean Operations Research and Management Science Society
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    • v.27 no.1
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    • pp.75-94
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    • 2002
  • The development of Information technologies huts contributed on-line training as one of important education methods. On-line training In firms, which is similar to e-learning or virtual education, provides trainees with more education opportunities in diverse ways. It has developed a range of innovative services with an one-stop solution of education within the electronic sector. Also under the on-line training environment, trainees can undertake customized training packages at anytime and any places. Moreover, information technology allows both the trainers and other trainees to be decoupled in any of the elements of time, place, and space. Two research questions are investigated : what are the determinants affecting the on-line training effectiveness and how those variables effect the two aspects of training effectiveness: learning performance and transfer performance. Based on the previous literature conducted on the traditional training environment, the determinants of training effectiveness are derived. light hypotheses are developed based on literature reviews and tested by questionnaires survey data. The collected data have been analyzed by LISREL. It is found that the relationship between individual, organizational and on-line sloe design variables and training effectiveness (learning and transfer) are significant. The contribution and limitations of this research are also discussed tilth future studies.

Theoretical And Methodological Principles Of Distance Learning: Priority Direction Of Education

  • Fabian, Myroslava;Tur, Oksana;Yablonska, Olha;Rumiantseva, Alla;Oliinyk, Halyna;Sukhlenko, Iryna
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.251-255
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    • 2022
  • The article considers the state and trends of distance learning in the world and Ukraine, identifies the main species differences between distance education and other forms of education, analyzes the state of the global market for educational services provided via the Internet. Important features and characteristics of distance learning, examples of its organization in higher education, as well as statistics on the development of distance learning in our country. The main problematic points on the way to the implementation of the distance education system in Ukraine and the factors that hinder the development of this promising form of education are outlined.

An Engine for DRA in Container Orchestration Using Machine Learning

  • Gun-Woo Kim;Seo-Yeon Gu;Seok-Jae Moon;Byung-Joon Park
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.126-133
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    • 2023
  • Recent advancements in cloud service virtualization technologies have witnessed a shift from a Virtual Machine-centric approach to a container-centric paradigm, offering advantages such as faster deployment and enhanced portability. Container orchestration has emerged as a key technology for efficient management and scheduling of these containers. However, with the increasing complexity and diversity of heterogeneous workloads and service types, resource scheduling has become a challenging task. Various research endeavors are underway to address the challenges posed by diverse workloads and services. Yet, a systematic approach to container orchestration for effective cloud management has not been clearly defined. This paper proposes the DRA-Engine (Dynamic Resource Allocation Engine) for resource scheduling in container orchestration. The proposed engine comprises the Request Load Procedure, Required Resource Measurement Procedure, and Resource Provision Decision Procedure. Through these components, the DRA-Engine dynamically allocates resources according to the application's requirements, presenting a solution to the challenges of resource scheduling in container orchestration.

Quality Indicators of ICT-Related Support for Blended-Learning in Traditional Universities

  • CHOI, Kyoung Ae;KIM, Dongil;PARK, Chunsung
    • Educational Technology International
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    • v.6 no.1
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    • pp.81-101
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    • 2005
  • Campus-based universities have provided face-to-face instruction traditionally. But recently, it is becoming a trend that they provide blended learning which combines e-learning and f2f instruction. Therefore, traditional university has been installing the ICT related convenience for the faculty and students to use easily to their classes. The purpose of this study is to develop quality indicators of ICT-related support for proper blended learning in traditional campus-based universities. This indicators are used for measuring the quality of ICT-related services at university level for quality education. To this end, first, we reviewed literature about quality indicators of university evaluation and e-learning. Second,we did case study. We selected and analyzed one university for a case, And we identified what elements are perceived important to faculty for more efficient use of technology to their class. Third, we summarized all this data and established the quality indicators framework of ICT-related components for blended learning in campus-based universities. Then, these indicators were revised after the expert evaluation. And then 10 experts and practitioners scored importance rating. Finally, we sum them up to 17 indicators and 48 sub-indicators in three phases (input, process, output). Among them, e-learning related organization or body, usability of Learning Management System, and quality assessment system got the highest scores. These indicators are supposed to contribute to measure the quality of ICT-related environment for blended learning and to provide informations about what is required for efficient blended learning in the campus-based universities.