• Journal of Korean Library and Information Science Society
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• v.45 no.4
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• pp.95-117
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• 2014

A number of studies have emphasized the importance and values of reading in character education. However, there is no tool or framework for developing character education program. If teacher librarian to develop a character education program by reading should be preceded the framework for a comprehensive and systematic approach. The framework for character education program by reading is required to develop a program. The framework must be considered with a character factor and reading elements. The purpose of this study is to establish a framework that will help teacher librarian to develop a character education program by reading. This study analyzed on construction elements of character, reading material for character education, reading strategies, teaching methods. Then, this study propose a framework for developing character education program based on the analysis information. The proposed framework in this study consists of construction elements of character, reading material for character education, reading strategies, teaching methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• Journal of Engineering Education Research
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• v.15 no.5
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• pp.64-68
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• 2012

Design factors such as design objects establishment, analysis, synthesis, production, test and evaluation should be educated in a systematic way. Also design ability to reflect practical restrictive conditions such as industrial standards, economic feasibility, environmental impact, aesthetics, safety and reliability, ethical impacts and social impacts should be cultivated. In this paper, we explain the meaning of these terms and propose a systematic engineering design education framework satisfying Korean engineering education accreditation criteria. We also present a simple implementation in information network engineering.

• IE interfaces
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• v.18 no.1
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• pp.1-9
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• 2005

A new logistics concept is needed through the sharing information between suppliers and consumers, which maximizes the customers service and its flexibility by changing functional- oriented to process-oriented. As in many other industries, communication and data manipulation technology have led to systematical change to the logistics industry. One of the biggest changes of the industry that lies ahead is Consolidated Transportation. To improve this systematically false logistical environment, developing an integrated logistics information system with consolidated transportation, framework, standardization, and data integration is essential. However, no party outstands as the leading party for nationwide improvement of logistics, nor does the right analysis and design for it. Therefore, successful nationwide logistics model is yet to exist. This paper provides individual parties, which consider efficient consolidated transportation as their business models, with instructions for logistics information system so that they could be competitive in the market. It also helps companies collect user requirements for efficient consolidated transportation, and utilize it for its development. Finally, this paper extracts the design of algorithm for the efficient consolidated transportation.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.37-43
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• 2018

In this paper, we propose a framework that automatically suggests emotion using emotion analysis method based on facial expression change. We use Microsoft's Emotion API to calculate and analyze emotion values in facial expressions to recognize emotions that change over time. In this step, we use standard deviations based on peak analysis to measure and classify emotional changes. The difference between the classified emotion and the normal emotion is calculated, and the difference is used to recognize the emotion abnormality. We match user's emotions to relatively relaxed emotions using histograms and emotional meshes. As a result, we provide relaxed emotions to users through images. The proposed framework helps users to recognize emotional changes easily and to train their emotions through emotional relaxation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.334-343
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• 2008

In this work we propose a universal pricing machine, which incorporates a universal pricing framework for the future IEEE802.16 WiMAX service with multiple classes of service. A multimedia service is provided by a QoS provisioning scheme in the WiMAX network and universal pricing means that it can compute the price for any type of service in a unified framework. In the proposed pricing framework we incorporate multiple types of services such as the real time and nonreal time services that are supposed to be provided in the WiMAX network. To that purpose, let us first carry out an analysis on the current pricing scheme of Korean WiMAX service which incorporates only the data size. From that analysis we propose a new pricing scheme for the future WiMAX service that provides different service classes in the network. Via numerical experiment, we verify the implication of the work.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.370-373
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• 2022

Recently, various deep learning framework models such as Tensorflow, Pytorch, Keras, etc. have appeared. In addition, CNN (Convolutional Neural Network) is applied to image recognition using frameworks such as Tensorflow, Pytorch, and Keras, and the optimization model in image classification is mainly used. In this paper, based on the results of training the CNN model with the Paitotchi and tensor flow frameworks most often used in the field of deep learning image recognition, the two frameworks are compared and analyzed for image analysis. Derived an optimized framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3865-3883
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• 2016

Infrastructure as a Service (IaaS) encapsulates computer hardware into a large amount of virtual and manageable instances mainly in the form of virtual machine (VM), and provides rental service for users. Currently, VM anomaly incidents occasionally occur, which leads to performance issues and even downtime. This paper aims at detecting anomalous VMs based on performance metrics data of VMs. Due to the dynamic nature and increasing scale of IaaS, detecting anomalous VMs from voluminous correlated and non-Gaussian monitored performance data is a challenging task. This paper designs an anomaly detection framework to solve this challenge. First, it collects 53 performance metrics to reflect the running state of each VM. The collected performance metrics are testified not to follow the Gaussian distribution. Then, it employs independent components analysis (ICA) instead of principal component analysis (PCA) to extract independent components from collected non-Gaussian performance metric data. For anomaly detection, it employs multi-class Bayesian classification to determine the current state of each VM. To evaluate the performance of the designed detection framework, four types of anomalies are separately or jointly injected into randomly selected VMs in a campus-wide testbed. The experimental results show that ICA-based detection mechanism outperforms PCA-based and LDA-based detection mechanisms in terms of sensitivity and specificity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3611-3634
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• 2015

In this paper, we build a theoretical framework for quantitatively measuring and graphically representing the degrees of closeness centralization among performers assigned to enact a workflow procedure. The degree of closeness centralization of a workflow-performer reflects how near the performer is to the other performers in enacting a corresponding workflow model designed for workflow-supported organizational operations. The proposed framework comprises three procedural phases and four functional transformations, such as discovery, analysis, and quantitation phases, which carry out ICN-to-WsoN, WsoN-to-SocioMatrix, SocioMatrix-to-DistanceMatrix, and DistanceMatrix-to-CCV transformations. We develop a series of algorithmic formalisms for the procedural phases and their transformative functionalities, and verify the proposed framework through an operational example. Finally, we expatiate on the functional expansion of the closeness centralization formulas so as for the theoretical framework to handle a group of workflow procedures (or a workflow package) with organization-wide workflow-performers.

• Journal of Information Technology Applications and Management
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• v.9 no.3
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• pp.129-139
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• 2002

There exist a number of information systems planning (ISP) methodologies. Historically these methodologies have been evolving to reflect new technologies and business requirements. In fact, it is an uneasy task to select a methodology that fits a business need. Though there have been a number of studies proposing new ISP approaches, we are unable to find much research doing a comparative analysis on existing ISP methodologies. Our study, therefore, is to present a classification scheme for ISP approaches and to provide a guideline framework for selecting an approach most suitable to a particular firm's need. Our classification utilizes types of components covered in ISP deliverables and the peculiarity of these components. Such classification scheme and selection framework would help derive an IT-driven new enterprise model more effectively.