• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.645-650
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• 2015

Tester Interface Software (TIS) provides all software functions that are necessary for a testing device to perform the test process on a memory semiconductor package from the time the device is put into the test equipment until the device is discharged from the equipment. TIS should perform the same work over all types of equipment regardless of their tester models. However, TIS has been developed and managed independently of the tester models because there are various equipment and computer models that are used in the test process. Therefore, more maintenance, time and cost are required for development, which adversely affects the quality of the software, and the problem becomes more serious when the new tester model is introduced. In this paper, we propose the Cross-platform Tester Interface Software (CTIS) framework, which can be integrated and operated on heterogeneous equipment and OSs.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.4
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• pp.336-349
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• 2001

Intelligent Network (IN) is an architectural framework for the rapid and uniform provision of advanced services. Therefore, Next-generation IN platform should support fast service handling, the dynamic adaptation of various services according to various requirements of users. In this paper, we design and implement the Service Control Point (SCP) that is based on the Internet environment. Especially, we consider the service flexibility, the dynamic distribution of service and propose a set of mechanisms to optimize the performance of this platform. This SCP consists of the platform kernel to control intemal operations, tbe service manager to control all of services, SLPI (Service Logic processing Program Instance) manager to manage each service, and SLPI to handle service interaction. In addition, we propose the Service Creation Environment (SCE) to create easily services on the implemented platfonn and show the example of Call Forwarding service operated on this platform.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.387-394
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• 2019

The purpose of this study is to analyze and identify the strengths of companies selected in each field based on data released by the IOTONE to see if the most influential companies in the industrial Internet of Things are gaining high competitiveness by exercising their capabilities in each field. The industrial Internet of Things is emerging as an essential element in the overall realm of business activity, as well as to make manufacturing factories competitive smart factories. Appropriate platforms should be applied to apply the industrial Internet of Things throughout the enterprise. Globally, many companies are proposing a platform for the industrial Internet of Things. We analyzed the strengths of the most influential companies in each field of connected machines, cybersecurity, analysis platforms, embedded computing, platform connectivity and hardware connectivity in the industrial Internet of Things, and looked at trends such as the current state of operations and the characteristics of the platform.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1688-1696
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• 2020

The paradigm of Internet-of-things(IoT) systems is changing from a cloud-based system to an edge-based system to solve delays caused by network congestion, server overload and security issues due to data transmission. However, edge-based IoT systems have fatal weaknesses such as lack of performance and flexibility due to various limitations. To improve performance, application-specific hardware can be implemented in the edge device, but performance cannot be improved except for specific applications due to a fixed function. This paper introduces a edge-centric metamorphic IoT(mIoT) platform that can use a variety of hardware through on-demand partial reconfiguration despite the limited hardware resources of the edge device, so we can increase the performance and flexibility of the edge device. According to the experimental results, the edge-centric mIoT platform that executes the reconfiguration algorithm at the edge was able to reduce the number of server accesses by up to 82.2% compared to previous studies in which the reconfiguration algorithm was executed on the server.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.65-72
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• 2022

In this paper, a zero trust-based complex biometric authentication was proposed in a passwordless environment. The linkage of FIDO 2.0 (Fast IDENTITY Online) transaction authentication platforms was designed in conjunction with metaverse. In particular, it was applied with the location information of a smart terminal according to a geomagnetic sensor, an accelerator sensor, and biometric information for multi-factor authentication(MFA). At this time, a FIDO transaction authentication platform was presented for adaptive complex authentication with user's environment through complex authentication with secondary authentication based on situational awareness such as illuminance and temperature/humidity. As a result, it is possible to authenticate secondary users based on zero trust with behavior patterns such as fingerprint recognition, iris recognition, face recognition, and voice according to the environment. In addition, it is intended to check the linkage result of the FIDO platform for complex integrated authentication and improve the authentication accuracy of the linkage platform for transaction authentication using FIDO2.0.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.331-337
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• 2022

Smart learning is augmented with digital, context-aware, and adaptable technologies to encourage students to learn better and faster. To ensure that digital learning is successful and that implementation is efficient, it is critical that the dimensions of digital learning are arranged correctly and that interactions between the various elements are merged in an efficient and optimal manner. This paper builds and discusses a basic framework for smart learning in the digital age, aimed to improve students' abilities and performance in learning. The proposed framework consists of five dimensions: Teacher, Technology, Learner, Digital content, and Evaluation. The Teacher and Learner dimensions operate on two levels: (a) an abstract level to fit in knowledge and skills or interpersonal characteristics and (b) a concrete level in the form of digital devices used by teachers and learners. Moreover, this paper proposes asynchronous online course delivery model. An Arabic smart learning platform has been developed, based on these smart learning core dimensions and the asynchronous online course delivery model, because despite the official status of this language in many countries, there is a lack of Arabic platforms to teach Arabic. Moreover, many non-native Arabic speakers around the world have expressed an interest in learning it. The Arabic digital platform consists of over 70 lessons classified into three competence levels: beginner, intermediate, and advanced, delivered by Arabic experts and Arabic linguists from various Arab countries. The five dimensions are described for the Arabic platform in this paper. Learner dimension is the Arabic and non-Arabic speakers, Teacher dimension is Arabic experts and Arabic linguistics, Technology dimension consists of technology for Arabic platform that includes web design, cloud computing, big data, etc. The digital contents dimension consists of web-based video, records, etc. The evaluation dimension consists of Teachers rating, comments, and surveys.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.71-79
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• 2016

As computer technology continues to evolve, the Computational Sciences utilized in Physics, Chemistry, Materials Science, and Life Sciences have been attracting more attention. In Korea, to compensate for the drawbacks in Computational Science, students and researchers have been using the EDISON platform. The EDISON platform provides a web portal service for education and research and an environment for addressing complex issues involving five fields, e.g., Computational Fluid Dynamics (CFD), Nanophysics, Computational Chemistry, Structural Dynamics, and Computational Design. As the platform and user scale increase beyond service provision, the need for efficient operation of its currently running data management system is on the rise. In this study, we resolve the data synchronization issues between the existing EDISON platform and web portal. As the EDISON platform is integrated with the web portal, a file management service is implemented to integrate the management of user data and files, which ultimately improves the overall efficiency of file management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2641-2654
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• 2014

In the smart media environment, magazine industry has been experiencing a transition to ecosystem of value network, which includes high complexity and ambiguity. Using case study method, this article conducts research on digital convergence, the model of magazine ecosystem and adaptation strategy of global magazine companies. Research findings have it that the way of contents production of global magazines has been based on collaborative production system within communities, expert communities, creative users, media contents companies and magazine platform. The system shows different patterns and characteristics depending on magazine-driven platform, Platform-driven platform or user-driven platform. Collaboration system has been confirmed in various cases: Huffington Post and Zinio which collaborate with media contents companies, Amazon magazines and Bookish with magazine companies, Huffington Post and Wired with expert communities, and Flipboard with creative users and communities. Foreign magazine contents diverge into (paper, electronic, app and web magazine) as they start the lively trades of their contents on the magazine platform. In the area of contents uses, readers employ smart media technology effectively such as cloud computing, artificial intelligence and module individualization, making it possible for the virtuous cycle to remain in the relationship within communities, expert communities and creative users.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.123-131
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• 2021

The Fourth Industrial Revolution was triggered by data-driven digital technologies such as AI and big data. There is a rapid movement to expand the scope of data utilization to the privacy area, which was considered only a protected area. Through the revision of the Data 3 Act, laws and systems were established that allow personal information to be freely transferred and utilized under their consent. But, it will be necessary to support the platform that encompasses the entire process from collecting personal information to managing and utilizing it. In this paper, we propose a platform model that can be applied to building mydata ecosystem using personal information. It describes the six essential functional requirements for building MyData platforms and the procedures and methods for implementing them. The six proposed essential features describe consent, sharing/downloading/ receipt of data, data collection and utilization, user authentication, API gateway, and platform services. We also illustrate the case of applying the MyData platform model to real-world, underprivileged mobility support services.