• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.975-980
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• 2019

In this paper, we propose a deep learning-based scheduling scheme for user selection in multi-user multi-antenna networks which is considered one of key technologies for the next generation mobile communication systems. We obtained 90,000 data samples from the conventional optimal scheme to train the proposed neural network and verified the trained neural network to check if the trained neural network is over-fitted. Although the proposed neural network-based scheduling algorithm requires considerable complexity and time for training in the initial stage, it does not cause any extra complexity once it has been trained successfully. On the other hand, the conventional optimal scheme continuously requires the same complexity of computations for every scheduling. According to extensive computer-simulations, the proposed deep learning-based scheduling algorithm yields about 88~96% average sum-rates of the conventional scheme for SNRs lower than 10dB, while it can achieve optimal average sum-rates for SNRs higher than 10dB.

• 한국벤처창업학회:학술대회논문집
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• 2018.11a
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• pp.187-192
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• 2018

현재 급변하는 정보기술, 다양성을 추구하는 시장의 니즈, 미리 예측하지 못한 다양한 형태의 경쟁자 등의 출현으로 인해 경영환경이 급변하고 있는 것은 더 이상 새로운 현상이라고 보기는 어렵다. 이와 같이 급변하는 경영 환경은 기업 간 경쟁 심화를 불러일으키고 있으며, 경쟁 심화는 생존 및 발전을 위해 기업 특성에 맞지 않는 무분별한 전략을 활용하면서 오히려 역효과를 내고 있다는 문제를 야기하고 있다. 특히 변화하고 있는 환경 내 벤처기업 및 창업기업들의 경우 창업 후 생존율이 점차 낮아지면서 일반 기업들에 비해 경쟁력을 갖춘 기업을 찾아보기 어려운 것이 현실이다. 이에 벤처기업들은 도태되지 않고 생존하기 위해경쟁력을 강화시킬 수 있는 다양한 전략을 구사하고 있다. 벤처기업은 하나의 비즈니스 생태계 내 유기적 생명체로서 진화하기 위해 제품이나 산업의 수명주기와 마찬가지로 창업기, 초기 성장기, 고도 성장기, 성숙기, 쇠퇴기 등의 정형화된 단계를 거친다. 따라서 벤처기업은 무차별적인 전략을 통해 기업의 생존 및 성장을 도모 하는 것이 아니라 해당 기업이 놓인 수명주기 단계별로 전략, 조직 구조, 의사결정방식, 통제유형 등을 상이하게 판단하고 이에 적절한 전략을 수행해야 한다. 예를 들어, 동일 생산요소를 투입하더라도 이를 적용할 수 있는 지식이 있는 경우 더 높은 가치 창출이 가능(Aghion & Howitt, 1992) 하지만 창업 초창기의 기업은 고도 성장기의 기업보다 보유한 지식 수준 및 경험이 상대적으로 낮기 때문에 다양한 협력을 필요로 한다. 그러나 현재의 여러 선행연구들은 기업이 처한 상황을 고려하지 않은 단편적인 대처 방안이거나 혹은 부분적인 방법론을 제공하는 수준에 그치고 있다는 한계가 있다(이병헌 외, 2014). 따라서 본 연구에서는 '2016년 벤처기업정밀실태조사' 데이터를 기반으로 기업의 외부 협력 정도 및 벤처기업 지원제도 활용 정도가 경쟁력과 성과에 미치는 영향이 기업의 수명주기별로 상이하다고 보고 관련 전략 프레임워크를 제시하고자 한다.

• Membrane Journal
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• v.31 no.5
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• pp.333-342
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• 2021

A flexible electrochromic device (ECD) is a promising technology that is expected to be applied in various fields such as smart windows. Polymer electrolyte is an important component that determines the bleaching-coloration performance and physical stability of flexible ECDs. In this study, a pore-filled polymer electrolyte membrane (PFPEM) with excellent dimensional stability was developed to effectively fabricate flexible ECDs and improve durability. Polyvinyl acetate, which has excellent adhesion, and polyethylene glycol, which can improve ionic conductivity, were filled in the pores of a porous substrate made of polyethylene, which is inexpensive and has excellent physical and chemical stability. The optimal lithium salt (LiTFSI) content of the prepared PFPEM was determined at about 27 wt%, and it was confirmed to possess excellent dimensional stability, adhesive strength, and ion conductivity close to that of conventional polymer electrolytes. Although the visible light transmittance was lowered by the use of the porous substrate, it was expected to act as an advantage in the colored state.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.53-58
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• 2018

MANET transmits data by hop-by-hop method because it is composed of mobile nodes without support of any infrastructure. Its structure is very similar to a block chain. However, it is exposed to various threats such as data tampering or destruction by malicious nodes because of transmission method. So, ensuring the integrity of transmitted data is an important complement to MANET. In this paper, we propose a method to apply the block chain technique in order to protect the reliability value of the nodes consisting the network from malicious nodes. For this, hierarchical structure of a cluster type is used. Only cluster head stores the reliability information of the nodes in a block and then, this can be spread. In addition, we applied block generation difficulty automatic setting technique using the number of nodes selecting cluster head and the reliability of cluster head to prevent the spread of wrong blocks. This can prevent block generation and spread by malicious nodes. The superior performance of the proposed technique can be verified by comparing experiments with the SAODV technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1588-1594
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• 2020

In this paper, we discuss a data balancing method for learning a neural network that generates digital holograms using a deep neural network (DNN). Deep neural networks are based on deep learning (DL) technology and use a generative adversarial network (GAN) series. The fringe pattern, which is the basic unit of a hologram to be created through a deep neural network, has very different data types depending on the hologram plane and the position of the object. However, because the criteria for classifying the data are not clear, an imbalance in the training data may occur. The imbalance of learning data acts as a factor of instability in learning. Therefore, it presents a method for classifying and balancing data for which the classification criteria are not clear. And it shows that learning is stabilized through this.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.179-184
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• 2021

In this study, the conversation behavior of users is investigated by using in-vehicle voice interaction system. The purpose of this study is to identify the elements of conversations that the users expect in voice interactions with systems and present the structural improvements to enable the voice interactions similar to those between people. To observe the users' behavior of voice interaction in the vehicle, the data through contextual inquiry are collected and the interview contents are analyzed by using the open coding. We have been able to explore the usefulness of voice interaction features, which are of great importance in that they increase the user's satisfaction with the features and their usage persistence. This study is meaningful in analyzing the user's empirical needs for the technology of interpersonal model from the perspective of conversation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.5
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• pp.75-85
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• 2002

In using elliptic curves in cryptography, it is important to find a secure elliptic curve. The security of elliptic curve cryptosystem is dependent on the cardinality of the given curve. So, it is necessary to count the number of points of a given elliptic curve to obtain secure curve. It is hewn that when the charateristic is two, the most efficient algorithm finding secure curves is combining the Satoh-FGH algorithm with early-abort strategy$^[1]$. In［1］, the authors wrote that they modified SEA algorithm used in early-abort strategy, but they didn't describe the varaint of SEA algorithm. In this paper, we present some modifications of SEA algorithm and show the result of our implementation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.27-38
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• 2023

In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user's characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate. And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time.

• The Journal of Sustainable Design and Educational Environment Research
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• v.21 no.1
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• pp.24-39
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• 2022

This study was conducted to provide implications so that teachers' voices are heard in the social consensus for future schools by exploring teachers' needs for future school spaces. A qualitative study was performed to listen to teachers' voices directly, and 10 teachers from "A" Elementary School (tentative name) participated in the study. The study 1) recognized the emergence of learning that transcends time and space, and emphasized the importance of an ICT-based informatization environment that can support such learning, 2) confirmed the characteristics of futuristic school spaces centered on "tradition" and "technology," 3) recognized the importance of learning community spaces, 4) emphasized "variable" classrooms for flexible teaching and learning activities, and 5) confirmed the need to introduce eco-friendly elements and provide support for those who may be vulnerable in high-tech learning environments. Finally, the study concluded that teachers need systematic education and experiences that contain sufficient important discourses related to future schools such as "eco-friendliness" and "connection with local communities".

• Membrane Journal
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• v.32 no.5
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• pp.336-347
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• 2022

Reverse electrodialysis (RED) is one of the promising eco-friendly renewable energy technologies which can generate electricity from the concentration difference between seawater and freshwater by using ion-exchange membranes as a diaphragm. The ion-exchange membrane is a key component that determines the performance of RED, and must satisfy requirements such as low electrical resistance, high permselectivity, excellent durability, and low manufacturing cost. In this study, pore-filled anion-exchange membranes were fabricated using porous polymer substrates having various thicknesses and porosity, and the effects of ion-exchange polymer composition and membrane thickness on the power generation performance of RED were investigated. When the electrical resistance of the ion-exchange membrane is sufficiently low, it can be confirmed that the RED power generation performance is mainly influenced by the apparent permselectivity of the membrane. In addition, it was confirmed that the apparent permselectivity of the membranes can be improved through IEC, crosslinking degree, membrane thickness, surface modification, etc., and the optimum condition must be found in consideration of the trade-off relationship with electrical resistance.