• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1396-1412
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• 2023

Conversation modeling is an important and challenging task in the field of natural language processing because it is a key component promoting the development of automated humanmachine conversation. Most recent research concerning conversation modeling focuses only on the current utterance (considered as the current question) to generate a response, and thus fails to capture the conversation's logic from its beginning. Some studies concatenate the current question with previous conversation sentences and use it as input for response generation. Another approach is to use an encoder to store all previous utterances. Each time a new question is encountered, the encoder is updated and used to generate the response. Our approach in this paper differs from previous studies in that we explicitly separate the encoding of the question from the encoding of its context. This results in different encoding models for the question and the context, capturing the specificity of each. In this way, we have access to the entire context when generating the response. To this end, we propose a deep neural network-based model, called the Context Model, to encode previous utterances' information and combine it with the current question. This approach satisfies the need for context information while keeping the different roles of the current question and its context separate while generating a response. We investigate two approaches for representing the context: Long short-term memory and Convolutional neural network. Experiments show that our Context Model outperforms a baseline model on both ConvAI2 Dataset and a collected dataset of conversational English.

• The Korea Genome Conference
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• 2006.09a
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• pp.42-42
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• 2006

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1214-1221
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• 2007

Ad-hoc network is soft wireless communication network that is consisted of mobile node and clusters without helping of infrastructure. We propose a new ad hoc multicast routing protocol for based on the ontology scheme called inference network. Ontology knowledge-based is one of the structure of context-aware. Proposed structure is consisted of context awareness parameters as like distance between each nodes. The proposed architecture performs two types of routing discovery. One is Flooding Discovery Routing(FDR) for comparing analysis step and Local Discovery Routing(LDR) to compose path of node forecast(preservation) step from node's state value. The inference network structure of proposed RODMRP(Resilient Ontology-based Dynamic Multicast Routing Protocol) adopts a tree structure to enhance an efficient packet in various environment between mobile node. We will have developed an algorithm that will desist multi-hierarchy Layered networks to simulate a desired system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.127-135
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• 2015

Context-aware mobile cloud computing is a new promising paradigm that allows to improve user experience by analyzing contextual information such as user location, time of the day, neighboring devices and current activity. In this paper we provide performance study of context-aware mobile cloud computing system with Volare middleware. Volare monitors the resources and context of the device. and dynamically adapts cloud service requests accordingly, at discovery time or at runtime. This approach allows for more resource-efficient and reliable cloud service discovery, as well as significant cost savings at runtime. We also have studied the performance of context-aware mobile cloud computing for different quality of service (QoS) adaptation policies. Our simulations results show that when battery level is low and CPU usage is high and user cannot maintain the initial QoS, service cost is decreased according to current adaptation policy. In conclusion, the current adaptation policy suggested in this paper may improve user experience by providing a dynamically adapted service cost according to a situation.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.281-288
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• 2017

In Smart-cities, various types of integrated services must be linked to provide services to applications. Therefore, flexibility must be ensured between services so that various services can be efficiently provided. In order to secure the flexibility among services, it is very important to have a function to dynamically discover and invoke a desired service by searching for a semantic service by reflecting a recognized context through real-time context-aware in smart-cities. To date, quite a number of semantic service discovery techniques have been developed. However, they have not been verified as suitable for use in the smart-city domain. In this study, we tried to verify the existing ones to use a suitable one. We tested most of existing semantic service discovery techniques, but we found that none of them is suitable to our research. Therefore, we developed our own semantic service discovery technique. This paper introduces our work and presents the performance evaluation results that demonstrate that our developed works well and show good performance. For the performance evaluation, the experimental system was actually constructed and the real performance was measured. In the experiment, we implemented the semantic service discovery scenario that dynamically searches and calls the services needed to provide fire accident management services in smart cities.

• Journal for History of Mathematics
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• v.16 no.2
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• pp.55-70
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• 2003

This study investigated tile intuitive level of justification in geometry, as the former step to the aximatization, with concrete examples. First, we analyze limitations that the axiomatic method has in tile context of discovery and the educational situation. This limitations can be supplemented by the proper use of the intuitive method. Then, using the histo-genetic analysis, this study shows the process of the development of geometrical thought consists of experimental, intuitive, and axiomatic steps. The intuitive method of proof which is free from the rigorous axiom has an advantage that can include the context of discovery. Finally, this paper presents the issue of intuitive proving that the three angles of an arbitrary triangle amount to 180$^{\circ}$, as an example of the local systematization.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.367-369
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• 2005

현재의 컴퓨팅 환경은 수많은 센서와 컴퓨팅 디바이스에서 사용자와 주위 환경에 대한 상황 정보를 생성하고 있다. 이러한 상황정보는 무선 네트워크와의 결합을 통하여 정보가 필요한 서비스로 전달되어 사용자에게 더욱 지능화된 서비스를 제공하는 방향으로 발전하고 있다. 이러한 환경에서 서비스는 주변에 존재하는 상황정보 제공자를 검색하여 상황정보를 제공받을 수 있어야 한다. 수많은 상황정보 정보제공자가 무선 네트워크를 통하여 상황정보를 제공하는 환경에서 필요한 상황정보 제공자를 찾고 상황정보를 전송하는 효율적인 프로토콜이 필요하다. 본 논문에서는 모바일 무선 네트워크에 적합한 상황정보 제공자의 검색과 상황정보 전송을 위한 상황정보 발견 프로토콜(Context Discovery Protocol)을 디자인하였다.

• Journal of the HCI Society of Korea
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• v.8 no.1
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• pp.11-17
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• 2013

Context aware systems are those systems that are aware about the environment and perform productive functions automatically by reducing human computer interactions(HCI). In this paper, we present common architecture principles of context-aware systems to explain the important aspects of context aware systems. Our study focuses on identifying common concepts in pervasive computing approaches, which allows us to devise common architecture principles that may be shared by many systems. The principles consists of context sensing, context modeling, context reasoning, context processing, communication modelling and resource discovery. Such an architecture style can support high degree of reusability among systems and allows for design flexibility, extensibility and adaptability among components that are independent of each other. We also propose a new architecture based on broker-centric middleware and using ontology reasoning mechanism together with an effective behavior based context agent that would be suitable for the design of context-aware architectures in future systems. We have evaluated the proposed architecture based on the design principles and have done an analyses on the different elements in context aware computing based on the presented system.

• Fashion & Textile Research Journal
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• v.25 no.1
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• pp.41-51
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• 2023

This study attempted to analyze the context characteristics and consumer characteristics that affect fashion curation shopping. The data used for this study were 223 questionnaires targeting male and female college students in their 20s in Busan and South Gyeongsang Province who had had the curated shopping experience in the latest three months. The SPSS program was used for the data analysis, and a reliability measurement, factor analysis, multiple regression analysis, T-test, and one-way ANOVA were conducted. The results were as follows. First, fashion curation shopping exhibited three factors: product subscription, marketing use, and product recommendation shopping. Furthermore, the context characteristics had sub concepts of five factors: selection, sharing, experience, discovery, and storage. Second, the context characteristics (selection, sharing, experience, discovery, and storage) had a significant influence on product subscription, marketing use, and product recommendation, which belong to the curation shopping category. Third, the fashion consumers' price sensitivity, trend sensitivity, and product knowledge had a deep impact on the marketing use and product recommendation. Fourth, there was no difference in the fashion curation shopping by male and female consumers and the average monthly fashion shopping frequency, and there were differences in shopping cost and time. This study can analyze the context and consumer characteristics that affect fashion curation shopping to establish an efficient fashion curation shopping system in practical terms. Additionally, academically, it can be proposed as basic data on the development of measurement tools for analyzing consumer behavior that prefers fashion curation shopping.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.39-40
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• 2000

Knowledge discovery has attracted increased attention in the biomedical industry in recent years is due to the increased availability of huge amount of biomedical data and the imminent need to turn such data into useful information and knowledge. In this talk, we discuss knowledge discovery techniques for gene expression analysis and MHC-peptide binding prediction in the context of discovering protein antigens and hot spots in these antigens.