• Journal of Korea Multimedia Society
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• v.19 no.1
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• pp.30-40
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• 2016

Recently, the competition among global IT companies for the market occupancy of the IoT(Internet of Things) is fierce. Internet of Things are all the things and people around the world connected to the Internet, and it is becoming more and more intelligent. In addition, for the purpose of providing users with a customized services to variety of context-awareness, IoT platform and related research have been active area. In this paper, we analyze third party instant messengers of Windows 8 Style UI and propose a digital forensic methodology. And, we are well aware of the Android-based map and navigation applications. What we want to show is GPS information analysis by using the R. In addition, we propose a structured data analysis applying the hierarchical clustering model using GPS data in the digital forensics modules. The proposed model is expected to help support the IOT services and efficient criminal investigation process.

• Genomics & Informatics
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• v.2 no.2
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• pp.99-106
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• 2004

In this paper we introduce PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature. PubMiner employs natural language processing techniques and machine learning based data mining techniques for mining useful biological information such as protein­protein interaction from the massive literature. The system recognizes biological terms such as gene, protein, and enzymes and extracts their interactions described in the document through natural language processing. The extracted interactions are further analyzed with a set of features of each entity that were collected from the related public databases to infer more interactions from the original interactions. An inferred interaction from the interaction analysis and native interaction are provided to the user with the link of literature sources. The performance of entity and interaction extraction was tested with selected MEDLINE abstracts. The evaluation of inference proceeded using the protein interaction data of S. cerevisiae (bakers yeast) from MIPS and SGD.

• Journal of Intelligence and Information Systems
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• v.1 no.1
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• pp.135-148
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• 1995

Neural Networks have been advocated as an alternative to statistical forecasting methods. However, the empirical evidences are not consistent. In the present experiments, multi-layered perceptron (MLP) are adopted as approximator to the time series generating processes. To prevent the MLP from being overfitted to the given time series, the information obtained from ARMA modeling is used to determine the architecture of MLP. The proposed approach was tested empirically using the subsamples of the 111 time series used in the first Markridakis Competition. The forecasting results were analyzed to find out the factors that affect the performance of MLP. The experimental results show that the proposed approach outperforms ARMA models in terms of fitting and forecasting accuracy. In addition, it is found that the use of deseasonalized data improves the forecasting accuracy of MLP.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.208-216
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• 2023

The purpose of our study is to design datasets for Artificial Intelligence learning for cold sea fish farming. Salmon is considered one of the most popular fish species among men and women of all ages, but most supplies depend on imports. Recently, salmon farming, which is rapidly emerging as a specialized industry in Gangwon-do, has attracted attention. Therefore, in order to successfully develop salmon farming, the need to systematically build data related to salmon and salmon farming and use it to develop aquaculture techniques is raised. Meanwhile, the catch of pollack continues to decrease. Efforts should be made to improve the major factors affecting pollack survival based on data, as well as increasing the discharge volume for resource recovery. To this end, it is necessary to systematically collect and analyze data related to pollack catch and ecology to prepare a sustainable resource management strategy. Image data was obtained using CCTV and underwater cameras to establish an intelligent aquaculture strategy for salmon and pollock, which are considered representative fish species in Gangwon-do. Using these data, we built learning data suitable for AI analysis and prediction. Such data construction can be used to develop models for predicting the growth of salmon and pollack, and to develop algorithms for AI services that can predict water temperature, one of the key variables that determine the survival rate of pollack. This in turn will enable intelligent aquaculture and resource management taking into account the ecological characteristics of fish species. These studies look forward to achievements on an important level for sustainable fisheries and fisheries resource management.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.269-276
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• 2015

Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

• Journal of the Korean Home Economics Association
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• v.43 no.12 s.214
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• pp.29-41
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• 2005

The purpose of this study was to define the residents' current uses and satisfaction of a home automation system. The data were collected from 85 residents living in a selected intelligent apartment, from whom 72 were used for the final analysis. The results were as follows: 1) The educational background was the most significant variable affecting differences among the groups in terms of use of the home automation system. 2) Even though the over 50 years age group showed a tendency toward lower technology acceptance, their utilization rates of the home automation system were higher than those of the under 40 years age group. 3) The respondents with dual income showed higher rates of utilization of the home automation system than the single income group. 4) In spite of positive satisfaction level for the home automation system, many improvements were still requested.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.223-229
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• 2008

In this paper. we propose the real-time vision system which judges drowsiness driving based on levels of drivers' fatigue. The proposed system is to prevent traffic accidents by warning the drowsiness and carelessness using face-image analysis and fuzzy logic algorithm. We find the face position and eye areas by using fuzzy skin filter and virtual face model in order to develop the real-time face detection algorithm, and we measure the eye blinking frequency and eye closure duration by using their informations. And then we propose the method for estimating the levels of drivel's fatigue based on measured data by using the fuzzy logic and for deciding whether drowsiness driving is or not. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.63-69
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• 2016

In this paper, we proposed the location tracking system based on MS-Based/Assisted(Mobile Station-Based and Assisted) location trigger service model with context-awareness for the intelligent location tracking of moving objects. It provides the proper resulting value that matches the context of users through the analysis about the situation of the user, physical environment, computing resource and the existing information on user input. In order to provide real-time data, we proposed the location tracking system which realizes the intelligent information such as the expecting arrival time and passing the specific area of the moving object by adopting the location trigger. So, it derives to minimize the costs of communication for the mobile object tracking applications. The proposed location tracking system based on context-awareness can be used for realtime monitoring, intelligent alarm/action, setting up of the optimized moving path, dynamic adjustment of strategies and policies. So it has the advantage to develop the application system which is aimed at optimization of the object tracking and movement.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.878-881
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• 2005

A Stereolithography technology is based on stacking of sliced layer from STL file that is converted from 3-dimensional CAD data. A microstereolithography technology is evolved from conventional stereolithography to fabricate microstructures. In this technology, we have to consider influence of resin flow to make refresh surface. To generate new resin surface, stage has to be moved downward deeply and upward to desired position. At this time, resin flow affects to refresh surface of resin. And resin viscosity is the key factor in simulation of resin flow. By setting optimal refresh time for resin surface, total fabrication time is reduced and there is no damage to fabricated layers. In this research, we simulate resin flow using CFD software and derive optimal stage moving time and dwelling time.

• Korean Journal of Artificial Intelligence
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• v.12 no.3
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• pp.17-24
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• 2024

This study aims to derive a technology development roadmap in related fields by utilizing patent documents of financial technology. To this end, patent documents are extracted by dragging technical keywords from prior research and related reports on financial technology. By applying the TF-IDF (Term Frequency-Inverse Document Frequency) technique in the extracted patent document, which is a text mining technique, to the extracted patent documents, the Latent Dirichlet Allocation (LDA) algorithm was applied to identify the keywords and identify the topics of the core technologies of financial technology. Based on the proportion of topics by year, which is the result of LDA, promising technology fields and convergence fields were identified through trend analysis and similarity analysis between topics. A first-stage technology development roadmap for technology field development and a second-stage technology development roadmap for convergence were derived through network analysis about the technology data-based integrated management system of the high-dimensional payment system using RF and intelligent cards, as well as the security processing methodology for data information and network payment, which are identified financial technology fields. The proposed method can serve as a sufficient reason basis for developing financial technology R&D strategies and technology roadmaps.