• Journal of Information Processing Systems
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• v.17 no.3
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• pp.599-614
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• 2021

This paper proposes a digital signage system based on an intelligent recommendation model. The proposed system consists of a server and an edge. The server manages the data, learns the advertisement recommendation model, and uses the trained advertisement recommendation model to determine the advertisements to be promoted in real time. The advertisement recommendation model provides predictions for various products and probabilities. The purchase index between the product and weather data was extracted and reflected using correlation analysis to improve the accuracy of predicting the probability of purchasing a product. First, the user information and product information are input to a deep neural network as a vector through an embedding process. With this information, the product candidate group generation model reduces the product candidates that can be purchased by a certain user. The advertisement recommendation model uses a wide and deep recommendation model to derive the recommendation list by predicting the probability of purchase for the selected products. Finally, the most suitable advertisements are selected using the predicted probability of purchase for all the users within the advertisement range. The proposed system does not communicate with the server. Therefore, it determines the advertisements using a model trained at the edge. It can also be applied to digital signage that requires immediate response from several users.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.1
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• pp.5-23
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• 2017

The purpose of this study is to analyze media in the elementary moral textbooks with the information processing model and suggest some ways to boost media literacy within the school library. In this study, the three national moral curriculum for the 4th, 5th and 6th elementary students are assayed. As the results of analysis, the inputs of the elementary moral textbooks are bias toward pictures (visual media) and stories (printed media), its' processing focus on investigation and workbooks using the table and its' outputs are based on the writing, speaking and making (creating). But there are so lack of specific activities to achieve relevant information form the media and the reading strategies of visual media as the elements of inputs. The school library should serve various reading materials considering the develop of reading interest, make workbooks for learning strategies according to the text types and try to secure collaborative teaching time to resolve the bias toward media of inputs, increase information processing activities and improve students' media literacy.

• The KIPS Transactions:PartD
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• v.18D no.1
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• pp.67-80
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• 2011

On an automated business document processing system maintaining financial data, errors on query based retrieval of numbers are critical to overall performance and usability of the system. Automatic spelling correction methods have been emerged and have played important role in development of information retrieval system. However scope of the methods was limited to the symbols, for example alphabetic letter strings, which can be reserved in the form of trainable templates or custom dictionary. On the other hand, numbers, a sequence of digits, are not the objects that can be reserved into a dictionary but a pure markov sequence. In this paper we proposed a new OCR model for spelling correction for numbers using the multiple streams and the context based correction on top of probabilistic information retrieval framework. We implemented the proposed error correction model as a sub-module and integrated into an existing automated invoice document processing system. We also presented the comparative test results that indicated significant enhancement of overall precision of the system by our model.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.3
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• pp.74-80
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• 2002

There are many researches on post-processing methods for the Korean continuous speech recognition enhancement using natural language processing techniques. It is very difficult to use a formal morphological analyzer for improving the speech recognition because the analysis technique of natural language processing is mainly for formal written languages. In this paper, we propose a speech recognition enhancement model using syntactic unit of morphemes. This approach uses the functional word level longest match which dose not consider spacing words. We describe the post-processing mechanism for the improving speech recognition by using proposed model which uses the relationship of phonological structure information between predicates md auxiliary predicates or bound nouns that are frequently occurred in Korean sentences.

• Journal of Biomedical Engineering Research
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• v.2 no.2
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• pp.127-140
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• 1981

This paper describes the mechanism of information processing in the nervous system through neuron pool model which is consisted of six single neural models. In the neuron pool model, summation characteristic of stimulus satisfies those of real nervous system and output impulse rate increases linearly to the input stimulus. Occlusion phenomena of the neuron pool model is approached to those of real nervous system and also if the threshold potential within sutlirninal fringe is increased, facilitation phenomena appreared. Therefore, the results of this study suggest that we can construct large neuron pool with many single neural models and verify the mechanism of information processing in the wide part of nervous system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.193-198
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• 2001

In the large scale B2B transaction like buying Express-Train or selling Daewoo Motor, a tremendous amount of variables and factors of chaos functionate in it directly or indirectly. To get effective information processing on the so called complex system like this, it should be possible to unite the global insight power of the human being and the local computing power of the machine. In this paper, we suggested a union model of human being and machine using Hugent concept. Hugent is defined as an agent model which allows us to chemically unite the human's component and the machine's component in terms of information processing. In this paper, we showed that some typical problems contained in the complex system can be treated more easily through the suggested Hugent concept.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.487-498
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• 2018

The purpose of the high-speed railway construction is to better satisfy passenger travel demands. Accordingly, the design of the train working plan must also take a full account of the interests of passengers. Aiming at problems, such as the complex transport organization and different speed trains coexisting, combined with the existing research on the train working plan optimization model, the multiobjective bi-level programming model of the high-speed railway passenger train working plan was established. This model considers the interests of passengers as the center and also takes into account the interests of railway transport enterprises. Specifically, passenger travel cost and travel time minimizations are both considered as the objectives of upper-level programming, whereas railway enterprise profit maximization is regarded as the objective of the lower-level programming. The model solution algorithm based on genetic algorithm was proposed. Through an example analysis, the feasibility and rationality of the model and algorithm were proved.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.159-172
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• 2022

The role of the interconnect network, which connects computing nodes to each other, is important in high-performance computing (HPC) systems. In recent years, the peripheral component interconnect express (PCIe) has become a promising interface as an interconnection network for high-performance and cost-effective HPC systems having the features of non-transparent bridge (NTB) technologies. OpenSHMEM is a programming model for distributed shared memory that supports a partitioned global address space (PGAS). Currently, little work has been done to develop the OpenSHMEM library for PCIe-interconnected HPC systems. This paper introduces a prototype implementation of the OpenSHMEM library through a switchless interconnect network using PCIe NTB to provide a PGAS programming model. In particular, multi-interrupt, multi-thread-based data transfer over the OpenSHMEM shared memory model is applied at the implementation level to reduce the latency and increase the throughput of the switchless ring network system. The implemented OpenSHMEM programming model over the PCIe NTB switchless interconnection network provides a feasible, cost-effective HPC system with a PGAS programming model.

• Journal of Science Education
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• v.44 no.1
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• pp.84-91
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• 2020

In this study, we investigated the elements of knowledge and information processing competence of science inquiry activities in grades 3-6 science textbooks. For this purpose, the elements of knowledge and information processing competence were extracted and a framework for analysis was created. Analysis of eight science textbooks for grades 3-6 in elementary school was carried out using the analysis framework. The following results were obtained by the analysis framework: First, we divided the knowledge and information processing competence into five elements: 'collection,' 'analysis,' 'expression,' 'selection,' and 'evaluation.' Second, the elements of knowledge and information processing competence of science inquiry activity of elementary science textbooks were not evenly composed. The science inquiry activities of elementary science textbooks focused on 'collection' and 'analysis' among the five elements of the knowledge and information processing competence, followed by 'expression,' 'selection,' and 'evaluation.' As a result, we found that a science inquiry model or a science instruction model is needed to develop the knowledge and information processing competence in elementary school science curriculum.