• KIPS Transactions on Computer and Communication Systems
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• v.12 no.4
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• pp.127-134
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• 2023

This paper describes how to port the eCos operating system and PROFINET communication stack developed based on gcc to the IAR compiler. The eCos operating system provides basic functions such as multi-thread, TCP/IP, and device driver for PROFINET operation, so there is no need to change it when developing PROFINET applications. Therefore, in this study, we reuse an eCos library built with gcc and it link with PROFINET communication stack that are ported to IAR complier. Due to the different of the gcc and IAR linker, symbol definitions and address of the constructors should be changed using the external tool that generates symbol definitions and address of the constructors from MAP file. In order to verify the proposed method, it was confirmed that the actual I/O was operating normally through PROFINET IRT communication by connecting to the Siemens PLC. IAR compiler has better performance in both the compile time and the size of the generated binary. The proposed method in this study is expected to help port various open sources as well as eCos and PROFINET communication stacks to other compilers.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.3
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• pp.316-327
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• 2007

In this study, a Korean native cattle strain (Hanwoo) evidencing high performance in terms of both meat quality and quantity was employed in the generation of 150,000 BAC clones with an average insert size of 140 kb, and corresponding to about a 6X coverage of bovine chromosomal DNA. The BAC clones were pooled in a mini-scale via three rounds of a pooling protocol, and the efficiency of this pooling protocol was evaluated by testing the accuracy of accessibility to the positive clones, via a PCR-based screening method. Two sets of primers designed from each of two known genes were tested, and each yielded 2 or 3 positive clones for each gene, thereby indicating that the BAC library pooling system was appropriate with regard to the accession of the target BAC clones. Analyses of $3.3{\times}10^6$ base pairs obtained from the 7,090 BAC end sequence (BES) showed that 34.88% of the DNA sequence harbored the repetition sequence. Analysis of the 7,090 BES to the $1^{st}$ and $2^{nd}$ generation radiation hybrid map of the cattle genome, using the COMPASS program designed for the construction of a cattle-human comparative mapping, resulted in the localization of a total of 1,374 clones proximal to 339 $1^{st}$ generation markers, and 1,721 clones proximal to 664 $2^{nd}$ generation markers. Collectively, the BAC library and pooling system of the BAC clones from the Korean cattle, coupled with the chromosome-localized BAC clones, will provide us with novel tools for the excavation of desired clones for genome mapping and sequencing, and will also furnish us with additional information regarding breed differences in cattle.

• Journal of the Korean association of regional geographers
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• v.13 no.3
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• pp.301-320
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• 2007

In Korean academic societies, old maps has not yet been properly investigated in terms of their genealogy, classification, detailed place names, historical backgrounds and the other aspects. With publication of the bibliographies and papers on old maps reserved in museum and library, the scope of research enlarged gradually its scope from 1970s. In 1980s, with the development of theoretical geography, scientific analysis were applied to investigate the projection method of Daedongyeo-jido. The 1990s proved a prominent decade for researches. The photo-copies of old maps enabled researchers to investigate the in-depth comparative study. The more important thing is that old maps became to be powerful instrument in the research of historical geography, such as territorial disputes and marine name(東海). And county old maps compiled by region became to be regional-cultural contents of local areas. Important issues in old map research in Korean academic societies are about Cheonha-do which is unique old world map in Korea, grid-system projection in old county maps and the genealogy of Daedongyeo-jido(manuscript and block print edition). This study shows that bibliography of all old maps preserved in each library and museum should be standardized. This could enable the exchange of information of old maps between institutes. The more important thing is that conciliation of human, social and natural sciences should be applied in the research of old maps.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.775-783
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• 2017

As interest in cloud computing grows, the number of users using cloud computing services is increasing. However, cloud computing technology has been steadily challenged by security concerns. Therefore, various security breaches are springing up to enhance the system security for cloud services users. In particular, research on detection of malicious VM (Virtual Machine) is actively underway through the introspecting virtual machines on the cloud platform. However, memory analysis technology is not used as a monitoring tool in the environments where multiple virtual machines are run on a single server platform due to obstructive monitoring overhead. As a remedy to the challenging issue, we proposes a computationally efficient instance memory introspection scheme to minimize the overhead that occurs in memory dump and monitor it through a partial memory monitoring based on the well-defined kernel memory map library.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1139-1144
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• 2008

In this paper, we propose an automatic generation method of transaction level(TL) model from algorithmic model to verify system specification fast and effectively using virtual platform. The TL virtual platform including structural properties such as timing, synchronization and real-time is one of the effective verification frameworks. However, whenever change system specification or HW/SW mapping, we must rebuild virtual platform and additional design/verification time is required. And the manual description is very time-consuming and error-prone process. To solve these problems, we build TL library which consists of basic components of virtual platform such as CPU, memory, timer. We developed a set of design/verification tools in order to generate a virtual platform automatically. Our tools generate a virtual platform which consists of embedded real-time operating system (RTOS) and hardware components from an algorithmic modeling. And for communication between HW and SW, memory map and device drivers are generated. The effectiveness of our proposed framework has been successfully verified with a Joint Photographic Expert Group (JPEG) and H.264 algorithm. We claim that our approach enables us to generate an application specific virtual platform $100x{\tims}1000x$ faster than manual designs. Also, we can refine an initial platform incrementally to find a better HW/SW mapping. Furthermore, application software can be concurrently designed and optimized as well as RTOS by the generated virtual platform

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.2
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• pp.5-23
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• 2024

The seventh year of implementing online material deposit demands a systematic collection, legal and regulatory improvements, and the establishment of a long-term strategic plan for online material collection. In this study, we aimed to propose an online material collection strategy and a long-term roadmap for preserving online resources as national intellectual and cultural heritage for future generations. To achieve this, we analyzed the status of domestic and foreign libraries, related laws and regulations, and the types and collection status of online materials. Based on this analysis, we proposed practical collection standards and methods. Ultimately, a long-term roadmap and implementation plan were suggested. The long-term development plan for online material collection established a phased, concrete implementation strategy. This includes the foundation-building phase of online material collection, followed by the expansion phase, and finally reaching the maturity phase.

• Journal of Information Management
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• v.34 no.2
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• pp.67-88
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• 2003

There have been increased interests in information visualization. Information visualization has been considered as a way to summarize textual data so that the users can access large amount of data more efficiently and effectively. However, many information visualization techniques stem from scientific visualization techniques, which might be difficult for the regular users to understand. More importantly, the system models used by most of the information visualization techniques do not have real world counterpart. For example, most of the users do not represent or process the textual data in terms of fisheye view or a topological map. This means that there is no affordance on the current information visualization systems from the users point of view. In this paper, we analyzed this problem by using the user interface design principles to point out what lacks in the current information visualization systems. More specifically, we have applied Nielson's Heuristic Evaluation technique to review four representative information visualization techniques. The analysis results confirmed our original hypothesis on why the current information visualization systems are not part of the mainstream information systems. Finally, we suggested to invest more efforts in improving the currently prevalent and familiar bullet list type textual information presentation method based on the usability studies and the intelligent content analysis.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.