• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.669-678
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• 2013

Recently, because the portable devices became popular, it is easily to see that each person carries more than just one portable device and the use of the smartphone stretches as time goes by. After the smartphone has propagated rapidly, the total usage of the smartphone applications has also increased. But still, each application store has a different platform to develop and to apply an application. The application store is divided into two big markets, the Android and the Apple. So the developers have to develop their application by using these two different platforms. Developing into two different platforms almost makes a double development cost. And for the other platforms, the weakness is, which still have a small market breadth like Bada is not about the cost, but about drawing the proper developers for the given platform application development. The web application is rising up as the solution to solve these problems, reducing the cost and time in developing applications for every platform. For web applications don't need to make a vassal relationship with application markets platform. Which makes it possible for an application to operate properly in every portable devices and reduces the time and cost in developing. Therefore, all of the application markets could be united into one big market through a protocol which will connect each web applications market. But, still there is no standard for the web application store and no current web application store is possible to interlock with other web application stores. In this paper, we are trying to suggest a protocol by developing a prototype and prove that this protocol can supplement the current weakness.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.35-42
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• 2013

Developing English-Korean machine translation system requires the construction of information about the languages, and the amount of information in English-Korean transfer dictionary is especially critical to the translation quality. Newly created words are out-of-vocabulary words and they appear as they are in the translated sentence, which decreases the translation quality. Also, compound nouns make lexical and syntactic analysis complex and it is difficult to accurately translate compound nouns due to the lack of information in the transfer dictionary. In order to improve the translation quality of English-Korean machine translation, we must continuously expand the information of the English-Korean transfer dictionary by collecting the out-of-vocabulary words and the compound nouns frequently used. This paper proposes a method for expanding of the transfer dictionary, which consists of constructing corpus from internet newspapers, extracting the words which are not in the existing dictionary and the frequently used compound nouns, attaching meaning to the extracted words, and integrating with the transfer dictionary. We also develop the tool supporting the expansion of the transfer dictionary. The expansion of the dictionary information is critical to improving the machine translation system but requires much human efforts. The developed tool can be useful for continuously expanding the transfer dictionary, and so it is expected to contribute to enhancing the translation quality.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.187-194
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• 2013

Recently, there have been many trials to analyze characteristics of research trends through a structural analysis of keyword networks in various fields. However, most previous studies have mainly focused on structural analysis harbored in some static networks and there is a lack of research on changes of such networks structure with time. In this paper, we constructed annual keyword networks by using a database of papers published in the international computer engineering-field journals from 2002 through 2011, and examined the changes of them. As a result, it was shown that most keywords in a network are preserved in the network of the next year, and their degree of connectivity and the average weight of the connections were higher and smaller, respectively, than those of the keywords which are not preserved. In addition, when a keyword network shifted to one of the next year, the connections between keywords were more likely to be removed than preserved, and the average weight of the removal connections was higher than that of the preserved ones. These results imply that the keywords are not changed over time but their connections are very likely to be changed; and there is apparent differences between the preserved and removal groups of keywords/connections with respect to degree and weights of connections. All these results are consistently observed over the ten-year datasets and they can be important principles in understanding the structural changes of the keyword networks.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.355-362
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• 2019

In the past, when research and development(R&D) resources were absolutely scarce, the so-called 'choice and concentration' strategy of national R&D projects has been persuasive. Under the current situation where various actors such as GRIs(Government-funded Research Institutes) and universities supported by more abundant R&D resources conduct national R&D projects, this strategy cannot be applied without distinction. In order to see how the strategy has worked, this paper analyzes the concentration of research funds allocated to actors performing national R&D projects. Concentration is measured based on the amount of research funds supported by government from 2002 to 2016 using the Theil index to break down the concentration of individual actors in the overall national R&D project. The results from the Theil index were compared with concentrations using the Gini coefficient, a widely known indicator. As a result, the Theil index could be used to analyze the concentration and sub-components' contribution such as universities and GRIs that make up the entire national R&D system. The results also showed GRIs had the highest concentration, followed by universities, but their concentration has been somewhat reduced compared to 10 years ago. On the other hand, small-sized companies have maintained a certain level, although they are not highly concentrated. In other words, universities and GRIs tend to reduce the gap in the allocation of research funds among institutions, while small-sized companies tend to distribute them evenly.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.1-12
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• 2019

In this paper, it was found that most of the machinery facilities problems generated by clients could be prevented in advance by systematically managing the mechanical equipment production process of small and medium enterprises (SMEs) that produce machinery facilities. Major point of this process is to establish an operating system that corresponds to reality of facility manufacturers as it represents 63% of machinery facilities problems that occur in customers and is a task that needs to be solved most intensively. Technical issues account for 23% of machinery facilities problems occurring at the client's companies and should be approached from a long-term perspective as they are directly related to the technical capabilities of the manufacturers. Organizational problems account for 14% of machinery facilities problems occurring in customer companies, and can change depending on the relationship of members and the nature of the human being, such as morality and motivation. In addition, we propose the establishment of an Internet-based production process management platform for smooth and efficient transfer of information between customers and machinery facilities manufacturers.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.317-322
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• 2019

Programming judge systems for programming training support are typically built on the Web, where the examiners uploads a programming problem, which the student reads and submits an answer to the problem. The judge system executes the submitted answer of source code to provide feedback such as pass, failure, and error messages. Students who receive the feedback except for the pass continues debugging the source code until they are judged to pass. We developed an online judge system to support programming training and analyzed answers submitted by the students and found that many of the students who were not judged to pass that test did not know exactly where they were wrong but continued to solve the problem. The current judge system generally feeds runtime error messages back to students. However, with only runtime error message, it is difficult for student who train to find the wrong part of the answer. Therefore, in this paper, we propose a system that provides the feedback of programming failure by analyzing the control flow of the test cases used in the source code submitted by the student. The proposed system helps students find the wrong parts more quickly by feeding back the paths where faults in the control flow may exist. In addition, we show that this system is applicable to the answer source code that the actual student submitted.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.79-88
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• 2019

Machine translation (MT) system, especially Korean-Mongolian MT system, has recently attracted much attention due to its necessary for the globalization generation. Korean and Mongolian have the same sentence structure SOV and the arbitrarily changing of their words order does not change the meaning of sentences due to postpositional particles. The particles that are attached behind words to indicate their grammatical relationship to the clause or make them more specific in meaning. Hence, the particles play an important role in the translation between Korean and Mongolian. However, one Korean particle can be translated into several Mongolian particles. This is a major issue of the Korean-Mongolian MT systems. In this paper, to address this issue, we propose a method to use the combination of UTagger and a Korean-Mongolian particles table. UTagger is a system that can analyze morphologies, tag POS, and disambiguate homographs for Korean texts. The Korean-Mongolian particles table was manually constructed for matching Korean particles with those of Mongolian. The experiment on the test set extracted from the National Institute of Korean Language's Korean-Mongolian Learner's Dictionary shows that our method achieved the accuracy of 88.38% and it improved the result of using only UTagger by 41.48%.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.213-222
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• 2019

Determining the meaning of a keyword in a speech dialogue system is an important technology for the future implementation of an intelligent speech dialogue interface. After extracting keywords to grasp intention from user's utterance, the intention of utterance is determined by using the semantic mark of keyword. One keyword can have several semantic marks, and we regard the task of attaching the correct semantic mark to the user's intentions on these keyword as a problem of word sense disambiguation. In this study, about 23% of all keywords in the corpus is manually tagged to build a semantic mark dictionary, a synonym dictionary, and a context vector dictionary, and then the remaining 77% of all keywords is automatically tagged. The semantic mark of a keyword is determined by calculating the context vector similarity from the context vector dictionary. For an unregistered keyword, the semantic mark of the most similar keyword is attached using a synonym dictionary. We compare the performance of the system with manually constructed training set and semi-automatically expanded training set by selecting 3 high-frequency keywords and 3 low-frequency keywords in the corpus. In experiments, we obtained accuracy of 54.4% with manually constructed training set and 50.0% with semi-automatically expanded training set.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.195-200
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• 2021

Due to the development of video sharing platforms, the amount of video uploads is exploding. Such videos often include various types of music, among which cover songs are included. In order to protect the copyright of music, an algorithm to find the original song of the cover song is essential. However, it is not easy to find the original song because the cover song is a modification of the composition, speed and overall structure of the original song. So far, there is no known effective algorithm for searching the original song of the cover song. In this paper, we propose an algorithm for searching the original song of the cover song using the inflection points of the melody line. Inflection points represent the characteristic points of change in the melody sequence. The proposed algorithm compares the original song and the cover song using the sequence of inflection points for the representative phrase of the original song. Since the characteristics of the representative phrase are used, even if the cover song is a song made by modifying the overall composition of the song, the algorithm's search performance is excellent. Also, since the proposed algorithm uses only the features of the inflection point sequence, the memory usage is very low. The efficiency of the algorithm was verified through performance evaluation.