KJC Korea
Journal Central

This paper presents the model of realizing requirement to ensure the QCD(Quality Cost Delivery) of medical software during the development cycle. In many cases, customer needs are likely to change in the process of carrying out projects. When medical software is released to customers without the needs to be reflected, many more defects can be found when the software is actually used in the medical field. The defects are fatal in the medical domain. To solve these problems, GQM(Goal Question Metric) methodology is used. With this methodology, goals are set, questionnaires are devised, and review of domain expert is sought. In addition, requirements are extracted and defined. And then, test cases are finally completed based on the requirements. The test cases made through these processes are quantitatively prioritized by using the AHP(Analytic Hierarchy Process) methodology. Once the priority is determined, the test case is configured in order to determine how the test case has been carried out in accordance with the number of test cases. It is possible to digitize the quality of software before it is delivered to the customers to see whether enough tests are officially performed for the project. Using this TQM, it is expected that the level of software quality is determined while the project is being carried out, instead of evaluating the software at the end of the project.

In this study, to observe the effect of olfactory fragrance stimuli on physiological change due to auditory stimuli by frequency, EEG test and ECG were conducted. As auditory stimuli by frequency, car horn(473Hz), ambulance siren(1,653Hz), and symphony(308Hz) of with about 85dB were presented in the conditions of no fragrance and Lavender fragrance for about 5 minutes. As for analysis method, two-way ANOVA based on olfactory fragrance stimuli and auditory stimuli was implemented. As a result of analysis, when interaction was observed in olfactory fragrance stimuli and auditory stimuli, one-way ANOVA about olfactory stimuli on the auditory stimuli was conducted. As a result of analysis, in α-wave, compared with control condition, Lavender fragrance increased, showing a significant difference(p<0.01) in siren. In LF, compared with control condition, Lavender fragrance increased, showing a significant difference(p<0.01), and compared with control condition and symphony, horn and siren increased, showing a significant difference(p<0.01). In HF, compared with no fragrance, Lavender fragrance increased, showing a significant difference(p<0.01) in control condition, symphony, and siren except for horn. In LF/HF ratio, compared with no fragrance, Lavender fragrance decreased, showing a significant difference(p<0.01) in horn condition, however, compared with no fragrance, it increased, showing a significant difference(p<0.01) in siren condition. In conclusion, it is considered that Lavender fragrance works positively and negatively, depending on the kinds of auditory stimuli.

In generally, time-lapse Images contains severe shaking phenomena according to the long time shooting period. Time-lapse videos were composed of multitude shooting image list and easily contained several shooting noise. The image shaking problems are based on the trembling movement of the camera supporting pore, strong wind, and so on. In this paper, we proposed a new image processing algorithm to solve the shaking problems of time-lapse video. Our algorithm is designed based on simple computation logic and comparison rules. For the reasons, our proposed algorithm is particularly appropriate for time-lapse photography. The algorithm was consisted of three steps. In the first step, we classified the image shaking type obtained from time-lapse video. In the second step, we computed the shaking degree values of input image list. Last, we reformed the all frames of time-lapse video to the new one according to the computed shaking values of the previous steps. we installed a remote camera shooting system for the stabilization experimental of time-lapse video. In results, we could confirm that our proposed algorithm could correct the shaking problem of time-lapse video. And we could obtain the experimental data that our proposed program was more efficient for vertical movement transition and rotation movement of shooting images. In the time measuring simulation we can confirmed that our program is more applicable to the area of real-time timelapse video photography.

Information Technology is played an important role for improving soldier capability like shooting practice in case of national defense field. To develop automative system for detecting and measuring shell crater and its management system, a low cost image processing system and Cloud computing system were applied in this paper. The image processing system was made by using general hardware and open source, OpenCV, and it could be removed noise in input processing by using infrared rays camera and infrared rays light source. And Arduino open source hardware and software was used for calculation collision time between target and projectile. The management system of detected data was developed, analyzed and tested for individual shooting skills data by using a cloud-based Web. The performance of proposed system was proved by measurement accuracy, measurement time and retrieved time, and comparison with other systems. This system is expected to be utilized in many IT areas as defense research. And it can be expected to upgrade defense system by low cost because it consists with general hardware and open source.

Modern database systems use different methods from traditional database processing systems. Since more and more different types of data need to be stored, modern database systems have become more important to efficiently process big data through distributed processing and system scalability. This importance will continue to grow. For this reason, databases for big data processing are being studied and developed in a service that continuously deals with big data such as search engines and SNS services. In particular, the key-value database model has advantages of fast I / O and scalability. Therefore, it is suitable for big data processing and it is used as a system of various applications. Also, studies on key-value databases have been actively conducted in big data researches, because other big data database models also share the characteristics of the key-value database model and borrow many of the techniques used in the key-value database model. However, there are some areas that can further improve the key-value database such as optimization research, next-generation storage. In this paper, we define the key-value database that emerged as a hot topic in the big data platform field, list the related technologies and platforms being studied, and present a methodology to complement existing platforms.

This study is to build an instructional strategy ontology to aid the effective design of a Teaching-Learning plan for novice designers who lack instructional design knowledge. Most of designer tend to represent ambiguously the instructional strategy. Therefore they need to provide fluently learning procedures and activities to achieve the learning goals. The Instructional model was selected as a direct instructional model that is appropriate for learning computer skills and is used widely in computer education field. This study constructed instructional strategy ontology for direct instruction model using ontology authoring tools. The study proposes a method for designing a Teaching-Learning plan in addition to analysis effects through the questionnaire. This method uses instructional strategy ontology of direct instruction model that was built by the author. The instructional ontology can be shared and reused among the designers. The proposed method made a Teaching-Learning plan that could describe teacher’ and learner’s activities concretely by decomposed instructional strategy. Finally, it made a Teaching-Learning plan with fluent content using instructional strategy ontology for novice designers. Moreover, it supports a balanced design considering the overall structure through the visual interface. However, we have limitations as this study proposes the only design method for Teaching-Learning plan using instructional strategy ontology. In the future, we will need further researches to support the automatic design of Teaching-Learning plan with intelligent facilities.

KOIN (Korean medicine 人, http://www.koin.re.kr) is a Korean medicine knowledge portal developed for users who are interested in Korean medicine to share relevant information. The purpose of the present study is to seek methods for advancing the quality of the contents and services of KOIN to secure future users of the portal services before fully initiating the KOIN service. The crowd testing method was applied to test the functionality and usability of the current KOIN service, and domestic and international websites providing similar services were investigated and analyzed. About 150 errors were found in this functional testing procedure, but the identified functional problems were all corrected. An average score of 3.33 was calculated in the usability test, in which the reliability and the playfulness showed the highest and lowest score, respectively. We in this paper surveyed the 15 relevant websites with respect to KOIN in the traditional medicine and the modern medicine fields. The strengths and weaknesses of similar websites were analyzed to improve the KOIN services. In particular, it is shown that the evidence-based Korean medicine knowledge is KOIN’s biggest strength. Users’ needs and demand for the KOIN services will be continuously gathered to provide the Korean medicine knowledge services that the users require.

Even experienced pilot, lack of energy recognition and management would lead to critical condition and fatal accident. The pilot should require aware of energy status of each flight phase and learning energy management. Basically, law of energy conservation on real flight maintains different way such as potential as a height, kinetic as a velocity and dissipation energy from chemical energy. In this study, it is shown the energy equations caused from energy status such as climb, decent, acceleration and deceleration for knowledge-based training. In order to understand how pilots can manage energy state on real flight, flight trajectories are displayed using the flowchart that explains the energy state of each flight phase. Also it is shown and compared with flight strategy single-input single-output and Multi-Input Multi-Output strategy using energy matrix. Multi-Input Multi-Output strategy helps student pilots to understand the energy management on knowledge-based training, it is explored the use of Work Domain Analysis of energy management. In order to provide a new way for effective flight training, skill-based and knowledge-based training program structures are designed using by abstraction hierarchy. Each training program structure based on whole-part is reclassified as structure based on goal–means domain analysis. This study shows that it is made the subject contents of the energy management which will be included in new curriculum for flight training, also each program structure of whole-part has been reclassified as structural goal-means.

South Korea is already positioning itself as the world-class IT power through rapid growth of information and communication technology and the government's policy. Internet use by young people is increasing rapidly. Internet usage is a situation that is close to 100%. Internet use is increasing due to the development of information and communication technologies, but has a serious problem, such as a social privacy, hacking and viruses etc. To minimize the side effects by use of the Internet frequency increase is desired the way, but it is necessary to recognize. To solve this problem, it is necessary to recognize the media-user, among other things, that their personal information to protect. The purpose of this study is to analyze about informations use and Informations recognition of media users and to propose appropriate methods. According to the analyze, respondents should like to disclose others personal information - Date of birth, education, experience, current membership, activities and publishing information(text, photos, videos, etc.), but his or her own personal information did not want to be released. We don't want our own privacy to be released. But we wonder other people's personal information. It is not unrelated with voyeurism of our society. There is a controversy for generalizing this results of the research. Because We were supposed to investigate a university student organization. There is meaning at point of group's result, which utilizes the media well and using media. We expand the subject of research in subsequent studies. In following research, will analyze whether there is difference about the personal information application and awareness according to an age. So, the customized personal information protection education wishes to be accomplished.

We are effectively utilized to practice in the field of sports. The maintenance of correct posture in sports is important role in protecting the body from injury, as well as enhancing the strength of your game. Especially, golf putting requires much more accurate and correct posture than other sports. This allows for the ability to achieve the desired power and stable exercise abilities. In golf putting, our head plays a very important role. It is known that the rotating axis can not be shaken, raising the consistency and accuracy of golf the putting. In this thesis, we designed a correcting device that would give him the value as the head of the movement fell forward, it suggested how to produce the PCB. For this purpose, it describes the key features that need to be equipped with the device, The measures and algorithms were proposed to measure motion of head. The posture correcting device suggested by this paper is that certain body parts can be applied to good performance only if they are fixed. This device can be used not only for golf but also for archery and shooting. In the future, we intend to develop applications that work with these devices to increase usability.

Today’s companies are in an environment where they have to survive in ever-increasing competition in the industry, by constantly identifying changes and trends in their industries and by periodically reflecting them in their policies and product development. For this purpose, one of the tasks that should be carried out is the analysis of industrial information. Most companies acquire industry analytical information at the cost of a large amount of time, manpower or, with the help of external professional analysts. However, since this conventional method is a somewhat heuristic and qualitative approach. The quality of these analysis results are different each time. A huge amount of industry related information is produced online in real time and when the information is reflected in the analysis as much as possible, it is required to introduce a new analytical method. In this paper, we propose a text mining methodology that extracts information from large amount of source data and automatically classifies it into each category of industry analysis framework. By constructing a sentence classifier using feature selection technique based on machine learning method, information that can be classified by indicators of universally used industry analysis framework is collected in sentence form. We performed PEST and polarity analysis by using our system and evaluated the classification accuracy of the proposed system through experiments.

As smart phones become more integrated in classrooms because of its mobility, accessibility, scalability, and speediness, researchers are looking for new ways to apply them to the learning process. The education applications can help automate current classroom processes or present new ways to learn that previously had been unexplored. Recently, the spread of smart phones, mobile applications to help you learn English faster is being developed actively. However, the existing mobile English learning apps did not effectively connected with the contents of the course. Also, this study of mobile English learning applications are still insufficient. Therefore, this study investigated the possibility of curriculum-connected experience learning based on a mobile device by developing and designing a mobile application program for the Middle School English Language using a location-based service, augmented reality technology based on smart phones. In order to evaluate the performance of the proposed apps, we have measured the precision and usability. As results of experiments, it were obtained significant results. The precision of learning contents is 88% and ‘Match between system and the real world’, ‘Recognition rather than recall’, ‘User control and freedom’, ‘Aesthetic and minimalist design’ appeared to be respectively 3.81, 3.84, 4.02, 40.05 in evaluation of usability.

Security has become an essential part of the software development process. However, previous researches have not adequately integrated the security properties and policies into the development process systematically covering entirely from an early business model to a software model. This, in turn, makes it difficult to create the application models that combine the functional models and the security models. To support the development of the applications that reflects the security properties and policies, this study proposes a hierarchical modeling approach that integrates the metamodel, the framework, and the process based on the degree of abstraction of the development so as to meet the functional (business) and security requirements of the systems. This study aims to establish a framework and process for integrated modeling of the functional and security (non-functional) design aspects necessary to develop applications. The process of integrated modeling ranging from the business modeling to the software modeling is described following the development phases. With the proposed method, reliable systems can be developed by modeling the application systems more clearly based on the integrated method to meet the functional and security requirements.

As the number of electronic documents explosively increases, it becomes more and more difficult to retrieve information from them rapidly and accurately. To solve this problem, documents are clustered in various ways and generally K-Means algorithm is used to achieve it. K-Means algorithm is adequate to cluster so many documents rapidly and easily, but it does not consider the meaning of documents on clustering. In this research, we propose a document clustering technique of using meaning-based paragraphs. The proposed technique divides documents in a document set into meaning-based paragraphs by measuring similarity between sentences, chooses representative paragraphs having the maximum coherence value from each document, and then commits K-Means algorithm depending on them. In this paper, different from existing methods, we proposed a novel similarity function between two adjacent sentences by using WordNet as a ontology to calculate the similarity between words. And we introduced a method which can be used to calculate coherence of meaning-based paragraph by normalizing the sum of tf-idf value of words in the paragraph. We conducted experiments to prove the performance of the proposed technique by using the Reuter-21578 document set. The experimental result showed the document clustering technique of using meaning-based paragraphs improves the precision and the recall of document retrieval.

This study examines the effects of child temperament on peer play interactions and teacher-child interactions. The mediating effect of teacher-child interactions on the path from child temperament to peer play interactions is also examined. The research makes use of the big data in 5th wave(2012) from Panel Study on Korean Children of Korea Institute of Child Care and Education as fundamental research. To analyze the data, SPSS 18.0 and AMOS 16.0 are used. The results are as follows. First, child temperament has an effect on the peer play interactions and teacher-child interactions had an effect on peer play interactions. Second, chid temperament does not show an effect on teacher-child interactions. Third, teacher-child interaction did not have a mediating effect on the path from child temperament to peer play interactions. With the results shown in the research, child temperament and teacher-child interactions have influence on peer play interaction directly. The suggestion is made that teachers need to interact with children considering their temperaments as important personal traits. For the future study, the research needs to be expanded with the variables including meaningful grown-ups with the concern for the children and physical environment including kindergartens and the correlations among them need to be analyzed .

Recently, realistic visual services such as 3DTV, UHDTV, 3D cinema, 3D gaming, augmented reality (AR), virtual reality (VR) and so on are introduced, and realistic audio services are getting more important to make the realistic visual services more realistic. Generally, the realistic audio services have a limitation that users should have multi-channel speaker layout for generating the realistic audio sound, so the binaural sound generation method that provides the users the realistic sound through a stereo headphone has been introduced. But, since the binaural sound has a constant sound scene, it can not reflect the users’ movement in the AR or the VR service. In this paper, we proposed a sound scene control scheme of binaural sound in the multi-channel audio coding for generating a more realistic audio sound in the VR or AR service. In the proposed method, multi-channel gain factors and a stereo down-mix signal are modified based on the new multi-channel layout to be arranged according to a user’s head movement. The experimental results show that the proposed sound scene control scheme of the binaural sound in the multi-channel audio coding can successfully generate the binaural sound with the controlled sound scene while maintaining the good sound quality.

SDN-based network control technology has attracted much attention on wired core networks, and therefore all control and resource management on the network is expected to be integrated into the SDN technology in the future. On the contrary, the IEEE 802.21 standard, Media Independent Handover (MIH), includes a technique for managing wireless resource information to support media independent handover services. By combining these two technologies, SDN controller, managing only the resource and control information of the existing wired network, also has the advantage of being able to manage information and mobility of wired/wireless network resources in an integrated manner by gathering information on MIH that manages wireless network resources and mobility related information together. In this paper, we propose an interworking scheme of MIH standard protocol in SDN environment and build an SDN-based MIH interworking platform. We also developed a simple SDN-based wireless resource management application on the platform and tested the performance of the platform constructed in this paper. The wireless interworking platform of the SDN environment developed in this paper can be used to test the wireless bandwidth management of SDN based APs and the load management function of APs. And it can also be utilized for developing terminal mobility technology based on the allocated resource information.

Electroencephalogram(EEG) has been a standard tool to monitor the status of the brain. For quantification of EEG, permutation entropy has been of interest due to simplicity and robustness to noise. A multiscale extension of PE, called multiscale PE(MPE), has been promising in fully describing the dynamical characteristics of EEG over multiple temporal scales. However, an imprecise estimation of MPE at large scales limits its application for analyzing of short EEG. Here, a new multiscale PE measure which aims at estimating entropy accurately is presented. By computing PE of all possible coarse-grained time series and averaging the values of PE at each scale, the resultant composite MPE (CMPE) yields improved accuracy in estimation of entropy. Thus, the CMPE measure accomplishes consistent quantification of entropy regardless of the length of data. This advantage of CMPE renders its capability for analyzing EEG signals. Through simulations with two synthetic noises, CMPE has proved its capability over MPE in terms of accuracy. Experimental results using normal, inter-ictal and ictal EEG recordings have shown that the CMPE measure has leaded an improved discrimination capability for three different neurological states (normal, inter-ictal, and ictal states) than the conventional PE family.

Improving predictive accuracy of recommendation algorithms is a major work in the area of recommender systems. Collaborative filtering is the most popular method for product recommender systems. User-based collaborative filtering recommends products using the information about product preference of Neighbors. Recently, some studies enhancing predictive accuracy of recommender systems using information about the relationship of friend or trust between users has been published. This study proposed a method constructing trust-based social networks and appling structural holes for improving predictive accuracy of collaborative filtering. It constructs a social network using dataset represented trust relationship and finds user impact using structural holes that is one of methods for social network analysis. Neighbor's similarities of a target user for recommendation are adjusted by neighbor's impact which was found in before procedure. This study experimented two techniques for adjusting similarities. LinearImpCF adjusts neighbor's similarities multiplying by and neighbor's impact. ExpImpCE adjusts neighbor's similarities multiplying neighbor's impact to the power. To validate, the proposed algorithms were applied to filmtrust dataset. The results of 10-fold cross validation showed that mean MAEs of LinearImpCF and ExpImpCF were lower than mean MAE of conventional CF. We knew that the proposed method improved the predictive accuracy slightly. To test statistical significance, we experimented 10-fold cross validation repeatedly three times. We confirmed the statistical significance by paired t-test using experiment results. In conclusion, we knew that the proposed recommendation algorithm combined collaborative filtering and user's impact by structural holes on trust-base social networks between users improved the predictive accuracy.