• Journal of Digital Convergence
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• v.15 no.10
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• pp.269-279
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• 2017

The purpose of this study was to analyze differences in learning ability, team satisfaction, and learning preference depending on teaming method and the key sub-variables involved in communication ability,, problem solving ability, self-directed learning ability changes before and after team-based learning, and then to apply a team-based learning method to nursing curriculum. From October to December, 2016, 96 first-year nursing students and 108 second-year nursing students of the K University in G city took TBL classes and their observation values before and after TBL classes was analysed with SPSS and Medcalc programs. The results of this study showed that team-based learning was effective in improving communication ability, problem solving ability, self-directed learning ability, and preference to team-based learning was high in teams composed of academic achievement. It is expected that team-based learning can be settled in the curriculum by emphasizing that students learn problem-solving and communication abilities through self-learning and team dynamics before the class, and that it also is a learning method that improves professionalism and individual development. More researches are needed to focus on various factors such as the methodological composition of team-based learning and the preferences of individual student characteristics and learning methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.32-39
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• 2015

The voice communications with wireless backbone based networks are evolving into a packet switching VoIP systems. In those networks, a call processing scheme is required for management of subscribers and connection between them. A VoIP service scheme for those systems requires reliable subscriber management and connection establishment schemes, but the conventional call processing schemes based on the centralized server has lack of reliability. Thus, the mutual-backup architecture of SIP-servers is required to ensure efficient subscriber management and reliable VoIP call processing capability, and the synchronization and call processing schemes should be changed as the architecture is changed. In this paper, a mutual-backup architecture of SIP-servers is proposed for wireless backbone based networks. A message format for synchronization and information exchange between SIP servers is also proposed in the paper. This paper also proposes a FSM scheme for the fast call processing in unreliable networks to detect multiple servers at a time. The performance analysis results show that the mutual backup server architecture increases the call processing success rates than conventional centralized server architecture. Also, the FSM scheme provides the smaller call processing times than conventional SIP, and the time is not increased although the number of SIP servers in the networks is increased.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.115-121
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• 2013

This paper related with the DSE-MMA (Dithered Sign-Error MMA) that is the simplification of computational arithmetic number in blind equalization algorithm in order to compensates the intersymbol interference which occurs the passing the nonlinear communication channel in the presence of the band limit and phase distortion. The SE-MMA algorithm has a merit of H/W implementation for the possible to reduction of computational arithmetic number using the 1 bit quantizer in stead of multiplication in the updating the equalizer tap weight. But it degradates the overall blind equalization algorithm performance by the information loss at the quantization process compare to the MMA. The DSE-MMA which implements the dithered signed-error concepts by using the dither signal before qualtization are added to MMA, then the improved SNR performance which represents the roburstness of equalization algorithm are obtained. It has a concurrently compensation capability of the amplitude and phase distortion due to intersymbol interference like as the SE-MMA and MMA algorithm. The paper uses the equalizer output signal, residual isi, MD, MSE learning curve and SER curve for the performance index of blind equalization algorithm, and the computer simulation were performed in order to compare the SE-MMA and DSE-MMA applying the same performance index. As a result of simulation, the DSE-MMA can improving the roburstness and the value of every performance index after steady state than the SE-MMA, and confirmed that the DSE-MMA has slow convergence speed which meaning the reaching the seady state from initial state of adaptive equalization filter.

• Korean Chemical Engineering Research
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• v.55 no.1
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• pp.60-67
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• 2017

In this study, we performed surface modification of biodegradable microcrystalline cellulose (MCC) to use as a filler in polyethylene (PE) composite in food packaging application. We modified MCC surface with (3-trimethoxysilylpropyl)diethylenetriamine (TPDT) silane coupling agent, which has one primary amino group and two secondary amino groups per molecule, to introduce amino groups with a carbon dioxide adsorption capability in MCC. Effects of each of the reaction conditions such as amount of TPDT introduced, swelling time, reaction temperature, and reaction time on surface modification degree of MCC were investigated by changing a variety of above reaction conditions. The amount of TPDT grafted on MCC surface and formation of chemical bonds were confirmed by Fourier transform infrared spectroscopy (FT-IR), elemental analysis (EA), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA) and solid state $^{29}Si$ nuclear magnetic resonance (NMR) spectroscopy. We confirmed increase of grafted amount of TPDT on MCC with increasing reaction time, reaction temperature, and amount of introduced TPDT.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.43-50
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• 2018

Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.319-329
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• 2016

This study aimed to identify nurses' participation motivation, its influence factors, and their job training need. A survey was conducted on 345 nurses of general hospitals in Gyeonggi-do. Data was collected from October 5th to 18th, 2016 and was analyzed through t-test, ANOVA, Bonferroni post-test, and multiple regressions using SPSS 21.0. Participation motivation was high in 'expertise capability improvement and development' and low in personal gain and job stability. Job training need was the highest in nosocomial infection management and CPR and was the lowest in hospice and rehabilitation nursing. Participation motivation had significant differences depending on age, marital status, educational level, and clinical experience, and was influenced by the job training need of professional nursing and medical knowledge for disease treatment. Therefore, it is necessary to plan medical educational programs to enhance job training effectiveness, establish a strategy to increase participation motivation; and expand various job training support.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.149-162
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• 2020

The purpose of this study was to suggest implications for improving training performance by studying how the capacity of IPP workers and the characteristics of training programs affect the training performance through social support of employees. The study was conducted by distributing the online questionnaire to 270 IPP learning worker(of 9 university). As a result, it was found that the characteristics of the learning worker and the characteristics of training programs were positively related to the social support of the employees, and their social support was positively related to the training performance. The results of this study can contribute to the training performance when used as reference materials for selection of trainees and participating companies and development and operation of training courses. However, the limitation of this study is that the objectivity of the result is rather low by deriving the response centered on the recognition of the learning workers. In future studies, it is necessary to increase the objectivity of the results through three-dimensional cross-checks with training participants.

• BMB Reports
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• v.53 no.6
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• pp.329-334
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• 2020

Inflammasomes are cytosolic, multiprotein complexes that act at the frontline of the immune responses by recognizing pathogen- or danger-associated molecular patterns or abnormal host molecules. Mesenchymal stem cells (MSCs) have been reported to possess multipotency to differentiate into various cell types and immunoregulatory effects. In this study, we investigated the expression and functional regulation of NLR Family Pyrin Domain Containing 3 (NLRP3) inflammasome in human umbilical cord blood-derived MSCs (hUCB-MSCs). hUCB-MSCs expressed inflammasome components that are necessary for its complex assembly. Interestingly, NLRP3 inflammasome activation suppressed the differentiation of hUCB-MSCs into osteoblasts, which was restored when the expression of adaptor proteins for inflammasome assembly was inhibited. Moreover, the suppressive effects of MSCs on T cell responses and the macrophage activation were augmented in response to NLRP3 activation. In vivo studies using colitic mice revealed that the protective abilities of hUCB-MSCs increased after NLRP3 stimulation. In conclusion, our findings suggest that the NLRP3 inflammasome components are expressed in hUCB-MSCs and its activation can regulate the differentiation capability and the immunomodulatory effects of hUCB-MSCs.

• International Commerce and Information Review
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• v.15 no.1
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• pp.227-256
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• 2013

Existing multinational subsidiary typologies seem to have limitations in two respects. First, the prevalence of subsidiary classification along two-dimensions fails to capture many distinct subsidiary types. Failure to reflect a sufficient richness in dimensionality can give rise to a partial picture of subsidiary typologies in the international business literature. A new typology developed from multi-dimensional approach will be required for reflecting various subsidiary roles in the multinational enterprise. Second, multinational subsidiary performing a number of activities is hard to be defined functionally across the value chain activities. In addition, multinational subsidiary roles can vary dramatically. In conclusion, despite a growing amount of work on subsidiary typologies, there seems to be limited convergence of results. the study regarding subsidiary roles still remain a challenge. In this respect, the purpose of this study is to develop a new typology based on multi-dimensional approach in order to overcome the limitations of traditional typologies. To classify subsidiary types, we propose 8 types of multinational subsidiary according to three dimensions that are adopted: (1) number of required value chain activities (2) subsidiary's sourcing capability and autonomy (3) global orientation (3) The case study analyzing Korean foreign subsidiaries appropriate for 8 types is performed to establish the validity of this study.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.173-181
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• 2017

In this paper, we have studied tracking as a training stage of considering the position and the scale of a person given its previous position, scale, as well as next and forward image fraction. Unlike other learning methods, CNN is thereby learning combines both time and spatial features from the image for the two consecutive frames. We introduce multiple path ways in CNN to better fuse local and global information. A creative shift-variant CNN architecture is designed so as to alleviate the drift problem when the distracting objects are similar to the target in cluttered environment. Furthermore, we employ CNNs to estimate the scale through the accurate localization of some key points. These techniques are object-independent so that the proposed method can be applied to track other types of object. The capability of the tracker of handling complex situations is demonstrated in many testing sequences. The accuracy of the SVM classifier using the features learnt by the CNN is equivalent to the accuracy of the CNN. This fact confirms the importance of automatically optimized features. However, the computation time for the classification of a person using the convolutional neural network classifier is less than approximately 1/40 of the SVM computation time, regardless of the type of the used features.