• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.215-227
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• 2017

The development of information technology are leading to the rapid evolution of SNS (Social Networking Services) in various directions and industries. Initially, SNS have been used as the form of networking between user's groups. Currently SNS has been developed towards multiple purposes and platforms such as the promotion and the advertising of a company. There are many SNSs including QQ, Weibo, and Wechat and so on in China. However, the use of companies in terms of advertising and information sharing with the customers do not meet the trend in China. Especially, there were little researches for Chinese travel agencies how to utilize SNS for attracting new customers and making them contribute to the firm's performance. In this study, we try to investigate the impact of the firm's characteristics and the usage of SNS on the performance of Chinese travel agencies. Based on Top 100 China travel agencies in 2009, we analyzed the relationships between firm's characteristics and the usage of SNS, and firm's performances in 2013. We expect that our study can contribute to the increasing academic and practical needs on the empirical evidence of the impacts of the SNS utilizations on the firm's performance.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.1118-1134
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• 2023

Previous research has shown that employees tend to react more positively to corrective feedback from supervisors to the extent they perceive that they were treated with empathy, respect, and concern towards fair interpersonal treatment in receiving the feedback information. Then, to facilitate effective supervisory feedback and coaching, it would be useful for organizations to monitor the contents of feedback exchanges between supervisors and employees to make sure that supervisors are providing performance feedback using languages that are more likely to be perceived as interpersonally fair. Computer-aided text analysis holds potential as a useful tool that organizations can use to efficiently monitor the quality of the feedback messages that supervisors provide to their employees. In the current study, we applied computer-aided text analysis (using closed-vocabulary text analysis) and machine learning to examine the validity of language-based algorithms trained on supervisor language in performance feedback situations for predicting human ratings of feedback interpersonal fairness. Results showed that language-based algorithms predicted feedback interpersonal fairness with reasonable level of accuracy. Our findings provide supportive evidence for the promise of using employee language data for managing (and improving) performance management in organizations.

• Information Systems Review
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• v.19 no.3
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• pp.105-125
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• 2017

Although the relationship between social networking sites (SNS) use and performance has been widely studied, most of these studies have focused on comparing the SNS users' overall performance with that of non-SNS users instead of examining how using SNS midway of a task affects one's task performance. To address this research gap, an experiment was conducted to examine SNS use during a task and its influence on the performance of that task. In this experiment, the role of SNS in various situations was examined by reviewing the literature on break and performance as well as the types of breaks and tasks. Owing to its exploratory nature, this study used various types of data, such as electroencephalography interpretation data generated from a brain-computer interface, self-reported data, and data recorded by a computer. Those participants who used SNS showed an improved performance compared with those who took a short break while doing a simple task. Further analysis showed that the degree of SNS usage and engagement with SNS had positive effects on the participants' simple task performance, while social presence and reassurance of self-worth had negative and positive effects on the participants' complex task performance, respectively.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.331-351
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• 2014

This study analyzed students', parents of student, and school master' survey materials and reading, math, and science knowledge performance based on OECD PISA 2009 Koreana data. Also, school library level variables grasped the impacts of academic achievement. Through this study looked for suggestion to improvement, educational accountability and leverage of school library. The results, first, when they use reading more pleasantly thought, they achieve higher scores in academic performance. Second, when they use more books and reading resources in housekeeping, they achieve higher scores in academic performance. Third, when they were more visits school library for exploit internet, they achieve higher lower scores in academic performance. Fourth, when the member of the staff in the school library are more lack of people, they achieve lower scores in academic performance. Fifth, private education's experience in reading have a negative influence in reading achievement and science achievement. Sixth, school library's visiting and library application study about national language curriculum in the impacts of academic performance would not change statistical evaluation significantly.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.379-381
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• 2008

TETRA(Terrestrial Trunked Radio) is a digital trunked radio standard developed by the ETSI(European Telecommunications Standards Institute). Currently, TETRA was set Digital TRS in electric power If wireless backbone network. In this time, we use many company's TETRA modem. So, TETRA modem performance evaluation is very important. TETRA modem use two type of Data transfer mode. One is Packet Data using UDP/IP. and the other is SDS(Short Data Service). In this paper, We generate Packet Data using Traffic Generator module. Packet Data transfer 1000 times each 10 bytes to 400 bytes. We analyze transmission delay time, success rate and standard deviation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8A
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• pp.804-813
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• 2006

In wireless Internet environment that demand of wireless Internet service increase steadily, wireless PKI(Public Key Infrastructure) service is appearing on stage as necessary essential base technology for information protection service offer, In this paper, we propose the method for verification to reduce the communication overload using VID to CSMP made with a goal of the performance guarantee for security and use in a real time and examine the existent certificate verification methods. The performance of security and the use in a real time is guaranteed by managing the note of authentification by the person who verifies and reducing the amount of the data transmission using VID.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.19-25
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• 2016

There are many free applications that need users to sign up before they can use the applications nowadays. It is difficult to choose a suitable password for your account. If the password is too complicated, then it is hard to remember it. However, it is easy to be intruded by other users if we use a very simple password. Therefore, biometric-based approach is one of the solutions to solve the issue. The biometric-based approach includes keystroke dynamics on keyboard, mice, or mobile devices, gait analysis and many more. The approach can integrate with any appropriate machine learning algorithm to learn a user typing behavior for authentication system. Preprocessing phase is one the important role to increase the performance of the algorithm. In this paper, we have proposed ensemble-by-session (EBS) method which to operate the preprocessing phase before the training phase. EBS distributes the dataset into multiple sub-datasets based on the session. In other words, we split the dataset into session by session instead of assemble them all into one dataset. If a session is considered as one day, then the sub-dataset has all the information on the particular day. Each sub-dataset will have different information for different day. The sub-datasets are then trained by a machine learning algorithm. From the experimental result, we have shown the improvement of the performance for each base algorithm after the preprocessing phase.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.343-351
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• 2017

With ICT technology develops, IoT environment is attracting attention. However, IoT devices have various CPU performance as much as various purpose of use. Some IoT devices use the cpu that doesn't support public key cryptogrphy or crypto acceleration. In this paper, we study Blockchain-based IoT Device Authentication Scheme that provides authentication, integirity and non-repudation through analysis of Lamport Hash-chain, Lamport Signature, Blockchain and existing Authentication protocols. The proposed scheme requires only simple hash operation in IoT devices and it can operate in low performance IoT device, thus ensuring secure authentication in IoT environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.127-133
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• 2019

Most studies of software fault prediction have been about supervised learning models that use only labeled training data. Although supervised learning usually shows high prediction performance, most development groups do not have sufficient labeled data. Unsupervised learning models that use only unlabeled data for training are difficult to build and show poor performance. Semi-supervised learning models that use both labeled data and unlabeled data can solve these problems. Self-training technique requires the fewest assumptions and constraints among semi-supervised techniques. In this paper, we implemented several models using self-training algorithms and evaluated them using Accuracy and AUC. As a result, YATSI showed the best performance.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.103-111
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• 2010

Syntactic analysis is an important step in natural language processing. However, we cannot use the syntactic analyzer in Korean for low performance and without robustness. We propose new robust, high speed and high performance Korean syntactic analyzer using CRFs. We treat a parsing problem as a labeling problem. We use a cascaded chunking for Korean parsing. We label syntactic information to each Eojeol at each step using CRFs. CRFs use part-of-speech tag and Eojeol syntactic tag features. Our experimental results using 10-fold cross validation show significant improvement in the robustness, speed and performance of long Korea sentences.