• Journal of Research and Publication Ethics
• /
• v.5 no.2
• /
• pp.17-23
• /
• 2024

Purpose: The internet, as a tool, avenue, and field, has wide-researching and specific ethical concerns. Internet-based research ethics is a field that spreads across numerous fields, scoping from natural and biomedical sciences to social sciences, and arts and humanities. Thus, this study which investigates research ethics within an Internet-based Research Setting will be quite valuable. Research design, data and methodology: The current authors widely took a look at prior and present literature dataset to explore research ethics within an Internet-based setting. Using numerous search engine, such as 'Goole Scholar', 'Scopus', and 'Web of Science', the current authors could obtain total 42 prior studies that are relevant with our research topic. Results: Based on the screening process in the literature datasets, this study could categorize four areas of the research ethics within Internet-based research setting as follows: (1) Human Subjects Ethics, (2) Big Data Ethical Issues, (3) Research Ethics and Cloud, and (4) Computing Interviews and Surveys Ethics. Conclusions: This study concludes that although internet-based research has many benefits, the accompanying ethical issues are many. The lack of uniformity in the concept and terminology of online research methods typically brings forth confusion and makes it hard for new researchers to develop mutual guidelines.

• Asia pacific journal of information systems
• /
• v.11 no.4
• /
• pp.135-153
• /
• 2001

Internet business is transforming the current structure and way of shopping behaviors. As a frontier area of internet business, internet shopping mall industry is influenced by this trend. In this shopping situation, shopping objects and information on the object are separated, which makes consumers to decide on the contents and marketing function offered by the shopping mall. This study proposes an integrated model including the influencing factors on customer royalty in Internet shopping environments. Eight hypotheses are proposed based on previous research in Internet marketing and information systems. The results are quite supporting the model and hypotheses. The contents structure, marketing activities, and customer satisfaction in the internet shopping environment influence shopping experience, next purchases and reference to other people. The proposed model and empirical results would contribute to setting up strategy of Internet shopping mall industry, and also to future research in information systems and Internet marketing.

• Asia pacific journal of information systems
• /
• v.13 no.4
• /
• pp.229-255
• /
• 2003

This article attempts to examine the well-known law that the increasing returns to scale(IRS) is effective in the Internet business. The effect of IRS is one of the hottest issues in the Internet business sector. Many cases and survey studies support the fact that the IRS phenomenon exists in the Internet business. Executives in Internet business generally give a deep trust on this theory. As the Internet business grows, however, the boundary of the business becomes widened and complicated. And each category of Internet business is characterized with a different business style and economic behavior. It may, therefore, be dangerous to accept that the phenomenon of IRS is applied to all areas of Internet business. For this reason, the research for the close look into the IRS phenomenon should provide significant implications for the managers in the Internet business industry. This article divides the internet business into four sub-areas, and analyzes the IRS phenomenon using AHP/DEA-based full ordering technique. Interpretations are given, based upon the research results, for each sub-area of Internet business, as a guideline of setting business strategies for practical managers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.115-117
• /
• 2016

Recently, many IoT(internet of things) products are emerging on the market and information technology companies are competing on the areas of internet of things standardization and platforms. This paper introduces many researches, standardizations, platforms on internet of things. Because of that, as the interest in this area out focused, many kinds of technology and new service are being exploited in this field. Therefore, we conducted a review research based on the internet of things. Also, this study was targeted a total of 34 research papers that are setting up the related internet of things among the research papers published in domestic academic journals since 2010. In this review, the studies related internet of things showed that the most is studied between 2014 and 2015. This study suggests practical and theoretical implications based on the results.

• Survey Research
• /
• v.10 no.3
• /
• pp.85-106
• /
• 2009

This study is an attempt to provide some answers to question about how characteristics and general recognition regarding internet use in Korea and Japan influence fostering and maintaining on-line social network in each of countries. Survey is used to compare Korean internet users and Japanese internet users in terms of characteristics of on-line social network, individual's propensity for internet use, including their recognition on internet. The study's main findings go as follows. First, Korean internet users tend to be more active in using internet than Japanese internet users do, thus having larger on-line social network and more intensive internet use than Japanese internet users do. However, there is a commonality that majority of internet users in both countries use internet to connect them to person with whom they have private relationship but they cannot meet frequently. Second, for Korean internet users, individual's propensity, characteristics, and recognition regarding internet use is not related to how to contact others. To the contrary, for Japanese internet users, how to contact others in on-line setting seems to vary according to whether or not they have relation-oriented internet use and how they recognize the availability of internet. Third, a commonality regarding the size of on-line social network is found between Korea and Japan that the total numbers of people enrolled as network increases if people use internet in order to get information. This confirms previous finding that relationship based on weak tie is instrumental in fostering on-line social relations and likely produces advantage in getting information. Finally, for Japanese internet users, the degree of risk recognized in on-line setting, that is the degree of interpersonal trust, appears to greatly influence overall relationship -building in on-line.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.130-133
• /
• 2015

Recently, with information communication technology becomes advanced, the importance of future internet is emphasized and in part of that, internet of things is magnified in terms of importance and usage in public and private sector. Because of that, as the interest in this area out focused, many kinds of technology and new service are being exploited in this field. Therefore, we conducted a review research based on the internet of things. Also, this study was targeted a total of 34 research papers that are setting up the related internet of things among the research papers published in domestic academic journals since 2010. In this review, the studies related internet of things showed that the most is studied between 2014 and 2015. This study suggests practical and theoretical implications based on the results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.494-510
• /
• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.27-32
• /
• 2024

Reliable and fine-grained musical metadata are required for efficient search of rapidly increasing music files. In particular, since the primary motive for listening to music is its emotional effect, diversion, and the memories it awakens, emotion classification along with genre classification of music is crucial. In this paper, as an initial approach towards a "ground-truth" dataset for music emotion and genre classification, we elaborately generated a music corpus through labeling of a large number of ordinary people. In order to verify the suitability of the dataset through the classification results, we extracted features according to MPEG-7 audio standard and applied different machine learning models based on statistics and deep neural network to automatically classify the dataset. By using standard hyperparameter setting, we reached an accuracy of 93% for genre classification and 80% for emotion classification, and believe that our dataset can be used as a meaningful comparative dataset in this research field.

• Journal of Internet Computing and Services
• /
• v.19 no.5
• /
• pp.123-131
• /
• 2018

A virtual team consists of various members with a range of professional skills. An IT virtual team can confer such advantages as improving creativity and solving problems in e-business. However, virtual teams are less cohesive than off-line based teams, at least partly because they do not meet face-to-face to solve problems. If the cohesion of the members in a team is weak, overall performance can decrease. Therefore, this study seeks to understand the specific types of leadership needed to increase the cohesiveness of the members in a virtual team. Leadership is the most important factor for the successful operation of a virtual team. Leaders engage members with goals, and motivate them by creating positive relationships. This study describes the idealized influence of transformational leadership in which a leader directly engages members in a goal, and the role of participative goal setting in which members set their own goals. In addition, this research demonstrates the benefits of a positive attitude of a leader towards their team members and the influence of leader-member exchanges. If the cohesion of virtual teams is improved through specific leadership, the team members will be more committed to their teams and work, and the team's performance will improve. Furthermore, the successful operation of virtual teams will provide an opportunity for companies in e-business to gain a competitive advantage in the contemporary environment, where creativity is important.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.5
• /
• pp.2299-2318
• /
• 2019

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.