• 연구윤리
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• 제5권2호
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• pp.17-23
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• 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
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• 제11권4호
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• pp.135-153
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• 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
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• 제13권4호
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• pp.229-255
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• 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.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 춘계학술대회
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• pp.115-117
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• 2016

최근에 각종 사물인터넷 제품이 시장에 출시되면서 관련 업체들은 시장 선점을 위해 표준화의 플랫폼 분야에서 경쟁을 벌이고 있다. 이런 상황을 분석하기 위해 먼저 사물인터넷 관련연구 분야인 사물 지능 통신, 무선 센서 네트워크, 사물 웹, 사물 모바일 등의 연구 내용에 대해 살펴보고자 한다. 이 기술 분야에 대한 관심은 꾸준히 증가하고 있는 추세이며 관련 서비스도 지속적으로 등장하고 있다. 따라서 사물인터넷을 기반 선행 연구들을 문헌적 분석을 실시하였다. 본 연구는 2010년 이후 국내 학술지에 게재된 연구 중 사물인터넷과 관련된 연구 34편의 연구논문을 대상으로 하였다. 분석결과 사물인터넷 관련 연구들은 2014년-2015년 사이에 대부분 이루어지고 있다는 것을 알 수 있었다. 이러한 결과는 사물인터넷이 정보통신기술을 기반으로 하고 있다는 것을 말해주고 있다. 결과를 바탕으로 연구의 한계와 시사점을 제시하고자 한다.

• 한국조사연구학회지:조사연구
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• 제10권3호
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• pp.85-106
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• 2009

본 연구는 한국과 일본에서 나타나는 인터넷 이용행태의 기본적인 특성과 전반적인 인식이 온라인에서의 관계망의 형성과 유지에 어떤 영향을 주고 받는지를 구체적으로 살펴보았다. 이를 위해 한국과 일본의 이용자들의 온라인 관계망의 현황과 개인적 성향, 인터넷 이용패턴, 그리고 인터넷에 대한 인식 등을 설문조사를 통해 알아보았다. 연구결과를 요약하면, 온라인 관계망의 크기와 활용에 있어서 한국의 이용자들이 보다 적극적인 것으로 나타났으며, 양국 모두 자주 만나기 어려운 사적인 관계의 대상들과 관계하는 비율이 높은 것을 알 수 있었다. 또한 한국의 이용자들은 개인적 성향이나 인터넷 관련 행태 및 인식이 전반적으로 만남의 방식에 영향을 미치지 않았던 데 비해 일본의 이용자들은 관계지향적인 인터넷 이용 패턴과 인터넷의 유용성에 대한 인식이 온라인에서의 접촉 양상에 영향을 미치는 것으로 나타났다. 온라인 관계망의 크기와 관련하여 양국 모두에 공통적으로 나타난 것은 인터넷을 정보지향적으로 이용할수록 등록된 대화상대가 증가한다는 점이었다. 이는 인터넷에서의 관계형성에 있어 약한 유대에 기반한 관계가 효율적이고, 이러한 관계를 통해 얻을 수 있는 혜택이 정보적 혜택이라는 기존의 이론과 잘 부합하는 결과라고 할 것이다. 아울러 일본의 경우 온라인에서의 관계형성 전반에 있어 온라인 공간에 대한 위험인식 정도, 즉 신뢰의 여부가 크게 영향을 미치는 것으로 분석되었다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.130-133
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• 2015

최근 정보통신기술의 발전에 따라 미래인터넷의 중요성이 강조되고 있으며 그 가운데 사물인터넷은 공공 및 민간 부분에서 활용 및 중요성이 크게 부각되고 있다. 이 기술 분야에 대한 관심은 꾸준히 증가하고 있는 추세이며 관련 서비스도 지속적으로 등장하고 있다. 따라서 사물인터넷을 기반 선행 연구들을 문헌적 분석을 실시하였다. 또한, 본 연구는 2010년 이후 국내 학술지에 게재된 연구 중 사물인터넷과 관련된 연구 34편의 연구논문을 대상으로 하였다. 분석결과 사물인터넷 관련 연구들은 2014년-2015년 사이에 대부분 이루어지고 있다는 것을 알 수 있었다. 문헌분석에 가장 많은 포함된 논문은 한국통신학회지로서 8편이었다. 이러한 결과는 사물인터넷이 정보통신기술을 기반으로 하고 있다는 것을 말해주고 있다. 결과를 바탕으로 연구의 한계와 시사점을 제시하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.494-510
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• 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
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• 제16권3호
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• pp.27-32
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• 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.

• 인터넷정보학회논문지
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• 제19권5호
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• pp.123-131
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• 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)
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• 제13권5호
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• pp.2299-2318
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• 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.