• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.23-30
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• 2021

This paper proposes a noise-tolerant image classification system using multiple autoencoders. The development of deep learning technology has dramatically improved the performance of image classifiers. However, if the images are contaminated by noise, the performance degrades rapidly. Noise added to the image is inevitably generated in the process of obtaining and transmitting the image. Therefore, in order to use the classifier in a real environment, we have to deal with the noise. On the other hand, the autoencoder is an artificial neural network model that is trained to have similar input and output values. If the input data is similar to the training data, the error between the input data and output data of the autoencoder will be small. However, if the input data is not similar to the training data, the error will be large. The proposed system uses the relationship between the input data and the output data of the autoencoder, and it has two phases to classify the images. In the first phase, the classes with the highest likelihood of classification are selected and subject to the procedure again in the second phase. For the performance analysis of the proposed system, classification accuracy was tested on a Gaussian noise-contaminated MNIST dataset. As a result of the experiment, it was confirmed that the proposed system in the noisy environment has higher accuracy than the CNN-based classification technique.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.89-107
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• 2021

This paper explores the empirically analyzes the competitive nature of the five social media by analyzing the proper SNS service such as Facebook, Instagram, YouTube, Pinterest, and Twitter. In this study, we surveyed the use and satisfaction of social media for SNS users by using the proper theory. A total of 224 users were selected for analysis. Based on the results of the questionnaire, factor analysis was carried out to extract common factors such as relationship, sociality, convenience, daily life, and entertainment. As a result of the research using proper analysis, Facebook showed the widest narrowness in sociality (.627) and convenience (.636) in the first place, and YouTube showed the lowest in daily life (.670) and entertainment (.615) In the relationship (.520), the Instagram was the widest. In terms of five factors, Facebook and YouTube have the greatest overlap in relationship (1.826) and sociality (2.696), while Pinterest and Twitter are the most common in daily life (1.937) and entertainment (2.263) There is redundancy, and for convenience (2.583), YouTube and Twitter have the most redundancy. Facebook, Instagram, and YouTube have a competitive advantage over Pinterest in terms of relationships, sociality, convenience, routine, and entertainment, and are competitive across all factors except Facebook, Instagram, and YouTube Twitter It is possible to confirm that it is superior.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.8
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• pp.215-222
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• 2021

In order to alleviate the limited resource problem and interference problem in cellular networks, the dual connectivity technology has been introduced with the cooperation of small cell base stations. In this paper, we design a new efficient and fair resource allocation scheme for the dual connectivity technology. Based on two different bargaining solutions - Generalizing Tempered Aspiration bargaining solution and Gupta and Livne bargaining solution, we develop a two-stage radio resource allocation method. At the first stage, radio resource is divided into two groups, such as real-time and non-real-time data services, by using the Generalizing Tempered Aspiration bargaining solution. At the second stage, the minimum request processing speeds for users in both groups are guaranteed by using the Gupta and Livne bargaining solution. These two-step approach can allocate the 5G radio resource sequentially while maximizing the network system performance. Finally, the performance evaluation confirms that the proposed scheme can get a better performance than other existing protocols in terms of overall system throughput, fairness, and communication failure rate according to an increase in service requests.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.3
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• pp.187-215
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• 2021

Archives should provide a web-based archival information service with good usability based on the understanding of users' needs. Thus, this study analyzed the usability of the National Archives of Korea (NAK) website's search service through expert and usability evaluations for various users and suggested improvement plans. A literature review, heuristic evaluation, one of the usability expert evaluation methods, and usability evaluation for users were performed. As a result of expert evaluation, the severity rating for the usability problem was highest regarding a match between the system and real world and the lowest in error prevention. In the usability evaluation, it was assumed that the user's background and whether the website's help was provided is associated with usability. Usability evaluation was conducted for 22 participants, including those majoring in records management, web/application developers, and people without such backgrounds. Furthermore, a presurvey, a five-second test, and search tasks were conducted in a row. The analysis based on usability components in ISO 9241-11: 2018, i.e., effectiveness, efficiency, and satisfaction, showed that web/application developers had the highest search effectiveness, and those majoring in records management showed high effectiveness only in the search for archival content services. Background factors did not affect efficiency, and the more familiar with the finding aids, the better the efficiency. Moreover, providing the website's help was found to be positively associated with effectiveness and satisfaction. This study suggests that the NAK website will offer a user-friendly interface and search function, expand help support, and display a consistent web interface.

• Journal of Plant Biotechnology
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• v.48 no.2
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• pp.71-76
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• 2021

Angelica is a perennial plant used widely for medicinal purposes. Information on the genetic diversity of Angelica populations is important for their conservation and germplasm utilization. Although Angelica is an important medicinal plant genus registered in South Korea, no molecular markers are currently available to distinguish individual species from other similar species in different countries, in particular, China and Japan. In this study, we developed single nucleotide polymorphism (SNP) markers derived from internal transcribed spacer regions of the nuclear ribosomal DNA to identify a distinct domestic species, Angelica gigas Nakai, via a high-resolution melting (HRM) curve analyses. We also performed HRM curve analysis of intentionally mixed genomic DNA samples from five Angelica species. Finally, we investigated A. gigas Nakai and A. sinensis using varying ratios of mixed genomic DNA templates. The SNP markers developed in this study are useful for rapidly identifying A. gigas species from different countries.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.123-134
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• 2021

This paper suggests that the Internet is not free through analysis of U.S. Internet history and lawsuits related to the Charter merger in 2016. Generally speaking, the players in internet connectivity market agree to Non-Disclosure Agreement, when connecting their facilities and networks each other. So, I adopted the case study & analysis as research methodologies due to limitation of collecting the transaction data between them. The former finds that Internet access has never been free in U.S Internet history. As we know, some including Content Providers(CPs) argue that the Internet is a free network and there are many cases to use the internet for free, so they came to conclusion that ISPs have no right to charge the users like CPs. This study refutes these arguments in two ways. One is that using the internet has never been free. From ARPANET, known as the beginning of the U.S. Internet, to the commercialization of backbone, no Internet has been considered or implemented for free since the early Internet network was devised. Also, the U.S government was paying subsidies or institutions were paying fees to secure network operations for the NSFNET backbone. the other is that "free peering" refers to barter transactions between ISPs, not to free access to counterpart internet networks. Second, this study analyze the FCC' executive order of conditioned merger approval and the court's related ruling and verify that using the internet is not free. According to the analysis, this study finds that it's real situation to make paid settlements between ISP-CPs (including OTTs) in the US Internet market at the moment. This study concludes that the Internet has never been free in terms of its technical characteristics, network structure, network operation, and system. Also it proposes how to improve the domestic settlement system between ISPs-CPs in terms of policy and regulation.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.1-11
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• 2021

As the Internet developed, various and complex cyber attacks began to emerge. Various detection systems were used outside the network to defend against attacks, but systems and studies to detect attackers inside were remarkably rare, causing great problems because they could not detect attackers inside. To solve this problem, studies on the lateral movement detection system that tracks and detects the attacker's movements have begun to emerge. Especially, the method of using the Remote Desktop Protocol (RDP) is simple but shows very good results. Nevertheless, previous studies did not consider the effects and relationships of each logon host itself, and the features presented also provided very low results in some models. There was also a problem that the model could not explain why it predicts that way, which resulted in reliability and robustness problems of the model. To address this problem, this study proposes an interpretable RDP-based lateral movement detection system using page rank algorithm and SHAP(Shapley Additive Explanations). Using page rank algorithms and various statistical techniques, we create features that can be used in various models and we provide explanations for model prediction using SHAP. In this study, we generated features that show higher performance in most models than previous studies and explained them using SHAP.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.27-36
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• 2019

In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.87-94
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• 2019

In this paper, the method of analyzing the unformatted data of consumers accumulated on social networks in the era of the Fourth Industrial Revolution by utilizing data from the service design and social psychology aspects was proposed. First, the fandom phenomenon, which shows subjective and collective behavior in a space on a social network rather than physical space, was defined from a data service perspective. The fandom model has been transformed into a collective level of customer Persona that has been analyzed at a personal level in traditional service design, and social network analysis that analyzes consumers' big data has been presented as an efficient way to pattern and visually analyze it. Consumer data collected through social leasing were pre-processed by column based on correlation, stability, missing, and ID-ness. Based on the above data, the company's brand strategy was divided into active and passive interventions and the effect of this strategic attitude on the growth direction of the consumer's fandom community was analyzed. To this end, the fandom model of consumers was proposed by dividing it into four strategies that the brand strategy had: stand-alone, decentralized, integrated and centralized, and the fandom shape of consumers was proposed as a growth model analysis technique that analyzes changes over time.