• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.

• Journal of Science and Technology Studies
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• v.5 no.1 s.9
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• pp.55-92
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• 2005

The factors contributing to the formation of an important scientific concept in South Korea and its circulation in the society are the scientific knowledge that had been already formed, matured, and established in the U.S.A, Europe and Japan and has been introduced into Korea, and the institutions that have been formed during the recent modernization in South Korea. The concept of 'genetic information' cannot be an exception in this context. The concept of genetic information is the one that has been extended and intensified by the genomics and bioinformatics formed and matured through the Human Genome Projects from the former concept of inheritance or heredity within the framework of classical and molecular genetics. The purpose of this study was to find out 'how the production structure of genetic information in South Korea has been formed', under the perspective of the conceptual, epistemic, and institutional holisticity or integratedness in the concept and knowledge production structure idealized in Western advanced nations. The discourse of genetic engineering popular in the mid 1980's in South Korea has catalyzed the development of molecular biology. However, the institutional balance that had been established for the biochemistry departments in Natural Science College and Medical College was not formed between the genetic engineering and genetics departments in South Korea. Therefore, they were unable to achieve the more integrative and macro-level disciplinary impact on life sciences, largely due to institutional lack of the capable (human) genetics departments in some leading Korean colleges of Medicine. In genomics, the cutting-edge reprogramming and restructuring of the traditional genetics in the West, South Korea has not invested, even meagerly, in the infrastructure, fund, and research and development (R & D) for the Basic or First Phase of the research trajectory in the Human Genome Project. Without a minimal Basic Phase, the genomics research and development in Korea has been running more or less for the Advanced or Second Phase. Bioinformatics has started developing in Korea under a narrow perspective which regards it as a mere sub-discipline of information technology (IT). Having developed itself in parallel with genomics, bioinformatics contains its own unique logics and contents that can be both directly and indirectly connected to the information science and technology. As a result, bioinformatics reveals a defect in respect of being synergistically integrated into genetics and life sciences in Korea. Owing to the structural problem in the production, genetic information appears to be produced in a fragmented pattern in the Korean society since its fundamental base is weak and thin. A good example of the conceptual and institutional fragmentedness is that 'the genetics of individual identification' is not a normal integrated part of the Korean genetics, but a scientific practice exercised in the departments of legal medicine in a few Medical Colleges. And the environment contributing to the production structure of genetic information in South Korea today comprises 'sangmyung gonghak'(or life engineering) discourse and non-governmental organization movement.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.216-225
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• 2011

Following the proliferation of three-dimensional video contents and displays, many terrestrial broadcasting companies have been preparing for stereoscopic 3DTV service. In terrestrial stereoscopic broadcast, it is a difficult task to code and transmit two video sequences while sustaining as high quality as 2DTV broadcast due to the limited bandwidth defined by the existing digital TV standards such as ATSC. Thus, a terrestrial 3DTV broadcasting with a heterogeneous video codec system, where the left image and right images are based on MPEG-2 and H.264/AVC, respectively, is considered in order to achieve both high quality broadcasting service and compatibility for the existing 2DTV viewers. Without significant change in the current terrestrial broadcasting systems, we propose a joint rate control scheme for stereoscopic 3DTV service based on the heterogeneous dual codec systems. The proposed joint rate control scheme applies to the MPEG-2 encoder a quadratic rate-quantization model which is adopted in the H.264/AVC. Then the controller is designed for the sum of the left and right bitstreams to meet the bandwidth requirement of broadcasting standards while the sum of image distortions is minimized by adjusting quantization parameter obtained from the proposed optimization scheme. Besides, we consider a condition on maintaining quality difference between the left and right images around a desired level in the optimization in order to mitigate negative effects on human visual system. Experimental results demonstrate that the proposed bit rate control scheme outperforms the rate control method where each video coding standard uses its own bit rate control algorithm independently in terms of the increase in PSNR by 2.02%, the decrease in the average absolute quality difference by 77.6% and the reduction in the variance of the quality difference by 74.38%.

• 기호학연구
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• no.56
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• pp.45-70
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• 2018

Criticism of the postmodern philosophy of the system of representation, which has continued since the Renaissance, is based on a critique of the dichotomy that separates the subjects and objects and the environment from the human being. Interactivity, highlighted in a series of works emerging as postmodern trends in the 1960s, was transmitted to an interactive aspect of digital art in the late 1990s. The key feature of digital art is the possibility of infinite variations reflecting unpredictable changes based on public participation on the spot. In this process, the importance of computer programs is highlighted. Instead of using the existing program as it is, more and more artists are creating and programming their own algorithms or creating unique algorithms through collaborations with programmers. We live in an era of paradigm shift in which programming itself must be considered as a creative act. Simulation technology and VR technology draw attention as a technique to represent the meaning of reality. Simulation technology helps artists create experimental works. In fact, Baudrillard's concept of Simulation defines the other reality that has nothing to do with our reality, rather than a reality that is extremely representative of our reality. His book Simulacra and Simulation refers to the existence of a reality entirely different from the traditional concept of reality. His argument does not concern the problems of right and wrong. There is no metaphysical meaning. Applying the concept of simulation to algorithmic art, the artist models the complex attributes of reality in the digital system. And it aims to build and integrate internal laws that structure and activate the world (specific or individual), that is to say, simulate the world. If the images of the traditional order correspond to the reproduction of the real world, the synthesized images of algorithmic art and simulated space-time are the forms of art that facilitate the experience. The moment of seeing and listening to the work of Ian Cheng presented in this article is a moment of personal experience and the perception is made at that time. It is not a complete and closed process, but a continuous and changing process. It is this active and situational awareness that is required to the audience for the comprehension of post-representation's forms.

• Journal of Science and Technology Studies
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• v.19 no.1
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• pp.1-51
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• 2019

The understanding of law and science as fundamentally different two systems, in which fact stands against justice, rapid progress against prudent process, is far too simple to be valid. Nonetheless, such account is commonly employed to explain the tension between law and science or justice and truth. Previous STS research raises fundamental doubts upon the off-the-shelf concept of "scientific truth" that can be introduced to the court for legal judgment. Delimiting the qualification of the expert, the value of the expert knowledge, or the criteria of the scientific expertise have always included social negotiation. What are the values that are affecting the boundary-making of the thing called "modern science" that is supposedly useful in solving legal conflicts? How do the value of law and the meaning of justice change as the boundaries of modern science take shapes? What is the significance of "science" when it is emphasized, particularly in relation to the legal provisions of paternity, and how does this perception of science affect unfoldings of legal disputes? In order to explore the answers to the above questions, we follow a process in which a type of "knowledge-deficient model" of a court-that is, law lags behind science and thus, under-employs its useful functions-can be closely examined. We attend to a series of discussions and subsequent changes that occurred in the US courts between 1930s and 1970s, when blood type tests began to be used to determine parental relations. In conclusion, we argue that it was neither nature nor truth in itself that was excavated by forensic scientists and legal practitioners, who regarded blood type tests as a truth machine. Rather, it was their careful practices and crafty narratives that made the roadmaps of modern science, technology, and society on which complex tensions between modern states, families, and courts were seen to be "resolved".

• The Southeast Asian review
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• v.28 no.1
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• pp.21-51
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• 2018

This article takes several approaches in explaining recent developments in Vietnam. First, it draws upon an array of sources that idealize Vietnam's embrace of capitalism and integration into the global market in order to sketch out its economy's progress in 2017. Second, it observes, evaluates, and diagnoses recent changes in the Vietnamese economy in the medium to long term by incorporating conflicting perspectives on Vietnam's performance as a capitalist country. Third, this article traces the power shifts that have risen from internal struggles in the Communist Party over political and social issues. Fourth, it elaborates on the aforementioned impact that foreign relations have had on socio-political developments in Vietnam, as well as the government's response. In so doing, it also attempts to evaluate, however briefly, the significance of the 25th anniversary of South Korea-Vietnam relations. Finally, it examines the public's reaction to the post-reform transitions in light of recent sociocultural changes. 2017 was a memorable year for Vietnam: a continuous march toward capitalism; the resulting expansion of the Vietnamese people's demands; political controversies and government control; the looming instability of United States-China relations and various attempts to address the situation. These events will inevitably replicate themselves in the future as the ostensibly socialist Vietnam adopts a capitalist model. The problem is that it is unclear whether these experiences will continue with the consent of the people of socialist Vietnam or engender resistance. It is difficult to achieve meaningful consent in the status quo of worsening inequalities, widespread corruption, monopoly on power, and sustained use of unskilled low-wage workers. In other words, when concerns such as welfare, public health, and the environment are set aside in favor of economic development and commercialization as they have been, discontent, rather than consent, will prevail. It is thus important to keep a watchful eye on the viability of the nominal economic growth, surface-level political stability, and strategic responses to foreign relations that took place in 2017.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.63-81
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• 2023

The purpose of this study was to utilize the Photovoice qualitative research method targeting university students. Through this method, we aimed to understand the perceptions of environmental issues, environmental barriers, and eco-friendly behaviors among university students. By employing the Photovoice methodology, we sought to share the perspectives of university students on eco-friendly behaviors, explore the motivations and manifestations of these behaviors, and reflect on their significance. The ultimate goal was to provide practical suggestions for fostering eco-friendly behaviors through an in-depth examination of the visual narratives and reflections of university students. Under the overarching theme of the environment, participants were given the opportunity to individually select and explore three specific sub-themes: 'My Concept of the Environment,' 'Environmental Barriers in My Life,' and 'My Eco-friendly Behaviors.' Participants engaged in the process of capturing photographs from their daily lives related to each theme, expressing their thoughts and perspectives through the selected images. Subsequently, they shared and discussed their insights, actively listening to the opinions of others in the group. The results of this study revealed several key findings. Firstly, participants assigned meaning to the photographs they selected by directly capturing aspects related to the environment, such as 'waste,' 'discomfort,' 'fine dust=environmental pollution,' and 'indifference.' Secondly, participants attributed meaning to the selected photographs related to environmental barriers, associating them with concepts like 'invisibility,' 'apathy,' 'social stigma,' 'inefficiency,' and 'compulsion.' Lastly, participants ascribed significance to photographs selected in the context of eco-friendly behaviors, with themes like 'recycling,' 'energy conservation,' 'reuse,' and 'reducing the use of disposable items.' Based on these research findings, the confirmation of the V-A-B (Values-Attitudes-Behavior) model was established. It was observed that consumers structure a hierarchical relationship between their personal values, attitudes, and behaviors. The study also identified clear impediments in consumers' daily lives hindering the practice of eco-friendly behaviors. In light of this, the research highlighted the need for strategies to address the discomfort or inconvenience associated with implementing environmentally friendly consumer behaviors. The implications of the study suggest that interventions or solutions are necessary to alleviate barriers and promote a more seamless integration of eco-friendly practices into consumers' daily routines.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.