• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.2977-2997
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• 2018

In big data era, fresh data grows rapidly every day. More than 30,000 gigabytes of data are created every second and the rate is accelerating. Many organizations rely heavily on real time streaming, while big data stream computing helps them spot opportunities and risks from real time big data. Storm, one of the most common online stream computing platforms, has been used for big data stream computing, with response time ranging from milliseconds to sub-seconds. The performance of Storm plays a crucial role in different application scenarios, however, few studies were conducted to evaluate the performance of Storm. In this paper, we investigate the performance of Storm under different application scenarios. Our experimental results show that throughput and latency of Storm are greatly affected by the number of instances of each vertex in task topology, and the number of available resources in data center. The fault-tolerant mechanism of Storm works well in most big data stream computing environments. As a result, it is suggested that a dynamic topology, an elastic scheduling framework, and a memory based fault-tolerant mechanism are necessary for providing high throughput and low latency services on Storm platform.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2006.02a
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• pp.78-78
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• 2006

Gene expression analysis can be performed by one-color (intensity-based) or two-color (ratio-based) microarray platforms depending on the specific applications and needs of the researcher. The traditional two-color approach is well founded from a historical and scientific standpoint, and the one-color approach, when paired with high quality microarrays and a robust workflow, offers additional flexibility in experimental design. Two of the major requirements of any microarray platform are system reproducibility, which provides the means for high confidence experiments and accurate comparison across multiple samples; and high sensitivity, for the detection of significant gene expression changes, including small fold changes across multiple gene sets. Each of these requirements is fulfilled by the Agilent One-color Gene Expression Platform as illustrated by the data included in this study. As a result, researchers have the ability to take advantage of the enhanced performance and sensitivity of Agilent's 60-mer oligonucleotide microarrays, and experience the first commercial microarray platform compatible with both one- and two-color detection.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.951-960
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• 2021

The paper aims to explain the influence of celebrity endorser on consumers' purchase intention, and explain the influence of brand perception on purchase decision in regard to the case of OPPO F-series and singer Son Tung MTP, in the Vietnamese context. Advertisement is regarded as the fastest and most effective communication method for brands to build an association and attract their target consumers. Among various types of communication tools, the use of celebrity endorsement is considerably growing owing to the explosion of social platforms. This study employs survey data from 258 people living and working in Ho Chi Minh City, Vietnam. Then, those data were used to analyze the general hypotheses by conducting research reviews based on foregoing investigations. The results from data analysis reveal that celebrity's physical attractiveness, credibility, popularity, expertise, match-up, and multiple endorsements all have positive impacts on purchase intention. The findings from this study would suggest that brands, in general, and smart-phone brands, in particular, should not only focus on these attributes to select a suitable brand endorser, but also need to predict some potential risks when utilizing celebrity endorsement. Finally, various implications and recommendations for further studies and marketers are also discussed.

• Smart Structures and Systems
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• v.31 no.1
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• pp.69-78
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• 2023

The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.83-94
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• 2016

Recent cloud, big data, there is a problem for the architectural security vulnerability to the server platforms of various fields such as artificial intelligence occurs consistently, but using the virtualization technology. In addition, most secure virtualization technology is known to be dependent on the type is limited and the platform provider. This paper presents a method for mutual authentication for secure data between multiple instances of a shared virtualized environment. The proposed method was designing a security architecture in consideration of the mutual authentication between multiple independent instances, and enhance the safety of a security protocol for sharing data by applying a key chain techniques. Performance analysis results and the existing security architecture demonstrated that protect each virtualized instances of the session and the other way, a compliance effectiveness for each instance of the mutual authentication process.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.161-172
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• 2006

As the innovative technologies related to ubiquitous computing are being rapidly developed in recent IT trend, the concern for IT dysfunction(e.g., personal information abuse, information risk, threat, vulnerability, etc.) are also increasing. In our study, we suggested how to design and implement to multiple schemes for strong authentication mechanism in real system environments. We introduce the systematic and secure authentication technologies that resolve the threats incurring from the abuse and illegal duplication of financial transaction card in the public and financial institutions. The multiple schemes for strong authentication mechanism applied to java technology, so various application programs can be embedded, Independent of different platforms, to the smartcard by applying the consolidated authentication technologies based on encryption and biometrics(e.g., finger print identification). We also introduce the appropriate guidelines which can be easily implemented by the system developer and utilized from the software engineering standpoint of view. Further, we proposed ways to utilize java card based biometrics by developing and applying the 'smartcard class library' in order for the developer and engineers involved in real system environment(Secure entrance system) to easily understand the program. Lastly, we briefly introduced the potential for its future business application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.714-721
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• 2020

DNN is expanding its use in embedded systems such as robots and autonomous vehicles. For high recognition accuracy, computational complexity is greatly increased, and multiple DNNs are running aperiodically. Therefore, the ability processing multiple DNNs in embedded environments is a crucial issue. Accordingly, multicore based platforms are being released. However, most DNN models are operated in a batch process, and when multiple DNNs are operated in multicore together, the execution time deviation between each DNN may be large and the end-to-end execution time of the whole DNNs could be long depending on how they are allocated to the cores. In this paper, we solve these problems by providing a framework that decompose each DNN into individual layers and then distribute to multicores through a global queue. As a result of the experiment, the total DNN execution time was reduced by 31%, and when operating multiple identical DNNs, the deviation in execution time was reduced by up to 95.1%.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.159-178
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• 2013

We present a model, combining servitization decision and a conventional two-sided market approaches, to understand expected outcomes and current market situations. We suppose an individual manufacturer participates in multiple platforms and decides whether to initiate servitization by considering latent profitability and risk. The analytical results from the model show that increasing competition within servitized companies lead to a servitization equilibrium, wherein the ratio of servitized companies in a market is stable, due to a gradual decline in relative benefits compared to non-servitized companies. This holds even in the case that the number of customer is increasing along the diffusion of servitization, under some restricted conditions.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.281-288
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• 2018

Crowdfunding has seen an enormous rise, becoming a new alternative funding source for emerging startup companies in recent years. Despite the huge success of crowdfunding, it has been reported that only around 40% of crowdfunding campaigns successfully raise the desired goal amount. The purpose of this study is to investigate key factors influencing successful fundraising on crowdfunding platforms. To this end, we mainly focus on contents of project campaigns, particularly their linguistic cues as well as multiple features extracted from project information and multimedia contents. We reveal which of these features are useful for predicting success of crowdfunding campaigns, and then build a predictive model based on those selected features. Our experimental results demonstrate that the built model predicts the success or failure of a crowdfunding campaign with 86.15% accuracy.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.765-773
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• 2016

As multimedia content technology developed, there are many cases that service contents are being provided in many different ways in the cloud-based media service system. A DRM is a technology that can enhance the copyright of the digital content by providing right information. It is available on a single platform and has a problem that the additional cost when the platform is changing. In this paper, we propose a media service system based on cloud computing. It can be used on multiple platforms at the same time by applying a number of DRM for digital contents, and allows use of a new authentication for another platform without any additional cost.