• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.4
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• pp.109-120
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• 2001

Live load data were collected with a systematic manner from a survey of a refrigeration stores. Using the collected floor live load survey data, the basic statistics, a histogram of the uniformly distributed loads, and the equivalent uniformly distributed loads are computed for various structural members. Based on the above results, the maximum values of a combined live loads during the design life have been estimated and compared with current design live loads. The ultimate goals of this study are to develop probabilistic live load models to analyze survey data of domestic refrigeration stores, and to propose design live loads for structural types.

• Smart Structures and Systems
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• v.30 no.2
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• pp.145-157
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• 2022

The design of safe and economical structures depends on the reliable live load from load survey. Live load surveys are traditionally conducted by randomly selecting rooms and weighing each item on-site, a method that has problems of low efficiency, high cost, and long cycle time. This paper proposes a deep learning-based method combined with Internet big data to perform live load surveys. The proposed survey method utilizes multi-source heterogeneous data, such as images, voice, and product identification, to obtain the live load without weighing each item through object detection, web crawler, and speech recognition. The indoor objects and face detection models are first developed based on fine-tuning the YOLOv3 algorithm to detect target objects and obtain the number of people in a room, respectively. Each detection model is evaluated using the independent testing set. Then web crawler frameworks with keyword and image retrieval are established to extract the weight information of detected objects from Internet big data. The live load in a room is derived by combining the weight and number of items and people. To verify the feasibility of the proposed survey method, a live load survey is carried out for a meeting room. The results show that, compared with the traditional method of sampling and weighing, the proposed method could perform efficient and convenient live load surveys and represents a new load research paradigm.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.90-97
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• 2016

Purpose: Majority of bridges and roads in Gangwon Province have been carrying loads associated with heavy materials such as rocks, mining products, and cement. This location-specific live loads have contributed to the present situation of overloading, compared to other provinces in Korea. However, the bridges in Gangwon province are designed by national bridge design specification, without considering the location-specific live load characteristics. Therefore, this study focuses on the real traffic data accumulated on regional weighing station to verify the live load characteristics, including actual live load gross vehicle weight, axle weight axle spacings, and number of trucks. Methods: In order to take into account the location specific live load, a governmental weigh station (38th national highway Miro) have been selected and the passing truck data are processed. Based on the truck survey, trucks are categorized into 3 different shapes, and each shape has been idealized into normal distribution. Then, the resulting survey data are processed to predict the target maximum live load values, including the axle loads and gross vehicle weights in 75 years service life span. Results: The results are compared to the nationally used DB-24 live loads, and the results show that nationally recognized DB-24 live load does not sufficiently represent real traffic in mountaineous region in Gangwon province. Conclusion: The comparison results in the recommendation of location-specific live load that should be taken into account for bridge design and evaluation.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.4
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• pp.1-18
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• 2022

Purpose - Through the analysis and research of different characteristics and related mechanisms of live commerce anchors, this paper aimed to help live commerce anchors to strengthen their characteristic advantages, beautify the live broadcast environment, improve resource allocation and enhance business performance, so as to help live commerce anchors to achieve better high-quality development. Research design, data, and methodology - This study was conducted by sample survey method on 361 live commercial anchors who have experience in using major online shopping malls for more than one year. Data analysis methods were frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structural equation model analysis. Result - Hypothesis 1 through Hypothesis 5 were all supported. The results of this study suggest that professionalism and mutual entertainment of live commercial anchors have a significant impact on business performance, survival strategy, resource allocation and environment selection. The resource allocation and environment selection of live commercial anchors play a mediating role in the professionalism and mutual entertainment of live commercial anchors on business performance and survival strategy. Conclusion -The results implied that the professionalism and inter entertainment of live commercial anchors have a positive impact on business performance and survival strategy. In the new situation, live commercial anchors should further improve their professionalism and mutual entertainment, so as to achieve better development.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.1-10
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• 2023

Purpose: This study investigated the relationship between product characteristics and customer purchase intention in live-streaming commerce. Research design, data and methodology: Six independent factors namely, scarcity, customization, discount, experimentalism, novelty, and informativeness were identified to analyze their effects on customer purchase intention in live-streaming commerce. The perceived value was accepted as a mediator between independent and dependent variables. Data were gathered from 643 respondents who experienced purchases in live-streaming commerce in China. Results: The results show that product characteristics strongly affect customer purchase intention, and perceived value plays an important mediating role in live-streaming commerce. Therefore, when developing a sales strategy in live-streaming commerce, product characteristics. Such as customization, discount, experimentalism, novelty, and information must be considered. Conclusions: The majority of live-streaming commerce research has focused on platform interactions and consumers. This study is meaningful in that it dealt with product characteristics and confirmed the mediating roles of perceived value in live-streaming commerce. The findings of this study have significant implications and offer valuable insights and practical guidance for both the academic community and practitioners engaged in the field of live-streaming commerce.

• Structural Engineering and Mechanics
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• v.76 no.1
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• pp.1-15
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• 2020

The aim of this paper is to simply present live load factor calculation methodology formulation with the addition of a simple new future load projection procedure to previously proposed two methods. For this purpose, Oregon Weigh-in-Motion (WIM) data were used to calculate live load factors by using WIM data. These factors were calculated with two different approaches and by presenting new simple modifications in these methods. A very simple future load projection method is presented in this paper. Using four different WIM sites with different average daily truck traffic (ADTT) volume, and all year data, live load factors were obtained. The live load factors, were proposed as a function of ADTT. ADTT values of these sites correspond to three different levels which are approximately ADTT= 5,000, ADTT = 1,500 and ADTT ≤ 500 cases. WIM data for a full year were used from each site in the calibration procedure. Load effects were projected into the future for the different span lengths considering five-year evaluation period and seventy-five-years design life. The live load factor for ADTT=5,000, AASHTO HS20 loading case and five-year evaluation period was obtained as 1.8. In the second approach, the methodology established in the Manual for Bridge Evaluation (MBE) was used to calibrate the live load factors. It was obtained that the calculated live load factors were smaller than those in the MBE specifications, and smaller than those used in the initial calibration which did not convert to the gross vehicle weight (GVW) into truck type 3S2 defined by AASHTO equivalents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.71-82
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• 2011

Live data in physical memory can be acquired by live forensics but not by harddisk file-system analysis. Therefore, in case of forensic investigation, live forensics is widely used these days. But, existing live forensic methods, that use command line tools in live system, have many weaknesses; for instance, it is not easy to re-analyze and results can be modified by malicious code. For these reasons, in this paper we explain the Windows kernel architecture and how to analyze physical memory dump files to complement weaknesses of traditional live forensics. And then, we design and implement the Physical Memory Dump Explorer, and prove the effectiveness of our tool through test results.

• Informatization Policy
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• v.30 no.2
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• pp.68-85
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• 2023

In this study, we collected data from live commerce streaming. Streamimg data were then categorized based on the degree of chatting activation, with the distribution of text responses generated by consumers analyzed. From a total of 2,282 streaming data on NAVER Shopping Live -which has the largest share in the domestic live commerce market- we selected 200 streaming data with the most active viewer responses and finally chose the streams that had steep increase or decrease in viewer responses. We synthesized variables from the existing literature on live commerce viewing intentions and participation motivations to create a table of variables for the purpose of the study. Then we applied them with events in the broadcast. Through this study, we identified which components of the broadcast stimulate the variables of consumer response found in previous studies, moreover, we empirically identified the motivations of consumers to participate in live commerce through data.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.31-51
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• 2020

During the last decade, social live streaming service like Periscope, Ustream, and YouNow has developed from a niche market into a mainstream activity. In this media environment, social live streaming service has a tremendous impact on the social behaviors of users. Despite the rapid development, there are a lack of studies to make better understand the media environment changes through social live streaming service. This study adopted an affordances approach that leads us to identify six distinctive social affordances (visibility, accessibility, information sharing, social interaction, role-taking, interactive revenue) for user engagement in social live streaming service. Specifically, this study explores the impact of social affordances on perceived flow, followed by user engagement including passive and active engagement. Empirical data analysis with 258 questionnaires suggests that social affordances affected users' flow perception, and flow has an effect on active as well as passive engagement. Contrary to the expectation in a hypothesized research model, only the impact of accessibility on flow was rejected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5130-5143
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• 2019

Football (soccer) is one of the most popular sports in the world. A huge number of people watch live football matches by TV or Internet. A football match takes 90 minutes, but viewers may only want to watch a few highlights to save their time. As far as we know, there is no such a product that can be put into use to achieve intelligent highlight extraction from live football matches. In this paper, we propose an intelligent editing system for live football matches. Our system can automatically extract a series of highlights, such as goal, shoot, corner kick, red yellow card and the appearance of star players, from the live stream of a football match. Our system has been integrated into live streaming platforms during the 2018 FIFA World Cup and performed fairly well.