• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.40-50
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• 2021

Science museum are dealing with exhibits on field of changing science and technology, and previous research suggested that exhibits replacement should carried out at least every 5 years. In order to efficiently replace exhibits within a limited budget, various studies analyzed visitors' preferences to exhibits. Recently, studies use various technologies to collect the data on visitors' preferences automatically, but almost of studies had a high dependency on their visitors such as visitors needed to carry specific sub-devices in the museums for gathering data. As complementing the limitations of previous research, this study introduces the improved method which is able to automatically collect and quantify visitors' preferences to exhibits using TensorFlow, a deep learning technology. By the proposed analysis method, it was possible to collect 2,520 data of visitors' experience on exhibits in totality. Based on collected data, attraction power and holding power indicating the preference of visitors on exhibits were able to be calculated. The result also confirmed antecedent research conclusion that the attraction power and holding power of the exhibit which consists of 3 dimensional structures work are higher than other exhibits. As a conclusion, the proposed method will provide more convenient data collection method for detecting visitors' preference.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.52-64
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• 2019

This research was aimed at studying the situation, problems, and requirements for digital collection lifecycle management of Thai theses and dissertations. The mixed research method used was composed of: (1) Study of the problem and situation in which the qualitative method was applied. The research site covered 10 higher education institutions where the Thailand Digital Collection (TDC) project is operated. The informants were key administrative officers of the TDC project of each institution. In-depth and structured interviews were conducted on an individual basis to obtain the most accurate answers. (2) Study of requirements based on the quantitative research method to survey the requirements for the digital collection management system for Thai theses and dissertations from 84 purposively-selected TDC project officers and 527 end users selected by accidental sampling, totaling 611 samples. Research findings are as follow: (1) The study of the situation and problems of digital collection lifecycle management shows that Thai higher institutions systematically manage their digital collection. The management lifecycle is consistent with the Guidance documents for lifecycle management of ETDs, which included seven steps: program planning, creation, submission, and ingestion, access and retrieval of digital objects, archiving and preservation, evaluation and assessment, interoperation (creation of institutional collaboration), and development of link data. (2) The study of requirements for digital collection management of Thai theses and dissertations shows five system requirements: acquisition and gathering, digitization, metadata standards, management of rights, and storage and retrieval, all of which are at M (mandatory) and D (desirable) levels.

• Architectural research
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• v.20 no.4
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• pp.109-120
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• 2018

In the context of ever-faster urbanization, cities are becoming increasingly complex, and data collection to understand such complex relationships is becoming a very important factor. This paper focuses on the lighter weight of the method of collecting urban data, and studied how to use such complementary data collection using crowdsourcing. Especially, the method of converting mobile acceleration sensor information to urban trip information by combining with locational information was experimented. Using the parameters for transportation type classification obtained from the research, information was obtained and verified in Singapore and Zurich. The result of this study is thought to be a good example of how to combine raw data into meaningful behavior information.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.131-139
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• 2019

From 2019, software education has become a required subject for all elementary school students. However, many teachers are still unfamiliar with how the classes should be instructed. So this paper presented the meaning, detailed competencies and achievement standard in order to help in the collection, analysis and representation of data among the computational thinking that are key to software education. And it also suggested the applicability of the classes. The full course of the paper is summarized as follows. First, existing studies have summarized the meaning, detail and achievement standard of data related competencies. Based on this, a preliminary investigation was instructed. Pilot study carried out both FGI and closed questions at the same time. This was done in response to the survey's questionnaire reflecting the opinions of experts. Second, the results of the questionnaire generated as a result of the above were verified for validity, stability, and reliability among the PhD, PhD courses, software education teachers, and software education workers. Third, I developed and applied the five lessons as a class objective as 'Choosing collection method-Select the collection method according to the problem situation.', 'Searching for meaning of data-Understand what the analyzed data mean..', 'Using various expression methods-Use a variety of expression tools.' using the backward design model to integrate education, class, and assessment. As a result, the detailed competencies of data collection, analysis, and representation and achievement standard were presented. This may help in setting specific and specific criteria for what direction classes are recommended when planning data-related classes in elementary schools.

• Journal of Korean Public Health Nursing
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• v.19 no.2
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• pp.217-228
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• 2005

Purpose: The purpose of this study is to understand nursing students' experiences during clinical practice at a public health center. Method: This research used narrative inquiry far data collection. From April 2005 to June 2006, data collection was conducted by open-ended interview, questionnaire and close observation. The participants, who were student nurses, were willing to take part in this study. Results: On the basis of these data, the experiences of clinical practice at public health center were: 1) when the student nurses begin clinical practice at public health centers for the first time, most of the students feel fearful, nervous and stressed. They also mentioned having a hard time being polite to clients and the staff. 2) The students had new experiences at the health public center compared with clinical practice. Especially, the student nurses who were determined to be good nurses were doing home visiting care service. Not only did they have the opportunity to confirm their identity as nurses, but also the students change their career course from clinical nursing to public health nursing. 4) They reflected on themselves after home visiting care service. Conclusion: On the basis of these findings, the following recommendations are made. 1) Data collection and analysis are needed, net only through the narrative method, but also through other various qualitative methods. 2) Comparative study is necessary to enhance clinical experiences through the analysis of the interfering factors and the original experiences.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.1-10
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• 2004

A web robot is a software that has abilities of tracking and collecting web documents on the Internet(l), The performance scalability of recent web robots reached the limit CIS the number of web documents on the internet has increased sharply as the rapid growth of the Internet continues, Accordingly, it is strongly demanded to study on the performance scalability in searching and collecting documents on the web. 'Design of web robot based on Multi-Agent to speed up documents collection ' rather than 'Sequentially executing Web Robot based on the existing Fork-Join method' and the results of analysis on its performance scalability is presented in the thesis, For collection speedup, a Multi-Agent based web robot performs the independent process for inactive URL ('Dead-links' URL), which is caused by overloaded web documents, temporary network or web-server disturbance, after dividing them into each agent. The agents consist of four component; Loader, Extractor, Active URL Scanner and inactive URL Scanner. The thesis models a Multi-Agent based web robot based on 'Amdahl's Law' to speed up documents collection, introduces a numerical formula for collection speedup, and verifies its performance improvement by comparing data from the formula with data from experiments based on the formula. Moreover, 'Dynamic URL Partition algorithm' is introduced and realized to minimize the workload of the web server by maximizing a interval of the web server which can be a collection target.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.3-11
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• 2023

This research examines the need for a quantitative and objective method of calculating baseline productivity in the construction industry, which is known for its high volatility in performance and productivity. The existing literature's baseline productivity calculation methods rely heavily on subjective criteria, limiting their effectiveness. Additionally, data collection methods such as the "Five-minute Rating" are costly and time-consuming, making it challenging to collect detailed data at construction sites. To address these issues, this study proposes an objective baseline calculation method using unimpacted productivity BP, a work check sheet to systematically record detailed data, and a data collection and utilization process that minimizes cost and time requirements. This paper also suggests using unimpacted productivity BP and comparative analysis to address the objectivity and reliability issues of existing baseline productivity calculation methods.

• Journal of Ecology and Environment
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• v.30 no.2
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• pp.201-207
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• 2007

Researchers have used a variety of methods to measure patterns of animal movement, including the use of spatial data (mapping the position of a moving animal at specified intervals) and direct estimation of travel path length by pacing under a moving animal or group. I collected movement data from five groups of siamangs (Symphalangus syndactylus) using two different methods concurrently to estimate the effects of the method of data collection on estimates of daily path length (DPL). Estimates of DPL produced from spatial data collected at 15-minute intervals were 12% lower than estimates of DPL produced by pacing under the traveling animal. The actual magnitude of the difference was correlated with the travel distance, but there was no correlation between the proportional difference and the travel distance. While the collection of spatial data is generally preferable, as spatial data permit additional analyses of patterns of movements in two or three dimensions, the relatively small difference between the DPL's produced using different methods suggests that pacing is an acceptable substitute where the collection of spatial data is impractical. I also subsampled the spatial data at increasing time intervals to assess the effect of sampling interval on the calculation of daily path lengths. Longer sampling intervals produced significantly shorter estimates of travel paths than shorter sampling intervals. These results suggest that spatial data should be collected at short time intervals wherever possible, and that sampling intervals should not exceed 30 minutes. Researchers should be cautious when comparing data generated using different methods.

• Resources Recycling
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• v.26 no.5
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• pp.29-38
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• 2017

This study suggests optimal policy options for collection of used diapers through benchmarking of foreign countries and perception surveys. By conducting a survey, this study can identify the actual problems involved in the collection process and enhance the social acceptance toward diaper recycling policies. As a perception survey result, the economic burden of emission bags and sanitary issues were most important for the collection pilot test. Respondents thought that twice-a-week collection frequency was appropriate and that free emission bags might be preferable to participants. Currently municipal wastes are subject to waste management laws, which are applied by local governments. Diaper waste is categorized with municipal waste, so it seems to be treated by municipal waste systems. In terms of connection with government, possible alternatives were suggested to identify the relevant local government. Useful data could be obtained, to determine the economical viability of any future diaper recycling system implementation in the entire Seoul metropolis and adjacent areas of dense population.

• ETRI Journal
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• v.44 no.3
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• pp.426-437
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• 2022

To understand the multilateral characteristics of human behavior and physiological markers related to physical, emotional, and environmental states, extensive lifelog data collection in a real-world environment is essential. Here, we propose a data collection method using multimodal mobile sensing and present a long-term dataset from 22 subjects and 616 days of experimental sessions. The dataset contains over 10 000 hours of data, including physiological, data such as photoplethysmography, electrodermal activity, and skin temperature in addition to the multivariate behavioral data. Furthermore, it consists of 10 372 user labels with emotional states and 590 days of sleep quality data. To demonstrate feasibility, human activity recognition was applied on the sensor data using a convolutional neural network-based deep learning model with 92.78% recognition accuracy. From the activity recognition result, we extracted the daily behavior pattern and discovered five representative models by applying spectral clustering. This demonstrates that the dataset contributed toward understanding human behavior using multimodal data accumulated throughout daily lives under natural conditions.