International conference on construction engineering and project management
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2022.06a
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pp.1001-1008
/
2022
As a part of the Smart Cities Mission, the Government of India in 2015 embarked upon the development of 100 existing cities as smart cities. In this study, the authors selected Ahmedabad city as the smart city development in India and presented project-level elements of the city based on the secondary data availability. At first, the authors focused on peer-reviewed articles, policy documents, and technical reports. Next, the authors collected the secondary data of project-level elements of the Ahmedabad city from the years 2015 to 2019. The findings show no significant improvement in the sewage system and waste collection as compared to the level of investment made in these sectors. The study showed that the water supply system outperformed revenue generation based on the government investment made in that sector. As a lesson learned, these findings indicate that significant improvement should be addressed in sewage management and waste collection. These study findings could help government officials, investors, developers, and city planners in making the appropriate decision before and during smart city execution. The lesson learned from this study could be used as a reference to improve revenue during the future smart city implication.
Journal of the Korean Society of Marine Environment & Safety
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v.30
no.3
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pp.263-274
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2024
The digitization of ship environments has increased the risk of cyberattacks on ships. The smartization and automation of ships are also likely to result in cyber threats. The International Maritime Organization (IMO) has discussed the establishment of regulations at the autonomous level and has revised existing agreements by dividing autonomous ships into four stages, where stages 1 and 2 are for sailors who are boarding ships while stages 3 and 4 are for those not boarding ships. In this study, the level of a smart ship was classified into LEVELs (LVs) 1 to 3 based on the autonomous levels specified by the IMO. Furthermore, a risk assessment for smart ships at various LVs in different risk scenarios was conducted The cyber threats and vulnerabilities of smart ships were analyzed by dividing them into administrative, physical, and technical security; and mitigation measures for each security area were derived. A total of 22 cyber threats were identified for the cyber asset (target system). We inferred that the higher the level of a smart ship, the greater the hyper connectivity and the remote access to operational technology systems; consequently, the greater the attack surface. Therefore, it is necessary to apply mitigation measures using technical security controls in environments with high-level smart ships.
Journal of Information Technology Applications and Management
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v.26
no.2
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pp.13-26
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2019
The purpose of this study is to examine the effect of each of the two technology acceptance factors(employees' attitude toward smart factory technology, and ease of smart factory technology use) on the introduction level of each of the three smart factory technologies (manufacturing big data technology, automation technology, and supply chain integration technology), and in turn, the effect of each of the three smart factory technologies on manufacturing performance. This study employed PLS statistics software package to empirically validate a structural equation model with survey data from 100 domestic small-and medium-sized manufacturing firms (SMMFs). The analysis results revealed the followings. First, it is founded that employees' attitude toward smart factory technology influenced all of the three smart factory technology introduction levels in a positive manner. In particular, SMMFs of which employees had more favorable attitude toward smart factory technology tended to increase introduction levels of both automation technology and supply chain integration technology more than in the case of manufacturing big data technology. Second, ease of smart factory technology use also had a positive impact on each of the three smart factory technology introduction levels, respectively. A noteworthy finding is this : SMMFs which perceived smart factory technology as easier to use would like to elevate the introduction level of manufacturing big data technology more than in the cases of either automation technology or supply chain integration technology. Third, smart factory technologies such as automation technology and supply chain integration technology had affirmative impacts on manufacturing performance of SMMFs. These results shed some valuable insights on the introduction of smart factory technology : The success of smart factory heavily depends on organization-and people-related factors such as employees' attitude toward smart factory technology and employees' perceived ease of smart factory technology use.
Journal of the Korea Institute of Information and Communication Engineering
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v.23
no.6
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pp.733-739
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2019
Water level measurement is highly demanding in IoT monitoring areas such as smart factory, smart farm, and smart fish farm. However, existing water level indicators are limited to be used in industrial fields as commercial products due to the high cost of sensors and the complexity of algorithms used. In order to solve these problems, our paper proposed methods using an infrared distance sensor as well as a hall sensor for the water level measurement, both of which are contactless smart sensors. Data errors caused by the inaccuracy of existing sensors were decreased by applying new simple structures so that versatility is enhanced. The performance of our method was validated using experiments based on simulations. We expect that our new water depth indicator can be extended to a general-purpose water level monitoring system based on IoT technology.
Objective: This study aimed to examine the effects of maternal monitoring, shared activities with children, maternal education-oriented behavior, and allowing children to own smart-phones on smart media usage patterns based on smart-phone usage time and purposes among elementary school children. Methods: The participants were 1,315 second-grade elementary school children from the 9th wave of PSKC. Latent profile analysis and the three-step estimation approach were used to examine the determinants of the latent profile and the effects of maternal parenting on the profile. Results: Four latent profiles were identified: 'High-level usage & Entertaining oriented,' 'Moderate-level usage & Social/entertaining oriented,' 'Moderate-level usage & Learning oriented,' and 'Low-level usage.' Additionally, results showed that each profile can be predicted by maternal monitoring, education-oriented behavior, and permitting children to own smart-phones. Conclusion/Implications: Our outcomes suggested that it would be necessary to understand the smart media usage patterns of elementary school children, considering both the amount of time spent with smart media and purposes of uses. Further, it is helpful for mothers to monitor children's daily activities, support their educational activities, and take the role of gatekeeper for smart media as a way of appropriate guidance for their children's use of smart media.
This study examined the preference and the purchase intention of male and female from 20s through 405 to smart phones. This study verified the differences between the groups according to the socio-demographic factors, the usage pattern of mobile phone, and the perceived cost and the expected benefit. The analysis of the relative influence of those relevant factors was followed. The summaries of this study are as follows; First, the high level factors in purchasing smart phones were the perceived cost and the expected benefit pointed over 3.82. It means that they arc interested in smart phones highly, and if they can support to buy smart phones and situations can be permitted, they would like to buy them. Second, the differences between groups of the preference and the purchase intention were found according to the ages, the marital status and the education level. The results showed that those preference and the purchase intension were measured high at the group of the 20s-30s, the married, and the higher educational level of collage students. Third, expected benefit on smart phones was shown to be divided into two characterized factors through factor analysis. One was 'functional expected benefit' and the other was 'emotional expected benefit'. The functional and the emotional benefit on the using of smart phones were presented high level in group of over graduated students. Forth, the results of the stepwise multiple analysis, which was carried out to find out the influencing factors on the preference and the purchasing intension to smart phones, showed that the most effective factor was the functional expected benefit. The self-expressive propensity, and the education level were followed sequentially. The purchase intention was influenced by both of the functional and the emotional expected benefit. The result of this study shows that the level of the consumer's perceived cost(economic, psychological) and the expected benefit were measured high at the same time. That means that it is necessary to make the consumer information and communicating smoothly in order to lower the cost and enhance the benefit. In addition, This study has its meaning because it found out that functional expected benefit is a factor which has an influence on the Consumer Preference and Purchase Intention on Smart phone. If consumer's function requirements on smart phone are satisfied, it will be able to reduce the consumer problems and increase the consumer satisfaction. The result of this study would be applicable when Smart Phone is used as one of the auxiliary tools for smart consumption.
Journal of the Korean Society of Systems Engineering
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v.13
no.2
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pp.57-64
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2017
A new paradigm based on distributed manufacturing services is emerging. This paradigm shift can be realized by smart functions and smart technologies such as Cyber Physical System (CPS), Artificial Intelligence (AI), and Cloud Computing. Most architectures define stack levels from Level 0 (equipment) to Level 4 (business area) and specify the services to be provided between them. Because of their a rough technical specification, there is a limitation on how to actually utilize a technology to actually implement a smart factory service with this architecture. In this paper, we propose a smart factory architecture that can be utilized directly from the perspective of a smart service system by making the use of System Engineering Process and System Modeling Language (SysML).
Journal of Korea Society of Digital Industry and Information Management
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v.14
no.4
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pp.189-204
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2018
The purpose of this study is to examine an organizational performance difference by individual utilization level of the smart work. The Smart work help minimizing business process and improving organization productivity based on information technology. This new technology provides a flexible way of the task through smart-work center, videoconferencing, telecommuting, mobile(remote control) and business-only messenger. This investment changes organizational culture, institutions and behavior by new technology applying. The organization system change due to smart work has trouble between alteration preferences and existing maintains a group. In response, the organization should make investment justification of smart work for institutional and culture stabilized by a new system in organization. I set up the analytical process of four stages for empirical research. It will analyze an operation difference of the smart work between pre and post investment in the first-step analysis. The two-step analysis will conduct a text mining analysis of smart work operations. The three-step analysis will identify organization performance differences among individual levels in smart work. The four-step analysis will identify a factor difference in organizational performance by individual utilization level on smart work. According to the study, It has been revealed a difference between the pre and post investment performance on smart work. The text mining analyses many appeared an improvement opinion of organizational culture. Next, there is a difference in organization performance among utilize groups of smart work. Furthermore, the factors of organizational performance among groups appeared differently. The theoretical contribution of this study provided to expand the organizational theory of organization change and resistance. The practical implications provided to require a strong guideline an organizational culture and institution for smart work.
Hotels have recently started to implement enterprise information systems to measure and report sustainability indicators in a smart manner. However, a complex ownership structure in a hotel chain prevents full smart systems adoption at the individual property level. This study explores how a smart sustainability performance measurement system (SPMS) for waste management adoption correlates with customer ratings, customer reviews, operational efficiency scores, and between franchised and corporate-managed properties. We derive insights from the secondary data constructed from multiple sources for a large multinational hotel chain hotel. The findings suggest that hotels that adopt SPMS have better operational efficiency scores and more customer reviews. Within the hotels that adopted SPMS, corporate-managed hotels have a lower level of ratings than franchised hotels, but they have higher operational efficiency scores and more reviews. We discuss research implications for the concept of smart tourism and hotel management literature and managerial implications.
A smart leveling equipment was developed in this study by improving present leveling equipment. Both hardware and software of the equipment was developed and several accuracy tests of bench mark were conducted using various survey equipments. National control point (UO992-A), control points (15-00-06-24)-B and (15-00-06-23)-C were used for the accuracy test. As a result, the stable results in the range of errors were obtained in the cases of auto-level and digital level. Approximately 24mm error in the section of A-B and 26mm of B-C section was occurred in Smart Level equipment. This is due to the lack of technology completion and errors via relatively many numbers of installation tests. 46mm error of RMSE of smart level survey was occurred through the difference of section test. A small error was detected in short range but errors were accumulated far from the bench mark. It's concluded that an in-depth study emphasizing accuracy improvement can be practically applied to the various areas of industry.
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