The intensification of the competition among container terminals has led to important affect such as, decision making or aggressive intervention of customers for terminal operation. Therefore, in case of developed ports, the large transition of port operation is composed of the press of terminal customer than decision making of terminal manager. Overall port tariffs for using terminal is made out by the conference of terminal customers than the supreme headquarters of terminal operation, and the related investment of terminal has been made according to requisition or proposal of customers. Therefore, among decision making problems that shippers, shipping companies, and freight forwarder among decision making problems that shippers, shipping companies, and freight forwarder face, the choice of the container terminal is one of the most important problems. So, the decision making of the users seems to have a significant impact on the competitive power of container terminals. The main objective of this study is to design port marketing strategy for strengthening the competitive power of container terminals. The results of this study were found as follows: Firstly, port authority should establish user-oriented operation policy of terminal as the means of activating the opinion window, using terminal monitoring system(TMS). Secondly, terminal planning and development of government should be made to minimize the lead time, to induce the civil capital and to utilize the economies of scale. Thirdly, port authority needs to endeavor to analyze the information of competing foreign terminals as well to promote the concentrated marketing for the terminal on the users, to train the expert and to develop the new port charge system. Fourthly, to improve the competitive power of the container terminal, Port Authority should optimize the subsystems related to port marketing, far more these systems should be joined organically to work effectively. Finally, port authority system should be introduced, Namely, port should have the enterprise inclination as well s the public inclination.
KSCE Journal of Civil and Environmental Engineering Research
/
v.26
no.6B
/
pp.605-612
/
2006
In this study(II), The developed rainfall forecast model was applied to the NakDong River Basin for the heavy rainfall on 6th to 16th of August in 2002. The results demonstrated that the rainfall forecasts of 3 hours lead time showed good agreement with observed data. The inundation aspect of simulation depends on actual levee failure in the same basin. Rainfall forecasts were used for flood amount computation in the target watershed. Also the flood amount in the target watershed was used on boundary condition for flood inundation simulation in a protected lowland and a river. The results of simulation are consistent with actuality inundation traces and flood level data of the target watershed. This study provides practical applicability of satellite data in rainfall forecast of extreme events such as heavy rainfall or typhoon. Also this study presented an advanced integrated model of rainfall, runoff, and inundation analysis which can be applicable for flood disaster prevention and mitigation.
Khan, Muhammad;Mccrary, Evan;Nnaji, Chukwuma;Awolusi, Ibukun
International conference on construction engineering and project management
/
2022.06a
/
pp.579-586
/
2022
Modular building is a fast-growing construction method, mainly due to its ability to drastically reduce the amount of time it takes to construct a building and produce higher-quality buildings at a more consistent rate. However, while modular construction is relatively safer than traditional construction methods, workers are still exposed to hazards that lead to injuries and fatalities, and these hazards could be controlled using emerging smart technologies. Currently, limited information is available at the intersection of modular construction, safety risk, and smart safety technologies. This paper aims to investigate what aspects of modular construction are most dangerous for its workers, highlight specific risks in its processes, and propose ways to utilize smart technologies to mitigate these safety risks. Findings from the archival analysis of accident reports in Occupational Safety and Health Administration (OSHA) Fatality and Catastrophe Investigation Summaries indicate that 114 significant injuries were reported between 2002 and 2021, of which 67 were fatalities. About 72% of fatalities occurred during the installation phase, while 57% were caused by crushing and 85% of crash-related incidents were caused by jack failure/slippage. IoT-enabled wearable sensing devices, computer vision, smart safety harness, and Augment and Virtual Reality were identified as potential solutions for mitigating identified safety risks. The present study contributes to knowledge by identifying important safety trends, critical safety risk factors and proposing practical emerging methods for controlling these risks.
Blockchains have recently struggled to design for the ideal distributed trust networks by solving scalability trilemma. However, local conflicts between some countries lead to imbalance on energy distribution. Besides, blockchain networks (e.g., Bitcoin) currently consume enormous energy for transaction and mining. The existing data volume based trust model evaluated an increasing blockchain size better than Lubin's trust model in scalability trilemma. In this paper, we propose a scalability based energy model to evaluate sustainability for blockchain networks, considering energy consumption for transaction, time duration, and the blockchain size of growing blockchain networks. Through the rigorous numerical analysis, we compare the proposed scalability based energy model with the existing model for the satisfaction and optimal blockchain size. Thus, the scalability based energy model will provide an assessment tool to choose the proper blockchain networks to solve scalability trilemma problem and prove sustainability.
Lee, Bo Young;Park, Mi-Young;Kim, Kirang;Shim, Jea Eun;Hwang, Ji-Yun
Korean Journal of Community Nutrition
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v.25
no.3
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pp.189-203
/
2020
Objectives: This study was performed to identify the current barriers of obesity management for children using Community Child Care Centers and their caregivers (parents and teachers working in the Centers). Further, this study explored the possibility of utilizing a mobile phone application for tailored obesity prevention and management programs to overcome the current difficulties associated with children's obesity management. Methods: The qualitative data were collected through in-depth interviews with 20 obese and overweight children or children who wanted to participate in this study using Community Child Care Centers, 12 teachers working at the Centers, and a focus group interview with five parents of children using the Centers. Data were analyzed with a thematic approach categorizing themes and sub-themes based on the transcripts. Results: The current barriers of obesity management of obese and overweight children using Community Child Care Centers were lack of self-directed motivation regarding obesity management (chronic obesity-induced lifestyles and reduced self-confidence due to stigma) and lack of support from households and Community Child Care Centers (latchkey child, inconsistency in dietary guidance between the Center and household, repetitive pressure to eat, and absence of regular nutrition education). Mobile phone applications may have potential to overcome the current barriers by providing handy and interesting obesity management based on visual media (real-time tracking of lifestyles using behavior records and social support using gamification), environmental support (supplementation of parental care and network-based education between the Community Child Care Center and household), and individualized intervention (encouragement of tailored and gradual changes in eating habits and tailored goal setting). It is predicted that the real-time mobile phone program will provide information for improving nutritional knowledge and behavioral skills as well as lead to sustainable children's coping strategies regarding obesity management. In addition, it is expected that environmental factors may be improved by network-based education between the Community Child Care Centers and households using the characteristics of mobile phones, which are free from space and time constraints. Conclusions: The tailored education program for children using Community Child Care Centers based on mobile phones may prevent and reduce childhood obesity by overcoming the current barriers of obesity management for children, providing environmental and individualized support to promote healthy lifestyles and quality of life in the future.
Recently, with the advent of applications using locations of moving objects, it becomes crucial to develop efficient index schemes for spatio-temporal databases. The $TPR^*$-tree is most popularly accepted as an index structure for processing future-time queries. In the $TPR^*$-tree, the future locations of moving objects are predicted based on the CBR(Conservative Bounding Rectangle). Since the areas predicted from CBRs tend to grow rapidly over time, CBRs thus enlarged lead to serious performance degradation in query processing. Against the problem, we propose a new method to adjust CBRs to be tight, thereby improving the performance of query processing. Our method examines whether the adjustment of a CBR is necessary when accessing a leaf node for processing a user query. Thus, it does not incur extra disk I/Os in this examination. Also, in order to make a correct decision, we devise a cost model that considers both the I/O overhead for the CBR adjustment and the performance gain in the future-time owing to the CBR adjustment. With the cost model, we can prevent unusual expansions of BRs even when updates on nodes are infrequent and also avoid unnecessary execution of the CBR adjustment. For performance evaluation, we conducted a variety of experiments. The results show that our method improves the performance of the original $TPR^*$-tree significantly.
In these day, many data including sensor, delivery, credit and stock data are generated continuously in massive quantity. It is difficult to learn from these data because they are large in volume and changing fast in their concepts. To handle these problems, learning methods based in sliding window methods over time have been used. But these approaches have a problem of rebuilding models every time new data arrive, which requires a lot of time and cost. Therefore we need very simple incremental learning methods. Bayesian method is an example of these methods but it has a disadvantage which it requries the prior knowledge(probabiltiy) of data. In this study, we propose a learning method based on attribute values. In the proposed method, even though we don't know the prior knowledge(probability) of data, we can apply our new method to data. The main concept of this method is that each attribute value is regarded as an expert learner, summing up the expert learners lead to better results. Experimental results show our learning method learns from data very fast and performs well when compared to current learning methods(decision tree and bayesian).
Non-invasive technique CT, called automated computed tomography, is used to detect lesion of a patient when diagnosing human body. Information obtained from CT plays an important role in assembling 3 dimensional images. Recently, new equipment, operated by CT, is required which can be appliable to physical and biological research. In accordance to this quest, micro-CT is invented that produce more detail and concrete information. Images supplied by CT are even more detailed and concrete, so it contributes much to the development of biology and polymer material engineering field. However, there has been little reliable reports regarding measuring information of space dose distribution about exposure dose limit of users operating micro-CT. In addition, little reports regarding space dose distribution of exposure has been known about unwanted diffraction light produced by usage of micro-CT. The exterior of micro-CT is covered by lead, which is for removing exposure of diffraction light. Thus, even if it is good enough to prevent exposure of diffraction light, consistent management of equipment will be required as time goes by and equipment are getting old as well. We measured space dose distribution regarding exposure of diffraction light of users operating micro-CT directly. Therefore, we suggest that proper management should be necessary for users operating micro-CT not to be exposed by unwanted diffraction light.
Journal of the Korea Society of Computer and Information
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v.19
no.4
/
pp.149-158
/
2014
The rapidly changing 21st-century knowledge and information society is emphasizing converged education that crosses various academic fields. In particular, the society expected the cultivation of the talent who balance scientific creativity and artistic sensitivity by adding arts to the existing converged education revolving around science and technology. However, at present, most STEAM education has been actively conducted with a focus on science and technology, whereas the subject of arts has been regarded or utilized as a supplementary means. Its problem is that the educational characteristics and values of art education have not been effectively utilized in educational terms and this could lead to superficial integrated education. In this respect, this study had the knowledge of various fields, such as science, technology, and mathematics, utilized usefully during the process of experiencing and creating arts. Accordingly, this study designed an education programs as with the case of Nam-Jun Baek who expanded the dominion of arts by creatively utilizing his own time's scientific technologies. In this educational process, the target program was developed in a manner that enables EPL to be utilized essentially as the study's knowledge-based tool and medium. The results of applying this educational program in 5th-grade elementary school students showed that the program has positive effects on the creative attributes of the students.
Journal of the Korea Society of Computer and Information
/
v.12
no.2
s.46
/
pp.231-242
/
2007
The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.
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