• International Journal of High-Rise Buildings
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• v.8 no.2
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• pp.101-106
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• 2019

Assessing the energy performance of supertall buildings often does not consider variations in energy consumption due to the change of environmental conditions such as temperature, pressure, and wind speed associated with differing elevations. Some modelers account for these changing conditions by using a conventional temperature lapse rate, but not many studies confirm to the appropriateness of applying it to tall buildings. This paper presents and discusses simulated annual energy consumption results from a 600 m tall skyscraper floor plate located in Dubai, UAE, assessed using ground level weather data, a conventional temperature lapse rate of $6.5^{\circ}C/km$, and more accurate simulated 600 m weather data. A typical office floorplate, with ASHRAE 90.1-2010 standards and systems applied, was evaluated using the EnergyPlus engine through the OpenStudio graphical user interface. The results presented in this paper indicate that by using ground level weather data, energy consumption at the top of the building can be overestimated by upwards of 4%. Furthermore, by only using a lapse rate, heating energy is overestimated by up to 96% due to local weather phenomenon such as temperature inversion, which can only be conveyed using simulated weather data. In addition, sizing and energy consumption of fans, which are dependent both on wind and atmospheric pressure, are not accurately captured using a temperature lapse rate. These results show that that it is important, with the ever increasing construction of supertall buildings, to be able to account for variations in climatic conditions along the height of the building. Adequately modeling these conditions using simulated weather data will help designers and engineers correctly size mechanical systems, potentially decreasing overall building energy consumption, and ensuring that these systems are able to provide the necessary indoor conditions to maintain occupant comfort levels.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.703-718
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• 2021

An irrigation monitoring system is an efficient approach to save water and to provide effective irrigation scheduling for rice cultivation in desert soils. This research aimed to design, fabricate, and evaluate the basic performance of an irrigation monitoring system based on information and communication technology (ICT) for rice cultivation under drip and micro-sprinkler irrigation in desert soils using a Raspberry Pi. A data acquisition system was installed and tested inside a rice cultivating net house at the United Arab Emirates University, Al-Foah, Al-Ain. The Raspberry Pi operating system was used to control the irrigation and to monitor the soil water content, ambient temperature, humidity, and light intensity inside the net house. Soil water content sensors were placed in the desert soil at depths of 10, 20, 30, 40, and 50 cm. A sensor-based automatic irrigation logic circuit was used to control the actuators and to manage the crop irrigation operations depending on the soil water content requirements. A developed webserver was used to store the sensor data and update the actuator status by communicating via the Pi-embedded Wi-Fi network. The maximum and minimum average soil water contents, ambient temperatures, humidity levels, and light intensity values were monitored as 33.91 ± 2 to 26.95 ± 1%, 45 ± 3 to 24 ± 3℃, 58 ± 2 to 50 ± 4%, and 7160-90 lx, respectively, during the experimental period. The ICT-based monitoring system ensured precise irrigation scheduling and better performance to provide an adequate water supply and information about the ambient environment.

• Geomechanics and Engineering
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• v.31 no.1
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• pp.113-127
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• 2022

The undrained shear strength of soil is considered one of the engineering parameters of utmost significance in geotechnical design methods. In-situ experiments like cone penetration tests (CPT) have been used in the last several years to estimate the undrained shear strength depending on the characteristics of the soil. Nevertheless, the majority of these techniques rely on correlation presumptions, which may lead to uneven accuracy. This research's general aim is to extend a new united soft computing model, which is a combination of random forest (RF) with grasshopper optimization algorithm (GOA) to the pile set-up parameters' better approximation from CPT, based on two different types of data as inputs. Data type 1 contains pile parameters, and data type 2 consists of soil properties. The contribution of this article is that hybrid GOA - RF for the first time, was suggested to forecast the pile set-up parameter from CPT. In order to do this, CPT data and related bore log data were gathered from 70 various locations across Louisiana. With an R² greater than 0.9098, which denotes the permissible relationship between measured and anticipated values, the results demonstrated that both models perform well in forecasting the set-up parameter. It is comprehensible that, in the training and testing step, the model with data type 2 has finer capability than the model using data type 1, with R² and RMSE are 0.9272 and 0.0305 for the training step and 0.9182 and 0.0415 for the testing step. All in all, the models' results depict that the A parameter could be forecasted with adequate precision from the CPT data with the usage of hybrid GOA - RF models. However, the RF model with soil features as input parameters results in a finer commentary of pile set-up parameters.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.871-879
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• 2022

An increasing global population requires a greater food supply, and accordingly there is demand for enhanced production of rice, as a major crop plant that covers half of the world's population. Rice production in arid area is extremely difficult due to poor soil fertility, salinity, deficit of irrigation water, and weather conditions. The aim of the present study was to determine whether various fertilization recipes could provide a countermeasure to allow rice production while also providing soil amendment such as soil pH adjustment. The study was conducted at an experimental field of the United Arab-Emirates (UAE) from January to April, 2022. Rice seedlings (cv. Asemi, alkaline-resistant) were transplanted in plastic containers, and different types of water and nutrient managements were employed as follows: water management (flooding and aerobic for NPKs treatment group) and nutrient management (NPKs, slow release fertilizers [SRFs] and SRFs + NPK-1 treatment groups with flooding). Water and nutrient management did not show any effect on soil pH adjustment. Rice growth was significantly enhanced in the flooding compared to the aerobic condition, whereas the effect of nutrient management clearly differed among the treatment groups, with SRFs + NPK-1 showing the best results followed by SRFs and NPKs. Most of the fertilization groups markedly accumulated soluble sugars in the shoots and grains of rice plants, but concomitantly a decrease in the roots. Overall, the level of starch showed a tendency of relatively slight perturbation by fertilization. Taken together, the results indicate that soil physical structure should be preferentially amended to find the key for suitable rice production.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.6
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• pp.599-614
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• 2014

When tunnelling with TBM (Tunnel Boring Machine), accessibility to tunnel face is very limited because tunnel face is mostly occupied by a bunch of machines. Existing techniques that can predict ground condition ahead of TBM tunnel are extremely limited. In this study, the TBM Resistivity Prediction (TRP) system has been developed for predicting anomalous zone ahead of tunnel face utilizing electrical resistivity. The applicability and prediction accuracy of the developed system has been verified by performing field tests at subway tunnel construction site in which an EPB (Earth Pressure Balanced) shield TBM was used for tunnelling work. The TRP system is able to predicts the location, thickness and electrical properties of anomalous zone by performing inverse analysis using measured resistivity of the ground. To make field tests possible, an apparatus was devised to attach electrode to tunnel face through the chamber. The electrode can be advanced from the chamber to the tunnel face to fully touch the ground in front of the tunnel face. In the 1st field test, none of the anomalous zone was predicted, because the rock around the tunnel face has the same resistivity and permittivity with the rock ahead of tunnel face. In the 2nd field test, 5 m thick anomalous zone was predicted with lower permittivity than that of the rock around the tunnel face. The test results match well with the ground condition predicted, respectively, from geophysical exploration, or directly obtained either from drilling boreholes or from daily observed muck condition.

• Strategy21
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• s.41
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• pp.261-293
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• 2017

Nuclear power is a way of attaining an enormous amount of energy with relatively small amount of resources and after it has been introduced to the submarine since 1954, there are approximately 150 of nuclear powered submarine currently on a mission around the world. This is due to the maneuverability, mountability and covertness of nuclear submarines. However, there are other tasks, not only the high level of nuclear technology that are needed to be dealt with in order to construct nuclear powered submarine. The biggest task of all is to secure the enriched uranium. Accordingly, this research is about the way of enriching and securing the nuclear fuel that are used in the nuclear submarine with the characteristics, merits and demerits of the nuclear submarine. Due to the fact that the pressurized water reactor in South Korea is the reactor that was originally built for the development of nuclear powered submarine, many parts is designed to be suitable for the submarine propulsion. However, in order to apply this to submarine it is needed to consider additional requests such as the position of reactor, accident-coping system, radioactive covering, reactor output adjustment and ship's pitch and roll in order to apply this to submarine. Nuclear submarines have much higher speed based on the powerful propulsion in comparison with diesel-electric submarine and also have bigger loading area. Besides, there is no need to snorkel and they also have advantages in covertness with the multi-noise proof system. The nuclear technology in South Korea has seen the dramatic development since 1962 and in 1998 reached to the level that we have succeeded in the localization of nuclear plant and exported the world-class one-piece small-sized reactor (SMART) to UAE. To operate these reactors, we import the whole quantity of low-enriched uranium and having our own uranium enrich facility is not probable because of the budget and international regulations. With the ROK/US nuclear agreement revised on 2015 November, the enrichment of uranium that are available without special permission has changed up to 20%. According to the assumption that we use the 20% enrichment of Uranium on U.S. virginia class submarine, it is necessary to change the fuel after 11 years and it will cause additional cost of 1 billion dollars. But the replace period by the uranium's enrichment rate is not fixed so that it is possible to change according to the design of reactor. Therefore, I would like to make a suggestion on two types of design concepts of nuclear submarine that can be operated for 30 years without nuclear fuel change by using the 20% enriched uranium from ONNp.First of all, it is possible by increasing the size of reactor by 3 times and it results in the 1,000t increase of the weight. And secondly, it is by designing the one piece reactor to insert devices such as steam turbine, condenser into the inside of nuclear core like the Rubis class submarines of France.

• Journal of Radiation Protection and Research
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• v.38 no.2
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• pp.100-105
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• 2013

With the export of commercial nuclear power plants to UAE and that of a research reactor to Jordan, as well as the additional construction of domestic nuclear power plants, the demand of nuclear manpower is expected to increase sharply. Accordingly, nuclear manpower development is recently becoming an important issue. Major institutes involved in nuclear programs are well equipped with education and training procedures and resources. However, small and medium sized businesses have difficulties to educate their employees due to their limited resources and capacity for the education. Addressing the difficulties, this study is intended to develop and education course in accordance with the "Systematic Approach to Training (SAT)". For this, a survey is conducted on the need of education in small and medium sized businesses, based on which a pilot course on the basics of radiation is developed and operated. An assessment on the development and operation using a survey regarding participants response has shown high grades of performance, i.e. above 4.0 points (full mark: 5.0 points) on each level of expectancy, satisfaction and lecturers' capacity. The experience from this study will be used to develop other programs of nuclear power and ASME code, which are also identified from the need analysis.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.117-124
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• 2013

Objective: This paper presents additional considerations related to organization and safety culture extracted from recent human error incidents in Korea, such as station blackout(i.e., SBO) in Kori#1. Background: Safety culture has been already highlighted as a major cause of human errors after 1986 Chernobyl accident. After Fukushima accident in Japan, the public acceptance for nuclear energy has taken its toll. Organizational characteristics and culture became elucidated as a major contributor again. Therefore many nuclear countries are re-evaluating their safety culture, and discussing any preparedness and its improvement. On top of that, there was an SBO in 2012 in the Kori#1. Korean public feels frustrated due to the similar human errors causing to a catastrophe like Fukushima accident. Method: This paper reassesses Japan's incidents, and revisits Korea's recent incidents. It focuses on the analysis of the hazards rather than the causes of human errors, the derivation of countermeasures, and their implementation. The preceding incidents and conclusions from Japanese experience are also re-analyzed. The Fukushima accident was an SBO due to the natural disaster such as earthquakes and a successive tsunami. Unlike the Fukushima accident, the Kori#1 incident itself was simple and restored without any loss and radioactive release. However, the fact that the incident was deliberately concealed led to massive distrust. Moreover, the continued violation of rules and organized concealment of the accident are serious signs of a new distorted type of human errors, blatantly revealing the cultural and fundamental weakness of the current organization. Result: We should learn from Japanese experiences who had taken pride in its safety technology and fairly high confidence in safety culture. Japan's first criticality accident in JCO facility splashed cold water on that confidence. It has turned out to be a typical case revealing the problems in the organization and safety culture. Since Japan has failed to gain lessons and countermeasure, the issue persists to the Fukushima incident. Conclusion: Safety culture is not a specific independent element, which makes it difficult to either evaluate it properly or establish countermeasures from the lessons. It may continue to expose similar human errors such as concealment of incident and manipulation of bad data. Application: Not only will this work establish the course of research for organization and safety culture, but this work will also contribute to the revitalization of Korea's nuclear industry from the disappointment after the export contract to UAE.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.24 no.1
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• pp.1-11
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• 2018

In this study, pro-oxidant($d2w^{(R)}$) and rPP/ZnO nanocomposite flexible films for food packaging were prepared, and their mechanical and antimicrobial properties were investigated. As a result, the carbonyl index and hydroxyl index increased with exposured time to heat and UV rays. Surface analysis showed that the addition of zinc oxide improved the dispersibility and compatibility of the polymer, so that the surface of the composite film was smooth and the zinc oxide particles were smaller than the compared film. And it kept the physical properties by heat and UV ray blocking effect, and it worked to reduce decomposition. In the antimicrobial activity test, the microbial reduction rate was 3 logs or more at the use concentration of zinc oxide. The tensile strength was increased and the elongation was decreased. Oxidative degradability of multi-layered film in UV exposured for 72 hours, the molecular weight of the film decreased by 75.6%, 1,294 g/mol Mn and 5,920 g/mol Mw. In the safety analysis of food packaging materials, we obtained that are in standard of polypropylene, a food contact material of domestic law.