A microgrid (MG) with integrated renewable energy resources can benefit both utility companies and customers. As a result, they are attracting a great deal of attention. The control of a MG is very important for the stable operation of a MG. The droop-control method is popular since it avoids circulating currents among the converters without using any critical communication between them. Traditional droop control methods have the drawback of an inherent trade-off between power sharing and voltage and frequency regulation. An adaptive droop control method is proposed, which can operate in both the island mode and the grid-connected mode. It can also ensure smooth switching between these two modes. Furthermore, the voltage and frequency of a MG can be restored by using the proposed droop controller. Meanwhile, the active power can be dispatched appropriately in both operating modes based on the capacity or running cost of the Distributed Generators (DGs). The global information (such as the average voltage and output active power of the MG and so on) required by the proposed droop control method to restore the voltage and frequency deviations can be acquired distributedly based on the Multi Agent System (MAS). Simulation studies in PSCAD demonstrate the effectiveness of the proposed control method.
Journal of Advanced Marine Engineering and Technology
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v.20
no.3
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pp.19-28
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1996
In Asia countries the productions of ship building and marine engines have been increasing, specially Japanese marine industries have worked hard after 1960s and Korean ones after 1980s. Recently the other countries, as Taiwan and China, have been working so that these hour Asian countries are occuping the high level of shared ratio of productions for gross tonnages and horse powers, which are 74 and 64[%] of the world ones ($8.6\times10$+6[GT], $8.6\times10$+6[PS]) in 1994. Korean industries had the highest shared ratio of production of tanker vessel and 2 stroke diesel engine as 45[%]($2.2\times10$+6[GT]) and 37[%]($1.0\times10$+6[PS]) which were more than those of Japan as 34 and 16[%] in 1989 respectively. Some marine databases and their network links among Asian countries are proposed due to the posibility of collection and analyses with their own specifications by the marine industries and operators as well as Japanese ship reliability investigation works(SRIW) like SRIC in Japan. During 1966 and 1996 16 times of SRIW in Japan have been carried out by ship reliability investigation group(SRIG) in Japan. There have been collected and evaluated a great number of field data of failures and maintenances($700\times10$+3[occ], $1.6\times10$+6[MH}) during running hours($13.4\times10$+6[Hrs]), from which many kinds of evaluation indices could be gotten as the three indices of occurring rate$\lambda$(52.2[occ/1000Hrs]), average man-hour mh(2.29[MH/occ]) and manning index MI(119[MH/1000Hrs]). An estimation example having the three indices$\lambda$, mh and MI were shown by the SRIC 1990 Data Base in Japan for the two kinds of fuel oil suppling subsystems which are dual fuel oil one(DFOS) and mono fuel oil one(MFOS). Three indices MI, and mh for DFOS and MFOS results in 7.16 and 5.20[MH/1000Hrs], 2.63 and 2.06[occ/1000 Hrs]. Therefore the more simple subsystem MFOS can save approximately 30[%] of maintenance load. Finlly an utilization methods are shown for the SRIC in Japan by means of computer system and worlwide internet links.
The possibility of circadian production of plant hormone gibberellin (GA0 was examined in phytochrome B mutant (plyB-1) and wild-type sorghum. GA$_{12}$, GA$_{20}$ and GA$_{1}$ levels were found to cycle circadianly in both phyB-1 and wild-type. The periods (33 h) of GA$_{20}$ and GA$_{1}$ cycling in constant light were longer than normal photoperiods in both genotypes and typical average free running periods in plants of 22 to 28 h. The biological clock was thus shown to function properly in phyB-1. However, circadian regulation of GAs productions were not clear as compared to circadian ethylene regulation reported by Lee (1996). Although, in sorghum, EOD FR treatment hasten floral inititation, the differences in GA concentrations between treatments and untreated control were generally less dramatic than expected. Thus, it can be concluded that FR does not act primarily by changing absolute levels of GAs but rather by increasing flowering responsiveness to GAs.
Cluster system provides attractive scalability in terms of compution power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive MPPs (massively parallel processors). Load balancing is very important issue since an inappropriate scheduling of tasks cannot exploit the true potential of the system and can offset the gain from parallelization. In parallel processing program, it is difficult to predict the load of each task before running the program. Furthermore, tasks are interdependent each other in many ways. The dynamic load balancing algorithm, which evaluates each processor's load in runtime, partitions each task into the appropriate granularity and assigns them to processors in proportion to their performance in cluster systems. However, if the communication cost between processing nodes is expensive, it is not efficient for all nodes to attend load balancing process. In this paper, we restrict a processor that attend load balancing by the communication cost and the deviation of its load from the average. We simulate various models of the cluster system with parameters such as communication cost, node number, and range of workload value to compare existing load balancing methods with the proposed dynamic algorithms.
International Journal of Computer Science & Network Security
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v.21
no.8
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pp.288-296
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2021
Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.
This study is a research study to determine the effect of online lecture substitution for subjects due to COVID-19 on self-directed learning ability, academic achievement, and online learning satisfaction of nursing students. From September to October 2020, the final 113 nursing students of data recovered as enrolled in the Department of Nursing at a university located in G City were analyzed. The data collected were analyzed by performing descriptive statistics and hierarchical regression analysis using the SPSS 21.0 program. The study results are summarized as follows. The average score of self-directed learning was 3.32±0.39, academic achievement 3.32±0.75, and learning satisfaction was 3.31±0.78. Factors affecting online learning satisfaction were found to be preferred learning methods and academic achievement. Based on the results of this study, it is necessary to design instruction and operate classes to improve online learning satisfaction by evaluating the learner's learning method in advance when running nursing school subjects as online lectures for nursing students.
Go, Woo-Seok;Yoon, Chun Gyeong;Rhee, Han-Pil;Hwang, Soon-Jin;Lee, Sang-Woo
Journal of Korean Society on Water Environment
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v.35
no.5
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pp.425-431
/
2019
Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.
The size of observation data in astronomy has been increasing exponentially with the advents of wide-field optical telescopes. This means the needs of changes to the way used for large-scale astronomy data analysis. The complexity of analysis tools and the lack of extensibility of computing environments, however, lead to the difficulty and inefficiency of dealing with the huge observation data. To address this problem, this paper proposes a workflow execution system for analyzing large-scale astronomy data efficiently. The proposed system is composed of two parts: 1) a workflow execution manager and its RESTful endpoints that can automate and control data analysis tasks based on workflow templates and 2) an elastic resource manager as an underlying mechanism that can dynamically add/remove virtualized computing resources (i.e., virtual machines) according to the analysis requests. To realize our workflow execution system, we implement it on a testbed using OpenStack IaaS (Infrastructure as a Service) toolkit and HTCondor workload manager. We also exhaustively perform a broad range of experiments with different resource allocation patterns, system loads, etc. to show the effectiveness of the proposed system. The results show that the resource allocation mechanism works properly according to the number of queued and running tasks, resulting in improving resource utilization, and the workflow execution manager can handle more than 1,000 concurrent requests within a second with reasonable average response times. We finally describe a case study of data reduction system as an example application of our workflow execution system.
Baek, Hae Sook;Lim, Sun Ha;Ahn, Ki Sung;Lee, Jong Won
The Korea Journal of Herbology
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v.28
no.3
/
pp.7-15
/
2013
Objectives : Interruption and subsequent restoration of blood flow into the kidney result in renal injury. As an approach to preventing the renal injury, we determined the optimal conditions and the underlying mechanisms by which supernatant of hot water extract of ground Triticum aestivum L. (extract) attenuated ischemia/reperfusion (I/R) injury. Methods : One hour after administration of the extract (400 mg/kg) by intraperitoneal injection, renal I/R injury was generated by clamping the left renal artery in rats after surgical removal of the right kidney, followed by reperfusion. The maximal difference between the vehicle-treated and the extract-treated group under ketamine/xylazine or enflurane anesthetization was assessed at varying periods of ischemia (30-45 min) and reperfusion (3-48 hr), based on the renal function assessed with serum creatinine levels, tissue injury with hematoxylin/eosin staining, and apoptosis with terminal deoxynucleotidyltransferase-mediated dUTP nick-end labeling staining. Results : Enflurane anesthetization with 40 min of ischemia and 24 hr of reperfusion was identified to be the optimal condition, under which condition serum creatinine levels and tubular damage in the extract-treated group were significantly reduced compared with those in the vehicle-treated group ($1.3{\pm}0.2$ versus $2.7{\pm}0.3$ mg/dL, P < 0.01, and average score $1.8{\pm}0.1$ versus $3.5{\pm}0.3$, P < 0.01, respectively). These beneficial effects were mediated by inhibition of apoptotic cascades through attenuation of renal tissue malondialdehyde levels, Bax/Bcl-2 ratio and caspase-3 levels. Conclusions : The extract conferred renal protection against ischemia/reperfusion injury in rats by scavenging reactive oxygen species and consequently blocking apoptotic cascades, plausibly augmented by enflurane protection.
The total number of Korean restaurants using delivery applications has substantially increased from 7.6% in 2018 to 11.2% in 2019. In 2020, the gross sales in the food delivery service market reached approximately 17 trillion won; this amount is virtually six times that in 2017 (i.e., 2 trillion won). Meanwhile, the annual average death toll of motorcycle riders increased by 3.5%, whereas the number of deaths due to other traffic accidents decreased by 8.2%. Consequently, the foregoing has become a critical social problem. Despite the continuing increase in the number of delivery riders due to the rapid expansion of the delivery industry, no appropriate safety management system has been established. Moreover, the government is experiencing difficulties in assessing the exact situation because of the absence of competent authority. In this study, fundamental data on the characteristics of delivery work and motorcycle accidents were collected through surveys and interviews; then, the influencing factors of traffic accidents were analyzed. Different influencing factors were identified: work experience as a rider; number of deliveries; whether to accept delivery requests in transit; manner of accepting delivery requests; and traffic law violations, such as speeding (for faster delivery) and running a red light. Because the motorcycle delivery industry has a relatively low job-entry barrier (i.e., special qualifications are not required), the riding skills of riders must be improved, and delivery companies must be technically developed to achieve a safe working environment. The results of this study can be utilized as fundamental data for system development or structural improvement of the delivery industry.
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