KSII Transactions on Internet and Information Systems (TIIS)
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v.15
no.5
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pp.1649-1665
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2021
In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.
Objectives: The aim of this study is to analyze cancer research trends in traditional Korean medical journals indexed in the Korea Citation Index since 2000. Methods: Cancer research papers published in traditional Korean medical journals were searched in databases from inception to October 2022. The numbers of publications by journal and by year were descriptively assessed. After natural language processing, topic modeling (based on Latent Dirichlet allocation) and keyword network analysis were conducted. Results: This research trend analysis involved 1,265 papers. Six topics were identified by topic modeling: case reports on symptom management, literature reviews, experiments on apoptosis, herbal extract treatments of breast carcinoma cell lines, anti-proliferative effects of herbal extracts, and anti-tumor effects. Keyword network analysis found that the effects of herbal medicine were assessed in clinical and experimental studies, while acupuncture was mainly mentioned in clinical reports. Conclusions: Cancer research papers in traditional Korean medical journals have contributed to evidence-based medicine. Further experimental studies are needed to elucidate the effects of on different hallmarks of cancer. Rigorous clinical studies are needed to support clinical guidelines.
Traditional sea Eel pots can be divided into two groups such as bamboo and plastic pots, however they are nearly same in a shape with one entrance and fishing efficiency, except their materials. Very few yet have been studied on their catching methods or catching mechanisms at the view point of behavior. Accordingly, we have designed tubular pots in order to fill up faults of traditional fishing gear construction and behaviors of sea eel. The suitable tubular pots was decided by comparative experiments in the water tank and the fishing efficiency was compared through the field experiments. The results obtained are as follows : 1. The differences between traditional plastic pots and improved tubular pots are firstly two entrances in both ends of tube without holes, secondly flapper nets are fixed at the end of each cone, and thirdly a bait bag is fixed at the center of pot. 2. The standard size of the suitable tubular pot is: $$Tube\;:\;\phi\;12\~13{\times}L80\;cm$$, $$Cone\;:\;Inside\;ring\;\phi6{\times}D5\;cm$$, Flapper : L10 cm. 3. The fishing efficiency of tubular rots is 2.3 times better than that of plastic pots.
Proceedings of the Korean Powder Metallurgy Institute Conference
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2006.09b
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pp.1018-1021
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2006
Powdered metal parts and components may be carburized successfully in a vacuum furnace by combining carburizing technology $VacCarb^{TM}$ with a hi-tech control system. This approach is different from traditional carburizing methods, because vacuum carburizing is a non-equilibrium process. It is not possible to set the carbon potential as in a traditional carburizing atmosphere and control its composition in order to obtain a desired carburized case. This paper presents test results that demonstrate that vacuum carburizing system $VacCarb^{TM}$ carburized P.M. materials faster than traditional steel with acceptable results. In the experiments conducted, PM samples with the lowest density and open porosity showed a dramatic increase in the surface carbon content up to 2.5%C and a 3 times deeper case. Currently the boost-diffusion technique is applied to control the surface carbon content and distribution in the case. In the first boost step, the flow of the carburizing gas has to be sufficient to saturate the austenite, while avoiding soot deposition and formation of massive carbides. To accomplish this goal, the proper gas flow rate has to be calculated. In the case of P.M. parts, more carbon can be absorbed by the part's surface because of the additional internal surface area created by pores present in the carburized case. This amount will depend on the density of the part, the densification grade of the surface layer and the stage of the surface. "as machined" or "as sintered". It is believed that enhanced gas diffusion after initial evacuation of the P.M. parts leads to faster carburization from within the pores, especially when pores are open . surface "as sintered" and interconnected . low density. A serious problem with vacuum carburizing is delivery of the carbon in a uniform manner to the work pieces. This led to the development of the different methods of carburizing gas circulation such as the pulse/pump method or the pulse/pause technique applied in SECO/WARWICK's $VacCarb^{TM}$ Technology. In both cases, each pressure change may deliver fresh carburizing atmosphere into the pores and leads to faster carburization from within the pores. Since today's control of vacuum carburizing is based largely on empirical results, presented experiments may lead to better understanding and improved control of the process.
Journal of the Korean Society for Library and Information Science
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v.53
no.2
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pp.179-199
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2019
In this paper, we propose optimal methodologies for classifying patent literature by examining various feature extraction methods, machine learning and deep learning models, and provide optimal performance through experiments. We compared the traditional BoW method and a distributed representation method (word embedding vector) as a feature extraction, and compared the morphological analysis and multi gram as the method of constructing the document collection. In addition, classification performance was verified using traditional machine learning model and deep learning model. Experimental results show that the best performance is achieved when we apply the deep learning model with distributed representation and morphological analysis based feature extraction. In Section, Class and Subclass classification experiments, We improved the performance by 5.71%, 18.84% and 21.53%, respectively, compared with traditional classification methods.
Proceedings of the Korean Society of Crop Science Conference
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2022.10a
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pp.75-75
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2022
Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.
Park, Young-Youn;Park, Chang-Geun;Choi, Young-Jean;Cho, Chun-Ho
Atmosphere
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v.17
no.4
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pp.435-453
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2007
KEOP (Korea Enhanced Observing Period)-2004 intensive summer observation was carried out from 20 June to 5 July 2004 over the Southwestern part of the Korean peninsula. In this study, the effects of KEOP-2004 intensive observation data on the simulation of precipitation system are investigated using KLAPS (Korea Local Analysis and Prediction System) and PSU/NCAR MM5. Three precipitation cases during the intensive observation are selected for detailed analysis. In addition to the control experiments using the traditional data for its initial and boundary conditions, two sensitivity experiments using KEOP data with and without Jindo radar are performed. Although it is hard to find a clear and consistent improvement in the verification score (threat score), it is found that the KEOP data play a role in improving the position and intensity of the simulated precipitation system. The experiments started at 00 and 12 UTC show more positive effect than those of 06 and 18 UTC. The effect of Jindo radar is dependent on the case. It plays a significant role in the heavy rain cases related to a mesoscale low over Changma front and the landing of a Typhoon. KEOP data produce more strong difference in the 06/18 UTC experiments than in 00/12 UTC, but give more positive effects in 00/12 UTC experiments. One of the possible explanations for this is that : KEOP data could properly correct the atmosphere around them when there are certain amounts of data, while gives excessive effect to the atmospheric field when there are few data. CRA analysis supports this reasoning. According to the CRA (Contiguous Rain Area) analysis, KEOP data in 00/12 UTC experiments improve only the surrounding area, resulting in essentially same precipitation system so the effects remain only in each convective cell rather than the system itself. On the other hand, KEOP data modify the precipitation system itself in 06/18 UTC experiments. Therefore the effects become amplified with time integration.
International Journal of Computer Science & Network Security
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v.22
no.10
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pp.374-388
/
2022
Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.
Hyo-Eun Son;Young-Sik Kim;YongBin Kim;SeonTae Na;HongJun Kim
Herbal Formula Science
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v.31
no.4
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pp.373-388
/
2023
Objectives : This study aimed to provide basic data for research by investigating non-clinical experimental studies on herbal medicines and its compounds for precocious puberty. Methods : A search was conducted for all literature until October 2023 using combinations of keywords such as precocious puberty, puberty, and chinese medicine in three databases (Pubmed, OASIS, and ScienceON). Results : 1. In animal experiments, studies were mainly conducted using a model that induced precocious puberty by subcutaneously administering danazol to SD rats on the 5th day after birth, and in cell experiments, precocious puberty was induced by treating GT1-7 cells with kisspeptin 10 or estradiol. 2. Anemarrhenae Rhizoma, Phellodendri Cortex, and Prunellae Spica were mainly used as herbal medicine to evaluate their efficacy on precocious puberty in non-clinical experiments. 3. Macroscopic observation, hematological analysis, histological analysis, and genetic analysis were performed as methods to analyze the experimental results. Conclusions : In this study, the effects of herbal medicine on precocious puberty and non-clinical research methods were confirmed. Based on the results of this study, it is expected that non-clinical effectiveness and mechanism research on materials that are clinically effective in Traditional Korean Medicine will be revitalized.
It has been widely said in Korea that early administrations of Cervi cornu parvum (deer antler) to febrile infants affect brain functions. Traditional Oriental Medicine states that the head is easily affected by fever and only an excess of heat causes headaches. Traditional Oriental Medicine also states that Cervi cornu parvum cannot be used in febrile conditions. With the aim of investigating different febrile response to LPS, experiments using intravenous injection of LPS have been carried out on Cervi comu parvum(CCP) and Soahbohyul - tang combined with Cervi comu parvum(SB-CCP) administered rabbits. Experiments were also conducted to evaluate the effects of early administration of CCP on learning and memory in 3 week old rats with LPS fever. These were evaluated by using the Morris water maze and the radial arm maze. Changes in body weight were also observed during this period. The results of these experiments are as follows. 1. In the experiments with febrile rabbits, the CCP and SB-CCP administered group showed statistically significant reductions of fever (p<0.05). 2. In the experiments with febrile rabbits, CCP and SB-CCP administered rabbits resulted in the tendency of lower body temperatures and shorter fever periods than the control group. 3. There were no differences of mean body weight and fever patterns among the 4 groups in the experiments on young rats with LPS fever. 4. There was no statistical difference of mean response latencies among the rats in Group I (DDW administered), GroupIII (CCP administered), and groupIV (SB-CCP administered) in the Morris water maze. However, Group Ⅱ (the scopolamine administered group) showed delayed latencies on the second day of the first session (p<0.05), and the second and third day of the second session (p< 0.05). 5. There were no statistical differences of mean response latencies among the rats in Group I, III and Ⅳ in the radial arm maze, but Group Ⅱ showed delayed latencies on the first and third day of the first session (p<0.05). 6. There was no influence from the administration of CCP and SB-CCP on the general behavior of the rats in Irwin´s test. These results suggest that Cervi cornu parvum and Soahbohyul - tang combined with Cervi comu parvum have anti-pyretic actions on LPS fever. The results also suggest that these drugs have no influence on learning and memory in young rats with LPS fever in the Morris water maze and the radial arm maze.
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