• The Journal of the Convergence on Culture Technology
• /
• 제9권4호
• /
• pp.611-616
• /
• 2023

ECG(electrocardiogram) is a test used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, the noise of the ECG signal was removed using the digital IIR Butterworth low-pass filter. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, was compared using the deep learning model of LSTM, it was confirmed that the activation function with the smallest error was the tanh() function. Also, When the performance evaluation and elapsed time were compared for LSTM and GRU models, it was confirmed that the GRU model was superior to the LSTM model.

• The Journal of the Convergence on Culture Technology
• /
• 제9권4호
• /
• pp.563-568
• /
• 2023

ECG(electrocardiogram) is used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, Noise included in the ECG signal was removed by using a lowpass filter of the Digital FIR Hamming window function. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, which was confirmed that the activation function with the smallest error was the tanh() function, the elapsed time was longer when the batch size was small than large. Also, it was confirmed that result of the performance evaluation for the GRU model was superior to that of the LSTM model.

• The Journal of Bigdata
• /
• 제8권2호
• /
• pp.27-36
• /
• 2023

The logistics industry is becoming increasingly important as it is closely linked to our daily lives, storing and transporting the goods and resources that businesses and consumers need. With its growing importance, the logistics industry strives to provide efficient and sustainable services through innovations and artificial intelligence are being used to optimize logistics networks, make transport more environmentally friendly, and more. Research and improvements are being undertaken in various domains, such as logistics network optimization and environmentally friendly transportation through technological innovation and artificial intelligence; however, there still needs to be more research in certain aspects of the logistics industry. In particular, devising an optimized stowage plan for vehicle carriers, considering various factors, involves a significant degree of complexity and remains an under-researched area. This paper studies the loading and unloading algorithms that enable to quickly and efficiently establish stowage plans for vehicle carriers, reflecting a variety of considerations and rules for stowage planning.

• Journal of Intelligence and Information Systems
• /
• 제17권4호
• /
• pp.109-130
• /
• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of the Daesoon Academy of Sciences
• /
• 제27집
• /
• pp.201-243
• /
• 2016

This paper analyzes the research trends from 358 scholarly articles published in the Journal of Daesoon Academy of Sciences from the first published journal in 1996 to the most recent journal published on the 25^th of 2015 and proposes ideas for improvement. First of all, "The Journal of Daesoon Academy of Sciences" does not meet the standards required by the National Research Foundation, falling short of the most important conditions for the registration such as the periodicity and punctuality expected from academic journals. Furthermore, in terms of the Bibliometrical analysis, the number of articles published by the journal is decreasing and the consistency, with regards to rules and principles regulating publication details and bibliography formats, is nonexistent. Although various authors seemed to be meeting these criteria on the surface, the ratio of co-authored articles is too small. Securing researchers specializing in Daesoon Thought for expanding the size of the journal is important, but it is also important to diversify the research topics through exchanging ideas among researchers from various organizations. Here are some ideas for the improvement of the Journal of Daesoon Academy of Sciences: First, in order to meet the standards for punctuality and periodicity, it would be best to publish the journal twice a year with 12 to 15 articles. Second, the journal must become searchable through the creation of a database. Third, the key words and abstracts of articles must be written in Korean and English to facilitate the sharing of articles among researchers. Fourth, the journal must have a diverse and outstanding editorial board which takes into account the geographical situations of its board members. Fifth, the Journal must include articles on relevant topics that reflect the core topics of the Daesoon Thought and other studies. Sixth, articles must have a front page that contains bibliographical items to convey information to the reader. Seventh, it is essential that the journal have a clear publication date detailing the year, month, and day as well as a standard numbering scheme (i.e, Vol. and no).

• International Commerce and Information Review
• /
• 제18권3호
• /
• pp.3-21
• /
• 2016

The thesis examines genealogical study of various aspects to overcome lots of problems which come by when we execute SWIFTNet TSU BPO. Practical implications regarding the innovation of electronic trade infrastructure are as follows. First, the shipping documents in the SWIFTNet TSU BPO are directly sent to an importer by an exporter after the baseline is confirmed. With this process itself, therefore, the bank cannot secure the account receivable. When initiating the SWIFTNet TSU BPO deal, it is needed to set regulations on the bank's account receivable security in the contract. Second, the SWIFTNet TSU BPO should also have an institutionally unified sharing platform with security, stability and convenience. It other words, it is needed to develop services which meet e-payment paradigm and international environments through continued analysis on market changes and flow. Third, the SWIFTNet TSU is useful in terms of promptness, reduction of risk in foreign exchange payment, cost reduction. Therefore, the SWIFT should be perfectly united and linked among the banks, importer and exporter to make the SWIFTNet TSU more convenient in countries around the world. Fourth, the SWIFT should be approached from the aspect of expansion of network and creation of a new business model through analysis on these problems with a worldwide perspective. At the same time, it is necessary to build a cooperative system to share information and promote comprehensive management for efficient operation.

• Applied Microscopy
• /
• 제32권4호
• /
• pp.319-327
• /
• 2002

Salvinia natans, an unique water fern having a small rootless body, developed three different types of trichomes throughout the plant. The most peculiar type exhibiting rows of obvious, whitish, multicellular trichome clusters was noticed in the upper surface of the floating leaves. Eight to ten branches within a cluster extended ca. $370{\sim}420{\mu}m$ from the leaf surface. No stalk cell was found, however, four large epidermal cells were discernable at the base of four central branches in the cluster. Each branch consisted of $8{\sim}10$ obliquely-oriented small cells that gradually decreased in size toward the branch tip. The second type was found in the lower surface of the floating leaves, stems, and sporocarps. Multicellular uniseriate trichomes, ca. $430{\sim}980{\mu}m$ long, were distributed all over these structures. The tip of trichome was acicular, but a semi-spheric protuberance of approximately $24{\sim}32{\mu}m$ in diameter occurred at the base of each trichome. The protuberance appeared to be firmly attached to the side of the basal cell, however, internal connection to the trichome cell itself was uncertain. The third type was similar to the second in that multicellur uniseriate trichomes with acicular tip and a protuberance at the base were present. However, the trichomes were considerably long relative to the second type, and only occurred along the surface of highly dissected, submerged leaves. A majority of the trichomes exceeded more than 2 mm in length that hung downward in the water. Regardless of trichome type, all trichomes contained a huge central vacuole with very thin cytoplasm, resulting from the fusion of several vacuoles during early trichome development. The various densely-distributed trichomes formed in Salvinia natans probably play an important role in plant buoyancy.

• Applied Microscopy
• /
• 제36권2호
• /
• pp.73-82
• /
• 2006

Major contributions has been made in cellular ultrastructure studies with the use of high voltage electron microscopy (HVEM) and tomography. Applications of HVEM, accompanied by appropriate image processing, have provided great improvements in the analysis of three-dimensional cellular structures. In the present study, structural patterns of the crystalline bodies that are distinguished in mesophyll plastids of CAM-performing Sedum rotundifolium L., have been investigated using HVEM and tomography. Tilting, and diffraction pattern analysis were performed during the investigation. The titlting was performed at ${\pm}60^{\circ}\;with\;2^{\circ}$ increments while examining serial sections ranging from 0.125 to $1{\mu}m$ in thickness. The young plastids exhibited crystalline inclusion bodies that revealed a peculiar structural pattern. They were irregular in shape and also variable in size. Their structural attributes affected the plastid morphology. The body consisted of a large number of tubular elements, often reaching up to several thousand in number. The tubular elements typically aggregated to form a fluster The elements demonstrated either a parallel or lattice arrangement depending on the sectioning angle. The distance between the elements was approximately 20nm as demonstrated by the diffraction analysis. HVEM examination of the serial sections revealed an occasional fusion or branching of elements within the inclusion bodies. Finally, a three-dimensional reconstruction of the plastid crystalline bodies has been attempted using two different image processing methods.

• Korean Journal of Remote Sensing
• /
• 제31권3호
• /
• pp.205-214
• /
• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• The Journal of the Convergence on Culture Technology
• /
• 제6권3호
• /
• pp.457-462
• /
• 2020

Osteoporosis is a disease that occurs mainly in the elderly and increases the risk of fractures due to structural deterioration of bone mass and tissues. The purpose of this study are to assess the relationship between nutritional components and osteoporosis and to evaluate models for predicting osteoporosis based on nutrient components. In experimental method, association was performed using binary logistic regression, and predictive models were generated using the naive Bayes algorithm and variable subset selection methods. The analysis results for single variables indicated that food intake and vitamin B2 showed the highest value of the area under the receiver operating characteristic curve (AUC) for predicting osteoporosis in men. In women, monounsaturated fatty acids showed the highest AUC value. In prediction model of female osteoporosis, the models generated by the correlation based feature subset and wrapper based variable subset methods showed an AUC value of 0.662. In men, the model by the full variable obtained an AUC of 0.626, and in other male models, the predictive performance was very low in sensitivity and 1-specificity. The results of these studies are expected to be used as the basic information for the treatment and prevention of osteoporosis.