• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.3
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• pp.425-430
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• 2014

Foods contain various nutrients such as carbohydrates, protein, oil, vitamins, and minerals. Among them, carbohydrates, protein, and oil are the main constituents of foods. Usually, these constituents are analyzed by the Kjeldahl and Soxhlet method and so on. However, these analytical methods are complex, costly, and time-consuming. Thus, this study aimed to rapidly and effectively analyze carbohydrate, protein, and oil contents with near-infrared reflectance spectroscopy (NIRS). A total of 517 food samples were measured within the wavelength range of 400 to 2,500 nm. Exactly 412 food calibration samples and 162 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of carbohydrates, the most accurate equation was obtained under 1, 4, 5, 1 (1st derivative, 4 nm gap, 5 points smoothing, and 1 point second smoothing) math treatment conditions using the weighted MSC (multiplicative scatter correction) scatter correction method with MPLS (modified partial least square) regression. In the case of protein and oil, the best equation were obtained under 2, 5, 5, 3 and 1, 1, 1, 1 conditions, respectively, using standard MSC and standard normal variate only scatter correction methods with MPLS regression. Calibrations of these NIRS equations showed a very high coefficient of determination in calibration ($R^2$: carbohydrates, 0.971; protein, 0.974; oil, 0.937) and low standard error of calibration (carbohydrates, 4.066; protein, 1.080; oil, 1.890). Optimal equation conditions were applied to a validation set of 162 samples. Validation results of these NIRS equations showed a very high coefficient of determination in prediction ($r^2$: carbohydrates, 0.987; protein, 0.970; oil, 0.947) and low standard error of prediction (carbohydrates, 2.515; protein, 1.144; oil, 1.370). Therefore, these NIRS equations can be applicable for determination of carbohydrates, proteins, and oil contents in various foods.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• The Korean Journal of Air & Space Law and Policy
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• v.28 no.2
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• pp.3-35
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• 2013

Air transport today is a means of transport that is optimized for exchanges between nations. Around the world, has experienced an increase in operating and the number of airline route expansion that has entered into the international aviation agreements in order to take advantage of the air transport efficient, but the possibility of the occurrence of air transport accidents increased. When compared to the accident of other means of transport, development of air transport accidents, not high, but it leads to catastrophe aviation accident occurs. Air Transport accident many international transportation accident than domestic transportation accident, in the event of an accident, the analysis of the legal responsibility of the shipper or the like is necessary or passenger air carrier. Judgment of the legal order of discipline of air transport accident is a classification of the type of air transport agreement. Depending on the object, air transport agreements are classified into the contract of carriage of aviation of the air passenger transportation contract. For casualties occurs, air passenger transportation accident is a need more discussion of legal discipline for this particular. Korean Commercial Code, it is possible to reflect in accordance with the actual situation of South Korea the contents of the treaty, which is utilized worldwide in international air transport, even on the system, to control land, sea, air transport and welcoming to international standards. However, Korean Commercial Code, the problem of the Montreal Convention has occurred as it is primarily reflecting the Montreal Convention. As a cause of liability for damages, under the Commercial Code of Korea and the contents of the treaty precedent is reflected, the concept of accident is necessary definition of the exact concept for damages of passengers in particular. Cause of personal injury or death of passengers, in the event of an accident to the "working for the elevation" or "aircraft" on, the Montreal Convention is the mother method of Korea Commercial Code, liability for damages of air carrier defines. The Montreal Convention such, continue to be a matter of debate so far in connection with the scope of "working for the lifting of" the concepts defined in the same way from Warsaw Convention "accident". In addition, it is discussed and put to see if you can be included mental damage passenger suffered in air transport in the "personal injury" in the damage of the passenger is in the range of damages. If the operation of aircraft, injury accident, in certain circumstances, compensation for mental damage is possible, in the same way as serious injury, mental damage caused by aviation accidents not be able to live a normal life for the victim it is damage to make. So it is necessary to interpret and what is included in the injury to the body in Korea Commercial Code and related conventions, non-economic damage of passengers, clearly demonstrated from the point of view of prevention of abuse of litigation and reasonable protection of air carrier it must compensate only psychological damage that can be. Since the compensation of delay damages, Warsaw Convention, the Montreal Convention, Korea Commercial Code, there are provisions of the liability of the air carrier due to the delayed arrival of passenger and baggage, but you do not have a reference to delayed arrival, the concept of delay arrangement is necessary. The strict interpretation of the concept of delayed arrival, because it may interfere with safe operation of the air carrier, within the time agreed to the airport of arrival that is described in the aviation contract of carriage of passenger baggage, or, these agreements I think the absence is to be defined as when it is possible to consider this situation, requests the carrier in good faith is not Indian or arrive within a reasonable time is correct. The loss of passenger, according to the international passenger Conditions of Carriage of Korean Air, in addition to the cases prescribed by law and other treaties, loss of airline contracts, resulting in passengers from a service that Korean Air and air transport in question do damage was is, that the fact that Korean Air does not bear the responsibility as a general rule, that was caused by the negligence or intentional negligence of Korean Air is proof, negligence of passengers of the damage has not been interposed bear responsibility only when it is found. It is a clause in the case of damage that is not mandated by law or treaty, and responsible only if the negligence of the airline side has been demonstrated, but of the term negligence "for" intentional or negligent "Korean Air's Terms" I considered judgment of compatibility is required, and that gross negligence is appropriate. The "Korean Air international passenger Conditions of Carriage", airlines about the damage such as electronic equipment that is included in the checked baggage of passengers does not bear the responsibility, but the loss of baggage, international to arrive or depart the U.S. it is not the case of transportation. Therefore, it is intended to discriminate unfairly passengers of international flights arriving or departure to another country passengers of international flights arriving or departure, the United States, airlines will bear the responsibility for the goods in the same way as the contents of the treaty it should be revised in the direction.