• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.186-197
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• 2023

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.99-109
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• 2023

The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.639-644
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• 2024

Recent developments in the use of drones on battlefields, extending beyond reconnaissance to firepower support, have greatly increased the importance of technologies for early automatic drone identification. In this study, to identify an effective image classification model that can distinguish drones from other aerial targets of similar size and appearance, such as birds and balloons, we utilized a dataset of 3,600 images collected from the internet. We adopted a transfer learning approach that combines the feature extraction capabilities of three pre-trained convolutional neural network models (VGG16, ResNet50, InceptionV3) with an additional classifier. Specifically, we conducted a comparative analysis of the performance of these three pre-trained models to determine the most effective one. The results showed that the InceptionV3 model achieved the highest accuracy at 99.66%. This research represents a new endeavor in utilizing existing convolutional neural network models and transfer learning for drone identification, which is expected to make a significant contribution to the advancement of drone identification technologies.

• Journal of Internet Computing and Services
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• v.13 no.6
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• pp.41-53
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• 2012

Open educational resources(OER) enable the spread of mutual information exchange and provide advantages to both their users and institutions, such as reducing costs, improving content quality, and establishing relationships. The recent research on OER was about their connection to formal education, copyright trends, and corporate e-learning. There have been very few studies, however, on the utilization of OER and on the problems related to their practical use. Thus, this study was conducted for the purposes of analyzing the status of OER usage in education-related institutions and of providing suggestions for institution operation based on the analysis results, to promote the use of OER. A survey was conducted among more than 200 institutions in Asia, and the survey results showed that 'images and visual materials' are the most commonly used materials in Asia, and that the factors barring OER usage in the said region are 'lack of awareness', 'lack of skills', 'the absence of a reward system', and poor cooperation in participation. To promote OER usage, each institution should provide training courses about awareness, utilization skills, and copyrights. There is also a need to provide support for the establishment of reward systems and environments for OER usage. Finally, more active participation is required for inter-agency cooperation in OER sharing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.41-46
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• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Proceedings of the KSPS conference
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• 1997.07a
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• pp.176-178
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• 1997

To make a long story short I made up my mind to experiment with a multimedia approach to my classroom presentations two years ago because my ways of giving instructions bored the pants off me as well as my students. My favorite ways used to be sometimes referred to as classical or traditional ones, heavily dependent on the three elements: teacher's mouth, books, and chalk. Some call it the 'MBC method'. To top it off, I tried audio-visuals such as tape recorders, cassette players, VTR, pictures, and you name it, that could help improve my teaching method. And yet I have been unhappy about the results by a trial and error approach. I was determined to look for a better way that would ensure my satisfaction in the first place. What really turned me on was a multimedia CD ROM title, ELLIS (English Language Learning Instructional Systems) developed by Dr. Frank Otto. This is an integrated system of learning English based on advanced computer technology. Inspired by the utility and potential of such a multimedia system for regular classroom or lab instructions, I designed a simple but practical multimedia language learning laboratory in 1994 for the first time in Korea(perhaps for the first time in the world). It was high time that the conventional type of language laboratory(audio-passive) at Hahnnam be replaced because of wear and tear. Prior to this development, in 1991, I put a first CALL(Computer Assisted Language Learning) laboratory equipped with 35 personal computers(286), where students were encouraged to practise English typing, word processing and study English grammar, English vocabulary, and English composition. The first multimedia language learning laboratory was composed of 1) a multimedia personal computer(486DX2 then, now 586), 2) VGA multipliers that enable simultaneous viewing of the screen at control of the instructor, 3) an amplifIer, 4) loud speakers, 5)student monitors, 6) student tables to seat three students(a monitor for two students is more realistic, though), 7) student chairs, 8) an instructor table, and 9) cables. It was augmented later with an Internet hookup. The beauty of this type of multimedia language learning laboratory is the economy of furnishing and maintaining it. There is no need of darkening the facilities, which is a must when an LCD/beam projector is preferred in the laboratory. It is headset free, which proved to make students exasperated when worn more than- twenty minutes. In the previous semester I taught three different subjects: Freshman English Lab, English Phonetics, and Listening Comprehension Intermediate. I used CD ROM titles like ELLIS, Master Pronunciation, English Tripple Play Plus, English Arcade, Living Books, Q-Steps, English Discoveries, Compton's Encyclopedia. On the other hand, I managed to put all teaching materials into PowerPoint, where letters, photo, graphic, animation, audio, and video files are orderly stored in terms of slides. It takes time for me to prepare my teaching materials via PowerPoint, but it is a wonderful tool for the sake of presentations. And it is worth trying as long as I can entertain my students in such a way. Once everything is put into the computer, I feel relaxed and a bit excited watching my students enjoy my presentations. It appears to be great fun for students because they have never experienced this type of instruction. This is how I freed myself from having to manipulate a cassette tape player, VTR, and write on the board. The student monitors in front of them seem to help them concentrate on what they see, combined with what they hear. All I have to do is to simply click a mouse to give presentations and explanations, when necessary. I use a remote mouse, which prevents me from sitting at the instructor table. Instead, I can walk around in the room and enjoy freer interactions with students. Using this instrument, I can also have my students participate in the presentation. In particular, I invite my students to manipulate the computer using the remote mouse from the student's seat not from the instructor's seat. Every student appears to be fascinated with my multimedia approach to English teaching because of its unique nature as a new teaching tool as we face the 21st century. They all agree that the multimedia way is an interesting and fascinating way of learning to satisfy their needs. Above all, it helps lighten their drudgery in the classroom. They feel other subjects taught by other teachers should be treated in the same fashion. A multimedia approach to education is impossible without the advent of hi-tech computers, of which multi functions are integrated into a unified system, i.e., a personal computer. If you have computer-phobia, make quick friends with it; the sooner, the better. It can be a wonderful assistant to you. It is the Internet that I pay close attention to in conjunction with the multimedia approach to English education. Via e-mail system, I encourage my students to write to me in English. I encourage them to enjoy chatting with people all over the world. I also encourage them to visit the sites where they offer study courses in English conversation, vocabulary, idiomatic expressions, reading, and writing. I help them search any subject they want to via World Wide Web. Some day in the near future it will be the hub of learning for everybody. It will eventually free students from books, teachers, libraries, classrooms, and boredom. I will keep exploring better ways to give satisfying instructions to my students who deserve my entertainment.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.71-77
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• 2014

The equalization algorithm based on the cross-information potential concept and Dirac-delta functions (CIPD) has outstanding ISI elimination performance even under impulsive noise environments. The main drawback of the CIPD algorithm is a heavy computational burden caused by the use of a block processing method for its weight update process. In this paper, for the purpose of reducing the computational complexity, a new method of the gradient calculation is proposed that can replace the double summation with a single summation for the weight update of the CIPD algorithm. In the simulation results, the proposed method produces the same gradient learning curves as the CIPD algorithm. Even under strong impulsive noise, the proposed method yields the same results while having significantly reduced computational complexity regardless of the number of block data, to which that of the e conventional algorithm is proportional.

• The Journal of Korean Institute for Practical Engineering Education
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• v.1 no.1
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• pp.99-105
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• 2009

Computer-based learning with the access to World Wide Web has become a fundamental base for adopting beneficial education. It provides significant facilities such as animation and interactive processes that are not possible with textbooks. Web/Internet-enabled applications which is fully controlled and monitored from remote locations are extensively used by a number of Universities, national laboratories and companies for different kinds of applications all over the world. Continuous advances in computers and electronics coupled with drooping prices of hardware have made Web/Internet-based technologies less costly than before, particularly for educational organizations. Thus, it is more affordable to invest in these technologies that are essential for both expanding education over Web and further improving and advancing such technologies the application of remote virtual instruments will be demonstrated in this context along with experiments that can be adopted to be educational experimental lab for Engineering Education students.

• Journal of The Korean Association of Information Education
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• v.18 no.2
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• pp.345-356
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• 2014

Modern internet service is characterized as opening, sharing and participation based on Web2.0 so that users might actively participate in the internet environment. In this study, we suggested an instructional model based on precedent model of robot programming to promote positive interaction in Web2.0 environment. First, we figured out implications of precedent research through review the environmental features of Web2.0 and educational tools, robot programming learning model. Also, we suggest an instructional model using Web2.0 tools(cyworld, prezi, Mindmeister) for promoting interaction and applied it to learners. As a result, we have acquired positive results of robot programming education using Web2.0 tools. Most participants were evaluated that Web2.0 tool would be helpful to the overall robot programming course.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.181-189
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• 2013

In this paper, we introduce the fuzzy neural network based on the individual input space to design the pattern recognizer. The proposed networks configure the network by individually dividing each input space. The premise part of the networks is independently composed of the fuzzy partition of individual input spaces and the consequence part of the networks is represented by polynomial functions. The learning of fuzzy neural networks is realized by adjusting connection weights of the neurons in the consequent part of the fuzzy rules and it follows a back-propagation algorithm. In addition, in order to optimize the parameters of the proposed network, we use real-coded genetic algorithms. Finally, we design the optimized pattern recognizer using the experimental data for pattern recognition.