• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.59-66
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• 2010

We present a personalized clothing recommender system - one that mines association rules from transaction described in ontologies and infers a recommendation from the rules. The recommender system can forecast frequently changing trends of clothing using the Onto-Apriori algorithm, and it makes appropriate recommendations for each users possible through the inference marked as meta nodes. We simulates the rule generator and the inferential search engine of the system with focus on accuracy and efficiency, and our results validate the system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.367-369
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• 2022

With the development of web technology, the web provides customized information that meets the needs of users. Information is provided according to the input form and the user's query, and a web service that provides information that is difficult to search with a search engine is called an in-depth web. These deep webs contain more information than surface webs, but it is difficult to collect information with general crawling, which collects information at the time of the visit. The deep web provides users with information on the server by running script languages such as javascript in their browsers. In this paper, we propose an algorithm capable of exploring dynamically changing websites and collecting information by analyzing scripts for deep web collection. In this paper, the script of the bulletin board of the Korea Centers for Disease Control and Prevention was analyzed for experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• Convergence Security Journal
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• v.24 no.2
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• pp.63-70
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• 2024

With the development of artificial intelligence technology, our lives are changing in innovative ways, but at the same time, new ethical issues are emerging. In particular, issues of discrimination due to algorithm and data bias, deep fakes, and personal information leakage issues are judged to be social priorities that must be resolved as artificial intelligence services expand. To this end, this paper examines the concept of artificial intelligence and ethical issues from the perspective of artificial intelligence ethics, and includes each country's ethical guidelines, laws, artificial intelligence impact assessment system, artificial intelligence certification system, and the current status of technologies related to artificial intelligence algorithm transparency to prevent this. We would like to examine and suggest institutional improvement measures to strengthen artificial intelligence ethics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.3
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• pp.13-23
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• 2024

For the purpose of predicting credit card customer churn accurately through data analysis Detecting and tracking objects in continuous video is essential in self-driving cars, security and surveillance systems, sports analytics, medical image processing, and more. Correlation tracking methods such as Normalized Cross Correlation(NCC) and Sum of Absolute Differences(SAD) are used as an effective way to measure the similarity between two images. NCC, a representative correlation tracking method, has been useful in real-time environments because it is relatively simple to compute and effective. However, correlation tracking methods are sensitive to rotation and size changes of objects, making them difficult to apply to real-time changing videos. To overcome these limitations, this paper proposes an object tracking method using the Histogram of Oriented Gradients(HOG) feature to effectively obtain object data and the Convolution Neural Network(CNN) algorithm. By using the two algorithms, the shape and structure of the object can be effectively represented and learned, resulting in more reliable and accurate object tracking. In this paper, the performance of the proposed method is verified through experiments and its superiority is demonstrated.

• Journal of IKEEE
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• v.18 no.4
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• pp.544-551
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• 2014

This paper suggests an algorithm to measure low-level radiation by radiation measuring devices, and the other algorithm to improve reaction speed of the device to better respond to dramatic changes in radiation amount. The former algorithm to improve the accuracy of measuring low-level radiation takes advantage of a dual window radiation measurement method which is based on accumulated average of pulses gathered by a radiation measuring sensor. The latter algorithm is to enhance reaction speed of a measuring device to more sensitively react to dramatic changes in radiation amount by adopting a dual window radiation measurement method which analyzes data patterns newly put into for six seconds. To verify the suggested algorithms, a hardware-which consists of sensor and high-voltage generator, controller, charger and power supply circuit, wireless communication part, and display part-was used. Tests conducted on the dual window radiation measurement method as used in the suggested algorithm have proved that accuracy improves to measure low-level radiation of 5uSv/h, and linearity also gets better. Other tests were conducted to see whether the suggested algorithm enhances the reaction speed of a radiation measuring device so that the device responds better to dramatically changing radiation amount. The experimental results have shown meaningful changes in numbers after six seconds. Therefore, the conclusions are made that the algorithm enhances the reaction speed of the device.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.889-897
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• 2004

In this Paper, we propose the algorithm to provide stable communication in OFDM system under the highly interfered environment by the same/different systems which use same bandwidth or other jamming signal, i.e., radar signal. The proposed Adaptive Subcarrier Assignment(ASA) method first estimates the received power of each subcarrier in the block or fin or OFDM receiver. Then we estimate the threshold level which is the average power of the transmitted OFDM signal with AWGN. The highly interfered subcarriers, which are greater powers than the specified threshold level, are rejected in the next transmission and the only non-interfered subcarriers are selected as the next transmission. This algorithm provides stable communication in any OFDM systems without changing the physical layer under the highly interfered communication environment. We estimated the status of the subcarriers based on the bandwidth and power of the jamming signal and showed the performance of the proposed algorithm by the simulation.

• Journal of The Korean Association of Information Education
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• v.16 no.4
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• pp.463-474
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• 2012

The necessity of computer science education has been increased in the society which has been changing rapidly by the development of information science. But most elementary school teachers don't realize its necessity and don't recognize the notion of computational thinking which is the fundamental principle of computer science. In this research, we designed and implemented an algorithm learning program based on computational thinking with using Logo, which was for pre-service elementary school teachers to be able to realize the necessity of computer science education and recognize computational thinking. As the findings analyzed between pre- and post-test, the averages of correlational reasoning, combinatorial reasoning and the sum of overall logical thinking increased significantly. Also, participants' awareness of computer science education and computational thinking changed positively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.46-56
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• 2017

Recently, the spread of IoT technology has been spreading, and it has been applied to all industrial fields such as home / home appliance / medical care. Due to the low specification, low power consumption characteristic and communication data characteristic of IoT, implementation of existing algorithm is difficult thing. From this reason, we have proposed for the first time that encryption and decryption can be proceeded by introducing a kind of variable length bit XOR operation method which changes a variable the bit length value by using carry up and carry down method. We confirmed the practicality of encrypting short message data frequently processed by IoT device / QR code / RFID / NFC without changing the size of data before and after encryption.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1755-1760
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• 2016

Automation of greenhouses has proved to be extremely helpful in maximizing crop yields and minimizing labor costs. The optimum conditions for cultivating plants are regularly maintained by the use of programmed sensors and actuators with constant monitoring of the system. In this paper, we have designed a prototype of a smart greenhouse using Arduino microcontroller, simple yet improved in feedbacks and algorithms. Only three important microclimatic parameters namely moisture level, temperature and light are taken into consideration for the design of the system. Signals acquired from the sensors are first isolated and filtered to reduce noise before it is processed by Arduino. With the help of LabVIEW program, Time domain analysis and Fast Fourier Transform (FFT) of the acquired signals are done to analyze the waveform. Especially, for smoothing the outlying data digitally, Moving average algorithm is designed. With the implement of this algorithm, variations in the sensed data which could occur from rapidly changing environment or imprecise sensors, could be largely smoothed and stable output could be created. Also, actuators are controlled with constant feedbacks to ensure desired conditions are always met. Lastly, data is constantly acquired by the use of Data Acquisition Hardware and can be viewed through PC or Smart devices for monitoring purposes.