• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.95-102
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• 2023

The emergence of Internet of Things (IoT) into our daily lives has grown rapidly. It's been integrated to our homes, cars, and cities, increasing the intelligence of devices involved in communications. Enormous amount of data is exchanged over smart devices through the internet, which raises security concerns in regards of privacy evasion. This paper is focused on the forensics and intrusion detection on one of the most common protocols in IoT environments, especially smart home environments, which is the Message Queuing Telemetry Transport (MQTT) protocol. The paper covers general IoT infrastructure, MQTT protocol and attacks conducted on it, and multiple network forensics frameworks in smart homes. Furthermore, a machine learning model is developed and tested to detect several types of attacks in an IoT network. A forensics tool (MQTTracker) is proposed to contribute to the investigation of MQTT protocol in order to provide a safer technological future in the warmth of people's homes. The MQTT-IOT-IDS2020 dataset is used to train the machine learning model. In addition, different attack detection algorithms are compared to ensure the suitable algorithm is chosen to perform accurate classification of attacks within MQTT traffic.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.13 no.2
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• pp.1-8
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• 2017

Outdoor design temperature is important for selecting proper capacity of heating and cooling systems of a building to implement indoor thermal comfort and save energy consumption. The purpose of this study is to investigate the change of South Korea outdoor design temperature according to the assigned period. When outdoor design temperature of 8 locations calculated with the latest weather data during 2008~2015 years using ASHRAE Bin method are compared to the standard temperature of Ministry of Land, Infrastructure and Transport which is widely used for designing South Korea air-conditioning system at present, the maximum temperature difference becomes $0.97^{\circ}C$ for cooling, and $1.94^{\circ}C$ for heating. Due to wide outdoor temperature variation, update of outdoor design temperature based on recent weather data is recommended.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.61-68
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• 2015

This paper deals with the pre-marshalling problem that the containers of container yard at container terminal are relocated in consensus sequence of loading schedule of container vessel. This problem is essential to improvement of competitive power of terminal. This problem has to relocate the all of containers in a bay with minimum number of movement. There are various algorithms such as metaheuristic as genetic algorithm and heuristic algorithm in order to find the solution of this problem. Nevertheless, there is no unique general algorithm that is suitable for various many data. And the main drawback of metaheuristic methods are not the solution finding rule but can be find the approximated solution with many random trials and by coincidence. This paper can be obtain the solution with O(m) time complexity that this problem deals with bin packing problem for m stack bins with descending order of take out ranking. For various experimental data, the proposed algorithm can be obtain the optimal solutions for all of data. And to conclude, this algorithm can be show that most simple and general algorithm with simple optimal solution finding rule.

• Journal of Smart Tourism
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• v.1 no.1
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• pp.53-64
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• 2021

Upselling is often a critical factor in revenue generation for businesses in the tourism and travel industry. Utilizing passenger data from a major international airline company, we develop the PAX (Passenger, Airline, eXternal) model to predict passengers that are most likely to accept an upgrade offer from economy to premium. Formulating the problem as an extremely unbalanced, cost-sensitive, supervised binary classification, we predict if a customer will take an upgrade offer. We use a feature vector created from the historical data of 3 million passenger records from 2017 to 2019, in which passengers received approximately 635,000 upgrade offers worth more than $422,000,000 U.S. dollars. The model has an F1-score of 0.75, outperforming the airline's current rule-based approach. Findings have several practical applications, including identifying promising customers for upselling and minimizing the number of indiscriminate emails sent to customers. Accurately identifying the few customers who will react positively to upgrade offers is of paramount importance given the airline 'industry's razor-thin margins. Research results have significant real-world impacts because there is the potential to improve targeted upselling to customers in the airline and related industries.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.275-287
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• 2022

As a result, for the increasing expansion by the university faculties in the field of postgraduate studies, The Deanship of Graduate Studies at the university has been established in 1430 AH/2009 CE to specifically address the needs of the current and prospective graduate population to supervise postgraduate studies programs in coordination with the concerned faculties. This comes as a result for the university being certain of the importance of providing postgraduate studies opportunities that follow the bachelor's degree to qualify our ambitious youth appropriately. The University offers 72 different Graduate programs, awarding doctoral and master's degrees along with fellowships and diplomas in various disciplines like health, engineering, science, literary, and educational. Currently, the financial model for admission and students' payment is manual and paper based. This paper proposes to provide a user interface for Financial Management in Deanship of Graduate studies The basic purpose of the system was to minimize human interference and reduce mistakes placed by human interference, also to have efficient and a fast performance, and perform Electronic Data Interchange (EDI) for various tasks such as billing and scheduling details.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.129-134
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• 2023

The greatest challenge of this century is the protection of stored and transmitted data over the network. This paper provides a new hybrid algorithm designed based on combination algorithms, in the proposed algorithm combined with Hill and the Advanced Encryption Standard Algorithms, to increase the efficiency of color image encryption and increase the sensitivity of the key to protect the RGB image from Keyes attackers. The proposed algorithm has proven its efficiency in encryption of color images with high security and countering attacks. The strength and efficiency of combination the Hill Chipper and Advanced Encryption Standard Algorithms tested by statical analysis for RGB images histogram and correlation of RGB images before and after encryption using hill cipher and proposed algorithm and also analysis of the secret key and key space to protect the RGB image from Brute force attack. The result of combining Hill and Advanced Encryption Standard Algorithm achieved the ability to cope statistically

• Magazine of the Korean Society of Agricultural Engineers
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• v.16 no.1
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• pp.3263-3291
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• 1974

Experimental work of grain bin was carried out to develop the methods of natural air in-bin drying and storage. The method is considered to be more economical, labour saving, and an effective countermeasure to grain loss. To examine the possibility of farm use of the grain bin and to analyze the related factors concerned with in-bin grain drying and storage, ambient air conditions (especially the change of air temperature and relative humidity) and grain quality during drying and storage periods were investigated. A laboratory model bin was constructed to investigate the effect of different forced air conditions on the drying characteristics of rice. In addition, a grain bin with 2.2m diameter and 1.8m height, considered to be the optimum size for the average Korean farm, was constructed and tested to examine the drying and storing characteristics of rice. The weather data analyzed in this study was the nine-year (from 1964 to 1972) record of air temperature and relative humidity in the Suweon area, and the thirty-year (from 1931 to 1960) record of pentad normal relative humidity and air temperature in the Seoul area. From the results of the weather data analyses, the adequate air delivery hours (which was arbitrary defined as the condition to give less than 75% relative humidity) to dry the rice during October were about nine hours (from approximately 10 A.M. to 7 P.M, ) a day, in which the average air temperature was about 15.9$^{\circ}C$ and average relative humidity was 66%. The occurence of days having three hours of such conditions was 1, 2, and 1-day within the 1st, 2nd add last 10-day periods for the month of October, respectively. Therefore, it may be considered that the weather condition in October was satisfactory for the forced natural air drying. The results of the laboratory model bin test were analyzed to obtain the drying curve and drying rate for different drying stages and grain layers in the bin corresponding to various conditions of forced natural air. A drying experiment with a prototype grain bin showed that an approximate 5 percent grain moisture gradient through a 1.6 meter grain deposit was observed after 80 hours of intermittent drying, giving an over dried zone in the lower grain layers and an extremely high grain moisture zone in the upper layers. This indicates that an effective measure should be taken to reduce this high moisture gradient. In order to investigate the drying characteristics of bulk grain in a layerturning operation a grain bin test was performed. This showed a significant improvement of uniform drying. In this test, approximate 107 hours were required to dry a depth of 1.6 meter of grain from an initial moisture content of 22.2 percent to a moisture content of 16.7 percent using an air delivery rate of 2.8 cubic meter per a minute per every cubic meter of grain. This resulted in a 2 percent moisture gradient from the top to the bottom of the bin. During storage period, till the end of June the average temperature of grain was 2~3$^{\circ}C$ higher than ambient air temperature. But during July when the grain moisture content went up slightly (less than 1 percent), the average temperature of the grain also increased to 3~5$^{\circ}C$ higher than ambient air temperature. It is therefore recommended that for safe grain storage, grain should not be stored in sheet metal bins after mid May. From the above results, in-bin rice drying and storage can be used effectively on Korean farms. It is strongly recommended that the use of grain-bin system should be implemented for farm use to improve farm drying and storage of rice.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.849-858
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• 2004

Most of supervised teaming algorithms could be applied after that continuous variables are transformed to categorical ones at the preprocessing stage in order to avoid the difficulty of processing continuous variables. This preprocessing stage is called global discretization, uses the class distribution list called bins. But, when data are large and the range of the variable to be discretized is very large, many sorting and merging should be performed to produce a single bin because most of global discretization methods need a single bin. Also, if new data are added, they have to perform discretization from scratch to construct categories influenced by the data because the existing methods perform discretization in batch mode. This paper proposes a method that extracts sample points and performs discretization from these sample points in order to solve these problems. Because the approach in this paper does not require merging for producing a single bin, it is efficient when large data are needed to be discretized. In this study, an experiment using real and synthetic datasets was made to compare the proposed method with an existing one.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.1031-1033
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• 2020

최근 지구온난화에 따른 기온 및 강수량 증가 등으로 인해 모기 개체 수가 증가함에 따라 말라리아, 일본뇌염, 뎅기열 등 모기를 통해 전파되는 질병에 감염병의 위험률도 높아지고 있어 머신러닝기반 기후 데이터를 활용하여 모기 개체 수를 예측할 수 있는 모델을 제안하였다.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.297-304
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• 2020

This paper applies the Data Envelopment Analysis (DEA) to compute the managerial efficiency of 30 insurance companies listed on the Saudi stock exchange for the duration of four years from 2015 to 2018. The companies taken as a sample of study included both conventional and Takaful insurance companies. The insurance sector of KSA is one of the largest sectors in the country, contributing a substantial percentage in the non-oil economy. Efficiency measurement and evaluation will provide a venue to introspect and benchmark frontiers to the sector. In the present study, we have utilized the basic Banker Charnes Cooper and Charnes Copper Rhodes models of DEA. Two inputs, namely, general & administrative expenses and policy & acquisition costs, and two outputs (Net premium earned and Investment Income & other incomes) were taken for efficiency calculations. The final outcomes of the study reveal that a good number of insurance companies operating in KSA are found to be efficient on managerial efficiency scale. Three firms remain the leader on the frontier of the managerial efficiency. And no company found with zero (0) efficiency or a negative efficiency. It is expected that the outcome of the study will provide benchmarks to managers and a road map to further improvement.