• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.35-52
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• 2019

As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.133-140
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• 2016

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, we were proposed the reliability model with the exponential and inverse exponential distribution, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, were employed. Analysis of failure, using real data set for the sake of proposing the exponential and inverse exponential distribution, was employed. This analysis of failure data compared with the exponential and inverse exponential distribution property. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the inverse exponential distribution model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.443-453
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• 2020

This study using the active vibration control technique attempts to alleviate numerically the airframe vibration of a UH-60A helicopter. The AVCS(Active Vibration Control System) is applied to reduce the 4/rev vibration responses at the specified locations of the UH-60A airframe. The 4/rev hub vibratory loads of the UH-60A rotor is predicted using the nonlinear flexible dynamics analysis code, DYMORE II. Various tools such as NDARC, MSC.NASTRAN, and MATLAB Simulink are used for the AVCS simulation with five CRFGs and seven accelerometers. At a flight speed of 158knots, the predicted 4/rev hub vibratory loads of UH-60A rotor excite the airframe, and then the 4/rev vibration responses at the specified airframe positions such as the pilot seat, rotor-fuselage joint, mid-cabin, and aft-cabin are calculated without and with AVCS. The 4/rev vibration responses at all the locations and directions are reduced by from 25.14 to 96.05% when AVCS is used, as compared to the baseline results without AVCS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1083-1091
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• 2017

This paper describes a design of cryptographic processor supporting 224-bit elliptic curves over prime field defined by NIST. Scalar point multiplication that is a core arithmetic function in elliptic curve cryptography(ECC) was implemented by adopting the modified Montgomery ladder algorithm. In order to eliminate division operations that have high computational complexity, projective coordinate was used to implement point addition and point doubling operations, which uses addition, subtraction, multiplication and squaring operations over GF(p). The final result of the scalar point multiplication is converted to affine coordinate and the inverse operation is implemented using Fermat's little theorem. The ECC processor was verified by FPGA implementation using Virtex5 device. The ECC processor synthesized using a 0.18 um CMOS cell library occupies 2.7-Kbit RAM and 27,739 gate equivalents (GEs), and the estimated maximum clock frequency is 71 MHz. One scalar point multiplication takes 1,326,985 clock cycles resulting in the computation time of 18.7 msec at the maximum clock frequency.

• The Journal of Engineering Geology
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• v.20 no.3
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• pp.231-242
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• 2010

In order to assess applicability of debris flow simulation on natural terrain in Korea, this study introduced the DEBRIS-2D program which had been developed by Liu and Huang (2006). For simulation of large debris flows composed of fine and coarse materials, DEBRIS-2D was developed using the constitutive relation proposed by Julien and Lan (1991). Based on the theory of DEBRIS-2D, this study selected a valley where a large debris flow was occurred on July 16th, 2006 at Deoksanri, Inje county, Korea. The simulation results show that all mass were already flowed into the stream at 10 minutes after starting. In 10minutes, the debris flow reached the first geological turn and an open area, resulting in slow velocity and changing its flow direction. After that, debris flow started accelerating again and it reached the village after 40 minutes. The maximum velocity is rather low between 1 m/sec and 2 m/sec. This is the reason why debris flow took 50 minutes to reach the village. The depth change of debris flow shows enormous effect of the valley shape. The simulated result is very similar to what happened in the field. It means that DEBRIS-2D program can be applied to the geologic and topographic conditions in Korea without large modification of analysis algorithm. However, it is necessary to determine optimal reference values of Korean geologic and topographic properties for more reliable simulation of debris flows.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.419-427
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• 2020

This study was undertaken to address the difficulties and inconveniences of an electric wheelchair. We focused on improving usability of initially completed products by augmenting the prototypes designed in the previous study. For evaluation of usability, 10 elderly women aged over 65 years, capable of movements and physical activities in daily life, were enrolled as subjects. The experimental method included a subjective satisfaction questionnaire evaluation of the elderly women using the target product, and the observation evaluation was achieved using video recording data, etc. Usability evaluation revealed that the elevating sector requires improvement of intuition through separation of the elevating control panel and the driving control panel. Improvements in the driving sector include corrections of the front wheel mechanism or driving control algorithm, UI, and sudden stop system. Transferring section assessment revealed a necessity to secure structures and add structures that support power. We believe that based on the inconveniences and improvements presented in the usability evaluation, appending the existing prototype with complementary products will improve the quality of life of elderly women with limited mobility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.660-665
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• 2018

Research into underwater wireless networks that enable the monitoring and controlling of the ocean environments has been continuing for disaster prevention and military proposes, as well as for the exploitation of ocean resources throughout the world. A research group led by Hoseo university has been studying a distributed underwater monitoring and controlling network. In this study, we developed an interpolator for acoustic communication between an underwater base station controller and underwater base station, which is included in this network. The underwater acoustic communication provided by this network defines four links whose sampling rates are different. Low power consumption is one of the most important requirements. Therefore, we adopted CIC interpolators, which are known to act as filters with a low power consumption, and some CIC interpolators with an appropriate changing rate were selected depending on the link. However, these interpolators have a large passband drop and wide transition region. To solve these problems, we added a compensator and half-band filter. After verifying the algorithm by using Matlab, we designed and verified it with Verilog-HDL in a ModelSim environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.451-457
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• 2020

Format recognition and OCR techniques are widely used as methods for detecting and protecting personal information from electronic documents. However, due to the poor recognition rate of the OCR engine, personal information cannot be detected or false positives commonly occur. It also takes a long time to analyze a large amount of electronic documents. In this paper, we propose a method to improve the speed of image analysis of electronic documents, character recognition rate of the OCR engine, and detection rate of personal information by improving the existing method. The analysis speed was increased using the format recognition method while the analysis speed and character recognition rate of the OCR engine was improved by image correction. An algorithm for analyzing personal information from images was proposed to increase the reconnaissance rate of personal information. Through the experiments, 1755 image format recognition samples were analyzed in an average time of 0.24 seconds, which was 0.5 seconds higher than the conventional PAID system format recognition method, and the image recognition rate was 99%. The proposed method in this paper can be used in various fields such as public, telecommunications, finance, tourism, and security as a system to protect personal information in electronic documents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.232-241
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• 2017

This paper presents an automated cow-feeding system based on an AGV and screw conveyor for domestic livestock farms, which are becoming larger and more commercialized. The system includes a hopper module for loading pellet-type mixed feed at the top of the system, a transfer module mounted with a screw conveyor to transfer feed from the hopper module to the outlet module, an outlet module composed of belt conveyors, and an electromagnetic guided driving-type AGV. The weight of the loaded feed is measured by a load cell located under the transfer module. The system reads the feed discharge information stored in RFID tags installed in each cowshed cell, and a predetermined amount of feed is discharged while the AGV is moving. A cow-feed test system was constructed to determine the design parameters of the screw conveyor in the transfer module that determine the feeding capacity. These parameters include the screw's outer diameter, the screw shaft outer diameter, and screw pitch. The parameters were applied to the finalized cow-feed system construction. A DSP-based main controller and cow-feeding algorithm for different scenarios were also developed to control the system. Experimental results confirmed that the system could supply a total of 21 kg of feed uniformly at 420 g/s for a cowshed cell which has 7 cows. The driving distance was 5 m and the speed was 0.1 m/s. Thus, the proposed system could be applied to standardized domestic livestock farms.