• Korean Journal of Heritage: History & Science
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• v.51 no.3
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• pp.4-31
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• 2018

It is difficult to ascertain exactly when the Hongjuupseong (Town Wall) was first constructed, due to it had undergone several times of repair and maintenance works since it was piled up newly in 1415, when the first year of the reign of King Munjong (the 5th King of the Joseon Dynasty). Parts of its walls were demolished during the Japanese occupation, leaving the wall as it is today. Hongseong region is also susceptible to historical earthquakes for geological reasons. There have been records of earthquakes, such as the ones in 1978 and 1979 having magnitudes of 5.0 and 4.0, respectively, which left part of the walls collapsed. Again, in 2010, heavy rainfall destroyed another part of the wall. The fortress walls of the Hongjuupseong comprise various rocks, types of facing, building methods, and filling materials, according to sections. Moreover, the remaining wall parts were reused in repair works, and characteristics of each period are reflected vertically in the wall. Therefore, based on the vertical distribution of the walls, the Hongjuupseong was divided into type I, type II, and type III, according to building types. The walls consist mainly of coarse-grained granites, but, clearly different types of rocks were used for varying types of walls. The bottom of the wall shows a mixed variety of rocks and natural and split stones, whereas the center is made up mostly of coarse-grained granites. For repairs, pink feldspar granites was used, but it was different from the rock variety utilized for Suguji and Joyangmun Gate. Deterioration types to the wall can be categorized into bulging, protrusion of stones, missing stones at the basement, separation of framework, fissure and fragmentation, basement instability, and structural deformation. Manually and light-wave measurements were used to check the amount and direction of behavior of the fortress walls. A manual measurement revealed the sections that were undergoing structural deformation. Compared with the result of the light-wave measurement, the two monitoring methods proved correlational. As a result, the two measuring methods can be used complementarily for the long-term conservation and management of the wall. Additionally, the measurement system must be maintained, managed, and improved for the stability of the Hongjuupseong. The measurement of Nammunji indicated continuing changes in behavior due to collapse and rainfall. It can be greatly presumed that accumulated changes over the long period reached the threshold due to concentrated rainfall and subsequent behavioral irregularities, leading to the walls' collapse. Based on the findings, suggestions of the six grades of management from 0 to 5 have been made, to manage the Hongjuupseong more effectively. The applied suggested grade system of 501.9 m (61.10%) was assessed to grade 1, 29.5 m (3.77%) to grade 2, 10.4 m (1.33%) to grade 3, 241.2 m (30.80%) and grade 4. The sections with grade 4 concentrated around the west of Honghwamun Gate and the east of the battlement, which must be monitored regularly in preparation for a potential emergency. The six-staged management grade system is cyclical, where after performing repair and maintenance works through a comprehensive stability review, the section returned to grade 0. It is necessary to monitor thoroughly and evaluate grades on a regular basis.

• Korean Journal of Heritage: History & Science
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• v.37
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• pp.65-89
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• 2004

Up to now, the studies for a pond of ancient palace of Korea are mainly achieved in a landscape architectural field. In fact, we can't grasp the general aspects but we are only heard about the fragmentary ruins and remains by the people who are in charge of an archaeological excavation. In this thesis, therefore, I attempt to grasp the relational categories of the ponds of an ancient palace of Korea, and find out the ideological backgrounds of the ponds of a palace construction through classify them excavated so far. The ancient ponds of Korea are divided to the class of square ponds(I) and curved ponds(II) according a shapes of planes. The class of square ponds(I) are subdivided to the form IA of the class of square ponds and form IB of the class of square ponds by whether it has an island, artificial hill and ornamental stone or not. And the class of the curved ponds(II) are divided to the form IIC that is only composed of curves in shore and the form IID that is composed of curves and straight lines. According the size, it is divided to a small size that is below the maximal diameter, 20m, and a large size that is more than 45m, after all, the ponds of the ancient palaces are devided to IAa, IAb, IBa, II Ca, IICb, IIDa. The square ponds and the curved ponds are co-exist from the initial stage when a pond of a place was found in our country and are succeeded or changed after Silla unified the three Kingdoms. In other words, we can infer a continuity from the earlier stage from the fact that there is a flat figure ground mainly constituted by the ponds of a palace mixed up of a straight line and a curved line in United Silla Kingdom while it succeeds the ponds of a palace that has a square form of Goguryo in Balhai. Different from the successional relation of the flat figure grounds, in an aspect of the elements of the construction, the site of the arbor at the top of the island and the bridge facilities in a field of a palace those are not exist in three Kingdoms period are appeared in United Silla Kingdom. The point that this aspect is simultaneously appeared in a neighboring country, or Japan, allows us to infer that there may be some motivations cause the changes in a construction of the ponds of a palace of Korea, China and Japan from the latter half of the 7th century to the first half of the 8th century. The ideological backgrounds of the ponds of a palace construction are divided roughly into Taoism and Buddhism. We can recognize that the ponds of a palace made up of the islands, the artificial hills and the garden rocks reflect Taiosm, considering the records of the ponds a palace of Korea and China are all use the term, Taoism, or the concrete statement represents that the islands, the artificial hills and the garden rocks are used in the description of the ponds of a palace of Korea. Both two are, therefore, obviously differentiated from the ponds of a palace that doesn't include them. We can conclude that the ponds of a palace that doesn't include them are colored by Buddhism since they are overtly distinguished from the class of curved ponds that reflect Taoism at the same period and they are identical with the site of an ancient temples in an aspect of their type and construction.

• Korean Journal of Poultry Science
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• v.46 no.2
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• pp.65-75
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• 2019

A number of Korean native chicken(KNC) populations were registered in FAO (Food and Agriculture Organization) DAD-IS (Domestic Animal Diversity Information Systems, http://www.fao.org/dad-is). But there is a lack of scientific basis to prove that they are unique population of Korea. For this reason, this study was conducted to prove KNC's uniqueness using 25 Microsatellite markers. A total of 548 chickens from 11 KNC populations (KNG, KNB, KNR, KNW, KNY, KNO, HIC, HYD, HBC, JJC, LTC) and 7 introduced populations (ARA: Araucana, RRC and RRD: Rhode Island Red C and D, LGF and LGK: White Leghorn F and K, COS and COH: Cornish brown and Cornish black) were used. Allele size per locus was decided using GeneMapper Software (v 5.0). A total of 195 alleles were observed and the range was 3 to 14 per locus. The MNA, $H_{\exp}$, $H_{obs}$, PIC value within population were the highest in KNY (4.60, 0.627, 0.648, 0.563 respectively) and the lowest in HYD (1.84, 0.297, 0.286, 0.236 respectively). The results of genetic uniformity analysis suggested 15 cluster (${\Delta}K=66.22$). Excluding JJC, the others were grouped in certain cluster with high genetic uniformity. JJC was not grouped in certain cluster but grouped in cluster 2 (44.3%), cluster 3 (17.7%) and cluster8 (19.1%). As a results of this study, we can secure a scientific basis about KNC's uniqueness and these results can be use to basic data for the genetic evaluation and management of KNC breeds.

• The Korean Journal of Archival Studies
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• no.32
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• pp.127-176
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• 2012

Metadata is well recognized as one of the foundational factors in archiving and long-term preservation of digital resources. There are several metadata standards for records management, archives and preservation, e.g. ISAD(G), EAD, AGRkMs, PREMIS, and OAIS. Consideration is important in selecting appropriate metadata standards in order to design metadata schema that meet the requirements of a particular archival system. Interoperability of metadata with other systems should be considered in schema design. In our previous research, we have presented a feature analysis of metadata standards by identifying the primary resource lifecycle stages where each standard is applied. We have clarified that any single metadata standard cannot cover the whole records lifecycle for archiving and preservation. Through this feature analysis, we analyzed the features of metadata in the whole records lifecycle, and we clarified the relationships between the metadata standards and the stages of the lifecycle. In the previous study, more detailed analysis was left for future study. This paper proposes to analyze the metadata schemas from the viewpoint of tasks performed in the lifecycle. Metadata schemas are primarily defined to describe properties of a resource in accordance with the purposes of description, e.g. finding aids, records management, preservation and so forth. In other words, the metadata standards are resource- and purpose-centric, and the resource lifecycle is not explicitly reflected in the standards. There are no systematic methods for mapping between different metadata standards in accordance with the lifecycle. This paper proposes a method for mapping between metadata standards based on the tasks contained in the resource lifecycle. We first propose a Task Model to clarify tasks applied to resources in each stage of the lifecycle. This model is created as a task-centric model to identify features of metadata standards and to create mappings among elements of those standards. It is important to categorize the elements in order to limit the semantic scope of mapping among elements and decrease the number of combinations of elements for mapping. This paper proposes to use 5W1H (Who, What, Why, When, Where, How) model to categorize the elements. 5W1H categories are generally used for describing events, e.g. news articles. As performing a task on a resource causes an event and metadata elements are used in the event, we consider that the 5W1H categories are adequate to categorize the elements. By using these categories, we determine the features of every element of metadata standards which are AGLS, AGRkMS, PREMIS, EAD, OAIS and an attribute set extracted from DPC decision flow. Then, we perform the element mapping between the standards, and find the relationships between the standards. In this study, we defined a set of terms for each of 5W1H categories, which typically appear in the definition of an element, and used those terms to categorize the elements. For example, if the definition of an element includes the terms such as person and organization that mean a subject which contribute to create, modify a resource the element is categorized into the Who category. A single element can be categorized into one or more 5W1H categories. Thus, we categorized every element of the metadata standards using the 5W1H model, and then, we carried out mapping among the elements in each category. We conclude that the Task Model provides a new viewpoint for metadata schemas and is useful to help us understand the features of metadata standards for records management and archives. The 5W1H model, which is defined based on the Task Model, provides us a core set of categories to semantically classify metadata elements from the viewpoint of an event caused by a task.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.197-218
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• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.60-74
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• 2018

This study was to investigate the pedestrian's thermal environments in the North Sidewalk of E-W Street during summer heatwave. We carried out detailed measurements with four human-biometeorological stations on Dongjin Street, Jinju, Korea ($N35^{\circ}10.73{\sim}10.75^{\prime}$, $E128^{\circ}55.90{\sim}58.00^{\prime}$, elevation: 50m). Two of the stations stood under one row street tree and hedge(One-Tree), two row street tree and hedge (Two-Tree), one of the stations stood under shelter and awning(Shelter), while the other in the sun (Sunlit). The measurement spots were instrumented with microclimate monitoring stations to continuously measure microclimate, radiation from the six cardinal directions at the height of 1.1m so as to calculate the Universal Thermal Climate Index (UTCI) from 24th July to 21th August 2018. The radiant temperature of sidewalk's elements were measured by the reflective sphere and thermal camera at 29th July 2018. The analysis results of 9 day's 1 minute term human-biometeorological data absorbed by a man in standing position from 10am to 4pm, and 1 day's radiant temperature of sidewalk elements from 1:16pm to 1:35pm, showed the following. The shading of street tree and shelter were mitigated heat stress by the lowered UTCI at mid and late summer's daytime, One-Tree and Two-Tree lowered respectively 0.4~0.5 level, 0.5~0.8 level of the heat stress, Shelter lowered respectively 0.3~1.0 level of the heat stress compared with those in the Sunlit. But the thermal environments in the One-Tree, Two-Tree and Shelter during the heat wave supposed to user "very strong heat stress" while those in the Sunlit supposed to user "very strong heat stres" and "exterme heat stress". The main heat load temperature compared with body temperature ($37^{\circ}C$) were respectively $7.4^{\circ}C{\sim}21.4^{\circ}C$ (pavement), $14.7^{\circ}C{\sim}15.8^{\circ}C$ (road), $12.7^{\circ}C$ (shelter canopy), $7.0^{\circ}C$ (street funiture), $3.5^{\circ}C{\sim}6.4^{\circ}C$ (building facade). The main heat load percentage were respectively 34.9%~81.0% (pavement), 9.6%~25.2% (road), 24.8% (shelter canopy), 14.1%~15.4% (building facade), 5.7% (street facility). Reducing the radiant temperature of the pavement, road, building surfaces by shading is the most effective means to achieve outdoor thermal comfort for pedestrians in sidewalk. Therefore, increasing the projected canopy area and LAI of street tree through the minimal training and pruning, building dense roadside hedge are essential for pedestrians thermal comfort. In addition, thermal liner, high reflective materials, greening etc. should be introduced for reducing the surface temperature of shelter and awning canopy. Also, retro-reflective materials of building facade should be introduced for the control of reflective sun radiation. More aggressively pavement watering should be introduced for reducing the surface temperature of sidewalk's pavement.

• Journal of the Korean Geotechnical Society
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• v.35 no.5
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• pp.5-19
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• 2019

Considering the natural phenomenon in which steep slopes ($65^{\circ}{\sim}85^{\circ}$) consisting of rock mass remain stable for decades, slopes steeper than 1:0.5 (the standard of slope angle for blast rock) may be applied in geotechnical conditions which are similar to those above at the design and initial construction stages. In the process of analysing the stability of a good to fair continuum rock slope that can be designed as a steep slope, a general method of estimating rock mass strength properties from design practice perspective was required. Practical and genealized engineering methods of determining the properties of a rock mass are important for a good continuum rock slope that can be designed as a steep slope. The Genealized Hoek-Brown (H-B) failure criterion and GSI (Geological Strength Index), which were revised and supplemented by Hoek et al. (2002), were assessed as rock mass characterization systems fully taking into account the effects of discontinuities, and were widely utilized as a method for calculating equivalent Mohr-Coulomb shear strength (balancing the areas) according to stress changes. The concept of calculating equivalent M-C shear strength according to the change of confining stress range was proposed, and on a slope, the equivalent shear strength changes sensitively with changes in the maximum confining stress (${{\sigma}^{\prime}}_{3max}$ or normal stress), making it difficult to use it in practical design. In this study, the method of estimating the strength properties (an iso-angle division method) that can be applied universally within the maximum confining stress range for a good to fair continuum rock mass slope is proposed by applying the H-B failure criterion. In order to assess the validity and applicability of the proposed method of estimating the shear strength (A), the rock slope, which is a study object, was selected as the type of rock (igneous, metamorphic, sedimentary) on the steep slope near the existing working design site. It is compared and analyzed with the equivalent M-C shear strength (balancing the areas) proposed by Hoek. The equivalent M-C shear strength of the balancing the areas method and iso-angle division method was estimated using the RocLab program (geotechnical properties calculation software based on the H-B failure criterion (2002)) by using the basic data of the laboratory rock triaxial compression test at the existing working design site and the face mapping of discontinuities on the rock slope of study area. The calculated equivalent M-C shear strength of the balancing the areas method was interlinked to show very large or small cohesion and internal friction angles (generally, greater than $45^{\circ}$). The equivalent M-C shear strength of the iso-angle division is in-between the equivalent M-C shear properties of the balancing the areas, and the internal friction angles show a range of $30^{\circ}$ to $42^{\circ}$. We compared and analyzed the shear strength (A) of the iso-angle division method at the study area with the shear strength (B) of the existing working design site with similar or the same grade RMR each other. The application of the proposed iso-angle division method was indirectly evaluated through the results of the stability analysis (limit equilibrium analysis and finite element analysis) applied with these the strength properties. The difference between A and B of the shear strength is about 10%. LEM results (in wet condition) showed that Fs (A) = 14.08~58.22 (average 32.9) and Fs (B) = 18.39~60.04 (average 32.2), which were similar in accordance with the same rock types. As a result of FEM, displacement (A) = 0.13~0.65 mm (average 0.27 mm) and displacement (B) = 0.14~1.07 mm (average 0.37 mm). Using the GSI and Hoek-Brown failure criterion, the significant result could be identified in the application evaluation. Therefore, the strength properties of rock mass estimated by the iso-angle division method could be applied with practical shear strength.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• 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.