• Proceedings of the Korean Society of Toxicology Conference
• /
• 2002.05b
• /
• pp.106.2-132
• /
• 2002

형질전환 (유전자 결핍; Knockout) Min 마우스를 이용하여 대장암 발생에서 배추, 양배추 주성분인 indole-3-carbinol (I3C)의 대장암 예방효과를 규명하고자 하였다. 실험동물로는 C57BL/6J-Apc$^{min/+}$(Min 마우스)계의 5내지 6주령의 수컷 이형접합체 형질전환 마우스 70마리와 C57BL/6J계의 동일 산자, 동일 주령의 수컷 wildtype 비형질전환 마우스 10kfl를 The Jackson Laboratory 사 (Bar harber, ME, USA)로부터 직접 구입하였다. C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 (Min)마우스 70마리를 각 군 20내지 25마리씩 세군으로 나누었다. Group 1에는 20마리, Group 2에는 25마리, Group 3에는 25마리를 배치하고, I3C 투여 실험군 (Group 1과 2)에는 실험시작시에 AIN-76A 분말사료에 I3C가 각각 100 및 300ppm이 함유되도록 조제하여 공급하였다. 그리고 실험군(Group 3)에는 실험시작부터 종료시까지 AIN-76A 정제고형사료(Teklad사, WI, USA)를 자유로이 급이하였다. 각군간의 체중, 사료 및 음수소비량을 매 2주마다 측정하였고, 10주간 (16주령)의 실험종료시에는 최종체중과 간장, 신장, 비장 등의 장기무게를 측정하여 상대장기 무게비를 산출하였다. 대조군으로서 C57BL/6J계의 동일 산자, 동일 주령의 수컷 wildtype 비형질전환 마우스 10마리는 같은 조건의 사육실에서 AIN-76A 정제고형사료를 33주간 자유로이 급이하였다. 실험동물은 부검전에 하룻밤 동안 절식하고 이산화탄소 흡입 마취하에서 흉대동맥을 절단하여 방혈하고 각 장기(심장, 폐, 위)를 적출하여 생리심염수에 넣어 장기무게를 측정하고 포르말린에 고정하였다. 소장과 대장의 검사를 위하여 위의 식도부위와 직장을 실로 결찰하여 적출하고 생리심염수를 주입하여 팽창시켜, 십이지장, 공장, 및 회장, 그리고 대장으로 나누어 여과지에 펼친 후 포르말린에 고정하였다. 소장과 대장은 육안 및 자동 영상분석길ㄹ 이용한 분석이 끝난 후에 각 부위별로 4-6개의 절편을 작제하여 포르말린에 재고정하고, 통상적인 조직처리과정, 파리핀 포매 및 3-4$\mu$m 두께의 조직절편을 제작하여 H&E 염색을 실시하여 현미경으로 검경하였다. 약 1주일간의 포르말린 고정이 끝난 소장 및 대장을 부위별, 별 종양개수 및 분포를 자동영상분석기(Kontron Co. Ltd., Germany)로 분석하였다. 체의 변화, 장기무게, 사료소비량 및 마리당 종양의 개수에 대한 통계학적 유의성 검증을 위하여 Duncan's t-test로 통계처리 하였고, 종양 발생빈도에 대하여는 Likelihood ration Chi-square test로 유의성을 검증하였다. C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 마우스에 AIN-76A 정제사료만을 투여한 대조군의 대장선종의 발생률은 84%(Group 3; 21/25례)로써 I3C 100ppm 및 300ppm을 투여한 경우에 있어서는 각군 모두 60%(Group 1; 12/20 례, Group 2; 15/25 례)로 감소하는 경향을 나타내었다. 대장선종의 마리당 발생개수에 있어서는 C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 마우스에 AIN-76A 정제사료만을 투여한 대조군은 1.40$\pm$0.24(100%)에 비하여 I3C 저농도 투여 실험군(Group 1; 0.85$\pm$0.23; 61%, P<0.01), 그리고 I3C 고농도 투여 실험군(Group 2 ; 1.32$\pm$0.29 ; 94%)의 순으로 감소하였다. 선종의 크기별 종양의 발생개수의 분포에 있어서 I3C 저농도 투여 실험군에 있어서는 선종의 크기가 3mm이하의 수가 현저하게 감소하였다. C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 마우스에 AIN-76A 정제사료만을 투여한 대조군의 부위별 소장선종의 발생수는 십이지장부위를 제외하고 각 군에서 유의한 변화는 관찰되지 않았다. 십이지장 종양의 발생개수에서만 I3C 저농도 투여 실험군(Group 1 ; 3.11$\pm$0.85)이 대조군 (Group 3: 1.48$\pm$0.35) 및 I3C 고농도 투여 실험군(Group 2: 1.56$\pm$0.47)에 비하여 유의성 있게 증가하였다. (P<0.05). 따라서 I3C은 소장에서는 암예방 효과가 뚜렷하지 않으나, 대장에 대한 암에방 효과가 있을 것으로 생각된다. 소장 및 대장을 제외한 간장, 신장, 비장, 심장, 폐 그리고 위 등의 기타 장기에서의 조직병리학적 변화는 관찰되지 않았다. 소장 및 대장의 종양은 선종(polyps)으로 관찰되었다. 지난 10여년간 형질전환 및 유전자 결핍 실험동물의 종류가 기하 급수적으로 증가하여 이용되고 있다. 가족성 대장 선종성 용종증(FAP)의 대표적인 모델로 이용되고 있는 C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 마우스를 사용하여 배추나 양배추의 주요성분인 Indole-3-carbinol(I3C)의 대장암 예방효과가 있는지를 검색하여 본 결과 AIN-76A정제사료만을 투여한 대조군의 대장선종의 발생률 84%에 비하여 I3C 100 및 300ppm을 투여한 실험군에 있어서 각군 모두 60%로서 감소하는 경향을 나타내었으며, 대장선종의 마리당 발생개수에 있어서는 대조군의 1.40$\pm$1.041를 100%로 환산하였을 경우 I3C 저농도 및 고농도 투여 실험군에서는 각각 약 61%와 94%를 나타내여 감소하였다. 특히 대장선종의 크기별 분포에 있어서 선종의 크기가 3mm이하의 수가 현저하게 감소하였다. 따라서 저농도 I3C의 투여는 실험적 유전성 가족성 대장 선종성 용종증 모델에 있어서 어느정도 암 예방효과가 있는 것으로 생각된다. 그러나 소장 선종의 발생에는 별 영향이 없는 것으로 생각된다. 그러나 본 실험에 사용된 C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 마우스는 실험개시 시점이 7내지 8주령이 경과하여 이미 태생기부터 소장 및 대장의 선종 발생이 진행되어 온 것을 감안하고 특히 비스테로이드계 항염증 소염제(NSAIDS)와 같은 강력한 COX-2억제제가 아님을 고려하면, 상당한 선종의 발생을 억제할 수 있는 가능성이 매우 높다고 생각한다. 또한 이제까지 배추나 양배추 성분의 복합성분들에 대한 실험적 대장암 모델에서의 촉진효과 등에 대한 보고들이 있어 온 점을 고려할 때 위암(Kim 등, 1994) 간암(Kim 등, 1994), 유방암(Grubbs, 등, 1995; Bradlow 등, 1995)에 대한 예방효과가 있을 것으로 생각된다. 앞으로 이러한 종양조직내에서의 COX-2 및 iNOS mRNA와 단백질의 발현정도를 분자병리학적으로 연구중에 있으며, 향후 십자화과식물 성분인 indole-3-carbinol이 마우스뿐 만 아니라 랫드의 화학발암물질에 의한 대장종양에 대한 억제효과 있는지 연구 필요가 있다. Min 마우스와 같은 형질 전환(유전자결핍;knockout) 실험동물을 이용한 새로운 중기 발암성 시험범의 확립을 통한 각종 환경 유해물질의 발암성 유무 및 COX-2 억제작용이 있는 식품인자의 암예방 후보물질을 체계적으로 검색하는데 유용하게 활용될 수 있을 것으로 생각한다.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.26 no.1
• /
• pp.69-89
• /
• 1981

Stevia (Stevia rebaudiana Bertoni) is a perennial herb widely distributed in the mountainous area of Paraguay. It belongs to the family Compositae and contains 6 to 12 percent stevioside in the leaves. Stevioside is a glucoside having similar sweetening character to surgar and the degree of sweetness is approximately 300 times of sugar. Since Korea does not produce any sugar crops, and the synthetic sweetenings are potentially hazardous for health, it is rather urgent to develop an economical new sweetener. Consequently, the current experiments are conducted to establish cultural practices of stevia, a new sweetening herbs, introduced into Korea in 1973 and the results are summarized as followings: 1. Days from transplanting of cuttings to the flower bud formation of 6 stevia lines were similar among daylengths of 8, 10 and 12 hours, but it was much greater at daylengths of 14 or 24 hour and varietal differences were noticable. All lines were photosensitive, but a line, 77013, was the most sensitive and 77067 and Suweon 2 were less sensitive to daylength. 2. Critical daylength of all lines seemed to be approximately 12 hours. Growth of plants was severely retarded at daylengths less than 12 hours. 3. Cutting were responded to short daylength before rooting. Number of days from transplanting to flower bud formation of 40-day old cuttings in the nursery bed was 20 days and it was delayed as duration of nursery were shorter. 4. Number of days from emergence to flower bud formation was shortest at short day treatment from 20 days after emergence. It was became longer as initiation of short day treatment was earlier or later than 20 days. 5. Plant height, number of branches, and top dry weight of stevia were reduced as cutting date was delayed from March 20 to May 20. The highest yield of dry leaf was obtained at nursery duration of 40-50 days in march 20 cutting, 30-40 days in April 20 cutting, and 30 days in May 20 cutting. 6. An asymptotic relationship was observed between plant population and leaf dry weight. Yield of dry leaf increased rapidly as plant population increased from 5,000 to 10,000 plants/10a with a reduced increasing rate from 10,000 to 20,000 plants/l0a, and levelled off at the plant population higher than 20,000 plants/l0a. 7. Stevia was adaptable in Suweon, Chengju, Mokpo and Jeju and drought was one of the main factors reducing yield of dry leaf. Yield of dry leaf was reduced significantly (approximately 30%) at June 20 transplanting compared to optimum transplanting. 8. Yield of dry leaf was higher in a vinyl house compared to unprotected control at long daylength or natural daylength except at short day treatment at March 20. Higher temperature ill a vinyl house does not have benefital effects at April 20 transplanting. 9. The highest content of stevioside was noted at the upper leaves of the plant but the lowest was measured at the plant parts of 20cm above ground. Leaf dry weight and stevioside yield was mainly contributed by the plant parts of 60 to 120cm above ground but the varietal differences were also significant. 10. Delayed harvest by the time of flower bud formation increased leaf dry weight remarkably. However, there were insignificant changes of yield as harvests were made at any time after flower bud formation. Content of stevioside was highest at the time of flower bud formation and earlier or later harvest than this time was low in its content. The optimum harvesting time determined by leaf dry weight and stevioside content was the periods from flower bud formation to right before flowering that would be the period from September 10 to September 15 in Suweon area. 11. Stevioside and rebaudioside content in the leaves of Stevia varieties were ranged from 5.4% to 14.3% and 1.5% to 8.3% respectively. However, no definit relationships between stevioside and rebaudioside were observed in these particular experiments.

• Journal of Korean Society of Transportation
• /
• v.20 no.7
• /
• pp.155-166
• /
• 2002

Since 1990s. there has been an increasing number of traffic accidents at intersection. which requires more urgent measures to insure safety on intersection. This study set out to analyze the road conditions, traffic conditions and traffic operation conditions on signalized intersection. to identify the elements that would impose obstructions in safety, and to develop a traffic accident prediction model to evaluate the safety of an intersection using the cop relation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on the intersection in developing a traffic accident prediction model fir a signalized intersection. The data for the study was collected at an intersection located in Wonju city from January to December 2001. It consisted of the number of accidents, the road conditions, the traffic conditions, and the traffic operation conditions at the intersection. The collected data was first statistically analyzed and then the results identified the elements that had close correlations with accidents. They included the area pattern, the use of land, the bus stopping activities, the parking and stopping activities on the road, the total volume, the turning volume, the number of lanes, the width of the road, the intersection area, the cycle, the sight distance, and the turning radius. These elements were used in the second correlation analysis. The significant level was 95% or higher in all of them. There were few correlations between independent variables. The variables that affected the accident rate were the number of lanes, the turning radius, the sight distance and the cycle, which were used to develop a traffic accident prediction model formula considering their distribution. The model formula was compared with a general linear regression model in accuracy. In addition, the statistics of domestic accidents were investigated to analyze the distribution of the accidents and to classify intersections according to the risk level. Finally, the results were applied to the Spearman-rank correlation coefficient to see if the model was appropriate. As a result, the coefficient of determination was highly significant with the value of 0.985 and the ranks among the intersections according to the risk level were appropriate too. The actual number of accidents and the predicted ones were compared in terms of the risk level and they were about the same in the risk level for 80% of the intersections.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.107-118
• /
• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

• Tuberculosis and Respiratory Diseases
• /
• v.44 no.2
• /
• pp.349-359
• /
• 1997

Background : The signal pathways and their precise roles for acute respiratory distress syndrome caused by endotoxin (ETX) has not been established. Since there has been several in vitro experiments suggesting that activation of protein kinase C (PKC) pathway may be responsible for endotoxin-induced inflammatory reaction, we performed in vivo experiments in the rats with the hypothesis that PKC-inhibition can effectively prevent endotoxin-induced acute lung injury. Methods : We studied the role of PKC in ETX-induced ALI using PKC inhibitor (staurosporine, STP) in the rat Specific pathogen free male Sprague-Dawley weighted from 165 to 270g were used for the study. Animals were divided into the normal control (NC)-, vehicle control (VC)-, ETX-, PMA (phorbolmyristateacetate)-, STP+PMA-, and STP+ETX-group. PMA (50mg/kg) or ETX (7mg/kg) was instilled through polyethylen catheter after aseptic tracheostomy with and without STP (0.2mg/kg)-pretreatment STP was injected via tail vein 30min before intratracheal injection (IT) of PMA or ETX. Bronchoalveolar lavage (BAL) was done 3-or 6-hrs after IT of PMA or ETX respectively, to measure protein concentration, total and differential cell counts. Results : The results were as follows. The protein concentrations in BALF in the PMA- and ETX-group were very higher than that of VC-group (p<0.001). When animals were pretreated with STP, the %reduction of the protein concentration in BALF was $64.8{\pm}8.5$ and $30.4{\pm}2.5%$ in the STP+PMA- and STP+ETX-group, respectively (p = 0.028). There was no difference in the total cell counts between the PMA-and VC-group (p = 0.26). However the ETX-group showed markedly increased total cell counts as compared to the VC- (p = 0.003) and PMA-group (p = 0.0027), respectively. The total cell counts in BALF were not changed after pretreatment with STP compared to the PMA- (p = 0.22) and ETX-group (p = 0.46). The percentage of PMN, but not alveolar macrophage, was significantly elevated in the PMA-, and ETX-group. Especially in the ETX-group, the percentage of PMN was 17 times higher than that of PMA (p < 0.001). The differential cell counts was not different between the PMA and STP+PMA On the contrary the STP+ETX-group showed decreased percentage of PMN (p = 0.016). There was no significant relationship between the protein concentration and the total or differential cell counts in each group. Conclusion : Pretreatment with PKC-inhibitor (staurosporine) partially but significantly inhibited ETX-induced ALI.

• Journal of Intelligence and Information Systems
• /
• v.20 no.3
• /
• pp.45-58
• /
• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of Intelligence and Information Systems
• /
• v.18 no.1
• /
• pp.1-21
• /
• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• Journal of Intelligence and Information Systems
• /
• v.19 no.4
• /
• pp.55-79
• /
• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.113-125
• /
• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

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