왕담배나방은 기주범위가 넓은 다식성으로 토마토, 옥수수, 담배, 해바라기, 땅콩, 면화, 콩 등 다양한 작물에 피해를 주는 해충이며, 장거리 이동성 해충으로도 유명하다. 본 연구에서는 기존 자료를 바탕으로 월동번데기의 성충으로 우화모델(2종)를 작성하고 포장 실측자료와 비교하여 평가하였다. 월동 번데기는 휴면을 종료한 후 안점소실 과정을 거쳐 정상의 번데기로 이행되고 비로소 성충으로 우화하는 것으로 가정하였다. 첫 번째 모형(모 형 1)은 2단계 휴면후발육 우화모형으로 안점소실에 필요한 적산온도 59.9DD (발육영점온도 15.9℃)와 번데기 발육완료에 필요한 192.3DD (발육영점온도 10.2℃)로 구성하였다. 두 번째 모형(모형 2)은 온도자극 우화모형으 로 17.63℃의 온도자극 이후에 번데기 발육을 개시하는 모형이었다. 적산온도는 단순 평균온도법과 사인곡선법 으로 계산하여 비교하였다. 포장자료와 비교 결과 모형 1에 사인곡선법을 적용했을 때 실측치와 편차가 3일보다 작거나 차이가 없었다. 반면 사인곡선법을 적용한 모형 2는 3~6.5일의 편차가 있었다. 평균온도법을 적용한 경우 두 모형 모두 실측치와 편차가 증가하였다. 모형을 활용하여 예측 우화시기와 트랩유살자료를 비교하여 왕담배 나방의 비래 가능성에 대하여 고찰하였다.

With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

This study tries to focus on the psychological influence by social media on user and tries to find a relationship between psychological influence and consumption patterns. Therefore, we contend that social media are platforms of interaction in that they can generate social empowerment—users feeling that they have an impact on others which gives them high self-worth (Sara Hanson, 2017) and temporarily rise self-worth can lead low self-control. Khan and Dhar (2006) find that a prior virtuous act can momentarily increase one’s self-concept, which leads to more self-indulgence in unrelated decisions. In this paper, we also investigated the two types of social media users by their presentation focus (self vs. other). In social media, there are two types of users: player & watcher. Players are users who have many followers, post lots of information about themselves and need love and attention from other users. Thus, a player which is called self-presentation focus (Wilcox, 2013) is defined as a user who focuses on information they are presenting to people in social media. In contrast, watchers are users who don’t post information on social media as actively as players but love to observe and like or dislike other users’ posts. Thus, a watcher which is called other-presentation focus (Wilcox, 2013) is defined as a user who focuses on information people present to them in social media and this is called other-presentation focus. In general, players could feel more social empowerment because posting information can be one of the activities involving interacting with other users. However, we contend that watchers will feel rather more social empowerment because having an impact, or having the feeling of social empowerment, involves the perception that one’s actions are beneficial to others, which is giving a like or comment to other user in social media (Grant and Campbell 2007). This research will have several theoretical and managerial implications. First, this study will show the influence of social media on users’ behavior and mentality, and which are related to self-control and social-empowerment. Second, this study will discover which type of social media user can be affected effectively by firms’ social media efforts.

ABSTRACT The growth of the social platform has led to a rapid increase in sustainable value cocreation activities with customers in order to know what a customer wants. In this study, we have studied about co-creation experience in social platform service. Previous prior studies have systematically classify co-creation between customer and enterprise as co-product and value-in-use, Conceptual factors. The co-creation and value-in-use factors theoretically derived from previous researches attempt to investigate the relationship between value co-creation experience and online service quality. We also tried to investigate the relationship between value co-creation experience and online service quality, customer equity, and online word of mouth. To do this, social platform services are divided into open sns and closed sns. Open SNS was targeted to Facebook, Twitter, and Pintrest users. Closed sns were targeted to Instagram, Cyworld, Band, and KakaoTalk users. In this study, it was confirmed that the relationship between online service quality, customer equity, and online word of mouth is significant through value co - creation experience. In the future, companies that design social platforms will be asked to do what they should do to co-create with customers, and provide suggestions for how to operate the platform in order to continuously activate value co-creative experiences.

For increase the game speed, game systems apply a multi-threading. The popularization of multi-core system accelerates multi-threading also. Multi-threading brings high performance, but this is not ease to apply the game logic. Because many multi-core system share the memory, if two or more threads access the same memory region, they can be conflicted. Multi-threading uses Lock method to prevent the conflict, but Lock method reduces the performance. For increase the performance, programmer can use Lock-Free method. In this case, we found strange phenomenon that Lock-Free queue operates incorrectly, and this phenomenon has been accelerated by number of threads. In this study, we analyzed the input output of the Lock-Free Queue in multi-core system.

1996년까지 급속한 산엽발전과 소비패턴의 고급화로 안정적이었던 안경 산업의 구 조가 1997년 경제위기 이후에 살아나던 경제활동이 최근 장기적인 불황으로 소비자 의 구매심리 위축을 가져와 안경 착용 인구의 증가에도 볼구하고 안경원의 수익구조 가 악화되고 무분별한 대형할인매장의 출현으로 과당 과열 경쟁 및 공산품과 의료용 구의 결합인 안경제품의 질적 하락이 나타나고 안경원의 목표 고객에 대한 표적 마 케팅 (Target Marketing) 보다는 다양한 고객을 대상으로 하는 대량 마케팅 (Mass Marketing) 에 집중하다보니 재고안경테와 안경렌즈에 대한 부담을 가지게 되고 그 결과 안경원의 구매심리도 위축되어 전반적인 안경 산업의 매출감소를 가져오고 소 비자의 구매의사결정에 혼란을 주고 있는 상황이다. 이러한 상황에서 급속한 소비시장의 침체로 인한 안경원의 매출감소 및 대형할인 매장의 저절불량렌즈의 저가유통으로 인한 피해를 줄이고 고객의 요구를 정확히 파 악하고 낙후된 마케팅환경에 변화를 꾀하고자 안경구매자가 어떤 동기와 이유에서 안경을 선택하며 구매의사결정에 있어서 중요한 변수가 무엇인지를 밝히고 특정 안 경원의 고객을 구매변수에 따라 세분화하여 안경원의 마케팅 전략수립에 유용한 시 사점을 찾아보았다. 따라서 특정 안경원을 방문하는 고객들이 어떠한 변수에 따라 세분화되는지 알아 보기 위하여 5개의 세분 집단으로 나누었고 각각의 집단이 어떠한 변수에 관섬을 가 지고 있는지 분석하였다. 본 연구는 시장을 세분화하여 목표 시장을 만족시킬 수 있는 요인들을 분석하고 세분화 집단별 요언을 분석하여 안경원 경영에 시사점을 주고자 하였다.