병충해의 조기 발견과 그에 따른 조치의 중요성은 농업 및 생태계 보전에 있어서 핵심적이다. 그러나 초기에는 일반적인 카메라나 센서로는 변화의 정도를 관측하기 어렵다. 이러한 한계를 극복하기 위해 초분광 모듈을 활용하여 파장대별 식 물 데이터를 관측함으로써, 딥러닝 모델을 통해 가로수 식생의 건강 상태를 판별, 병충해 여부를 초기에 확인 가능하다. 이를 통해 조기에 병충해에 대해 조치함으로써 더 큰 피해를 방지할 수 있다. 이러한 접근 방식은 농업 및 생태학 분야 에서 식물의 건강을 모니터링하고 보전하는 데 적극적으로 연구되고 있다.

도로의 포장 상태의 노후화나 관리미흡으로 인하여 시민의 사유 재산 중 주요한 요소인 자동차 등의 손상이나 자동차 사고 로 이어질 수 있어 큰 사회적 비용이 발생할 뿐 아니라, 시민들의 불편과 불만을 초래할 수 있다. 최근 도로 포장의 경우 포트홀 발생 건수와 그에 따른 민원 및 소송 건수가 증가해 행정력 및 예산이 낭비되고 있으며, 서울시의 경우 포장도로 노후화 추이가 증가함에 따라 유 지 관리 비용 또한 증가하고 있다. SOC 시설물 안전성 강화에 대한 사회적 요구는 지속적으로 증가하고 있어 한정된 예산의 효율적 활용을 위한 첨단 유지관리기술 도입이 시급하다.

Second language (L2) peer response literature is defined in part by discourse research, yet there is scant research on text-specific comments, or comments that make explicit text references, thus resisting generic qualities. The purpose of this case study was to examine such peer response activities in an English writing course at a South Korean university. The data comprises two essay assignments with peer response conducted between two drafts – as accomplished during class time on the class learning management system (LMS) – as well as the subsequent revisions in second drafts. This paper expands on previous coding schemes accounting for area, nature and type commentary to account for a specificity dimension, and also links these categories to revision practices. While students entertained diverse commenting and revising options, popular practices included generic evaluating or revising local or surface-level concerns. This paper offers implications for modelling response activities as well as for how to better define specific and complex idea construction exhibited during response.

Contemporary University students are considered the Z generation who were born after 1995. They are more tech savvy than millennials. To target the generation, traditional class management platforms have evolved to smart LMS that is more customized and accessible for smart devices. Global level information search and collaboration can also be implemented using such smart LMS. However, switching from one LMS to another LMS requires great effort from teachers and support from staffs. This study measured the learners’ perception of the system when they were exposed to a new smart-LMS. Blackboard Learn Ultra was used for 15 weeks and at the end of the semester, a questionnaire was administered to the students of these classes. Results indicated that experience with previous LMS discouraged students from adopting Blackboard Learn. Result of TAM modeling indicated that perceived usefulness, compared to perceived ease of use and attitude, was an effective aspect to bring positive acceptance of the system. A qualitative approach and network analysis were also conducted based on students’ responses. Both positive and negative responses were detected. Inconvenience due to mechanical aspects was mentioned. Dissatisfaction compared to previous local LMS use was also mentioned. Mobile application and communication effectiveness were positive aspects. Revised course development and promoting how useful the system may help enhance the acceptance of the new system.

This study presents a research methodology based on a successful e-learning model, which presents the inter-relationship between an e-learner’s characteristics and quality perception in regard to LMS (learning management systems). This research model focuses on the e-Learner’s cognitive empathy, self-regulatory efficacy, self-regulated learning strategies, and satisfaction with the learning environment. The learning environment consists of a learning management system, learning content, as well as interactions which were provided through the e-learning procedures. Based on the assumption that e-learning, as information system - its attributes, correlates with the learner’s characteristics, the study verified user-satisfaction and system’s quality to information systems. In the information systems success model, independent variables are such as an e-Learner’s cognitive empathy, self-regulated learning strategy, self-regulatory efficacy, satisfaction regarding learning content, system quality, and interactions between the teacher and learner; and the dependent variables are such as the e-Learner’s expected performance and actual performance levels through professor evaluations. This paper concludes that the e-learner’s characteristics, such as cognitive empathy and self-regulated learning strategies, are considered as important variables in respect to e-learning performance. Additionally, LMS quality is also considered to be important. The validity of this research model will be demonstrated on an empirical basis.