Invasive species compete with native species and damage ecosystems. Due to their limited resources, island ecosystems are vulnerable to impacts of invasive species. In the Deokjeok archipelago, South Korea, invasive sika deer (Cervus nippon ssp. taiouanus) introduced for economic purposes are causing harm through severe browsing. This study aimed to evaluate long-term browsing impacts of invasive deer by tracking vegetation index changes from 1986 to 2020 with Landsat satellite imagery and the LandTrendr algorithm. We compared vegetation index trend using Sen’s slope and Disturbance/Recovery area ratio (D/R ratio) between Gureop-do, where these deer were introduced with rapid population increase, and Deokjeok-do, Baega-do, and Mungapdo where these deer have not been introduced yet. Results showed a decreasing trend of the vegetation index in Gureop-do, while other islands without those deer increased. The cumulative D/R ratio on Gureop-do was 212.44%, meaning that disturbance exceeded the recovery area more than two-fold. In contrast, the D/R ratios for other islands remained under 50%. Sen’s slope and t-test showed a significant decrease of NDVI in Gureop-do after deer introduction in 2000. By quantifying the browsing impact of invasive ungulates in island ecosystems using satellite imagery, time and costeffective strategies for invasive species monitoring are provided.

This study is a preliminary investigation into a method for updating analytical models using actual vibration measurement data to improve the reliability of the seismic performance evaluations. The research was conducted on 26 models with various parameters, aiming to develop an optimal analytical model that closely matches the natural frequencies of the actual building. By identifying the dynamic characteristics of the target building through vibration measurements taken just before the demolition of the structure, the natural frequency analysis results of the analytical models were compared to the measured data. Based on this comparison, an optimized method for adjusting the parameters of the analytical models was derived. Throughout the analysis, various parameters were adjusted, and the eigenvalue analysis results were corrected by comparing them with vibration measurements. Among the comparative analytical models, the model with the lowest error rate was selected. The results showed that, in all cases, the analytical model with a concrete compressive strength of 16 MPa (based on actual measurements), pin boundary conditions, and an idealized strip footing cross-section had the closest match to the actual building's natural frequencies, with an average error of less than 8%.

A total of 225, 3 weeks old weaned pigs of the Landrace × Yorkshire × Duroc breeds with initial average body weight (BW) of 6.25±0.6 kg were randomly assigned to 3 different treatments based on their BW, with each having 5 replicates. Each replicate contained 15 pigs, resulting in 75 pigs per treatment group. The treatment included a basal diet (CON), CON + allicin and cinnamaldehyde mixture 500 ppm (ALI), CON + Bacillus-based probiotics 500 ppm (PRO) tested for 42 days in a 3-phase feeding program (0–14 as phase 1, days 15–28 as phase 2, and days 29–42 as phase 3). Result shows final BW (6.3%) and average daily gain (9.0%) in the overall phase were higher (p<0.05) in PRO compared with CON. At d 14, the level of Escherichia coli was lower (p<0.05) in ALI (12.0%) and PRO (13.2%) over CON. At days 28 (14.6%) and 42 (12.8%), the level of Escherichia coli was lower (p<0.05) in PRO compared with CON. The level of tumor necrosis factor-α was lower (p<0.05) in PRO over CON (15.0%). Superoxide dismutase (9.2%) and immunoglobulin A (19.4%) were higher (p<0.05) in PRO over CON. We concluded that dietary PRO at 500 ppm showed better performance in piglets by enhancing their growth performance and health.

본 연구는 기술수용모델(TAM), 컴퓨터 사회적 행위자 이론(CASA), 그 리고 자극-유기체-반응(S-O-R) 모델을 종합적으로 활용하여, AI 기반 디지털 휴먼 투어 가이드의 ‘신기술적 속성’과 ‘사회적 행위자 특성’이 문화관광 맥락에서 방문객의 감정적 경험 및 문화적 정체성 형성에 어떻 게 작용하는지를 규명하였다. 이를 위해 현장 조사와 온라인 설문을 통 해 총 436부의 유효 표본을 확보하고, 구조방정식 모형과 매개분석을 실 시하였다. 연구 결과, 지각된 기술적 새로움(technological novelty), 신 뢰도(credibility), 인간적 특성(anthropomorphism), 그리고 행위성 (agency)은 모두 방문객의 감정적 경험을 유의미하게 높이는 것으로 나 타났으며, 이는 직·간접적으로 문화적 정체성을 강화하는 데 기여하였다. 반면 지각된 지능적 우위(intelligent advantage)는 통계적으로 유의한 영향이 확인되지 않아, 경험 중심의 맥락에서는 순수하게 합리적인 기술 적 특성만으로는 충분한 방문객 공감을 이끌어내기 어렵다는 점이 시사 되었다. 본 연구는 S-O-R 모델 내에서 감정적 경험의 매개 역할을 부각 함으로써, TAM 및 CASA 이론의 적용 범위를 확장하였다. 또한 실무적 으로는 AI 기반 투어 가이드 디자인 시 새로움, 신뢰도, 인간적 특성, 그 리고 상호작용적 행위성을 강조함으로써 방문객의 감정적 몰입과 문화적 태도를 제고할 수 있음을 제안한다.

This paper addresses a scheduling problem aimed at minimizing makespan in a permutation flow shop with two machines and an inspection process that must be conducted at least once every certain number of outcomes from the first machine. A mathematical programming approach and a genetic algorithm, incorporating Johnson's rule and a specific mutation process, were developed to solve this problem. Johnson's rule was used to generate an initial population, while the mutation process ensured compliance with the inspection constraints. The results showed that within a computation time limit of 300 seconds, the mathematical programming approach often failed to provide optimal or feasible solutions, especially for larger job sets. For instance, when the process times of both machines were similar and the inspection time was longer, the mathematical programming approach failed to solve all 10 experiments with just 15 jobs and only had a 50% success rate for 100 jobs. In contrast, the proposed genetic algorithm solved all instances and delivered equal or superior results compared to the mathematical programming approach.