As solar photovoltaic (PV) generation becomes cost-effective, power comes into its own as the alternative energy with potential to make up a larger share of growing needs. Consequently, operations and maintenance cost now have large impact on profit managing modules, market participants need estimate in short or long terms future. In this paper, we propose forecasting technique by utilizing convolutional neural networks long–short-term memory recently developed for analyzing time series data...

Several postharvest diseases of table grapes (Vitis vinifera) occur during storage, and gray mold rot is a particularly severe disease because the causal agent, Botrytis cinerea, grows at temperatures as low 0°C. Other diseases, such those caused by Penicillium spp. Aspergillus spp., also often lead to deterioration in quality after harvest. The use plant essential oils thymol linalool, reduce several kinds fruits, including oranges, has received much attention European countries. However,...

Generating realistic synthetic tabular data presents a critical challenge in machine learning. This study introduces simple yet effective method employing Large Language Models (LLMs) tailored to generate data, specifically addressing imbalance problems. We propose novel group-wise prompting CSV-style formatting that leverages the in-context learning capabilities of LLMs produce closely adheres specified requirements and characteristics target dataset. Moreover, our proposed random word...

Multivariate time-series prediction is a common task, but it often becomes challenging due to missing data caused by unreliable sensors and other issues. In fact, inaccurate imputation of values can degrade the downstream performance, so may be better not rely on estimated data. Furthermore, observed contain noise, denoising them helpful for main task at hand. response, we propose novel approach that automatically utilize optimal combination generate only complete, also noise-reduced our own...

In this paper, we aim to unveil the impact of data augmentation in audio-language multi-modal learning, which has not been explored despite its importance. We explore various methods at only train-time but also test-time and find out that proper can lead substantial improvements. Specifically, applying our proposed paired PairMix, is first method, outperforms baselines for both automated audio captioning audio-text retrieval tasks. To fully take advantage augmentation, present multi-level...

Shadow detection is one of the most challenging issues in computer vision. Inspired by great success convolutional neural network (CNN) for problem image restoration, learned features have been widely adopted shadow detection. However, existing methods still suffer from ambiguities driven black-colored objects, which are not actually shaded, as well background clutter. In this letter, we propose attentive feedback feature pyramid (AFFPN) a single image. The key idea proposed method to...

Presently, multirotor unmanned aerial vehicles (UAV) are utilized in numerous applications. Their design governs the system’s controllability and operation performance by influencing achievable forces moments produced. However, unexpected causalities, such as actuator failure, adversely affect their controllability, which raises safety concerns about service. On other hand, flexibility allows further optimization for various requirements, including failure tolerance. Thus, this study...

이 연구의 목적은 제주도로 이주한 경력중단 여성의 노인운동지도자 취업 경험과 의미를 내러티브로 이해하는 데 있다. 이를 위해 연구참여자는 2023년 서귀포 YWCA 교육 수료생 중 취업한 5명이다. 자료수집은 수업 관찰 5회, 인터뷰 8회를 진행하였고, 동료 간 합의 과정을 통해 참여자의 경험에서 공통으로 나타나는 찾아 주제 이야기 구성으로 내용분석 하였다. 연구 결과 첫째, 참여자들은 경험이 자기 이해와 역량 개발에 집중하는 기회로 보고 노인운동지도자의 역할은 직업 가치를 높이고 지역 사회에 기여한다는 자부심을 느끼고 있었다. 둘째, 기혼 여성에게 일과 가정의 양립은 중요한 사안으로 직업전환이 시간제 근무 조건이라는 데에 만족하고 노인운동지도자에 취업함으로써 삶과 역할에 의미 있는 정체성을 갖고 셋째, 참여자에게 재취업은 사회와의 네트워크 통로이자 지역민과 유대관계를 높이는 재사회화 매개 역할로 연구는 여성이 교육을 전환 경험을 탐색했다는 의의가

Visual object tracking, one of the main topics in computer vision, aims to chase a target every frame video sequences. In particular, Siamese-based network architectures have been adopted widely for visual tracking due their correlation-based nature. On other hand, features encoded from template and search image Siamese branches still suffer ambiguities, which are driven by complicated real-world environments, e.g., occlusions rotations. This paper proposes feedback robust tracking. The key...

최근 COVID-19로 인해 교육 현장에서의 e-learning에 대한 요구가 한층 증가하였다. 특히 발음 교육의 경우 학습자가 교사의 입모양을 보고 발음을 들으면서 학습하는데 코로나 이후 교실에서 마스크를 낀 채 수업을 진행하고 있어 학습에 어려움이 따른다. 이에 본 연구에서는 에듀테크에 기반하여 연습할 수 있는 방안에 대해 고찰하였다. 연구 대상은 학습자 말뭉치 나눔터에서 제공하는 학습자의 오류 데이터를 기반으로 하였다. 방법은 중국어를 모국어로 하는 오류를 추출하여 규칙을 분석하는 방식으로 진행하였다. 그 결과 오류가 많이 나타난 규칙은 경음화, 연음, 격음화 순이었다. 이 결과를 바탕으로 교육에 음성 인식 기술(Speech Recognition Technology), SVM(Support Vector Machine) 기술, 3D 기술 등의 적용을 제안하였다. 결론에서는 에 듀테크 기반의 교육은 시간과 공간을 한계를 극복할 있고, 자가학습과 학습 수준에 따른 맞춤형...

Random expression plays a pivotal role in author’s algorithmic artwork composition. Author tries to find beauty form where perceptibility and randomness are appropriately harmonized. In this paper, author introduces method of using random within limited range intention forming arranging visual elements during the production virtual sculptures. This paper also explains how these two can be interrelated strengthen each other which intentional expressions merged. Randomness has always been...

Diagnosis based on medical images, such as X-ray often involves manual annotation of anatomical keypoints. However, this process significant human efforts and can thus be a bottleneck in the diagnostic process. To fully automate procedure, deep-learning-based methods have been widely proposed achieved high performance detecting keypoints images. these still clinical limitations: accuracy cannot guaranteed for all cases, it is necessary doctors to double-check predictions models. In response,...