With the widespread adoption of smart farms and continuous advancements in IoT (Internet of Things) technology, acquiring diverse additional data has become increasingly convenient. Consequently, studies relevant to deep learning models that leverage multimodal data for crop disease diagnosis and associated data augmentation methods are significantly growing. We propose a comprehensive deep learning model that predicts crop type, detects disease presence, and assesses disease severity at the same time. We utilize multimodal data comprising crop images and environmental variables such as temperature, humidity, and dew points. We confirmed that the results of diagnosing crop diseases using multimodal data improved 2.58%p performance compared to using crop images only. We also propose a multimodal-based mixup augmentation method capable of utilizing both image and environmental data. In this study, multimodal data refer to data from multiple sources, and multimodal mixup is a data augmentation technique that combines multimodal data for training. This expands the conventional mixup technique that was originally applied solely to image data. Our multimodal mixup augmentation method showcases a performance improvement of 1.33%p compared to the original mixup method.

The increasing demand for laparoscopic surgery due to its cosmetic benefits and rapid post-surgery recovery is juxtaposed with a shortage of surgical support staff. This juxtaposition highlights the necessity for improved camera management in laparoscopic procedures, encompassing positioning, zooming, and focusing. Our feasibility study introduces the information and communications technology (ICT) laparoscopy system designed to aid solo laparoscopic surgery. This system tracks a surgeon’s body motion using a controller, manipulating an embedded camera to focus on specific surgical areas. It comprises a camera module, a camera movement controller, and a motor within the main body, operating connected wires according to controller commands for camera movement. Surgeon movements are detected by an inertial measurement unit (IMU) sensor, facilitating precise camera control. Additional features include a foot pedal switch for motion tracking, a dedicated trocar for main body stability, and a display module. The system’s effectiveness was evaluated using an abdomen phantom model and animal experimentation with a porcine model. The camera responded to human movement within 100 ms, a delay that does not significantly affect procedural performance. The ICT laparoscopy system with advanced motion-tracking technology is a promising tool for solo laparoscopic surgery, potentially improving surgical outcomes and overcoming staff shortages.

Traditional surgical interventions for frontal sinus fractures necessitate a cut on the forehead skin, and extant closed reduction techniques aimed at enhancing accessibility continue to grapple with secure tool fixation, stable bone elevation, and screw breakage risk. To address these challenges and augment surgical efficiency, this study introduces novel surgical devices. Design parameters for models with spiral or L‐shaped tips are established, considering practical medical requirements and constraints, and subsequently validated through finite element method numerical simulations using commercial software, Ansys. Four spiral‐type prototypes are constructed, and three scenarios for each prototype, varying in projection distance from the device handle to the bone‐device contact point, are examined via nonlinear simulation analyses. For the L‐shaped type, three prototypes are developed, and static analyses are conducted for four scenarios per prototype, differing in traction force locations, based on another simulation result concerning moments of inertia calculation with a force boundary condition unlike pressure. Maximum stress results under a specific force are analyzed, and the maximum permissible force is determined under the most unfavorable force application condition. Simulation outcomes indicate that the spiral type offers greater applicability with less force to lift multiple bones, while the L‐shaped type is more suitable under bone hardening conditions.