PDF-VQA: A New Dataset for Real-World VQA on PDF Documents

Document-based Visual Question Answering examines the document understanding of document images in conditions of natural language questions. We proposed a new document-based VQA dataset, PDF-VQA, to comprehensively examine the document understanding from various aspects, including document element recognition, document layout structural understanding as well as contextual understanding and key information extraction. Our PDF-VQA dataset extends the current scale of document understanding that limits on the single document page to the new scale that asks questions over the full document of multiple pages. We also propose a new graph-based VQA model that explicitly integrates the spatial and hierarchically structural relationships between different document elements to boost the document structural understanding. The performances are compared with several baselines over different question types and tasks\footnote{The full dataset will be released after paper acceptance

Form-NLU: Dataset for the Form Language Understanding

Compared to general document analysis tasks, form document structure understanding and retrieval are challenging. Form documents are typically made by two types of authors; A form designer, who develops the form structure and keys, and a form user, who fills out form values based on the provided keys. Hence, the form values may not be aligned with the form designer's intention (structure and keys) if a form user gets confused. In this paper, we introduce Form-NLU, the first novel dataset for form structure understanding and its key and value information extraction, interpreting the form designer's intent and the alignment of user-written value on it. It consists of 857 form images, 6k form keys and values, and 4k table keys and values. Our dataset also includes three form types: digital, printed, and handwritten, which cover diverse form appearances and layouts. We propose a robust positional and logical relation-based form key-value information extraction framework. Using this dataset, Form-NLU, we first examine strong object detection models for the form layout understanding, then evaluate the key information extraction task on the dataset, providing fine-grained results for different types of forms and keys. Furthermore, we examine it with the off-the-shelf pdf layout extraction tool and prove its feasibility in real-world cases.Comment: Accepted by SIGIR 202

Effect of shared decision-making education on physicians’ perceptions and practices of end-of-life care in Korea

Background Evidence of the ethical appropriateness and clinical benefits of shared decision-making (SDM) are accumulating. This study aimed to not only identify physicians’ perspectives on SDM, and practices related to end-of-life care in particular, but also to gauge the effect of SDM education on physicians in Korea. Methods A 14-item questionnaire survey using a modified Delphi process was delivered to nephrologists and internal medicine trainees at 17 university hospitals. Results A total of 309 physicians completed the survey. Although respondents reported that 69.9% of their practical decisions were made using SDM, 59.9% reported that it is not being applied appropriately. Only 12.3% of respondents had received education on SDM as part of their training. The main obstacles to appropriate SDM were identified as lack of time (46.0%), educational materials and tools (29.4%), and education on SDM (24.3%). Although only a few respondents had received training on SDM, the proportion of those who thought they were using SDM appropriately in actual practice was high; the proportion of those who chose lack of time and education as factors that hindered the proper application of SDM was low. Conclusion The majority of respondents believed that SDM was not being implemented properly in Korea, despite its use in actual practice. To improve the effectiveness of SDM in the Korean medical system, appropriate training programs and supplemental policies that guarantee sufficient application time are required

Extrinsic Calibration of Multiple 3D LiDAR Sensors by the Use of Planar Objects

Three-dimensional light detection and ranging (LiDAR) sensors have received much attention in the field of autonomous navigation owing to their accurate, robust, and rich geometric information. Autonomous vehicles are typically equipped with multiple 3D LiDARs because there are many commercially available low-cost 3D LiDARs. Extrinsic calibration of multiple LiDAR sensors is essential in order to obtain consistent geometric information. This paper presents a systematic procedure for the extrinsic calibration of multiple 3D LiDAR sensors using plane objects. At least three independent planes are required within the common field of view of the LiDAR sensors. The planes satisfying the condition can easily be found on objects such as the ground, walls, or columns in indoor and outdoor environments. Therefore, the proposed method does not require environmental modifications such as using artificial calibration objects. Multiple LiDARs typically have different viewpoints to reduce blind spots. This situation increases the difficulty of the extrinsic calibration using conventional registration algorithms. We suggest a plane registration method for cases in which correspondences are not known. The entire calibration process can easily be automated using the proposed registration technique. The presented experimental results clearly show that the proposed method generates more accurate extrinsic parameters than conventional point cloud registration methods

Autonomous Navigation of a Surveillance Robot in Harsh Outdoor Road Environments

This paper deals with the autonomous navigation problem of a mobile robot in outdoor road environments. The target application is surveillance in petroleum storage bases. Although there have been remarkable technological achievements recently in the area of outdoor navigation, robotic systems are still expensive due to a large number of high cost sensors. This paper proposes the reliable extraction algorithm of traversable regions using a single onboard Laser Range Finder (LRF) in outdoor road environments. The traversable regions are derived from the classifications of the road surfaces, curbs, and obstacles. The proposed scheme was experimentally tested in success. Since there are many potential applications that require autonomous service robots to move in semistructured road environments, the proposed scheme can be widely used as a low-cost practical solution

Statistical study on the environmental effects on the natural variation of nutritional components in rice varieties

This study was investigated to compare the natural variation of nutrients in rice variety by different environmental factors. Fifteen kinds of rices were used, which were cultivated in two locations for 2 years. All data were analyzed by the various statistical tools to identify the nutritional variations of nutrients. The results of variable importance in the prediction analysis were found to be consistent with the % variability. The nutrient compositions most affected by variety were fatty acids, and next were vitamins, proximate nutrients, minerals, and amino acids in order. The nutrient compositions most affected by location were proximate, followed by minerals, vitamins, fatty acids, and amino acids. For cultivation year, vitamins were most affected and then minerals, fatty acids, proximate nutrients, and amino acids in order. These findings could explain that each kind of nutrients can be naturally varied by different environmental factors

V-Doc : Visual questions answers with Documents

We propose V-Doc, a question-answering tool using document images and PDF, mainly for researchers and general non-deep learning experts looking to generate, process, and understand the document visual question answering tasks. The V-Doc supports generating and using both extractive and abstractive question-answer pairs using documents images. The extractive QA selects a subset of tokens or phrases from the document contents to predict the answers, while the abstractive QA recognises the language in the content and generates the answer based on the trained model. Both aspects are crucial to understanding the documents, especially in an image format. We include a detailed scenario of question generation for the abstractive QA task. V-Doc supports a wide range of datasets and models, and is highly extensible through a declarative, framework-agnostic platform.Comment: Accepted by CVPR 202

Total kidney and liver volume is a major risk factor for malnutrition in ambulatory patients with autosomal dominant polycystic kidney disease

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)Background In patients with autosomal dominant polycystic kidney disease (ADPKD), malnutrition may develop as renal function declines and the abdominal organs become enlarged. We investigated the relationship of intra-abdominal mass with nutritional status. Methods This cross-sectional study was performed at a tertiary hospital outpatient clinic. Anthropometric and laboratory data including serum creatinine, albumin, and cholesterol were collected, and kidney and liver volumes were measured. Total kidney and liver volume was defined as the sum of the kidney and liver volumes and adjusted by height (htTKLV). Nutritional status was evaluated by using modified subjective global assessment (SGA). Results In a total of 288 patients (47.9% female), the mean age was 48.3 ± 12.2 years and the mean estimated glomerular filtration rate (eGFR) was 65.3 ± 25.3 mL/min/1.73 m2. Of these patients, 21 (7.3%) were mildly to moderately malnourished (SGA score of 4 and 5) and 63 (21.7%) were at risk of malnutrition (SGA score of 6). Overall, patients with or at risk of malnutrition were older, had a lower body mass index, lower hemoglobin levels, and poorer renal function compared to the well-nourished group. However, statistically significant differences in these parameters were not observed in female patients, except for eGFR. In contrast, a higher htTKLV correlated with a lower SGA score, even in subjects with an eGFR ≥45 mL/min/1.73 m2. Subjects with an htTKLV ≥2340 mL/m showed an 8.7-fold higher risk of malnutrition, after adjusting for age, hemoglobin, and eGFR. Conclusions Nutritional risk was detected in 30% of ambulatory ADPKD patients with relatively good renal function. Intra-abdominal organomegaly was related to nutritional status independently from renal function deterioration

Total kidney and liver volume is a major risk factor for malnutrition in ambulatory patients with autosomal dominant polycystic kidney disease

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)Background In patients with autosomal dominant polycystic kidney disease (ADPKD), malnutrition may develop as renal function declines and the abdominal organs become enlarged. We investigated the relationship of intra-abdominal mass with nutritional status. Methods This cross-sectional study was performed at a tertiary hospital outpatient clinic. Anthropometric and laboratory data including serum creatinine, albumin, and cholesterol were collected, and kidney and liver volumes were measured. Total kidney and liver volume was defined as the sum of the kidney and liver volumes and adjusted by height (htTKLV). Nutritional status was evaluated by using modified subjective global assessment (SGA). Results In a total of 288 patients (47.9% female), the mean age was 48.3 ± 12.2 years and the mean estimated glomerular filtration rate (eGFR) was 65.3 ± 25.3 mL/min/1.73 m2. Of these patients, 21 (7.3%) were mildly to moderately malnourished (SGA score of 4 and 5) and 63 (21.7%) were at risk of malnutrition (SGA score of 6). Overall, patients with or at risk of malnutrition were older, had a lower body mass index, lower hemoglobin levels, and poorer renal function compared to the well-nourished group. However, statistically significant differences in these parameters were not observed in female patients, except for eGFR. In contrast, a higher htTKLV correlated with a lower SGA score, even in subjects with an eGFR ≥45 mL/min/1.73 m2. Subjects with an htTKLV ≥2340 mL/m showed an 8.7-fold higher risk of malnutrition, after adjusting for age, hemoglobin, and eGFR. Conclusions Nutritional risk was detected in 30% of ambulatory ADPKD patients with relatively good renal function. Intra-abdominal organomegaly was related to nutritional status independently from renal function deterioration