Row and Column Distributions of Letter Matrices

A letter matrix is an n-by-n matrix whose entries are n symbols, each appearing n times. The row (column) distribution of a letter matrix is an n-by-n nonnegative integer matrix that tells how many of each letter are in each row (column). A row distribution R and a column distribution C are compatible if there exits a letter matrix A whose row distribution is R and whose column distribution is C. We show that the matrix J of all ones is compatible with any C, and we also consider the the problem of when R and C pairs are compatible in terms of their values and patterns inside the distribution matrices

The Application of Real Option in Corporate Investment

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Ranks of permutative matrices

A new type of matrix, termed permutative, is defined and motivated herein. The focus is upon identifying circumstances under which square permutative matrices are rank deficient. Two distinct ways, along with variants upon them are given. These are a special kind of grouping of rows and a type of partition in which the blocks are again permutative. Other, results are given, along with some questions and conjectures

RSGPT: A Remote Sensing Vision Language Model and Benchmark

The emergence of large-scale large language models, with GPT-4 as a prominent example, has significantly propelled the rapid advancement of artificial general intelligence and sparked the revolution of Artificial Intelligence 2.0. In the realm of remote sensing (RS), there is a growing interest in developing large vision language models (VLMs) specifically tailored for data analysis in this domain. However, current research predominantly revolves around visual recognition tasks, lacking comprehensive, large-scale image-text datasets that are aligned and suitable for training large VLMs, which poses significant challenges to effectively training such models for RS applications. In computer vision, recent research has demonstrated that fine-tuning large vision language models on small-scale, high-quality datasets can yield impressive performance in visual and language understanding. These results are comparable to state-of-the-art VLMs trained from scratch on massive amounts of data, such as GPT-4. Inspired by this captivating idea, in this work, we build a high-quality Remote Sensing Image Captioning dataset (RSICap) that facilitates the development of large VLMs in the RS field. Unlike previous RS datasets that either employ model-generated captions or short descriptions, RSICap comprises 2,585 human-annotated captions with rich and high-quality information. This dataset offers detailed descriptions for each image, encompassing scene descriptions (e.g., residential area, airport, or farmland) as well as object information (e.g., color, shape, quantity, absolute position, etc). To facilitate the evaluation of VLMs in the field of RS, we also provide a benchmark evaluation dataset called RSIEval. This dataset consists of human-annotated captions and visual question-answer pairs, allowing for a comprehensive assessment of VLMs in the context of RS

Impact of Different Vegetation Zones on the Velocity and Discharge of Open-Channel Flow

Different types of vegetation widely exist in rivers and wetlands. The vegetation will affect the ecological environment and flow process, thus becoming increasingly significant in river engineering and aquatic environmental management. Previous research on vegetated flow is mainly to understand the flow structure of open channels with fully covered one-layer vegetation. However, vegetation often grows along a river bank and co-exists in different heights. The present paper presents experimental results about the flow characteristics of an open-channel with two sides covered by differently layered vegetation, focusing on the effect of vegetation on the velocity distribution and discharge. Two heights of dowels in 10 cm and 20 cm were used to simulate rigid vegetation and arranged in a linear form on both sides of a channel bed under emergent and fully submerged flow conditions. The velocity at different positions was obtained using ADV (Acoustic Doppler Velocimetry). Measured results demonstrate that there exists a shear layer between free-flow and vegetated zones, indicating that the flow transition occurs between fast-moving flow in the free zone and slowly obstructed flow in the vegetated zone and induces a high shear layer and transverse coherent vortices near the interface. Furthermore, compared with the emergent condition, the discharge through the free-flow region slightly decreases under full submerged conditions while the discharge in the vegetated region increases, indicating that the vegetation does not significantly change the discharge percentage in the free region. These findings on differently-layered vegetation would help riparian management practices to maintain healthy ecological and habitat zones.</jats:p