There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited. In vision, attention is either applied in conjunction with convolutional networks, or used to replace certain components of convolutional networks while keeping their overall structure in place. We show that this reliance on CNNs is not necessary and a pure transformer applied directly to sequences of image patches can perform very well on image classification tasks. When pre-trained on large amounts of data and transferred to multiple mid-sized or small image recognition benchmarks (ImageNet, CIFAR-100, VTAB, etc.), Vision Transformer (ViT) attains excellent results compared to state-of-the-art convolutional networks while requiring substantially fewer computational resources to train.

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

From the Publisher:
This book explores the meta-heuristics approach called tabu search, which is dramatically changing our ability to solve a hostof problems that stretch over the realms of resource planning,telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics,pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservationand scores of other problems. The major ideas of tabu search arepresented with examples that show their relevance to multipleapplications. Numerous illustrations and diagrams are used to clarifyprinciples that deserve emphasis, and that have not always been wellunderstood or applied. The book's goal is to provide ''hands-on' knowledge and insight alike, rather than to focus exclusively eitheron computational recipes or on abstract themes. This book is designedto be useful and accessible to researchers and practitioners inmanagement science, industrial engineering, economics, and computerscience. It can appropriately be used as a textbook in a masterscourse or in a doctoral seminar. Because of its emphasis on presentingideas through illustrations and diagrams, and on identifyingassociated practical applications, it can also be used as asupplementary text in upper division undergraduate courses. 

Finally, there are many more applications of tabu search than canpossibly be covered in a single book, and new ones are emerging everyday. The book's goal is to provide a grounding in the essential ideasof tabu search that will allow readers to create successfulapplications of their own. Along with the essentialideas,understanding of advanced issues is provided, enabling researchers togo beyond today's developments and create the methods of tomorrow.

Tabu Search

We consider the problem of cooperation among a collection of vehicles performing a shared task using intervehicle communication to coordinate their actions. Tools from algebraic graph theory prove useful in modeling the communication network and relating its topology to formation stability. We prove a Nyquist criterion that uses the eigenvalues of the graph Laplacian matrix to determine the effect of the communication topology on formation stability. We also propose a method for decentralized information exchange between vehicles. This approach realizes a dynamical system that supplies each vehicle with a common reference to be used for cooperative motion. We prove a separation principle that decomposes formation stability into two components: Stability of this is achieved information flow for the given graph and stability of an individual vehicle for the given controller. The information flow can thus be rendered highly robust to changes in the graph, enabling tight formation control despite limitations in intervehicle communication capability.

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Information flow and cooperative control of vehicle formations

Object detection serves as one of most fundamental computer vision tasks. Existing works on object detection heavily rely on dense object candidates, such as k anchor boxes pre-defined on all grids of an image feature map of size H×W. In this paper, we present Sparse R-CNN, a very simple and sparse method for object detection in images. In our method, a fixed sparse set of learned object proposals ( N in total) are provided to the object recognition head to perform classification and localization. By replacing HWk (up to hundreds of thousands) hand-designed object candidates with N (e.g., 100) learnable proposals, Sparse R-CNN makes all efforts related to object candidates design and one-to-many label assignment completely obsolete. More importantly, Sparse R-CNN directly outputs predictions without the non-maximum suppression (NMS) post-processing procedure. Thus, it establishes an end-to-end object detection framework. Sparse R-CNN demonstrates highly competitive accuracy, run-time and training convergence performance with the well-established detector baselines on the challenging COCO dataset and CrowdHuman dataset. We hope that our work can inspire re-thinking the convention of dense prior in object detectors and designing new high-performance detectors. Our code is available at: https://github.com/PeizeSun/SparseR-CNN.

Sparse R-CNN: An End-to-End Framework for Object Detection.

Safety is important in rehabilitation assist suits. To address this issue, we have developed a velocity-based mechanical safety device (VBMSD) for an assist suit to aid flexion and extension of a patient’s knee joint. The VBMSD turns off the assist suit’s motor when the knee joint angular velocity generated by the motor is equal to or higher than a preset threshold level. The name for this level is the “detection velocity level (DVL).” The DVL is adjustable according to the requirement of each patient’s gait exercise. In addition, the VBMSD works even when the assist suit’s computer has broken down, because it consists of only passive mechanical components such as springs. However, not only safety, but portability is also important in the assist suit because patients wear it. Therefore, the VBMSD attached to it is also required to be as small and light as possible. In this paper, we introduce a new compact velocity-based mechanical safety device (compact VBMSD) designed in this study. Comparing the previous VBMSD and the compact VBMSD, we describe how much smaller and lighter the compact VBMSD is. Furthermore, we check that the compact VBMSD does not theoretically resonate with a walking cycle (0-IHz) in their gait exercise. Finally, in order for many patients to use it, we confirm that the DVL in the compact VBMSD is adjustable up to the kneejoint angular velocity of 6 rad/s, which is the velocity level of healthy adults’ walking.

Design of a New Compact Velocity-Based Mechanical Safety Device for a Knee Joint Assist Suit

Vehicle Lateral Control Under Fault in Front Sensors: Controller Design with Mismatched Observers

Hierarchical Adaptable and Transferable Networks (HATN) for Driving Behavior Prediction.

Soft pneumatic actuators are widely used for soft grippers, which are known for their compliance as compared with traditional grippers. The generated force/torque of soft pneumatic actuators directly determines the grasping force. This paper introduces a computationally efficient soft pneumatic actuator (SPA) design methodology. The complex structure of the pneumatic actuator is approximated by a cantilever beam. The relationship between input pressure and output torque is derived by standard mechanical analysis. The design problem is formulated as a model-based optimization problem by treating the input-output mathematical model as the objective function. By solving the optimization problem, the optimal design parameters are obtained. Finite element analysis is applied to preliminarily verify the design parameters without the time-consuming fabrication of many actuators. Three soft actuators with different design parameter sets were fabricated to validate the optimal parameters. This work shows the utility of surprisingly simple calculations and assumptions for rapid parametric design studies.

Masayoshi Tomizuka

Papers

Sparse R-CNN: An End-to-End Framework for Object Detection.

Design of a New Compact Velocity-Based Mechanical Safety Device for a Knee Joint Assist Suit

Vehicle Lateral Control Under Fault in Front Sensors: Controller Design with Mismatched Observers

Hierarchical Adaptable and Transferable Networks (HATN) for Driving Behavior Prediction.

Mechanical Modeling and Optimal Model-based Design of a Soft Pneumatic Actuator