YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

Twining Poly(polyoxometalate) Chains into Nanoropes

Organic polymers and inorganic clusters belong to two different disciplines and have completely different properties and structures. When a cluster is attached to the backbone of a polymer as a pendant, the resultant hybrid polymers (polyclusters) exhibit unique behaviours totally different from those of conventional polymers owing to the nanoscale size of the cluster and its particular interactions. Herein, the aggregation of a poly(polyoxometalate)—a polynorbornene backbone with inorganic polyoxometalate cluster pendants—upon addition of a non-solvent to its dilute solution is reported. A three-dimensional network of tangled and snake-like nanothreads was observed. Direct visualisation of individual nanoscale clusters enabled identification of single chains within the nanothreads. These observations suggest that during the process of aggregation, the hybrid polymer forms curved or extended chains as a consequence of an armouring effect in which the collapsed cluster pendants wrap around the backbone. The collapse occurs because they become less soluble in the solvent/non-solvent mixture. The extended chains then become entwined and form nanoropes consisting of multiple chains wound around each other. This study provides a deeper understanding of the nature of polyclusters and should also prove useful for their future development and application.     

Range Assignment for Biconnectivity and k-Edge Connectivity in Wireless Ad Hoc Networks

Depending on whether bidirectional links or unidirectional links are used for communications, the network topology under a given range assignment is either an undirected graph referred to as the bidirectional topology, or a directed graph referred to as the unidirectional topology. The Min-Power Bidirectional (resp., Unidirectional) k-Node Connectivity problem seeks a range assignment of minimum total power subject to the constraint that the produced bidirectional (resp. unidirectional) topology is k-vertex connected. Similarly, the Min-Power Bidirectional (resp., Unidirectional) k-Edge Connectivity problem seeks a range assignment of minimum total power subject to the constraint the produced bidirectional (resp., unidirectional) topology is k-edge connected. The Min-Power Bidirectional Biconnectivity problem and the Min-Power Bidirectional Edge-Biconnectivity problem have been studied by Lloyd et al. [23]. They show that range assignment based the approximation algorithm of Khuller and Raghavachari [18], which we refer to as Algorithm KR, has an approximation ratio of at most 2(2 – 2/n)(2 + 1/n) for Min-Power Bidirectional Biconnectivity, and range assignment based on the approximation algorithm of Khuller and Vishkin [19], which we refer to as Algorithm KV, has an approximation ratio of at most 8(1 – 1/n) for Min-Power Bidirectional Edge-Biconnectivity. In this paper, we first establish the NP-hardness of Min-Power Bidirectional (Edge-) Biconnectivity. Then we show that Algorithm KR has an approximation ratio of at most 4 for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity, and Algorithm KV has an approximation ratio of at most 2k for both Min-Power Bidirectional k-Edge Connectivity and Min-Power Unidirectional k-Edge Connectivity. We also propose a new simple constant-approximation algorithm for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity. This new algorithm applies only to Euclidean instances, but is best suited for distributed implementation. A preliminary version of this work appeared in the proceedings of the 2nd International Conference on AD-HOC Network and Wireless (Adhoc-Now 2003). Research performed in part while visiting the Max-Plank-Institut fur Informatik. Gruia Calinescu is an Assistant Professor of Computer Science at the Illinois Institute of Technology since 2000. He held postdoc or visiting researcher positions at DIMACS, University of Waterloo, and Max-Plank Institut fur Informatik. Gruia has a Diploma from University of Bucharest and a Ph.D. from Georgia Insitute of Technology. His research interests are in the area of algorithms. Peng-Jun Wan has joined the Computer Science Department at Illinois Institute of Technology in 1997 and has been an Associate Professor since 2004. He received his Ph.D. in Computer Science from University of Minnesota in 1997, M.S. in Operations Research and Control Theory from Chinese Academy of Science in 1993, and B.S. in Applied Mathematics from Tsinghua University in 1990. His research interests include optical networks and wireless networks.     

Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.     

A Bluetooth Based Sensor Network for Civil Infrastructure Health Monitoring

Communicating with sensors has long been limited either to wired connections or to proprietary wireless communication protocols. Using a ubiquitous and inexpensive wireless communication technology to create Sensor Area Networks (SANs) will accelerate the extensive deployment of sensor technology. Bluetooth, an emerging, worldwide standard for inexpensive, local wireless communication is a viable choice for SANs because of its inherent support for some of the important requirements – low power, small form factor, low cost and sufficient communication range. In this paper we outline an approach, centered on the Bluetooth technology, to support a sensor network composed of fixed wireless sensors for health monitoring of highways, bridges and other civil infrastructures. We present a topology formation scheme that not only takes into account the traffic generated by different sensors but also the associated link strengths, buffer capacities and energy availability. The algorithm makes no particular assumptions as to the placement of nodes, and not all nodes need to be in radio proximity of each other. The output is a tree shaped scatternet rooted at the sensor hub (data logger) that is balanced in terms of traffic carried on each of the links. We also analyze the scheduling, routing and healing aspects of the resulting sensor-net topology.     

A Multilayer Optical Packet Switching Network Based on the Kautz Graph and Optical Passive Star Couplers

The multihop optical network is the most appropriate solution to satisfy the increasing applications of Internet services. This paper extends the regular Kautz graph to one with multiple layers in order to produce more architectural variations. The connectivity between adjacent layers utilizes the systematic connection patterns of a regular Kautz graph. A routing algorithm based on its property is presented. Optical passive star (OPS) couplers are adopted to implement our new topologies. Three scheduling criteria that can solve the contention problem in the intermediate nodes are evaluated and compared in terms of their capability to improve the accessibility.     

固体力学有限元体系的结构拓扑变化理论

本文是文[1]的继续.文[1]提出了杆件系统的结构拓扑变化理论和拓扑变化法本文将这一理论和方法推进到连续体有限元体系;且在此基础上揭示出有限元体系的一个新性质,称为基本位移之梯度的正交性定理,从而给出一套设计敏度的显式表达式,可直接用于计算.