Interference-Aware Scheduling for Connectivity in MIMO Ad Hoc Multicast Networks

We consider a multicast scenario involving an ad hoc network of co-channel MIMO nodes in which a source node attempts to share a streaming message with all nodes in the network via some pre-defined multi-hop routing tree. The message is assumed to be broken down into packets, and the transmission is conducted over multiple frames. Each frame is divided into time slots, and each link in the routing tree is assigned one time slot in which to transmit its current packet. We present an algorithm for determining the number of time slots and the scheduling of the links in these time slots in order to optimize the connectivity of the network, which we define to be the probability that all links can achieve the required throughput. In addition to time multiplexing, the MIMO nodes also employ beamforming to manage interference when links are simultaneously active, and the beamformers are designed with the maximum connectivity metric in mind. The effects of outdated channel state information (CSI) are taken into account in both the scheduling and the beamforming designs. We also derive bounds on the network connectivity and sum transmit power in order to illustrate the impact of interference on network performance. Our simulation results demonstrate that the choice of the number of time slots is critical in optimizing network performance, and illustrate the significant advantage provided by multiple antennas in improving network connectivity.Comment: 34 pages, 12 figures, accepted by IEEE Transactions on Vehicular Technology, Dec. 201

An XPS Study of the Radiation-induced Effect on the Thermal Degradation and Charring of Butadiene and its Copolymers

A pseudo-in-situ XPS approach shows that cross-linking induced by irradiation may lead to char formation even though it shows only a small or no effect on the onset temperature of degradation

Additional XPS Studies on the Degradation of Poly(Methyl Methacryalte) and Polystyrene Nanocomposites

XPS studies have been undertaken on exfoliated nanocomposites of polystyrene and poly(methyl methacrylate). One can clearly see that carbon is lost and that oxygen, silicon and aluminum accumulate at the surface of the degrading polymer. The concentration of aluminum at the surface is very low at the beginning of the experiment but makes a large jump at the same temperature at which carbon is lost and oxygen begins to accumulate at the surface. It appears that the ratio of silicon to aluminum changes as the polymer is lost. A brief discussion is given to explain the origin of oxygen at the surface

An XPS study of the thermal degradation of polystyrene-clay nanocomposites

X-ray photoelectron spectroscopy, XPS, has been used to examine several polystyrene-clay nanocomposites. The accumulation of oxygen, from the almuniosilicate, on the surface of the polymer was observed, along with the loss of carbon. This confirms that the barrier properties of the clay provide a mechanism by which nanocomposite formation can enhance the fire retardancy of the polymers. No difference is detected depending upon the extent of exfoliation or intercalation of the nanocomposite. #2002 Elsevier Science Ltd. All rights reserved

Polystyrene Magadiite Nanocomposites

An organically modified magadiite has been prepared and used to make a mixed intercalated-exfoliated polystyrene nanocomposite by bulk polymerization. This system gives excellent improvement in mechanical properties, but the thermogravimetric analysis curves do not show any change in the onset of the degradation and the degradation pathway is not changed from that for virgin polystyrene, unlike the situation for an aluminosilicate clay, monlmorillonite. By cone calorimetry, the peak heat release rate is not changed, again unlike the results with the aluminosilicate. This suggests that not all clays exhibit the same behavior in nanocomposite formation

Cooperative Jamming in MIMO ad-hoc networks

Abstract—In this work, we investigate cooperative jamming schemes for the transmission of confidential messages in ad-hoc networks. By letting mobile units (the helpers) in the vicinity of a legitimate receiver send out jamming signals while a transmitter communicates with the receiver, an environment that is hostile to any eavesdroppers can be established. Meanwhile, the jamming signals are designed in an intelligent way such that the interference that the legitimate receiver experiences is kept low. Two particular approaches are considered, namely, Uncoordinated Cooperative Jamming (UCJ) and Coordinated Cooperative Jamming (CCJ). For both approaches, we present simulation results of the secrecy rate with respect to the node density of the network, the area the helpers occupy, and the number of transmit/receive antennas. Index Terms—Secrecy capacity, MIMO, ad hoc networks, cooperative jamming I

Adaptive fault-tolerant control of uncertain nonlinear systems under Actuator failure of unmanned aerial vehicles

With the increasingly extensive application of UAV technology, UAV accidents are increasing, and the safety problem is becoming more and more serious. Therefore, it is urgent to ensure the safety and reliability of UAV. This paper fi rstly introduces the application requirements and research signifi cance of the fault-tolerant control system of UAV; Secondly, the classifi cation of fault-tolerant control system of UAV is introduced. Finally, taking the nonlinear system of UAV as an example, the controller and its parameters are derived, and Simulink simulation model is established with MATLAB software to verify that the designed adaptive fault-tolerant controller can eff ectively maintain the stability and reliability of the system

ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification

Skin image datasets often suffer from imbalanced data distribution, exacerbating the difficulty of computer-aided skin disease diagnosis. Some recent works exploit supervised contrastive learning (SCL) for this long-tailed challenge. Despite achieving significant performance, these SCL-based methods focus more on head classes, yet ignoring the utilization of information in tail classes. In this paper, we propose class-Enhancement Contrastive Learning (ECL), which enriches the information of minority classes and treats different classes equally. For information enhancement, we design a hybrid-proxy model to generate class-dependent proxies and propose a cycle update strategy for parameters optimization. A balanced-hybrid-proxy loss is designed to exploit relations between samples and proxies with different classes treated equally. Taking both "imbalanced data" and "imbalanced diagnosis difficulty" into account, we further present a balanced-weighted cross-entropy loss following curriculum learning schedule. Experimental results on the classification of imbalanced skin lesion data have demonstrated the superiority and effectiveness of our method