Ultrareliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB) are two types of services with delay Quality-of-Service (QoS) demands. Considering the random and sporadic URLLC packets arrival feature, slicing puncture is believed to be the suitable method to support coexistence communication scenario of eMBB and URLLC terminals. However, slicing puncture in a short time is not trivial, and needs accurate wireless resource scheduling. At the same time, it may damage the QoS of eMBB service. All of these make the QoS guaranteed scheduling problem more challenging. In this article, we investigate the bandwidth, power allocations, slice puncturing problems to find the way satisfying services’ individual QoS demands. For the scheduling of eMBB service, we formulate a joint optimization problem for bandwidth and power allocations with long-term constraints of queues backlog. To solve this problem, we utilize the Lyapunov drift-plus-penalty (DPP) method to establish the relationship between the long-term constraints and the short-term optimization problem, which means that the long-term constraints are gradually satisfied by the proposed strategy at each step. We further divide the short-term optimization problem into two subproblems and adopt a block coordinate descent (BCD) algorithm to reduce the computation complexity. Then, we put forward a one-to-one matching method to solve the integer programming in resource block (RB) allocation and slicing puncture problems. Numerical results demonstrate that the proposed dynamic resource allocation and puncturing strategy (DRAPS) can solve the scheduling problem of eMBB and URLLC services in the presence of multiple randomness of channel-state information (CSI) and URLLC packet arrival.

Fairy circles are circular patches of barren soil forming large clusters in the arid grasslands of Southern Africa (especially in Namibia) and Western Australia. Fairy circles are clearly visible in aerial images shown in applications such as Google Maps, and they can be recorded using sensors mounted on drones in very high image and video resolution for ecological studies aiming at understanding the origin of these patterns. Traditional analysis of fairy circles is done by manual digitising and counting. We also showed recently that, despite being challenging, traditional computer vision methods enabled the detection of fairy circles. To improve fairy circle detection and localization automatically in aerial images, we here present the use of a convolutional neural network (CNN). The results suggest that new methods using CNNs outperform other methods in terms of accuracy.

One of the key features in machine type communications (MTCs), especially for MTCs embracing ultrareliable and low latency communications (URLLCs), is the short packet transmission with finite block-length. Both feature of short packet transmissions and requirement on supporting low latency communications or URLLCs pose challenges to radio access design for MTC networks in fifth generation. In this paper, for the MTC networks with delay-insensitive/URLLC terminals co-existence scenarios, we propose the energy-efficient differentiated ALOHA (D-ALOHA) random access algorithms, which simultaneously achieve energy efficient and satisfy the requirements of URLLC in a distributed mode. First, we abstract a service model of an MTC terminal with joint consideration of the achievable rate for short packet transmissions, the truncated channel inverse scheme, and the D-ALOHA scheme. Based on the formulated service model, then we derive the martingale parameters of service process for each terminal, and analyze the delay-bound violation probability of a terminal via the optimum stopping theory for martingales. The martingales-based delay analysis is verified via simulations. Finally, we formulate our energy-efficient D-ALOHA algorithm as an energy efficiency maximization problem with martingales-based statistical delayquality of service constraints, and the resultant optimization problem is solved by the invasive weed optimization-differential evolution (IWO-DE) algorithm. Furthermore, we propose a suboptimal but low-complexity energy-efficient D-ALOHA scheme, which neglects the distance difference of delay-insensitive terminals, such that the same access probability is imposed on these terminals for reducing the computational complexity of IWO-DE. Simulation results demonstrate that the energy efficiency performance of our D-ALOHA algorithms is favorite, and our D-ALOHA can achieve URLLCs in case of short duration of a slot.

Robots become more and more widely used in medical application especially in minimally invasive surgery (MIS) these years, and endoscope robot is a typical example. There is sill not a kind of conventional endoscope which can reach the whole gastrointestinal (GI) tract. And conventional endoscopes generate pain and discomfort to patients due to the stiffness of their body. Such disadvantages do not exist in endoscope robots. However, the soft and elastic characters of GI tract make the locomotion efficiency of endoscope robot very low. To resolve this problem, it is necessary to find a special locomotion principle which fit the GI tract, and many researchers have paid a lot of effort. In this paper, a novel locomotion principle is proposed, which is the first time used in the endoscope robot. The locomotion principle is obtained by analyzing, simulating and simplifying the movement of mucus-cilia system. To evaluate its performance, a prototype of the endoscope robot adopting this locomotion principle is developed, which is driven by shape memory alloy (SMA) actuator. An in-vitro experiment shows that the robot can move successfully with efficiency about 27%. The result of experiment validates that the proposed locomotion principle fit the GI tract. And some suggestions to enhance the locomotion efficiency are proposed

A family of binary sequences is presented and proved to have optimal correlations and large linear span. It includes the small set of Kasami sequences, No sequence set and TN sequence set as special cases. A lower bound on the linear span of the family is provided. With suitable choices of parameters, it is proved that the family has exponentially larger linear spans than both No sequences and TN sequences.

We study a class of circuit-switched wavelength-routing networks with fixed or alternate routing and with random wavelength allocation. We present an iterative path decomposition algorithm to evaluate accurately and efficiently the blocking performance of such networks with and without wavelength converters. Our iterative algorithm analyzes the original network by decomposing it into single-path subsystems. These subsystems are analyzed in isolation, and the individual results are appropriately combined to obtain a solution for the overall network. To analyze individual subsystems, we first construct an exact Markov process that captures the behavior of a path in terms of wavelength use. We also obtain an approximate Markov process which has a closed-form solution that can be computed efficiently for short paths. We then develop an iterative algorithm to analyze approximately arbitrarily long paths. The path decomposition approach naturally captures the correlation of both link loads and link blocking events. Our algorithm represents a simple and computationally efficient solution to the difficult problem of computing call-blocking probabilities in wavelength-routing networks. We also demonstrate how our analytical techniques can be applied to gain insight into the problem of converter placement in wavelength-routing networks.

We study a class of circuit-switched wavelength routing networks with and without wavelength converters, and we present the first part of a new analytical framework to accurately and efficiently evaluate the blocking performance of such networks. The model allows non-uniform traffic, it accounts for the correlation among the loads at all links in a path, and it can be used when the location of converters is fixed but arbitrary. We first construct an exact Markov process that captures the behaviour of a path in terms of wavelength use. We also obtain an approximate Markov process which has a closed-form solution that can be efficiently computed for short paths. We then develop an iterative algorithm to analyze approximately arbitrarily long paths. The algorithm decomposes a path into shorter segments which are then studied in isolation using the corresponding approximate Markov process. The individual solutions are appropriately combined to obtain a solution for the original path. Finally, we demonstrate how the analytical techniques can be used to gain insight into the problem of converter placement in wavelength routing networks.