Search

The emergence of incremental sheet forming has led to the development of innovative manufacturing techniques that possess great adaptability and hold the potential to provide substantial economic advantages in the realms of advanced technologies and low‐volume production. In this study, specialized analyses are conducted to determine the structure and morphology of the surfaces produced after single‐point incremental sheet forming (SPISF). The material subjected to SPISF is Al 3003. For the material forming, two types of tools, one uncoated and one coated with titanium nitride (TiN), are used. It is observed that the TiN‐coated tool yields the most favorable roughness outcomes and also reduces the values of the forming components. According to the scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis, the deposition of the TiN on the tool is uniform, thus the results relate to the surface roughness and not only justified. [ABSTRACT FROM AUTHOR]

This paper provides an analysis from a biomechanical perspective of the medial opening wedge high tibial osteotomy surgery, a medical procedure commonly used in treating knee osteoarthritis. The aim of this research is to improve the analysed surgical strategy by establishing optimal values for several very important parameters for the geometric planning of this type of surgical intervention. The research methods used are numerical and experimental. We used finite element, a numerical method used to study the intraoperative behavior of the CORA area for different positions of the initiation point of the cut of the osteotomy plane and for different correction angles. We also used an experimental method in order to determine the maximum force which causes the occurrence of cracks or microcracks in the CORA area. This helped us to determine the stresses, the maximum forces, and the force-displacement variations in the hinge area, elements that allowed us to identify the optimal geometric parameters for planning the surgery.

Featured Application: This research provides a "mini intraoperative guide" for geometrical and dimensional planning of the medial wedge open high tibial osteotomy. The values obtained in our study are useful for preventing or minimizing the microfractures that can occur in the center of the rotation of the angulation (CORA) hinge area. This paper provides an analysis from a biomechanical perspective of the medial opening wedge high tibial osteotomy surgery, a medical procedure commonly used in treating knee osteoarthritis. The aim of this research is to improve the analysed surgical strategy by establishing optimal values for several very important parameters for the geometric planning of this type of surgical intervention. The research methods used are numerical and experimental. We used finite element, a numerical method used to study the intraoperative behavior of the CORA area for different positions of the initiation point of the cut of the osteotomy plane and for different correction angles. We also used an experimental method in order to determine the maximum force which causes the occurrence of cracks or microcracks in the CORA area. This helped us to determine the stresses, the maximum forces, and the force-displacement variations in the hinge area, elements that allowed us to identify the optimal geometric parameters for planning the surgery. [ABSTRACT FROM AUTHOR]

Video streaming over cellular network has become extremely popular in 4G and will be an integral part of future cellular networks. While most modern-day video clients continually adapt quality of video streams, they neither coordinate with network elements nor among each other. Consequently, a streaming client may quickly overload the cellular network, leading to poor Quality of Experience (QoE) for users in the network. Motivated by this problem, we present D-VIEWS — a scheduling paradigm that assures video bitrate stability of adaptive video streams while ensuring better system utilization. D-VIEWS only needs to be aware of the set of video bitrates and requires no changes to streaming clients and other network functions. Through simulations, we also study the performance of proportional fairness scheduler and D-VIEWS in the presence of user arrival and departure events. [ABSTRACT FROM AUTHOR]

Lightweight construction combines various materials to create resource efficient components. Thermoplastics (TPs) combined with polyurethane (PUR) foams are increasingly used to create hybrid composites. Optimizing the energy efficiency is one of the main issues in the development of production processes of components. Reducing the number of process steps offers great potential in this respect. PUR foam develops a strong adhesive bond with most materials. This is used for the manufacturing of hybrid composite components by filling complex cavities with PUR foam simultaneously bonded with other TP polymer components. This way, one process step for joining is saved. The interfaces in this composite structures are critical points of the failure. A huge variety of TP is used for the production of hybrid composite components and PUR foam develops varying bonding strengths with all of them. Selecting the suitable TPs for a durable bonding with PUR foam in the desired production process necessarily requires information about the respective specific adhesion. In this investigation, different TPs were processed with PUR foams in order to manufacture sandwich composites. The TP facings are produced in the injection moulding process. Subsequently, the facings are combined with the foam core during reaction injection moulding. The wetting behaviour was examined using the contact angle measurement and the mechanical strength of the interface in the sandwich composite was determined using a tensile test. A precise order of the selected TPs concerning their specific adhesion to PUR foams was achieved with these investigative methods. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of reconstructing coverage maps from path-loss measurements in cellular networks. We propose and evaluate two kernel-based adaptive online algorithms as an alternative to typical offline methods. The proposed algorithms are application-tailored extensions of powerful iterative methods such as the adaptive projected subgradient method (APSM) and a state-of-the-art adaptive multikernel method. Assuming that the moving trajectories of users are available, it is shown how side information can be incorporated in the algorithms to improve their convergence performance and the quality of the estimation. The complexity is significantly reduced by imposing sparsity awareness in the sense that the algorithms exploit the compressibility of the measurement data to reduce the amount of data that is saved and processed. Finally, we present extensive simulations based on realistic data to show that our algorithms provide fast and robust estimates of coverage maps in real-world scenarios. Envisioned applications include path-loss prediction along trajectories of mobile users as a building block for anticipatory buffering or traffic offloading. [ABSTRACT FROM AUTHOR]

With the advent of 5G, standardization and research are currently defining the next generation of radio access. Considering the high constraints imposed by future standards, disruptive technologies such as massive MIMO are being proposed. At the heart of this process are wireless channel models that now need to cover a massive increase in design parameters, a large variety of frequency bands, and heterogeneous deployments. This tutorial presents the key drivers behind the evolution of channel modeling and simulation tools as a platform to evaluate future radio access technologies. This evolution comes with new challenges for the research community; this tutorial surveys these challenges, and the approaces to overcome them. [ABSTRACT FROM PUBLISHER]

In this paper, a novel approach for optimizing resource allocation in wireless small cell networks (SCNs) with device-to-device (D2D) communication is proposed. The proposed approach allows jointly exploiting the wireless and social context of wireless users for optimizing the overall allocation of resources and improving the traffic offload in SCNs. This context-aware resource allocation problem is formulated as a matching game, in which user equipments (UEs) and resource blocks (RBs) rank one another, based on utility functions that capture both wireless and social metrics. Due to social interrelations, this game is shown to belong to a class of matching games with peer effects. To solve this game, a novel self-organizing algorithm is proposed, using which UEs and RBs can interact to decide on their desired allocation. The proposed algorithm is then proven to converge to a two-sided stable matching between UEs and RBs. The properties of the resulting stable outcome are then studied and assessed. Simulation results using real social data show that clustering of socially connected users allows offloading a substantially larger amount of traffic than the conventional context-unaware approach. These results show that exploiting social context has high practical relevance in saving resources on wireless links and in the backhaul. [ABSTRACT FROM PUBLISHER]

Minimizing the cost of deploying and operating a wireless sensor network (WSN) involves deciding how to partition a budget between competing expenses such as node hardware, energy, and labor. Most commercial network operators account for interest rates in their budgeting exercises, providing a financial incentive to defer some costs until a later time. In this paper, we propose a net present cost (NPC) model for WSN capital and operating expenses that accounts for interest rates. Our model optimizes the number, size, and spacing between expenditures in order to minimize the NPC required for the network to achieve a desired operational lifetime. In general, this optimization problem is non-convex, but if the spacing between expenditures is linearly proportional to the size of the expenditures, and the number of maintenance cycles is known in advance, the problem becomes convex and can be solved to global optimality. If non-deferrable recurring costs are low, then evenly spacing the expenditures can provide near-optimal results. With the provided models and methods, network operators can now derive a payment schedule to minimize NPC while accounting for various operational parameters. The numerical examples show substantial cost benefits under practical assumptions. [ABSTRACT FROM PUBLISHER]

The unprecedented growth of mobile video traffic is adding significant pressure to the energy drain at both the network and the end user. Energy-efficient video transmission techniques are thus imperative to cope with the challenge of satisfying user demand at sustainable costs. In this paper, we investigate how predicted user rates can be exploited for energy-efficient video streaming with the popular Hypertext Transfer Protocol (HTTP)-based adaptive streaming (AS) protocols [e.g., dynamic adaptive streaming over HTTP (DASH)]. To this end, we develop an energy-efficient predictive green streaming (PGS) optimization framework that leverages predictions of wireless data rates to achieve the following objectives: 1) Minimize the required transmission airtime without causing streaming interruptions; 2) minimize total downlink base station (BS) power consumption for cases where BSs can be switched off in deep sleep; and 3) enable a tradeoff between AS quality and energy consumption. Our framework is first formulated as mixed-integer linear programming (MILP) where decisions on multiuser rate allocation, video segment quality, and BS transmit power are jointly optimized. Then, to provide an online solution, we present a polynomial-time heuristic algorithm that decouples the PGS problem into multiple stages. We provide a performance analysis of the proposed methods by simulations, and numerical results demonstrate that the PGS framework yields significant energy savings. [ABSTRACT FROM PUBLISHER]

This Special Issue is devoted to the latest advances and challenges in analysis, design, modeling, measurement, and performance evaluation of QoE and QoE-oriented metrics. In " I Impact of VNF Placements on QoE Monitoring in the Cloud i ", Dinh-Xuan et al. discuss challenges for QoE Monitoring. By Arisu et al., and "MUSLIN: A QoE-Aware CDN Resources Provisioning and Advertising System for Cost-Efficient Multi-Source Live Streaming" by Da Silva et al. focus on video streaming in the context of QoE. [Extracted from the article]

The deployment of small cell base stations, SCBSs, overlaid on existing macrocellular systems is seen as a key solution for offloading traffic, optimizing coverage, and boosting the capacity of future cellular wireless systems. The next generation of SCBSs is envisioned to be multimode (i.e., capable of transmitting simultaneously on both licensed and unlicensed bands). This constitutes a cost-effective integration of both WiFi and cellular radio access technologies that can efficiently cope with peak wireless data traffic and heterogeneous quality of service requirements. To leverage the advantage of such multimode SCBSs, we discuss the novel proposed paradigm of cross-system learning by means of which SCBSs self-organize and autonomously steer their traffic flows across different RATs. Cross-system learning allows the SCBSs to leverage the advantage of both the WiFi and cellular worlds. For example, the SCBSs can offload delay-tolerant data traffic to WiFi, while simultaneously learning the probability distribution function of their transmission strategy over the licensed cellular band. This article first introduces the basic building blocks of cross-system learning and then provides preliminary performance evaluation in a Long-Term Evolution simulator overlaid with WiFi hotspots. Remarkably, it is shown that the proposed cross-system learning approach significantly outperforms a number of benchmark traffic steering policies. [ABSTRACT FROM PUBLISHER]