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Automated valet parking (AVP) systems aim to use automated driving technology to park a vehicle from the passenger’s boarding/exiting location to a parking space in a parking lot and recall the vehicle from the parking space to the boarding/exiting location. For multiple vehicles to move efficiently through a parking lot, travel must be mediated between each vehicle. We have proposed a driving control method that improves the efficiency of AVP by using the Spatio-Temporal Grid Reservation mechanism. We previously compared it with an autonomous driving, which showed that the proposed method improved the efficiency of vehicle movement when vehicles are entering small parking lots. In this paper, we modified our previous method to accommodate the increasing number of vehicles in a parking lot and created Spatio-Temporal Grid Model as a vehicle movement model. we evaluate this model by comparing it with Conflict Zone Model and MAPF Model created by the methods proposed in related studies, in addition to an autonomous driving model. We performed simulations varying the percentage of vehicles arriving at the parking lot and showed that Spatio-Temporal grid model improves the efficiency of vehicle movement when vehicles are entering and exiting the lot.

The reliability of V2X (vehicle-to-everything) communication is important for safe automated driving. With the advances in wireless communication and multipath transport protocols, a vehicle can employ multiple wireless interfaces and carry out multipath communication. Although there has been extensive research into increasing the Quality of Service (QoS) performance, such as throughput and delay in V2X communication, few studies have addressed explicit ways of improving the reliability of vehicle-to-cloud (V2C) communication through multipath-based redundancy. This paper addresses the issue of improving V2C reliably via multipath-based packet duplication, with particular consideration given to redundancy mitigation. We propose a method that employs dynamic adjustment of multipath redundancy to maintain packet-delivery reliability in V2C communication while enabling redundancy mitigation. The evaluation results show that the proposed method allows the vehicle to maintain the desired reliability in terms of successful packet transmission while reducing redundancy caused by packet duplication in a multipath connection.

Aerocapture maneuvers refer to a single atmospheric crossing to deplete orbital energy and establish a closed orbit. During the atmospheric flight, adjusting the spacecraft’s vertical lift component in an optimal manner, bang-bang bank control, will minimize the propulsion fuel consumption required to establish the target orbit. However, such methods have been suffering from the performance’s oversensitivity to the control’s instantaneous switching time and poor robustness. To address these problems, we propose a new numerical predictor-corrector guidance algorithm based on the saturation function profile in this paper. The saturation function is used to basically simulate the bang-bang control structure, which enhances the algorithm’s robustness by reducing its dependence on the relevant parameters without losing too much optimality. Monte Carlo simulations in both Earth and Mars scenarios demonstrate the robustness, accuracy, and near-optimal performance of the proposed guidance method.

Preformed crowns are preferred to reduce the failure risk of restoration of primary teeth, but some drawback of conventional material is still a main barrier for their clinical use. Polyether etherketone (PEEK), a tooth colored, high-performance thermoplastic polymer, has been recognized as a promising alternative to manufacture the restoration of primary teeth. However, the hydrophobic surface and low surface energy of PEEK make it hard to establish a strong and durable adhesion. In this study, we have evaluated a modification method of polydopamine (PDA) coating with plasma pretreatment for the PEEK films by physical and chemical characterization, bonding properties, and biocompatibility. The surface properties of PEEK were well-characterized by scanning electron microscope (SEM) and X-ray photoelectron spectroscopy (XPS). The adhesive strength of the PEEK films was greatly improved without significant reduction of the proliferation rate of human gingival fibroblast cells in MTT and Live/Dead assays. Therefore, PDA coating with plasma pretreatment may give a new solution for effective clinical application of PEEK in primary performed crowns.

This paper proposes a novel method to efficiently construct the aerocapture attainability set based on convex optimization. Using dimensionality reduction, constructing the attainability set is equivalent to solving a set of discrete points on its boundary. As solving each of the boundary points is a typical nonlinear optimal control problem, a sequential convex programming method is adopted. The efficiency and accuracy of the proposed algorithm is demonstrated by high-fidelity numerical results. This is the first time that the configuration of the aerocapture attainability set is precisely described by the state variables at atmospheric exit. Since the quantification of the set is significant for assessing the feasibility of performing an aerocapture maneuver, the proposed method can be used as a reliable tool for systematic design for aerocapture mission.

Vehicle-to-Everything (V2X) communications provide opportunities for information sharing among vehicles, edge servers, and cloud services. By the collection and extraction of sensing information from vehicles, such as communication quality or free space size, the edge server in V2X communications can improve its sensing and perception coverage. However, the collection of sensing data from vehicles consumes a large amount of wireless resources and computing resources at the edge server. The objective of this study is to extract object sensing information from vehicles, including the minimum or maximum of the sensing values, with low resource consumption and with high scalability. We propose a method that transforms the extraction of sensing information into a two-level procedure that includes (1) the local sharing and extraction of sensing information among vehicles and (2) the efficient extraction of sensing information at the edge server. Moreover, hybrid communication methods are employed at vehicles, with a short range of communication between vehicles to reduce the consumption of wireless resources for the local sharing of sensing data. The evaluation results show that the proposed method highly reduces the number of reports from the vehicles to the edge server, with a small amount of network resource consumption and scalability.

Natural killer (NK) cells are innate immune effectors with potent antitumor activity. However, tumor cells can create an immunosuppressive microenvironment to escape immune surveillance. Although accumulating evidence indicates that microenvironmental hypoxia plays an important role in favoring tumor development and immune evasion, it remains unclear by what means hypoxia directly impairs NK cell antitumor activity. In this study, we confirmed that hypoxic NK cells showed significantly lower cytotoxicity against tumor cells. Consistent with this finding, we found that the reduction in NK cell cytotoxicity resulting from hypoxia correlated to the lower expression of granzyme B, IFN-γ, and degranulation marker CD107a, as well as activating receptors including NKp30, NKp46, and NKG2D expressed on the surface of NK cells. More importantly, we further demonstrated that a reduction in the phosphorylation levels of ERK and STAT3 secondary to hypoxia was strongly associated with the attenuated NK cell cytotoxicity. Focusing on the mechanism responsible for reduced phosphorylation levels of ERK and STAT3, we reveal that the activation of protein tyrosine phosphatase SHP-1 (Src homology region 2 domain-containing phosphatase-1) following hypoxia might play an essential role in this process. By knocking down SHP-1 or blocking its activity using a specific inhibitor TPI-1, we were able to partially restore NK cell cytotoxicity under hypoxia. Taken together, we demonstrate that hypoxia could impair NK cell cytotoxicity by decreasing the phosphorylation levels of ERK and STAT3 in a SHP-1-dependent manner. Therefore, targeting SHP-1 could provide an approach to enhance NK cell-based tumor immunotherapy.

Gesture recognition (GR) has many applications for human-computer interaction (HCI) in the healthcare, home, and business arenas. However, the common techniques to realize gesture recognition using video processing are computationally intensive and expensive. In this work, we propose to task existing visible light communications (VLC) systems with gesture recognition. Different finger movements are identified by training on the light transitions between fingers using the long short-term memory (LSTM) neural network. This paper describes the design and implementation of the gesture recognition technique for a practical VLC system operating over a distance of 48 cm. The platform uses a single low-cost light-emitting diode (LED) and photo-diode sensor at the receiver side. The system recognizes gestures from interruptions in the direct light transmission, and is therefore suitable for high-speed communication. Gesture recognition accuracies were conducted for five gestures, and results demonstrate that the proposed system is able to accurately identify the gestures in up to 88% of cases.

Wireless multihop infrastructures (WMIs) are promising network platforms that facilitate applications, such as smart cities, emergency responses, and outdoor events. WMIs can allow coverage over large areas with low setup and maintenance overheads. However, WMIs may be susceptible to loss of network connectivity caused by node damage or energy depletion. The end-to-end reachability is essential for the WMI to provide network service to users. This paper studies the problem of network self-recovery to sustain reachability in a WMI network by utilizing autonomous mobile base stations (MBSs). It is assumed that MBS is able to move to and pause or stop at positions in the network area. An MBS could be a self-driving robotic vehicle, or vehicle driven directly or remotely by a human. The proposed MBS approach, MBS-Fit, is a distributed and packet-interaction-based mechanism that allows MBS to automatically construct new routes, assess, and adaptively respond to the fitness of pause positions, such that MBS can provide links to recover the disconnected WMIs. We adopt packet-level evaluation to study the automatic interactions of MBS with the static WMI objects. In particular, the network reachability is measured by the amount of packets successfully delivered from users to the gateway through the WMI. Simulation results reveal that the proposed MBS-Fit approach achieves up to 30% improvement of network reachability in terms of successfully packet delivery compared with the conventional MBS. MBS-Fit mechanism also enables up to 80% improvement in terms of number of packets forwarded at MBS.

A wireless multihop infrastructure (WMI) employs homogeneous and easily deployable wireless routers to facilitate disaster-resilient Internet access in smart cities, emergency situations, and the Internet of Things. On the other hand, however, a WMI is subject to energy constraints, carries unbalanced traffic, and has weaknesses in terms of maintenance, such as the lack of human management. Therefore, efficiently sharing network tasks and energy consumption in a WMI are essential to network sustainability. In this paper, we consider the problem of explicit differentiation presentation for improving network sustainability, which involves two aspects. One is the problem of quantifying the differentiation of network activities and energy consumption. The other is the problem of utilizing the differentiation factor of each node for routing operations so as to regulate network packet flows for sustaining Internet access in a WMI. We examine the differentiation of network activities and energy consumption in WMIs by considering network activities, including not only packet transmission and reception but also packet overhearing, and other types of energy consumption. Based on the quantification of energy differentiation at each base station (BS), we design a novel router metric that enables an efficient sharing of network activities among BSs. The theoretical analyses of energy differentiation were validated based on the packet-level simulation. The simulation results demonstrate that our proposed router metric based on energy differentiation outperforms various other competitive metrics of multihop wireless networks to improve network sustainability for different network models.

Networking services may be broken down in a disaster situation while people in the disaster area(s) strongly demand networking services for both communication and information sharing among users. This requires the fast restoration of networking services to fulfil the demand–supply gap. Although there are a number of studies on restoring communication and networking in disasters, few studies have explicitly examined the service availability during the temporary and partial recovery process of network restoration. From the perspective of users in the disaster area, it is important to be able to communicate or share information with people whenever they want/need to do so. Therefore, partial and local recovery of the networking services also plays an important role for improving service availability in the disaster situations. To assess the restoration effectiveness of networking services with a measure of user satisfaction level, we propose to use instant networking service availability (I-NSA), a novel metric, and we examine the effectiveness of networking service restoration solutions using the metric. I-NSA allows us to clearly express the instant availability of networking services that drastically changes with the elapsed time from the disaster occurrence in disaster areas. This paper examines the effective improvement of I-NSA when Local-and-Instant Clouds (LI-Clouds) are applied to the disaster situation. LI-Cloud has been designed and practically developed to provide deployable networking services to users. We verify that LI-Cloud enables significant improvement on the I-NSA performance in the fast restoration of networking services.

An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner.

On-demand information retrieval enables users to query and collect up-to-date sensing information from sensor nodes. Since high energy efficiency is required in a sensor network, it is desirable to disseminate query messages with small traffic overhead and to collect sensing data with low energy consumption. However, on-demand query messages are generally forwarded to sensor nodes in network-wide broadcasts, which create large traffic overhead. In addition, since on-demand information retrieval may introduce intermittent and spatial data collections, the construction and maintenance of conventional aggregation structures such as clusters and chains will be at high cost. In this paper, we propose an on-demand information retrieval approach that exploits the name resolution of data queries according to the attribute and location of each sensor node. The proposed approach localises each query dissemination and enable localised data collection with maximised aggregation. To illustrate the effectiveness of the proposed approach, an analytical model that describes the criteria of sink proxy selection is provided. The evaluation results reveal that the proposed scheme significantly reduces energy consumption and improves the balance of energy consumption among sensor nodes by alleviating heavy traffic near the sink.

Recently there have been large advances in energy technologies for battery-operated systems, including green energy resources and high capacity batteries. The effective use of battery energy resources in wireless infrastructure networks to improve the versatility and reliability of wireless communications is an important issue. Emerging applications of smart cities, Internet of Things (IoT), and emergency responses highly rely on the basic communication network infrastructures that enable ubiquitous network connections. However, energy consumption by nodes in a wireless infrastructure network depends on the transmissions of other nodes in the network. Considering this inter-dependence is necessary to achieve efficient provision of energy in wireless networks. This paper studies the issue of energy provision for wireless relay nodes in Wireless Multihop Infrastructures (WMI) assuming constraints on the total energy provision. We introduce a scheme of Energy Provision Matching (Matching-EP) for WMI which optimizes energy provision based on matching of energy provision with estimates of differentiated position-dependent energy consumption by wireless nodes distributed in the network. The evaluation results show that Matching-EP with 4%–34% improvement in energy matching degree enables 10%–40% improvement of the network lifetime, and 5%–40% improvement of packet delivery compared with conventional WMI networks.

This study uses an infrared cutting laser system to dice GaAs wafers. The Taguchi method determines the laser wafer dicing parameters [laser power (W), depth of focus (μm), and platform speed (m/s)] in relation to the dicing yield and single-grain compressive strength. An orthogonal array (L9 33), a signal-to-noise ratio, and an analysis of variance are employed to study the effects of these parameters. The result shows that the laser wafer dicing yield ranges from 85.53% to 95.20%, with laser power accounting for 86.08% of the total variation, making it the most significant factor. Additionally, the wafer dicing yield is positively correlated with grain compressive strength. Grain defects and corner chipping produced during the cutting process will reduce the compressive strength of the grains. Under the optimized laser wafer cutting conditions, the dicing yield and grain compressive strength reached 95.87% and 331.93 N/mm2, respectively. [ABSTRACT FROM AUTHOR]