Showing papers by "University of Electro-Communications published in 2018"
TL;DR: AkaBLI produced emissions in vivo that were brighter by a factor of 100 to 1000 than conventional systems, allowing noninvasive visualization of single cells deep inside freely moving animals, and is therefore a bioengineered light source to spur unprecedented scientific, medical, and industrial applications.
Abstract: Bioluminescence is a natural light source based on luciferase catalysis of its substrate luciferin. We performed directed evolution on firefly luciferase using a red-shifted and highly deliverable luciferin analog to establish AkaBLI, an all-engineered bioluminescence in vivo imaging system. AkaBLI produced emissions in vivo that were brighter by a factor of 100 to 1000 than conventional systems, allowing noninvasive visualization of single cells deep inside freely moving animals. Single tumorigenic cells trapped in the mouse lung vasculature could be visualized. In the mouse brain, genetic labeling with neural activity sensors allowed tracking of small clusters of hippocampal neurons activated by novel environments. In a marmoset, we recorded video-rate bioluminescence from neurons in the striatum, a deep brain area, for more than 1 year. AkaBLI is therefore a bioengineered light source to spur unprecedented scientific, medical, and industrial applications.
275 citations
04 Apr 2018
TL;DR: This novel realistic medical image generation approach shows that GANs can generate 128 χ 128 brain MR images avoiding artifacts, and even an expert physician was unable to accurately distinguish the synthetic images from the real samples in the Visual Turing Test.
Abstract: In medical imaging, it remains a challenging and valuable goal how to generate realistic medical images completely different from the original ones; the obtained synthetic images would improve diagnostic reliability, allowing for data augmentation in computer-assisted diagnosis as well as physician training. In this paper, we focus on generating synthetic multi-sequence brain Magnetic Resonance (MR) images using Generative Adversarial Networks (GANs). This involves difficulties mainly due to low contrast MR images, strong consistency in brain anatomy, and intra-sequence variability. Our novel realistic medical image generation approach shows that GANs can generate 128 χ 128 brain MR images avoiding artifacts. In our preliminary validation, even an expert physician was unable to accurately distinguish the synthetic images from the real samples in the Visual Turing Test.
216 citations
TL;DR: The first C–H bond of CH4 is activated by Rh1O5 anchored on the wall of micropores of ZSM-5; the formed CH3 then couples with CO and OH, to produce acetic acid over a low activation barrier.
Abstract: Catalytic transformation of CH4 under a mild condition is significant for efficient utilization of shale gas under the circumstance of switching raw materials of chemical industries to shale gas. Here, we report the transformation of CH4 to acetic acid and methanol through coupling of CH4, CO and O2 on single-site Rh1O5 anchored in microporous aluminosilicates in solution at ≤150 °C. The activity of these singly dispersed precious metal sites for production of organic oxygenates can reach about 0.10 acetic acid molecules on a Rh1O5 site per second at 150 °C with a selectivity of ~70% for production of acetic acid. It is higher than the activity of free Rh cations by >1000 times. Computational studies suggest that the first C–H bond of CH4 is activated by Rh1O5 anchored on the wall of micropores of ZSM-5; the formed CH3 then couples with CO and OH, to produce acetic acid over a low activation barrier. Catalytic transformation of CH4 under mild conditions has implications to shale gas utilization. Here, the authors report the transformation of CH4 to acetic acid through coupling of CH4, CO and O2 on single-site Rh1O5 anchored in microporous aluminosilicates in liquid phase.
206 citations
TL;DR: This work proposes a new type of perovskite material based on mixed tin and germanium, which showed a band gap around 1.4-1.5 eV as measured from photoacoustic spectroscopy, which is ideal from the perspective of solar cells.
Abstract: Lead-based perovskite solar cells have gained ground in recent years, showing efficiency as high as 20%, which is on par with that of silicon solar cells. However, the toxicity of lead makes it a nonideal candidate for use in solar cells. Alternatively, tin-based perovskites have been proposed because of their nontoxic nature and abundance. Unfortunately, these solar cells suffer from low efficiency and stability. Here, we propose a new type of perovskite material based on mixed tin and germanium. The material showed a band gap around 1.4–1.5 eV as measured from photoacoustic spectroscopy, which is ideal from the perspective of solar cells. In a solar cell device with inverted planar structure, pure tin perovskite solar cell showed a moderate efficiency of 3.31%. With 5% doping of germanium into the perovskite, the efficiency improved up to 4.48% (6.90% after 72 h) when measured in air without encapsulation.
181 citations
TL;DR: Novel inorganic CsPb1-x Gex I2 Br perovskite solar cells prepared in humid ambient atmosphere without a glovebox showed nearly no decay after 7 h measurement in 50-60 % relative humidity without encapsulation and the phase stability of the all-inorganic perovkite was effectively enhanced after germanium addition.
Abstract: Compared with organic-inorganic perovskites, all-inorganic cesium-based perovskites without volatile organic compounds have gained extensive interests because of the high thermal stability. However, they have a problem on phase transition from cubic phase (active for photo-electric conversion) to orthorhombic phase (inactive for photo-electric conversion) at room temperature, which has hindered further progress. Herein, novel inorganic CsPb1-x Gex I2 Br perovskites were prepared in humid ambient atmosphere without a glovebox. The phase stability of the all-inorganic perovskite was effectively enhanced after germanium addition. In addition, the highest power conversion efficiency of 10.8 % with high open-circuit voltage (VOC ) of 1.27 V in a planar solar cell based on CsPb0.8 Ge0.2 I2 Br perovskite was achieved. Furthermore, the highest VOC up to 1.34 V was obtained by CsPb0.7 Ge0.3 I2 Br perovskite, which is a remarkable record in the field of all-inorganic perovskite solar cells. More importantly, all the photovoltaic parameters of CsPb0.8 Ge0.2 I2 Br perovskite solar cells showed nearly no decay after 7 h measurement in 50-60 % relative humidity without encapsulation.
161 citations
TL;DR: This survey paper starts with the basic concept of EONs and their unique properties, and then moves to the fragmentation problem in Eons, and evaluates and analyzes the major fragmentation management approaches in terms of blocking probability.
Abstract: Bandwidth fragmentation, a serious issue in elastic optical networks (EONs), can be suppressed by proper management in order to enhance the accommodated traffic demands. In this context, we need an in-depth survey that covers bandwidth fragmentation problems and how to suppress them. This survey paper starts with the basic concept of EONs and their unique properties. This paper then moves to the fragmentation problem in EONs. We discuss and analyze the major conventional spectrum allocation policies in terms of the fragmentation effect in a network. The taxonomies of the fragmentation management approaches are presented along with different node architectures. Subsequently, this paper reviews state-of-the-art fragmentation management approaches. Next, we evaluate and analyze the major fragmentation management approaches in terms of blocking probability. Finally, we address the research challenges and open issues on fragmentation problem in EONs that should be addressed in future research.
156 citations
137 citations
25 Jul 2018
TL;DR: An origami inspired by insect wings is described that displays both high load bearing and high resilience characteristics and is validated by using the origami as an element of a quadcopter frame that can withstand aerodynamic forces within its flight envelope but softens during collisions to avoid permanent damage.
Abstract: Origami manufacturing has led to considerable advances in the field of foldable structures with innovative applications in robotics, aerospace, and metamaterials. However, existing origami are either load-bearing structures that are prone to tear and fail if overloaded or resilient soft structures with limited load capability. In this manuscript, we describe an origami structure that displays both high load bearing and high resilience characteristics. The structure, which is inspired by insect wings, consists of a prestretched elastomeric membrane, akin to the soft resilin joints of insect wings, sandwiched between rigid tiles, akin to the rigid cuticles of insect wings. The dual-stiffness properties of the proposed structure are validated by using the origami as an element of a quadcopter frame that can withstand aerodynamic forces within its flight envelope but softens during collisions to avoid permanent damage. In addition, we demonstrate an origami gripper that can be used for rigid grasping but softens to avoid overloading of the manipulated objects.
112 citations
TL;DR: Improved Voc in tin-lead mixed perovskite solar cells is attributed to the facile charge flow at the interface owing to the reduction of interfacial traps and carrier recombination with spike structure as evidenced by time-resolved photoluminescence, nanosecond transient absorption, and electrochemical impedance spectroscopy measurements.
Abstract: Frequently observed high Voc loss in tin–lead mixed perovskite solar cells is considered to be one of the serious bottle-necks in spite of the high attainable Jsc due to wide wavelength photon harvesting. An amicable solution to minimize the Voc loss up to 0.50 V has been demonstrated by introducing an n-type interface with spike structure between the absorber and electron transport layer inspired by highly efficient Cu(In,Ga)Se2 solar cells. Introduction of a conduction band offset of ∼0.15 eV with a thin phenyl-C61-butyric acid methyl ester layer (∼25 nm) on the top of perovskite absorber resulted into improved Voc of 0.75 V leading to best power conversion efficiency of 17.6%. This enhancement is attributed to the facile charge flow at the interface owing to the reduction of interfacial traps and carrier recombination with spike structure as evidenced by time-resolved photoluminescence, nanosecond transient absorption, and electrochemical impedance spectroscopy measurements.
102 citations
94 citations
TL;DR: In this paper, the major construction and initial phase operation of a second-generation gravitational-wave detector, KAGRA, has been completed and the entire 3 km detector is installed underground in a mine in order to be isolated from background seismic vibrations on the surface.
Abstract: The major construction and initial-phase operation of a second-generation gravitational-wave detector, KAGRA, has been completed. The entire 3 km detector is installed underground in a mine in order to be isolated from background seismic vibrations on the surface. This allows us to achieve a good sensitivity at low frequencies and high stability of the detector. Bare-bones equipment for the interferometer operation has been installed and the first test run was accomplished in March and April of 2016 with a rather simple configuration. The initial configuration of KAGRA is called iKAGRA. In this paper, we summarize the construction of KAGRA, including a study of the advantages and challenges of building an underground detector, and the operation of the iKAGRA interferometer together with the geophysics interferometer that has been constructed in the same tunnel.
TL;DR: Flexibility in forming is reviewed from the viewpoints of process, material, manufacturing environment, new process combinations and machine–system–software interactions.
01 Aug 2018
TL;DR: In this paper, the authors considered MEC for a representative mobile user in an ultra dense network, where one of multiple base stations (BSs) can be selected for computation offloading.
Abstract: To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is emerging as a promising paradigm by providing computing capabilities within radio access networks in close proximity. Nevertheless, the design of computation offloading policies for a MEC system remains challenging. Specifically, whether to execute an arriving computation task at local mobile device or to offload a task for cloud execution should adapt to the environmental dynamics in a smarter manner. In this paper, we consider MEC for a representative mobile user in an ultra dense network, where one of multiple base stations (BSs) can be selected for computation offloading. The problem of solving an optimal computation offloading policy is modelled as a Markov decision process, where our objective is to minimize the long-term cost and an offloading decision is made based on the channel qualities between the mobile user and the BSs, the energy queue state as well as the task queue state. To break the curse of high dimensionality in state space, we propose a deep $Q$ -network-based strategic computation offloading algorithm to learn the optimal policy without having a priori knowledge of the dynamic statistics. Numerical experiments provided in this paper show that our proposed algorithm achieves a significant improvement in average cost compared with baseline policies.
TL;DR: In this paper, the effects of the conduction band offset (CBO) between the electron selective layer (ESL) and the perovskite layer in planar-heterojunction perovsite solar cells (PSCs) have been systematically investigated for the first time.
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TL;DR: In this paper, a deep Q$-network-based strategic computation offloading algorithm is proposed to minimize the long-term cost in a MEC system, where an offloading decision is made based on channel qualities between the mobile user and the BSs, the energy queue state as well as the task queue state.
Abstract: To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is emerging as a promising paradigm by providing computing capabilities within radio access networks in close proximity. Nevertheless, the design of computation offloading policies for a MEC system remains challenging. Specifically, whether to execute an arriving computation task at local mobile device or to offload a task for cloud execution should adapt to the environmental dynamics in a smarter manner. In this paper, we consider MEC for a representative mobile user in an ultra dense network, where one of multiple base stations (BSs) can be selected for computation offloading. The problem of solving an optimal computation offloading policy is modelled as a Markov decision process, where our objective is to minimize the long-term cost and an offloading decision is made based on the channel qualities between the mobile user and the BSs, the energy queue state as well as the task queue state. To break the curse of high dimensionality in state space, we propose a deep $Q$-network-based strategic computation offloading algorithm to learn the optimal policy without having a priori knowledge of the dynamic statistics. Numerical experiments provided in this paper show that our proposed algorithm achieves a significant improvement in average cost compared with baseline policies.
TL;DR: A variational method to obtain many-body ground states of the Bose–Hubbard model using feedforward artificial neural networks is developed and it is shown that many- body ground states with different numbers of particles can be generated by a single network.
Abstract: We have developed a variational method to obtain many-body ground states of the Bose–Hubbard model using feedforward artificial neural networks. A fully connected network with a single hidden layer works better than a fully connected network with multiple hidden layers, and a multilayer convolutional network is more efficient than a fully connected network. AdaGrad and Adam are optimization methods that work well. Moreover, we show that many-body ground states with different numbers of particles can be generated by a single network.
TL;DR: This paper proposes a method for expressing the target form of a snake robot by connecting curve segments whose curvature and torsion are already known and demonstrates the effectiveness of the two gaits on a pipe and rough terrain in experiments.
Abstract: This paper presents a method for designing the gait of a snake robot that moves in a complicated environment. We propose a method for expressing the target form of a snake robot by connecting curve segments whose curvature and torsion are already known. Because the characteristics of each combined shape are clear, we can design the target form intuitively and approximate a snake robot configuration to this form with low computational cost. In addition, we propose two novel gaits for the snake robot as a design example of the proposed method. The first gait is aimed at moving over a flange on a pipe, while the other is the crawler gait aimed at moving over rough terrain. We demonstrated the effectiveness of the two gaits on a pipe and rough terrain in experiments.
TL;DR: Experimental results show under a low excitation intensity that ∼99% of the photoexcited electrons in CsPbI3 QDs can be injected into TiO2 with a size-dependent rate, which is also ∼2.5 times faster than that in the case of ZnO.
Abstract: Photoexcited electron injection dynamics from CsPbI3 quantum dots (QDs) to wide gap metal oxides are studied by transient absorption spectroscopy. Experimental results show under a low excitation intensity that ∼99% of the photoexcited electrons in CsPbI3 QDs can be injected into TiO2 with a size-dependent rate ranging from 1.30 × 1010 to 2.10 × 1010 s–1, which is also ∼2.5 times faster than that in the case of ZnO. A demonstration QD-sensitized solar cell based on a CsPbI3/TiO2 electrode is fabricated that delivers a power conversion efficiency of 5%.
TL;DR: In this paper, a simple yet efficient approach is developed to synthesize perovskite films consisting of monolithic-like grains with micrometer size through in situ deposition of octadecylamine functionalized single-walled carbon nanotubes (ODA-SWCNTs) onto the surface of the perovsite layer.
Abstract: Organic–inorganic lead halide perovskites have shown great future for application in solar cells owing to their exceptional optical and electronic properties. To achieve high-performance perovskite solar cells, a perovskite light absorbing layer with large grains is desirable in order to minimize grain boundaries and recombination during the operation of the device. Herein, a simple yet efficient approach is developed to synthesize perovskite films consisting of monolithic-like grains with micrometer size through in situ deposition of octadecylamine functionalized single-walled carbon nanotubes (ODA-SWCNTs) onto the surface of the perovskite layer. The ODA-SWCNTs form a capping layer that controls the evaporation rate of organic solvents in the perovskite film during the postthermal treatment. This favorable morphology in turn dramatically enhances the short-circuit current density of the perovskite solar cells and almost completely eliminates the hysteresis. A maximum power conversion efficiency of 16.1% is achieved with an ODA-SWCNT incorporated planar solar cell using (FA0.83MA0.17)0.95Cs0.05Pb(I0.83Br0.17)3 as light absorber. Furthermore, the perovskite solar cells with ODA-SWCNT demonstrate extraordinary stability with performance retention of 80% after 45 d stability testing under high humidity (60–90%) environment. This work opens up a new avenue for morphology manipulation of perovskite films and enhances the device stability using carbon material.
TL;DR: It is shown that fiberoptic illumination to Purkinje cells expressing PhotonSABER in vivo inhibited cerebellar motor learning during adaptation of the horizontal optokinetic response and vestibulo-ocular reflex, as well as synaptic AMPA receptor decrease in the flocculus.
TL;DR: In this article, the initial conditions occurring during star formation and the evolution of molecular clouds, across a wide range of environments, are studied in a joint survey program targeting ~2000 Planck Galactic cold clumps (PGCCs) in J = 1-0 transitions of CO isotopologues and ~1000 PGCCs in 850 μm continuum emission.
Abstract: The low dust temperatures (<14 K) of Planck Galactic cold clumps (PGCCs) make them ideal targets to probe the initial conditions and very early phase of star formation. "TOP-SCOPE" is a joint survey program targeting ~2000 PGCCs in J = 1–0 transitions of CO isotopologues and ~1000 PGCCs in 850 μm continuum emission. The objective of the "TOP-SCOPE" survey and the joint surveys (SMT 10 m, KVN 21 m, and NRO 45 m) is to statistically study the initial conditions occurring during star formation and the evolution of molecular clouds, across a wide range of environments. The observations, data analysis, and example science cases for these surveys are introduced with an exemplar source, PGCC G26.53+0.17 (G26), which is a filamentary infrared dark cloud (IRDC). The total mass, length, and mean line mass (M/L) of the G26 filament are ~6200 M ☉, ~12 pc, and ~500 M ☉ pc−1, respectively. Ten massive clumps, including eight starless ones, are found along the filament. The most massive clump as a whole may still be in global collapse, while its denser part seems to be undergoing expansion owing to outflow feedback. The fragmentation in the G26 filament from cloud scale to clump scale is in agreement with gravitational fragmentation of an isothermal, nonmagnetized, and turbulent supported cylinder. A bimodal behavior in dust emissivity spectral index (β) distribution is found in G26, suggesting grain growth along the filament. The G26 filament may be formed owing to large-scale compression flows evidenced by the temperature and velocity gradients across its natal cloud.
TL;DR: In this article, a method to hinder formation of photoinactive δ-FAPbI3 and hysteresis behavior in planar heterojunction perovskite solar cells based on Kx(MA0.17FA0.83)1-PbI2.5Br0.5 (0≤ x ≤ 0.1) through incorporation of potassium ions (K+).
Abstract: Organic–inorganic hybrid lead halide perovskite solar cells have demonstrated competitive power conversion efficiency over 22%; nevertheless, critical issues such as unsatisfactory device stability, serious current–voltage hysteresis, and formation of photo nonactive perovskite phases are obstacles for commercialization of this photovoltaics technology. Herein we report a facial yet effective method to hinder formation of photoinactive δ-FAPbI3 and hysteresis behavior in planar heterojunction perovskite solar cells based on Kx(MA0.17FA0.83)1–xPbI2.5Br0.5 (0≤ x ≤ 0.1) through incorporation of potassium ions (K+). X-ray diffraction patterns demonstrate formation of photoinactive δ-FAPbI3 was almost completely suppressed after K+ incorporation. Density functional theory calculation shows K+ prefers to enter the interstitial sites of perovskite lattice, leading to chemical environmental change in the crystal structure. Ultrafast transient absorption spectroscopy has revealed that K+ incorporation leads to enh...
Leiden University1, National Institutes of Natural Sciences, Japan2, Newcastle University3, University of Chile4, Liverpool John Moores University5, Harvard University6, University of Toronto7, University of Electro-Communications8, Korea Astronomy and Space Science Institute9, Commonwealth Scientific and Industrial Research Organisation10, Boston University11
TL;DR: In this article, the authors analyzed the physical properties of the most massive core, ALMA1, which has no molecular outflows detected in the CO (2-1), SiO (5-4), and H$_2$CO (3-2) lines.
Abstract: Using Galactic Plane surveys, we have selected a massive (1200 M$_\odot$), cold (14 K) 3.6-70 $\mu$m dark IRDC G331.372-00.116. This IRDC has the potential to form high-mass stars and, given the absence of current star formation signatures, it seems to represent the earliest stages of high-mass star formation. We have mapped the whole IRDC with the Atacama Large Millimeter/submillimeter Array (ALMA) at 1.1 and 1.3 mm in dust continuum and line emission. The dust continuum reveals 22 cores distributed across the IRDC. In this work, we analyze the physical properties of the most massive core, ALMA1, which has no molecular outflows detected in the CO (2-1), SiO (5-4), and H$_2$CO (3-2) lines. This core is relatively massive ($M$ = 17.6 M$_\odot$), subvirialized (virial parameter $\alpha_{vir}=M_{vir}/M=0.14$), and is barely affected by turbulence (transonic Mach number of 1.2). Using the HCO$^+$ (3-2) line, we find the first detection of infall signatures in a relatively massive, prestellar core (ALMA1) with the potential to form a high-mass star. We estimate an infall speed of 1.54 km s$^{-1}$ and a high accretion rate of 1.96 $\times$ 10$^{-3}$ M$_\odot$ yr$^{-1}$. ALMA1 is rapidly collapsing, out of virial equilibrium, more consistent with competitive accretion scenarios rather than the turbulent core accretion model. On the other hand, ALMA1 has a mass $\sim$6 times larger than the clumps Jeans mass, being in an intermediate mass regime ($M_{J}=2.7
TL;DR: In this paper, a training method for deep neural network (DNN) based source enhancement to increase objective sound quality assessment (OSQA) scores such as the perceptual evaluation of speech quality was proposed.
Abstract: We propose a training method for deep neural network (DNN) based source enhancement to increase objective sound quality assessment (OSQA) scores such as the perceptual evaluation of speech quality. In many conventional studies, DNNs have been used as a mapping function to estimate time–frequency masks and trained to minimize an analytically tractable objective function such as the mean squared error (MSE). Since OSQA scores have been used widely for sound-quality evaluation, constructing DNNs to increase OSQA scores would be better than using the minimum MSE to create high-quality output signals. However, since most OSQA scores are not analytically tractable, i.e., they are black boxes, the gradient of the objective function cannot be calculated by simply applying backpropagation. To calculate the gradient of the OSQA-based objective function, we formulated a DNN optimization scheme on the basis of black-box optimization , which is used for training a computer that plays a game. For a black-box-optimization scheme, we adopt the policy gradient method for calculating the gradient on the basis of a sampling algorithm. To simulate output signals using the sampling algorithm, DNNs are used to estimate the probability density function of the output signals that maximize OSQA scores. The OSQA scores are calculated from the simulated output signals, and the DNNs are trained to increase the probability of generating the simulated output signals that achieve high OSQA scores. Through several experiments, we found that OSQA scores significantly increased by applying the proposed method, even though the MSE was not minimized.
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TL;DR: In this article, a novel deep learning model, category-based Deep Canonical Correlation Analysis (C-DCCA), is proposed to find the venue where the photo was taken and group venue search by the cross-modal correlation between the input photo and textual description of venues.
Abstract: In this work, travel destination and business location are taken as venues. Discovering a venue by a photo is very important for context-aware applications. Unfortunately, few efforts paid attention to complicated real images such as venue photos generated by users. Our goal is fine-grained venue discovery from heterogeneous social multimodal data. To this end, we propose a novel deep learning model, Category-based Deep Canonical Correlation Analysis (C-DCCA). Given a photo as input, this model performs (i) exact venue search (find the venue where the photo was taken), and (ii) group venue search (find relevant venues with the same category as that of the photo), by the cross-modal correlation between the input photo and textual description of venues. In this model, data in different modalities are projected to a same space via deep networks. Pairwise correlation (between different modal data from the same venue) for exact venue search and category-based correlation (between different modal data from different venues with the same category) for group venue search are jointly optimized. Because a photo cannot fully reflect rich text description of a venue, the number of photos per venue in the training phase is increased to capture more aspects of a venue. We build a new venue-aware multimodal dataset by integrating Wikipedia featured articles and Foursquare venue photos. Experimental results on this dataset confirm the feasibility of the proposed method. Moreover, the evaluation over another publicly available dataset confirms that the proposed method outperforms state-of-the-arts for cross-modal retrieval between image and text.
TL;DR: A vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles.
Abstract: We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches.
TL;DR: The proposed protocol uses a cluster-based approach, where a fuzzy logic-based algorithm is employed to select efficient gateway nodes which bridge the licensed Sub-6 GHz communication and the mmWave communication in order to maximize the overall network throughput.
Abstract: With the rapid increase of vehicular Internet of things applications, it is urgent to design a mobile edge computing architecture, which is possible to distribute and process a large amount of contents with vehicles on the road. From a communication perspective, the current cellular technology faces challenges due to the limited bandwidth in a dense vehicle environment. In this paper, we propose a multi-access edge computing framework and the corresponding communication protocol which integrates licensed Sub-6 GHz band, IEEE 802.11p, and millimeter wave (mmWave) communications for the content distribution and processing in vehicular networks. The proposed protocol uses a cluster-based approach, where a fuzzy logic-based algorithm is employed to select efficient gateway nodes which bridge the licensed Sub-6 GHz communication and the mmWave communication in order to maximize the overall network throughput. IEEE 802.11p vehicle-to-vehicle communication is used to share information among vehicles in order to achieve efficient clustering. We conduct extensive simulations to evaluate the performance of the proposed protocol under various network conditions. Simulation results show that the proposed protocol can achieve significant improvements in various scenarios compared with the existing approaches.
TL;DR: An articulated mobile robot that can climb stairs, and also move in narrow spaces and on 3-D terrain is developed and two control methods are presented that are used to adapt the robot to the surrounding terrain.
Abstract: In this paper, we develop an articulated mobile robot that can climb stairs, and also move in narrow spaces and on 3-D terrain. This paper presents two control methods for this robot. The first is a 3-D steering method that is used to adapt the robot to the surrounding terrain. In this method, the robot relaxes its joints, allowing it to adapt to the terrain using its own weight, and then, resumes its motion employing the follow-the-leader method. The second control method is the semi-autonomous stair climbing method. In this method, the robot connects with the treads of the stairs using a body called a connecting part, and then shifts the connecting part from its head to its tail. The robot then uses the sensor information to shift the connecting part with appropriate timing. The robot can climb stairs using this method even if the stairs are steep, and the sizes of the riser and the tread of the stairs are unknown. Experiments are performed to demonstrate the effectiveness of the proposed methods and the developed robot.
TL;DR: It is shown that the electric field can control the domain wall velocity in a Pt/Co/Pd asymmetric structure and an EF-induced change in the interfacial Dzyaloshinskii-Moriya interaction up to several percent is found to be the origin of the velocity modulation.
Abstract: We show that the electric field (EF) can control the domain wall (DW) velocity in a Pt/Co/Pd asymmetric structure. With the application of a gate voltage, a substantial change in DW velocity up to 50 m/s is observed, which is much greater than that observed in previous studies. Moreover, modulation of a DW velocity exceeding 100 m/s is demonstrated in this study. An EF-induced change in the interfacial Dzyaloshinskii-Moriya interaction (DMI) up to several percent is found to be the origin of the velocity modulation. The DMI-mediated velocity change shown here is a fundamentally different mechanism from that caused by EF-induced anisotropy modulation. Our results will pave the way for the electrical manipulation of spin structures and dynamics via DMI control, which can enhance the performance of spintronic devices.
TL;DR: This paper discusses integrating LTE (Long Term Evolution) with IEEE 802.11p for the content distribution in VANETs and proposes a two-level clustering approach where cluster head nodes in the first level try to reduce the MAC layer contentions for vehicle-tovehicle (V2V) communications, and cluster headNode are responsible for providing a gateway functionality between V2V and LTE.
Abstract: There is an increasing demand for distributing a large amount of content to vehicles on the road. However, the cellular network is not sufficient due to its limited bandwidth in a dense vehicle environment. In recent years, vehicular ad hoc networks (VANETs) have been attracting great interests for improving communications between vehicles using infrastructure-less wireless technologies. In this paper, we discuss integrating LTE (Long Term Evolution) with IEEE 802.11p for the content distribution in VANETs. We propose a two-level clustering approach where cluster head nodes in the first level try to reduce the MAC layer contentions for vehicle-tovehicle (V2V) communications, and cluster head nodes in the second level are responsible for providing a gateway functionality between V2V and LTE. A fuzzy logic-based algorithm is employed in the first-level clustering, and a Q-learning algorithm is used in the second-level clustering to tune the number of gateway nodes. We conduct extensive simulations to evaluate the performance of the proposed protocol under various network conditions. Simulation results show that the proposed protocol can achieve 23% throughput improvement in highdensity scenarios compared to the existing approaches.