Showing papers by "Panasonic published in 2017"

GaN-on-Si Power Technology: Devices and Applications

Abstract: In this paper, we present a comprehensive reviewand discussion of the state-of-the-art device technology and application development of GaN-on-Si power electronics. Several device technologies for realizing normally off operation that is highly desirable for power switching applications are presented. In addition, the examples of circuit applications that can greatly benefit from the superior performance of GaN power devices are demonstrated. Comparisonwith other competingpower device technology, such as Si superjunction-MOSFET and SiC MOSFET, is also presented and analyzed. Critical issues for commercialization of GaN-on-Si power devices are discussed with regard to cost, reliability, and ease of use.

Migration of cations induces reversible performance losses over day/night cycling in perovskite solar cells

Abstract: Perovskites have been demonstrated in solar cells with a power conversion efficiency of well above 20%, which makes them one of the strongest contenders for next generation photovoltaics. While there are no concerns about their efficiency, very little is known about their stability under illumination and load. Ionic defects and their migration in the perovskite crystal lattice are some of the most alarming sources of degradation, which can potentially prevent the commercialization of perovskite solar cells (PSCs). In this work, we provide direct evidence of electric field-induced ionic defect migration and we isolate their effect on the long-term performance of state-of-the-art devices. Supported by modelling, we demonstrate that ionic defects, migrating on timescales significantly longer (above 103 s) than what has so far been explored (from 10−1 to 102 s), abate the initial efficiency by 10–15% after several hours of operation at the maximum power point. Though these losses are not negligible, we prove that the initial efficiency is fully recovered when leaving the device in the dark for a comparable amount of time. We verified this behaviour over several cycles resembling day/night phases, thus probing the stability of PSCs under native working conditions. This unusual behaviour reveals that research and industrial standards currently in use to assess the performance and the stability of solar cells need to be adjusted for PSCs. Our work paves the way for much needed new testing protocols and figures of merit specifically designed for PSCs.

Deep-ultraviolet light-emitting diodes with external quantum efficiency higher than 20% at 275 nm achieved by improving light-extraction efficiency

Abstract: Enhancing the light-extraction efficiency is the key issue for realizing highly efficient AlGaN-based ultraviolet light-emitting diodes (UV-LEDs). We introduced several features to improve the light extraction: a transparent AlGaN:Mg contact layer, a Rh mirror electrode, an AlN template on a patterned sapphire substrate, and encapsulation resin. The combination of the AlGaN:Mg contact layer and the Rh mirror electrode significantly improved the output power and the external quantum efficiency (EQE) of UV-LEDs. By introducing the aforementioned features, a maximum EQE of >20% at an emission wavelength of 275 nm and a 20-mA direct current was achieved.

Where, When, and How mmWave is Used in 5G and Beyond

Abstract: Wireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but instead an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes. The paper starts with 28 GHz outdoor backhauling for fixed wireless access and moving hotspots, which will be demonstrated at the PyeongChang winter Olympic games in 2018. The second deployment example is a 60 GHz unlicensed indoor access system at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC) to enable ultra-high speed content download with low latency. The third example is mmWave mesh network to be used as a micro Radio Access Network ({\\mu}-RAN), for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and Vehicular-to-Everything (V2X) communications system, which enables automated driving by exchanging High Definition (HD) dynamic map information between cars and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play important roles for a diverse set of applications that require both ultra-high data rate and low latency communications.

Neural Person Search Machines

Abstract: We investigate the problem of person search in the wild in this work. Instead of comparing the query against all candidate regions generated in a query-blind manner, we propose to recursively shrink the search area from the whole image till achieving precise localization of the target person, by fully exploiting information from the query and contextual cues in every recursive search step. We develop the Neural Person Search Machines (NPSM) to implement such recursive localization for person search. Benefiting from its neural search mechanism, NPSM is able to selectively shrink its focus from a loose region to a tighter one containing the target automatically. In this process, NPSM employs an internal primitive memory component to memorize the query representation which modulates the attention and augments its robustness to other distracting regions. Evaluations on two benchmark datasets, CUHK-SYSU Person Search dataset and PRW dataset, have demonstrated that our method can outperform current state-of-the-arts in both mAP and top-1 evaluation protocols.

Room‐Temperature Formation of Highly Crystalline Multication Perovskites for Efficient, Low‐Cost Solar Cells

Abstract: A room-temperature perovskite material yielding a power conversion efficiency of 18.1% (stabilized at 17.7%) is demonstrated by judicious selection of cations. Both cesium and methylammonium are necessary for room-temperature formamidinium-based perovskite to obtain the photoactive crystalline perovskite phase and high-quality crystals. This room-temperature-made perovskite material shows great potential for low-cost, large-scale manufacturing such as roll-to-roll processing.

Real-time Navigation for Liver Surgery Using Projection Mapping With Indocyanine Green Fluorescence: Development of the Novel Medical Imaging Projection System.

Abstract: Objective The aim of the present study was to evaluate the usefulness of a new imaging device, the Medical Imaging Projection System (MIPS), which uses the indocyanine green emission signal and active projection mapping, for liver resection. Background During anatomic liver resection, surgeons cannot completely view the intraparenchymal structure. Although a fluorescent imaging technique using indocyanine green has recently been developed for hepatobiliary surgery, limitations in its application for real-time navigation persist. Methods We conducted a retrospective review of surgical and clinical outcomes for 23 patients who underwent anatomic hepatectomy using the MIPS and 29 patients who underwent the procedure without MIPS guidance, between September 2014 and September 2015. Results Preoperative characteristics were comparable between the 2 groups. No significant between-group differences were identified with regard to surgical and clinical outcomes. The demarcation lines were clearly projected by the MIPS in 21 patients; however, the boundary line was undetectable in 2 patients. Conclusions We developed the MIPS to address limitations in current intraoperative imaging methods. Our retrospective analysis provides evidence of the feasibility and clinical utility of the MIPS to identify anatomical landmarks for parenchymal dissection. The MIPS holds promise as a novel real-time navigation system for liver resection.

Crystalline Copper(II) Phthalocyanine Catalysts for Electrochemical Reduction of Carbon Dioxide in Aqueous Media

Abstract: We achieved highly selective electrochemical reduction of CO2 to C2H4 (faradaic efficiency of 25%) by crystalline copper phthalocyanine (CuPc) supported on carbon black. Remarkably, noncrystalline CuPc generated by treatment of crystalline CuPc with sulfuric acid did not give C2H4 selectively, suggesting that catalyst crystallinity is crucial for the selective conversion of CO2 to C2H4. The stability of crystalline CuPc under electrochemical reduction conditions was also evaluated, showing that crystalline CuPc can selectively convert CO to C2H4 in the initial stage (<10 000 s), as long as the crystallinity of the catalyst is maintained.

Neural Person Search Machines

Abstract: We investigate the problem of person search in the wild in this work. Instead of comparing the query against all candidate regions generated in a query-blind manner, we propose to recursively shrink the search area from the whole image till achieving precise localization of the target person, by fully exploiting information from the query and contextual cues in every recursive search step. We develop the Neural Person Search Machines (NPSM) to implement such recursive localization for person search. Benefiting from its neural search mechanism, NPSM is able to selectively shrink its focus from a loose region to a tighter one containing the target automatically. In this process, NPSM employs an internal primitive memory component to memorize the query representation which modulates the attention and augments its robustness to other distracting regions. Evaluations on two benchmark datasets, CUHK-SYSU Person Search dataset and PRW dataset, have demonstrated that our method can outperform current state-of-the-arts in both mAP and top-1 evaluation protocols.

Audio-visual emotion recognition using deep transfer learning and multiple temporal models

Abstract: This paper presents the techniques used in our contribution to Emotion Recognition in the Wild 2017 video based sub-challenge. The purpose of the sub-challenge is to classify the six basic emotions (angry, sad, happy, surprise, fear and disgust) and neutral. Our proposed solution utilizes three state-of-the-arts techniques to overcome the challenges for the wild emotion recognition. Deep network transfer learning is used for feature extraction. Spatial-temporal model fusion is to make full use of the complementary of different networks. Semi-auto reinforcement learning is for the optimization of fusion strategy based on dynamic outside feedbacks given by challenge organizers. The overall accuracy of the proposed approach on the challenge test dataset is 57.2%, which is better than the challenge baseline of 40.47% .

17.9 A 105Gb/s 300GHz CMOS transmitter

Abstract: “High speed” in communications often means “high data-rate” and fiber-optic technologies have long been ahead of wireless technologies in that regard. However, an often overlooked definite advantage of wireless links over fiber-optic links is that waves travel at the speed of light c, which is about 50% faster than in optical fibers as shown in Fig. 17.9.1 (top left). This “minimum latency” is crucial for applications requiring real-time responses over a long distance, including high-frequency trading [1]. Further opportunities and new applications might be created if the absolute minimum latency and fiber-optic data-rates are put together. (Sub-)THz frequencies have an extremely broad atmospheric transmission window with manageable losses as shown in Fig. 17.9.1 (top right) and will be ideal for building light-speed links supporting fiber-optic data-rates. This paper presents a 105Gb/s 300GHz transmitter (TX) fabricated using a 40nm CMOS process.

Reliability of hybrid-drain-embedded gate injection transistor

Abstract: Reliability tests on 600V-rated GaN-based normally-off hybrid-drain-embedded Gate Injection Transistor (HD-GIT) are performed High-temperature reverse-bias test on HD-GIT reveals that the lifetime is dependent on the leakage current before the reliability test Acceleration factors for the temperature and reverse bias voltage are extracted Based on the obtained results, devices are designed so that their lifetimes under Vbs=480V (80% de-rated) at 80°C are longer than 1000 years, which are long enough for most conventional power converter applications Dynamic high-temperature operation life test is also performed, under which their DC characteristics are within their normal range up to 3600h In addition, HD-GITs are within their normal range under the similar reliability tests as applied for Si-based power transistors The physical mechanisms for the reliability of HD-GIT are discussed We conclude that the OFF-state reliability is explained by the so-called percolation degradation model, and that the hole injection from the p-type GaN embedded in the drain plays an important role to suppress the degradation under hard-switching operation test

Comprehensive study on initial thermal oxidation of GaN(0001) surface and subsequent oxide growth in dry oxygen ambient

Abstract: Initial oxidation of gallium nitride (GaN) (0001) epilayers and subsequent growth of thermal oxides in dry oxygen ambient were investigated by means of x-ray photoelectron spectroscopy, spectroscopic ellipsometry, atomic force microscopy, and x-ray diffraction measurements. It was found that initial oxide formation tends to saturate at temperatures below 800 °C, whereas the selective growth of small oxide grains proceeds at dislocations in the epilayers, followed by noticeable grain growth, leading to a rough surface morphology at higher oxidation temperatures. This indicates that oxide growth and its morphology are crucially dependent on the defect density in the GaN epilayers. Structural characterizations also reveal that polycrystalline α- and β-phase Ga2O3 grains in an epitaxial relation with the GaN substrate are formed from the initial stage of the oxide growth. We propose a comprehensive model for GaN oxidation mediated by nitrogen removal and mass transport and discuss the model on the basis of ex...

Colour preference varies with lighting application

Abstract: Numerous efforts have been made to investigate how to characterize the effect of light sources on colour preference. This paper describes a psychophysical experiment to compare the colour preference evaluation among three sources for different lighting applications. Three lighting applications – restaurant, retail display, and supermarket – were created in two side-by-side full-scaled rooms. It was found that the colour preference varied with the lighting applications. Although none of the existing single-value measures can predict the preference for all three applications, a single measure is necessary for general consumer use given a careful definition of general lighting. In addition, lighting application specific measures could be useful for lighting professionals and experts. To provide detailed information, a colour distortion icon, with improved test colour samples will be useful.

Transmitting method, transmitting apparatus, and program

Abstract: A visible light signal transmitting method includes: determining a luminance change pattern to transmit the visible light signal; switching a common switch according to the luminance change pattern, the common switch being for turning ON a plurality of light sources in common; and turning ON a first pixel switch, to cause the first light source to be ON for a period in which the common switch is ON and the first pixel switch is ON, to transmit the visible light signal, the first light source being one of the plurality of light sources. In the turning ON of a first pixel switch, when the image is displayed on the display, the first pixel switch is switched to increase a lighting period that corresponds to the first light source, to compensate a period in which the first light source is OFF for transmission of the visible light signal.

Video-based Person Re-identification with Accumulative Motion Context

Abstract: Video based person re-identification plays a central role in realistic security and video surveillance. In this paper we propose a novel Accumulative Motion Context (AMOC) network for addressing this important problem, which effectively exploits the long-range motion context for robustly identifying the same person under challenging conditions. Given a video sequence of the same or different persons, the proposed AMOC network jointly learns appearance representation and motion context from a collection of adjacent frames using a two-stream convolutional architecture. Then AMOC accumulates clues from motion context by recurrent aggregation, allowing effective information flow among adjacent frames and capturing dynamic gist of the persons. The architecture of AMOC is end-to-end trainable and thus motion context can be adapted to complement appearance clues under unfavorable conditions (e.g. occlusions). Extensive experiments are conduced on three public benchmark datasets, i.e., the iLIDS-VID, PRID-2011 and MARS datasets, to investigate the performance of AMOC. The experimental results demonstrate that the proposed AMOC network outperforms state-of-the-arts for video-based re-identification significantly and confirm the advantage of exploiting long-range motion context for video based person re-identification, validating our motivation evidently.

A 2-GS/s 8-bit Time-Interleaved SAR ADC for Millimeter-Wave Pulsed Radar Baseband SoC

Abstract: This paper presents a 2-GS/s 8-bit 16 $\times$ time-interleaved (TI) analog-to-digital converter (ADC) for a millimeter-wave pulsed radar baseband system-on-chip (SoC). To suppress sampling timing errors among sub-ADCs, a foreground timing-skew calibration technique with small additional circuits is proposed. Measured spurious-free dynamic range and signal-to-noise distortion ratio at 1-GHz full Nyquist is, therefore, enhanced by 16 and 11 dB, respectively. Unlike conventional calibration techniques based on redundant ADCs or complicated digital calculations, additional circuit components are only several small resistors and a capacitor, resulting in only 0.4% area penalty. This area saving enables the compact integration of the radar baseband SoC with digital beamforming, where eight-channel TI-ADCs occupy the dominant chip area otherwise. Even though this is foreground, no system performance is sacrificed because the calibration sequence is closed loop and fast enough to be executed during an existing calibration interval in a periodic beam transmission sequence. The TI-ADCs are embedded on industrial SoC in a 40-nm CMOS process. The power consumption including the input buffer and the reference buffer is 54.2 mW from a 1.1-V supply, and figure of merit is 355 fJ/conversion step.

5G-MiEdge: Design, standardization and deployment of 5G phase II technologies: MEC and mmWaves joint development for Tokyo 2020 Olympic games

Abstract: This paper presents the vision of 5G-MiEdge, a research project leveraging the benefits of merging MEC and mmWave technologies. Based on that vision, the most relevant use cases and services for the forthcoming Tokyo 2020 Olympics are proposed. The focus is on showing how integrating MEC and mmWave into the 5G network architecture can offer a much more effective system. That is achieved by means of an edge cloud and the introduction of an ultra-lean and inter-operable signaling, called ‘liquid control plane’, capable of providing ubiquitous allocation of computation and communication resources, in an application-/user-centric framework. Finally standards-related aspects like the 5G-MiEdge impact on the ongoing 3GPP work and the services that compose the 5G phases are discussed.

Impact of assimilating GOES imager clear-sky radiance with a rapid refresh assimilation system for convection-permitting forecast over Mexico

Abstract: The Geostationary Operational Environmental Satellite (GOES) imager data could provide a continuous image of the evolutionary pattern of severe weather phenomena with its high spatial and temporal resolution. The capability to assimilate the GOES imager radiances has been developed within the Weather Research and Forecasting (WRF) model's data assimilation (WRFDA) system. Compared to the benchmark experiment with no GOES imager data, the impact of assimilating GOES imager radiances on the analysis and forecast of convective process over Mexico in 7-10 March 2016 was assessed through analysis/forecast cycling experiments using rapid refresh assimilation system with hybrid-3DEnVar scheme. With GOES imager radiance assimilation, better analyses were obtained in terms of the humidity, temperature and simulated water vapor channel brightness temperature distribution. Positive forecast impacts from assimilating GOES imager radiance were seen when verified against the TAMDAR observation, GOES imager observation and Mexico station precipitation data.

Improved resource allocation for transmissions on unlicensed carriers

Abstract: The invention relates to a method for allocating radio resources to a user terminal for performing communication between a radio control entity and the user terminal in a communication system. At least first predetermined radio resources are configured in the user terminal for use in connection with a particular carrier and are associated with a particular format of a downlink control information, DCI, message. The user terminal receives a DCI message of the particular format from the radio control entity. Upon receiving the DCI message of the particular format, the user terminal identifies the first predetermined radio resources associated with this received DCI message, and using the identified first predetermined radio resources for communication between the user terminal and the radio control entity via the particular carrier. The particular carrier can be an unlicensed carrier.

Update management method, update management system, and non-transitory recording medium

Abstract: An update management method causes an external tool, capable of transmitting an update message to update data such as shared keys within electronic control units (ECUs) making up an onboard network, to update shared keys and the like within the ECUs, while reducing the risk of all ECUs being unauthorizedly rewritten in a case where secret information given to the external tool is leaked. The update management method receives and verifies update authority information indicating authority of the external tool. In a case that an update message instructing updating of shared keys or the like of one or multiple ECUs has been transmitted from the external tool, if the verification is successful and the update authority information indicates that the transmission of the update message is within the range of authority of the external tool, the update is executed at the ECU, and otherwise, update at the ECU is inhibited.

Know You at One Glance: A Compact Vector Representation for Low-Shot Learning

Abstract: Low-shot face recognition is a very challenging yet important problem in computer vision. The feature representation of the gallery face sample is one key component in this problem. To this end, we propose an Enforced Softmax optimization approach built upon Convolutional Neural Networks (CNNs) to produce an effective and compact vector representation. The learned feature representation is very helpful to overcome the underlying multi-modality variations and remain the primary key features as close to the mean face of the identity as possible in the high-dimensional feature space, thus making the gallery basis more robust under various conditions, and improving the overall performance for low-shot learning. In particular, we sequentially leverage optimal dropout, selective attenuation, l2 normalization, and model-level optimization to enhance the standard Softmax objective function for to produce a more compact vectorized representation for low-shot learning. Comprehensive evaluations on the MNIST, Labeled Faces in the Wild (LFW), and the challenging MS-Celeb-1M Low-Shot Learning Face Recognition benchmark datasets clearly demonstrate the superiority of our proposed method over state-of-the-arts. By further introducing a heuristic voting strategy for robust multi-view combination, and our proposed method has won the Top-1 place in the MS-Celeb-1M Low-Shot Learning Challenge.

Convolutional Neural Networks for Multi-topic Dialog State Tracking

Abstract: The main task of the fourth Dialog State Tracking Challenge (DSTC4) is to track the dialog state by filling in various slots, each of which represents a major subject discussed in the dialog. In this article we focus on the ‘INFO’ slot that tracks the general information provided in a sub-dialog segment, and propose an approach for this slot-filling using convolutional neural networks (CNNs). Our CNN model is adapted to multi-topic dialog by including a convolutional layer with general and topic-specific filters. The evaluation on DSTC4 common test data shows that our approach outperforms all other submitted entries in terms of overall accuracy of the ‘INFO’ slot.

Study of Ultrafine Bubble Stabilization by Organic Material Adhesion

Abstract: We confirmed the effect of organic material adhesion as ultrafine bubble (UFB) stabilization mechanism. Organic material was added to generate UFB, and the state of UFB particles was investigated by dynamic light scattering method, transmission electron microscope (TEM), resonance mass measurement method. Disappearance of UFB was suppressed by the addition of organic material, and it was confirmed that the organic material adhered to the surface of UFB. We got the conclusion that adhesion of organic material inhibit gas dissolution from bubbles.

A Multichannel Convolutional Neural Network For Cross-language Dialog State Tracking

Abstract: The fifth Dialog State Tracking Challenge (DSTC5) introduces a new cross-language dialog state tracking scenario, where the participants are asked to build their trackers based on the English training corpus, while evaluating them with the unlabeled Chinese corpus. Although the computer-generated translations for both English and Chinese corpus are provided in the dataset, these translations contain errors and careless use of them can easily hurt the performance of the built trackers. To address this problem, we propose a multichannel Convolutional Neural Networks (CNN) architecture, in which we treat English and Chinese language as different input channels of one single CNN model. In the evaluation of DSTC5, we found that such multichannel architecture can effectively improve the robustness against translation errors. Additionally, our method for DSTC5 is purely machine learning based and requires no prior knowledge about the target language. We consider this a desirable property for building a tracker in the cross-language context, as not every developer will be familiar with both languages.

Improving defrosting performance by controlling frost distribution to match defrosting heat distribution in frost-free household refrigerators

Abstract: In the defrosting process of most of existing frost-free refrigerators, major part of the heat generated by electric heater cannot be absorbed by the frost, resulting in the raise of the energy consumption. The objective of this study is to present a new method to improve the energy efficiency in the defrosting process. Based on the idea of making the frost absorb most of the heat generated by electric heater, a new method of defrosting is proposed, and its principle is to make the defrosting process at different locations complete simultaneously by optimizing the frost mass distribution on the evaporator. In this method, the defrosting heat distribution on evaporator surface, the required frost mass distribution, the required air flow distribution and the structure of return air duct are determined, respectively. Application of this method in an actual household refrigerator shows that the defrosting efficiency is improved by 29.8%.

Driving assistance apparatus and driving assistance method

Abstract: Provided is a method for use by a driving assistance apparatus that assists a transition from an autonomous driving mode in which a vehicle is driven under autonomous control to a manual driving mode in which the vehicle is driven by a driver. The method includes: detecting an activity by the driver; detecting conditions of the driver; and determining a take-over request method which is a method of presenting, in the vehicle, a take-over request that informs the driver that the autonomous driving mode is going to be cancelled, the determining being based on at least the detected activity by the driver and the detected conditions.

Dissociation and Nucleation of Tetra-n-butyl Ammonium Bromide Semi-Clathrate Hydrates at High Pressures

Abstract: The equilibrium pressure–temperature relations of the tetra-n-butyl ammonium bromide (TBAB) semiclathrate hydrate were measured at pressures of up to 80 MPa by high-pressure differential scanning calorimetry. As a pressurizing medium, tetrafluoromethane (CF4), which cannot occupy any hydrate cages in the TBAB semiclathrate hydrate at the present experimental pressures, was used. The dissociation temperature of tetragonal TBAB semiclathrate hydrate (TBAB·26H2O) increases with the increase in pressure, whereas the dissociation enthalpy is (192 ± 3) J·g–1 and almost constant at pressures of up to 80 MPa. The temperature difference between formation and dissociation at the same pressure, that is, the maximum allowable degree of supercooling, is (17.7 ± 0.7) K and independent of the pressure.