Potential energy landscape for oxygen vacancy dynamics in ceria-based solid electrolytes

In this contribution, I provide a comprehensive picture of the potential energy landscape for oxygen-vacancy migration in the lattice of ceria-based solid electrolytes based on the results from a combined application nuclear magnetic resonance and electrochemical impedance spectroscopy. The oxygen vacancies in acceptor-doped ceria perform rapid symmetry-related jumps in the nearest-neighbor coordination shell of the dopant traps as well as hopping from one trap to another over length scales of a few nanometers. The hopping of vacancies between the dopant traps control the ionic conduction process in the ceria solid solutions. In addition, I discuss the extra potential barrier forms at the grain boundary in polycrystalline ceria electrolytes. The additional barrier attributed to the formation of the space charge in the vicinity of the grain boundary results in substantial current obstruction across the grain boundary. It is the high grain boundary resistance that reduces the effective conductivity in ceria-based solid electrolytes. The potential barrier height has been determined using the ratio of the grain boundary resistivity to the bulk counterpart exclusively to date. I will demonstrate using a simple consistency check that the resistivity ratio overestimates the barrier height. Finally, I introduce a new linear diffusion model which allows for more accurate determination of the potentia

Optimization of Reconfigurable Satellite Constellations Using Simulated Annealing and Genetic Algorithm

Agile Earth observation can be achieved with responsiveness in satellite launches, sensor pointing, or orbit reconfiguration. This study presents a framework for designing reconfigurable satellite constellations capable of both regular Earth observation and disaster monitoring. These observation modes are termed global observation mode and regional observation mode, constituting a reconfigurable satellite constellation (ReCon). Systems engineering approaches are employed to formulate this multidisciplinary problem of co-optimizing satellite design and orbits. Two heuristic methods, simulated annealing (SA) and genetic algorithm (GA), are widely used for discrete combinatorial problems and therefore used in this study to benchmark against a gradient-based method. Point-based SA performed similar or slightly better than the gradient-based method, whereas population-based GA outperformed the other two. The resultant ReCon satellite design is physically feasible and offers performance-to-cost(mass) superior to static constellations. Ongoing research on observation scheduling and constellation management will extend the ReCon applications to radar imaging and radio occultation beyond visible wavelengths and nearby spectrums. Keywords: Earth observation; remote sensing; satellite constellation; reconfigurability; repeat ground tracks; simulated annealing; genetic algorith

2Dデザインデータのみで3DCG化する自動3DCG生成システムの開発 : 食品パッケージデザインを中心に

エンジニアリング分野をはじめ、建築、工業製品、エンタテインメント業界において標準となっている3DCGは、CAD・CAM によるデザイン・設計・モデリング・検証・製造までのデータを一貫管理できる。しかし加工食品業界でのパッケージデザイン版下作成にはCGを用いるものの、完成品イメージ画像の作成は現物、もしくはモックアップと呼ばれる模型を用いて写真撮影を行う手法が一般的である。食品産業は「企画・生産・販売のサイクルが短い」ため、新商品をいかに早く市場に送り出せるのかが大きな課題である［1］，［3］。その状況の中、模型制作・写真撮影・背景抜き・画像合成などの作業にかかる手間を考えると3DCGは、効率よい提案となる。しかしながら3DCG用ハードウェア・ソフトウェアの初期費用や熟練された人材確保とその一連のランニングコストは、会社にとって大きな負担になっている。本研究では、リアルタイム3DCG技術とフォルダ監視用スクリプトを融合し、非専門家でもデザイン版下ファイルのみをコピーペーストするだけで、簡単に3DCG 画像を生成できる自動化システムを構築した。クラウドサービスのファイル共有機能と組み合わせれば、世界中どこからでも2Dイメージさえあれば3DCG画像作成が可能となる。The industrial product design and manufacturing use of 3DCG software based on CAD/CAM are mandatory tools to realize precise design and accurate production process. On the other hand, grocery industries are in the middle of severe competitions, each maker tries to launch new products as soon as possible. Shortening the cycle time of new product planning, design & manufacturing and marketing & sale, is one of the keys to success for each company. On the other hand, in recent years of cloud services, improvement of productivity has been increasing year by year due reasons such as cost reduction. In this paper, we combine the real time 3DCG technology and folder monitoring batch technology. Copy paste just did the design image filing, and we build the automation system into which 3DCG picture can be formed easily. When two technologies combined with the file sharing of cloud service, It will be possible anytime and everywhere in the world to make the 3DCG images

Utilization of a combined EEG/NIRS system to predict driver drowsiness

The large number of automobile accidents due to driver drowsiness is a critical concern of many countries. To solve this problem, numerous methods of countermeasure have been proposed. However, the results were unsatisfactory due to inadequate accuracy of drowsiness detection. In this study, we introduce a new approach, a combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG and NIRS signals have been measured during a simulated driving task, in which subjects underwent both awake and drowsy states. The blinking rate, eye closure, heart rate, alpha and beta band power were used to identify subject’s condition. Statistical tests were performed on EEG and NIRS signals to find the most informative parameters. Fisher’s linear discriminant analysis method was employed to classify awake and drowsy states. Time series analysis was used to predict drowsiness. The oxy-hemoglobin concentration change and the beta band power in the frontal lobe were found to differ the most between the two states. In addition, these two parameters correspond well to an awake to drowsy state transition. A sharp increase of the oxy-hemoglobin concentration change, together with a dramatic decrease of the beta band power, happened several seconds before the first eye closure

Enabling Grant-Free URLLC for AoI Minimization in RAN-Coordinated 5G Health Monitoring System

Age of information (AoI) is used to evaluate the performance of 5G health monitoring systems because stale data can be fatal for patients with serious illness. Recently, grant-free ultra-reliable and low latency communications (URLLC) have shown greater potential of minimizing AoI than conventional grant-based approaches; however, existing grant-free schedulers cannot provide guaranteed performance in 5G health monitoring systems because they involve two fundamental problems in time and frequency domains, namely the joint scheduling problem and physical resource block (PRB) allocation. In this study, we investigate two resource allocation problems for the first time, aiming to enable grant-free URLLC to minimize AoI in 5G health monitoring systems. Specifically, we propose two adaptive solutions based on an open radio access network-coordinated wireless system: 1) a joint scheduling algorithm and 2) an adaptive PRB allocation algorithm. To verify the effectiveness of the proposed solutions, we built a simulation environment similar to a real health monitoring system and captured the performance variations under realistic deployment scenarios