The Development of the Social Studies Lesson Plan focusing on Modern Political Issues: A Case of A Tentative Lesson Plan "Takeshima Problem"

本研究は、現代社会に対する認識を深めることを目指した社会科歴史の単元開発を目指したものである。そのために、本研究においては、現代、政治の場において問題となっている政策課題を取り上げ、その起源を追及させることを通して現代政治をよりよく理解させるとともに、生徒に問題解決への自分なりの見通しを持たせるように授業を構成している。取り上げた政策課題は領土問題であり、具体的には日韓の間で議論となっている「竹島問題」を扱った。開発した単元は、特定の主義・主張を教え込むのではなく、公立な立場から政策問題について思考・判断させ、自主的な思想形成を促すものと評価され得るものである

Neutrino emissions in all flavors up to the pre-bounce of massive stars and the possibility of their detections

This paper is a sequel to our previous one (Kato et al.2015), which calculated the luminosities and spectra of electron-type anti-neutrinos ($\bar{\nu}_e$'s) from the progenitors of core-collapse supernovae. Expecting that a capability to detect electron-type neutrinos ($\nu_e$'s) will increase dramatically with the emergence of liquid-argon detectors such as DUNE, we broaden the scope in this study to include all-flavors of neutrinos emitted from the pre-bounce phase. We pick up three progenitor models of an electron capture supernova (ECSN) and iron-core collapse supernovae (FeCCSNe). We find that the number luminosities reach $\sim10^{57} \mathrm{s^{-1}}$ and $\sim10^{53} \mathrm{s^{-1}}$ at maximum for $\nu_e$ and $\bar{\nu}_e$, respectively. We also estimate the numbers of detection events at terrestrial neutrino detectors including DUNE, taking flavor oscillations into account and assuming the distance to the progenitors to be 200 pc. It is demonstrated that $\bar{\nu}_e$'s from the ECSN-progenitor will be undetected at almost all detectors, whereas we will be able to observe $\gtrsim$15900 $\nu_e$'s at DUNE for the inverted mass hierarchy. From the FeCCSN-progenitors, the number of $\bar{\nu}_e$ events will be largest for JUNO, 200-900 $\bar{\nu}_e$'s, depending on the mass hierarchy whereas the number of $\nu_e$ events at DUNE is $\gtrsim$2100 for the inverted mass hierarchy. These results imply that the detection of $\bar{\nu}_e$'s is useful to distinguish FeCCSN- from ECSN-progenitors, while $\nu_e$'s will provide us with detailed information on the collapse phase regardless of the type and mass of progenitor.Comment: 22 pages, 14 figures, 4 tables, accepted to Ap

Idea Creation: Function Synthesis Approach with Simplification and Evaluation

AbstractProduct engineer is being required to design attractive products in a short product development cycle from stakeholder. And, its attraction is influenced a great deal by idea creation in a conceptual design phase of this cycle. On the other hand, K. Yoshioka and H. Hasegawa proposed the FSA (Function Synthesis Approach) to create a combination of a large number of functions in a short period of time. FSA become a conceptual design support tool that combines the PSO (Particle Swarm Optimization) and the particle method of USIT. However, FSA is only to outputting combination of large numbers of functions. For this reason, there is a need to provide a way to support the conceptual design process systematically. Therefore, this paper proposes a method to systematically support the conceptual design process from the output of the FSA. This systematic process is consisted from two phases. First, the design solution is built by combination of large number of function via using axiomatic design and function structure method. Next, it is evaluated by using UCP (Use Case Points) method. And, this paper described these phases via example to the refrigerator

Coupled Simulation of Shock Waves in Gas-Particle Mixtures Introducing Motion Equations

In this work, direct numerical analyses for flow around particles passing a shock wave was carried out to predict effects of small particles in rocket plumes. A flow solver based on three-dimensional compressible Navier-Stokes equations is developed for the purpose of high accurate prediction of the acoustic field around rocket plumes. This flow solver is capable of analysing a flow around moving multiple particles and motion equations was introduced. The flow field and the drag coefficient after the shock wave passage were validated by comparing with the drag models at shock Mach number 1.2-2.8. The result was in good agreement with the drag models. In the flow around multiple particles, the interference between particles was confirmed

Classification of Known and Unknown Environmental Sounds Based on Self-Organized Space Using a Recurrent Neural Network

Our goal is to develop a system to learn and classify environmental sounds for robots working in the real world. In the real world, two main restrictions pertain in learning. (i) Robots have to learn using only a small amount of data in a limited time because of hardware restrictions. (ii) The system has to adapt to unknown data since it is virtually impossible to collect samples of all environmental sounds. We used a neuro-dynamical model to build a prediction and classification system. This neuro-dynamical model can self-organize sound classes into parameters by learning samples. The sound classification space, constructed by these parameters, is structured for the sound generation dynamics and obtains clusters not only for known classes, but also unknown classes. The proposed system searches on the basis of the sound classification space for classifying. In the experiment, we evaluated the accuracy of classification for both known and unknown sound classes