Status Report of Neutral Kaon photo-production study using Neutral Kaon Spectrometer 2 (NKS2) at LNS-Tohoku(I. Nuclear Physics)

The approach described in this paper uses an array of Field Programmable Gate Array (FPGA) devices to implement a fault tolerant hardware system that can be compared to the running of fault tolerant software on a traditional processor. Fault tolerance is achieved is achieved by using FPGA with on the fly partial programmability feature. Major considerations while mapping to the FPGA includes the size of the area to be mapped and communication issues related to their communication. Area size selection is compared to the page size selection in Operating System Design. Communication issues between modules are compared to the software engineering paradigms dealing with module coupling, fan-in, fan-out and cohesiveness. Finally, the overhead associated with the downloading of the reconfiguration files is discussed

Vision-Based Classification of Mosquito Species: Comparison of Conventional and Deep Learning Methods

This study aims to propose a vision-based method to classify mosquito species. To investigate the efficiency of the method, we compared two different classification methods: The handcraft feature-based conventional method and the convolutional neural network-based deep learning method. For the conventional method, 12 types of features were adopted for handcraft feature extraction, while a support vector machine method was adopted for classification. For the deep learning method, three types of architectures were adopted for classification. We built a mosquito image dataset, which included 14,400 images with three types of mosquito species. The dataset comprised 12,000 images for training, 1500 images for testing, and 900 images for validating. Experimental results revealed that the accuracy of the conventional method using the scale-invariant feature transform algorithm was 82.4% at maximum, whereas the accuracy of the deep learning method was 95.5% in a residual network using data augmentation. From the experimental results, deep learning can be considered to be effective for classifying the mosquito species of the proposed dataset. Furthermore, data augmentation improves the accuracy of mosquito species’ classification

Double Pion Photoproduction on Deuteron(I. Nuclear Physics)

Exclusive cross sections for double-pion photoproductions on proton and deuteron were measured in an energy range from 0.8 to 1.1GeV using tagged photons at Laboratory of Nuclear Science, Tohoku University. We employed the Neutral Kaon Spectrometer (NKS) to detect two pions in the final state, and deduced the cross section for the π^+π^- photoproduction on the "free" and "bound" proton. We have discriminated between the quasi-free and non-quasi-free process applying the kinematical cut on the missing momentum. We found that the total cross section for the γ"p"→pπ^+π^- reaction was about 60% of that for the "free" proton, and this is consistent with the previously obtained data. The one of the dominant part of the non-quasi-free process was found to be the double Δ production. Its cross section is smaller than the previous investigations

Photoproduction of Neutral Kaons on Liquid Deuterium Target(I. Nuclear Physics)

We have performed the experiment of K^0 photoproduction on the liquid deuterium target with Neutral Kaon Spectrometer (NKS) at LNS-Tohoku. The K^0s were measured via K^0_S→π^+π^- decay channel in the threshold region. The momentum spectra of K^0 photoproduction cross sections were derived and compared with the calculations using representative models