This paper addresses a secure caching scheme for information-centric network (ICN)-based wireless sensor networks (WSNs). In order to achieve the above mechanism, we utilize both the public-key cryptography technique and the blockchain technique, which enable data to be safely gathered and the decentralized and crossverified sensing data to be copied and stored. In addition, we propose a protocol design for introducing the proposed structure into an ICN-based WSN system. Furthermore, we formulate statistical models and demonstrate numerical results by performing computer simulations and hardware-based experiments.

We construct detection systems for lung cancer in chest X-ray images with neural networks. The exact position of abnormal area in the X-ray images, namely lung cancer is determined with the result from CT images, and then, the one-dimensional numeric sequences including the abnormal area are used as a teacher signal. In order to reduce noise included in the images, the two-dimensional median filters with various sizes are used in the pre-processing unit of this system, and their sizes are optimized with a view of the performance of the system. At the same time, the ensemble learning method is applied to the detection system. As a result, we were able to construct the detection system with high performance for lung cancer in chest X-ray images.

We propose a multistructure convolutional neural network (CNN) for hiragana recognition of remarkably degraded license plate images captured by security cameras for the purpose of criminal investigation. The proposed multistructure CNN can use the optimal resolution image that cannot be used by conventional CNN by processing multiresolution images so that the recognition performance is improved. In many cases, plural candidates are allowed in remarkably degraded license plate character recognition for criminal investigation because it is not realistic to achieve practical level correct rate with a single candidate. The general criterion of practical level recognition accuracy for criminal investigation is whether the method achieves the correct rate of 90 percent by allowing up to the second candidate. Generally, the recognition accuracy of CNN decreases when the degradation estimation is inaccurate, and the CNN is not optimized. Under the condition that the CNN was not optimized, the proposed multistructure CNN could achieve practical level recognition performance while the conventional CNN could not achieve that performance.

In quantum mechanics and quantum theory, there are interactive phenomena that are dependent on time in the theory of relativity as well as phenomena that are independent of time, such as those discussed with renormalization, gauge theory, and the reduction of wave packets. The steady-state response in circuit theory is independent of time derivative terms. In this session, we attempt to apply circuit theory to renormalization, gauge theory, and the reduction of wave packets on the basis of the steady-state response and losslessness.