Underwater image enhancement recovers degraded underwater images to produce corresponding clear images. Image enhancement methods based on deep learning usually use paired data to train the model, while such paired data, e.g., the degraded images and the corresponding clear images, are difficult to capture simultaneously in the underwater environment. In addition, how to retain the detailed information well in the enhanced image is another critical problem. To solve such issues, we propose a novel unpaired underwater image enhancement method via a cycle generative adversarial network (UW-CycleGAN) to recover the degraded underwater images. Our proposed UW-CycleGAN model includes three main modules: (1) A content loss regularizer is adopted into the generator in CycleGAN, which constrains the detailed information existing in one degraded image to remain in the corresponding generated clear image; (2) A blur-promoting adversarial loss regularizer is introduced into the discriminator to reduce the blur and noise in the generated clear images; (3) We add the DenseNet block to the generator to retain more information of each feature map in the training stage. Finally, experimental results on two unpaired underwater image datasets produced satisfactory performance compared to the state-of-the-art image enhancement methods, which proves the effectiveness of the proposed model.

We have calculated and simulated B field along the radial of coil using MATLAB and MAXWELL. Then B field of the transmitting coil and the bucking coil of different radius are generated. Based on the results above, two methods of the magnetic offset are proposed, the B field offset method and magnetic flux offset method. Firstly, we talk about the magnetic field left along the radius of the coil. Secondly we calculate the magnetic flux left when using different radius of the bucking coil to obtain the best results. The magnetic moment of the bucking coil almost has no impact on the total magnetic moment.

The internet of things (IoT) devices are expected to collect vast amounts of data that support different kinds of applications such as health monitor, smart home, and traffic management. However, its characteristics such as resource-constrained nature, dynamicity, and large-scale growth bring challenges to secure IoT data sharing. Nowadays, blockchain-based ciphertext-policy attribute-based encryption (CP-ABE) was proposed to realize secure IoT data sharing. In blockchain-based CP-ABE data sharing schemes, the data are encrypted and stored in the cloud. Once users want to process the data, they should download and then decrypt the ciphertext in the client-end, and after processing the data, users encrypt and upload the ciphertext onto the cloud. This outweighs the advantage of using cloud computing resources. Fully homomorphic encryption (FHE) and homomorphic signature technology may be adopted to realize ciphertext computation and for correctness checking of ciphertext computation results. In this paper, we propose a secure and computable IoT data sharing system to ensure users enjoying the computation convenience of the cloud-end. Specifically, the proposed system integrates CP-ABE and FHE to realize secure IoT data sharing and ciphertext computation. In addition, we generated homomorphic signatures of ciphertexts to enable users to check the correctness of the ciphertext computation results. Moreover, to supervise the cloud, providing the honest IoT data access control, storage, and computing services for users, we recorded the access policy of the data, the hash of the data, the signature of the ciphertext, and the homomorphic signature of the ciphertext on the blockchain. The performance evaluation and security analysis show the proposed scheme is practical and secure.

In a distributed system, cross-domain access control is an important mechanism to realize secure data sharing among multiple domains. Most of the existing cross-domain access control mechanisms are generally based on a single-server architecture, which has limitations in terms of security and reliability (the access decision may be incorrect) and completeness and confidentiality (the access records can be modified). Blockchain technology with decentralization, verifiability, and immutability properties can solve these problems. Motivated by these facts, in this article, we construct a trusted and efficient cross-domain access control system based on blockchain. Consequently, we integrate blockchain and role mapping technology to provide reliable and verifiable cross-domain access process. We use blockchain to record user roles, role mapping rules, access policies, and audit records, realizing user self-validation, and access nonreputation. Considering the low throughput of the blockchain, we design an efficient smart contract to make the access decision based on the access history of users. Finally, a performance evaluation of the system is presented to demonstrate the feasibility of the proposed system.