Dynamic SHA-2

In this paper I describe the construction of Dynamic SHA-2 family of cryptographic hash functions. They are built with design components from the SHA-2 family, but I use the bits in message as parameters of function G, R and ROTR operation in the new hash functionh. It enabled us to achieve a novel design principle: When message is changed, the calculation will be different. It make the system can resistant against all extant attacks

Ways to restrict the differential path

People had developed some attack methods to attack hash function. These methods need to choose some differential pattern [Dau05]. We present a way to restrict the collisions that hold the differential pattern . At the same time, to build a hash function that meet the different needs, we propose a construction

A Way Reduce Signed Bitwise Differences that Transformed Into Same Modular Differences

We study signed bitwise differences and modular differences. We find a way to reduce signed bitwise differences that can be transformed into same modular differences. In this way, it needs arithmetic difference. We establish one-one relationship between modular differences and arithmetic difference. And establish one-one relationship between signed bitwise differences and arithmetic difference. Then it will reduce signed bitwise differences that can be transformed into same arithmetic difference. In this paper, we design a construction with ways we find. Given modular differences, some signed bitwise difference is uniquely determined

Data-Depend Hash Algorithm

We study some technologys that people had developed to analyse and attack hash algorithm. We find a way that use data-depend function to resist differential attack. Then we design a hash algorithm that called Data-Depend Hash Algorit(DDHA). And DDHA is simple and strong under differential attack

Use Data-depend Function Build Message Expansion Function

We had found functions can be used to fix bits [2] by given differences. We use these functions build a message expansion function. In the message expansion function, there are some bits include message bits and incremental bits produced from message bits, these bits will be used as parameter of date-depend function. This message expansion function will fixed at lease n × 5.5 bits with given differences, and any message modification will affect at least 8 data-depend function parameter

The effect of supercritical CO2 on failure mechanisms of hot dry rock

Hot dry rock is a clean, renewable resource of geothermal energy with good stability and a high utilization rate. Supercritical CO2 has shown promising results for improving the permeability and heat exchange of hot dry rock. In order to demonstrate the effect of supercritical CO2 on the failure mechanism of granite, the acoustic emission of granite during its failure process were studied in addition to X-ray diffraction, scanning electron microscopy, and optical electron microscopy investigations. The experimental results showed that for granite without supercritical CO2 treatment, as it approached failure, there were many acoustic emission events with a waiting time less than 0.0001 s, and that the power law exponent of the acoustic emission energy distribution decreased. The failure mechanisms were a combination of fracture and friction, with fracturing dominant. After immersion in supercritical CO2 , new cracks and pores appeared in the granite due to the dissolution of minerals, but friction was also a factor evidenced in particle crumbing. Generally, the acoustic emission statistical distributions of granite before and after supercritical CO2 soaking conformed to the seismic statistical distribution law. This study is conducive to increasing the understanding of artificial earthquakes induced by the development of hot dry rock.Cited as: Li, H., Jiang, X., Xu, Z., Bowden, S. The effect of supercritical CO2 on failure mechanisms of hot dry rock. Advances in Geo-Energy Research, 2022, 6(4): 324-333. https://doi.org/10.46690/ager.2022.04.0

Modeling Intra- and Inter-Modal Relations: Hierarchical Graph Contrastive Learning for Multimodal Sentiment Analysis

The existing research efforts in Multimodal Sentiment Analysis (MSA) have focused on developing the expressive ability of neural networks to fuse information from different modalities. However, these approaches lack a mechanism to understand the complex relations within and across different modalities, since some sentiments may be scattered in different modalities. To this end, in this paper, we propose a novel hierarchical graph contrastive learning (HGraph-CL) framework for MSA, aiming to explore the intricate relations of intra- and inter-modal representations for sentiment extraction. Specifically, regarding the intra-modal level, we build a unimodal graph for each modality representation to account for the modality-specific sentiment implications. Based on it, a graph contrastive learning strategy is adopted to explore the potential relations based on unimodal graph augmentations. Furthermore, we construct a multimodal graph of each instance based on the unimodal graphs to grasp the sentiment relations between different modalities. Then, in light of the multimodal augmentation graphs, a graph contrastive learning strategy over the inter-modal level is proposed to ulteriorly seek the possible graph structures for precisely learning sentiment relations. This essentially allows the framework to understand the appropriate graph structures for learning intricate relations among different modalities. Experimental results on two benchmark datasets show that the proposed framework outperforms the state-of-the-art baselines in MSA