Encoding Conversion Algorithm of Quaternary Triangular Mesh

In the process of global information construction, different fields have built their own discrete global grid systems (DGGS). With the development of big data technology, data exchange, integration, and update have gradually become a trend, as well as the associative integration of different DGGS. Due to the heterogeneity of DGGS and the different encoding rules, how to build the encoding conversion rules and data mapping relationship between the same object in various DGGS is an effective support and key technology to achieve the interoperability of DGGS. As a kind of multipurpose DGGS, the quaternary triangular mesh (QTM) has become an effective spatial framework for constructing the digital earth because of its simple structure. At present, there are many schemes for QTM encoding research, which plays a key role in the development of QTM, but at the same time, it also leads to difficulties in the communication and integration of QTM under different encoding. In order to solve this problem, we explore the characteristics of QTM encoding, and put forward three conversion algorithms: resampling conversion algorithm, hierarchical conversion algorithm, and row–column conversion algorithm.

Based on Consortium Blockchain to Design a Credit Verifiable Cross University Course Learning System

In recent years, the attention of online cross-university courses has been increasing, and students in universities want to increase their knowledge and professional skills by taking online courses from different universities, which raises the issue of course credit verification. In the past, the credits obtained by students in online courses lack endorsement from the education department, and the students’ learning process could not be verified. Therefore, the credits of online courses in one university could not be recognized by other universities. The education departments of some countries and regions implement credit conversion rules to convert the credits obtained by students in online courses into university credits or certificates endorsed by the education department. However, these schemes rely too much on the authority of the education department, and the process of students obtaining credits cannot be verified. In addition, the centralized storage method makes the data of education departments at risk of leakage or tampering. With the emergence of blockchain technology, some researchers have proposed the use of blockchain to store students’ credits, making it possible to reach consensus among multiple parties on the blockchain while ensuring that credits are not tampered with, but these schemes cannot test the learning process of students and the recognition of credits still relies on the authority of the education department. To solve the above problems, this paper proposes a cross-university course learning system with verifiable credits based on Hyperledger Fabric consortium blockchain technology, and the consortium includes many universities. The credits obtained by students in the course and the hash value of the learning records are stored on the blockchain, and the data on the blockchain is jointly maintained by the universities in the system. One university can verify the homework and final examination of students to check the real ability of students, thus recognizing the credits from other universities, and at the same time, to protect the privacy of students, the important data of students are encrypted for transmission.

Stochastic Damage Constitutive Relationship of Steel-Reinforced Concrete Bond-Slip

The bond-slip damage of the interface between profile steel and concrete is the key point of steel-reinforced concrete structure. This paper is based on the statistical analysis of a large amount of experimental data and the distribution characteristics of bonding stress on the bonding surface of the profile steel and concrete, and the conversion rules between the three parts (chemical bonding force, frictional resistance, and mechanical interaction) of the bond force are obtained. According to the mutual conversion rules of the three parts of the bonding force on the steel-reinforced concrete bonding surface, a mesomechanical model based on the spring-friction block element is established. Taking into account the discreteness of concrete performance on the bonding surface and the randomness of defects, using the stochastic damage theory, a constitutive model of stochastic bonding damage on the steel-reinforced concrete bonding surface is established. The comparative analysis with the results of a large number of steel-reinforced concrete pull-out tests shows that the model can reasonably reflect the damage characteristics of the steel-reinforced concrete bonding surface.

Survey on Online Log Parsers

Technological dependence is growing in leaps and bounds as days progress. As a result, software applications are required to be up and running at all times without fail. The health and safety of these applications need to be monitored regularly by theuse of constant logging of any faults that occur at their runtime executions. Log analysis techniques are applied to recorded logsto obtain a better overview of how to handle failures and health deterioration. Before these algorithms can be utilized in practice, the raw unstructured logs need to be converted into structured log events. This process is performed by log parsers, which are accessible in two different modes – offline and online. While offline log parsers have a predefined knowledge base containing templates and conversion rules, online log parsers learn new templates on the job. This paper focuses on surveying and creating a comparative study on online log parses by analysing the type of technique used, efficiency and accuracy of the parser on a given dataset, time complexity, and their effectiveness in motivating applications.

Simulation of Land-Use Changes Using the Partitioned ANN-CA Model and Considering the Influence of Land-Use Change Frequency

Land-use change is a typical geographic evolutionary process characterized by spatial heterogeneity. As such, the driving factors, conversion rules, and rate of change vary for different regions around the world. However, most cellular automata (CA) models use the same transition rules for all cells in the model space when simulating land-use change. Thus, spatial heterogeneity change is ignored in the model, which means that these models are prone to over- or under simulation, resulting in a large deviation from reality. An effective means of accounting for the influence of spatial heterogeneity on the quality of the CA model is to establish a partitioned model based on cellular space partitioning. This study established a partitioned, dual-constrained CA model using the area-weighted frequency of land-use change (AWFLUC) to capture its spatial heterogeneity. This model was used to simulate the land-use evolution of the Dianchi Lake watershed. First, the CA space was divided into subzones using a dual-constrained spatial clustering method. Second, an artificial neural network (ANN) was used to automatically acquire conversion rules to construct an ANN-CA model of land-use change. Finally, land-use changes were simulated using the ANN-CA model based on data from 2006 to 2016, and model reliability was validated. The experimental results showed that compared with the non-partitioned CA model, the partitioned counterpart was able to improve the accuracy of land-use change simulation significantly. Furthermore, AWFLUC is an important indicator of the spatial heterogeneity of land-use change. The shapes of the division spaces were more similar to reality and the simulation accuracy was higher when AWFLUC was considered as a land-use change characteristic.

Multi-time correlations in the positive-P, Q, and doubled phase-space representations

A number of physically intuitive results for the calculation of multi-time correlations in phase-space representations of quantum mechanics are obtained. They relate time-dependent stochastic samples to multi-time observables, and rely on the presence of derivative-free operator identities. In particular, expressions for time-ordered normal-ordered observables in the positive-P distribution are derived which replace Heisenberg operators with the bare time-dependent stochastic variables, confirming extension of earlier such results for the Glauber-Sudarshan P. Analogous expressions are found for the anti-normal-ordered case of the doubled phase-space Q representation, along with conversion rules among doubled phase-space s-ordered representations. The latter are then shown to be readily exploited to further calculate anti-normal and mixed-ordered multi-time observables in the positive-P, Wigner, and doubled-Wigner representations. Which mixed-order observables are amenable and which are not is indicated, and explicit tallies are given up to 4th order. Overall, the theory of quantum multi-time observables in phase-space representations is extended, allowing non-perturbative treatment of many cases. The accuracy, usability, and scalability of the results to large systems is demonstrated using stochastic simulations of the unconventional photon blockade system and a related Bose-Hubbard chain. In addition, a robust but simple algorithm for integration of stochastic equations for phase-space samples is provided.

Monitoring and Simulation of Dynamic Spatiotemporal Land Use/Cover Changes

Changes in land use/cover are among the most prominent impacts that humans have on the environment. Therefore, exploring land use/cover change is of great significance to urban planning and sustainable development. In this study, we preprocessed multiperiod land use and socioeconomic data, combined with spatial zoning, multilayer perception (MLP) artificial neural network, and Markov chain (MC), to construct a cellular automaton model of spatial zoning. Moreover, with the help of ArcGIS 10.2 and TerrSet 18.07 software, we explore the current status of land use and predict future changes. The results showed that drastic changes have occurred among different land use classes in Jinzhou District over the past 13 years owing to the impact of economic development and reclamation projects. Construction land, arable land, and waters have changed by +85.09, −24.42, and −23.62 km2, respectively. By comparing the FoM and Kappa coefficients, we concluded that the prediction accuracy of partitioned MLP-MC is better than that of unpartitioned MLP-MC. Therefore, using the spatial zoning approach to identify the conversion rules among land use classes in different zones can more effectively predict future land use changes and provide a reference for urban planning and policy making.

Voice Conversion Using a Perceptual Criterion

In voice conversion (VC), it is highly desirable to obtain transformed speech signals that are perceptually close to a target speaker’s voice. To this end, a perceptually meaningful criterion where the human auditory system was taken into consideration in measuring the distances between the converted and the target voices was adopted in the proposed VC scheme. The conversion rules for the features associated with the spectral envelope and the pitch modification factor were jointly constructed so that perceptual distance measurement was minimized. This minimization problem was solved using a deep neural network (DNN) framework where input features and target features were derived from source speech signals and time-aligned version of target speech signals, respectively. The validation tests were carried out for the CMU ARCTIC database to evaluate the effectiveness of the proposed method, especially in terms of perceptual quality. The experimental results showed that the proposed method yielded perceptually preferred results compared with independent conversion using conventional mean-square error (MSE) criterion. The maximum improvement in perceptual evaluation of speech quality (PESQ) was 0.312, compared with the conventional VC method.

CREATING AND MAINTAINING IFC–CITYGML CONVERSION RULES

<p><strong>Abstract.</strong> We employ a triple graph grammar to enable configurable conversion from IFC to CityGML. In this paper, we present the mathematical framework behind the graph transformation approach as well as an application to create, store and maintain transformation rules implementing this framework. Particular emphasis is put on how the approach enables graphical representation and static analysis of rules and rulesets, both in the theoretical framework and prototypical implementation. Even if various publications and tools for general graph transformation do already exist, we hope that the BIM–GIS community will benefit from a domain-specific introduction to the theory and dedicated software tools.</p>