Information Systems-based Real Estate Macrocontrol Systems

With the continuous increase of marketization and normalization in the Chinese real estate market, the market mechanism now plays an important role in market regulation. The existing macro-control system for the real estate market, however, appears to lack the ability to regulate it. Thus, an effective and efficient information-oriented tool is needed to guide the development of China’s real estate market. The research reported herein constructs a new macro-control system for this market that is based on information systems, specifically, a real estate warning system, a confidence index system, and a simulation system. This paper first presents the framework of the new information systems-based macro-control system, and its functions are analyzed. The methods of constructing the system are then discussed. Based on these methods, the index systems of the respective information systems are established, and the main models are presented. Finally, a case study that is based on survey data from the Shenzhen real estate market is described to demonstrate the applicability of the new macrocontrol system.Real estate; Macro-control system; Warning system; Confidence index; System simulation

Exhumation History of the Greater Khingan Mountains (NE China) Since the Late Mesozoic: Implications for the Tectonic Regime Change of Northeast Asia

The Greater Khingan Mountains (GKMs) are a prominent orogenic zone in Northeast Asia that offers significant insights into the evolution of the Mongol-Okhotsk Ocean and the Pacific Ocean during the Phanerozoic. A comprehensive study integrating a low-temperature thermochronology analysis pertaining to the Greater Khingan area and its associated basins has been conducted. Apatite fission-track (AFT) tests conducted on detrital samples from the GKMs in Northeast China have yielded central ages ranging from 260 to 62 Ma. Two-dimensional thermal history inversion modeling and three-dimensional numerical simulations were used to investigate the GKMs' thermal history, revealing at least two distinct tectonic cooling and exhumation events: one occurring between 147 and 70 Ma and another around 35 Ma. The fission-track age groups of the GKMs, Hailar-Erlian Basin, and Mohe Basin bear some resemblance (>105 Ma), but the results from the Songliao Basin are unique. This implies that the Songliao Basin and the GKMs were likely under the influence of different tectonic domains during this period, while AFT age peaks between 105 and 45 Ma, indicating the basin-mountain systems were likely influenced by a unified Paleo-Pacific plate process, which prevailed from about 105 Ma. The 147–70 Ma cooling event can be attributed to the combined effects of the compression orogeny, resulting from the closure of the Mongol-Okhotsk Ocean during the Early Cretaceous and the extension orogeny triggered by the subduction of the Paleo-Pacific Ocean during the early Late Cretaceous. Since approximately 35 Ma, the increase in Pacific plate subduction speed may have established a post-arc extensional tectonic environment in the GKMs that has persisted until now

Data-driven solution-based synthesis design for inorganic materials

The development of a materials synthesis route is usually based on heuristics and experience. This thesis proposes to apply data-driven approaches to learn the patterns of synthesis from past experience and use them to predict the syntheses of novel materials. However, this route is impeded by the lack of a large-scale database of synthesis formulations. Scientific publications represent the largest repository of knowledge about material synthesis and can be used as a reliable source of data. However, human-written descriptions of syntheses require additional levels of interpretation for conversion into a codified, machine-operable format. Therefore, this thesis aims to achieve two objectives: 1) constructing a text-mining pipeline that extracts synthesis datasets from scientific publications, and 2) validating a novel synthesis hypothesis, minimum thermodynamic competition, by the text-mined dataset and systematic synthesis experiments. To fulfill the first objective, we need to build a text-mining pipeline to extract essential information from scientific publications. Extraction of synthesis information is challenging, especially for extracting synthesis actions, because of the lack of a comprehensive labeled dataset using a solid, robust, and well-established ontology for describing synthesis procedures. In order to extract synthesis actions (Chapter 2), we propose the first unified language of synthesis actions (ULSA) for describing inorganic synthesis procedures. We created a dataset of 3,040 synthesis procedures annotated by domain experts according to the proposed ULSA scheme, and then built a neural network-based model to map arbitrary inorganic synthesis paragraphs into ULSA and used it to construct synthesis flowcharts for synthesis procedures. We constructed the first large dataset of solution-based inorganic materials synthesis procedures by designing an advanced text-mining pipeline (Chapter 3), including the ULSA synthesis action extraction framework alone with other natural language processing(NLP) and deep learning techniques. The dataset consists of 35,675 solution-based synthesis procedures. Each procedure contains essential synthesis information, including the precursors and target materials, their quantities, and the synthesis actions and corresponding attributes. Every procedure is also augmented with the reaction formula. Digitizing and systemizing the large synthesis corpus of existing materials science publications provides a foundation not only to build machine learning models, but also empirically validate the fundamental physical theory. Thermodynamics has strong predictive power for materials synthesis by identifying the stability regions of target phases, which can guide synthesis planning for computationally-designed materials. However, a stability domain does not give explicit information about the relative competitiveness of undesired byproduct phases, nor does it identify a precise synthesis condition for optimized kinetics to produce the target phase. To fulfill the second objective, in Chapter 4, we define thermodynamic competition as the difference in driving force between one phase and its competing phases, and we hypothesize that one approach to optimizing the kinetics of phase-pure synthesis is to minimize the thermodynamic competition between the desired target phase and its competing phases. We systematically validate this hypothesis with two approaches: (1) we analyze large-scale solution synthesis procedures as text-mined from the literature and show that experimentally-optimized synthesis conditions are near our predicted thermodynamic optimum point, and (2) direct experimental evaluation of synthesis in LiIn(IO3)4 and LiFePO4; where we show phase-pure synthesis occurs only when thermodynamic competition is minimized. Our work demonstrates that thermodynamic competition is an effective descriptor for synthesis optimization and a promising tool for optimizing aqueous solution-based experimental synthesis conditions. Finally, Chapter 5 summarizes the main findings of the dissertation and provides an outlook for the future directions of data-driven approaches synthesis design

Turbo Equalization Based on a Combined VMP-BP Algorithm for Nonlinear Satellite Channels

Close to saturation operation of high power amplifier (HPA) leads to strong nonlinear and dispersive characteristic of satellite channels. At the receiver, the observation signals are distorted by not only the linear inter-symbol interference (ISI), but also the nonlinear ones, which makes it challenge to perform optimal detection. In this paper, we study factor graph (FG)-based turbo equalization for nonlinear satellite channels characterized by Volterra series. Factor nodes on FG are classified into Belief propagation (BP) set and variational message passing (VMP) set to enable low complexity combined message passing implementation while with high performance. BP is used on the hard constraint nodes, such as demapping and decoding, while VMP is employed to update messages of the likelihood function node. It is shown that, without any approximation on the Volterra series channel model, messages can be expressed in a closed form via canonical parameters, and the extrinsic information from equalizer to decoder is derived in an explicit way. Simulation results demonstrate the superior performance of the proposed combined VMP-BP algorithm with low computational complexity

Research on Applicability of the Practical Transient Voltage Stability Criterion Based on Voltage Magnitude and Sag Duration

Voltage sags threaten the transient voltage stability of power systems. To evaluate the transient voltage stability, practical criteria based on voltage magnitude and sag duration are widely used in practical engineering. However, the applicability of practical criteria needs to be studied. In this paper, in a single-load system, a theoretical derivation was first made to obtain the transient voltage stability boundary. Then, by studying the relationship between the practical criteria and the stability boundary, the application scope of the practical criteria was determined. The application scope described in this paper can guide operators to use the practical criteria correctly and avoid misjudgment of the transient voltage stability as much as possible. Finally, a case study based on PSCAD/EMTDC is presented, and the simulation results verified the conclusions proposed in this paper

An Investigation of a New Parameter Based on the Plastic Strain Gradient to Characterize Composite Constraint around the Crack Front at a Low Temperature

Stress corrosion cracking (SCC) is an important destruction form of materials such as stainless steel, nickel-based alloy and their welded components in nuclear reactor pressure vessels and pipes. The existing popular quantitative prediction models of SCC crack growth rate are mainly influenced by fracture toughness values KJc or Jc. In particular, the composite constraint, containing the in-plane constraints and out-of-plane constraints around the crack front, has a significant influence on the fracture toughness of structures in nuclear power plants. Since the plastic strain gradient is a characterization parameter of the quantitative prediction model for crack growth rate, it may be a characterization parameter of composite constraint. On the basis of the experimental data at a low temperature of alloy steel 22NiMoCr3-7 used in nuclear pressure vessels, the gradient of equivalent plastic strain DPEEQ around the crack fronts at different constraint levels was calculated using the finite element method, which introduces a new non-dimensional constraint parameter Dp, to uniformly characterize the in-plane and out-of-plane constraint effects. Compared with constraint parameters APEEQ or Ap, the process of obtaining parameters DPEEQ or Dp is much simpler and easier. In a wide range, a single correlation curve was drawn between parameter Dp and normalized fracture toughness values KJc/Kref or Jc/Jref of specimens at a low or high constraint level. Therefore, regardless of whether the constraint levels of the structures or standard specimens are low or high, constraint parameter Dp can be used to measure their fracture toughness. To build an evaluation method that has structural integrity and safety while containing the composite constraint effects, in addition to accurate theoretical interpretation, further verification experiments, numerical simulations and detailed discussions are still needed