222 research outputs found

    Dynamic Optimal Control of a CO2 Heat Pump Coupled with Hot and Cold Thermal Storages

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    This study presents a model-based dynamic optimization strategy for a dual-mode CO2 heat pump coupled with hot and cold thermal storages, which was proposed as a high-efficiency smart grid enabling option in heating and cooling services for buildings or industry. Dynamic optimal control for simultaneously charging of hot and cold thermal storages is very delicate. The optimal control of compressor discharge pressure were commonly used for optimal control of heat pump systems. In this study, the outlet water temperatures of hot and cold tanks are used as indicators in the dynamic optimal strategy for charging of hot and cold storages using a dual-mode heat pump. The Modelica based dynamic model of the coupled system was developed and validated. To optimize the overall coefficient of performance (COP) during energy process, the transient total COP is optimized by genetic algorithm based on Modelica-based modeling of dynamic system. A dynamic optimal control strategy was developed and implemented into an experimental system. Test results show that this developed model-based dynamic optimal control strategy is able to search the optimal transient total COP and optimize the overall COP of such coupled systems during energy charging; and the optimal results is better than those obtained using another two experiment-based methods

    Linear codes with few weights from non-weakly regular plateaued functions

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    Linear codes with few weights have significant applications in secret sharing schemes, authentication codes, association schemes, and strongly regular graphs. There are a number of methods to construct linear codes, one of which is based on functions. Furthermore, two generic constructions of linear codes from functions called the first and the second generic constructions, have aroused the research interest of scholars. Recently, in \cite{Nian}, Li and Mesnager proposed two open problems: Based on the first and the second generic constructions, respectively, construct linear codes from non-weakly regular plateaued functions and determine their weight distributions. Motivated by these two open problems, in this paper, firstly, based on the first generic construction, we construct some three-weight and at most five-weight linear codes from non-weakly regular plateaued functions and determine the weight distributions of the constructed codes. Next, based on the second generic construction, we construct some three-weight and at most five-weight linear codes from non-weakly regular plateaued functions belonging to NWRF\mathcal{NWRF} (defined in this paper) and determine the weight distributions of the constructed codes. We also give the punctured codes of these codes obtained based on the second generic construction and determine their weight distributions. Meanwhile, we obtain some optimal and almost optimal linear codes. Besides, by the Ashikhmin-Barg condition, we have that the constructed codes are minimal for almost all cases and obtain some secret sharing schemes with nice access structures based on their dual codes.Comment: 52 pages, 34 table

    A Further Study of Vectorial Dual-Bent Functions

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    Vectorial dual-bent functions have recently attracted some researchers' interest as they play a significant role in constructing partial difference sets, association schemes, bent partitions and linear codes. In this paper, we further study vectorial dual-bent functions F:Vn(p)β†’Vm(p)F: V_{n}^{(p)}\rightarrow V_{m}^{(p)}, where 2≀m≀n22\leq m \leq \frac{n}{2}, Vn(p)V_{n}^{(p)} denotes an nn-dimensional vector space over the prime field Fp\mathbb{F}_{p}. We give new characterizations of certain vectorial dual-bent functions (called vectorial dual-bent functions with Condition A) in terms of amorphic association schemes, linear codes and generalized Hadamard matrices, respectively. When p=2p=2, we characterize vectorial dual-bent functions with Condition A in terms of bent partitions. Furthermore, we characterize certain bent partitions in terms of amorphic association schemes, linear codes and generalized Hadamard matrices, respectively. For general vectorial dual-bent functions F:Vn(p)β†’Vm(p)F: V_{n}^{(p)}\rightarrow V_{m}^{(p)} with F(0)=0,F(x)=F(βˆ’x)F(0)=0, F(x)=F(-x) and 2≀m≀n22\leq m \leq \frac{n}{2}, we give a necessary and sufficient condition on constructing association schemes. Based on such a result, more association schemes are constructed from vectorial dual-bent functions

    Mixture Conditional Regression with Ultrahigh Dimensional Text Data for Estimating Extralegal Factor Effects

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    Testing judicial impartiality is a problem of fundamental importance in empirical legal studies, for which standard regression methods have been popularly used to estimate the extralegal factor effects. However, those methods cannot handle control variables with ultrahigh dimensionality, such as found in judgment documents recorded in text format. To solve this problem, we develop a novel mixture conditional regression (MCR) approach, assuming that the whole sample can be classified into a number of latent classes. Within each latent class, a standard linear regression model can be used to model the relationship between the response and a key feature vector, which is assumed to be of a fixed dimension. Meanwhile, ultrahigh dimensional control variables are then used to determine the latent class membership, where a Na\"ive Bayes type model is used to describe the relationship. Hence, the dimension of control variables is allowed to be arbitrarily high. A novel expectation-maximization algorithm is developed for model estimation. Therefore, we are able to estimate the interested key parameters as efficiently as if the true class membership were known in advance. Simulation studies are presented to demonstrate the proposed MCR method. A real dataset of Chinese burglary offenses is analyzed for illustration purpose

    On the Dual of Generalized Bent Functions

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    In this paper, we study the dual of generalized bent functions f:Vnβ†’Zpkf: V_{n}\rightarrow \mathbb{Z}_{p^k} where VnV_{n} is an nn-dimensional vector space over Fp\mathbb{F}_{p} and pp is an odd prime, kk is a positive integer. It is known that weakly regular generalized bent functions always appear in pairs since the dual of a weakly regular generalized bent function is also a weakly regular generalized bent function. The dual of non-weakly regular generalized bent functions can be generalized bent or not generalized bent. By generalizing the construction of \cite{Cesmelioglu5}, we obtain an explicit construction of generalized bent functions for which the dual can be generalized bent or not generalized bent. We show that the generalized indirect sum construction method given in \cite{Wang} can provide a secondary construction of generalized bent functions for which the dual can be generalized bent or not generalized bent. By using the knowledge on ideal decomposition in cyclotomic field, we prove that fβˆ—βˆ—(x)=f(βˆ’x)f^{**}(x)=f(-x) if ff is a generalized bent function and its dual fβˆ—f^{*} is also a generalized bent function. For any non-weakly regular generalized bent function ff which satisfies that f(x)=f(βˆ’x)f(x)=f(-x) and its dual fβˆ—f^{*} is generalized bent, we give a property and as a consequence, we prove that there is no self-dual generalized bent function f:Vnβ†’Zpkf: V_{n}\rightarrow \mathbb{Z}_{p^k} if p≑3Β (modΒ 4)p\equiv 3 \ (mod \ 4) and nn is odd. For p≑1Β (modΒ 4)p \equiv 1 \ (mod \ 4) or p≑3Β (modΒ 4)p\equiv 3 \ (mod \ 4) and nn is even, we give a secondary construction of self-dual generalized bent functions. In the end, we characterize the relations between the generalized bentness of the dual of generalized bent functions and the bentness of the dual of bent functions, as well as the self-duality relations between generalized bent functions and bent functions by the decomposition of generalized bent functions

    ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning

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    Logical rules are essential for uncovering the logical connections between relations, which could improve the reasoning performance and provide interpretable results on knowledge graphs (KGs). Although there have been many efforts to mine meaningful logical rules over KGs, existing methods suffer from the computationally intensive searches over the rule space and a lack of scalability for large-scale KGs. Besides, they often ignore the semantics of relations which is crucial for uncovering logical connections. Recently, large language models (LLMs) have shown impressive performance in the field of natural language processing and various applications, owing to their emergent ability and generalizability. In this paper, we propose a novel framework, ChatRule, unleashing the power of large language models for mining logical rules over knowledge graphs. Specifically, the framework is initiated with an LLM-based rule generator, leveraging both the semantic and structural information of KGs to prompt LLMs to generate logical rules. To refine the generated rules, a rule ranking module estimates the rule quality by incorporating facts from existing KGs. Last, a rule validator harnesses the reasoning ability of LLMs to validate the logical correctness of ranked rules through chain-of-thought reasoning. ChatRule is evaluated on four large-scale KGs, w.r.t. different rule quality metrics and downstream tasks, showing the effectiveness and scalability of our method.Comment: 11 pages, 4 figure

    A Three-Input Central Capacitor Converter for a High-Voltage PV System

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    High-voltage photovoltaic (PV) techniques have their own advantages in PV plants for reducing the construction cost and improving the operational efficiency. However, the high input PV voltage increases the mismatch losses of PV arrays, which is also a key factor that influences the energy yield of PV plants. This paper proposes a three-input central capacitor (TICC) dc/dc converter for a high-voltage PV system, where four low-rating cascaded buck-boost converters connect to the series-connected three low-voltage PV arrays and two capacitors and realize the maximum power point tracking independently. Meanwhile, there is a neutral point in the proposed converter, enabling it to be connected with the rear-end three-level inverter directly. It can also help balance the three-level dc-link voltage by properly regulating the transferred energy among three input sources. Compared with other transformer-less dc-dc converters, the proposed converter is able to reduce the semiconductor voltage/current stress and therefore achieve the high efficiency. Simulation and experimental results verified the performance of the proposed TICC converter

    Global Epidemiological Patterns in the Burden of Main Non-Communicable Diseases, 1990–2019: Relationships With Socio-Demographic Index

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    Objectives: This study aimed to analyze spatio-temporal patterns of the global burden caused by main NCDs along the socio-economic development.Methods: We extracted relevant data from GBD 2019. The estimated annual percentage changes, quantile regression and limited cubic splines were adopted to estimate temporal trends and relationships with socio-demographic index.Results: NCDs accounted for 74.36% of global all-cause deaths in 2019. The main NCDs diseases were estimated for cardiovascular diseases, neoplasms, and chronic respiratory diseases, with deaths of 18.56 (17.08–19.72) million, 10.08 (9.41–10.66) million and 3.97 (3.58–4.30) million, respectively. The death burden of three diseases gradually decreased globally over time. Regional and sex variations existed worldwide. Besides, the death burden of CVD showed the inverted U-shaped associations with SDI, while neoplasms were positively correlated with SDI, and CRD showed the negative association.Conclusion: NCDs remain a crucial public health issue worldwide, though several favorable trends of CVD, neoplasms and CRD were observed. Regional and sex disparities still existed. Public health managers should execute more targeted programs to lessen NCDs burden, predominantly among lower SDI countries

    A Further Study of Vectorial Dual-Bent Functions

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    Vectorial dual-bent functions have recently attracted some researchers\u27 interest as they play a significant role in constructing partial difference sets, association schemes, bent partitions and linear codes. In this paper, we further study vectorial dual-bent functions F:Vn(p)β†’Vm(p)F: V_{n}^{(p)}\rightarrow V_{m}^{(p)}, where 2≀m≀n22\leq m \leq \frac{n}{2}, Vn(p)V_{n}^{(p)} denotes an nn-dimensional vector space over the prime field Fp\mathbb{F}_{p}. We give new characterizations of certain vectorial dual-bent functions (called vectorial dual-bent functions with Condition A) in terms of amorphic association schemes, linear codes and generalized Hadamard matrices, respectively. When p=2p=2, we characterize vectorial dual-bent functions with Condition A in terms of bent partitions. Furthermore, we characterize certain bent partitions in terms of amorphic association schemes, linear codes and generalized Hadamard matrices, respectively. For general vectorial dual-bent functions F:Vn(p)β†’Vm(p)F: V_{n}^{(p)}\rightarrow V_{m}^{(p)} with F(0)=0,F(x)=F(βˆ’x)F(0)=0, F(x)=F(-x) and 2≀m≀n22\leq m \leq \frac{n}{2}, we give a necessary and sufficient condition on constructing association schemes. Based on such a result, more association schemes are constructed from vectorial dual-bent functions
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