222 research outputs found
Dynamic Optimal Control of a CO2 Heat Pump Coupled with Hot and Cold Thermal Storages
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
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 (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
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 , where , denotes an
-dimensional vector space over the prime field . 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 , 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 with and , 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
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
In this paper, we study the dual of generalized bent functions where is an -dimensional vector space over and is an odd prime, 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 if is a generalized bent function and its dual is also a generalized bent function. For any non-weakly regular generalized bent function which satisfies that and its dual is generalized bent, we give a property and as a consequence, we prove that there is no self-dual generalized bent function if and is odd. For or and 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
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
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, 1990β2019: Relationships With Socio-Demographic Index
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 (17.08β19.72) million, 10.08 (9.41β10.66) million and 3.97 (3.58β4.30) 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
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 , where , denotes an -dimensional vector space over the prime field . 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 , 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 with and , 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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