We consider the problem of portfolio optimization with a correlation constraint. The framework is the multi-period stochastic financial market setting with one tradable stock, stochastic income, and a non-tradable index. The correlation constraint is...
Water scarcity has become a major impediment to economic development, and a scientifically sound water allocation plan is essential to alleviate water scarcity. An opportunity constraint approach is introduced to optimise the uncertainty of the minim...
Given that the observations from current space geodetic techniques do not carry all the necessary datum information to realize a Terrestrial Reference System (TRS), and each of the four space geodetic techniques has limits, for instance: Very Long Ba...
Large-scale knowledge graphs not only store entities and relations but also provide ontology-based information about them. Type constraints that exist in this information are of great importance for link prediction. In this paper, we proposed a novel...
The Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS/DNB) nighttime light data is a powerful remote sensing data source. However, due to stray light pollution, there is a lack of VIIRS data in mid-high latitudes during the summer, resu...
Under the background of spatially correlated color noise, the incidence angle of a jamming signal in a high-speed moving platform rapidly changes, which leads to the degradation of the anti-interference performance and the waveform distortion of the...
Uncertainty in travel and service times poses significant challenges for vehicle routing in logistics systems. This paper proposes a stochastic model predictive control (SMPC) strategy to manage a Vehicle Routing Problem with time windows (VRPTW) und...
Networked systems operating under uncertainty require decision making frameworks capable of balancing nominal efficiency and robustness against correlated risks. In this work, we study a distributionally robust weighted dominating set problem as a sy...
Model-based design principles have received considerable attention in biotechnology and the chemical industry over the last two decades. However, parameter uncertainties of first-principle models are critical in model-based design and have led to the...
We propose a generalized method of the canonical correlation analysis using Alpha-Beta divergence, called AB-canonical analysis (ABCA). From observations of two random variables, x ∈ RP and y ∈ RQ, ABCA finds directions, wx ∈ RP and wy ∈ RQ, such t...
Many modulated signals exhibit a cyclostationarity property, which can be exploited in direction-of-arrival (DOA) estimation to effectively eliminate interference and noise. In this paper, our aim is to integrate the cyclostationarity with the spatia...
The accuracy of ultra-rapid orbits is a key parameter for the performance of GNSS (Global Navigation Satellite System) real-time or near real-time precise positioning applications. The quality of the current BeiDou demonstration system (BDS) ultra-ra...
Stratigraphic correlation plays a crucial role in reservoir characterization. However, it is often time-consuming and heavily dependent on geological expertise. To address this issue, we propose a novel method called CMT-enhanced Hiformer, which inte...
Object tracking in satellite videos has garnered significant attention due to its increasing importance. However, several challenging attributes, such as the presence of tiny objects, occlusions, similar objects, and background clutter interference,...
Mapping surface currents with high spatiotemporal resolution over a wide coverage is crucial for understanding ocean dynamics and associated biogeochemical processes. The most widely used algorithm for estimating surface velocities from sequential sa...
Owing to the advantages of cost-effectiveness, compactness, and the avoidance of complicated camera synchronization, single-camera three-dimensional (3D) digital image correlation (DIC) techniques have gained increasing attention for deformation meas...
Numerical weather prediction (NWP) is crucial in the current short-term wind power forecasting (STWPF) based on data, but it is difficult for STWPF to achieve high accuracy due to the limited accuracy of NWP, which poses a serious challenge to the fo...
Background: This study aims to evaluate patients with locally advanced cervical cancer who underwent definitive radiochemotherapy, including brachytherapy, at the University Hospital of Muenster (UKM), focusing on target volume coverage, oncologic ou...
A quantitative expression for the value of information within the framework of information theory and of the maximal entropy formulation is discussed. We examine both a local, differential measure and an integral, global measure for the value of the...
In this paper, we consider a new design problem of optimizing a linear transceiver for correlated multiple-input multiple-output (MIMO) interference channels in the presence of channel state information (CSI) errors, which is a more realistic and pra...
To solve the problem of the redundant number of training samples in a correlation filter-based tracking algorithm, the training samples were implicitly extended by circular shifts of the given target patches, and all the extended samples were used as...
In the present paper, we propose a large sample asymptotic approximation for the sampling and posterior distributions of differential entropy when the sample is composed of independent and identically distributed realization of a multivariate normal...
Large, high-quality patient datasets are essential for applications like economic modeling and patient simulation. However, real-world data is often inaccessible or incomplete. Synthetic patient data offers an alternative, and current methods often f...
The presence of salinity and sodicity in the root zone can limit root development and impact crop yield. Topsoil constraints are likely to have the greatest impact on crop growth early in the growing season, when plant roots are still shallow. Later...
Based on the two-dimensional hydrodynamic model of the finite volume method and structured multigrid, the flow characteristics around a square cylinder with boundary constraint are analysed. The gap ratio G/D (G is the distance from the cylinder to t...
An investigated process can be studied in terms of the causal relations among the involved variables, representing it as a causal model. Some causal models are particularly relevant, since they can be tested through mathematical constraints between t...
The continuous increase in generation from renewable energy sources, marked by correlated forecast uncertainties, requires specific methodologies to support power system operators in security management. This paper proposes a probabilistic preventive...
Background: Whole-genome models (GEMs) have become a versatile tool for systems biology, biotechnology, and medicine. GEMs created by automatic and semi-automatic approaches contain a lot of redundant reactions. At the same time, the nonlinearity of...
A general framework of data fusion is presented based on projecting the probability distribution of true states and measurements around the predicted states and actual measurements onto the constraint manifold. The constraint manifold represents the...
The paper focuses on linguistic complexity and language universals, which are two important and controversial issues in language research. A Fuzzy Property Grammar for determining the degree of universality and complexity of a natural language is int...
As global environmental problems become increasingly severe, corporate social (environmental) responsibility has become a hot topic in research, but there is still a lack of clear understanding of corporate environmental irresponsibility behavior and...
The operation of water distribution systems (WDS) is an energy-intensive process, which is subject to constraints such as consumer demands, water quality, and pressure domains. As such, tracing an operation policy in which constraints are met while e...
Radargrammetry is a widely used methodology to generate the large-scale Digital Surface Model (DSM). Stereo matching is the most challenging step in radargrammetry due to the significant geometric differences and the inherent speckle noise. The speck...
Operators of mobile platforms that employ hydraulic actuation, such as excavators, seek more efficient power transfer from source to load. Pump-controlled architectures achieve greater efficiency than valve-controlled architectures but exhibit poor t...
The consequence of cardiac substructure irradiation in patients receiving stereotactic body radiation therapy (SBRT) is not well characterized. We reviewed the charts of patients with central lung tumors managed by definitive SBRT from June 2010&ndas...
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 o...
Background: Social constraints are perceived as unsupportive behaviors, leading to inadequate psychosocial adjustment, while optimism can help people recover from distress and reduce any negative effects of chronic disease. The aim of this study was...
We compare the application of Bayesian inference and the maximum entropy (MaxEnt) method for the analysis of flow networks, such as water, electrical and transport networks. The two methods have the advantage of allowing a probabilistic prediction of...
Maximum entropy inference can be used to find equations for the critical currents (Jc) in a type II superconductor as a function of temperature, applied magnetic field, and angle of the applied field, θ or φ . This approach provides an understanding...
Corporate innovation is an important topic in the academic community, but there are few studies on the impact of the micro operation environment on corporate innovation. Using the data of A-share listed companies in Shanghai and Shenzhen from 2009 to...
Artificial intelligence plays an indispensable role in improving productivity and promoting social development, and causal discovery is one of the extremely important research directions in this field. Acyclic directed graphs (DAGs) are the most comm...
The effective management of the triple constraints, time, cost, and quality, is imminently essential for the success of construction projects, and it is considered a hot research topic nowadays. For this purpose, we carried out this study to systemat...
Quantum reference frames are expected to differ from classical reference frames because they have to implement typical quantum features such as fluctuations and correlations. Here, we show that fluctuations and correlations of reference variables, in...
Background: We analyze several constraints on the nuclear equation of state (EOS) currently available from neutron star (NS) observations and laboratory experiments and study the existence of possible correlations among properties of nuclear matter a...
In a previous paper (C. Cafaro et al., 2012), we compared an uncorrelated 3D Gaussian statistical model to an uncorrelated 2D Gaussian statistical model obtained from the former model by introducing a constraint that resembles the quantum mechanical...
Many aerial images with similar appearances have different but correlated scene labels, which causes the label ambiguity. Label distribution learning (LDL) can express label ambiguity by giving each sample a label distribution. Thus, a sample contrib...
Background. We investigate possible correlations between neutron star observables and properties of atomic nuclei. In particular, we explore how the tidal deformability of a 1.4 solar mass neutron star,
Efforts by various researchers in recent years to design simple causal control laws that can be applied to WEC devices suggest that these controllers can yield similar levels of energy output as those of more complex non-causal controllers. However,...
MC-SCF wavefunctions for three endohedral Mn/Si clusters, Mn2Si10, Mn2Si12, and [Mn2Si13]+, show evidence for strong static correlation, both in the Mn-Si bonds (‘in–out correlation’) and between the two Mn centers (‘up–...
Full-waveform inversion for borehole seismic data is an ill-posed problem and constraining the problem is crucial. Constraints can be imposed on the data and model space through covariance matrices. Usually, they are set to a diagonal matrix. For the...
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