Electricity distribution network optimisation has attracted attention in recent years due to the widespread penetration of distributed generation. A considerable portion of network optimisation algorithms rely on an initial solution that is supposed...
Traditional Hopfield neural networks (HNNs) suffer from limitations in generating controllable chaotic dynamics, which are essential for applications in neuromorphic computing and secure communications. Memristors, with their memory-dependent nonline...
The initial model plays an important role in seismic inversion. Generally, the initial model is constructed by lateral extrapolation of parameters under horizons constraints. However, without horizon data, initial modeling becomes a challenging task....
Traditional numerical methods often provide local solutions for initial value problems of differential equations, even though these problems may have solutions over larger intervals. Current neural network algorithms and deep learning methods also st...
Phase field models are widely employed in materials science, fluid dynamics, fracture mechanics, and image processing to describe physical processes involving complex interface evolution, with the Allen–Cahn equation serving as a classic exampl...
Initialization methods for underwater wireless acoustic sensor networks (UWASNs) have been proposed as a subset of other network protocols under the simple assumption that all the nodes in the network can be initialized at once. However, it is genera...
Local energy initiatives are of growing interest to studies of grassroots innovation for sustainability. Some of these initiatives have developed novel technological solutions to fulfil local demand for renewable energy. However, whereas the upscalin...
This work introduces a new initialization scheme for complex-valued layers in physics-informed neural networks that use holomorphic activation functions. The proposed method is derived empirically by estimating the activation and gradient gains speci...
The Belt and Road Initiative (BRI) is an ambitious infrastructure and development project promoting sustainable economic growth through facilitating prosperous trade across Eurasia and Africa; however, its potential remains underexploited. Logistics...
In strong clutter and maneuvering scenarios, radar track initiation faces the dual challenges of a low initiation rate and high false alarm rate. Although the existing deep learning methods show promise, the commonly adopted “feature flattening...
In underwater sensor networks (UWSNs), the unique characteristics of acoustic channels have posed great challenges for the design of medium access control (MAC) protocols. The long propagation delay problem has been widely explored in recent literatu...
A reasonable definition of nodes load and capacity is essential for improving the robustness of scale-free networks against cascading failure, which has gained significant attention over recent years. This paper presents two methods for defining the...
The Belt and Road Initiative (BRI) under the auspices of the Chinese government was created as a regional integration and development model between China and her trade partners. Arguments have been raised as to whether this initiative will be benefic...
In recent times, there has been a growing interest in the role of food trade in achieving food security. This study presents a comprehensive analysis of the relationship between food trade and food security within the context of the Belt and Road Ini...
There is a global need to jointly build the green Belt and Road Initiative (BRI) in order to develop a philosophy of ecological civilisation and achieve sustainable development. This paper aims to analyse the temporal and spatial characteristics of t...
The Kunming–Montreal Global Biodiversity Framework (hereafter “KMGBF”) sets 23 action targets for 2030, and its implementation has now entered a critical phase. Despite the Framework’s emphasis on a whole-of-society approach,...
Against the backdrop of global energy transition and the imperative for sustainable development, the trade dynamics of solar photovoltaic (PV) products among “Belt and Road Initiative (BRI)” countries gained momentum. This study investigates the evol...
The graph convolutional network (GCN) has become a mainstream technology in skeleton-based action recognition since it was first applied to this field. However, previous studies often overlooked the pivotal role of heuristic model initialization in t...
The network regulatory mechanism governing the dynamics of plant maturity and tuber development in potatoes (Solanum tuberosum L.) has remained a major focus in potato molecular biology research. In this study, three potato cultivars with different m...
In dynamic space networks, achieving high precision and fast initial pointing of the optical line of sight (LOS) is the key goal in developing this technology. It is the premise and basis of realizing optical LOS capture. Based on the composition and...
For the numerical forecasting of ocean temperature, the effective fusion of observations and the initial field under the conditions of limited observations has always been a significant problem. Traditional data assimilation methods cannot make full...
Smart surveillance cameras are increasingly employed for automated tasks such as event and anomaly detection within smart city infrastructures. However, the heterogeneity of deployment environments, ranging from densely populated urban intersections...
In this paper, we propose a method for sharing the handshakes of control packets among multiple nodes, which we call a hybrid sender- and receiver-initiated (HSR) protocol scheme. Handshake-sharing can be achieved by inviting neighbors to join the cu...
The choice of activation functions and weight initialization strategies plays a critical role in the trainability and performance of deep neural networks. In deep architectures, improper weight initialization can lead to vanishing or exploding signal...
The East Asian VLBI Network (EAVN) is an international VLBI facility in East Asia and is operated under mutual collaboration between East Asian countries, as well as part of Southeast Asian and European countries. EAVN currently consists of 16 radio...
Due to its abundant reserves, tight oil has emerged as a significant substitute for conventional petroleum resources. It has become one of the focal points of exploration and research, and a new hot spot in global unconventional oil and gas explorati...
Orthotropic steel decks (OSDs) are inevitably subjected to fatigue damage caused by cycled vehicle loads in long-span bridges. This study establishes a probabilistic analysis framework integrating the dynamic Bayesian network (DBN) and fracture mecha...
In this paper, we propose to review the ways to produce, through photopolymerization, interpenetrating polymer networks (IPN) based, e.g., on acrylate/epoxide or acrylate/vinylether blends and to outline the recent developments that allows a one-step...
The demand for hydrogen in refineries is growing due to its importance as a sulfur capture element. Therefore, hydrogen management is critical for fulfilling demands as efficiently as possible. Through mathematical modeling, hydrogen network manageme...
A district heating (DH) system is one of the most important components of infrastructures in cold areas. Proper DH network design should balance the initial investment and the heat distribution cost of the DH network. Currently, this design is often...
Knowledge of the structural properties of biological neural networks can help in understanding how particular responses and actions are generated. Recently, Witvliet et al. published the connectomes of eight isogenic Caenorhabditis elegans hermaphrod...
In this study, an artificial neural network (ANN) model is developed to predict the stability number of breakwater armor stones based on the experimental data reported by Van der Meer in 1988. The harmony search (HS) algorithm is used to determine th...
Green and energy cooperation is the core issue of the Belt and Road Initiative, which has a profound impact on the reshaping of renewable energy trade networks. In this study, renewable energy trade data from 66 “Belt and Road” partner na...
A dendritic neuron model (DNM) is a deep neural network model with a unique dendritic tree structure and activation function. Effective initialization of its model parameters is crucial for its learning performance. This work proposes a novel initial...
Climate change and its challenges have long been incorporated into the policy-making process. Advocacy actions urge to strengthen the socio-ecological resilience through engagement with stakeholders, feedback recollection, and testing of solutions. S...
The shock initiation randomness problem of energetic materials (SIREM) is an important problem in the research field of energetic material safety. With the purposes of solving SIREM on a macroscopic scale and obtaining the statistics, such as the ini...
This paper presents Laor Initialization, an innovative weight initialization technique for deep neural networks that utilizes forward-pass error feedback in conjunction with k-means clustering to optimize the initial weights. In contrast to tradition...
The prevalence of the Internet of Things (IoT) paradigm in more and more applications associated with our daily lives has induced a dense network in which numerous wireless devices, many of which have limited capabilities (e.g., power, memory, comput...
Software defined network (SDN) is a new network architecture in which the control function is decoupled from the data forwarding plane, that is attracting wide attentions from both research and industry sectors. However, SDN still faces the energy wa...
Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions...
The Belt and Road Initiative (B&R), was initiated by China in 2013, and it covers over 60% and 30% of the world’s population and GDP, respectively. The initiative has directed a great deal of investment in energy, transportation, and 5G. Wh...
Remaining useful life (RUL) prediction of rolling bearings is of significance for improving the reliability and durability of rotating machinery. Aiming at the problem of suboptimal RUL prediction precision under cross-working conditions due to distr...
Offshore oil platforms are difficult to detect due to the complex sea state, the sparseness of target distribution, and the similarity of targets with ships. In this paper, we propose an oil platform detection method in polarimetric synthetic apertur...
Compared to supervised denoising models based on deep learning, the unsupervised Deep Image Prior (DIP) denoising approach offers greater flexibility and practicality by operating solely with the given noisy image. However, the random initialization...
At present, memristive neural networks with various topological structures have been widely studied. However, the memristive neural network with a star structure has not been investigated yet. In order to investigate the dynamic characteristics of ne...
With the in-depth implementation of the “Belt and Road” initiative (BRI), the investment patterns between Belt and Road countries have also become more complicated. The impact of this complex investment network on regional economic develo...
Behavioral malware analysis is a powerful technique used against zero-day and obfuscated malware. Additionally referred to as dynamic malware analysis, this approach employs various methods to achieve enhanced detection. One such method involves usin...
The spiking neural network (SNN) has attracted the attention of many researchers because of its low energy consumption and strong bionics. However, when the network conversion method is used to solve the difficulty of network training caused by its d...
To address the challenge of effective roof support in fully mechanized excavation roadways, this paper proposes an adaptive control method for the initial support force of self-shifting temporary supports based on pressure sensors. First, the mechani...
Occlusion removal in light-field images remains a significant challenge, particularly when dealing with large occlusions. An architecture based on end-to-end learning is proposed to address this challenge that interactively combines CSPDarknet53 and...
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