To address the difficulty of separating background materials from similar materials associated with the use of “single-spectral information” for hyperspectral anomaly detection, a fast hyperspectral anomaly detection algorithm based on what we term t...
The core–periphery structure is one of the key concepts in the structural analysis of complex networks. It consists of a partitioning of the node set of a given graph or network into two groups, called core and periphery, where the core nodes i...
Research front detection and topic evolution has for a long time been an important direction for research in the informetrics field. However, most previous studies either simply use a citation count for scientific document clustering or assume that e...
Bin Packing is one of the research areas of Operations Research with many industrial applications, as well as rich theoretical impact. In this article, the authors deal with Bin Packing on the practical side: they consider two Bin Packing Benchmark c...
This paper presents a performance comparison of greedy heuristics for a recent variant of the dominating set problem known as the minimum positive influence dominating set (MPIDS) problem. This APX-hard combinatorial optimization problem has applicat...
In emerging Cyber-Physical Systems (CPS), the demand for higher communication performance and enhanced wireless connectivity is increasing fast. To address the issue, in our recent work, we proposed a dynamic programming algorithm with polynomial tim...
In the wartime scenario of large-scale air combat, the battlefield situation is dynamically changing, and damaged aircraft often face issues such as limited maneuverability and fuel shortages. Relying on fixed corridors for return flights is no longe...
This paper proposes a random tree algorithm based on a potential field oriented greedy strategy for the path planning of unmanned aerial vehicles (UAVs). Potential-field-RRT (PF-RRT) discards the defect of traditional artificial potential field (APF)...
We propose a new iterative greedy algorithm to reconstruct sparse signals in Compressed Sensing. The algorithm, called Conjugate Gradient Hard Thresholding Pursuit (CGHTP), is a simple combination of Hard Thresholding Pursuit (HTP) and Conjugate Grad...
The prediction of reservoir and caprock thickness is important in geological evaluations for site selection for aquifer underground gas storage. Therefore, high-resolution seismic identification of reservoirs and caprocks is crucial. High-resolution...
The privacy and security of the Internet of Things (IoT) are emerging as popular issues in the IoT. At present, there exist several pieces of research on network analysis on the IoT network, and malicious network analysis may threaten the privacy and...
To address the registration problem in current machine vision, a new three-dimensional (3-D) point cloud registration algorithm that combines fast point feature histograms (FPFH) and greedy projection triangulation is proposed. First, the feature inf...
The differences in constraints between an automotive painting workshop and a final assembly workshop can lead to production scheduling disruptions, and using the Painted Body Store (PBS) in automotive manufacturing can optimize production scheduling...
A dominating set of a graph is a subset of vertices such that every vertex not in the subset has at least one neighbor within the subset. The corresponding optimization problem is known to be NP-hard. It is proved to be beneficial to separate the sol...
In this paper; we introduce an enhanced electromyography (EMG) pattern recognition algorithm based on a split-and-merge deep belief network (SM-DBN). Generally, it is difficult to classify the EMG features because the EMG signal has nonlinear and tim...
This work develops an improved integrated planning and control framework for an unmanned aerial vehicle (UAV) in complex environments with dense obstacles to achieve fast and accurate path planning, trajectory generation, and tracking control. Utiliz...
Orthogonal transformations, proper decomposition, and the Moore–Penrose inverse are traditional methods of obtaining the output layer weights for an extreme learning machine autoencoder. However, an increase in the number of hidden neurons caus...
In this paper, we investigate a lossy source coding problem, where an upper limit on the permitted distortion is defined for every dataset element. It can be seen as an alternative approach to rate distortion theory where a bound on the allowed avera...
Community detection has been a subject of extensive research due to its broad applications across social media, computer science, biology, and complex systems. Modularity stands out as a predominant metric guiding community detection, with numerous a...
The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more...
With regard to low-voltage (LV) distribution networks, the quality of distributed electricity can be compromised by the level of phase load imbalance. Consequently, numerous phase load balancing (PLB) algorithms have been proposed in the specialized...
This paper describes the design and optimization of a smart algorithm based on artificial intelligence to increase the accuracy of an ocean water current meter. The main purpose of water current meters is to obtain the fundamental frequency of the oc...
Smart devices have become the core ingredient in maintaining human society, where their applications span basic telecommunication, entertainment, education, and even critical security tasks. However, smartphone security measures have not kept pace wi...
With the rapid advancement of the electric vehicle (EV) industry, the ownership of EVs and their charging power have increased significantly, gradually exerting a greater impact on the power grid. To meet the diverse charging needs of different EV us...
Federated learning (FL) can tackle the problem of data silos of asymmetric information and privacy leakage; however, it still has shortcomings, such as data heterogeneity, high communication cost and uneven distribution of performance. To overcome th...
The Whittle index for restless bandits (two-action semi-Markov decision processes) provides an intuitively appealing optimal policy for controlling a single generic project that can be active (engaged) or passive (rested) at each decision epoch, and...
Nowadays, heterogeneous CPU-GPU systems have become ubiquitous, but current parallel spatial interpolation (SI) algorithms exploit only one type of processing unit, and thus result in a waste of parallel resources. To address this problem, a hybrid p...
In light of the increasing scarcity of frequency spectrum resources for satellite communication systems based on the transparent transponder, fast and efficient satellite resource allocation algorithms have become key to improving the overall resourc...
Trie is one of the most common data structures for string storage and retrieval. As a fast and efficient implementation of trie, double array (DA) can effectively compress strings to reduce storage spaces. However, this method suffers from the proble...
This paper focuses on the aircraft landing problem with time windows (ALP-TW), which consists of determining a landing schedule for each aircraft within a specified time window and determining the minimum required separation interval between successi...
Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, lea...
The discounted {0-1} knapsack problem (D{0-1}KP) is a multi-constrained optimization and an extended form of the 0-1 knapsack problem. The DKP is composed of a set of item batches where each batch has three items and the objective is to maximize prof...
To solve the low efficiency of traditional sheet metal measurement, this paper proposes a digital inspection method for sheet metal parts based on 3D point clouds. The 3D point cloud data of sheet metal parts are collected using a 3D laser scanner, a...
Current Field Programmable Gate Arrays (FPGAs) provide fast routing links and special logic to perform carry operations; however, these resources can also be used to implement non-arithmetic circuits. In this paper, a new approach for mapping logic f...
Recently, the chaotic compressive sensing paradigm has been widely used in many areas, due to its ability to reduce data acquisition time with high security. For cognitive radio networks (CRNs), this mechanism aims at detecting the spectrum holes bas...
Lithology classification is important in mineral resource exploration, engineering geological exploration, and disaster monitoring. Traditional laboratory methods for the qualitative analysis of rocks are limited by sampling conditions and analytical...
Full Matrix Capture is a multi-channel data acquisition method which enables flexible, high resolution imaging using ultrasound arrays. However, the measurement time and data volume are increased considerably. Both of these costs can be circumvented...
The importance of individuals and groups in networks is modeled by various centrality measures. Additionally, Freeman’s centralization is a way to normalize any given centrality or group centrality measure, which enables us to compare individua...
Ant colony optimization (ACO) is a well-known class of swarm intelligence algorithms suitable for solving many NP-hard problems. An important component of such algorithms is a record of pheromone trails that reflect colonies’ experiences with p...
Quantitative Structure–Activity Relationship (QSAR) aims to correlate molecular structure properties with corresponding bioactivity. Chance correlations and multicollinearity are two major problems often encountered when generating QSAR models. Featu...
Recently, drones, have been utilized in many real-life applications including healthcare services. For example, providing medical supplies, blood samples, and vaccines to people in remote areas or during emergencies. In this study, the maximum covera...
The body dimension measurement of large animals plays a significant role in quality improvement and genetic breeding, and the non-contact measurements by computer vision-based remote sensing could represent great progress in the case of dangerous str...
Influence maximization in online social networks is used to select a set of influential seed nodes to maximize the influence spread under a given diffusion model. However, most existing proposals have huge computational costs and only consider the dy...
In this paper, we investigate dynamic resource selection in dense deployments of the recent 6G mobile in-X subnetworks (inXSs). We cast resource selection in inXSs as a multi-objective optimization problem involving maximization of the minimum capaci...
For the past few years, flash memory has been widely used because of its prominent advantages such as fast access speed, nonvolatility, high reliability, and low power consumption. However, flash memory still has several drawbacks that need to be ove...
Planar surfaces are prevalent components of man-made indoor scenes, and plane extraction plays a vital role in practical applications of computer vision and robotics, such as scene understanding, and mobile manipulation. Nowadays, most plane extracti...
This paper proposes a simple yet effective method for improving the efficiency of sparse coding dictionary learning (DL) with an implication of enhancing the ultimate usefulness of compressive sensing (CS) technology for practical applications, such...
We propose using five data-driven community detection approaches from social networks to partition the label space in the task of multi-label classification as an alternative to random partitioning into equal subsets as performed by RAkELd. We evalua...