The Aquila Optimizer (AO) algorithm is a meta-heuristic with excellent performance, although it may be insufficient or tend to fall into local optima as the complexity of real-world optimization problems increases. To overcome shortcomings AO, we propose an improved (IAO) which improves original AO via three strategies. First, in order improve process, introduce search control factor (SCF) absolute value decreasing iteration progresses, improving hunting strategies AO. Second, random...

Osteosarcoma and chondrosarcoma are common malignant bone tumors, accurate differentiation between these two tumors is crucial for treatment strategies prognosis assessment. However, traditional radiological methods face diagnostic challenges due to the similarity in imaging two.

Abstract Skeleton Ground Truth (GT) is critical to the success of supervised skeleton extraction methods, especially with popularity deep learning techniques. Furthermore, we see GTs used not only for training detectors Convolutional Neural Networks (CNN), but also evaluating skeleton-related pruning and matching algorithms. However, most existing shape image datasets suffer from lack GT inconsistency standards. As a result, it difficult evaluate reproduce CNN-based algorithms on fair basis....

Summary The general Global Navigation Satellite System (GNSS) receiver faces several challenges because of jamming signals, spoofing and multipath which severely influence its safety. In this paper, a scheme with an interference recognition function is designed. the latter, correlation peak different shapes produced according to interferences. machine learning method then applied recognize classify these feature maps. This transforms problem into learning‐based classification problem. order...

In order to accelerate the convergence speed and accuracy of artificial bee colony algorithm, a double strategy improved algorithm is proposed, validate with classical testing functions. Firstly, using tent chaotic mapping, random numbers are generated during search process increase diversity, reverse learning used improve quality solutions, allowing explore more solution spaces process; Then, an adaptive elite guidance introduced hiring process, utilizing global optimal individual...

In view of the variable task structure and complex scheduling environment heterogeneous computing system, low efficiency existing algorithms, this paper abstracts system by establishing a directed acyclic graph target model, proposes Q-learning based intelligent ant colony algorithm. The algorithm adapts scene to environment, dynamically calculates Q matrix according reward function, is used as initial pheromone According pseudo-random proportional rule select processor, list formed...

The security of cryptographic algorithms is great importance to information security. Power attack technology poses a serious threat the algorithm operations. In this paper composite field-based AES mask protection design proposed, realizing inversion operation in S-box through decomposition field. And random added each operations based on structure. Each intermediate value randomized, and cyclic shift used implement transformation round operation, thus improving ability resist power...

With the rapid development of LBS system in recent years, existed communication and cognition model cannot describe its features entirely. After analysis system, aiming at limitations theory, this paper proposes spatial information subscribers.

Aiming at the no-wait flow shop scheduling problem with goal of minimizing maximum makespan, a discrete wolf pack algorithm has been proposed. First, methods for solving and application research were summarized, it was pointed out that there lack on to solve problem. According analysis characteristics problem, individual coded by decimal integer; searching behavior realized through exchange different code bits in wolf, continuous segment head randomly selected replace corresponding fierce...

Skeleton Ground Truth (GT) is critical to the success of supervised skeleton extraction methods, especially with popularity deep learning techniques. Furthermore, we see GTs used not only for training detectors Convolutional Neural Networks (CNN) but also evaluating skeleton-related pruning and matching algorithms. However, most existing shape image datasets suffer from lack GT inconsistency standards. As a result, it difficult evaluate reproduce CNN-based algorithms on fair basis. In this...

In order to give full play the high parallel and efficiency characteristics of heterogeneous signal processing platforms, relevant scholars at home abroad have proposed many task scheduling algorithms with their own advantages improve efficiency. However, for communication intensive tasks, existing deployment methods are no longer applicable because higher requirements delay becomes key limit performance platform. For communication-intensive this paper proposes a load balancing method based...

In recent years, with the popularization of 5G communication technology and rapid growth data traffic network bandwidth, aiming at problem large CPU (Central Processing Unit) processing burden low occupancy in protocol processing, this paper uses TOE (TCP Offload Engine) to implement on ZYNQ hardware. is unload TCP/IP execute it hardware, convert C/RTL (Register Transfer Level) code through high-level integrated HLS (High Level Synthesis). The results show that accelerated method based can...

Deep learning techniques have been widely used in the field of Side Channel Attack (SCA), which poses a serious threat to security cryptographic algorithms. However, deep learning-based side channel attack also has problems such as inefficient models, poor robustness, and longtime consumption. To address these problems, this paper focuses on performance Long Short-term Memory(LSTM) combining with dimensional compression technique Sparse Auto Encoder (SAE), validates it fully synchronized...

Global navigation satellite system (GNSS) has been widely used around the world, but problems like low signal intensity or blocked could often cause users unable to collect enough for position purpose. A pseudolite geolocation is designed which can worked instead of non-line-of-sight (NLOS) satellites, cooperate with on orbit GNSS satellites. We detailed a novel consists and working progress. Through application scenario analysis simulation we verified that pseudorange errors main factor...