Neural Computing and Applications

Nowadays, cryptographic systems’ designers are facing significant challenges in their designs. They have to constantly search for new ideas of fast unbreakable algorithms with a very powerful key generator. In this paper, we propose a novel hybrid ...

Fingerprint has been widely used in biometric applications. Numerous established researches on image enhancement techniques have been done to improve the quality of fingerprint images. However, the production of low-quality images due to the ...

This study investigates the capability of sequence-to-sequence machine learning (ML) architectures in an effort to develop streamflow forecasting tools for Canadian watersheds. Such tools are useful to inform local and region-specific water ...

This study proposes a new nature-inspired metaheuristic that mimics the behaviour of the prairie dogs in their natural habitat called the prairie dog optimization (PDO). The proposed algorithm uses four prairie dog activities to achieve the two ...

Dental radiography offers significant indication for medical/clinical diagnosis, quality assessment and treatment. Huge efforts have been taken while developing the digital dental X-ray image analysis system for the enhancement of clinical ...

The mismatch between power generation and load demand causes unwanted fluctuations in frequency and tie-line power, and load frequency control (LFC) is an inevitable mechanism to compensate the mismatch. For this issue, this paper explores the ...

Human trajectory prediction is a challenging task with important applications such as intelligent surveillance and autonomous driving. We recognize that pedestrians in close and distant neighborhoods have different impacts on the person’s decision ...

Currently, angle two-dimensional principal component analysis (Angle 2DPCA) effectively enhances the robustness of traditional 2DPCA by using a measurement model based on F-norm in the relationship between reconstruction error and variance, and ...

Accurate identification of invasive plants (IPs) is critical for the preservation of natural ecosystems. Unmanned Aerial Systems (UAS) offer an efficient method of monitoring IPs in conservation areas. However, the process of finding IPs in UAS is ...

Over the last few years, studies related to the detection of mental disorders in social media have been increasing. The latter because the awareness created by health campaigns that emphasizes the commonness of these disorders among all of us has ...

Sea surface temperature modifies the air in the earth’s atmosphere. $\text{EINi}\tilde{\eta }\text{o}$ signs in the sea surface temperature spread the warm water in the ocean and take the rain. Several existing models forecast rainfall using statistical analysis, machine ...

Brain–Computer Interface (BCI) technology has been tested as a method to restore or improve brain function. It attempts to improve human cognitive functions by using BCI's ability to predict cognitive situations (e.g., attention and memory ...

The quantitative analysis of brain magnetic resonance imaging (MRI) represents a tiring routine and enormously on accurate segmentation of some brain regions. Gliomas represent the most common and aggressive brain tumors. In their highest grade, ...

What makes artificial intelligence techniques so remarkable in the field of computer science is undoubtedly their success in producing effective solutions to difficult computational problems. In particular, metaheuristic optimization algorithms ...

In the era of social networking and e-commerce sites, users provide their feedback and comments in the form of reviews for any product, topic, or organization. Due to high influence of reviews on users, spammers use fake reviews to promote their ...

Frequent entry in the tunnel boring machine cutterhead for disc cutter wear inspection is a risky, time-consuming, and labor-intensive activity. Existing disc cutter wear prediction models mainly focus on cutter consumption before construction, ...

Adversarial examples can attack multiple unknown convolutional neural networks (CNNs) due to adversarial transferability, which reveals the vulnerability of CNNs and facilitates the development of adversarial attacks. However, most of the existing ...

The need for better-performing algorithms to solve real-world power systems engineering problems has always been a challenging topic. Due to their stochastic nature, metaheuristic algorithms can provide better results. Thus, they have a rising ...

Prohibited item detection from X-ray images determines whether any prohibited items are present in baggage, and great progress has recently been made in this field with the development of deep learning. Nevertheless, the appearance of an occluded ...

Training a deep neural network in consecutive tasks remains a challenge due to catastrophic forgetting. Although class incremental learning (CIL) has been an active research area, CIL in deep metric learning has scarcely been discussed. One of the ...

Deep large excavations in urban areas are an important engineering challenge, whereas secant piling techniques are among the best solutions to have a safe workplace environment. Optimal design of these structures will increase efficiency as well ...

In this paper, we propose a Skeleton-based Relation Consistency Learning scheme (SRCL) for unsupervised 3D action representation learning. By leveraging the inter-instance similarity score distribution as relation metric, SRCL is able to pursue ...

Today, the estimation of physical parameters has become very important; for instance, the water flow rate (RWFR) estimation is one of the types that will gain considerable significance among the others performed in this way. The forecasting of ...

The Covid-19 pandemic is a deadly epidemic and continues to affect all world. This situation dragged the countries into a global crisis and caused the collapse of some health systems. Therefore, many technologies are needed to slow down the spread ...

Several cybersecurity domains, such as ransomware detection, forensics and data analysis, require methods to reliably identify encrypted data fragments. Typically, current approaches employ statistics derived from byte-level distribution, such as ...$\mathrm{}$$\mathrm{}$

Solving the optimal reactive dispatch (ORPD) is a strenuous task to assign the best operating point of the electrical system components to obtain the most secure and stable state of system. This problem became more complex problem due the ...

The multiphase shock wave phenomenon is significantly affected by accumulated upstream sediment deposition and downstream hydraulic conditions. There is a lack of studies evaluating the efficacy of intelligent models in representing multiphase ...

In conversational systems, we can use external knowledge to generate more diverse sentences and make these sentences contain actual knowledge. Leveraging knowledge for conversation system is important but challenging. Firstly, the conversation ...