Tissue engineering is a powerful tool with which to systematically identify the determinants of biological functions. Applied to the design and fabrication of biomimetic brains, tissue engineering serves to disentangle the complex anatomy of neural c...
Biological neural networks demonstrate remarkable resilience and the ability to compensate for neuron losses over time. Thus, the effects of neural/synaptic losses in the brain go mostly unnoticed until the loss becomes profound. This study analyses...
This paper examines the use of deep recurrent neural networks to classify traffic patterns in smart cities. We propose a novel approach to traffic pattern classification based on deep recurrent neural networks, which can effectively capture traffic p...
The recent arrival on the market of high-performing neural MT engines will likely lead to a profound transformation of the translation profession. The purpose of this study is to explore how this paradigm change impacts the post-editing process, with...
The current study uses a novel method of multilevel neurons and high order synchronization effects described by a family of special metrics, for pattern recognition in an oscillatory neural network (ONN). The output oscillator (neuron) of the network...
Gait patterns are a result of the complex kinematics that enable human two-legged locomotion, and they can reveal a lot about a person’s state and health. Analysing them is useful for researchers to get new insights into the course of diseases, and f...
The detection and identification of non-random patterns is an important task in statistical process control (SPC). When a non-random pattern appears on a control chart, it means that there are assignable causes which will gradually deteriorate the pr...
Driving patterns exert an important influence on the fuel economy of vehicles, especially hybrid electric vehicles. This paper aims to build a method to identify driving patterns with enough accuracy and less sampling time compared than other driving...
Prolific growth of sensors and sensor technology has resulted various applications in sensing, monitoring, assessment and control operations. Owing to the large number of sensing units the the aggregate data volume creates a burden to the central dat...
Inefficient utilization of the frequency spectrum due to conventional regulatory limitations and physical performance limiting factors, mainly the Signal to Noise Ratio (SNR), are prominent restrictions in digital wireless communication. Pattern Base...
Fabric properties significantly influence the accuracy of pattern dimensions derived from 3D scanned garment samples. To enhance the generated pattern accuracy, a novel predictive model was proposed to estimate the pattern dimension change ratio by i...
The oil and gas industry consistently embraces innovative technologies due to the significant expenses associated with hydrocarbon transportation, pipeline corrosion issues, and the necessity to gain a deeper understanding of two-phase flow character...
Partial discharge (PD) is one of the major form expressions of gas-insulated switchgear (GIS) insulation defects. Because PD will accelerate equipment aging, online monitoring and fault diagnosis plays a significant role in ensuring safe and reliable...
The classification of sound signals can be applied to the fault diagnosis of mechanical systems, such as vehicles. The traditional sound classification technology mainly uses the time-frequency domain characteristics of signals as the basis for ident...
This paper proposes radiation pattern synthesis of almost periodic antenna arrays including mutual coupling effects (extracted by Floquet analysis according to our previous work), which in principal has high directivity and a large bandwidth. For mod...
With recent advancements in digital environments, user authentication is becoming increasingly important. Traditional authentication methods such as passwords and PINs suffer from inherent limitations, including vulnerability to theft, guessing, and...
Stall flow patterns occur frequently in pump turbines under off-design operating conditions. These flow patterns may cause intensive pressure pulsations, sudden increases in the hydraulic forces of the runner, or other adverse consequences, and are s...
Spiking neural network (SNN) has emerged as one of the most powerful brain-inspired computing paradigms in complex pattern recognition tasks that can be enabled by neuromorphic hardware. However, owing to the fundamental architecture mismatch between...
The power system on the offshore platform is of great importance since it is the power source for oil and gas exploitation, procession and transportation. Transformers constitute key equipment in the power system, and partial discharge (PD) is its mo...
The accurate identification of the gas–liquid two-phase flow pattern within the impeller of a centrifugal pump is critical to develop a reliable model for predicting the gas–liquid two-phase performance of the centrifugal pump. The influe...
Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these...
As the current standardization for the 5G networks nears completion, work towards understanding the potential technologies for the 6G wireless networks is already underway. One of these potential technologies for the 6G networks is reconfigurable int...
Forecasting time series with multiple seasonal cycles such as short-term load forecasting is a challenging problem due to the complicated relationship between input and output data. In this work, we use a pattern representation of the time series to...
With the recent growth of the Internet of Things (IoT) and the demand for faster computation, quantized neural networks (QNNs) or QNN-enabled IoT can offer better performance than conventional convolution neural networks (CNNs). With the aim of reduc...
(1) Background: The present study aims to evaluate and compare the model performances of different convolutional neural networks (CNNs) used for classifying sagittal skeletal patterns. (2) Methods: A total of 2432 lateral cephalometric radiographs we...
Associative learning is a fundamental neural mechanism in human memory and cognition. It has attracted considerable attention in neuromorphic system design owing to its multimodal integration, fault tolerance, and energy efficiency. However, prior st...
On a global scale, the process of automatic defect detection represents a critical stage of quality control in textile industries. In this paper, a semantic segmentation network using a repeated pattern analysis algorithm is proposed for pixel-level...
Distinguishing the types of partial discharge (PD) caused by different insulation defects in gas-insulated switchgear (GIS) is a great challenge in the power industry, and improving the recognition accuracy of the relevant models is one of the key pr...
Partial discharge (PD) is a crucial and intricate electrical occurrence observed in various types of electrical equipment. Identifying and characterizing PDs is essential for upholding the integrity and reliability of electrical assets. This paper pr...
Given the increasing climate variability, it is becoming difficult to predict flooding events. We may be able to manage or even prevent floods if detecting global climate patterns, which affect flood occurrence, and using them to make predictions are...
Agriculture is an area that currently benefits from the use of new technologies and techniques, such as artificial intelligence, to improve production in crop fields. Zacatecas is one of the states producing the most onions in the northeast region of...
In order to improve the accuracy and efficiency of flow pattern recognition and to solve the problem of the real-time monitoring of flow patterns, which is difficult to achieve with traditional visual recognition methods, this study introduced a flow...
Bearings are complex components with onlinear behavior that are used to mitigate the effects of inertia. These components are used in various systems, including motors. Data analysis and condition monitoring of the systems are important methods for b...
Different types of partial discharge (PD) in gas-insulated switchgear (GIS) cause different damage to GIS insulation, correctly identifying the PD type is very important for evaluating the insulation status of GIS. This paper proposes a PD pattern re...
A method for gas–solid two-phase flow pattern identification in horizontal pneumatic conveying pipelines is proposed based on an electrostatic sensor array (ESA) and artificial neural network (ANN). The ESA contains eight identical arc shaped e...
Rapid urbanization has altered the land use pattern, reducing urban green space and increasing carbon emissions, and it is critical to scientifically examine the interaction mechanism between green space and carbon emissions in order to drive low-car...
There are inevitable multiphase flow problems in the process of subsea oil-gas acquisition and transportation, of which the two-phase flow involving gas and liquid is given much attention. The performance of pipelines and equipment in subsea systems...
Development of neuromorphic systems based on new nanoelectronics materials and devices is of immediate interest for solving the problems of cognitive technology and cybernetics. Computational modeling of two- and three-oscillator schemes with thermal...
Recognizing morphological patterns in lines and segmenting them into homogeneous segments is critical for line generalization and other applications. Due to the excessive dependence on handcrafted features in existing methods and their insufficient c...
Control charts are an important tool in statistical process control (SPC). They have been commonly used for monitoring process variation in many industries. Recognition of non-random patterns is an important task in SPC. The presence of non-random pa...
Nowadays, the popularity of the internet has continuously increased. Predicting human body dimensions intelligently would be beneficial to improve the precision and efficiency of pattern making for enterprises in the apparel industry. In this study,...
Ultra-high density data storage has gained high significance given the increasing amounts of data; many technologies have been proposed to achieve a high density. Among them, bit-pattern media recording (BPMR) is a promising technology. In BPMR syste...
Control charts are an important tool for statistical process control (SPC). SPC has the characteristics of fluctuation and asymmetry in the symmetrical coordinate system. It is a graph with control limits used to analyze and judge whether the process...
Wafer defect pattern recognition can help engineers improve the production process of semiconductor chips. In real industrial scenarios, the recognition of mixed-type wafer defects is difficult and the production scale of semiconductor wafers is larg...
Recently, sound-based diagnosis systems have been given much attention in many fields due to the advantages of their simple structure, non-touching measurement style, and low-power dissipation. In order to improve the efficiency of coal production an...
This paper proposes a hybrid algorithm combining the symmetrized dot pattern (SDP) method and a convolutional neural network (CNN) for fault detection in lithium battery modules. The study focuses on four fault types: overcharge, over-discharge, agin...
As a novel neural network learning framework, Twin Extreme Learning Machine (TELM) has received extensive attention and research in the field of machine learning. However, TELM is affected by noise or outliers in practical applications so that its ge...
In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decompositio...
In the field of the muscle–computer interface, the most challenging task is extracting patterns from complex surface electromyography (sEMG) signals to improve the performance of myoelectric pattern recognition. To address this problem, a two-s...
As global oil demand continues to increase, in recent years, countries have continued to expand the development of oil reserves, highlighting the importance of oil. In order to adapt to different strata distribution conditions, domestic drilling tech...
of 103