Objectives: The temporal and spatial information of electroencephalogram (EEG) signals is crucial for recognizing features in emotion classification models, but it excessively relies on manual feature extraction. transformer model has the capability performing automatic extraction; however, its potential not been fully explored emotion-related EEG signals. To address these challenges, present study proposes a novel based convolutional neural networks (TCNN) spatial–temporal (EEG ST) learning...

Refuse Derived Fuel (RDF) was formulated from several municipal waste components in Singapore order to maximize energy efficiency and minimize the environmental impacts. At first, physicochemical properties (proximate ultimate analysis, chloro, heavy metals) heating values of were analyzed assess their thermal behaviour. Three RDF prototypes by combining individual type various fractions with respect values. Landfill mining material chicken manure also involved formation as alternative fuel...

The designed solar-thermal-electric device using the as-prepared MH-AlN/SA composite presents a high output voltage and current of 409 mV 110.8 mA, respectively. Its peak power density is up to 113.3 W m −2 .

<bold><italic>Purpose:</italic></bold> To compare the functional fitness (FF) of community dwelling older adults in Shan Dong (SD) mainland China with their peers from Hong Kong (HK). <bold><italic>Methods:</italic></bold> 1887 living SD were assessed Senior Fitness Test (SFT). One-sample t-tests used to determine age group differences each FF component between and HK populations. <bold><italic>Results:</italic></bold> Compared peers, showed better performance task 30s arm curl, but lower...

Underwater images frequently experience degradation, including color shifts, blurred details, and reduced contrast, primarily caused by light scattering the challenging underwater conditions. The conventional methods based on physical models have proven insufficient for effectively addressing diverse conditions, while deep learning approaches are limited quantity diversity of data, making it to perform well in unknown environments. Furthermore, these typically fail fully exploit spectral...

Problems of data classification can be studied in the framework regularization theory as ill-posed problems. In this framework, loss functions play an important role application to classification. paper, we review some convex functions, including hinge loss, square modified exponential logistic regression well non-convex such sigmoid φ-loss, ramp normalized and function 2 layer neural network. Based on analysis these propose a new differentiable nonconvex function, called smoothed 0-1 which...

This paper presents the optimal finite horizon linear-quadratic control for a class of continuous linear time-invariant descriptor systems subject to previewable desired output. For quadratic performance index and giving reference sequence, solution is obtained in four steps. First, continuous-time with tracking signals are transformed into augmented error systems. Then, necessary optimality conditions derived from maximum principle. Finally, can be differential Riccati equation by...

In industrial manufacturing, metal surface defect detection often suffers from low accuracy, high leakage rates, and false rates. To address these issues, this paper proposes a novel model named DSL-YOLO for detection. First, we introduce the C2f_DWRB structure by integrating DWRB module with C2f, enhancing model's ability to detect small occluded targets effectively extract sparse spatial features. Second, design SADown improve feature extraction in challenging tasks involving blurred...

This study presents a non-linear tip speed ratio (TSR) cascade controller for high power wind turbines (WTs) considering the effects of large rotor inertia and torsional behaviour shafts. A model-based is proposed inner loop. The required reference provided by an outer design procedure control WTs based on backstepping design. It shown that above two-loop schemes lead to nice structure closed-loop systems. Stability result adapted analysis this particular kind systems developed....

Abstract Underwater images are the most direct and effective ways to obtain underwater information. However, typically suffer from contrast reduction colour distortion due absorption scattering of water by light, which seriously limits further development visual tasks. Recently, convolutional neural network has been extensively applied in image enhancement for its powerful local information extraction capabilities, but locality convolution operation, it cannot capture global context well....

Underwater target detection is of great significance in underwater ecological assessment and resource development. To better protect the environment optimize development resources, we propose a new model with several innovations based on YOLOv8 framework. Firstly, SAConv convolutional operation introduced to redesign C2f, core module YOLOv8, enhance network’s feature extraction capability for targets different scales. Secondly, RFESEConv convolution instead conventional neural networks cope...

Two novel constant false alarm rate (CFAR) detectors, the And-CFAR and Or-CFAR, are proposed, The two new CFAR detectors improve conventional cell averaging (CA-CFAR) order statistics (OS-CFAR) by making full use of information. processors combine result CA-CFAR OS-CFAR to get a better detection performance. In homogeneous background, mathematical medals derived their performance has been evaluated compared with that OS-CFAR.

A rapid HPLC-DAD method for analysis of concentrated BTEX and styrene (BTEXS) aqueous mixtures is reported. Good resolutions close to or greater than 1.5 were obtained high equimolar BTEXS concentrations up 2.0 mM. At 5.5 min per sample analysis, this also one the fastest HPLC methods date, providing throughput lowering price.

Emotional brain-computer interface based on electroencephalogram (EEG) is a hot issue in the field of human-computer interaction, and also an important part emotional computing. Among them, recognition EEG induced by emotion key problem. Firstly, preprocessed decomposed tunable-Q wavelet transform. Secondly, sample entropy, second-order differential mean, normalized Hjorth parameter (mobility complexity) each sub-band are extracted. Then, binary gray wolf optimization algorithm used to...

Environmental factors have effects on the growth of plants in greenhouse, so it is significant to research changes environmental greenhouse. The dynamic mathematical model about temperature and humidity this situation analyzed paper. greenhouse are not simple linear process but complicated nonlinear process. theory method used analyze controller's parameters order meet optimal quadratic performance indexes. rationality feasibility proved by simulating MATLAB2008a.

Hybrid model is a simple and accurate for stable heat transfer process. Its theoretical basis shows that it inappropriate to be applied system with severe coefficient drifting. However, drifting normal phenomenon in power chemical industrial due fouling. In this paper, modified hybrid of exchanger proposed. The derivation based on balance fouling principle the exchanger. Considering effect, comprehensive derived. catalog results experiment data show proposed can predict accurately real-time...