In this study, we developed a system based on deep space-time neural networks for gesture recognition. When users change or the number of categories increases, accuracy recognition decreases considerably because most systems cannot accommodate both user differentiation and diversity. To overcome limitations existing methods, designed one- dimensional parallel long short-term memory-fully convolutional network (LSTM-FCN) model to extract features different dimensions. LSTM can learn complex...

Background Acute kidney injury (AKI) is the most common major complication of cardiac surgery field. The purpose this study to investigate association between acute and prognoses patients in Medical Information Mart for Intensive Care III (MIMIC-III) database. Methods Clinical data were extracted from MIMIC-III Adult (≥18 years) database enrolled. Multivariable logistic regression analyses employed assess associations comorbidity 30-day mortality, 90-day mortality hospital mortality....

The Internet of Things (IoT) is an advanced technology that comprises numerous devices with carrying sensors to collect, send, and receive data. Due its vast popularity efficiency, it employed in collecting crucial data for the health sector. As generate huge amounts data, better be aggregated before being transmitting further. These redundant frequently transmit same values again unless there no variation base scheme has mechanism comprehend duplicate This problem a negative effect on...

Intelligent radios collect information by sensing signals within the radio spectrum, and automatic modulation recognition (AMR) of is one their most challenging tasks. Although result a classification based on deep neural network better, training requires complicated calculations expensive hardware. Therefore, in this paper, we propose master–slave AMR architecture using reconfigurability field-programmable gate arrays (FPGAs). First, discuss method building AMR, stack convolution...

Large-scale optimization is a challenging problem because it involves large number of decision variables. In this paper, simple but effective method, called hierarchical sorting swarm optimizer (HSSO), proposed for large-scale optimization. As variant representative particle (PSO), HSSO first sorts the initial particles according to their fitness values, and then partitions sorted into two groups, namely, good group corresponding better bad with worse values. The updated by learning from...

The rapid development of the Internet Things (IoT) has opened way for transformative advances in numerous fields, including healthcare. IoT-based healthcare systems provide unprecedented opportunities to gather patients’ real-time data and make appropriate decisions at right time. Yet, deployed sensors generate normal readings most time, which are transmitted Cluster Heads (CHs). Handling these voluminous duplicated is quite challenging. existing techniques have high energy consumption,...

A chiller is a machine that removes heat from liquid through one of the refrigeration cycles and exchangers uses it to cool air equipment. In this paper, new method for solving dynamic optimal loading problem proposed. The paper improved technique, quantum emperor penguin optimisation algorithm solve (OCL) with minimum power consumption. proposed used improve ability. To investigate applied three OCL benchmarks results are compared some algorithms such as World Cup Optimisation (WCO),...

ABSTRACT This paper presents a two-stage approach, named Cooperatively Coevolving Competition Swarm Optimiser (C3SO), for large-scale optimisation. C3SO first detects interactions among the original variables by differential grouping algorithm, therein decomposing problem into several sub-components. In next stage, new approach is developed using competition mechanism to independently optimise each sub-component obtained in stage. Hence, takes advantages of both divide-and-conquer and...

In an integrated sensing and communication (ISAC) system, improving the accuracy of delay Doppler shift parameter estimation is a critical task that sustains performance system. To tackle this task, we introduce two-stage algorithm named matched filter-Fibonacci (MF-F), which employs orthogonal time frequency space (OTFS) waveform characteristics in delay-Doppler (DD) domain. first step (MF), parameters are approximated on integer grid using relationship between input output signals DD...

The main processes of a cognitive radio system include spectrum sensing, decision, sharing, and conversion.Experimental results show that these stages introduce time delay affects the sensing accuracy, reducing its efficiency.To reduce delay, frequency prediction was proposed to alleviate burden on sensing.In this paper, deep recurrent neural network (DRNN) predict multiple slots, since existing methods only one slot.The continuous state channel is divided into many forming series...

Existing spectrum-sensing techniques for cognitive radios require an analog-to-digital converter (ADC) to work at high dynamic range and a sampling rate, resulting in cost. Therefore, this paper, method based on unidirectionally coupled, overdamped nonlinear oscillator ring is proposed. First, the numerical model of such system established circuit oscillator. Through analysis model, critical condition system's starting oscillation determined, simulation results response Gaussian white noise...

The shape of radio signals determined by modulation system and that produced the nonlinear transform are different in kind, which is basis for discriminating them. Feature extraction based on fractal theory a new method. In this paper,the features projected to feature space computing variance dimension Mandelbrot singularity spectra dimensions. numerical result show differences do exist between modulated transformed signals. results these can be extracted theory, has engineering value identification

Non-Orthogonal Multiple Access (NOMA) enables superposition of user signals in power domain. Combining NOMA with Multiple-input Multiple-output (MIMO) technology can improve system spectral efficiency. Successive interference cancellation (SIC) receiver is often used NOMA. However, most schemes are limited by high complexity and assume perfect channel state information ( CSI) that may not be available reality. To this end, we propose a novel deep learning based MIMO-NOMA paper. We train the...

The computer simulation technique has been widely applied to the mine disaster control field. In this paper, we discuss use of dense borehole pre-drainage technology as a preventive measure for coal and gas outburst. order enhance efficiency rationally arrange borehole, solid-gas coupled RFPA <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2D</sup> -Gas software is used study variation regularity in pressure drainage radius under different...

City-wide parking guidance systems (CPGS) is a specialized cyber-physical search engine for vehicles to look proper available lots nearby, aiming relieve the pains. If from perspective of engine, will constitute city-wide network, as nodes and roads linking them edges. Inspired by PageRank, classic ranking model in WEB, we propose new named ParkingRank-D, evaluate importance all over city, help recommend more accurately. ParkingRank-D spatial-temporal model, including three steps. Firstly,...

This paper discusses the security of clock synchronization algorithm based on biological example Asian Fireflies in wireless sensor networks.Huge swarms these fireflies use principle pulse coupled oscillators order to synchronously emit light flashes attract mating partners.When applying this real networks, potential threat hostile may disturb synchronization.An improved Reachback Firefly Algorithm is implemented MAC layer networks (WSNs), which change coupling strength among anti attack...

In this paper, the receiver of multi-user uplink non orthogonal multiple access (NOMA) combined with frequency division multiplexing (OFDM) signal is studied. The designed based on deep neural network(DNN) in learning, which consists a layer DNN and soft decision. It solves problems channel estimation error, time delay restriction decoding between users traditional detection methods. can recover symbols all at one perform jointly. simulation results show that has strong robustness to user's...

As an important branch of array signal processing, the beamforming algorithm can form gain in direction desired and null interference signal, which effectively suppress multipath signals. To address problem that classical spatial spectrum estimation does not have high resolution for coherent sources, a DOA method based on Witch function normalization variable-step-size LMS is proposed this paper. By defining reciprocal pattern as spectrum, regards peak search. The simulation results show And...

Accurate classification of wine quality may help to improve making technology wine. For achieving more effective classification, a method named DE_PSO_SVM (dataset enhancement (DE)_particle swarm optimization (PSO)_support vector machine (SVM)) is proposed. The correlation between feature attributes and labels samples were analyzed achieve dimension reduction. DE was achieved by calculating the different weight sums adjacent odd even rows, both which belong same class samples. PSO used...

OFDM is one of the most widely used multi-carrier modulation technologies in wireless communication. However, case high mobility, orthogonality between sub-carriers destroyed due to existence time selective fading, and performance system greatly affected. In order reduce this effect, data can be pre-coding before modulation. The technique adopted paper Walsh-Hadamard transform (WHT). are distributed evenly on all by WHT operation, which avoids problem loss caused some can’t recovered. paper,...