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Sensory modulation is an emerging approach that aims to reduce distress and agitation in mental health service users and potentially avoid the necessity for coercive practices such as seclusion and restraint. Despite the growing use of this intervention, there has been limited research exploring the implementation of sensory modulation at an organisational level, both internationally and within the New Zealand context. The purpose of this study is to investigate the implementation of a sensory modulation programme in two New Zealand inpatient mental health services using an exploratory organisational case study design.

Organisational case study design methodology was used to explore the implementation of a sensory modulation programme in two New Zealand acute adult inpatient mental health services. This study explored how key organisational and staff factors (including policies and practices related to de-escalation and seclusion reduction) influence sensory modulation implementation. Cases were described and examined the pattern of findings.

Strategies found to support implementation were identified at environmental, organisational, group and individual staff levels. Aspects highlighted as being particularly important included taking an inter-professional approach in leadership and training, rostering flexibility and leeway in staffing levels to support training attendance and responsiveness to crises.

The facilitators and strategies highlighted in this study may be used to support the design and implementation of future sensory modulation programmes in New Zealand and internationally.

The complexity of factors that influenced the implementation of the sensory modulation approach within an inpatient setting made determining the effectiveness of the approach challenging. However, the general principles and strategies identified in this study offer useful insights for the design and implementation of future sensory modulation programmes.

The purpose of this paper is to find out the use of compressive sensing (CS) algorithm for wireless sensor networks (WSNs). As energy-efficient algorithms are required for WSNs, CS is very much useful as less than 25 per cent of the entire input data alone is required to be transmitted, and reconstruction at the receiver with this reduced data set is of good quality. But, the usefulness of the algorithm with suitable modulation schemes is not analyzed so far in the literature. Hence, this work concentrated on the algorithm performance with different modulation schemes and different channel conditions.

Compressive sensing encoding is performed by using suitable transform on the input signal. Here, DCT and DWT are used to generate the sparse signal. Random measurement matrix is used to generate the compressed output, which is reconstructed using the Basis Pursuit (BP) method. Also, an analysis for the energy-efficient modulation scheme is performed by modulating the compressed output using QPSK/BPSK/QAM and transmitted by considering the Gaussian and Rayleigh Channels. Energy required per bit transmission is modeled and computed for different schemes.

Simulation result shows that the use of CS algorithm for data compression tremendously reduces the number of transmission bits and, hence, enhances the transmission and bandwidth efficiency in WSN. Results show that DWT is a much suitable transform to be used for sparse measurement generation. In comparison with DCT, DWT is computationally simple and takes very less time, which is expected in real-time application. The reconstruction result shows that about 25 per cent of the data sample is sufficient to recover the original image, perhaps which is the most surprising result. An extensive analysis of various modulation schemes based on the energy model shows that QPSK is in the AWGN channel, and QAM modulation in the Rayleigh channel is a much suitable modulation scheme to be used in WSN for further reduction of energy consumption.

Compressive sensing is recently gaining importance for quantization, compression and noise removal in images. In this paper, this technique was used along with modulation schemes to analyze the suitability of the algorithm for WSN.

Workshops are commonly used to up-skill staff and their usefulness can be determined by measuring whether or not learning needs have been met and, in particular, whether attitudes have changed. In the field of mental health, sensory modulation workshops have been introduced to educate staff about preventative measures that reduce the use of seclusion and restraint for service users with challenging behaviours. The purpose of this paper is to evaluate the impact of such a workshop.

A one-day workshop was developed based on a review of the literature and feedback from previous workshops, and with input from an industry-based reference group. An evaluation tool was designed to measure the learning outcomes, i.e., the knowledge, skills, and attitudes of the 23 participants. The Statistical Package for the Social Sciences (SPSS v20) was used to analyse the data. Multi-variate analysis of variance was used to determine the relationship between variables.

A significant increase in the knowledge, skills, and attitudes of mental health staff was identified after the one-day workshop (F=106.346, df=1, p<0.000). When considering which participants showed most benefits, it was shown that the demographics had no effect, i.e., education level, practice discipline, years of work experience in mental health, and previous sensory modulation training.

Measuring learning outcomes provides essential information about whether or not the learning objectives have been met. This allows future workshops to be tailored to ensure that the learning opportunity is at the correct level for the learners. More traditional evaluations that elicit the views of the content covered and teaching methods should additionally be used to supplement this information.

Workshops are often evaluated on the basis of the participants’ subjective response to a quick questionnaire. Developing a tool to measure outcomes is a more effective way to determine what has been learned and to ensure that positive outcomes for individuals and their organisations can be reached.

Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed by these works cannot be directly applied to the actual wireless communication scenario, because there are usually two kinds of dilemmas when recognizing the real modulated signal, namely, long sequence and noise. This paper aims to effectively process in-phase quadrature (IQ) sequences of very long signals interfered by noise.

This paper proposes a general model for a modulation classifier based on a two-layer nested structure of long short-term memory (LSTM) networks, called a two-layer nested structure (TLN)-LSTM, which exploits the time sensitivity of LSTM and the ability of the nested network structure to extract more features, and can achieve effective processing of ultra-long signal IQ sequences collected from real wireless communication scenarios that are interfered by noise.

Experimental results show that our proposed model has higher recognition accuracy for five types of modulation signals, including amplitude modulation, frequency modulation, gaussian minimum shift keying, quadrature phase shift keying and differential quadrature phase shift keying, collected from real wireless communication scenarios. The overall classification accuracy of the proposed model for these signals can reach 73.11%, compared with 40.84% for the baseline model. Moreover, this model can also achieve high classification performance for analog signals with the same modulation method in the public data set HKDD_AMC36.

At present, although many AMR methods based on deep learning have been proposed, these works are based on the model’s classification results of various modulated signals in the AMR public data set to evaluate the signal recognition performance of the proposed method rather than collecting real modulated signals for identification in actual wireless communication scenarios. The methods proposed in these works cannot be directly applied to actual wireless communication scenarios. Therefore, this paper proposes a new AMR method, dedicated to the effective processing of the collected ultra-long signal IQ sequences that are interfered by noise.

The specific modulation methods are used to control different kind of single-phase, as well as three-phase, inverters to ensure flexibility and high quality of the output waveform. This paper aims to present a combination of two classical methods, namely, pulse width modulation method and direct digital synthesis modulation method.

The total harmonic distortion of output waveforms of single-phase inverter based on elaborated modulation method has been determined by means of fast Fourier transform analysis. Tests have been carried out by using standard low-frequency application and also a wireless resonant energy link system.

Applying appropriate timer parameters of microcontroller enables to obtain a waveform for given output parameters (amplitude, frequency, frequency modulation index, etc.). The only limitation is the computing power of a microcontroller.

The elaborated method can be successfully used in both low- and high-frequency application ensuring high level of output waveform quality. Additional signal generators and the control of amplitude modulation ratio are no longer indispensable, what simplify immensely a control system.

These implementations not only generate excessive voltage levels to enhance the quality of power but also include a detailed investigating of the various modulation methods and control schemes for multilevel inverter (MLI) topologies. Reduced harmonic modulation technology is used to produce 11-level output voltage with the production of renewable energy applications. The simulation is done in the MATLAB/Simulink for 11-level symmetric MLI and is correlated with the conventional inverter design.

This paper is focused on investigating the different types of asymmetric, symmetric and hybrid topologies and control methods used for the modular multilevel inverter (MMI) operation. Classical MLI configurations are affected by performance issues such as poor power quality, uneconomic structure and low efficiency.

The variations in both carrier and reference signals and their performance are analyzed for the proposed inverter topologies. The simulation result compares unipolar and bipolar pulse-width modulation (PWM) techniques with total harmonic distortion (THD) results. The solar-fed 11-level MMI is controlled using various modulation strategies, which are connected to marine emergency lighting loads. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by using SPARTAN 3A field programmable gate array (FPGA) board and the least harmonics are obtained by improving the power quality.

The simulation result compares unipolar and bipolar PWM techniques with THD results. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by a SPARTAN 3A field programmable gate array (FPGA) board, and the power quality is improved to achieve the lowest harmonics possible.

Sinusoidal gravity modulation fields imposed on two‐dimensional Rayleigh‐Benard convection flow are studied to understand the effects of periodic source (g‐jitter) on fluids system and heat transfer mechanism. The transient Navier‐Stokes and energy equations are solved by semi‐implicit operator splitting finite element method. Results include two sets. One is considered at normal terrestrial condition and the other one is related to low‐gravity condition. Under low‐gravity condition the research focuses on the effects of modulation frequency and direction in order to find out the critical frequency for heat transfer mechanism transferring from conduction to convection.

The purpose of this paper is to investigate the thermal convection inside a spatially modulated domain.

The governing equations are mapped onto an infinite strip, allowing Fourier expansion of the flow and temperature in the streamwise direction.

Similar to Rayleigh‐Benard convection, conduction is lost to convection at a critical Rayleigh number, which depends strongly on both the modulation amplitude and the wavenumber. The effect of modulation is found to be destabilizing (stabilizing) for conduction for relatively large (small) modulation wavelength. Oscillatory convection sets in as the Rayleigh number is increased.

This paper presents novel results.

The purpose of this paper is to propose a DC-port voltage balance strategy realizing it by logic combination modulation (LCM). This voltage balance strategy is brief and high efficient, which can be used in many power electronic devices adopting the cascaded H-bridge rectifier (CHBR) such as power electronic transformer (PET).

The CHBR is typically as a core component in the power electronic devices to implement the voltage or current conversion. The modulation method presented here is aiming to solve the voltage imbalance problem occurred in the CHBR with more stable work station and higher reliability in ordinary operating conditions. In particular, by changing the switch states smoothly and quickly, the DC-port voltage can be controlled as the ideal value even one of the modules in CHBR is facing the load-removed problem.

By using the voltage balance strategy of LCM, the problem of voltage imbalance occurring in three-phase cascaded rectifiers has been solved properly. With the lower modulation depth, the efficiency of the strategy is shown to be better and stronger. The strategy can work reliably and quickly no matter facing the problem as load-removed change or the ordinary operating conditions.

The limitation of the proposed DC-port voltage balance strategy is calculated and proved, in a three-module CHBR, the LCM could balance the DC-port voltage while one module facing the load-removed situation under 0.83 modulation depth.

This paper provides a useful and particular voltage balance strategy which can be used in the topology of three-phase cascaded rectifier. The value of the strategy is that a brief and reliable voltage balance method in the power electronic devices can be achieved. What is more, facing the problem, such as load-removed, in outport, the strategy can response quickly with no switch jump and switch frequency rising.

This paper presents and investigates a method named M×N‐ary chaotic pulse‐width‐position modulation (CPWPM) which is based on the combination of M‐ary chaotic pulse‐position modulation (CPPM) and N‐ary chaotic pulse‐width modulation (CPWM) in order to provide a better performance in noise‐affected environments as well as improve significantly bit rate.

Analysis of schemes for modulator and demodulator are presented in detail through describing the schemes of the individual methods and their combination. Theoretical evaluation of bit‐error rate (BER) performance in presence of additive white Gaussian noise (AWGN) is provided. Chaotic behavior with tent map in variation of modulation parameters is also investigated. In order to verify the theoretical analyses, numerical simulations are carried out and their results are reported.

Both evaluation and simulation results show that when the number of symbols increases, the bit rate is improved significantly but the BER performance is just slightly worse. This makes M×N‐ary CPWPM become an effective method for chaos‐based digital communication.

Although CPPM, CPWM and M‐ary modulation methods have been described in the literature separately, their combination is presented and investigated for the first time in this paper.