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Environmentally-friendly polymers which can be recycled and reused at the end of life are urgently needed for the development of advanced high-voltage direct current (HVDC) systems. Polymer nanocomposites have attracted considerable attention owing to their unique features arising from synergistic combination of inorganic fillers and polymer matrices. Here we describe thermoplastic poly(ether imide) (PEI) nanocomposites that contain boron nitride nanosheets (BNNSs). It is found that the polymer nanocomposites exhibit simultaneous improvements in multiple physical properties, such as the DC electrical breakdown strength, volume resistivity, mechanical strength and thermal stability, along with substantial reduction in loss tangent, compared with neat PEI. A great improvement in thermal conductivity has been attributed to the presence of BNNSs in the composites, which improves heat dissipation in comparison with neat polymers. The composite approach provides a promising solution for alleviating temperature-gradient distribution and addressing heat accumulation issues in HVDC equipment, and enables broader applications of insulation materials in HVDC systems operated under high voltages.

This paper shows time-asymptotic nonlinear stability and existence of the viscous shock profiles to the Cauchy problem of the one-dimensional compressible planar magnetohydrodynamics system, which describes the motions of a conducting fluid in an electro-magnetohydrodynamics system. We can prove that the solutions to the compressible planar magnetohydrodynamics system tend time-asymptotically to the viscous shock profiles provided that the initial disturbance is small and of integral zero.

This paper presents a single-trial evoked potential (EP) estimation method based on an autoregressive model with exogenous input modeling and sparse coding. This method uses sparse coding instead of the autoregressive-moving-average model to model EPs, as the former is more flexible. The best matching atoms from the dictionary are used to represent the EP signal without needing to estimate the number of atoms beforehand. By transforming the electroencephalography signal into white noise, the single-trial EP estimation is transformed into a signal denoising problem for white noise. With the dictionary constructed specially for EPs, the EP signal can be extracted easily with sparse coding. Moreover, since the location of the atom in the dictionary has no influence on the effectiveness of sparse decomposition, variations of the amplitude and latency of EPs have only a minor impact on the performance of the proposed method. The proposed method can thus track EP signal variations. Experimental results also demonstrate that this method is effective.

Sparse representation is a powerful tool in signal denoising, and visual evoked potentials (VEPs) have been proven to have strong sparsity over an appropriate dictionary. Inspired by this idea, we present in this paper a novel sparse representation-based approach to solving the VEP extraction problem. The extraction process is performed in three stages. First, instead of using the mixed signals containing the electroencephalogram (EEG) and VEPs, we utilise an EEG from a previous trial, which did not contain VEPs, to identify the parameters of the EEG autoregressive (AR) model. Second, instead of the moving average (MA) model, sparse representation is used to model the VEPs in the autoregressive-moving average (ARMA) model. Finally, we calculate the sparse coefficients and derive VEPs by using the AR model. Next, we tested the performance of the proposed algorithm with synthetic and real data, after which we compared the results with that of an AR model with exogenous input modelling and a mixed overcomplete dictionary-based sparse component decomposition method. Utilising the synthetic data, the algorithms are then employed to estimate the latencies of P100 of the VEPs corrupted by added simulated EEG at different signal-to-noise ratio (SNR) values. The validations demonstrate that our method can well preserve the details of the VEPs for latency estimation, even in low SNR environments.

This paper presents the design and characterization of a turbidity transducer, intended for measuring water turbidity in distributed measurement system (DMS). The design of the transducer based on IEEE 1451 standard focus on the networking capability in distributed measurement applications. The design of Smart Transducers Interface Module (STIM), Transducers Electronic Data Sheets (TEDS), self-recognition of STIM and temperature self-compensating are presented. The electrical characterization and fabrication of the transducer are also investigated. The Transducer Independent Interface (TII) has been replaced with a more conventional and widely used RS-485. The turbidity transducer proposed suitable for continuous monitoring of water turbidity, and the prototype developed is appropriate for turbidity measurement in the range of 0–100 NTU. The transducer described here has the characteristics of good linearity, high reproducibility, high accuracy, low power dissipation and no significant temperature effect on the turbidity transducer.

Aquaculture is the fastest growing food-producing sector in the World, especially, in P. R. China. In the ongoing process of Internet growth, a new development is on its way, namely the evolution from a network of interconnected computers to a network of interconnected objects that is called the Internet of Things (IoT). Constructing an affordable, easy-to-use, aquaculture information system based on IoT is the future trend for modern aquaculture. The prototype IoT of aquaculture information system is developed with following functions: (1) Sense in real time the water quality in aquaculture ponds and send water quality data in time to remote IoT Platform with wireless sensor network and mobile internet; (2) Forecast the change trend of water quality based real-time data and operating suggestion will be created for special aquaculture application automatically; (3) Real-time and efficient exchange with special users and common users with WEB, WAP and SMS; (4) Some control devices may be operated ...

Because of the rapid development of aquaculture in China at present, it is more and more urgent to apply hi-tech devices in aquaculture field to guarantee its efficiency. There are already many devices used for monitoring water quality have been developed. However, many of them are only in a step of academic research or too expensive to apply to practices. In this paper, a multi-parameter integrated water quality sensors system which has a practical value based on self-contained design is introduced and the hardware and software of this system are researched and discussed. A test conducted at Taihu Lake in Jiangsu province, China shows that this system can perform well. And this system has many features such as low cost, low consumption, multi-parameter and real-time data upload. The features and good performance above suggest the practical and potential application of the system in water monitoring. And this system still has much space to improve. It may become lighter, more integrated, and more portable in the future.

International audience; Conductivity is regard as a key technical parameter in modern intensive fish farming management. The water conductivity sensors are sophisticated devices used in the aquaculture monitoring field to understand the effects of climate changes on fish ponds. In this paper a new four-electrode smart sensor is proposed for water conductivity measurements of aquaculture monitoring.The main advantages of these sensors include a high precision, a good stability and an intrinsic capability to minimize errors caused by polarization. A temperature sensor is also included in the system to measure the water temperature and, thus, compensate the water-conductivity temperature dependence. The prototype developed is appropriate for conductivity measurement in the range of 0-50mS/cm, 0-40 ℃. A cure relationship was found between the out-put value of each standard solution measured by the sensor and the electric conductivity concentration.

Chlorophyll-a was regarded as the important indicator to describe the marine primary production because the chlorophyll a content of phytoplankton in the ocean is related to its photosynthesis production. The concentration of chlorophyll a is also the major parameter to evaluate marine water quality, organic pollution and detect the fishing ground, and the temporal and spatial variation of chlorophyll a contains the basic information of sea areas. Based on the spectral characteristics of chlorophyll fluorescence, this document recommends a new dual optical detecting instrument for the measurement of chlorophyll-a concentration, the microcontroller MSP430F149 as the key control module, by controlling the ultra-high brightness LED which wavelength is 450nm to excite chlorophyll a to produce the fluorescent signal about 680nm , at the same time this LED is used as reference light, the dual-optical structure exclude the light fluctuations due to the impact of test results. At last, we get the relationship between relative fluorescence intensity and chlorophyll-a concentration with the spectrophotometer, we find the system has the good linear consistency when measures the low concentrations of chlorophyll-a.

This paper presents a system framework taking the advantages of the WSN for the real-time monitoring on the water quality in aquaculture. We design the structure of the wireless sensor network to collect and continuously transmit data to the monitoring software. Then we accomplish the configuration model in the software that enhances the reuse and facility of the monitoring project. Moreover, the monitoring software developed to represent the monitoring hardware and data visualization, and analyze the data with expert knowledge to implement the auto control. The monitoring system has been realization of the digital, intelligent, and effectively ensures the quality of aquaculture water. Practical deployment results are to show the system reliability and real-time characteristics, and to display good effect on environmental monitoring of water quality.

Turbidity sensor for water treatment applications are based on scattered light measurement. The electrooptical characteristic of light emitter and detector has a close relationship with the environmental temperature. Fluctuations in water temperature can potentially affect electronic components and cause output signal errors in turbidity sensor. Decrease or eliminate temperature error is necessary. With this background we have taken the temperature experiment of turbidity sensor developed by us. 11 different concentrations were measured, ranging from 0 to 100NTU. Each solution was cooled to 1°C, and then gradually heated to 40°C. The output signal of sensor increased according to the rise of temperature found from the experiment. In order to compensate the temperature errors, we developed a novel method to take temperature compensation by using software. The method carried by MCU which is used to compensate the measurement errors by soft programming is simple and effective; it can improve the error compensation precision on sensors greatly.

Automatic monitoring and controlling system is essential for improvement of aquaculture industry. This paper presents an intelligent PH sensor that applied to water quality monitoring. It involved signal processing, self-calibration. Using low power and high performance microcontroller MSP430F149, Smart Transducer Interface Module (STIM) based on IEEE1451standard was embedded. The design of software and hardware was described in detail, and an initial calibration experiment was carried out to establish a calibration parameter. The results indicate that the pH sensor is more accurate, reliable and easy to use, which is suitable to spread the application in aquaculture industry.

Based on the problems caused by current automatic irrigation system with a large number of cables, such as installation, maintenance, and difficult expansion, this paper proposed a wireless integrated irrigation control system and developed a wireless intelligent valve controller which can satisfy the requirements for agricultural irrigation in our country. The controller consisted of the control unit, power unit, wireless communication unit, relay boost driver unit, state feedback switch, etc. It received the control command from the remote control center by the wireless communication unit, actuated the relay boost driver unit to turn on/off irrigation solenoid valves. The controller includes the functions of remote control, parameter setting, feedback status detecting, etc. Since the rational design, simple command, and low cost, the controllers have been pilot in Beijing and Xinjiang. The results indicate that the controller is effective in practice and can be used a normal irrigation season.

An intelligent conductivity meter based on MSP430F149 microcontroller was proposed in this paper. The intelligent conductive meter was composed by MSP430F149 microcontroller and its peripheral circuits, bipolar pulse excitation circuit and waveform transform circuit. The MSP430F149 was chosen to control the generation of bipolar pulse excitation signal and take temperature compensation. It adopted bipolar pulse excitation signal to avoid the electrode polarization effects. The measurement error generated by the solution temperature fluctuation could be amended by the temperature compensation. It could self- compensation and self-tuning to fit variance solution.