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Thermopile infrared (IR) detectors are one of the most important IR devices. Considering that the surface area of conventional four-end-beam (FEB)-based thermopile devices cannot be effectively used and the performance of this type of devices is relatively low, this paper aims to present a double-end-beam (DEB)-based thermopile device with high duty cycle and performance. The paper aims to discuss these issues.

Numerical analysis was conducted to show the advantages of the DEB-based thermopile devices.

Structural size of the DEB-based thermopiles may be further scaled down and maintain relatively higher responsivity and detectivity when compared with the FEB-based thermopiles. The authors characterized the thermoelectric properties of the device proposed in this paper, which achieves a responsivity of 1,151.14 V/W, a detectivity of 4.15 × 108 cm Hz1/2/W and a response time of 14.46 ms sensor based on DEB structure.

The paper proposed a micro electro mechanical systems (MEMS) thermopile infrared sensor based on double-end-beam structure.

Physical contact and traditional sensitive structure Physical contact and traditional pressure-sensitive structures typically do not operate well in harsh environments. This paper proposes a high-temperature pressure measurement system for wireless passive pressure sensors on the basis of inductively coupled LC resonant circuits.

This paper begins with a general introduction to the high-temperature pressure measurement system, which consists of a reader antenna inductively coupled to the sensor circuit, a readout unit and a heat insulation unit. The design and fabrication of the proposed measurement system are then described in detail.

A wireless passive pressure sensor without an air channel is fabricated using high-temperature co-fired ceramics (HTCC) technology and its signal is measured by the designed measurement system. The designed heat insulation unit keeps the reader antenna in a safe environment of 159.5°C when the passive sensor is located in a 900°C high-temperature zone continuously for 0.5 h. The proposed system can effectively detect the sensor’s resonance frequency variation in a high bandwidth from 1 to 100 MHz with a frequency resolution of 0.006 MHz, tested from room temperature to 500°C for 30 min.

Expensive and bulky equipment (impedance analyzers or network analyzers) restrict the use of the readout method outside the laboratory environment. This paper shows that a novel readout circuit can replace the laboratory equipment to demodulate the measured pressure by extracting the various sensors’ resonant frequency. The proposed measurement system realizes automatic and continuous pressure monitoring in a high-temperature environment with a coupled distance of 2.5 cm. The research finding is meaningful for the measurement of passive pressure sensors under a wide temperature range.

The purpose of this paper is to propose a pressure-, temperature- and acceleration-sensitive structure-integrated inductor-capacitor (LC) resonant ceramic sensor to fulfill the measurement of multi-parameters, such as the measurement of pressure, temperature and acceleration, simultaneously in automotive, aerospace and aeronautics industries.

The ceramic-based multi-parameter sensor was composed of three LC tanks, which have their resonant frequencies sensitive to pressure, temperature and acceleration separately. Two aspects from the specific sensitive structure design to the multiple signals reading technology are considered in designing the multi-parameter ceramic sensor. Theoretical analysis and ANSYS simulation are used in designing the sensitive structure, and MATLAB simulation and experiment are conducted to verify the feasibility of non-coverage of multi-readout signals.

It is found that if the parameters of sensitive structure and layout of the LC tanks integrated into the sensor are proper, the implementation of a multi-parameter sensor could be feasible.

The ceramic sensor proposed in the paper can measure pressure, temperature and acceleration simultaneously in harsh environments.

The paper creatively proposes a pressure-, temperature- and acceleration-sensitive structure-integrated LC resonant ceramic sensor for harsh environments and verifies the feasibility of the sensor from sensitive structure design to multiple-signal reading.

The paper aims to highlight a wireless pressure-sensitive micro-device with high pressure sensitivity and accuracy. It is based on the partially stabilized Zirconia (PSZ) ceramic material which is capable of excellent elasticity and robustness.

The paper begins with a general introduction to the wireless interrogating method and then the fabrication processes of the device using high temperature co-fired ceramic (HTCC) technology are described in detail.

A passive wireless micro-device made from a novel material-PSZ ceramic on pressure monitoring is fabricated and tested and the authors proved that the device possesses an advantages over some proposed wireless sensors on interrogating distance. The pressure sensitivity of the device is 336 kHz/bar at readout distance 2.5 cm and that is an excellent property.

The paper shows a new design scheme for wireless pressure measurement. The future application of the wireless device indicates the problem on external packaging and wire connection could be avoided. The allowable interrogation distance between the device and readout circuit reaches 2.5 cm which is mentioned for the first time so far. The distance is long enough to insert a thermal insulation material which can protect the vulnerable readout circuit from harsh environment, so the research finding is meaningful for the modern measurement technology.

The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred boundaries and edema around the brain tumor region, the brain tumor image has indistinct features in the tumor region, which pose a problem for diagnostics. The paper aims to discuss these issues.

In this paper, the authors propose an original solution for segmentation using Tamura Texture and ensemble Support Vector Machine (SVM) structure. In the proposed technique, 124 features of each voxel are extracted, including Tamura texture features and grayscale features. Then, these features are ranked using the SVM-Recursive Feature Elimination method, which is also adopted to optimize the parameters of the Radial Basis Function kernel of SVMs. Finally, the bagging random sampling method is utilized to construct the ensemble SVM classifier based on a weighted voting mechanism to classify the types of voxel.

The experiments are conducted over a sample data set to be called BraTS2015. The experiments demonstrate that Tamura texture is very useful in the segmentation of brain tumors, especially the feature of line-likeness. The superior performance of the proposed ensemble SVM classifier is demonstrated by comparison with single SVM classifiers as well as other methods.

The authors propose an original solution for segmentation using Tamura Texture and ensemble SVM structure.

In this paper, considering a tradeoff between consumers comfort and energy efficiency, a multi-period joint energy scheduling algorithm (MPJ-ESA) based on prediction of residents energy consumption is proposed, which includes long-period preliminary sch eduling, short-period preliminary scheduling, and real-time fine-tuning scheduling. First, by analyzing historical data of energy consumption, preferred usage profile of consumers is inferred, and the dynamic comfort level is presented. Then the paper uses the wavelet neural networks (WNNs) prediction algorithm to predict the operation of the appliances which are classified into appliances with unschedulable mode and schedulable mode. Based on the energy consumption prediction and dynamic comfort level, home appliances running state are scheduled according to the prediction of renewable energy available amount and real-time pricing (RTP). The simulation results show that scheduling algorithm effectively improves the energy efficiency and enhances user satisfaction with the operation of scheduled appliances and let the consumers comfort and energy efficiency achieve a better tradeoff.

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues.

First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives.

This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective.

This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value.

Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.

The importance of Carbon dioxide (CO₂) gas detection as a greenhouse and exhale breathe gas is an undeniable issue. This study aims to propose a new miniaturized, low cost and portable no dispersive infrared (NDIR) system for detecting CO₂ gas.

Poly(methyl methacrylate) (PMMA)-based channels with Au coating because of its high reflection properties in IR region were used in this work. The optical windows were fabricated using PDMS polymer which is cost effective and novel in comparison to other conventional methods. The effects of channel dimensions, lengths and entrance angle of light on optical path length and losses were analyzed with four types of channel using both simulation and experimental tests.

The simulation results indicate that the 0 degree light entrance angle is the most efficient angle among different investigated conditions. The experimental data are in agreement with the simulation results regarding the loss and optical path length in different types of channel. The experimental tests were performed for the 0.5% up to 20% of CO₂ concentration under constant temperature and humidity condition. The results show that the device with 5  and 2 cm channels length were saturated in 4% and 8% concentration of CO₂ gas, respectively. Response and recovery times were depending on gas concentration and channels specifications that in average found to be 10 S and 14 S, respectively, for the largest size channel. Moreover, the environment humidity effect on detection system performance was investigated which had no considerable influence. Also, the saturation fraction absorbance value for devices with various dimensions were 0.62 and 0.8, respectively.

According to the performed curve fitting for practical situation and selected CO₂ concentration range for experimental tests, the device is useful for medical and environmental applications.

PMMA with Au deposition layer was used as a basic material for this NDIR system. Besides, a novel PDMS optical window helps to have a low cost device. The effects of channel dimensions, lengths and entrance angle of light on optical path length and losses were analyzed using both simulation and experimental tests. Using narrowband optical filter (100 nm bandwidth) helps to have a system with good CO₂ selectivity. In addition, experimental tests with different channel dimensions and lengths covered a considerable range of CO₂ concentration useful for medical and environmental applications. Finally, curve fitting was adopted for a modified Beer–Lambert law as a practical situation.