Microwave dielectric properties of low loss microwave dielectric ceramics: A0.5Ti0.5NbO4 (A = Zn,Co)

The microwave dielectric properties of low-loss A_0.5Ti_0.5NbO₄ (A = Zn, Co) ceramics prepared by the solid-state route had been investigated. The influence of various sintering conditions on microwave dielectric properties and the structure for A_0.5Ti_0.5NbO₄ (A = Zn, Co) ceramics were discussed systematically. The Zn_0.5Ti_0.5NbO₄ ceramic (hereafter referred to as ZTN) showed the excellent dielectric properties, with ɛ_r = 37.4, Q × f = 194,000 (GHz), and τ_f = −58 ppm/°C and Co_0.5Ti_0.5NbO₄ ceramic (hereafter referred to as CTN) had ɛ_r = 64, Q × f = 65,300 (GHz), and τ_f = 223.2 ppm/°C as sintered individually at 1100 and 1120 °C for 6 h. The dielectric constant was dependent on the ionic polarizability. The Q × f and τ_f are related to the packing fraction and oxygen bond valence of the compounds. Considering the extremely low dielectric loss, A_0.5Ti_0.5NbO₄ (A = Zn and Co) ceramics could be good candidates for microwave or millimeter wave device application.     

提高感应无线位置检测分辨率的方法

感应无线位置检测技术已经广泛应用于工业机车自动化,机车全自动无人操作的精确定位,要求进一步提高位置检测分辨率。文中以感应无线车上位置检测技术为研究对象,对应用中影响检测分辨率的原因进行了分析。提出了提高检测分辨率的方法:设计一种独特的感应线圈结构,采用具有抑制干扰能力副线圈检测精密位置,并且在编码电缆的交叉处采用同一信号参数计算一般位置与精密位置而消除内部串扰的影响。实验结果表明所述方法对提高检测分辨率有明显效果。     

C波段高稳定度磁控管微波源实验研究

由于物理机制和工艺结构的固有限制,各种微波源均有其功率极限,而以锁相技术为基础的功率合成技术是获得大功率微波的一条重要途径。主要研究了以磁控管为基本单元的注入式锁相方案,并且采用注入锁相方法对现有的c波段磁控管进行了锁相实验验证,研制出频率、相位、幅度可调的高稳定度磁控管微波源,并结合实验分析了系统的性能指标。     

差分振子时间历程在微弱调制信号检测中的应用

单一的差分振子仅可实现对周期信号中某一频率成分进行检测,对于强噪声背景下的边频带,尽管可以利用多个差分振子组成差分阵列进行逐个检测,进而确定边频带的间隔,但这种做法无疑会带来巨大的计算量。在对调制信号进行Hilbert变换包络分析时,所得到的时域信号是原始调制信号中的低频分量,亦是调制波信号,若该低频分量仍然包含较强的噪声成分,传统的频谱分析将会失效。此时,我们可借助差分振子时间历程对含较强的噪声的包络进行检测。因此,提出基于差分振子时间历程的微弱调制信号检测方法,即首先对信号进行Hilbert包络解调,然后利用差分振子时间历程对含较强的噪声的幅值包络进行检测,并成功应用于风机早期故障检测中。     

Photo-controlled redox of hydrogen-terminated silicon nanowire established by the reversible color alteration of methylene blue

The surface of hydrogen-terminated silicon nanowires was proved to be photo-active and redox-controllable under a visible light by the color alteration of methylene blue: colorless in dark and blue in light in the presence of H-SiNWs. The process of the redox reaction was monitored by a UV–vis spectrophotometry, showing a repeatable interconversion between methylene blue and lueco methylene blue within 2 h under conditions of alternant dark and light environments. During the redox process, oxygen was proved necessary for the reversible color alteration of methylene blue. The high repeatability in dark-reduction and photo-oxidation of methylene blue demonstrates the catalytic activity of ultrafine hydrogen-terminated silicon nanowires. Finally, a possible mechanism is deduced.     

Localization for mobile target in wireless sensor networks

A precise localization for mobile target in wireless sensor networks is presented in this letter,where a geometrical relationship is explored to improve the location estimation for mobile target,instead of a simple centroid approach.The equations of location compensation algorithm for mobile target are derived based on linear trajectory prediction and sensor selective activation.The results based on extensive simulation experiments show that the compensation algorithm gets better performance in metrics of quality of tracking and energy efficiency with the change of sensor sensing range,the ratio of sensing range and sensor activation range,and the data sampling rate than traditional methods,which means our proposing can achieve better quality-energy tradeoff for mobile target in wireless sensor networks.     

Optimum operating conditions of a solar cell panel and prediction of solar radiation in Sanaa,Yemen

The performance of a solar cell panel is evaluated under the actual conditions prevailing in Sanna, Yemen. The availability of solar energy is predicted using an empirical formula (with the number of hours of sunshine as an input). The results agree with measurements made using a pyranometer over a period of 1 year with a deviation of less than 10% and reveal a high annual insolation in Sanaa.The power output of the panel is linearly dependent on the solar irradiation and on the total cell conversion efficiency. The total cell conversion efficiency is highly sensitive to variation in temperature. A drop of 4% in the efficiency was detected at midday temperatures. If the panel is tilted towards the Equator in the winter months, the power output can be increased by 16%. For such a low latitude (15°N) the angle of tilt may be fixed in order to simplify construction and to reduce costs.An estimate is given of the active cell area requered to supply an energy of 1 kW h.     

Optimizing Polynomial-Time Solutions to a Network Weighted Vertex Cover Game

Weighted vertex cover (WVC) is one of the most important combinatorial optimization problems. In this paper, we provide a new game optimization to achieve efficiency and time of solutions for the WVC problem of weighted networks. We first model the WVC problem as a general game on weighted networks. Under the framework of a game, we newly define several cover states to describe the WVC problem. Moreover, we reveal the relationship among these cover states of the weighted network and the strict Nash equilibriums (SNEs) of the game. Then, we propose a game-based asynchronous algorithm (GAA), which can theoretically guarantee that all cover states of vertices converging in an SNE with polynomial time. Subsequently, we improve the GAA by adding 2-hop and 3-hop adjustment mechanisms, termed the improved game-based asynchronous algorithm (IGAA), in which we prove that it can obtain a better solution to the WVC problem than using a the GAA. Finally, numerical simulations demonstrate that the proposed IGAA can obtain a better approximate solution in promising computation time compared with the existing representative algorithms.      

Pd–La0.6Sr0.4Co0.2Fe0.8O3–δ composite as active and stable oxygen electrode for reversible solid oxide cells

To promote the electrocatalytic activity and stability of traditional La_0.6Sr_0.4Co_0.2Fe_0.8O_3–δ (LSCF) oxygen electrodes in reversible solid oxide cells (RSOCs), conventional physical mixed method was used to prepare the Pd-LSCF composite oxygen electrode. The cell with Pd-LSCF|GDC|YSZ|Ni-YSZ configuration shows perfect electrochemical performance in both solid oxide fuel cell (SOFC) mode and solid oxide electrolysis cell (SOEC) mode. In the SOFC mode, the cell achieves a power density of 1.73 W/cm² at 800 °C, higher than that of the LSCF oxygen electrode with 1.38 W/cm². In the SOEC mode, the current density at 1.5 V is 1.67 A/cm² at 800 °C under 50 vol% steam concentration. Moreover, the reversibility and stability of the RSOCs were tested during 192 h long-term reversible operation. The degradation rate of the cell is only 2.2%/100 h and 2.5%/100 h in the SOEC and the SOFC modes, respectively. These results confirm that compositing Pd with the LSCF oxygen electrode can considerably boost the electrochemical performance of LSCF electrode in RSOCs field.     

Application of machine learning algorithms for predicting the engine characteristics of a wheat germ oil–Hydrogen fuelled dual fuel engine

In this research work, performance and emission parameters of wheat germ oil (WGO) -hydrogen dual fuel was investigated experimentally and these parameters were predicted using different machine learning algorithms. Initially, hydrogen injection with 5%, 10% and 15% energy share were used as the dual fuel strategy with WGO. For WGO +15% hydrogen energy share the NO emission is 1089 ppm, which is nearly 33% higher than WGO at full load. As hydrogen has higher flame speed and calorific value and wider flammability limit which increases the combustion temperature. Thus, the reaction between nitrogen and oxygen increases thereby forming more NO. Smoke emission for WGO +15% hydrogen energy share is 66%, which is 15% lower compared to WGO, since the heat released in the pre-mixed phase of combustion is increased to a maximum with higher hydrogen energy share compared to WGO. Different applications including internal combustion engines have used machine learning approaches for predictions and classifications. In the second phase various machine learning techniques namely Decision Tree (DT), Random Forest (RF), Multiple Linear Regression (MLR), and Support Vector Machines (SVM)) were used to predict the emission characteristics of the engine operating in dual fuel mode. The machine learning models were trained and tested using the experimental data. The most effective model was identified using performance metrics like R-Squared (R²) value, Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The result shows that the prediction by MLR model was closest to the experimental results.