Miniaturized wideband dual linearly and circularly polarized printed square slot antenna for multiradio wireless systems

A dual symmetrical coplanar waveguide (CPW)-fed small size wideband printed square slot antenna (SSA) with dual linearly and circularly polarized radiation capability is presented. The antenna is composed using a square slot, two symmetrical orthogonal CPW feed lines connected to horizontal and vertical arm of L-shaped radiator, an embedded parasitic inverted-L strip at the lower left corner of the square ground slot and engraving slots in the ground plane. Circular polarization (CP) is achieved due to two orthogonal CPW feed lines and a common L-shaped radiator. Isolation between ports is improved by engraving slots at the lower left corner of ground plane and embedded parasitic inverted-L strip. The sense of dual-polarization can be changed in pass-band by changing the port excitation. Measured antenna reveals that an 84.4% (4.6 GHz, 3.15–7.75 GHz) −10 dB impedance bandwidth (IBW) and about 33% (2.03 GHz, 5.12–7.15 GHz) 3-dB axial ratio bandwidth (ARBW). Isolation between ports <−16 dB is achieved over usable CP band.     

Integrated well pad development scheduling with steam injection control in steam-assisted gravity drainage

In this paper, we study the problem of integrated well pad development scheduling with nonlinear model predictive control based steam injection in steam-assisted gravity drainage (SAGD). The scheduling problem has been modeled as a mixed-integer program to find optimal development sequence and timing of multiple well-pads. Model predictive control problems are solved to find optimal steam injection profile such that the reservoir is under control. The integrated problem is solved using open-loop and closed-loop methods: (1) scheduling problem is only solved at the beginning of project operation, (2) Scheduling problem is solved every year with shrinking horizon implementation, and (3) shrinking horizon implementation of scheduling with reservoir model update based on feedback from control level. Simulation results demonstrate the benefits of closed-loop integrated scheduling and control: the NPV increase is 19%.     

Prescribed performance adaptive DSC for a class of time-delayed switched nonlinear systems in nonstrict-feedback form: Application to a two-stage chemical reactor

This study deals with the tracking problem for a class of nonstrict-feedback switched nonlinear systems (SNSs) with unknown time-delay and unknown functions under arbitrary switching. To achieve this goal, an adaptive neural network-based dynamic surface control (DSC) based on backstepping approach is proposed. A neural network (NN) approximator based on radial basis functions (RBFs) is utilized to approximate unknown functions. Considering properties of Gaussian basis function in RBFNNs, an adaptive neural network DSC for nonstrict-feedback structure has been developed. A Lyapunov-krasovskii functional is applied to compensate the effect of unknown delay terms. Furthermore, a prescribed performance bound (PPB) control strategy is utilized to retain the tracking error within a predefined bound. Finally, a practical example is provided to prove the effectiveness of the proposed method.     

均衡单进化布谷鸟算法

针对布谷鸟算法采用整体评价策略处理多维度自变量相关优化问题时,维度耦合现象会恶化算法的搜索速度和收敛精度,提出均衡单进化的布谷鸟算法（ESCES）.该算法给出一种新型的均衡单进化函数评价策略,即每一代进化只随机更新目标函数的单个维度,并且随机更新的维度服从均匀分布,避免多维度之间互相干扰.同时,提出两种新型随机游动步长更新学习律,提高了优化算法的全局搜索速度和收敛精度.实验测试结果和显著性统计结果表明,ESCES算法与5个改进CS算法及7个其它最新智能优化算法相比,在全局寻优性能、搜索速度和收敛精度上均获得较大的改进.     

A Steganography Based on Optimal Multi-Threshold Block Labeling

Hiding secret data in digital images is one of the major research fields in information security. Recently, reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services. This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique (OMTBL-RDHEI). In our scheme, the content owner encrypts the cover image with block permutation, pixel permutation, and stream cipher, which preserve the in-block correlation of pixel values. After uploading to the cloud service, the data hider applies the prediction error rearrangement (PER), the optimal threshold selection (OTS), and the multi-threshold labeling (MTL) methods to obtain a compressed version of the encrypted image and embed secret data into the vacated room. The receiver can extract the secret, restore the cover image, or do both according to his/her granted authority. The proposed MTL labels blocks of the encrypted image with a list of threshold values which is optimized with OTS based on the features of the current image. Experimental results show that labeling image blocks with the optimized threshold list can efficiently enlarge the amount of vacated room and thus improve the embedding capacity of an encrypted cover image. Security level of the proposed scheme is analyzed and the embedding capacity is compared with state-of-the-art schemes. Both are concluded with satisfactory performance.     

基于事件触发的三阶离散多智能体系统一致性分析

研究了基于事件触发控制的三阶离散多智能体系统的一致性问题.首先,基于位置、速度和加速度三者的测量误差,设计了一个新颖的事件触发控制机制.然后,利用不等式技巧,得到了使离散多智能体系统达到一致的充分条件.所得到的条件揭示了系统的通信拓扑的Laplacian矩阵特征值和耦合强度对于系统一致性的影响.此外,还给出了事件触发控制器排除类Zeno行为的确定条件,这意味着事件触发控制器不会每个迭代时刻都更新.最后,通过仿真实验验证了所获得理论结果的正确性和可用性     

H2O treatment-induced uniform NiOX interfacial layer boosting brightness and light-emitting efficiency of blue perovskite electroluminescence

The reported NiO_x interfacial layers in blue perovskite light-emitting diodes (PeLEDs) usually require high-temperature annealing and complex interface modification. Herein, we report a kind of uniform NiO_x anode interfacial layer induced by H₂O treatment, which effectively enhances the brightness and light-emitting efficiency of blue PeLEDs simultaneously. Compared to the as-prepared NiO_x anode interfacial layer, H₂O treatment renders uniform and pinhole-free NiO_x morphology. The solution-processed perovskite blue emissive layer prepared atop the H₂O-treated NiO_x interfacial layer demonstrates enhanced photoluminescent property and superior morphology with low trap density. The blue PeLEDs employing H₂O-treated NiO_x as anode interfacial layer show a maximum luminance of 9052 cd/m² and a maximum external quantum efficiency (EQE) of 1.80%, whereas the control device based on the as-prepared NiO_x anode interfacial layer merely exhibits a maximum luminance of 3850 cd/m² and an EQE of 0.88%, leading to about 135% and 104% increase in brightness and efficiency, respectively. The PeLEDs emit pure blue light with emission peak located at 482 nm and demonstrate superior spectral stability under different driving voltages and operating time.     

Enhanced performance of spectra stable blue perovskite light-emitting diodes through Poly(9-vinylcarbazole) interlayer incorporation

Since the emergence of organic-inorganic hybrid perovskites, the development of perovskite light-emitting diodes (PeLEDs) with green/red emission have made great progress, and the corresponding external quantum efficiency (EQE) has exceeded 20%. However, the research progress of blue-emitting PeLED still has certain challenges. In this article, a multi-cation per-bromine perovskite film is prepared by introducing polymer molecules poly(9-vinylcarbazole) (PVK) in an anti-solvent (chloroform). When the concentration of PVK is optimized to 0.1 mg/mL, a smooth, dense, high-quality film with photoluminescence quantum efficiency (PLQY) up to 20.70% is obtained. The introduction of PVK can assist the formation of perovskite films for interface modification via surface defect passivation. The optimized blue PeLED has a maximum brightness of 3136 cd/m² and a maximum EQE of 3.49% at 488 nm. More importantly, the optimized blue PeLED has excellent color stability under high applied voltage up to 12 V or continuous operation.     

基于面向对象时间Petri网的智能电商物流服务系统建模

电商物流服务系统是一种集商流、物流、信息流和资金流于一体的大规模复杂系统,具有离散事件动态系统的一般特征。将面向对象技术与Petri网相结合,引入时间因素,应用于大规模复杂信息系统建模上,不仅能降低系统模型复杂度,还可以针对模块性能做定量分析。在分析研究电商物流服务系统主要功能和Petri网理论的基础上,给出了一种面向对象时间Petri网（OOTPN）的形式定义,描述了电商物流服务系统的主要对象和业务流程,采用面向对象时间Petri网构建了电商物流服务系统的OOTPN模型,分析了子网的相关时间特性,利用可覆盖性树、关联矩阵对子网的可达性、有界性、守恒性等性质进行了分析,证明了模型系统的可靠性和健壮性,体现了OOTPN模型具有模块化、图形化、结构化特点和可扩展、可重用、易于维护等特性。     

Performance analysis of classification algorithms on early detection of liver disease

The human liver is one of the major organs in the body and liver disease can cause many problems in human life. Fast and accurate prediction of liver disease allows early and effective treatments. In this regard, various data mining techniques help in better prediction of this disease. Because of the importance of liver disease and increase the number of people who suffer from this disease, we studied on liver disease through using two well-known methods in data mining area.In this paper, novel decision tree based algorithms is used which leads to considering more factors in general and predictions with high accuracy compared to other studies in liver disease. In this application, 583 UCI instances of liver disease dataset from the UCI repository are considered. This dataset consists of 416 records of liver disease and 167 records of healthy liver. This dataset is analyzed by two algorithms named Boosted C5.0 and CHAID algorithms. Until now there is no work in the literature that uses boosted C5.0 and CHAID for creating the rules in liver disease. Our results show that in both algorithms, the DB, ALB, SGPT, TB and A/G factors have a significant impact on predicting liver disease which according to the rules generated by both algorithms important ranges are DB = [10.900–1.200], ALB [4.00–4.300], SGPT = [34–37], TB = [0.600–1.200] (by boosted C5.0), A/G = [1.180–1.390], as well as in the Boosted C5.0 algorithm, Alkphos, SGOT and Age have significant impact in prediction of liver disease. By comparing the performance of these algorithms, it becomes clear that C5.0 algorithm via Boosting technique has an accuracy of 93.75% and this result reveals that it has a better performance than the CHAID algorithm which is 65.00%. Another important achievement of this paper is about the ability of both algorithms to produce rules in one class for liver disease. The results of our assessment show that Boosted C5.0 and CHAID algorithms are capable to produce rules for liver disease. Our results also show that boosted C5.0 considers the gender in liver disease, a factor which is missing in many other studies. Meanwhile, using the rules generated in boosted C5.0 algorithm, we obtained the important result about low susceptibility of female to liver disease than male. This factor is missing in other studies of liver disease. Therefore, our proposed computer-aided diagnostic methods as an expert and intelligent system have impressive impact on liver disease detection. Based on obtained results, we observed that our model had better performance compared to existing methods in the literature.