蒲石河抽水蓄能电站输水系统充排水试验方法

高水头大型抽水蓄能电站输水系统的充水和排水,是电站投入运行不可缺少的一项安全检验,初期充排水试验是加载、卸载、检查、监测、发现问题和处理缺陷的过程,为今后电站正式运行提供安全可靠的质量保证。本文详细介绍了辽宁蒲石河抽水蓄能电站输水系统充排水试验方法,可供类似工程参考。     

Time series forecasting with a neuro-fuzzy modeling scheme

Time series forecasting concerns the prediction of future values based on the observations previously taken at equally spaced time points. Statistical methods have been extensively applied in the forecasting community for the past decades. Recently, machine learning techniques have drawn attention and useful forecasting systems based on these techniques have been developed. In this paper, we propose an approach based on neuro-fuzzy modeling for time series prediction. Given a predicting sequence, the local context of the sequence is located in the series of the observed data. Proper lags of relevant variables are selected and training patterns are extracted. Based on the extracted training patterns, a set of TSK fuzzy rules are constructed and the parameters involved in the rules are refined by a hybrid learning algorithm. The refined fuzzy rules are then used for prediction. Our approach has several advantages. It can produce adaptive forecasting models. It works for univariate and multivariate prediction. It also works for one-step as well as multi-step prediction. Several experiments are conducted to demonstrate the effectiveness of the proposed approach.     

Rational Design of Polymeric Hybrid Micelles with Highly Tunable Properties to Co‐Deliver MicroRNA‐34a and Vismodegib for Melanoma Therapy

A polymeric hybrid micelle (PHM) system with highly tunable properties is reported to co‐deliver small molecule and nucleic acid drugs for cancer therapy; this system is structurally simple and easy‐to‐fabricate. The PHM consists of two amphiphilic diblock copolymers, polycaprolactone‐polyethylenimine (PCL‐PEI) and polycaprolactone‐polyethyleneglycol (PCL‐PEG). PHMs are rationally designed with different physicochemical properties by simply adjusting the ratio of the two diblock copolymers and the near neutral PHM‐2 containing a low ratio of PCL‐PEI achieves the optimal balance between high tumor distribution and subsequent cellular uptake after intravenous injection. Encapsulating Hedgehog (Hh) pathway inhibitor vismodegib (VIS) and microRNA‐34a (miR‐34a) into PHM‐2 generates the VIS/PHM‐2/34a co‐delivery system. VIS/PHM‐2/34a shows synergistic anticancer efficacy in murine B16F10‐CD44⁺ cells, a highly metastatic tumor model of melanoma. VIS/PHM‐2/34a synergistically attenuates the expression of CD44, a vital receptor indicating the metastasis of melanoma. Intriguingly, inhibiting Hh pathway by VIS is accompanied by downregulation of CD44 expression, revealing that Hh signaling might be an upstream regulator of CD44 expression in melanoma. Thus, co‐delivery of miR‐34a and VIS demonstrates great potential in cancer therapy, and PHM offers a structurally simple and highly tunable platform for the co‐delivery of small molecule and nucleic acid drugs in tumor combination therapy.     

Formulation of solid self-nanoemulsifying drug delivery systems using N-methyl pyrrolidone as cosolvent

Atorvastatin calcium (ATRC) is a poor water soluble drug used for treatment of hypercholesterolemia. This research is aimed to improve solubility and dissolution rate of ATRC by formulating into solid self-nanoemulsifying drug delivery system (S-SNEDDS) using N-methyl pyrrolidone (NMP) as cosolvent. Solubility of ATRC was determined in various vehicles. Ternary phase diagrams were constructed to identify stable nanoemulsion region. SNEDDS formulations were evaluated for robustness to dilution, thermodynamic stability study, % transmittance, self-emulsification time, globule size and transmission electron microscopy. The optimized liquid SNEDDS showed robust to all dilutions exhibiting no signs of phase separation or precipitation for 24?h. Liquid SNEDDS was transformed into S-SNEDDS using different adsorbents. Differential scanning calorimetry and scanning electron microscopy studies unravel the transformation of native crystalline state to amorphous state/solubilized state. In vitro dissolution study of S-SNEDDS was found to be significantly higher in comparison to that from plain drug, irrespective of pH (p?ex vivo permeation studies showed a 4.45-fold improvement in apparent permeability coefficient (P_app) from S-SNEDDS compared to plain drug. In conclusion, S-SNEDDS prepared using NMP as cosolvent provides an effective approach for improved oral delivery of ATRC.     

Selecting supplier combination based on fuzzy multicriteria analysis

Existing multicriteria analysis (MCA) methods are probably ineffective in selecting a supplier combination. Thus, an MCA-based fuzzy 0-1 programming method is introduced. The programming relates to a simple MCA matrix that is used to select a single supplier. By solving the programming, the most feasible combination of suppliers is selected. Importantly, this result differs from selecting suppliers one by one according to a single-selection order, which is used to rank sole suppliers in existing MCA methods. An example highlights such difference and illustrates the proposed method.     

The implementation of a smartphone-based fall detection system using a high-level fuzzy Petri net

The falling down problem has become one of the very important issues of global public health in an aging society. The specific equipment was adopted as the detection device of falling-down in the early studies, but it is inconvenient for the elderly and difficult for future application. The smart phone more commonly used than the specific fall detection equipment is selected as a mobile device for human fall detection, and a fall detection algorithm is developed for this purpose. What the user has to do is to put the smart phone in his/her thigh pocket for falling down detection. The signals detected by the tri-axial G-sensor are converted into signal vector magnitudes as the basis of detecting a human body in a stalling condition. The Z-axis data sets are captured for identification of human body inclination and the occurrence frequencies at the peak of the area of use are used as the input parameters. A high-level fuzzy Petri net is used for the analysis and the development of identifying human actions, including normal action, exercising, and falling down. The results of this study can be used in the relevant equipments or in the field of home nursing.     

Kariya (Hildegardia barteri) seed oil extraction: comparative evaluation of solvents,modeling, and optimization techniques

In this work, the effects of solid/solvent ratio (0.10–0.25?g/ml), extraction time (3–8?h), and solvent type (n-hexane, ethyl acetate, and acetone) together with their shared interactions on Kariya seed oil (KSO) yield were investigated. The oil extraction process was modeled via response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) while the optimization of the three input variables essential to the oil extraction process was carried out by genetic algorithm (GA) and RSM methods. The low mean relative percent deviation (MRPD) of 0.94–4.69% and high coefficient of determination (R²) > 0.98 for the models developed demonstrate that they describe the solvent extraction process with high accuracy in this order: ANFIS, ANN, and RSM. The best operating condition (solid/solvent ratio of 0.1?g/ml, extraction time of 8?h, and acetone as solvent of extraction) that gave the highest KSO yield (32.52?wt.%) was obtained using GA-ANFIS and GA-ANN. Solvent extraction efficiency evaluation showed that ethyl acetate, n-hexane, and acetone gave maximum experimental oil yields of 19.20?±?0.28, 25.11?±?0.01, and 32.33?±?0.04?wt.%, respectively. Properties of the KSO varied based on the type of solvent used. The results of this work showed that KSO could function as raw material in both food and chemical industries.     

Density estimates on the unit simplex and calculation of the mode of a sample

This paper addresses reliable and efficient calculation of the mode of a multivariate sample, which is a classical fusion function. In particular, we focus on the inputs given on the unit simplex, when aggregating elements of Atanassov intuitionistic fuzzy sets, interval-valued fuzzy sets and their extensions, as well as compositional data. We outline the use of a specially designed 2-additive fuzzy measures and the Choquet integral for the purposes of reducing computational complexity in higher dimensions. We present computational analysis and benchmark four different methods of density-based mode estimation.     

Telesurgery QoS improvement over SDN based on a Type‐2 fuzzy system and enhanced cuckoo optimization algorithm

Telemedicine is a new area based on the information and communication technology for collecting, storing, organizing, retrieving and exchanging medical information. One of the most important applications of telemedicine is indeed telesurgery in which an efficient telecommunication infrastructure between the surgery room and remote surgeons need to be established. One of the most important issues to be tackled in telesurgery is to find favorable links for routing as well as providing high Quality of Service (QoS). In this paper, an efficient model based on the hybridization of Type‐2 Fuzzy System (T2FS) and Cuckoo Optimization Algorithm (COA) over the Software Defined Networks (SDN) is proposed in order to achieve optimal and reliable routes for telesurgery application. Using T2FS, the fitness of the links is determined; then, a COA is conducted over the Constraint Shortest Path (CSP) problem to find the best routes. Delay is considered as a CSP problem which is satisfied by trying to find the paths with minimum cost. Due to the NP‐completeness of the CSP problem, an Enhanced COA (so‐called E‐COA) is proposed and utilized as a metaheuristic solver. To the best of our knowledge, this paper is the first SDN‐based communication model that applies both T2FS and E‐COA for assigning proper costs to the network's links, and solves the consequence CSP problem according to the QoS requirement for telesurgery. The model also recognizes and preserves the second‐best routes in order to keep the reliability for such a critical application. In addition to the simulations, the performance evaluation is also conducted on a real experimental scenario. Many comparisons are carried out between the proposed model and other conventional methods, and the evaluation study shows the superiority of the proposed model on all the three QoS‐related metrics, i.e. average end‐to‐end delay, packet loss ratio and PSNR.     

四轮轮毂电机驱动电动汽车电液复合制动平顺性控制策略

液压制动与电机再生制动的时域响应差异导致电动汽车在制动模式切换时产生冲击感，影响驾驶员驾驶感受和乘坐舒适性。以四轮轮毂电机驱动电动汽车为研究对象，提出一种基于分层架构的电液复合制动平顺性控制策略。针对"高压蓄能器+电机泵"式电子液压制动系统（EHB），上层控制器提出基于模糊控制的轮缸压力控制策略；针对制动模式切换过程中产生的冲击，下层控制器提出包括液压介入预测模块和电机制动补偿模块的电液复合制动平顺性控制策略。通过Simulink-AMESim联合仿真平台进行仿真试验验证。结果表明，轮缸压力控制策略能够保证轮缸液压力较好地追随目标压力，且稳态误差不超过2%；电液复合制动平顺性控制策略能够有效提高制动系统的响应速度，同时显著降低制动模式切换时的冲击，能提升车辆制动平顺性和乘坐舒适性。