Using Electrons on Liquid Helium for Quantum Computing

We describe a quantum computer based on electrons supported by a helium film and localized laterally by small electrodes just under the helium surface. Each qubit is made of combinations of the ground and first excited state of an electron trapped in the image potential well at the surface. Mechanisms for preparing the initial state of the qubit, operations with the qubits, and a proposed readout are described. This system is, in principle, capable of 10 ⁵ operations in a decoherence time.     

Computing Division Using Single-Electron Tunneling Technology

Emerging nanotechnologies, like single-electron tunneling (SET) technology, possesses properties that are fundamentally different from what CMOS offers to engineers. This opens up avenues for novel computational paradigms, which can perform arithmetic operations efficiently by utilizing these new available properties. In this line of reasoning, in this paper we investigate the implementation of division in SET technology using a novel computation paradigm called electron counting. First, we present two schemes that are based on sequential approximation of the quotient. The first scheme is basic and simple to build, but suffers from overshoot and has a rather large delay. The second scheme, which is a modification of the first one, has a delay logarithmic in the quotient magnitude and the simulation results we present indicate that this scheme works correctly. Finally, we propose a division scheme based on the computation of periodic symmetric functions. Although this scheme requires a varactor for which no nanoscale implementation yet exists and which cannot be directly simulated, it demonstrates the possibilities that nanotechnology, and specifically SET technology, potentially offers as it has a time complexity of O(1).     

超支化聚硅氧烷改性聚偏氟乙烯微孔膜的制备及膜蒸馏性能

采用γ-甲基丙烯酰氧基丙基三甲氧基硅烷(A-174)水解缩合反应合成超支化聚硅氧烷(HPSi O),并用其改性聚偏氟乙烯(PVDF)制备疏水HPSiO-PVDF微孔膜。通过红外光谱、核磁共振、水接触角、孔隙率、孔径分布、力学强度等表征方法研究了所制膜的结构和性能,以及微孔膜膜蒸馏性能。结果表明,HPSiO的加入降低了膜孔径,提高了微孔膜的孔隙率、疏水性能、力学性能及真空膜蒸馏性能。     

应用Excel进行统计运算流量的标准差

对测井仪器流量刻度数据进行处理,能够检测仪器的性能,减少计算结果的误差,应用Excel对所测得的数据进行线性回归,在此基础上进行统计运算流量的标准差.结果表明,这种方法能够适用于目前仪器刻度工作的需要.     

Effective Product Family Design Using Physical Programming

In response to today's highly competitive global marketplace, many companies are utilizing product families - groups of related products derived from a product platform - to maintain economies of scale while satisfying a variety of customer requirements. This paper focuses on scale-based product families and presents a new single-stage approach for simultaneously optimizing a product platform and the resulting family of products based on one or more scaling variables - variables that are used to instantiate the product platform by "stretching" or "shrinking" it in one or more dimensions to satisfy a variety of customer requirements. The proposed approach is also unique in that it employs the Physical Programming method, enabling designers to formulate the product family optimization problem in terms of physically meaningful terms and parameters. The design of a family of ten universal electric motors is used as an example to benchmark the effectiveness of the proposed approach against previous results. While the emphasis in this paper is on the design method rather than the results per se , performance gains are achieved in the motor family by using the proposed single-stage approach and Physical Programming.     

Efficient Resource Allocation in Fog Computing Using QTCS Model

Infrastructure of fog is a complex system due to the large number of heterogeneous resources that need to be shared. The embedded devices deployed with the Internet of Things (IoT) technology have increased since the past few years, and these devices generate huge amount of data. The devices in IoT can be remotely connected and might be placed in different locations which add to the network delay. Real time applications require high bandwidth with reduced latency to ensure Quality of Service (QoS). To achieve this, fog computing plays a vital role in processing the request locally with the nearest available resources by reduced latency. One of the major issues to focus on in a fog service is managing and allocating resources. Queuing theory is one of the most popular mechanisms for task allocation. In this work, an efficient model is designed to improve QoS with the efficacy of resource allocation based on a Queuing Theory based Cuckoo Search (QTCS) model which will optimize the overall resource management process.     

A New Process for Drug Loaded Nanocapsules Preparation Using a Membrane Contactor

ABSTRACT

In this paper, we describe a new process for the preparation of drug loaded nanocapsules using a membrane contactor which may be scaled up for industrial applications. Nanocapsules are prepared according to the nanoprecipitation method. The organic phase (solvent, polymer, oil, and drug) is pressed through the pores of an ultrafiltration membrane via the filtrate side. The aqueous phase (water and surfactant) circulates inside the membrane module, and sweeps away the nanocaspules forming at the pore outlets. Two model drugs are selected for the preparation of drug loaded nanocapsules: indomethacin and vitamin E. It is shown that indomethacin loaded nanocapsules with a mean diameter of 240 nm and vitamin E loaded nanocapsules with a mean diameter of 230 nm are obtained with a 150,000 daltons ultrafiltration membrane, a transmembrane pressure of 3 bar, and a crossflow rate of 1.7 m.s^{? 1}. High fluxes are also obtained (around 0.6 m³/h.m²), leading to the preparation of 1.8 10^{? 3} m³ drug loaded nanocapsules in 8 min. The advantage of this membrane contactor compared to other processes for drug loaded nanocapsules preparation is shown to be its scale-up ability.     

An Effective Emissivity Model for Rapid Thermal Processing Using the Net-Radiation Method

A reflective shield has been placed in the lower chamber of some rapid thermal processing (RTP) systems so that the temperature of the silicon wafer can be accurately measured in situ with light-pipe radiometers. Better knowledge of the effective emissivity of the wafer reduces the uncertainty in the temperature measurement. This paper describes an enclosure model based on the net-radiation method for predicting the effective emissivity of the wafer. The model treats the surfaces in the enclosure as diffuse emitters, with a reflectivity that may include a diffuse component and a specular component. Using this model, a parametric study is performed to investigate the influence of the geometric arrangement, surface temperature and properties, and wavelength on the effective emissivity. The algorithm developed in this work may serve as a tool to improve radiometric temperature measurement in RTP systems.     

基于分形理论的开孔聚氨酯泡沫等效导热系数研究

开孔聚氨酯泡沫保温材料是一种典型的多孔介质。采用分形理论描述开孔聚氨酯泡沫材料的微尺度空间结构,建立了简化单元体模型,提出了计算其有效导热系数的分形模型,并导出了气相和固相热传导计算公式、热辐射等效导热系数计算公式、材料总有效导热系数计算公式。模型计算值与实验测量值比较具有较好的一致性,同时总结了多孔介质材料绝热性能的主要影响因素。该分析方法对新型绝热材料的研制和绝热性能的提高具有实用价值。     

Prediction of COVID-19 Cases Using Machine Learning for Effective Public Health Management

COVID-19 is a pandemic that has affected nearly every country in the world. At present, sustainable development in the area of public health is considered vital to securing a promising and prosperous future for humans. However, widespread diseases, such as COVID-19, create numerous challenges to this goal, and some of those challenges are not yet defined. In this study, a Shallow Single-Layer Perceptron Neural Network (SSLPNN) and Gaussian Process Regression (GPR) model were used for the classification and prediction of confirmed COVID-19 cases in five geographically distributed regions of Asia with diverse settings and environmental conditions: namely, China, South Korea, Japan, Saudi Arabia, and Pakistan. Significant environmental and non-environmental features were taken as the input dataset, and confirmed COVID-19 cases were taken as the output dataset. A correlation analysis was done to identify patterns in the cases related to fluctuations in the associated variables. The results of this study established that the population and air quality index of a region had a statistically significant influence on the cases. However, age and the human development index had a negative influence on the cases. The proposed SSLPNN-based classification model performed well when predicting the classes of confirmed cases. During training, the binary classification model was highly accurate, with a Root Mean Square Error (RMSE) of 0.91. Likewise, the results of the regression analysis using the GPR technique with Matern 5/2 were highly accurate (RMSE = 0.95239) when predicting the number of confirmed COVID-19 cases in an area. However, dynamic management has occupied a core place in studies on the sustainable development of public health but dynamic management depends on proactive strategies based on statistically verified approaches, like Artificial Intelligence (AI). In this study, an SSLPNN model has been trained to fit public health associated data into an appropriate class, allowing GPR to predict the number of confirmed COVID-19 cases in an area based on the given values of selected parameters. Therefore, this tool can help authorities in different ecological settings effectively manage COVID-19.     

SMBR中不同膜组件形式的膜通量变化数学模型分析

以一体式膜生物反应器（SMBR）处理污水,对自行研制的两种膜组件形式的膜通量变化进行考察,运行结果表明：A和B两种组件均好于对照组件,且B种能有效防止端头污染,在一定程度上减缓膜通量的衰减。通过建立数学模型,提出求解的数值计算方法,并编程进行上机计算,从理论上说明B种优于A种及对照,证实膜组件形式优化的必要性。     

Effective Separation of CO2 Using Metal-Incorporated rGO Membranes

Graphene-based materials, primarily graphene oxide (GO), have shown excellent separation and purification characteristics. Precise molecular sieving is potentially possible using graphene oxide-based membranes, if the porosity can be matched with the kinetic diameters of the gas molecules, which is possible via the tuning of graphene oxide interlayer spacing to take advantage of gas species interactions with graphene oxide channels. Here, highly effective separation of gases from their mixtures by using uniquely tailored porosity in mildly reduced graphene oxide (rGO) based membranes is reported. The gas permeation experiments, adsorption measurement, and density functional theory calculations show that this membrane preparation method allows tuning the selectivity for targeted molecules via the intercalation of specific transition metal ions. In particular, rGO membranes intercalated with Fe ions that offer ordered porosity, show excellent reproducible N₂/CO₂ selectivity of ≈97 at 110 mbar, which is an unprecedented value for graphene-based membranes. By exploring the impact of Fe intercalated rGO membranes, it is revealed that the increasing transmembrane pressure leads to a transition of N₂ diffusion mode from Maxwell–Stefan type to Knudsen type. This study will lead to new avenues for the applications of graphene for efficiently separating CO₂ from N₂ and other gases.     

Effective Form Error Assessment Using Improved Particle Swarm Optimization

This paper presents an improved variant of particle swarm optimization (MPSO) algorithm for the form error evaluation, from a set of coordinate measurement data points. In classical particle swarm optimization (PSO), new solution is updated by the existing one without really comparing which one is better. This behaviour is considered to be caused by lack in exploitation ability in the search space. The proposed algorithm generates new swarm position and fitness solution employing an improved and modified search equation. In this step, the swarm searches in proximity of the best solution of previous iteration to improve the exploitation behaviour. The particle swarm employs greedy selection procedure to choose the best candidate solution. A non-linear minimum zone objective function is formulated mathematically for each form error and consequently optimized using proposed MPSO algorithm. Five benchmark functions are used to prove the efficiency of the proposed MPSO algorithm, by comparing the proposed algorithm with established PSO and genetic algorithm. Finally, the results of the proposed MPSO algorithm are compared with previous literature and with other nature inspired algorithms on the same problem. The results validate that proposed MPSO algorithm is more efficient and accurate as compared to other conventional methods and is well suited for effective form error evaluation using CMMs.     

基于免疫遗传计算的零件多目标优化

由生物引发的信息处理系统可分为:人工神经网络、进化计算和人工免疫系统(AIS)。其中神经网络和进化计算已被广泛用于各领域,而AIS则由于其复杂性较少应用。笔者将免疫算法与遗传计算结合,研制了一个基于免疫遗传计算的优化设计系统(Immune ＆ Genetic Algorithm based Design SupportSystem-IGBODS)。IGBODS用于零件的优化设计,避免了遗传算法搜索效率低,过早收敛和不能很好保持个体的多样性等问题,具有很大的优越性。     

多块结构化网格CFD并行计算和负载平衡研究

基于连续拼接多块结构化网格,通过求解雷诺平均Navier-Stokes方程研究并行计算中的负载平衡问题。利用组合优化中的排序理论设计负载平衡算法,实现了网格数据的自动划分和各处理机上计算任务的自动分配。在工作站集群MPI并行环境下,通过实例考察了负载平衡算法和并行计算的性能,16个处理机上的负载均方差和负载相对均方差分别为0.0084和0.1347%,并行计算结果和实验数据吻合良好,并行效率高。本文算法具有良好的可扩展性,适用于MIMD结构计算机上基于多块结构化网格并行计算中的负载平衡问题。     

Determining Effective Thermal Conductivity of Fabrics by Using Fractal Method

In this article, a fractal effective thermal conductivity model for woven fabrics with multiple layers is developed. Structural models of yarn and plain woven fabric are derived based on the fractal characteristics of macro-pores (gap or channel) between the yarns and micro-pores inside the yarns. The fractal effective thermal conductivity model can be expressed as a function of the pore structure (fractal dimension) and architectural parameters of the woven fabric. Good agreement is found between the fractal model and the thermal conductivity measurements in the general porosity ranges. It is expected that the model will be helpful in the evaluation of thermal comfort for woven fabric in the whole range of porosity.     

The Choice of Variables Sampling Plans Using Cost Effective Criteria

In this paper two total cost models are presented for acceptance sampling by variables. The first model is for the case where rejected lots are screened and the second for scrapping of rejected lots. Conditions for optimal sampling plan development are presented for both models and illustrated by example. In addition, the sensitivity of both models to errors in parameter estimation and distributional shape is analyzed and discussed.     

Effective Moduli Evaluation of Carbon Nanotube Reinforced Polymers Using Micromechanics

A multistep homogenization method is adopted to compute the effective moduli of carbon nanotube reinforced composites. The composite is assumed to be reinforced with isolated individual fibers and clustered fibers. A uniform agglomeration model is introduced assuming constant carbon nanotube cluster size throughout the matrix. Agglomeration volume fraction—a critical parameter in the simulation—is considered to be an explicit function of inter-particle distance and quality of dispersion of fibers. The micromechanics model also incorporates random fiber orientation using a statistical approach. It is seen that these parameters reduce the stiffening effect of carbon nanotubes significantly in the composite.