Exact Tail Asymptotics for a Queueing System with a Retrial Orbit and Batch Service

This paper discusses a queueing system with a retrial orbit and batch service, in which the quantity of customers’ rooms in the queue is finite and the space of retrial orbit is infinite. When the server starts serving, it serves all customers in the queue in a single batch, which is the so-called batch service. If a new customer or a retrial customer finds all the customers’ rooms are occupied, he will decide whether or not to join the retrial orbit. By using the censoring technique and the matrix analysis method, we first obtain the decay function of the stationary distribution for the quantity of customers in the retrial orbit and the quantity of customers in the queue. Then based on the form of decay rate function and the Karamata Tauberian theorem, we finally get the exact tail asymptotics of the stationary distribution.

A Cooperated Imperialist Competitive Algorithm for Unrelated Parallel Batch Machine Scheduling Problem

This study focuses on the scheduling problem of unrelated parallel batch processing machines(BPM)with release times,a scenario derived from the moulding process in a foundry.In this process,a batch is initially formed,placed in a sandbox,and then the sandbox is positioned on a BPM formoulding.The complexity of the scheduling problem increases due to the consideration of BPM capacity and sandbox volume.To minimize the makespan,a new cooperated imperialist competitive algorithm(CICA)is introduced.In CICA,the number of empires is not a parameter,and four empires aremaintained throughout the search process.Two types of assimilations are achieved:The strongest and weakest empires cooperate in their assimilation,while the remaining two empires,having a close normalization total cost,combine in their assimilation.A new form of imperialist competition is proposed to prevent insufficient competition,and the unique features of the problem are effectively utilized.Computational experiments are conducted across several instances,and a significant amount of experimental results show that the newstrategies of CICAare effective,indicating promising advantages for the considered BPMscheduling problems.

A Blind Batch Encryption and Public Ledger-Based Protocol for Sharing Sensitive Data

For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.

基于TFIDF+LDA和Mini Batch K⁃means算法的在线课程推荐方法研究

在线教育资源急剧增长让学习者难以抉择,研究在线课程分类推荐,能帮助学习者快速获取所需资源。首先将潜在狄利克雷分配算法融入词频-逆向文件频率算法对数据进行预处理,生成词向量矩阵;之后采用Mini Batch K-means算法训练聚类模型,并采用T分布随机邻域嵌入降维算法对训练结果进行可视化分析。实验采用从Pluralsight在线课程API获取8016条数据进行实验,实验结果表明融入潜在狄利克雷分配算法的词频-逆向文件频率算法效果更好。

An improved multi-objective optimization algorithm for solving flexible job shop scheduling problem with variable batches

In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.

Robust design of self-starting drains using Random Forest

Groundwater lowering is one of the most important countermeasures to avoid the risk of rainfall-triggered landslides.However,the long-term reliability of many drainage methods is often a matter of concern since the drains may easily get clogged.A new hydraulic-driven self-starting drainage method is presented in this paper.In the proposed Random Forest(RF)based robust design approach for the selfstarting drains,the datasets are generated using an automatically controlled numerical modeling technology.The deterministic analysis is carried out based on uncertain soil parameters and the specific designs selected using Uniform Design(UD).The ensemble of RF models is applied in the design process to improve computing efficiency.Safety requirements,design robustness,and cost efficiency are simultaneously considered utilizing multiobjective optimization.A straightforward and efficient framework that focuses on difficulties caused by an enormous design space is established for the robust design of the self-starting drains,and improved computation efficiency is achieved.The effectiveness of the proposed approach is illustrated with a case study,the Qili landslide in Zhejiang Province,China.

Self-starting mode-locked picosecond Ti：sapphire laser by using of a fast SESAM

A stable continuous wave mode-locked picosecond Ti：sapphire laser by using a fast semiconductor saturable absorber mirror （SESAM） is demonstrated. The laser delivers pulse width of 20 ps at a central wavelength of 813 nm and a repetition rate of 100 MHz. The maximum output power is 1.34 W with pump power of 7 W which corresponds to an optical^optical conversion efficiency of 19.1%.

The Poverty Alleviation Model for the Solitary Elderly People in the Poor Mountainous Areas of Southwest China: Analysis of "Five Batches Project" in Xundian County

The solitary elderly people in rural areas are not only an important part of the rural population,but also an important issue that can not be ignored in the battle to get rid of poverty. In recent years,according to the working thinking of ' accurate statistics,scientific arrangement,classified implementation,and rapid progress',Xundian County has gone through joint exploration and practice at the county and township levels,and has found out the path of work of ' Five Batches Project' to solve the problem of poverty alleviation for the solitary elderly people and make them live in their own homes. This has effectively solved the problem of safe and stable housing for 4 443 solitary elderly people in the county. It has found a new way to solve the housing problem of the solitary elderly people. At the end of 2017,the incidence of poverty in the county dropped to 0. 35%,and it was successfully listed as one of the first counties in Yunnan Province to get rid of poverty. Based on field research and interviews,this paper analyzes and summarizes the concrete methods,main achievements,practical experience,lessons and reference of the poverty alleviation model of ' Five Batches Project' in Xundian County to solve the problem of housing for the elderly,in order to provide necessary reference for the poor counties in Yunnan Province and other similar provinces( cities,autonomous regions) to solve the problem of housing for ' solitary elderly people' in Yunnan Province.

A wind tunnel experiment of self-starting capability for straight-bladed vertical axis wind turbine

In this study,wind tunnel experiment was carried out to investigate the self-staring capability for straight-bladed vertical axis wind turbine.The flow visualization also was been performed at the rest of the rotor.The effect of the azimuthal angle of blade position relative to wind direction on the self-starting capability was discussed based on the results of flow visualization.The torque and centripetal force of the rotor when the self-starting behavior starts were roughly calculated with the flow visualization results of the rotor.It is suggested that there exists the condition of wind speed and configuration of the blade position of the rotor at the rest of rotor to the reach to situational rotation number.

Study on the Treatment Strategy of Batches of the Wounded and Partial First-Aid Procedures in Public Emergencies in Tertiary General Hospitals

Objective: The purpose is to formulate treatment strategies of batches of the wounded and partial first-aid procedures, and further improve the emergency rescue capability of hospitals. Methods: This study analyzed the emergency treatment case that we participated in. In this case, we used various means to start the emergency plan, run the emergency procedures, optimize diagnosis, treatment, and rescue procedures, mobilize medical rescue resources, provide a reference for emergency command decisions, formulate a set of coping strategies of tertiary general hospitals on public emergencies. Results: Through the scientific and effective management of our hospital, 20 wounded have been discharged from the hospital and achieved the ideal effect of zero deaths in the hospital. Conclusions: The new mode of first-aid and health emergency management on the scene of modern disaster needs to find ways to minimize the loss of life and property brought by public emergencies, integrate the various sections of modern disaster medicine, integrate a large number of international and domestic basic and clinical research achievements of disaster first-aid, and upgrade to information, digital system.

基于在线梯度下降的Mini Batch K-Prototypes算法

K-Prototypes算法每次迭代都需要花费大量时间来计算所有样本与每个簇中心的相异度以将其划分到各个聚类簇中,这导致K-Prototypes算法在处理大型数据集时运行时间急剧增加。根据在线梯度下降算法对K-Prototypes算法的迭代过程进行优化,减少算法每次迭代所需的计算量从而降低算法的时间复杂度,提升算法运行效率。实验结果表明,提出的基于在线梯度下降的K-Prototypes聚类算法,可以在不影响算法收敛性和有效性的前提下降低算法的时间复杂度,提升算法运行效率。

基于PCS7的BATCH控制在生物制药单抗生产中的应用

随着生物制药的发展,单抗药物的生产越来越朝着系统化、集成化、数字化的方向发展。针对单抗药物复杂的工艺生产过程和配方多变的生产方式。本文采用西门子PCS7全集成DCS系统,利用符合ISA-S88标准的批量控制软件和配方管理,研究单抗控制方案和第三方设备集成方案,设计出适用于单抗生产的批次控制DCS系统,满足其生产工艺、参数多变的柔性化需求和数据完整性要求。

APPLICATION OF CONVECTION-DIFFUSION EQUATION TO THEANALYSES OF CONTAMINATION BETWEEN BATCHESIN MULTI-PRODUCTS PIPELINE TRANSPORT

Contamination between batches in multi-products pipeline transport is studied. The influences of convection and diffusion on the contamination are studied in detail. Diffusion equations, which are mainly controlled by convection, are developed under turbulent pipe flow. The diffusion equation is separated into a pure convection equation and a pure diffusion equation which are solved by characteristics method and finite difference method respectively to obtain numerical solutions. The results of numerical computation explain the forming and developing of contamination very well.

Foreign trade apparel companies transforming in small batches of personalized customization

Faced with the new changes in the market affected by the pandemic,Chinese foreign trade apparel companies have adjusted their market models and product structures,upgrading from traditional manufacturing to flexible manufacturing and itelligent manufacturing to improve priaillity.

Assessing the Impact of Fugitive Dust Emissions from Cement Silos at Cluster of Concrete Batching Facilities Using Air Dispersion Modeling

This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM10) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM10 released from the cement silos into the air. Simulations were carried out for PM10 emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM10 emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m3, and the highest daily emission value is 0.6 μg/m3;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m3. The highest daily emission average value was 1250.09 μg/m3;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM10 pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.

Research on Optimization of Dual-Resource Batch Scheduling in Flexible Job Shop

With the rapid development of intelligent manufacturing and the changes in market demand,the current manufacturing industry presents the characteristics of multi-varieties,small batches,customization,and a short production cycle,with the whole production process having certain flexibility.In this paper,a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop,and an improved nested optimization algorithm is designed to solve the problem.The outer layer batch optimization problem is solved by the improved simulated annealing algorithm.The inner double resource scheduling problem is solved by the improved adaptive genetic algorithm,the double coding scheme,and the decoding scheme of Automated Guided Vehicle(AGV)scheduling based on the scheduling rules.The time consumption of collision-free paths is solved with the path planning algorithm which uses the Dijkstra algorithm based on a time window.Finally,the effectiveness of the algorithm is verified by actual cases,and the influence of AGV with different configurations on workshop production efficiency is analyzed.

Rockburst Intensity Grade Prediction Model Based on Batch Gradient Descent and Multi-Scale Residual Deep Neural Network

Rockburst is a phenomenon in which free surfaces are formed during excavation,which subsequently causes the sudden release of energy in the construction of mines and tunnels.Light rockburst only peels off rock slices without ejection,while severe rockburst causes casualties and property loss.The frequency and degree of rockburst damage increases with the excavation depth.Moreover,rockburst is the leading engineering geological hazard in the excavation process,and thus the prediction of its intensity grade is of great significance to the development of geotechnical engineering.Therefore,the prediction of rockburst intensity grade is one problem that needs to be solved urgently.By comprehensively considering the occurrence mechanism of rockburst,this paper selects the stress index(σθ/σc),brittleness index(σ_(c)/σ_(t)),and rock elastic energy index(Wet)as the rockburst evaluation indexes through the Spearman coefficient method.This overcomes the low accuracy problem of a single evaluation index prediction method.Following this,the BGD-MSR-DNN rockburst intensity grade prediction model based on batch gradient descent and a multi-scale residual deep neural network is proposed.The batch gradient descent(BGD)module is used to replace the gradient descent algorithm,which effectively improves the efficiency of the network and reduces the model training time.Moreover,the multi-scale residual(MSR)module solves the problem of network degradation when there are too many hidden layers of the deep neural network(DNN),thus improving the model prediction accuracy.The experimental results reveal the BGDMSR-DNN model accuracy to reach 97.1%,outperforming other comparable models.Finally,actual projects such as Qinling Tunnel and Daxiangling Tunnel,reached an accuracy of 100%.The model can be applied in mines and tunnel engineering to realize the accurate and rapid prediction of rockburst intensity grade.

Aspen Batch Process Developer在原料药工程设计中的应用研究

基于Aspen Batch Process Developer软件对原料药工程设计进行应用研究。在某原料药项目中,通过软件建立工艺流程模拟模型,分析批次操作时间、年生产批次、年生产规模、物料衡算、设备选型和利用率、公用工程消耗等,在满足生产需求的情况下,达到优化生产排班、设备选型和公用工程量的目的。

Comparative Analysis of PM10 Emission Rates from Controlled and Uncontrolled Cement Silos in Concrete Batching Facilities

This research study quantifies the PM10 emission rates (g/s) from cement silos in 25 concrete batching facilities for both controlled and uncontrolled scenarios by applying the USEPA AP-42 guidelines step-by-step approach. The study focuses on evaluating the potential environmental impact of cement dust fugitive emissions from 176 cement silos located in 25 concrete batching facilities in the M35 Mussafah industrial area of Abu Dhabi, UAE. Emission factors are crucial for quantifying the PM10 emission rates (g/s) that support developing source-specific emission estimates for areawide inventories to identify major sources of pollution that provide screening sources for compliance monitoring and air dispersion modeling. This requires data to be collected involves information on production, raw material usage, energy consumption, and process-related details, this was obtained using various methods, including field visits, surveys, and interviews with facility representatives to calculate emission rates accurately. Statistical analysis was conducted on cement consumption and emission rates for controlled and uncontrolled sources of the targeted facilities. The data shows that the average cement consumption among the facilities is approximately 88,160 (MT/yr), with a wide range of variation depending on the facility size and production rate. The emission rates from controlled sources have an average of 4.752E-04 (g/s), while the rates from uncontrolled sources average 0.6716 (g/s). The analysis shows a significant statistical relationship (p < 0.05) and perfect positive correlation (r = 1) between cement consumption and emission rates, indicating that as cement consumption increases, emission rates tend to increase as well. Furthermore, comparing the emission rates from controlled and uncontrolled scenarios. The data showed a significant difference between the two scenarios, highlighting the effectiveness of control measures in reducing PM10 emissions. The study’s findings provide insights into the impact of cement silo emissions on air quality and the importance of implementing control measures in concrete batching facilities. The comparative analysis contributes to understanding emission sources and supports the development of pollution control strategies in the Ready-Mix industry.