Economic Evaluation of Power System Flexibility by Commercial Air Conditioner Control with Large Penetration of Photovoltaic Generation

High penetration of intermittent renewable energy such as photovoltaic (PV) and wind power could cause shortage of power system flexibility. Demand response is expected to help supply ancillary service instead of the conventional power plant. Commercial air conditioners are a promising responsive load for demand response because they account for a large proportion of power consumption in the power system. We calculate a system operation cost and hourly operation pattern of each power plant by using the optimal power generation model considering flexibility supply from controlling commercial air conditioner. We obtained the following results as an effect of commercial air conditioner control. (1) The power generation of oil fired power plants decreases at peak time and annual fuel cost of oil fired plant is reduced by approximately 30% at most in Kanto area. (2) The percentage of rated operation mode of LNG combined cycle plants increases. (3) Curtailed energy rate of PV decreases because a power storage amount by pumped hydropower generation increases. (4) Required battery capacity to reduce PV curtailed amount decreased by combining battery energy storage system in case of high penetration of PV.     

Effect of resiliency and age on musculoskeletal injuries and lost workdays in emergency medical service personnel

Emergency medical service (EMS) personnel are highly skilled health care professionals who often provide lifesaving clinical care to patients. Paradoxically, they may be repeatedly exposed to a unique set of occupational hazards that could endanger their own health. This cross-sectional study sought to examine the relation between resiliency and musculoskeletal injuries (MSIs) and between resiliency and lost workdays due to MSIs, and explore whether age modifies these associations. Multivariable Poisson main effects regression models showed that resiliency had a protective effect against MSIs, but not lost workdays. In the unadjusted regression model to evaluate the relation between resiliency and age, results suggested that no differences in distributions existed between younger and older EMS personnel and resiliency. However, given the same unit increase in resiliency, findings from multivariable Poisson interaction regression models indicated that older workers had a higher prevalence of MSIs and lost workdays than younger workers. Results from main effects models may reflect diverging routes on a pathophysiological pathway, in which resiliency acts as a prognostic factor for MSIs but not lost workdays. Findings might also indicate the association between resiliency, and MSIs and lost workdays varies by age.Relevance to industryThe largest growth of labor in the US is expected to occur in the oldest segments of the population. While older workers may offer more experience and show similar resiliency to younger workers, they might be more vulnerable to individual risk factors and occupational exposures. If management wants to retain older workers as assets, they should design the work environment to match the capabilities of all workers.     

物联网环境下基于情境的语义Web服务选择

当前Web服务海量增加，物联网应用技术快速发展、不断普及，而现有的Web服务选择算法低效、用户匹配度低。针对该问题提出一种物联网环境下基于情境的语义Web服务选择方法。该方法应用QoS参数的无量纲化与语义Web服务动态选择方式，将物联网环境下服务与语义Web服务相结合，并根据用户需求针对QoS选择最优的服务集。实验表明，该方法能有效地提高用户服务动态选择的成功率。     

Hybridizing adaptive large neighborhood search with kernel search: a new solution approach for the nurse routing problem with incompatible services and minimum demand

The average age of the population has grown steadily in recent decades along with the number of people suffering from chronic diseases and asking for treatments. Hospital care is expensive and often unsafe, especially for older individuals. This is particularly true during pandemics as the recent SARS-CoV-2. Hospitalization at home has become a valuable alternative to face efficiently a huge increase in treatment requests while guaranteeing a high quality of service and lower risk to fragile patients. This new model of care requires the redefinition of health services organization and the optimization of scarce resources (e.g., available nurses). In this paper, we study a Nurse Routing Problem that tries to find a good balance between hospital costs reduction and the well-being of patients, also considering realistic operational restrictions like maximum working times for the nurses and possible incompatibilities between services jointly provided to the same patient. We first propose a Mixed Integer Linear Programming formulation for the problem and use some valid inequalities to strengthen it. A simple branch-and-cut algorithm is proposed and validated to derive ground benchmarks. In addition, to efficiently solve the problem, we develop an Adaptive Large Neighborhood Search hybridized with a Kernel Search and validate its performance over a large set of different realistic working scenarios. Computational tests show how our matheuristic approach manages to find good solutions in a reasonable amount of time even in the most difficult settings. Finally, some interesting managerial insights are discussed through an economic analysis of the operating context.     

Research on Circular Area Search algorithm of multi-robot service based on SOA cloud platform

Considering autonomous mobile robots with a variety of specific functions as a kind of service, when there are many types and quantities of services and the density of regional services is large, proposing an algorithm of Circular Area Search (CAS) because of the problem of multi-robot service scheduling in various areas. Firstly, Django is used as the web framework to build the Service-Oriented Architecture (SOA) multi-robot service cloud platform, which is the basic platform for multi-service combination. Then, the service type, the latitude and longitude and the scoring parameters of the service are selected as the service search metrics to design the CAS algorithm that based on the existing service information registered in MySQL and the Gaode Map for screening optimal service, and then providing the service applicant with the best service. Finally, the service applicant applies for the self-driving tour service as an example to perform performance simulation test on the proposed CAS algorithm. The results show that the CAS algorithm of the multi-robot service cloud platform proposed in this paper is practical compared to the global search. And compared with the Greedy Algorithm experiment, the service search time is reduced about 58% compared with the Greedy Algorithm, which verifies the efficiency of CAS algorithm.     

Improving the risk management of Type 2 diabetes mellitus in China from the perspective of social relationships

In China, Type 2 diabetes mellitus (T2DM) is increasingly affecting people's health. Although many risk factors related to T2DM have been researched, the association between social relationships and risk management of T2DM in China has not been fully researched. Therefore, we obtained 2,969 valid cases from the National Chinese Medicine Clinical Research Base-Key Disease of Diabetes Mellitus Study to evaluate the role of social relationships in the risk management of T2DM. We first establish an indicators system of social relationship factors and then propose a comprehensive method that integrates subjective (analytical network process) and objective (entropy weight method) evaluations to rank the importance of the 17 social relationship factors that were the most important and commonly used. The results suggest that different social relationship factors have different effects on the risk management of T2DM. Patients and health workers should pay more attention to the high-benefit factors and thus improve the efficiency of the risk management of T2DM. These findings provided theoretical support for patients and health workers by developing the positive effects of social relationships in improving the risk management of T2DM to the fullest degree.     

基本公共服务均等化背景下吉林市社区养老问题研究

近年来，以推进基本公共服务均等化为依托而促进养老等社会服务的发展已成为各省市的重点工作之一，立足于吉林市市情，通过调查研究、定量分析等方式探索本地社区养老存在的问题以及对策。     

Quantum computation based bundling optimization for combinatorial auction in freight service procurements

Combinatorial auction is a useful trade manner for transportation service procurements in e-marketplaces. To enhance the competition of combinatorial auction, a novel auction mechanism of two-round bidding with bundling optimization is proposed. As the recommended the auction mechanism, the shipper/auctioneer integrates the objects into several bundles based on the bidding results of first round auction. Then, carriers/bidders bid for the object bundles in second round. The bundling optimization is described as a multi-objective model with two criteria on price complementation and combination consistency. A Quantum Evolutionary Algorithm (QEA) with β-based rotation gate and the encoding scheme based on non-zero elements in complementary coefficient matrix is developed for the model solution. Comparing with a Contrast Genetic Algorithm, QEA can achieve better computational performances for small and middle size problems.     

Liner services network design and fleet deployment with empty container repositioning

Transportation demand of shipping container fluctuates due to the seasonality of international trade, thus, every 3–6 months, the liner company has to alter its current liner shipping service network, redeploy ships and design cargo routes with the objective of minimizing the total cost. To solve the problem, the paper presents a mixed integer linear program model. The proposed model incorporates several relevant constraints, such as weekly frequency, the transshipment of cargo between two or more service routes, and transport time. Extensive numerical experiments based on realistic date of Asia–Europe–Oceania shipping operations show that the proposed model can solve real-case problems efficiently by CPLEX. The results demonstrate that the model can reduce ship’s capacity consumption and raise ships’ capacity utilization.     

Resource allocation for multi-class services in multipath networks

In multipath networks, multiple paths are available for each pair of source and destination and can be used to carry data packets parallelly. It has been recognized that using multipath could promote the transmission reliability and fault tolerance, and improve the performance of increasingly bandwidth-hungry multi-media applications. In this paper we propose the resource allocation model for multi-class services in multipath networks with the objective of utility maximization, which is an intrinsically difficult problem of nonconvex optimization. We firstly analyze the model for only elastic services and obtain the optimal rate allocation for them. Then we also discuss the model for inelastic services with nonconcave (sigmoidal or discontinuous) utilities which share common links with elastic ones, and obtain some sufficient conditions under which the global optimum for both elastic and inelastic services can be obtained. For the nonconvex optimization problem, we present a heuristic algorithm using Particle Swarm Optimization (PSO), which can lead to improved solutions over existing approaches. Finally, some numerical examples are given to verify the results obtained.