Study on the Alignment Between Talent Training Directions and Employment Market Demands in the Landscape Architecture Industry

Currently,talent training in Chinese universities for landscape architecture is mainly divided into three directions:“landscape planning and design,”“landscape construction management,”and“landscape plant planting and maintenance.”However,with the background of the slowing urbanization process and the widespread demand for composite talents in society,it remains to be verified whether the traditional three major talent training directions in landscape architecture align with the job demands in the current construction market.Based on a survey and analysis of over 300 industry practitioners,this study found a clear trend of merging the three major employment directions into“landscape design and construction”and“landscape plant planting and maintenance.”This presents new requirements and directions for the skill training of landscape architecture majors in universities and provides insights into the alignment between talent training and employment demands in other industries.

Research on design methodology for railway freight service combination plans to meet diverse demands

Purpose–Facing the diverse needs of large-scale customers,based on available railway service resources and service capabilities,this paper aims to research the design method of railway freight service portfolio,select optimal service solutions and provide customers with comprehensive and customized freight services.Design/methodology/approach–Based on the characteristics of railway freight services throughout the entire process,the service system is decomposed into independent units of service functions,and a railway freight service combination model is constructed with the goal of minimizing response time,service cost and service time.A model solving algorithm based on adaptive genetic algorithm is proposed.Findings–Using the computational model,an empirical analysis was conducted on the entire process freight service plan for starch sold from Xi’an to Chengdu as an example.The results showed that the proposed optimization model and algorithm can effectively guide the design of freight plans and provide technical support for real-time response to customers’diversified entire process freight service needs.Originality/value–With the continuous optimization and upgrading of railway freight source structure,customer demands are becoming increasingly diverse and personalized.Studying and designing a reasonable railway freight service plan throughout the entire process is of great significance for timely response to customer needs,improving service efficiency and reducing design costs.

Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.

Vickrey-Clark-Groves-based Method for Eradicating Deceptive Behaviors in Demand Response Transactions

Demand response transactions between electric con-sumers,load aggregators,and the distribution network manag-er based on the"combination of price and incentive"are feasi-ble and efficient.However,the incentive payment of demand re-sponse is quantified based on private information,which gives the electric consumers and load aggregators the possibility of defrauding illegitimate interests by declaring false information.This paper proposes a method based on Vickrey-Clark-Groves(VCG)theory to prevent electric consumers and load aggrega-tors from taking illegitimate interests through deceptive behav-iors in the demand response transactions.Firstly,a demand re-sponse transaction framework with the price-and-incentive com-bined mode is established to illustrate the deceptive behaviors in the demand response transactions.Then,the idea for eradi-cating deceptive behaviors based on VCG theory is given,and a detailed VCG-based mathematical model is constructed follow-ing the demand response transaction framework.Further,the proofs of incentive compatibility,individual rationality,cost minimization,and budget balance of the proposed VCG-based method are given.Finally,a modified IEEE 33-node system and a modified IEEE 123-node system are used to illustrate and val-idate the proposed method.

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

Optimal dispatching strategy for residential demand response considering load participation

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.

Vehicle routing optimization algorithm based on time windows and dynamic demand

To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.

A Note on an Order Level Inventory Model with Varying Two-Phased Demand and Time-Proportional Deterioration

The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.

Demand and Analysis of Clinical Research Curriculum in Medical Universities

Objective:To investigate the needs of medical students regarding clinical research curricula to provide scientifically sound offerings and cultivate their clinical research thinking.Methods:From June to October 2022,medical students at medical universities in Shaanxi Province were surveyed using online questionnaires.The survey covered their demographic information,awareness of their major,understanding of clinical research,and preferences for curriculum content.Results:A total of 341 valid questionnaires were analyzed.Medical students demonstrated a strong awareness of their majors but a relatively low awareness of clinical research.There was significant demand for clinical research courses,with preferences for professionally oriented(81.8%),market-oriented(100%),theoretically and practically integrated teaching(78.6%),and application-focused(73.0%)courses.Conclusion:Medical colleges and universities should align clinical research curricula with the actual needs of medical students and clinical practice.Reforms in curriculum design and teaching methods are essential to better prepare students for careers in public health.

Survey on the Demand for Elderly Care Services of Community Residents in Beijing and Analysis of Influencing Factors

Objective: To investigate the current situation of the demand for geriatric care services of community residents in Beijing and analyze the influencing factors to provide a reference basis for meeting the demand for diversified and professional geriatric care services. Methods: A self-made questionnaire was used to randomly survey 1558 elderly individuals at community health service centers in 8 urban districts where elderly care centers were planned to be built. The influencing factors of the different characteristics of elderly care service needs from three aspects were analyzed using a dichotomous logistic regression model: predisposing, enabling, and, need factors. Results: 69.7% of the elderly required home care services, 22.8% wanted to get care services at elderly care centers, 15.9% wanted to get care services at nursing homes, 12.3% required community care services, and 7.4% didn’t know where to access care services. 68.5% of the elderly required care services for disabilities/semi-disabilities, 58.0% for dementia, 54.7% for common diseases, 34.9% for rehabilitation training, 33.0% for plumbing care, and 7.5% for hospice care. At the same time, there were urban- rural differences in the demand for elderly care services, with suburban elderly having a higher demand for care services than those living in urban areas (P < 0.05). The elderly’s demand for care services was mainly related to age, place of residence, and gender in the causative factors, mode of residence and physical condition among able factors, and mode of care services and care needs among need factors (P < 0.05). Conclusion: The demand for elderly care services was differentiated by factors including place of residence, age, and gender. It is crucial to accurately match the demand for elderly care services, innovate the mode of elderly care services, and improve the service quality to improve the elderly health service system.

Research on Adaptability Analysis of Environmental Space Demand and Design Optimization of Daycare Centers: Taking Chongqing’s Community F as an Example

Currently,there is a lack of research on the detailed environmental spatial design of community daycare centers at the micro level.This study focuses on Community F in Chongqing,using the elderly’s“willingness to demand”as a central aspect.It examines indoor and outdoor environmental space needs at a micro level,considering both functional requirements and spiritual needs based on existing research.The analysis incorporates three adaptive elements:current construction,surrounding environment,and operational management.It explores the feasibility of restructuring spatial layouts,utilizing local resources,and integrating Bayu cultural characteristics.Finally,through design optimization practices,the study proposes three strategies for aging optimization:functional integration and interaction,user-friendly facilities,and emotional connections to place.

RESEARCH ON MUNICIPAL WATER DEMANDS FORECAST

Based on the changing law of municipal water demand,a trigonometric function model for short-term water demand forecast is established using the time-series analysis approach.The method for forecasting water demand during holidays and under unexpected events is also presented.Meanwhile,a computer software is developed.Through actual application,this method performs well and has high accuracy,so it can be applied to the daily operation of a water distribution system and lay a foundation for on-line optimal operation.

Research of Informatization Demands of New Countryside in Poyang Lake Ecological Economic Zone and Related Countermeasures

[Objective] The aim was to survey and analyze informatization demand in new countryside in Poyang Lake Ecological Economic Zone and to propose counter- measures, [Method] A questionnaire was made among farmers on informatization de- mands in different regions in Poyang Lake Ecological Economic Zone and the re- sults were analyzed to propose countermeasures promoting informatization. [Result] With strengthening of information awareness, information demands in rural areas in Poyang Lake Ecological Economic Zone change as follows： Information demand car- rier changes from traditional media to modern media; demand on information content changes from one-way to diversified one; demand of information service changes from one-way transmission to interaction and exchange. However, some problems still exist in informatization process, such as poor infrastructure, dispersed information resources, higher information expense and shortage of information-based talents. Hence, the countermeasures were proposed, as follows： Rational security systems should be established; financing should be as diversified as possible; informatization infrastructure should be reinforced; agricultural economic information and informatiza- tion service system should be established. [Conclusion] The research lays foundation for construction of informatization in new countryside in Poyang Lake Ecological Economic Zone.

Challenges and Demands for College English Teachers Raised by Training All-round Qualified Persons

The latest issue of College English Curriculum Requirements has posed challenges and demands for teachers in terms of linguistic competence, academic knowledge, language skills, professional morality, emotional and attitudinal qualifications, etc., which requires teachers to embrace and handle with active and open-minded responses. Hence, teachers ought to strive to develop and improve their own overall qualifications in collaboration with the long-term development of the subject and of the national higher education, with the need of qualified persons demanded by social development and the students＇ learning. Teachers also ought to form a notion of scientific development by keeping pace with the time, so as to discern the trend of subject development, to form appropriate judgments concerning the social development and to properly regulate their own development.

Link Demands对.NET Framework分布式系统安全性的影响

客观地讲,.NET安全体系是采用全新的模式建立的,更多地考虑了基于.NET的应用系统在安全性和执行效率上的统一,这一点是可以理解的。它提出了基于WEB的分布式应用系统在安全核心技术上新的设计思想。影响.NETFramework应用系统安全性的因素有很多,其中由链接请求(Linkdemands)引起的影响系统安全性的潜在错误相当多。文章分析了Linkdemands可能带来的系统安全性隐患,并就此提出了一些建议。

Ductility demands on buckling-restrained braced frames under earthquake loading

Accurate estimates of ductility demands on buckling-restrained braced frames(BRBFs)are crucial to performance-based design of BRBFs.An analytical study on the seismic behavior of BRBFs has been conducted at the ATLSS Center,Lehigh University to prepare for an upcoming experimental program.The analysis program DRAIN-2DX was used to model a one-bay,four-story prototype BRBF including material and geometric nonlinearities.The buckling- restrained brace(BRB)model incorporates both isotropic and kinematic hardening.Nonlinear static pushover and time- history analyses were performed on the prototype BRBF.Performance objectives for the BRBs were defined and used to evaluate the time-history analysis results.Particular emphasis was placed on global ductility demands and ductility demands on the BRBs.These demands were compared with anticipated ductility capacities.The analysis results,along with results from similar previous studies,are used to evaluate the BRBF design provisions that have been recommended for codification in the United States.The results show that BRB maximum ductility demands can be as high as 20 to 25.These demands significantly exceed those anticipated by the BRBF recommended provisions.Results from the static pushover and time- history analyses are used to demonstrate why the ductility demands exceed those anticipated by the recommended provisions. The BRB qualification testing protocol contained in the BRBF recommended provisions is shown to be inadequate because it requires only a maximum ductility demand of at most 7.5.Modifications to the testing protocol are recommended.