线上中文学习平台Lingo Bus和Lingo Ace比较研究

Lingo Bus和Lingo Ace平台是当前受到市场青睐的知名线上中文学习平台。对两个学习平台的建设、教学和管理营销三个方面的情况进行比较研究后发现:两个平台均通过线上直播课程面向海外青少儿教授中文,均建立了各自的官网和客户端,在品牌定位、课程资源体系、选课方式和学习者服务模式等方面的设计上都有差异,针对教师选拔、培训的侧重点和严格程度也有不同的标准;两个平台均注重通过口碑、新闻软文和社交媒体等途径进行营销,但在推广方式和营销经费投入力度方面做法不同。线上中文学习平台应建设本土化和标准化教学资源,提升系统稳定性和智能化水平,完善教师管理机制,建立良好服务体系,组建本土团队,实施精准营销等发展策略。

Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

Entropy Assessment on Environmental Influence of Condense Heat in Recovery System in Air-Conditioning Refrigerating Machine

This paper presented an entropy evaluation method for the influences of condense heat recovery system on the environment.Aiming at the damage of the condense heat to the environment,an entropy of resource loss and an emission entropy from the condense heat recovery system in the air conditioning refrigerating machine were introduced.For the evaluation of the entropies,we developed a new algorithm for the parameter identification,called the composite influence coefficient,based on the Least Squares Support Vector Machine method.By simulation,the numerical experiments shows that the Least Squares Support Vector Machine method is one of the powerful methods for the parameter identification to compute the damage entropy of the condense heat,with the largest training error being-0.025(the relative error being-3.56%),and the biggest test error being 0.015(the relative error being 2.5%).

Impact of summer office set air-conditioning temperature on energy consumption and thermal comfort

To explore the relationship between summer office set air-conditioning temperature and energy consumption related to air conditioning use to provide human thermal comfort,a comparison experiment was conducted in three similar offices at temperatures of 24,26 and 28 ℃ respectively. A thermal comfort questionnaire survey was conducted. It is demonstrated that air-conditioner energy consumption at the set temperature of 28 ℃ is 113% and 271% lower than at 26 ℃ and 24 ℃,respectively. A linear relationship exists between air-conditioner energy consumption and the indoor and outdoor temperature difference. When comfortably dressed,over 80% of research participants accept the set temperature of 28 ℃. The regression analysis leads to a neutral temperature of 26.2 ℃ and an acceptable temperature of 28.2 ℃ for over 80% of the research participants subjects,indicating that the current 26 ℃ set temperature for offices in summer,required by Chinese General Office of the State Council,can be increased to 28 ℃. Moreover,analysis of predicted mean vote(PMV) index shows that a set temperature of 27 ℃,not 26 ℃,is sufficiently comfortable for office staff wearing long-sleeve shirts,long pants and leather shoes.

A fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of communication link in IoT-enabled building automation systems

Internet of Things(IoT)technologies are increasingly implemented in buildings as the cost-effective smart sens-ing infrastructure of building automation systems(BASs).They are also dispersed computing resources for novel distributed optimal control approaches.However,wireless communication networks are critical to fulfill these tasks with the performance influenced by inherent uncertainties in networks,e.g.,unpredictable occurrence of link failures.Centralized and hierarchical distributed approaches are vulnerable against link failure,while the robustness of fully distributed approaches depends on the algorithms adopted.This study therefore proposes a fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of com-munication link in IoT-enabled BASs.The distributed algorithm is adopted that agents know their out-neighbors only.Agents directly coordinate with the connected neighbors for global optimization.Tests are conducted to test and validate the proposed approach by comparing with existing approaches,i.e.,the centralized,the hierarchical distributed and the fully distributed approaches.Results show that different approaches are vulnerable against to uncertainties of communication link to different extents.The proposed approach always guarantees the optimal control performance under normal conditions and conditions with link failures,verifying its high robustness.It also has low computation complexity and high optimization efficiency,thus applicable on IoT-enabled BASs.

Selection of Weather Parameters for Air-Conditioning System Design for Buildings with Long Thermal Lag

Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.

The Experiment and Simulation of Solid Desiccant Dehumidification for Air-Conditioning System in a Tropical Humid Climate

The aim of this research was to study and design a solid desiccant dehumidification system suitable for tropical climate to reduce the latent load of air-conditioning system and improve the thermal comfort. Different dehumidifiers such as desiccant column and desiccant wheel were investigated. The ANSYS and TRASYS software were used to predict the results of dehumidifiers and the desiccant cooling systems, respectively. The desiccant bed contained approximately 15 kg of silica-gel, with 3 mm average diameter. Results indicated that the pressure drop and the adsorption rate of desiccant column are usually higher than those of the desiccant wheel. The feasible and practical adsorption rate of desiccant wheel was 0.102 kgw/h at air flow rate 1.0 kg/min, regenerated air temperature of 55?C and at a wheel speed of 2.5 rpm. The humidity ratio of conditioning space and cooling load of split-type air conditioner was decreased to 0.002 kgw/kgda (14%) and 0.71 kWth (19.26%), respectively. Consequently, the thermal comfort was improved from 0.5 PMV (10.12% PPD) to 0.3 PMV (7.04% PPD).

An Energy-Saving Control Strategy on Central Air-Conditioning System

An energy-saving control strategy based on predictive control for central air-conditioning systems is proposed in this paper. The cold load model is developed to describe the dynamic characteristics of temperature control systems, and then parameters in the cold load model and in the central air-conditioning system model are estimated. Generalized predictive control (GPC) is used to establish an optimization model to minimize the consumption of energy and the control error of temperature. The simulated annealing (SA) algorithm, combined with quadratic programming, is adopted to solve the optimal problem. Contrasted with the simulation of traditional PID control, the results prove the effectiveness of this proposed strategy.

Application of Fuzzy Comprehensive Evaluation to Air-conditioning Competitive Power Analysis

As the conceptual design of air-conditioning is done using the theory of Quality Function Deployment (QFD),cus- tomer requirements should be understood and the product competitive power be analyzed as exactly as possible for new product de- signing.Lots of information in the process of this research is fuzzy and uncertain,but traditional QFD can not deal with it well. Fuzzy theory can solve the problem.So a fuzzy model for analyzing product competitive power is formulated in this paper to im- prove traditional QFD,after that it is applied to analyze air-conditioning competitive power.When air-conditioning competitive power is analyzed using this model,firstly the importance weight of the customer requirements o fair-conditioning is determined us- ing the Analytic Hierarchy Process (AHP) weighting process,then air-conditloning competitive power is evaluated using fuzzy comprehensive evaluation.It is proved that the model is feasible and has good applicability.

Application of Dual Throttling Air-Conditioning System to Explosion-Proof Frequency Converter

An explosion-proof dual throttling air-conditioning system was put forward to solve the heat dissipation and internal dewing problems of explosion-proof frequency converter in the underground coal mine. This study investigated the feasibility and benefits of explosion-proof dual throttling cooling and dehumidification air-conditioning system applied to the explosion-proof frequency converter. The physical model of dual throttling air-conditioning system was established and its performance parameter was described by mathematical method. The design calculation of the system has also been done. The experimental result showed that the system reached the steady state at the refrigeration mode after running 45 min, and the maximum internal temperature of the flame-proof cavity was 31.0 ℃. The system reached the steady state at the dehumidification mode after running 37 min. The maximum internal relative humidity and temperature of the flame-proof cavity were 33.4% and 36.3 ℃, respectively. Therefore, the proposed system had excellent ability of heat dissipation and avoided internal dewing. Compared with water cooling system, it was more energy-saving and economical. The airflow field of dual throttling air-conditioning system was also studied by CFD simulation. It was found that the result of CFD numerical simulation was highly consistent with the experimental data.

Simulation of Artificial Intelligence for Automotive Air-conditioning System

The artificial intelligence is applied to the simulation of the automotive air-conditioning system ( AACS )According to the system's characteristics a model of AACS, based on neural network, is developed. Different control methods of AACS are discussed through simulation based on this model. The result shows that the neural- fuzzy control is the best one compared with the on-off control and conventional fuzzy control method.It can make the compartment's temperature descend rapidly to the designed temperature and the fluctuation is small.

Point Cloud Based Semantic Segmentation Method for Unmanned Shuttle Bus

The complexity of application scenarios and the enormous volume of point cloud data make it difficult to quickly and effectively segment the scenario only based on the point cloud.In this paper,to address the semantic segmentation for safety driving of unmanned shuttle buses,an accurate and effective point cloud-based semantic segmentation method is proposed for specified scenarios(such as campus).Firstly,we analyze the characteristic of the shuttle bus scenarios and propose to use ROI selection to reduce the total points in computation,and then propose an improved semantic segmentation model based on Cylinder3D,which improves mean Intersection over Union(mIoU)by 1.3%over the original model on SemanticKITTI data;then,a semantic category division method is proposed for road scenario of shuttle bus and practical application requirements,and then we further simplify the model to improve the efficiency without losing the accuracy.Finally,the nuScenes dataset and the real gathered campus scene data are used to validate and analyze the proposed method.The experimental results on the nuScenes dataset and our data demonstrate that the proposed method performs better than other point cloud semantic segmentation methods in terms of application requirements for unmanned shuttle buses.Which has a higher accuracy(82.73%in mIoU)and a higher computational efficiency(inference speed of 90 ms).

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

Research on the Arrangement of Dew Point Temperature Detectors of Capillary Plane Radiation Air-Conditioning

Based on analysis of the reason and process of condensation on ceiling radiant cooling panels, two kinds of arrangement of detectors are put forward. The physical model is established, the results show that detectors are arranged as the form of triangle is more suitable. It can not only satisfy the use requirement but also it is economical and practical. Finally we can conclude that the inlet water temperature 0.5°C higher than dew point temperature is safe and reliable.

Analysis of Solar Direct-Driven Organic Rankine Cycle Powered Vapor Compression Cooling System Combined with Electric Motor for Office Building Air-Conditioning

Solar energy powered organic Rankine cycle vapor compression cycle(ORC-VCC)is a good alternative to convert solar heat into a cooling effect.In this study,an ORC-VCC system driven by solar energy combined with electric motor is proposed to ensure smooth operation under the conditions that solar radiation is unstable and discontinuous,and an office building located in Guangzhou,China is selected as a case study.The results show that beam solar radiation and generation temperature have considerable effects on the system performance.There is an optimal generation temperature at which the system achieves optimum performance.Also,as a key indicator,the cooling power per square meter collector should be considered in the hybrid solar cooling system in design process.Compared to the vapor compression cooling system,the hybrid cooling system can save almost 68.23%of electricity consumption.

Analysis of Fresh Air Volume of Air-conditioning System for Railway Vehicles

The relevant standard requirements both in domestic and abroad provide the basis for designing air-conditioning system of railway vehicles present. However, there are great differences in the fresh air volume indicators among different standards requirements, and the requirements of each vehicle procurement contracts are also different. The design of air-conditioning become difficult above these. In this paper, the fresh air volume of different type railway vehicles is analyzed from health and equipment electricity consumption according to the railway vehicles air-conditioning system standard requirements in domestic and abroad. Some advises for designing air-conditioning system of railway vehicles through the fresh air volume calculation and comparison for domestic air-conditioning system of railway vehicles was provided.

Autonomous bus services:current research status and future recommendations

Implementing autonomous bus services in several cities has garnered substantial research attention worldwide.However,the benefits and challenges of this emerging mode remain insufficiently understood.Consequently,VOSviewer was employed for a bibliometric analysis involving 300 publications,investigating the associations among authors,journals,and keywords.Subsequently,we comprehensively reviewed the current state of research on two topics and proposed future recommendations.Results indicate that the first document related to autonomous bus services was published in 2009.Most user attitude-related research data are obtained via questionnaires and analyzed using statistical techniques.Autonomous bus services are expected to benefit passengers regarding travel time,cost,safety,etc.,while passenger preferences are inconsistent.However,integrating the service into existing bus systems requires careful consideration of the schedule sequences.Notably,modular autonomous bus services present a new opportunity for the further optimization of bus services.In future studies,standardized data acquisition procedures should be developed to achieve comparable results.Regarding traveler choice behavior,the effect of specific autonomous bus service policies over time and the heterogeneity due to cultural or social contexts across regions should be assessed.To further promote autonomous bus services,based on fluctuating travel demands,the effects of vehicle capacity,speed,and cost of fleet composition should be evaluated comprehensively to optimize the bus network and schedule sequence.Owing to the protracted nature of the transition from conventional to fully autonomous buses,one should prioritize semi-autonomous bus services.Another essential future research direction is to integrate modular autonomous bus assembly or disassembly strategies with different fine-grained operation optimization techniques in various scenarios.

Shaping a New Level of Bus Service under a Novel Concept of Bus Interaction: A Meta-Review

Public transport services, particularly bus services, play an important role in a sustainable transportation system. However, despite various efforts, bus ridership has decreased. The appearance of shared and on-demand vehicle services is one of the main reasons for this issue. In addition, bus tourism services have been successfully developed to meet the exigent needs of tourists. Therefore, a new level of daily bus service is necessary to adapt to the changing demands of customers. Bus interaction (BI) plays an important role in bus services. Nevertheless, the conventional concept of BI mainly refers to users, physical interaction, and safety, but it does not address non-users, non-physical interactions, service quality, and other aspects. This study aims to elaborate on a new concept of bus services. Based on this, we developed a theoretical framework for BI. A meta-analysis was then conducted to identify the achievements and untouched aspects. The results of this study provide three main contributions. First, an unprecedented novel concept of BI is defined, including 13 types of interactions. Second, a comprehensive theoretical framework of BI is established based on the relationships between eight sustainable bus system sub-aspects and 13 BI types. Third, based on the theoretical framework and findings of the reviewed studies, a common finding comprehensive framework of BI is completed, which is accompanied by 1) key findings of the 13 BI types, 2) conclusions of traffic conditions affecting BI research, 3) BI research gaps, and 4) 16 main suggestions for future BI research.

Modified Satin Bowerbird for Distributed Generation in Remotely Controlled Voltage Bus

The distributed generators in the radial distribution network are to improve the Grid performance and its efficiency.These Distributed Generators control the PV bus;it is converted as a remote controlled PVQ bus.This PVQ bus reduces the power loss and reactive power.Initially,the distributed generators were placed in the system using mathematical modelling or the optimization.This approach improves the efficiency but it has no effect in loss minimization.To minimize the loss the reconfigured network with Genetic algorithm based Distributed generator placement proposed as existing work.This approach minimizes the loss effectively;but the genetic algorithm takes more time for DG placement.Hence,in this,the network reconfiguration is performed using a modified Satin bower bird algorithm after DG placement and DG sizing.Initially,the sensitive analysis applied the loadflow analysis to identify the optimal placement for the distributed generator.Then,the modified Satin Bowerbird(SBO)used for the network reconfiguration.This approach minimizes the loss of effectively by combining the network reconfiguration process.The proposed modified SBO-based network reconfiguration implemented on standard bus systems 33 and 69 using MATLAB R2021b version under Windows 10 environment.The proposed approach compared with the existing work in terms of real power loss and loss reduction.

Investigating the Effects of Slack Bus Selection in Load Flow Studies: A Comparative Analysis of Robust and Weak Grids

Load flow studies play a critical role in the analysis of power systems. They enable the computation of voltage, current, and power flows in a power system. They provide valuable insights into the steady-state performance of the power system under different operating conditions. Choosing a slack bus is a vital step in conducting load flow simulations. A slack bus is a PV bus that includes a generator and is used to balance real and reactive power during load flow studies. Many studies have been conducted on the selection of slack buses in load flow analysis. However, varied conclusions regarding the impact on system losses and power flows were obtained during these studies. Therefore, using the IEEE-14 bus test system, this study investigated the effects of slack bus selection in strong and weak grids by alternating slack buses among PV buses and observing the effects on bus voltage magnitude, bus voltage phase angle, total power flows, and active and reactive power losses. The study noted that the effect of slack bus selection on these system quantities is contingent upon the voltage stability of the grid. Whereas in a robust grid, system losses and power flows remained constant irrespective of the choice of slack bus, a weak grid experienced some variations in these system quantities under similar circumstances. The simulation results led to the conclusion that, to a large extent, the voltage stability of the grid plays a significant role in determining the degree to which slack bus selection affects system losses and other quantities in load flow studies.