Forwarding Scheme Research Articles

W-GPSR Routing Based on Mobility Prediction for Vehicular Ad-Hoc Network (VANET)

In recent years, Vehicular Ad-Hoc Networks (VANETs) innovation has been regarded as a significant research area. This is owing to the increasing popularity of vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications in the area of Intelligent Transportation System (ITS) to improve traffic management, safety, CO2 emission mitigation, and other applications. A variety of routing protocols for VANETs are being recently developed. More specifically, geographic-based routing algorithms such as Greedy Perimeter Stateless Routing (GPSR) have provoked the most interest in VANETs due to their compatibility with a regularly changing network structure and the highly unsteady nature of automobile nodes. This paper proposes an efficient weight based mobility method in VANET to improve the mechanism of the GPSR protocol through optimizing the greedy forwarding strategy; which is so called O-Greedy Mode. Therefore, the key goal is to achieve the optimal data forwarding paths. The next hop is determined by estimating the neighbors' mobility based on each neighbor's Greedy Link Weight Factor (GLWF). The Weighted GPSR (W-GPSR) based on Mobility Prediction is then evaluated using OMNeT++ simulator with Inet, Veins and SUMO traffic simulator. The results demonstrate the efficiency of W-GPSR in contrast with the traditional existing protocols for essential metrics of Packet Delivery Ratio (PDR), throughput, End-to-End Delay (E2ED), Normalized Routing Load (NRL) and Packet Loss Ratio (PLR).

Performance and Energy Consumption Analysis for UWSNs with Priority Scheduling Based on Access Probability and Wakeup Threshold.

As advancements in autonomous underwater vehicle (AUV) technology unfold, the role of underwater wireless sensor networks (UWSNs) is becoming increasingly pivotal. However, the high energy consumption in these networks can significantly reduce their operational lifespan, while latency issues can impair overall network performance. To address these challenges, a novel mixed packet forwarding strategy is developed, which incorporates a wakeup threshold and a dynamically adjusted access probability for the cluster head (CH). This approach aims to conserve energy while maintaining acceptable network latency levels. The wakeup threshold restricts the frequency of state switching for the CH, thereby reducing energy consumption. Meanwhile, the dynamic access probability regulates the influx of packets to mitigate system congestion based on current network conditions. Furthermore, to accommodate the network's varied transmission demands, packets generated by sensor nodes (SNs) are categorized into two types according to their sensitivity to latency. A discrete-time queueing model with preemptive priority is then established to evaluate the performance of different packets and the CH. Numerical results show how different parameters affect network performance and demonstrate that the proposed mixed packet forwarding mechanism can effectively manage the trade-off between latency and energy consumption, outperforming the traditional mechanism within a specific range of parameters.

Practical Exploration of Engineering-Based Training Equipment and Integration of Theory and Practice in Chemical Engineering Education

This paper mainly discusses the practical exploration of the training equipment and integration of theoretical and practical teaching of chemical engineering education, aiming to solve the problems existing in the current higher vocational chemical engineering education such as unreasonable curriculum, lack of innovation in teaching mode, unclear training objectives, and weak practical teaching links. The paper puts forward strategies such as course development based on the integration of practical teaching, course system construction based on vocational skill training, engineering design of practical training equipment based on post-vocational skills, and manufacturing of chemical engineering training equipment based on the enterprise work process, which is conducive to the realization of “combining practical with work” and provides systematic ideas and methods for the innovation and reform of chemical engineering education.

RESEARCH ON THE STRATEGY OF PROMOTING LOCAL LOCAL CULTURE INHERITANCE BY FAMILY, SCHOOL AND SOCIETY

The cooperative education of home, school and community can provide strong support for the inheritance of local culture. From the perspective of home-school cooperative education between family and society, this paper summarizes and analyzes the significance of jointly promoting local culture inheritance, and puts forward detailed strategies from the level of family, school and society, in order to provide useful reference for local culture inheritance.

A Hybrid Caching Scheme with Dynamic Forwarding Strategy in Information‐Centric Network

In this era of huge data traffic, the information‐centric network (ICN) is a switching strategy from conventional host‐centric communication to a new data‐centric one. In‐network caching an integral part of ICN can reduce the shortcomings of today's location‐based internet paradigm. As ICN has limited caching capability, the decision of optimal routing and content placement are the major challenges. In this study, we suggest a hybrid caching with a dynamic forwarding (HCDF) strategy which takes advantage of the off‐path hash routing scheme and on‐path caching scheme. To facilitate both caching schemes, a fraction of the caching space is allotted in each cache node for local caching. At the user‐end segment, an estimation‐based content placement (ECP) policy is designed using content popularity state and cache node position. This policy helps to cache popular content near the consumer's location using the shared cache space. At the server‐end segment, the HCDF scheme dynamically selects the most appropriate routing strategy among three strategies (symmetric, asymmetric, and multicast) based on hop count and path stretch. To demonstrate the effectiveness of HCDF, extensive simulation on real‐world internet topologies has been carried out. From our investigation, it is observed that the suggested approach exhibits an impressive performance in terms of cache hit, latency, and average link load compared to other standard hash routing and well‐known on‐path caching schemes. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

DCDiff: Dual-Granularity Cooperative Diffusion Models for Pathology Image Analysis.

Whole Slide Images (WSIs) are paramount in the medical field, with extensive applications in disease diagnosis and treatment. Recently, many deep-learning methods have been used to classify WSIs. However, these methods are inadequate for accurately analyzing WSIs as they treat regions in WSIs as isolated entities and ignore contextual information. To address this challenge, we propose a novel Dual-Granularity Cooperative Diffusion Model (DCDiff) for the precise classification of WSIs. Specifically, we first design a cooperative forward and reverse diffusion strategy, utilizing fine-granularity and coarse-granularity to regulate each diffusion step and gradually improve context awareness. To exchange information between granularities, we propose a coupled U-Net for dual-granularity denoising, which efficiently integrates dual-granularity consistency information using the designed Fine- and Coarse-granularity Cooperative Aware (FCCA) model. Ultimately, the cooperative diffusion features extracted by DCDiff can achieve cross-sample perception from the reconstructed distribution of training samples. Experiments on three public WSI datasets show that the proposed method can achieve superior performance over state-of-the-art methods. The code is available at https://github.com/hemo0826/DCDiff.

A128: Research on Safety Risk Management of Youth Short-Term Swimming Training

Purpose: Through the investigation and analysis of the current situation of safety risk management in short-term swimming training for teenagers, to put forward strategies and suggestions for risk prevention and risk management, to improve the awareness of safety risk prevention of swimming training managers, instructors and participants. Methods: Literature analysis, interview, questionnaire and mathematical statistics were used. Results: It was discovered that there were many security risks in the management of short-term swimming training for teenagers: (1) There are security risks in the management of swimming venues and facilities. (2) The lifeguard qualifications do not meet the required standards. (3) The qualification level of swimming training coaches is not high. (4) There are hidden dangers in the safety risk management of swimming training teaching organization, such as the large scale of teaching class system and the lack of safety education in classroom organization. (5) Swimming training managers lack safety training awareness. Simultaneously, an analysis of the factors influencing the safety risks associated with short-term swimming training for teenagers was conducted. This primarily encompasses (1) safety aspects concerning swimming training facilities; (2) safety risk factors pertaining to swimming coaches, such as their qualifications and workload intensity; (3) safety risk factors associated with swimming training institutions; (4) factors impacting the safety risks faced by swimming training managers; and (5) factors affecting the safety risks encountered by students undergoing swimming training. Conclusion/Discussion: (1) There were problems in the safety of the hardware facilities of some swimming training institutions. (2) There were safety problems in the health prevention of swimming training institutions. (3) Swimming training institutions had security risks in personnel management. (4) Swimming students' self-rescue abilities were weak. (5) The water safety education of parents with children enrolled in swimming classes was insufficient. We put forward the following countermeasures and suggestions: (1) The hardware facilities at swimming training institutions have been strengthened and improved to ensure optimal conditions for training. (2) Health facilities are staffed with specialized personnel and equipped with relevant treatment options to ensure the safety and well-being of all participants. (3) Staffing levels at venues have been increased to provide adequate support for all activities. (4) Self-rescue skills are now incorporated into daily teaching practices, promoting a culture of safety among students. (5) Efforts have been made to enhance students' awareness of water safety through various educational initiatives.

An evaluation of random forest based input variable selection methods for one month ahead streamflow forecasting

In the development of data-driven models for streamflow forecasting, choosing appropriate input variables is crucial. Although random forest (RF) has been successfully applied to streamflow forecasting for input variable selection (IVS), comparative analysis of different random forest-based IVS (RF-IVS) methods is yet absent. Here, we investigate performance of five RF-IVS methods in four data-driven models (RF, support vector regression (SVR), Gaussian process regression (GP), and long short-term memory (LSTM)). A case study is implemented in the contiguous United States for one-month-ahead streamflow forecasting. Results indicate that RF-IVS methods enable to acquire enhanced performance in comparison to widely used partial Pearson correlation and conditional mutual information. Meanwhile, performance-based RF-IVS methods appear to be superior to test-based methods, and the test-based methods tend to select redundant variables. The RF with a forward selection strategy is finally recommended to connect with GP model as a promising combination having potential to yield favorable performance.

Research on the Mode of E-Commerce Assisting Agricultural Innovation and Entrepreneurship under the Background of Platform Economy—A Case Study of E-Commerce Assisting Farmers in Wenchuan County

This paper takes the case of e-commerce aiding agriculture in Wenchuan County as an example to analyze the specific practices and economic benefits of e-commerce aiding agriculture in Wenchuan County. It is discovered that there exist problems such as backward infrastructure construction, shortage of skilled talents, and insufficient market credibility in e-commerce aiding agriculture in Wenchuan County. According to the innovation theory and in combination with the background of platform economy, this paper puts forward strategies and suggestions such as innovating the supply of industrial space, strengthening the introduction and cultivation of talents, and guaranteeing the quality and safety of agricultural products, with the aim of providing references for the development of rural e-commerce.

Interest Classification on Named Data Network Using the Supervised Learning Method

Named Data Network (NDN) is a next-generation network architecture that shifts the traditional data communications paradigm Unlike conventional networks that rely on IP addresses, NDN delivers content based on data names rather than specific locations. In NDN, consumers express their requests by sending interest packets containing content names. These names are then propagated through the network nodes, which forward them to the appropriate destinations. The forwarding strategy in an NDN network plays a crucial role in ensuring efficient data delivery. This strategy includes a set of rules that determine the next hop for each interest packet. These rules are designed to optimize the forwarding process, minimizing delays and improving network efficiency. However, if the forwarding strategy is implemented without accurately identifying the appropriate face (i.e., the network interface) to forward interests toward the producer or the nearest cache node, it can lead to significant delays and packet drops. This, in turn, negatively impacts Quality of Service (QoS) parameters and the overall performance of the NDN network. This study applies supervised learning to classify consumer-requested interests to overcome this issue. This technique leverages several related variables to accurately classify these interests. The outcomes of the conducted research demonstrated that raw data from the mini-NDN output can be processed and transformed into a usable dataset. This data is then utilized to train a classification model with supervised learning. In a scenario with 9 NDN nodes and varying numbers of interests, distributed both uniformly and according to Zipf's law, the Random Forest model performs effectively, achieving an accuracy rate of 86.2% with an error rate of 14.8%.

Data-Driven Bi-Directional Lattice Property Customization and Optimization.

Customizing and optimizing lattice materials poses a challenge to designers. This study proposed a data-driven generative method to customize and optimize lattice material. The method utilizes subdivision modeling to parametrically describe lattice morphologies and skeletons. Next, the homogenization method is employed to analyze elastic moduli for collecting a dataset. Then, a two-tiered machine learning (ML) framework is proposed to predict the elastic modulus for a forward design. The first-tier model employs polynomial regression to estimate relative density, which serves as an additional input feature for the second-tier model. The prediction accuracy of the second-tier model is improved through the additional inputs. The forward and reverse design strategies offer a flexible and accurate means of tailoring lattice properties to meet specific performance requirements. Two case studies demonstrate the practical value of the framework: customizing a lattice material to achieve a desired elastic modulus and optimizing the mechanical performance of lattice materials under relative density constraints. The results show that the prediction accuracy of the elastic modulus using the two-tiered ML model achieved an error of less than 10% compared to finite element analysis, demonstrating the reliability of the proposed approach. Furthermore, the optimization design achieved up to a 25% improvement in mechanical performance compared to conventional lattice configurations under the same relative density constraints. These findings underscore the advantages of combining generative design, machine learning, and genetic algorithms to navigate complex design spaces and achieve enhanced material performance.

Combined carbapenem resulted in a 4.48-fold increase in valproic acid clearance: a population pharmacokinetic model in Chinese children and adults with epilepsy or after neurosurgery.

Our study aims to explore the pharmacokinetics of valproic acid (VPA) in Chinese patients with epilepsy or after neurosurgery and establish a robust population pharmacokinetics (PPK) model. The PPK model was developed using nonlinear mixed-effects modeling, incorporating a total of 615 VPA plasma concentration data points from 443 Chinese epilepsy or after neurosurgery patients. A one-compartment model with an additive residual model was established. Forward addition and backward elimination strategies were used to assess the impact of covariates on the model parameters. Goodness-of-fit plots, bootstrap, visual predict check and normalized prediction distribution errors were used for model validation. In the final model, the apparent clearance (CL) was estimated using the following formula: (gender = 0.121 when is female, otherwise = 0; CBP = 1.50 when combined with carbapenems, otherwise = 0; IND2 = 0.15 when combined with oxcarbazepine, carbamazepine, phenobarbital, or phenytoin, otherwise = 0). The volume of distribution (Vd) was estimated using the formula: . Comedication with carbapenems could increase VPA clearance by 4.48 times, and comedication with oxcarbazepine could enhance VPA clearance by 116%. Besides, creatinine and albumin could affect VPA clearance. Goodness-of-fit plots, bootstrap, visual predict check and normalized prediction distribution showed acceptable data fit, stability, and predictability of the model. In our study, a PPK model was utilized to attain a more comprehensive insight into these variables, improving the accuracy and individualization of VPA therapy in Chinese patients with epilepsy or after neurosurgery.

Infrastructuring informal urbanism: Negotiation of water, electricity, and natural gas in urban villages in Chengdu, China

Infrastructure such as water, electricity, and natural gas fundamentally underpins informal housing and industrial development in urban villages. Yet how the infrastructure is built, maintained, and governed, and what are the underlying mechanisms, remain peripheral to existing literature and policy agenda. This study addresses this gap by incorporating a socio-technical approach to infrastructure into informal urbanism to understand the negotiation of water, electricity, and natural gas in two neighboring urban villages in Chengdu, China. Four rounds of fieldwork and in-depth interviews with various stakeholders found highly precarious provision of infrastructure in urban villages. Its spatial layout, facilities, charges, quality control, and maintenance rest uneasily on, and then in turn shape, the development of informal renting markets and industries in different urban villages, especially when considering the cross-sectional interactions between different types of infrastructure. These processes are dominated by stakeholders’ commercial logics embedded in informal urbanism, including the urban village and infrastructure providers’ profit-seeking strategies, enterprises and migrants’ cost-saving behaviors, and the governments’ purposive absence in governing infrastructure, which leads to difficulties in meeting urban village residents’ needs for qualified infrastructure. This study unravels the “black box” of infrastructure in urban villages and puts forward inclusive planning strategies to promote infrastructure in urban villages.

On the clinical interpretation of overground gait stability indices in children with cerebral palsy

Several indices have been devised to quantify a person’s stability from its gait pattern during overground walking. However, clinical interpretation of the indices is difficult because the link between being stable and adopting a mechanically stable gait pattern may not be straightforward. This is particularly true for one of these indices, the margin of stability, for which opposite interpretations are available in the literature. We collected overground walking data in two groups of 20 children, with unilateral cerebral palsy (CP) and typically developing (TD), for two conditions, on flat and on uneven grounds (UG). We postulated that TD children were more stable during gait than children with CP and that both groups were more stable on flat compared to UG. We explored the coherent association between several indices and the two postulates to clarify clinical interpretation. Our results showed that increased margin of stability, increased amplitude of the whole-body angular momentum, decreased duration of single limb support, increased variability (gait kinematics, step length, and step width) were associated with reduced stability for both postulates. However, results for the margin of stability were paradoxical between the sides in the CP group where small margin of stability was indicative of a fall forward strategy on the affected side rather than improved stability. Whole-body angular momentum and duration of single limb support appeared as the most sensitive indices. However, walking speed influenced these and would need to be considered when comparing groups of different walking speed.

Research on Measures to Improve Students’ Learning Effectiveness by Improving the Classroom Teaching Model

The importance of an effective classroom teaching model in enhancing students’ learning does not need to be overemphasized. With the development of society and the evolution of educational needs, the demand for innovative teaching strategies to meet different learning needs is also constantly developing. This article discusses various classroom teaching models, including traditional, flipped classroom, and project-based learning, and studies their advantages and disadvantages. By summarizing past literature, the study identifies the gaps in the current teaching model and puts forward strategies to solve these shortcomings. The research results show that although there is no single model that is universally valid, a hybrid method combining different models may improve learning outcomes. The government needs to formulate policies to emphasize the importance of teaching, schools need to provide a platform for teachers’ communication and students’ practice, and teachers also need to use scientific and technological tools to attract students’ attention in the classroom.

Research on Teaching Reform of Landscape Engineering Course based on the Concept of CDIO

With the advancement of new engineering construction, it is urgent to explore the teaching reform of professional courses in the cultivation of landscape architecture professionals in combination with industry needs. In order to solve the problems existing in the current Landscape Engineering course, such as traditional teaching methods, insufficient student interest, lack of practical links, and the disconnection between teaching content and industry demand. This study discusses the teaching reform of the Landscape Engineering course based on the CDIO (Conceive-Design-Implement-Operate) concept, aiming at solving the problems mentioned. Through the integration of CDIO mode, the core competencies that students should have are defined, including environmental landscape design and planning, innovative thinking, project management, and so on. The research emphasizes project-driven learning, interdisciplinary knowledge integration, and practical skill training, and puts forward strategies such as teacher training and professional development support to ensure the implementation of the reform. The purpose of the reform was to improve students’ professional ability and employment competitiveness, promote the improvement of education quality and the sustainable development of the industry, and exert a positive impact on landscape engineering education and industry progress.

Research on The Front Line Staff Recruitment Problem of HDL Catering Enterprises

With the rapid development of China's catering industry, HDL catering enterprises as the leading brand in the industry, its frontline staff recruitment problems become particularly prominent. Under the background of the continuous expansion of the industry scale and the continuous improvement of the chain rate, the demand for professional talents of HDL catering enterprises is growing, especially the demand for store manager talents who are experienced and can quickly adapt to the business operation mode. However, the high turnover rate and employee turnover rate of the catering industry, coupled with the lack of competitiveness of compensation and benefits compared with other industries, as well as the repetitive and hard work of the work content, make it difficult for employees to achieve sustainable growth and career development in the work, thus aggravating the problem of talent shortage. Through literature review and current situation, this paper analyzes the problems existing in the process of recruitment of front line employees in HDL catering enterprises, and further analyzes the influence of internal management, market environment factors of employees on the recruitment effect. In order to improve the efficiency and quality of recruitment, this study puts forward strategies to optimize the recruitment process, expand diversified recruitment channels, innovate selection methods and improve the professional quality of recruitment teams.

Frieght forwarding strategies for perishable goods with reference to Global Tide Shipping and Logistics in Cochin

Frieght forwarding strategies for perishable goods with reference to Global Tide Shipping and Logistics in Cochin

Research on investment and financing risk problems and countermeasures of PPP construction projects

This study analyzes financing costs, capital liquidity, policy changes and contract execution risks in PPP project investment and financing, and puts forward strategies such as optimizing financing platforms, reducing costs, strengthening regulations, regulatory coordination and improving prevention capabilities. By exploring the causes and effects of risks, combined with domestic and foreign cases to verify the effectiveness of the strategy. This study enriches the theory of PPP risk management, provides guidance for the practical operation of the project, and promotes the healthy development of the PPP project.

Family Involvement in Routine Services for Individuals With Severe Mental Illness: Scoping Review of Barriers and Strategies.

The authors investigated barriers to practices that promote family involvement in mental health services, focusing on individuals with severe mental illness, their families, and mental health providers. Additionally, the authors sought to identify strategies to facilitate family involvement in mental health provision to highlight the engagement process in routine practice and propose future directions for organizations to establish a family-friendly environment. Systematic searches for literature published from January 1990 to March 2023 were conducted in PsycInfo, PubMed, CINAHL, Sociological Abstracts, and Scopus databases. Gray literature searches and backward and forward snowballing strategies were also used. Forty-six articles were reviewed, revealing contextual backgrounds and engagement practices that hindered family involvement. Inconsistencies in family involvement stemmed from organizational culture, societal attitudes, and providers' negating of family expertise. Uncertainty regarding confidentiality policies and the absence of practice guidelines posed challenges for providers. Negative experiences of families within the mental health system along with variable commitment also hampered involvement. Some service users declined family involvement because of privacy concerns and differing expectations regarding the extent of involvement. Promoting a shared culture of family work, integrating practice standards, and engaging in professional development activities emerged as key strategies. A gap exists between implementing policies and practices for family involvement in mental health treatment. Without cultural and organizational shifts in support of working with families, the uptake of family involvement practices will remain inadequate. Each stakeholder has different perceptions of the barriers to family involvement, and family involvement will remain elusive without a shared agreement on its importance.