Research on Enterprise Legal Service Strategy Based on Compliance Management Optimization

With the background of enterprise compliance management,this paper discusses how to improve the level of enterprise legal service and reduce enterprise legal risks by optimizing the compliance management system.It aims to analyze the current situation and existing problems of enterprise legal services through the analysis of the importance of compliance management.Furthermore,it delves into the case of enterprise legal service strategy based on compliance management optimization to verify the effectiveness and feasibility of enterprise legal service strategy.

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

The Chinese Consumers’Service Quality Satisfaction Differences of Cruise Tourism and Precision Marketing Strategy

The paper selected Chinese Cruise Line as the case study. Having based on the survey data of Chinese cruise tourism consumers, the factor analysis method, one-way analysis of variances method, cluster analysis method, and other quantitative and qualitative methods were taken to analyze Chinese consumers’ satisfaction differences of cruise tourism service quality with different segmentation markets and clusters markets, and the reasons of satisfaction differences were also explored. Then precision marketing strategy of Chinese cruise tourism with different segmentation markets and clusters markets from the supply-side reform perspective was discussed. The purpose of current research was to provide suggestions of precision management and precision marketing of Chinese cruise tourism for relevant enterprises and government departments.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Implementation Strategy of“Eight in One”of Integrated Medical and Care Service System in China:A Case Study of Anshan City of Liaoning

With the gradual intensification of aging in China,the issue of elderly care has become the primary issue that needs to be urgently solved in society.The construction of a reasonable and scientific integrated medical and care service system can not only efficiently allocate medical resources and services,but also better meet the needs of the elderly.Due to the involvement of multiple disciplines such as architecture,sociology,psychology,and behavioral science in the construction of the system,as well as the restriction of various objective factors such as medical capacity,spatial scale,and operating costs,the government and elderly care institutions have always been unable to find the best solution for how to scientifically and reasonably construct an integrated medical and care service system.This paper is based on Anshan City,Liaoning Province,which has prominent aging issues and distinct characteristics of the elderly population.Through extensive field research in elderly care institutions,and face-to-face communication with personnel from relevant government departments such as the Municipal Commission on Aging,the Civil Affairs Bureau,the Health Commission,the Medical Insurance Bureau,and the Human Resources and Social Security Bureau,it truly understands the problems that arise in the construction of the urban integrated medical and care service system.From three aspects:urban situation,institutional situation and the needs of the elderly,it is proposed to establish a clear departmental linkage mechanism with clear rights and responsibilities,a policy guarantee mechanism tailored to local conditions,a multi-measure operation mechanism,a technology first intelligent response mechanism,a warm and efficient service mechanism for the people,an overall layout mechanism,an evaluation and supervision mechanism for full process control,and a talent supply mechanism of external introduction and internal training.It aims to provide reference for the construction of an integrated medical and care service system in similar cities.

Equilibrium Strategy of the Pursuit-Evasion Game in Three-Dimensional Space

The pursuit-evasion game models the strategic interaction among players, attracting attention in many realistic scenarios, such as missile guidance, unmanned aerial vehicles, and target defense. Existing studies mainly concentrate on the cooperative pursuit of multiple players in two-dimensional pursuit-evasion games. However, these approaches can hardly be applied to practical situations where players usually move in three-dimensional space with a three-degree-of-freedom control. In this paper,we make the first attempt to investigate the equilibrium strategy of the realistic pursuit-evasion game, in which the pursuer follows a three-degree-of-freedom control, and the evader moves freely. First, we describe the pursuer's three-degree-of-freedom control and the evader's relative coordinate. We then rigorously derive the equilibrium strategy by solving the retrogressive path equation according to the Hamilton-Jacobi-Bellman-Isaacs(HJBI) method, which divides the pursuit-evasion process into the navigation and acceleration phases. Besides, we analyze the maximum allowable speed for the pursuer to capture the evader successfully and provide the strategy with which the evader can escape when the pursuer's speed exceeds the threshold. We further conduct comparison tests with various unilateral deviations to verify that the proposed strategy forms a Nash equilibrium.

Data Center Traffic Scheduling Strategy for Minimization Congestion and Quality of Service Guaranteeing

According to Cisco’s Internet Report 2020 white paper,there will be 29.3 billion connected devices worldwide by 2023,up from 18.4 billion in 2018.5G connections will generate nearly three times more traffic than 4G connections.While bringing a boom to the network,it also presents unprecedented challenges in terms of flow forwarding decisions.The path assignment mechanism used in traditional traffic schedulingmethods tends to cause local network congestion caused by the concentration of elephant flows,resulting in unbalanced network load and degraded quality of service.Using the centralized control of software-defined networks,this study proposes a data center traffic scheduling strategy for minimization congestion and quality of service guaranteeing(MCQG).The ideal transmission path is selected for data flows while considering the network congestion rate and quality of service.Different traffic scheduling strategies are used according to the characteristics of different service types in data centers.Reroute scheduling for elephant flows that tend to cause local congestion.The path evaluation function is formed by the maximum link utilization on the path,the number of elephant flows and the time delay,and the fast merit-seeking capability of the sparrow search algorithm is used to find the path with the lowest actual link overhead as the rerouting path for the elephant flows.It is used to reduce the possibility of local network congestion occurrence.Equal cost multi-path(ECMP)protocols with faster response time are used to schedulemouse flows with shorter duration.Used to guarantee the quality of service of the network.To achieve isolated transmission of various types of data streams.The experimental results show that the proposed strategy has higher throughput,better network load balancing,and better robustness compared to ECMP under different traffic models.In addition,because it can fully utilize the resources in the network,MCQG also outperforms another traffic scheduling strategy that does rerouting for elephant flows(namely Hedera).Compared withECMPandHedera,MCQGimproves average throughput by 11.73%and 4.29%,and normalized total throughput by 6.74%and 2.64%,respectively;MCQG improves link utilization by 23.25%and 15.07%;in addition,the average round-trip delay and packet loss rate fluctuate significantly less than the two compared strategies.

Design Strategy of Digital Display Based on the Concept of Service Design

Based on the analysis of the concept,core,research content and method of service design,this paper explains the necessity of service design to participate in digital display,and further discusses how service design integrates with digital display,how to redesign the digital display system under the intervention of service design,and how to integrate user needs into it at all times.Finally,the design strategy of digital display under the concept of service design is proposed.

Optimization Strategies of Beijing Elderly Care Service Stations Based on Questionnaire Survey Method: A Case Study of Zhanlan Road Street of Xicheng District

4 elderly care service stations in Zhanlan Road Street,Xicheng District,Beijing are selected,and questionnaires are designed and distributed to the surrounding elderly population to understand their needs and satisfaction with the station environment.By observing elderly care service stations on site,the characteristics,obstacles,and shortcomings of the environment are recorded,and relevant data are collected and analyzed,such as the characteristics of the elderly population being interviewed,the planning and design data of the station environment,and the distribution of service facilities.The overall characteristics of the spatial environment of elderly care stations are summarized,and renovation measures and optimization suggestions are provided for the current shortcomings,thereby providing some basis for the spatial design of community elderly care service stations in the future.

Research on the Strategy of Promoting Daqing to Create a National Public Employment and Entrepreneurship Service Demonstration City

Based on the research on the basic status quo of the construction of public employment and entrepreneurship service system in Daqing, this paper analyzes the problems existing in Daqing’s establishment of a national public employment and entrepreneurship service demonstration city, and gives countermeasures and suggestions from three levels: optimizing the public employment and entrepreneurship service system, innovating the public employment and entrepreneurship service mode, and improving the entrepreneurship driven employment support system.

Neural Network-Based State Estimation for Nonlinear Systems With Denial-of-Service Attack Under Try-Once-Discard Protocol

Dear Editor,This letter deals with state estimation issues of discrete-time nonlinear systems subject to denial-of-service(DoS)attacks under the try-once-discard(TOD)protocol.More specifically,to reduce the communication burden,a TOD protocol with novel update rules on protocol weights is designed for scheduling measurement outputs.In addition,unknown nonlinear functions vulnerable to DoS attacks are considered due to the openness and vulnerability of the network.

Deep Reinforcement Learning-Based Task Offloading and Service Migrating Policies in Service Caching-Assisted Mobile Edge Computing

Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.

Interpretation of Chinese Expert Consensus on the Diagnosis and Management Strategy of Patients with Statin Intolerance: A guiding file for helping to lipid management for Chinese population

It is well-known that elevated low-density lipoprotein cholesterol(LDL-C)is a causal risk factor for atheroscler-otic cardiovascular disease(ASCVD),statins are cornerstone drugs for the cause-based treatment of ASCVD,which has created a new era for ASCVD therapy.However,statin intolerance is not clinically uncommon,which there are several issues with confu-sion and misunderstandings.Hence,a file named Chinese Expert Consensus on the Diagnosis and Management Strategy of Pa-tients With Statin Intolerance,like a navigator,has recently been published written by a team of experts from the Cardiovascular Metabolic Medicine Professional Committee,Expert Committee of the National Center for Cardiovascular Diseases aiming to en-hance the standardized clinical application of statins and improve the prevention and clinical outcome.In this article,author briefly summarized the key points of above consensus in order to helping to comprehending the content of the consensus sugges-tions.

Detection of Real-Time Distributed Denial-of-Service (DDoS) Attacks on Internet of Things (IoT) Networks Using Machine Learning Algorithms

The primary concern of modern technology is cyber attacks targeting the Internet of Things.As it is one of the most widely used networks today and vulnerable to attacks.Real-time threats pose with modern cyber attacks that pose a great danger to the Internet of Things(IoT)networks,as devices can be monitored or service isolated from them and affect users in one way or another.Securing Internet of Things networks is an important matter,as it requires the use of modern technologies and methods,and real and up-to-date data to design and train systems to keep pace with the modernity that attackers use to confront these attacks.One of the most common types of attacks against IoT devices is Distributed Denial-of-Service(DDoS)attacks.Our paper makes a unique contribution that differs from existing studies,in that we use recent data that contains real traffic and real attacks on IoT networks.And a hybrid method for selecting relevant features,And also how to choose highly efficient algorithms.What gives the model a high ability to detect distributed denial-of-service attacks.the model proposed is based on a two-stage process:selecting essential features and constructing a detection model using the K-neighbors algorithm with two classifier algorithms logistic regression and Stochastic Gradient Descent classifier(SGD),combining these classifiers through ensemble machine learning(stacking),and optimizing parameters through Grid Search-CV to enhance system accuracy.Experiments were conducted to evaluate the effectiveness of the proposed model using the CIC-IoT2023 and CIC-DDoS2019 datasets.Performance evaluation demonstrated the potential of our model in robust intrusion detection in IoT networks,achieving an accuracy of 99.965%and a detection time of 0.20 s for the CIC-IoT2023 dataset,and 99.968%accuracy with a detection time of 0.23 s for the CIC-DDoS 2019 dataset.Furthermore,a comparative analysis with recent related works highlighted the superiority of our methodology in intrusion detection,showing improvements in accuracy,recall,and detection time.

New Trends in Japan's“Indo-Pacific”Strategy

Introduced by the late Prime Minister Shinzo Abe and inherited and developed by Fumio Kishida,Japan's“Indo–Pacific”strategy has gradually taken shape.This strategy can be deemed a broad vision,covering a wide range of topics and an extensive network of partners,with a strong trend of pan-securitization.It is a comprehensive inter national st rateg y based on Japan's alliance policy and China containment strategy,following a global,security-oriented approach.Driven by considerations such as maintaining its economic status,realizing its long-cherished dream of becoming a political powerhouse,and containing China,Japan has stepped up its“Indo–Pacific”strategy,which may influence global development,undermine regional maritime security,and impede China's reunification process.Meanwhile,Japan's“Indo–Pacific”strategy faces the triple challenge of a strategic overdraft,the unstable economic foundations,and the weak external support.These constraints may not suffice to reverse the direction of Japan's“Indo–Pacific”strategy in the short term but will limit its effectiveness.

The Caching and Pricing Strategy for Information-Centric Networking with Advertisers’Participation

As users’access to the network has evolved into the acquisition of mass contents instead of IP addresses,the IP network architecture based on end-to-end communication cannot meet users’needs.Therefore,the Information-Centric Networking(ICN)came into being.From a technical point of view,ICN is a promising future network architecture.Researching and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of ICN.The current research on ICN pricing mechanism is focused on paid content.Therefore,we study an ICN pricing model for free content,which uses game theory based on Nash equilibrium to analysis.In this work,advertisers are considered,and an advertiser model is established to describe the economic interaction between advertisers and ICN entities.This solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each entity.Our extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.

Sharing Smart Services,Jointly Promoting Trade Development

In 2024,the China International Fair for Trade in Services (hereinafter referred to as CIFTIS) opened in the China National Convention Center and Shougang Park on September 12th.The theme of the CIFTIS this time was"global services,shared prosperity",which is not only a window for allowing the world to discover the development of China's service trade,but is also a bridge for promoting global cooperation with regards to the service trade.As one of the world-famous service trade events,the CIFTIS has become an important business card allowing China to open up.The CIFTIS has attracted the attention of the whole world and become a bridge for all parties to share development opportunities,promote industrial growth,and strengthen communication.

Making the Complicated Simple:A Minimizing Carrier Strategy on Innovative Nanopesticides

The flourishing progress in nanotechnology offers boundless opportunities for agriculture,particularly in the realm of nanopesticides research and development.However,concerns have been raised regarding the human and environmental safety issues stemming from the unrestrained use of non-therapeutic nanomaterials in nanopesticides.It is also important to consider whether the current development strategy of nanopesticides based on nanocarriers can strike a balance between investment and return,and if the complex material composition genuinely improves the efficiency,safety,and circularity of nanopesticides.Herein,we introduced the concept of nanopesticides with minimizing carriers(NMC)prepared through prodrug design and molecular self-assembly emerging as practical tools to address the current limitations,and compared it with nanopesticides employing non-therapeutic nanomaterials as carriers(NNC).We further summarized the current development strategy of NMC and examined potential challenges in its preparation,performance,and production.Overall,we asserted that the development of NMC systems can serve as the innovative driving force catalyzing a green and efficient revolution in nanopesticides,offering a way out of the current predicament.

An Adaptive Hybrid Optimization Strategy for Resource Allocation in Network Function Virtualization

With the rapid development of Network Function Virtualization(NFV),the problem of low resource utilizationin traditional data centers is gradually being addressed.However,existing research does not optimize both localand global allocation of resources in data centers.Hence,we propose an adaptive hybrid optimization strategy thatcombines dynamic programming and neural networks to improve resource utilization and service quality in datacenters.Our approach encompasses a service function chain simulation generator,a parallel architecture servicesystem,a dynamic programming strategy formaximizing the utilization of local server resources,a neural networkfor predicting the global utilization rate of resources and a global resource optimization strategy for bottleneck andredundant resources.With the implementation of our local and global resource allocation strategies,the systemperformance is significantly optimized through simulation.

Machine learning solution for regional landslide susceptibility based on fault zone division strategy

Landslide susceptibility assessment is an essential tool for disaster prevention and management. In areas with multiple fault zones, the impact of fault zone on slope stability cannot be disregarded. This study performed qualitative analysis of fault zones and proposed a zoning method to assess the landslide susceptibility in Chengkou County, Chongqing Municipality, China. The region within a distance of 1 km from the faults was designated as sub-zone A, while the remaining area was labeled as sub-zone B. To accomplish the assessment, a dataset comprising 388 historical landslides and 388 non-landslide points was used to train the random forest model. 10-fold cross-validation was utilized to select the training and testing datasets for the model. The results of the models were analyzed and discussed, with a focus on model performance and prediction uncertainty. By implementing the proposed division strategy based on fault zone, the accuracy, precision, recall, F-score, and AUC of both two sub-zones surpassed those of the whole region. In comparison to the results obtained for the whole region, sub-zone B exhibited an increase in AUC by 6.15%, while sub-zone A demonstrated a corresponding increase of 1.66%. Moreover, the results of 100 random realizations indicated that the division strategy has little effect on the prediction uncertainty. This study introduces a novel approach to enhance the prediction accuracy of the landslide susceptibility mapping model in areas with multiple fault zones.