An Investigation on Open-RAN Specifications:Use Cases,Security Threats,Requirements,Discussions

The emergence of various technologies such as terahertz communications,Reconfigurable Intelligent Surfaces(RIS),and AI-powered communication services will burden network operators with rising infrastructure costs.Recently,the Open Radio Access Network(O-RAN)has been introduced as a solution for growing financial and operational burdens in Beyond 5G(B5G)and 6G networks.O-RAN promotes openness and intelligence to overcome the limitations of traditional RANs.By disaggregating conventional Base Band Units(BBUs)into O-RAN Distributed Units(O-DU)and O-RAN Centralized Units(O-CU),O-RAN offers greater flexibility for upgrades and network automation.However,this openness introduces new security challenges compared to traditional RANs.Many existing studies overlook these security requirements of the O-RAN networks.To gain deeper insights into the O-RAN system and security,this paper first provides an overview of the general O-RAN architecture and its diverse use cases relevant to B5G and 6G applications.We then delve into specifications of O-RAN security threats and requirements,aiming to mitigate security vulnerabilities effectively.By providing a comprehensive understanding of O-RAN architecture,use cases,and security considerations,thisworkserves as a valuable resource for future research in O-RAN and its security.

How Does Urban Shrinkage Affect Land Use Efficiency?A Case Study of Shrinking Cities in Northeast China

The effect of urban shrinkage has gradually become a new topic.Theoretically,urban shrinkage may exert great influence on land use efficiency(LUE)through various urban subsystems,but there is currently limited research examining these pathways.Using the Super-SBM-Undesirable model and the Structural Equation Model(SEM),this study calculates the LUE of shrinking cities in Northeast China and simulates the process of urban shrinkage affecting LUE.To quantify the process of urban shrinkage affecting LUE,three mediation variables,namely the economy,public services,and innovation,are used as latent variables to apply SEM.The results show that urban shrinkage will affect LUE through a direct path and indirect paths.In the direct path,urban shrinkage leads to an improvement in LUE.In the indirect paths,the economy and innovation will transmit the negative effect of urban shrinkage on LUE,while public services will reverse this effect.An important contribution of this study is that it quantifies the paths of urban shrinkage affecting LUE,thereby expanding the understanding of urban shrinkage effect and laying a foundation for the sustainable development of shrinking cities.

Dynamics of Land Use/Land Cover Considering Ecosystem Services for a Dense-Population Watershed Based on a Hybrid Dual-Subject Agent and Cellular Automaton Modeling Approach

Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.

Optimization of water-urban-agricultural-ecological land use pattern:A case study of Guanzhong Basin in the southern Loess Plateau of Shaanxi Province,China

Extensive land use will cause many environmental problems.It is an urgent task to improve land use efficiency and optimize land use patterns.In recent years,due to the flow decrease,the Guanzhong Basin in Shaanxi Province is confronted with the problem of insufficient water resources reserve.Based on the Coupled Ground-Water and Surface-Water Flow Model(GSFLOW),this paper evaluates the response of water resources in the basin to changes in land use patterns,optimizes the land use pattern,improves the ecological and economic benefits,and the efficiency of various spatial development,providing a reference for ecological protection and high-quality development of the Yellow River Basin.The research shows that the land use pattern in the Guanzhong Basin should be further optimized.Under the condition of considering ecological and economic development,the percentage change of the optimum area of farmland,forest,grassland,water area,and urban area compared with the current land use area ratio is+2.3,+2.4,-6.1,+0.2,and+1.6,respectively.The economic and ecological value of land increases by14.1%and 3.1%,respectively,and the number of water resources can increase by 2.5%.

What are the underlying causes and dynamics of land use conflicts in metropolitan junction areas?A case study of the central Chengdu–Chongqing region in China

Land use conflicts(LUCs),as a spatial manifestation of the conflicts in the human-land relationships,have a profound impact on regional sustainable development.For China’s metropolitan junction areas(MJAs),the existence of“administrative district economies”has made the issue of LUCs more prominent.Based on a case study of the central Chengdu–Chongqing region,we conducted an exploratory spatial data analysis of the evolutionary process of regional LUCs.Furthermore,structural equation modeling was utilized to analyze the dynamic mechanism of LUCs in MJAs,with a particular emphasis on exploring the influences of administrative boundary.The results showed that from 2010 to 2020,LUCs in the central Chengdu–Chongqing region continued to worsen,and the spatial process conflict and spatial structure conflict indices increased by more than 30.0%.The intensification of LUCs in the central Chengdu–Chongqing region from 2010 to 2020 was mainly the result of the deterioration of conflicts in evaluation units with low conflict levels.LUCs in China’s metropolitan areas generally presented a circular gradient distribution,weakening from the core to the periphery,but there were some strong isolated conflict zones in the outer regions.LUCs in China’s MJAs were the result of interactions among multiple factors,e.g.,natural environment,socio-economic development,policy and institutional processes,and administrative boundary effects.Administrative boundary affected the flow of socio-economic elements,changing the supply-and-demand competition of stakeholders for land resources,consequently exerting an indirect influence on LUCs.This study advances the theory of the dynamic mechanism of LUCs,and provides theoretical support for the governance of these conflicts in transboundary areas.

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

Country-based modelling of COVID-19 case fatality rate:A multiple regression analysis

BACKGROUND The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection.The determinants of mortality on a global scale cannot be fully understood due to lack of information.AIM To identify key factors that may explain the variability in case lethality across countries.METHODS We identified 21 Potential risk factors for coronavirus disease 2019(COVID-19)case fatality rate for all the countries with available data.We examined univariate relationships of each variable with case fatality rate(CFR),and all independent variables to identify candidate variables for our final multiple model.Multiple regression analysis technique was used to assess the strength of relationship.RESULTS The mean of COVID-19 mortality was 1.52±1.72%.There was a statistically significant inverse correlation between health expenditure,and number of computed tomography scanners per 1 million with CFR,and significant direct correlation was found between literacy,and air pollution with CFR.This final model can predict approximately 97%of the changes in CFR.CONCLUSION The current study recommends some new predictors explaining affect mortality rate.Thus,it could help decision-makers develop health policies to fight COVID-19.

Land use change modeling through an integrated Multi-Layer Perceptron Neural Network and Markov Chain analysis(case study: Arasbaran region, Iran)

Temporal land use/land cover (LULC) change information provides a variety of applications for informed management of land resources. The aim of this study was to detect and predict LULC changes in the Arasbaran region using an integrated Multi-Layer Perceptron Neural Network and Markov Chain analysis. At the first step, multi-temporal Landsat images (1990, 2002 and 2014) were processed using ancillary data and were classified into seven LULC categories of high density forest, low-density forest, agriculture, grassland, barren land, water and urban area. Next, LULC changes were detected for three time profiles, 1990–2002, 2002–2014 and 1990–2014. A 2014 LULC map of the study area was further simulated (for model performance evaluation) applying 1990 and 2002 map layers. In addition, a collection of spatial variables was also used for modeling LULC change processes as driving forces. The actual and simulated 2014 LULC change maps were cross-tabulated and compared to ensure model simulation success and the results indicated an overall accuracy and kappa coefficient of 97.79% and 0.992, respectively. Having the model properly validated, LULC change was predicted up to the year 2025. The results demonstrated that 992 and 1592 ha of high and lowdensity forests were degraded during 1990–2014,respectively, while 422 ha were added to the extent of residential areas with a growth rate of 17.58 ha per year. The developed model predicted a considerable degradation trend for the forest categories through 2025, accounting for 489 and 531 ha of loss for high and low-density forests, respectively. By way of contrast, residential area and farmland categories will increase up to 211 and 427 ha, respectively. The integrated prediction model and customary area data can be used for practical management efforts by simulating vegetation dynamics and future LULC change trajectories.

An Aspect-Oriented Approach for Use Case Based Modeling of Software Product Lines

Software Product Line Development advocates software reuse by modeling common and variable artefacts separately across members of a family of products. Aspect-Oriented Software Development aims at separation of concerns with “aspects” to increase modularity, reusability, maintainability and ease of evolution. In this paper, we apply an as-pect-oriented use case modeling approach to product line system modeling. A use case specification captures stake-holders concerns as interactions between a system and its actors. We adapt our previous work with the introduction of a “variability” relationship for the expression of variabilities. This relationship is used to model variable and common behaviours across a family of products as use cases. A variability composition mechanism enables building of executa-ble behaviour models for each member of a product line family by integrating common elements with the applicable variable elements.

Considering Regional Connectivity and Policy Factors in the Simulation of Land Use Change in New Areas:A Case Study of Nansha New District,China

Numerous emerging development areas worldwide are receiving attention;however,current research on land use change simulation primarily concentrates on cities,urban clusters,or larger scales.Moreover,there is a limited focus on understanding the impact of regional connectivity with surrounding cities and policy factors on land use change in these new areas.In this context,the present study utilizes a cellular automata(CA)model to investigate land use changes in the case of Nansha New District in Guangzhou,China.Three scenarios are examined,emphasizing conventional locational factors,policy considerations,and the influence of regional connectivity with surrounding cities.The results reveal several key findings:(1)Between 2015 and 2021,Nansha New District experienced significant land use changes,with the most notable shifts observed in cultivated land,water area,and construction land.(2)The comprehensive scenario exhibited the highest simulation accuracy,indicating that Nansha New District,as an emerging area,is notably influenced by policy factors and regional connectivity with surrounding cities.(3)Predictions for land use changes in Nansha by 2030,based on the scenario with the highest level of simulation accuracy,suggest an increase in the proportion of cultivated and forest land areas,alongside a decrease in the proportion of construction land and water area.This study contributes valuable insights to relevant studies and policymakers alike.

Evaluation of Intensive Urban Land Use Based on an Artificial Neural Network Model:A Case Study of Nanjing City,China

In this paper, the artificial neural network(ANN) model was used to evaluate the degree of intensive urban land use in Nanjing City, China. The construction and application of the ANN model took into account the comprehensive, spatial and complex nature of urban land use. Through a preliminary calculation of the degree of intensive land use of the sample area, representative sample area selection and using the back propagation neural network model to train, the intensive land use level of each evaluation unit is finally determined in the study area. Results show that the method can effectively correct the errors caused by the limitations of the model itself and the determination of the ideal value and weights when the multifactor comprehensive evaluation is used alone. The ANN model can make the evaluation results more objective and practical. The evaluation results show a tendency of decreasing land use intensity from the core urban area to the periphery and the industrial functional area has relatively low land use intensity compared with other functional areas. Based on the evaluation results, some suggestions are put forward, such as transforming the mode of urban spatial expansion, strengthening the integration and potential exploitation of the land in the urban built-up area, and strengthening the control of the construction intensity of protected areas.

Association between Macroscopic-factors and Identified HIV/AIDS Cases among Injecting Drug Users: An Analysis Using Geographically Weighted Regression Model

Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug users （IDUs）[1]. Previous studies have proven that needles or cottons sharing during drug injection were major risk factors for HIV/AIDS transmission at the personal level[z4]. Being a social behavioral issue, HIV/AIDS related risk factors should be far beyond the personal level. Therefore, studies on HIV/AIDS related risk factors should focus not only on the individual factors, but also on the association between HIV/AIDS cases and macroscopic-factors, such as economic status, transportation, health care services, etc[1]. The impact of the macroscopic-factors on HIV/AIDS status might be either positive or negative, which are potentially reflected in promoting, delaying or detecting HIV/AIDS epidemics.

Model-Driven Derivation of Domain Functional Requirements from Use Cases

Domain analysis is essential to core assets development in software product line engineering. Most existing approaches, however, depend on domain experts’ experience to analyze the commonality and variability of systems in a domain, which remains a manual and intensive process. This paper addresses the issue by proposing a model-driven approach to automating the domain requirements derivation process. The paper focuses on the match between the use cases of existing individual products and the domain functional requirements of a product line. By introducing a set of linguistic description dimensions to differentiate the sub-variations in a use case, the use case template is extended to model variability. To this end, a transformation process is formulated to sustain and deduce the information in use cases, and to match it to domain functional requirements. This paper also presents a prototype which implements the derivation as a model transformation described in a graphical model transformation language MOLA. This approach complements existing domain analysis techniques with less manual operation cost and more efficiency by automating the domain functional requirements development.

Influence of land use characteristics and trip attributes on commuting mode choice: a case of Nanjing

The effects of socio-demographics, land use characteristics and trip attributes on the commute mode choice are studied with a nested logit （NL） model. Based on the random utility maximum theory, the NL model is formulated. The analysis is carried out in the main area of Nanjing. Direct and cross elasticities are calculated to analyze the effects of travel time and travel cost on the selection of travel mode choice. The results reveal that the non-motorized travel modes are more attractive in the areas with higher housing and employment accessibility and car owners are found to be more likely to commute to work by car. The bus and subway choice probabilities are more sensitive to changes in travel times than to changes in travel costs. In conclusion, a comprehensive public transit system and effective integration of land use and transportation policies help to relieve the traffic congestion levels caused by the increasing urban sprawl.

Spatiotemporal characteristics of cultivated land use eco-efficiency and its influencing factors in China from 2000 to 2020

Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.

Evaluating the Conservation Efforts of Multi-Projects Using Remote Sensing and Light Use Efficiency Model: A Case of Nyungwe Forest National Park, Rwanda

This paper investigates the effectiveness of conservation efforts in the Nyungwe Forest National Park (Nyungwe). The forest is one of the six key landscapes identified for conservation in the Albertine Rift because it hosts many threatened species. As such, a number of different stakeholders have been involved in its conservation since 1987;yet, studies that emphasize and evaluate the success of these conservation efforts are limited. We combined a rapid and relatively low cost remotely-sensed data and the Light Use Efficiency model to generate forest conservation indicators such as NDVI, forest canopy Net Primary Productivity and carbon sequestered from 1986 to 2010. The influence of topographic and climatic factors on these indicators was examined. The supervised classifier was used to catalogue the area into Forest, Wetland, and Bareland. The forest was the major category (above 90%) of Nyungwe relative to wetland and bareland. Based on degradation intensity, two distinctive periods were realised;the first period spans 8 years (1986-1994) whereas the second spans 16 years (1994-2010). The former degradation intensity period is 10 times higher than the latter period. Although the size of forest recovered up to 90%, the daily NPP and carbon sequestration capacity decreased by 37.1% (i.e. NPP 6.5 Mg tons in 1986 to 4.1 Mg tons in 2010). Areas of the forest that are physically constrained (high altitude) had a higher degradation. Guided by our indicators, there is an overall success in conservation efforts, but efforts were mostly concentrated in accessible areas. Therefore, conservation efforts that aim to respond to degradation of the inaccessible areas of the forest should be stressed in the management plan of the park.

角色Use Case:UML的一个更加完全的分析方法

根据角色模型 ,讨论了一个更加完全的 U ML角色 U se Case分析方法 .提倡使用角色的视点定义和分析UML Use Case,使用概念的角色 Use Case模型定义和分析系统的需求 .提出了运用 AOP和角色 U se Case法的求精 (refine)、实现 (realization)和反演 (reflection)的 3R机制与 U ML相结合 ,跨越系统分析和设计之间的鸿沟 .为开发可构造、可扩充的开放式软件系统提供了一些方法和手段 .

Use Case可视化自动建模工具的设计与实现

围绕UML中Usecase的可视化自动建模进行了研究,设计与实现了一个Usecase可视化自动建模工具,并通过在金融贸易系统需求建模中的应用,说明了这一方法对于提高需求建模的速度、确保文档的规范化和模型语法的正确性等具有明显的效果。

Rational统一过程中的Use Case业务建模

在利用统一建模语言UML和Rational统一过程建立软件系统模型和开发软件系统时 ,首要的任务就是建立系统的业务模型。本文通过实例详细论述了UseCase以及利用UseCase建立系统业务模型的方法。

Use Case驱动的软件需求获取过程模型

对UseCase建模进行分析后,提出了基于UseCase驱动的软件需求获取过程模型。该模型中通过不断迭代的两个阶段:分析阶段和综合阶段,来正确和完整地获取软件需求。文章对此模型进行了描述,并就一些关键问题展开了讨论,最后介绍了软件需求获取中的一些常用技术。