Security Vulnerability Analyses of Large Language Models (LLMs) through Extension of the Common Vulnerability Scoring System (CVSS) Framework

Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, and more. However, their widespread usage emphasizes the critical need to enhance their security posture to ensure the integrity and reliability of their outputs and minimize harmful effects. Prompt injections and training data poisoning attacks are two of the most prominent vulnerabilities in LLMs, which could potentially lead to unpredictable and undesirable behaviors, such as biased outputs, misinformation propagation, and even malicious content generation. The Common Vulnerability Scoring System (CVSS) framework provides a standardized approach to capturing the principal characteristics of vulnerabilities, facilitating a deeper understanding of their severity within the security and AI communities. By extending the current CVSS framework, we generate scores for these vulnerabilities such that organizations can prioritize mitigation efforts, allocate resources effectively, and implement targeted security measures to defend against potential risks.

Evaluating Common Land Model Energy Fluxes Using FLUXNET Data

Given the crucial role of land surface processes in global and regional climates, there is a pressing need to test and verify the performance of land surface models via comparisons to observations. In this study, the eddy covariance measurements from 20 FLUXNET sites spanning more than 100 site-years were utilized to evaluate the performance of the Common Land Model （CoLM） over different vegetation types in various climate zones. A decomposition method was employed to separate both the observed and simulated energy fluxes, i.e., the sensible heat flux, latent heat flux, net radiation, and ground heat flux, at three timescales ranging from stepwise （30 rain） to monthly. A comparison between the simulations and observations indicated that CoLM produced satisfactory simulations of all four energy fluxes, although the different indexes did not exhibit consistent results among the different fluxes, A strong agreement between the simulations and observations was found for the seasonal cycles at the 20 sites, whereas CoLM underestimated the latent heat flux at the sites with distinct dry and wet seasons, which might be associated with its weakness in simulating soil water during the dry season. CoLM cannot explicitly simulate the midday depression of leaf gas exchange, which may explain why CoLM also has a maximum diurnal bias at noon in the summer. Of the eight selected vegetation types analyzed, CoLM performs best for evergreen broadleaf forests and worst for croplands and wetlands.

Development and Evaluation of Species-Specific Biomass Models for Most Common Timber and Fuelwood Species of Bangladesh

Allometric biomass models are efficient tools to estimate biomass of trees and forest stands in a non-destructive way. Development of species-specific allometric biomass models requires extensive fieldwork and time. Our study aimed to generate species-specific allometric biomass models for the most common fuelwood and timber species of Bangladesh. We also wanted to evaluate the performances of our models relative to the performances of regional and commonly used pan-tropical biomass models. We used semi-destructive method that incorporates tree-level volume, species-specific biomass expansion factor (BEF), and wood density. We considered four base models, 1) Ln (biomass) = a + bLn (D);2) Ln (biomass) = a + bLn (H);3) Ln (Biomass) = a + bLn (D^2H);4) Ln (Biomass) = a + bLn (D) + cLn (H) to develop species-specific best-fitted models for Total Above-Ground Biomass (TAGB) and stem biomass. The best-fitted model for each species was selected by the lowest value of Akaike Information Criterion (AIC), Residual Standard Error (RSE) and Root Mean Square Error (RMSE). The derived best-fitted models were then evaluated with respect to regional and pan-tropical models using a separate set of observed data. This evaluation was conducted by computing ME (Model Efficiency) and MPE (Model Prediction Error). The best-fitted allometric biomass models have shown higher model efficiency (0.85 to 0.99 at scale 1) and the lowest model prediction error (-8.94% to 5.27%) compared to the regional and pan-tropical models. All the examined regional and pan-tropical biomass models showed different magnitude of ME and MPE. Some models showed higher level (>0.90 at scale 1) of ME compared to the best-fitted specific species biomass model.

Land Response to Atmosphere at Different Resolutions in the Common Land Model over East Asia

Towards a better understanding of hydrological interactions between the land surface and atmosphere, land surface mod- els are routinely used to simulate hydro-meteorological fluxes. However, there is a lack of observations available for model forcing, to estimate the hydro-meteorological fluxes in East Asia. In this study, Common Land Model （CLM） was used in offline-mode during the summer monsoon period of 2006 in East Asia, with different forcings from Asiaflux, Korea Land Data Assimilation System （KLDAS）, and Global Land Data Assimilation System （GLDAS）, at point and regional scales, separately. The CLM results were compared with observations from Asiaflux sites. The estimated net radiation showed good agreement, with r = 0.99 for the point scale and 0.85 for the regional scale. The estimated sensible and latent heat fluxes using Asiaflux and KLDAS data indicated reasonable agreement, with r = 0.70. The estimated soil moisture and soil temperature showed similar patterns to observations, although the estimated water fluxes using KLDAS showed larger discrepancies than those of Asiaflux because of scale mismatch. The spatial distribution of hydro-meteorological fluxes according to KLDAS for East Asia were compared to the CLM results with GLDAS, and the GLDAS provided online. The spatial distributions of CLM with KLDAS were analogous to CLM with GLDAS, and the standalone GLDAS data. The results indicate that KLDAS is a good potential source of high spatial resolution forcing data. Therefore, the KLDAS is a promising alternative product, capable of compensating for the lack of observations and low resolution grid data for East Asia.

Developing biomarkers for neurodegenerative diseases using genetically-modified common marmoset models

Mouse and non-human primate models of neurodegenerative disease：The prevalence of age-related neurodegenerative diseases continues to increase with ever increasing aging population over the age of 60.Although the difficulties associated with neurodegenerative diseases present an urgent global issue,there is no effective treatment for these conditions.

Common Management Process Model of New TQM Based on the Situation Analysis

In the previous study, we suggested the concept of new TQM based on the consideration of basic concept of Quality Control. Also, in the previous study, we suggested the target domains and entities of product and process based on the TQM Matrix and view point of Three Dimensional Unification Value Models for managing quality of organization systems. Furthermore, in the previous study, we suggest the Common Management Process of organizations. Based on the above suggestion, in this paper, we would like to propose the Common Management Process Model of Total Quality Management based on the consideration of situation analysis and more precise definition of TQM Matrix and Three Dimensional Unification Value Model of “Product and Process”. Improvement of quality and efficiency of organization management can be expected by the integration of conventional different management such as quality assurance, quality improvement, risk management, investment individually from the view point of common management process.

Common Information Model： A Bus Service for Electric Calculations in AES Eletropaulo

This paper resumes a research project developed in the concession area of AES Eletropaulo, the largest electrical energy distribution company in Brazil. First, the global standards of information exchange within power transmission and distribution area were evaluated, allowing the definition of state of the art on the theme, followed by determining its applications considering technologies already applied by the company. The specifications needed for the generation of a data integration model are adapted to radial overhead network at company concession area. The project developed an intermediary connectivity layer, based on the CIM （common information model）, which enables corporative systems to communicate in a standard way, through the use of integrating technologies. It, therefore, enabled modeling all main subjects of an electrical network in an open, extensible and non-proprietary way, in a model that contains classes and attributes of such subjects, as well as their relationships. Calculation and planning products adopted by the company were integrated to the technological layer implemented.

Establishing a Social Governance Model Based on Collaboration,Participation,and Common Interests:Value,Structure and Roadmap

The 19th National Congress of the Communist Party of China(CPC)put forward the proposal of establishing a social governance model based on collaboration,participation,and common interests,with the aim of developing new approaches to social governance and further modernizing China’s social system and capacity for governance.As a structuralized social relation addressing diversified governance bodies,the model has consolidated the social governance innovations achieved since the 18th CPC National Congress.Focusing on three dimensions—"value,""structure"and"roadmap,"this paper tries to interpret the value connotations and defining features behind the model and explores its development roadmap.Such a social governance model is a response to political,social and public value appeals,and an adjustment to the order of governance bodies,resource allocations and the benefit distribution structure.Its construction is a systematic and long-term project,which should aim continuously at satisfying people’s ever-higher needs,perfecting laws and regulations,cultivating a pool of specialized organizations and talents,exerting the technology advantages of the Internet in governance,and promoting socialization,legalization,specialization and intellectualization in social development.

Information Commons的理性审视

文摘Information Commons(信息共享中心)是20世纪90年代后期兴起的一种新型图书馆服务模式。本文论述了IC兴起的背景,分析了其构成和服务模式;并从信息服务模式演变、图书馆功能发挥、信息共有理念等角度对其进行审视,揭示了IC“空间共用、资源共用”、“用户交流互动”、“维护信息共有”等核心理念。

国外图书馆Information Commons的兴起和发展及其启示

Information Commons(IC,信息共享中心)是20世纪90年代国外高校图书馆为适应用户需求的变化而建立起来的一种新型的图书馆服务模式。本文阐明了IC兴起的背景及其发展和应用;分析了其构成要素和服务模式;从4个方面探讨了对我国图书馆的启示和借鉴作用。

网络环境下多元著作权保护制度的建构——以“Creative Commons”机制与合理使用为视角

“Creative Commons”授权许可机制的实施必然在一定程度上对传统著作权制度造成影响,使得著作权学者必须开始考虑现有的著作权体系是否能够支持这一在网络环境下逐步流行的授权许可协议。在一定条件下,这一系列协议形式会在很大程度和范围上,让一般公众和使用者得以规避愈来愈倾向加强网络著作权保护的相关著作权法律。从另一个角度来看,这种网络自发采用的许可合同形式很可能会“改写版权法的规则”,促进建立全新的、多层次的、立体的合理使用法律体系,并在此基础上推动著作权法的相关发展,从而在网络环境下建立更合理、更有弹性的著作权保障模式。

Information Commons的结构及其模型研究

IC的理论构成可划分为物理空间、虚拟空间、政策空间和情感空间等四个维面/方面。从建设所涉及的范围及其功能的发挥等因素考虑,IC分为宏观层次上的全球IC巨/型IC、中观层次上的区域/系统IC和微观层次上的机构/组织IC等三大类型。不同层次类型的IC,具有不同的功能与特点,其结构模型也各不相同。

Information Commons的研究及其在国内高校的应用

文章主要研究信息共享区(IC-Information Commons)的实践和相关理论研究,及其在国内高校的应用。IC高度整合了图书馆的信息资源和各部门及功能,为用户提供平等的、开放的、一站式的信息及服务。IC模式是当今图书馆服务模式发展的主流,国内高校图书馆应当结合自己的实际情况尝试建立IC,为用户提供一个更适于研究和学习的有效集成图书馆各种功能的新环境。

以乘用车标签开发浅析任务驱动的共用件知识管理模型应用

为了满足汽车行业技术革新和市场需求,以提升乘用车共用件的开发效率和资源利用为目标,探索知识分析管理模型在乘用车标签领域的应用。通过构建知识复用库和验证模型,提出了一种基于任务驱动的共用件知识管理新策略,知识分析管理模型为乘用车共用件的高效开发提供了一种创新方法。结果表明,该模型能有效促进知识共享、缩短开发周期、降低成本、提升企业竞争力。

XML-based integration data model and schema mappingin multidatabase systems

Multidatabase systems are designed to achieve schema integration and data interoperation among distributed and heterogeneous database systems. But data model heterogeneity and schema heterogeneity make this a challenging task. A multidatabase common data model is firstly introduced based on XML, named XML-based Integration Data Model (XIDM), which is suitable for integrating different types of schemas. Then an approach of schema mappings based on XIDM in multidatabase systems has been presented. The mappings include global mappings, dealing with horizontal and vertical partitioning between global schemas and export schemas, and local mappings, processing the transformation between export schemas and local schemas. Finally, the illustration and implementation of schema mappings in a multidatabase prototype - Panorama system are also discussed. The implementation results demonstrate that the XIDM is an efficient model for managing multiple heterogeneous data sources and the approaches of schema mapping based on XIDM behave very well when integrating relational, object-oriented database systems and other file systems.

Machine Learning for Selecting Important Clinical Markers of Imaging Subgroups of Cerebral Small Vessel Disease Based on a Common Data Model

Differences in the imaging subgroups of cerebral small vessel disease(CSVD)need to be further explored.First,we use propensity score matching to obtain balanced datasets.Then random forest(RF)is adopted to classify the subgroups compared with support vector machine(SVM)and extreme gradient boosting(XGBoost),and to select the features.The top 10 important features are included in the stepwise logistic regression,and the odds ratio(OR)and 95%confidence interval(CI)are obtained.There are 41290 adult inpatient records diagnosed with CSVD.Accuracy and area under curve(AUC)of RF are close to 0.7,which performs best in classification compared to SVM and XGBoost.OR and 95%CI of hematocrit for white matter lesions(WMLs),lacunes,microbleeds,atrophy,and enlarged perivascular space(EPVS)are 0.9875(0.9857−0.9893),0.9728(0.9705−0.9752),0.9782(0.9740−0.9824),1.0093(1.0081−1.0106),and 0.9716(0.9597−0.9832).OR and 95%CI of red cell distribution width for WMLs,lacunes,atrophy,and EPVS are 0.9600(0.9538−0.9662),0.9630(0.9559−0.9702),1.0751(1.0686−1.0817),and 0.9304(0.8864−0.9755).OR and 95%CI of platelet distribution width for WMLs,lacunes,and microbleeds are 1.1796(1.1636−1.1958),1.1663(1.1476−1.1853),and 1.0416(1.0152−1.0687).This study proposes a new analytical framework to select important clinical markers for CSVD with machine learning based on a common data model,which has low cost,fast speed,large sample size,and continuous data sources.

On the Range of the Common Cycle Time in a Road Network

In a coordinated road network,the optimal common cycle time is determined by evaluating the performance of the network in the given range of cycles. Normally,this range is determined by users 'experience. And a large range of common cycle time,e. g. [30,200] is chosen,which requires long computation time. This study considers that the optimal common cycle time ranges between the minimal and maximal value of intersections' individual optimal cycle time. It is proved mathematically from the convexity condition,that the delay of the network and each individual intersection are convex functions of the cycle time according to Webster delay model. Finally,2 000 random cases for the network composed of two intersections and of eight intersections are created to underline the proposed conclusions. The results of all cases confirm the validity,and show up to 90% improvement in computation time to compare with experience range. The signal optimization tool,Synchro,is also used to validate the conclusion by 50 random cases. The results confirm reliability further.

Older Adults’ Explanatory Models of Colds and Flu

Systematic data collection and analysis techniques were used in Los Angeles to discover older adults’ shared explanatory models (EM) of the causes, prevention, symptoms, treatment and consequences of late life illnesses, including influenza and the common cold. Recorded narratives also were analyzed to illustrate similarities and differences in shared cultural knowledge of these illnesses. Consensus analyses results suggest that shared EM of influenza and the common cold are similar. Participants identified both illnesses as contagious, caused or exacerbated by bad weather, but not the result of lifestyle, aging or heredity. Other shared cultural knowledge includes that both illnesses can be treated with home remedies, over-the-counter medications and medical care;both illnesses cause discomfort but are not serious, life-threatening or disabling. Despite the similarities and the apparent merging of the two illnesses in popular thought, many older adults do distinguish them, based on symptom patterns and severity, as revealed in their transcribed narratives. Consistent with other studies, participants attribute gastrointestinal symptoms to influenza but not to colds. They do not understand the potential role of lifestyle, age and chronic conditions in etiology and onset, and they are not concerned with their vulnerability to the potential sequelae of influenza. Public health education explaining the effects of lifestyle on susceptibility and vulnerability to the flu, how to distinguish and appropriately treat colds and the flu, and when to contact physicians, is recommended for older adults. Mixed method studies can prove useful at the planning stages of such interventions.

CIM Model Extension for Intelligent DAS of Smart Power Grid in Korea

The CIM （common information model） is an abstract information model that can be used to model an electrical network and various equipments used on the network. By using a common model, utilities and vendors can reduce their integration costs, which should allow more resources to be applied toward increased functionality for managing and optimizing the electrical system. As a part of smart grid, the SPG （smart power grid） was built on Jeju Island. The SPG consists of IDAS （intelligent distribution automation system）, substation automation system, intelligent transmission system, and active telemetrics system. To integrate these systems which have different operating systems and platforms CIM standard was used. But IDAS has many functions and advanced algorithms not defined in CIM. In this paper, the authors introduce how to develop and extend the CIM model for managing the IDAS.

Feature Modeling and Variability Modeling Syntactic Notation Comparison and Mapping

Feature Model (FM) became an important role in Software Product Line Engineering (SPLE) field. Many approaches have been introduced since the original FM came up with Feature Oriented Domain Analysis (FODA) introduced by Kang in 1990. The main purpose of FM is used for commonality and variability analysis in domain engineering, to optimize the reusable aspect of software features or components. Cardinality-based Feature Model (CBFM) is one extension of original FM, which integrates several notations of other extensions. In CBFM, feature model defined as hierarchy of feature, with each of feature has a cardinality. The other notation to express variability within SPLE is Orthogonal Variability Model (OVM). At the other hand, OMG as standard organization makes an effort to build standard generic language to express the commonality and variability in SPL field, by initiate Common Variability Language (CVL). This paper reports the comparison and mapping of FODA, CBFM and OVM to CVL where need to be explored first to define meta model mapping of these several approaches. Furthermore, the comparison and mapping of those approaches are discussed in term of R3ST (read as “REST”) software feature model as the case study.