Revisiting future-proofing for large-scale acquisitions

Human Rights, Civics and Democracy Curriculum for 4th graders was began to be implemented in 2015-2016 academic year. In this study, we aim to evaluate this curriculum regarding the universality of human rights concept; the appropriateness of the curriculum with its educational goals, content, instructional material and methods in terms of students’ cognitive level and finally teacher competencies to teach this course. A qualitative intrinsic case study method was utilized. The data was collected through document analysis; eight-hours of classroom observation, and semi-structured interviews with seven elementary school teachers and six “experts”. Eisner’s Educational Connoisseurship and Criticism Model was used as an evaluation framework. Deductive content analysis was used to analyze the data and to illuminate specific details about the case under investigation. Results showed that attainments and content were consistent with the universality of human rights perspective; also, instruction and assessment methods were consistent with the philosophy (constructivism) of the curriculum. However, the course material, as regards to its aims, content and philosophy; and the practices applied inside the classroom were highly inconsistent with the goals of the curriculum.

In recent years, with the problem of network security is getting worse, the network threat situation assessment becomes an important approach to solve these problems. Aiming at the traditional methods based on data category tag that has high modeling cost, low efficiency, and a long period in the network threat situation assessment, this paper proposes a Variational-Generative (V-G) network assessment method. Firstly, we design the V-G network which is composed of VAE’s encoder and GAN’s discriminator and obtain the reconstruction error of each layer network by training the network collection layer of the V-G network with normal network traffic. Then, conduct the reconstruction error learning by the 3-layer variational autoencoder of the output layer and calculate the abnormal threshold of the training. Moreover, carry out the group threat testing with the test dataset contains abnormal network traffic and calculate the threat probability of each test group. Finally, obtain the Threat Situation Value (TSV) according to the threat probability and the threat impact. The simulation results show that compared with the other methods, this proposed method can evaluate the overall situation of network security threat more intuitively and has a stronger characterization ability for network threats.

Elaboration of a Framework for Assessment of IT-based Interventions in the Field of Autism Disorder

This paper presents a mathematical programming model that allows quality to be explicitly considered in project planning and scheduling, while addressing the tradeoffs between quality, time, and cost. A quality function is used to represent the relationships between time, cost, and quality for individual tasks. The initial problem formulation maximizes the minimum quality (weakest link) over all project tasks, subject to bounds on cost and completion time. Using a construction example we show how this model can be adapted to generate quality level curves to illustrate the trade-offs among time, cost, and quality. These level curves can then be used by project managers to make project scheduling decisions that explicitly model and consider quality as well as time and cost, so that better and more appropriate decisions can be made for a particular situation. We also offer some managerial insights for project planning and scheduling that are derived from the analysis through improved understanding of these choices and tradeoffs.

With increasing numbers and types of nature reserves (NRs), objective evaluation and comparison of the effects of different nature NRs on conservation efforts are of great importance for protecting species diversity, ensuring reasonable national economic input, and adjusting government management schemes. Developing a method for the combined assessment of flagship or umbrella species and ecosystem quality will improve the evaluation of NRs. However, it is also important to establish a new framework for rapid evaluation of ecosystem quality, supported by the advantages of scientific, economic, and regular principles. Here, we proposed a new framework that incorporates the novel concept of ideal references into evaluation systems, which will facilitate the comparison of results from different periods and regions. Furthermore, from the perspective of making the framework as objective, rapid, and economical as possible, we recommended some key ecological indicators, such as net primary productivity, soil organic matter, plant diversity, for use in the new evaluation framework. The new framework, referred to as “ideal reference and key indicators” (IRKI), can sufficiently meet the requirements for the rapid evaluation of ecosystem quality both regionally and nationally. Furthermore, IRKI can identify the restoration potential and restoration periods of NRs, thus facilitating the rational distribution of resources and enhancing the protective effect. There are many types of NRs in China, and it is necessary to partially alter the assessment methods or parameters for different types of NRs. Overall, IRKI provides a simple, clear, and comparable framework that will strongly enhance the conservation of protected areas (PAs) and facilitate the standardization of management practices.

Conducting performance assessment during the early phases of system development enhances early design decisions of system design. The generated performance models from system design will help in identifying the potential performance problems in the system design based on the result of the performance assessment. In recent years, several methods for performance assessment and modeling have been proposed. This paper presents the comparative evaluation of performance assessment and modeling methods to discover the strengths and weaknesses of the existing methods based on a set of criteria which includes process and modeling elements that was developed with the purpose to represent a specific process to assess the performance attributes with the help of modeling concepts. The four selected methods were evaluated based on these criterions and the results will hopefully guidance for developers to propose better methods for performance assessment and modeling in the future.

Designing reverse logistics networks in shipyards: integrating cost, safety, and environmental trade-offs in location-routing decisions

Today there is increasing emphasis on knowledge exchange (KE), the movement of knowledge and expertise amongst diverse groups to enhance research uptake, use, and impact in healthcare, government, and community settings. Library and information science (LIS) professionals are central actors in KE though community engagement, scholarly communication, literacy, and cultural heritage initiatives, but (how) is this work formally documented and evaluated? Through interviews with 24 information professionals working in varied settings, we considered how KE activities fit into the current library assessment and evaluation landscape. Using thematic analysis, we identified challenges with placing this work within current assessment practices and evaluation frameworks and showing its value, as well as a desire for alternative, more dynamic assessment and evaluation methods. We discuss these findings with respect to previous research in LIS and KE more broadly to consider professional and organizational implications.

The network security status assessment (NSSA) method can evaluate the network security status of cloud manufacturing systems (CMSs), which is of great significance to reduce the network security risk and loss of CMSs. At present, the NSSA of CMSs suitable for semiquantitative and uncertain information conditions is commonly used, which has certain limitations and low accuracy. This paper proposes an NSSA method for CMSs based on semiquantitative information. First, through the detailed analysis of the influencing factors of the network security status of the CMSs, the security evaluation indicators were selected, and the evaluation framework containing multilevel indicators was established by combining semiquantitative information. Second, the evaluation level was established according to the data distribution and the properties of the indicators. Third, a process of data fusion reasoning based on an evidential reasoning algorithm is designed, and a strong reference fusion case is given. Finally, the effectiveness of the proposed security state assessment algorithm in the NSSA of CMSs was verified and analyzed by simulation experiments. The experimental results show that the proposed method can make full use of semiquantitative information and uncertain information to evaluate the network security status of CMSs, and the evaluation results can reflect the actual security status of CMSs.

Computational experiments are an important method for carrying out the quantitative analysis of complex systems and play a major role in mapping the real world to the virtual world. However, the flexibility of computational experiments leads to arbitrary modeling processes and unconvincing results, which greatly hinder the large-scale application of this method. In this context, the verification of computational models has become an urgent problem in this field. Currently, model evaluation is still in its infancy and the existing evaluation methods are not mature enough. Thus, we took epidemic models as the research object and proposed a capability maturity evaluation framework for computational models of artificial society. The framework differs from previous assessment methods that focus on the validity of results, but instead provides a comprehensive evaluation from two perspectives: 1) evaluation of the model itself—by comparing the expectation with the final implementation, we can obtain whether the model meets the expectation and 2) comparison between different models—by evaluating the implementation process of each model and comparing the results, we can identify more mature models. The implementation of the model is evaluated from input, process, and output. Further, specific analyses and evaluations are conducted for several representative COVID-19 models to verify the validity of this evaluation framework. The results of the case study show that the proposed evaluation framework can help decision-makers identify more mature and referential models, and point out the directions where modelers can improve their models.

Eyewitness testimony is both an important and a notoriously unreliable type of criminal evidence. How should investigators, lawyers and decision-makers evaluate eyewitness reliability? In this article, I argue that Testimonial Inference to the Best Explanation (TIBE) is a promising, but underdeveloped prescriptive account of eyewitness evaluation. On this account, we assess the reliability of eyewitnesses by comparing different explanations of how their testimony came about. This account is compatible with, and complementary to both the Bayesian framework of rational eyewitness evaluation and with prescriptive methods for eyewitness assessment developed by psychologists. Compared to these frameworks, the distinctive value of thinking in terms of competing explanations is that it helps us select, interpret and draw conclusions from the available evidence about the witness’s reliability.

The selection of suitable personnel is of great importance for the successful operation of companies. Therefore, this article investigates the application of the Multi-Objective Optimization by Ratio Analysis plus Full Multiplicative Form (MULTIMOORA) and Simplified PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA-S) methods to evaluate candidates under the conditions of group decision-making. The MULTIMOORA method is used for ranking candidates while PIPRECIA-S method is used for determining criteria weights. As main objective of this article can be identified proposing and checking the usability of an easy-to-use and at the same time easy-to-understand framework for personnel evaluation that supports group decision-making and negotiation among human resource managers in the evaluation process. Additionally, the objective is to propose a framework that can be used for solving similar decision-making problems, as well as to propose a framework that can serve as a basis for the development of appropriate software.

The objectives of this research are to review existing methods used for assessing mining sustainability, analyze the limited prior research that has evaluated the methods, and identify key characteristics that would constitute an enhanced sustainability framework that would serve to improve sustainability reporting in the mining industry. Five of the most relevant frameworks were selected for comparison in this analysis, and the results show that there are many commonalities among the five, as well as some disparities. In addition, relevant components are missing from all five. An enhanced evaluation system and framework were created to provide a more holistic, comprehensive method for sustainability assessment and reporting. The proposed framework has five components that build from and encompass the twelve evaluation characteristics used in the analysis. The components include Foundation, Focus, Breadth, Quality Assurance, and Relevance. The enhanced framework promotes a comprehensive, location-specific reporting approach with a concise set of well-defined indicators. Built into the framework is quality assurance, as well as a defined method to use information from sustainability reports to inform decisions. The framework incorporates human health and socioeconomic aspects via initiatives such as community-engaged research, economic valuations, and community-initiated environmental monitoring.

In response to negative impacts of human disturbances, governments and international organizations have launched large-scale environmental restoration programs to mitigate ecological degradation. However, few studies have assessed these projects from a cost-efficiency perspective. In the context of increasing global macroeconomic uncertainty, such projects face mounting challenges to their financial sustainability, underscoring the need for systematic evaluations of their cost efficiency. This study takes the forest-steppe ecotone project within China's Three-North Shelter Forest Program as a case study. Using 18 years of project implementation data, we establish an evaluation framework that integrates ecological returns and cost efficiency to assess project effectiveness. The results show that from 2002 to 2019, the forest area in the project region increased by 5.32 %, while sand-fixing capacity rose from 2.00 × 10 11 tons in 2005 to 4.39 × 10 11 tons in 2019. In terms of cost efficiency, the total investment in afforestation from 2002 to 2019 ranged from CNY 341.134–391.537 billion, with an average annual investment of CNY 18.952–21.752 billion. Sub-regional analyses revealed that the Liao River Basin and Taihang Mountains zones exhibited relatively lower ecological returns. Correlation analysis indicated strong relationships between afforestation cost and sand-fixing capacity in certain regions (|cor| = 0.89–0.91), moderate correlations in others (|cor| ≈ 0.59), and weak correlations in some areas (|cor| ≈ 0.47), accounting for 1.58 %, 6.19 %, and 7.62 % of the total area, respectively. These findings establish a preliminary cost-effectiveness evaluation framework, highlighting the linkages between financial investments and ecological benefits. Regions showing positive correlations demonstrate high ecological payoffs from investment, while negatively correlated areas suggest issues of diminishing returns and resource misallocation. • Focus on the sustainability of large-scale environmental restoration project. • Linking ecological return assessment and cost-efficiency analysis. • Identification of low-efficiency area for sand fixation. • Engineering cost-efficiency analysis at pixel level. • Correlation analysis between investment and windbreak-sand fixation benefits.

Developing good practices and organisational resilience during the COVID-19 pandemic: A retrospective qualitative case study in a higher education institution