Life Cycle Framework Research Articles

Comprehensive review of additive manufacturing lifecycle optimization in a cloud environment: from distributed manufacturing to postprocessing

Purpose This paper aims to offer a comprehensive review and categorization of production optimization throughout the additive manufacturing lifecycle in a cloud environment. It aims to provide a structured approach to identifying and addressing issues. Design/methodology/approach This paper systematically reviews 75 technical papers on cloud manufacturing, nesting, scheduling and postprocessing in additive manufacturing. This includes a detailed discussion of the key issues. Findings This paper introduces a production framework for the entire lifecycle of additive manufacturing in a cloud environment. This framework aids in problem identification and decision-making based on the process flow. It provides an integrated view from cloud to postprocessing, examining decision interdependencies and enhancing problem identification and organization. Originality/value To the best of the authors’ knowledge, this paper is the first to review the complete lifecycle of additive manufacturing, emphasizing the often-overlooked aspects of postprocessing and cloud manufacturing. It offers a comprehensive study of lifecycle optimization challenges and suggests ways to streamline the production process.

The security impact of Nigerian fallow tourist attractions on the residents of surrounding communities

Amidst globalisation, tourism industry has emerged as a huge revenue source for different countries across the globe, most especially in the developed world. Nigeria is one of the developing countries that are yet to fully tap their tourism potentials, due to many socio-political factors. Beyond undermining the country’s quest for economic diversification, fallow tourist attractions across the country hypothetically negate internal safety and security, hence the need for empirical researches to inform policy interventions. This study specifically focused on Zuma Rock (in Niger state) to examine the relationship between the rock’s physical surrounding and criminal occurrences, analyse the feeling of safety among the residents of communities surrounding it, and establish the extent of their confidence in the formal agencies of social control. The study utilised area life cycle model to view the place of the rock in relation to other developed tourist sites, which shows it remains at the first stage of tourism development. Further, insight was drawn from defensible space theory to analyse the relationship between the rock’s physical environment and crime. A mixed-methods approach involving quantitative and qualitative data was adopted for the study. A total of 304 respondents across five communities surrounding the rock were randomly selected for questionnaire administration, and additional 80 were judgementally selected for a total of 10 FGD sessions—two in each of the five selected communities. In light of the area life cycle and defensible space framework, the study found that failure to develop a notable tourist attraction breeds crime. It is also found that the study population live in fear due to the prevalence of violent crimes in the rock’s vicinity, and their lack of confidence in formal law enforcement agents. It is therefore recommended that government should prioritise the development of the destination while making effort to strengthen the law enforcement agencies.

Enhancing preparedness by developing robust implementation

Abstract In EUVABECO, a goal is defined as a public health objective that motivates a vaccination practice. A vaccination practice encompasses specific methods or approaches used in vaccination efforts, while a tool refers to a tangible resource or software developed to support the implementation of these practices. EUVABECO is undertaking a series of structured activities from January 2024 until mid-2026. These include mapping innovative practices, deriving requirements for tools and validation plans, developing implementation plans, and facilitating their adoption by European MS. The project will also evaluate, validate, and verify these plans to ensure their efficacy and sustainability. EUVABECO’s methodology is informed by the Systems Development Lifecycle (SDLC) framework, utilizing the V-model to ensure a strong linkage between the development and testing phases, thereby guaranteeing a cohesive workflow. Each implementation plan developed will feature comprehensive policy recommendations and a workplan that covers the necessary organizational, technical, legal, and ethical aspects required for the tool’s deployment. Additionally, these plans will include tailored strategies to enhance the tool’s functionality during outbreaks, criteria for verifying implementation effectiveness, and financial considerations critical for supporting adoption. The implementation plans will undergo a rigorous validation process to assess their suitability, transferability, and sustainability across MS. The ultimate goal is to disseminate validated plans whilst ensuring a parallel multistakeholder engagement approach to ensure MS are actively involved in key project phases, thus, facilitating rapid uptake of said plans across EU MS and a transformation of the vaccination ecosystem across Europe.

The Gender Investment Gap over the Life Cycle

Abstract Single women invest less in risky assets than do single men. This paper analyzes the determinants of the “gender investment gap” based on a structural life-cycle framework. The model can rationalize the gender investment gap without gender heterogeneity in preferences. Rather, lower deterministic income and larger household sizes shift the composition of single women toward poorer households that invest less risky (composition effect). Additionally, future outcomes of both variables (which cannot easily be controlled for in regressions) make single women more vulnerable to financial shocks and decrease their optimal equity share even conditional on state variables (policy effect). (JEL E21, G11, G50, J16)

Integrating life cycle assessment and multi criteria decision making analysis towards sustainable cocoa production system in Indonesia: An environmental, economic, and social impact perspective

Sustainable Cocoa production practices should be investigated comprehensively to address sustainability requirements and mitigate Cocoa production issues in Indonesia. This study aims to identify the sustainable Cocoa production system considering the environmental, economic, and social impacts. Life cycle framework and multicriteria decision-making (MCDM) were integrated to obtain the study's objectives by comparing Cocoa monocropping system (CM) and Cocoa intercropping systems (IC). The result indicated that in the environmental sustainability aspect, the monocropping system (CM) showed higher performance as indicated by the lower environmental impact in all indicators; for example, CM emitted a lower Global Warming Potential (GWP) that has a lower margin of 34.5–55.9 % compared to the intercropping system (IC-I and IC-II). In the economic aspect, both on the short-term and long-term analysis, the Cocoa intercropping system (IC-II) generated higher value-added and economic feasibility, with a higher profit margin of 150–205 % compared to CM and IC-1. Along with the increase of economic benefits in IC II, this system also significantly provides social benefits, as presented by the higher social index margin of 4.9–23.7 % compared to other systems. Furthermore, by applying decision-making analysis, the result determines the highest index on the Cocoa intercropping system II (IC-II). These findings highlight that applying the intercropping system II is recommended to overcome the cocoa issue at the farmer and decision-maker levels. Additionally, the proposed method that combined LCA-MCDM can be applied to another agricultural commodity to achieve sustainable agriculture production.

Data Monetization Service Development Using Iterative Lifecycle Framework, Quality Assurance, and Open Web Application Security Project: A Case Study of a Utility Company in Indonesia

The research aims to provide Data Monetization (DM) services for an Indonesian utility company as a pilot to generate additional revenue beyond the primary operation. The service is built using an iterative development lifecycle framework and evaluated based on five Quality Goals (QGs), including application and security testing activities. The framework includes methods for processing and modeling electricity usage data, testing application quality, checking infrastructure quality, and ensuring access security for front-end and back-end applications using the Open Web Application Security Project (OWASP). For data modeling, Support Vector Regression (SVR) is used, and it outperforms Polynomial Regression (PR) and Multi-Layer Perception (MLP) Neural Networks. Furthermore, QG shows strong performance with an Relative Root Mean Squared Error (RRMSE) value < 10%, high forecasting ability with Mean Average Probability Error (MAPE) < 10%, and a near-zero average error rate (Mean Squared Error (MSE)) square using minimal data from four months. The services go through functional and integration test to ensure product quality and application performance, which results in a minimum of 95% service response in throughput, 0.128 seconds for processing 2,000 requests, stability at 300–500 in one second per hour, and 7–21 seconds during peak hours. Additionally, the service passes nine penetration tests and ten vulnerability assessments using the OWASP top 10:2021 category. Based on the comprehensive testing and evaluation results, both the application and the service are considered ready and secured for deployment.

An Urban Renewal Design Method Based on Carbon Emissions and Carbon Sink Calculations: A Case Study on an Environmental Improvement Project in the Suzhou Industrial Investment Science and Technology Park

In the process of urban renewal, the high carbon emissions caused by pollution from construction waste and the consumption of materials and energy via “demolition and construction” present significant problems. Calculating carbon emissions and sinks is a prerequisite to carving out a low-carbon path via urban renewal. In this paper, we take an environmental improvement project in the Suzhou Industrial Investment Science and Technology Park as an example. Under the framework of the entire life cycle, we define the “renewal phase”, which includes “demolition” and “construction”, as the calculation boundary, and use the emission coefficient method as the primary calculation approach to assess carbon emissions and sinks. We construct a design-oriented carbon revenue and expenditure estimation system based on the BIM model. After its application in empirical cases, the results show the following: ① The building carbon emissions of Scheme A are 342 t higher than those of Scheme B, due to the fact that the “demolition and construction” works in the former increased by 6000 m2 compared to the latter. ② The landscape carbon emissions of Scheme B are 269 t higher than those of Scheme A, due to the addition of a 2500 m2 reinforced concrete overhead walking platform. ③ The annual carbon sink of Scheme A is six times higher than that of Scheme B, due to the fact that the number of trees and shrubs in the former is five-to-six times greater than in the latter. The number of trees planted plays a decisive role in enhancing the carbon sink benefit. ④ In the year during which the renewal project was implemented, the difference in carbon emissions between Scheme A and Scheme B was 72.9 t. By the 16th year, the difference in carbon emissions between the two schemes approached zero, and the carbon reduction advantages of Scheme A became more pronounced over the entire life cycle thereafter. Finally, this article summarizes four low-carbon design strategies for industrial park renewal projects: rational construction and demolition, three-dimensional parking, low-carbon materials, and plant carbon sequestration. In the context of inventory renewal, this article makes a significant contribution in terms of carbon footprint control and the “dual-carbon” goal.

Low-altitude intelligent transportation: System architecture, infrastructure, and key technologies

In the context of the burgeoning low-altitude economy, low-altitude intelligent transportation (LAIT) has emerged as the focal point of research. This study comprehensively explores the current state, challenges, and future development prospects of LAIT from three key aspects: system architecture, infrastructure, and critical technologies. First, we propose a future LAIT system framework based on a cyber-physical system (CPS) layered architecture to provide a potential solution for urban air transport. Second, we introduce a framework for the entire lifecycle and management chain of the LAIT system, offering an in-depth analysis of each stage from design, construction, and operation to management, with the aim of realizing intelligent management and operation of low-altitude transportation. Finally, this study discusses the technical, security, and social challenges that future LAIT will face in the context of Industry 4.0, while envisioning the pathways of technological innovation. It summarizes the need for advanced infrastructure and breakthroughs in key technologies such as the Internet of Things (IoT), 6G, artificial intelligence (AI), and low-altitude geographic information system. This study provides a systematic framework and technical guidelines for the future development of low-altitude intelligent transportation, supporting continuous innovation, and upgrading the low-altitude economy.

Research on carbon emission reduction based on responsibility of four participants with consideration of circular economy factors in China

Abstract The complex relationship between carbon emissions and economic development has become a global issue. In China, the pressure to reduce carbon emissions is very great because the responsibility of four participants for economic activities has not been able to break away from the linear economic model of ‘produce-consume-discard’. In this paper, four categories of participants, namely extractors/producers, manufacturers, consumers and recyclers, are classified according to the life cycle framework, and the impact of their activities on carbon emission reduction is analysed taking into account circular economy factors. The results of the study show that during the rapid development of China’s economy from 2005 to 2021, there is a significant correlation between carbon emission reduction and the activity behaviour of the four participants with consideration of circular economy factors. In particular, the activity behaviours of the extractors/producers, manufacturers and consumers have a very strong correlation with the carbon emission reduction. Our findings indicate that China should continue to exert efforts in the existing circular economy model to achieve the double carbon goals.

A Novelty Model Employing the Quality Life Cycle Assessment (QLCA) Indicator and Frameworks for Selecting Qualitative and Environmental Aspects for Sustainable Product Development

The objective of this investigation was: (i) to develop a model that supports sustainable product development, considering the quality aspect and the environmental impact in the product life cycle, and (ii) to establish a framework to select the proportion of the share of these aspects during product development decisions. This research concentrates on achieving products that meet customer demand and have environmentally friendly life cycles. It also supports the implementation of design activities at an early stage of product development, positioning the share of quality in relation to environmental impact. The model is based on creating hypothetical prototypes of current products, and this approach concentrated on aggregating the quality (customer satisfaction) with life cycle environmental impacts (as in ISO 14040). The model was developed in five main stages, including: (i) defining product prototypes according to the modifications of quality criteria most desired by customers, (ii) assessing the quality of prototypes according to the Q quality index, (iii) prospective assessment of the environmental impacts of the life cycles of prototypes according to the LCA environmental index, (iv) methodical integration of the above-mentioned indicators into one quality and environmental indicator QLCA, and (v) analysis of possible production solutions and setting the direction of product development, taking into account both quality and environmental aspects. This research was extended with a sensitivity analysis of the QLCA indicator, after which a framework for selecting the proportion of the Q and LCA indicator’s share in product development decisions was established. The originality of this research is the ability of the developed model to facilitate eco-innovative product design and improvements while also selecting the share of qualitative and environmental aspects needed to develop sustainable products. The results provide a dynamic and effective tool for manufacturing companies; mainly designers and managers during qualitative and environmental prototyping of products commonly used by customers. The model will provide support in predicting a product that will be manufactured that will be satisfactory for customers and environmentally friendly based on LCA.

A Standard Approach to Project-Based Learning in a Clinical Informatics Fellowship.

The Accreditation Council for Graduate Medical Education suggests that Clinical Informatics (CI) fellowship programs foster broad skills, which include collaboration and project management. However, they do not dictate how to best accomplish these learning objectives. This study aimed to describe a standard approach to project-based learning for CI, to share its implementation, and to discuss lessons learned. We created a standard approach to project-based learning based on concepts from adult learning theory, the project life cycle framework, the Toyota Production System, and Improvement Science. With this standard approach in place, we learned how best to support fellows in its use. In addition to this approach to supporting needs assessment, risk/change management, implementation, and evaluation/improvement skills, we found the need to develop fellow skills in collaboration, leadership, and time management/managing up. Supported by project-based learning using this standard approach, and with targeted project selection to meet topic-based learning objectives, fellows reached the ability to practice independently in 15 to 21 months. Fellows are uniquely positioned to ensure the success of projects due to their increased availability and protected time compared with attendings. They are readily available for project teams to draw upon their expertise with clinical workflows and understanding of technological solutions. Project-based learning addressing organizational priorities complements fellow project management coursework and improves fellows' ability to function successfully in large, complex, and dynamic organizations. Exposing fellows to contemporary problems, then addressing them through projects, provides fellows with up-to-date applied informatics knowledge. Project-based learning can ensure that many general CI learning objectives are supported inherently. It reinforces project management teachings, while providing fellows with a marketable project portfolio to aid with future job applications. Having projects tightly aligned with organizational priorities supports ongoing investment in fellowship programs.

Incorporating Anti-racist Principles Throughout the Research Lifecycle: A Position Statement from the Society of General Internal Medicine (SGIM).

Biomedical research has advanced medicine but also contributed to widening racial and ethnic health inequities. Despite a growing acknowledgment of the need to incorporate anti-racist objectives into research, there remains a need for practical guidance for recognizing and addressing the influence of ingrained practices perpetuating racial harms, particularly for general internists. Through a review of the literature, and informed by the Research Lifecycle Framework, this position statement from the Society of General Internal Medicine presents a conceptual framework suggesting multi-level systemic changes and strategies for researchers to incorporate an anti-racist perspective throughout the research lifecycle. It begins with a clear assertion that race and ethnicity are socio-political constructs that have important consequences on health and health disparities through various forms of racism. Recommendations include leveraging a comprehensive approach to integrate anti-racist principles and acknowledging that racism, not race, drives health inequities. Individual researchers must acknowledge systemic racism's impact on health, engage in self-education to mitigate biases, hire diverse teams, and include historically excluded communities in research. Institutions must provide clear guidelines on the use of race and ethnicity in research, reject stigmatizing language, and invest in systemic commitments to diversity, equity, and anti-racism. National organizations must call for race-conscious research standards and training, and create measures to ensure accountability, establishing standards for race-conscious research for research funding. This position statement emphasizes our collective responsibility to combat systemic racism in research, and urges a transformative shift toward anti-racist practices throughout the research cycle.

The relationship between firm life cycle and firm strategies: A systematic review and future direction

The business life cycle is examined through a comprehensive literature review in this academic study. Our initial approach involves searching for relevant articles on firm life cycle and strategy using the Web of Science and Scopus databases. We conduct bibliometric analyses to identify key contributors and recurring keywords. Subsequently, we select twenty-seven research papers to explore the Theory Development, Characteristics, Context, and Methodology (TCCM) framework for firm life cycle and strategy. Our analysis summarizes corresponding business strategies for each stage, including the use of Initial Management Control Systems (MCS) in the introduction phase. As companies grow, a high inventory-to-sales ratio may hinder effectiveness, but it proves beneficial in the growth and revival stages. Mature companies excel in green process innovation and engage more in Corporate Social Responsibility (CSR) activities. In the decline stage, firms use cost efficiencies, asset retrenchment, and core activity focus for recovery, signaling commitment to a successful turnaround. However, there is a research gap in exploring appropriate global strategies for various life cycle stages, providing an opportunity for additional articles to thoroughly investigate this relationship and assess multinational enterprises’ success trajectories throughout their life cycles.

Applying a Master Project Plan Methodology to Develop an Age-Friendly 4Ms Clinical Documentation Tool.

The issue of lacking standardized organizational guidance is examined in the context of providing patient-centered care to meet the needs of an aging population. Standardization across an integrated organization is increasingly recognized as a social justice concern in the pursuit of equitable and timely healthcare delivery, particularly as the healthcare industry grapples with a severe nursing shortage in the United States. A master project plan methodology (MPPM) was tested to effectively develop an electronic Age-Friendly 4Ms documentation tool using the system development lifecycle (SDLC) framework. The MPPM successfully guided the design and national implementation, achieving an 84% installation rate across 124 facilities within one of America's largest integrated healthcare systems.

A parametric life cycle framework to promote sustainable-by-design product development: Application to a hydrogen production technology

The European Ecodesign Directive is an effective normative framework that has been extensively proven to support the energy transition of numerous European industrial sectors. From an analytical standpoint, it provides practitioners with the EcoReport tool, a simplified life cycle spreadsheet that is aimed at guiding the development of ecodesign measures of mandatory compliance in European countries. In this regard, several studies have highlighted the limitations of the EcoReport tool when addressing emerging technologies like those tied to the hydrogen sector. These works also propose to further integrate material criticality and social metrics in order to enlarge the scope of the European Directive and foster the shift from ecodesign to sustainable-by-design product development. In this situation, building upon the principles of the EcoReport tool and recognizing the outcomes of the aforementioned critical analyses, the conceptualization of a novel sustainable-by-design framework is presented and applied to a Solid Oxide Electrolysis Cell (SOEC) stack for hydrogen production. The operationalization of the framework is conducted, for the first time in the context of sustainable design, by combining the use of the Brightway2 and lca_algebraic Python packages. Overall, the proposed approach succeeds in providing a complete sustainability perspective to the design of emerging technologies. Regarding the tangible lessons learned on the hydrogen-related case study, product concepts are proven to progressively improve the sustainability performance of the technology. It is noticeable that the enhancement of the economic competitivity is more limited than that achieved at the remaining sustainability indicators (i.e., environmental, social and material criticality metrics). In line with the outcomes of the life cycle contribution assessment, multi-criteria decision analysis ratings lead to concluding that a sustainable-by-design SOEC stack product concept should prioritize limiting its material intensity.

The life cycle of large language models in education: A framework for understanding sources of bias

AbstractLarge language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM‐based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education technology has renewed concerns over algorithmic bias, which may exacerbate educational inequalities. Building on prior work that mapped the traditional machine learning life cycle, we provide a framework of the LLM life cycle from the initial development of LLMs to customizing pre‐trained models for various applications in educational settings. We explain each step in the LLM life cycle and identify potential sources of bias that may arise in the context of education. We discuss why current measures of bias from traditional machine learning fail to transfer to LLM‐generated text (eg, tutoring conversations) because text encodings are high‐dimensional, there can be multiple correct responses, and tailoring responses may be pedagogically desirable rather than unfair. The proposed framework clarifies the complex nature of bias in LLM applications and provides practical guidance for their evaluation to promote educational equity. Practitioner notesWhat is already known about this topic The life cycle of traditional machine learning (ML) applications which focus on predicting labels is well understood. Biases are known to enter in traditional ML applications at various points in the life cycle, and methods to measure and mitigate these biases have been developed and tested. Large language models (LLMs) and other forms of generative artificial intelligence (GenAI) are increasingly adopted in education technologies (EdTech), but current evaluation approaches are not specific to the domain of education. What this paper adds A holistic perspective of the LLM life cycle with domain‐specific examples in education to highlight opportunities and challenges for incorporating natural language understanding (NLU) and natural language generation (NLG) into EdTech. Potential sources of bias are identified in each step of the LLM life cycle and discussed in the context of education. A framework for understanding where to expect potential harms of LLMs for students, teachers, and other users of GenAI technology in education, which can guide approaches to bias measurement and mitigation. Implications for practice and/or policy Education practitioners and policymakers should be aware that biases can originate from a multitude of steps in the LLM life cycle, and the life cycle perspective offers them a heuristic for asking technology developers to explain each step to assess the risk of bias. Measuring the biases of systems that use LLMs in education is more complex than with traditional ML, in large part because the evaluation of natural language generation is highly context‐dependent (eg, what counts as good feedback on an assignment varies). EdTech developers can play an important role in collecting and curating datasets for the evaluation and benchmarking of LLM applications moving forward.

CausalOps — Towards an industrial lifecycle for causal probabilistic graphical models

Context:Causal probabilistic graph-based models have gained widespread utility, enabling the modeling of cause-and-effect relationships across diverse domains. With their rising adoption in new areas, such as safety analysis of complex systems, software engineering, and machine learning, the need for an integrated lifecycle framework akin to DevOps and MLOps has emerged. Currently, such a reference for organizations interested in employing causal engineering is missing. This lack of guidance hinders the incorporation and maturation of causal methods in the context of real-life applications. Objective:This work contextualizes causal model usage across different stages and stakeholders and outlines a holistic view of creating and maintaining them within the process landscape of an organization. Methods:A novel lifecycle framework for causal model development and application called CausalOps is proposed. By defining key entities, dependencies, and intermediate artifacts generated during causal engineering, a consistent vocabulary and workflow model to guide organizations in adopting causal methods are established. Results:Based on the early adoption of the discussed methodology to a real-life problem within the automotive domain, an experience report underlining the practicability and challenges of the proposed approach is discussed. Conclusion:It is concluded that besides current technical advancements in various aspects of causal engineering, an overarching lifecycle framework that integrates these methods into organizational practices is missing. Although diverse skills from adjacent disciplines are widely available, guidance on how to transfer these assets into causality-driven practices still need to be addressed in the published literature. CausalOps’ aim is to set a baseline for the adoption of causal methods in practical applications within interested organizations and the causality community.

A comparative analysis of recent life cycle assessment guidelines and frameworks: Methodological evidence from the packaging industry

In recent years, a number of new guidelines and frameworks for Life Cycle Assessment (LCA) have emerged, trying to support analysts in dealing with certain methodological issues and “gaps” of the ISO 14040-44, that are still the main LCA reference standards. This trend can be considered as positive, because the lack of shared, standardised and more detailed rules regarding LCA has affected for years the consistency of LCA analyses and their potential comparisons. However, the proliferation of guidelines and frameworks can also have negative consequences, first of all related to the potential resulting confusion and the lack of a clear reference for LCA analysts. These potential risks are particularly accentuated for multinational companies, which deal with many clients, in different markets, countries and sectors, and have to conform their analyses to different requirements each time.Focusing on the plastic packaging industry, this study compares six LCA guidelines and frameworks to highlight their similarities and differences. The documents selected to be analysed were: three documents applicable to products in general (ILCD, PAS 2050 and PEF), two packaging-specific guidelines (Pathfinder Framework and SPICE Methodological Guidelines) and a product specific standard for the packaging industry (PCR 2013:19). The methodological aspects analysed and compared, grouped according to the LCA stages, are: units of analysis; system boundaries; allocation methods; cut-off criteria; end-of-life; packaging; storage; biogenic CO2 emissions; carbon removals and carbon content; land use; offsets; impact categories and indicators; LCA methods and models; normalisation and weighting; data quality; sensitivity analysis. The aim is to understand to what extent potential differences may impact on companies and LCA analysts who conduct the assessments. Results highlight that the six guidelines and frameworks analysed are not always aligned and that, although some misalignments can be easily addressed, others could negatively affect the reliability of the analyses conducted.

From Pixels to Principles: A Decade of Progress and Landscape in Trustworthy Computer Vision

The rapid development of computer vision technologies and applications has brought forth a range of social and ethical challenges. Due to the unique characteristics of visual technology in terms of data modalities and application scenarios, computer vision poses specific ethical issues. However, the majority of existing literature either addresses artificial intelligence as a whole or pays particular attention to natural language processing, leaving a gap in specialized research on ethical issues and systematic solutions in the field of computer vision. This paper utilizes bibliometrics and text-mining techniques to quantitatively analyze papers from prominent academic conferences in computer vision over the past decade. It first reveals the developing trends and specific distribution of attention regarding trustworthy aspects in the computer vision field, as well as the inherent connections between ethical dimensions and different stages of visual model development. A life-cycle framework regarding trustworthy computer vision is then presented by making the relevant trustworthy issues, the operation pipeline of AI models, and viable technical solutions interconnected, providing researchers and policymakers with references and guidance for achieving trustworthy CV. Finally, it discusses particular motivations for conducting trustworthy practices and underscores the consistency and ambivalence among various trustworthy principles and technical attributes.

Analysis and Reflection on the Strategy Benchmarking of Power Battery Management in China and Europe

In 2023, the European Union (EU) enacted the Regulation on Batteries and Waste Batteries (hereinafter referred to as the New Law on Batteries), which strengthens the regulatory framework for the entire lifecycle of power batteries. This development presents both challenges and opportunities for global power battery manufacturers and operators. As a significant player in the global power battery industry chain and the world’s largest producer of electric vehicles and power batteries, China must systematically assess the impact of global battery management strategies, including the EU’s New Law on Batteries, from a lifecycle perspective. This understanding is crucial for maintaining China’s competitive edge in the global power battery market and achieving mutually beneficial outcomes in international trade negotiations. This paper constructs a strategy analysis framework based on the lifecycle approach. By summarizing the power battery management strategies of both the EU and China, it provides a comprehensive overview of strategies across different countries, highlights the key regulatory focus areas, and offers relevant strategy recommendations. The main conclusions and insights are as follows: (1) The New Law on Batteries achieves lifecycle regulation from “cradle” to “grave” and back to “cradle”. (2) China emphasizes the management of waste power batteries, with an increasingly robust strategy system at the recycling stage, yet lacks comprehensive measures for other lifecycle stages. (3) The EU has established a comprehensive lifecycle strategy management system centered on the New Law on Batteries, characterized by strong coordination and a synergistic combination of strategies across different sectors. Finally, this paper identifies three major compliance challenges posed by the New Law on Batteries, necessitating enhanced strategy development and implementation in the areas of carbon footprint management, circular economy, and digital battery passports.