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The militarisation of Artificial Intelligence Diplomacy has resulted in the development of heavy weapons that are more powerful than traditional weaponry, fail to distinguish between civilians and combatants, and cause unnecessary suffering. Superpowers and middle powers have made significant investments in digital technologies, resulting in the production of digital weapons that violate international humanitarian law and human rights standards, and complicate the achievement of global peace. Armed drones and militarised robots cause unnecessary pain and suffering to helpless civilians. These weapons have been used to combat terrorism, but, surprisingly, have not addressed issues of terrorism that affect post-Cold War international relations. As a result, the use of armed drones is causing more harm than is necessary to achieve the objective of war. There is a call for international artificial intelligence (AI) governance, as well as a need to understand the effects and serious threats that armed drones pose to international humanitarian law (IHL), as well as to peace processes in international relations and global cooperation. Scholars, policy-makers, human rights activists and peace practitioners should participate more actively in debates about the military application of AI diplomacy, in order to develop effective AI diplomacy rules and regulations. This serves to mitigate the risks and threats associated with armed drones on IHL and international human rights standards, which are the foundations of the post-modern world.

Accurate and well-managed medical records play a major role in high-quality health care. They are a valuable asset that allows hospitals to treat patients in an effective and efficient way. They also play an important role in health care governance, providing evidence in court cases between patients and hospitals. However, in Africa, medical records are not given much academic attention. Good record-keeping has been hampered by a poor management, as well as a lack of trained personnel who understand how to record and keep these records. This study is aimed at exploring the utilisation of blockchain technology in improving medial records at African hospitals. The reserach is qualitative, comprising desktop research of secondary material and its analysis. It finds that poor medical records in hospitals contribute to the prevalence of disease in African countries, which results in funds that could be invested in development projects being diverted to health care instead. It also shows that 4IR, specifically blockchain-based technology, could play a significant role in the management of medical records in Africa. It could help staff to capture and maintain more accurate medial records, and ensure their security and longevity. Moreover, it could improve access to medical records for all health practitioners. Patients could also access their records, thus helping them to evaluate and manage their own health.

International audience; Value Analysis (VA) is a collaborative method that could be used to make a decision in the early phase of complex projects. In this framework, Stakeholders are involved into the process of decision-making and project success is facilitated. Systeme Architechting (SA) is a set of processes used for the conceptual phase of the design of complex systems while System Engineering (SE) is the set of processes used for the design phase of the system. The difference resides in the information on which the decision-making is based: it is very abstract in the architecting phase while it is materialized in the engineering phase. In complex projects, Stakeholders are multiple and carry specific technical, social and environmental expectations that define their perceived Value of the project. The aim of this paper is to demonstrate that VA and SA are two complementary approaches to collect and analyse Stakeholder needs in a complex project. The article presents an analysis of the literature review on VA and SA / SE, which shows the complementarity of these approaches to involve Stakeholders in the upstream phases of the design of complex systems. Based on this analysis, an illustration case is proposed to show how to integrate VA into SA to understand the needs of Stakeholders. The article concludes that the two methods VA and SA can be combined to analyze and would allow following several dimensions of Value (economic, social and environmental) within a complex project.

International audience; Stakeholders are key elements of complex technical projects. They can determine orientation, evolution and success of the project. They can cause uncertainties, changes in objectives and lead the project to failure. In this context, it is always more important to involve them in project decisions. Value Analysis (VA) is a means to introduce management and decision-making in design of complex projects, based on stakeholder needs. A method named Function Analysis aims at identifying and treating functions that the system has to complete. However, this functional approach does not allow some non-functional attributes to be included in the design phases. This is a lack identified by some engineering companies. The proposed paper aims at identifying the challenges encountered by the Stakeholder approaches to translate their needs into nonfunctional dimensions to deal with VA practices to design technical solutions. The research methodology combines a classical bibliographical analysis on VA that led us to show FA limits. Thus, we propose a Stakeholder-based “Non-Functional Analysis” to determine the non-functional attributes to characterize for the design of complex projects, and an industrial company’s feedback practices on a case study. This will allow practitioners to have a systems approach to Value in the context of a VA but it will also allow scientists to compare theory and lack of practice around the identification and characterization of the needs of a set of stakeholders.

Due to social, environmental and technical evolutions, complex technical projects (numerous stakeholders and several/high level expertises) need to evolve in their management practices. Many management and design methodologies exist to limit costs and resources used in a project. The proposed paper aims at identifying the challenges encountered in complex projects’ management and determining how one of them, the Value Management, should be evolved. The research methodology combines a bibliographical analysis (on engineering methodologies for complex projects’ management) and a demonstration of Value Management interest on a case study to address sustainable stakes.

International audience; In the context of autonomous navigation, the vehicle trajectory estimation and the detection of surrounding obstacles are two critical functionalities that must be robust to difficult environmental conditions (e.g. fog, dust, snow) and the unavailability of infrastructure signals (e.g. GPS). With the advantage of remaining operable in low-visibility conditions, radar sensors are good candidates to detect obstacles in an autonomous navigation context. In this paper, we show that radars can also be successfully used for real-time trajectory estimation. We address the case of an autonomous micro-drone intended for the exploration of piping networks and embedding a Frequency Modulated Continuous Waves (FMCW) MIMO radar. We show that using a beamforming technique to virtually steer the radar field-of-view, we can simultaneously estimate the horizontal and vertical velocity of the drone as well as its height. These results are first validated through simulations based on experimental drone flight data and a radar simulator. Then, using an \textit{Infineon} $77GHz$ FMCW radar, we show through real-world experiments the high performance attainable with our solution with a velocity estimation accuracy of up to $0.03m.s^{-1}$.

This paper proposes a recursive interval-valued estimation framework for identifying the parameters of linearly parameterized systems which may be slowly time-varying. It is assumed that the model error (which may consist in measurement noise or model mismatch or both) is unknown but lies at each time instant in a known interval. In this context, the proposed method relies on bounding the error generated by a given reference point-valued recursive estimator, for example, the well-known recursive least squares algorithm. We discuss the trade-off between computational complexity and tightness of the estimated parametric interval., 11 pages, 4 figures

Seconde soumission; International audience; Value Analysis (VA) is a collaborative method that could be used to make decision-making in complex projects. System Engineering (SE) is a design method used in complex projects. In complex projects, stakeholders are multiple and carry specific technical, social and environmental expectations that define the value of the project. The aim of this paper is to demonstrate that VA and SE are two complementary approaches to collect and analyzeStakeholder’ expectations in a complex project. The paper presents a literature review on VA and SE that show the complementarity of the methods to involve Stakeholders in projects. From this analysis,a case study is proposed to illustrate the complementarities of the method. The paper concludes that the two methods VA and SE can be combined to analyzeand track multiple dimensions of value (as economic, social and environmental) ina complex projectcontext.

The chapter explores financial exclusion, its causes, and consequences in society. The chapter found that the existing discrepancy in financial inclusion between the developed and developing world is driven by financial exclusion that makes it difficult for financial service providers to expand outreach to the poor at affordable prices. The chapter aims to investigate the role of mobile financial service design and development in dealing with financial exclusion. It was found that mobile financial services are promoting financial inclusion in various markets. However, few studies have been undertaken on the benefits of mobile financial services in dealing with the high rates of financial exclusion. The chapter recommended that to achieve financial inclusion, there is need for mobile financial services providers to take into account customer experience through the ease of using the phone interface. The chapter concluded that there is need for scholars in the fields of finance and economics to conduct research in the areas of mobile financial services and their role in society.

International audience; This paper deals with the analysis of a class of offline state estimators for LTI discrete-time systems in the presence of an arbitrary measurement noise which can potentially take any value. The considered class of estimators is defined as the solution of an optimization problem involving a performance function which can be interpreted as a generalization of cost functions used in the Maximum Correntropy Criterion. The conclusion of the analysis is that if the system is observable enough, then the considered class of estimators is resilient, which means that the obtained estimation error is independent from the highest values of the measurement noise. In the case of systems with a bounded process noise, the considered class of estimators provides a bounded estimation error under the appropriate conditions despite not being designed for this scenario.

International audience; This paper proposes to analyze the resilient properties of a specific state estimator for LTI discrete-time systems. The dynamic equation of the system is assumed to be affected by a bounded process noise. As to the available measurements, they are potentially corrupted by a noise of both dense and impulsive natures. In this setting, we define an estimator as the map which associates to the measurements, the minimizing set of an appropriate (convex) performance function. It is then shown that the proposed estimator enjoys the property of resilience, that is, it induces an estimation error which, under certain conditions, is independent of the extreme values of the (impulsive) measurement noise. Therefore, the estimation error may be bounded while the measurement noise is virtually unbounded. Moreover, the expression of the bound depends explicitly on the degree of observability of the system being observed and on the considered performance function. Finally, a few simulation results are provided to illustrate the resilience property.

International audience; The quality of requirements is fundamental in engineering projects. Requirements are usually expressed partly or totally in a natural language (NL) format and come from different documents. Their qualities are difficult to analyze manually, especially when hundreds of thousands of them have to be considered. The assistance of software tools is becoming a necessity. In this article, the goal was to develop a set of metrics supported by NL processing (NLP) methods supporting different types of analysis of requirements and especially the dependencies between requirements. An NLP approach is used to extract requirements from text; to analyze their quality, links, similarities , and contradictions; and to cluster them automatically. The analysis framework includes different combinations of methods such as cosine similarity, singular value decomposition, and K-means clustering. One objective is to assess the possible combinations and their impacts on detections to establish optimal metrics. Three case studies exemplify and support the validation of the work. Graphs are used to represent the automatically clustered requirements, as well as similarities and contradictions. A new contradiction analysis process that includes a rules-based approach is proposed. Finally, the combined results are presented as graphs, which unveil the semantic relationships between requirements. Subsection 4.8 compares the results provided by the tool and the results obtained from experts. The proposed methodology and network presentation not only support the understanding of the semantics of the requirements but also help requirements engineers to review the interconnections and consistency of requirements systems and manage trace-ability. The approach is valuable during the early phases of projects when requirements are evolving dynamically and rapidly.

This article examines good governance-mediation nexus in peace processes and its role in leading to the creation of a peaceful society and sustainable peace. After defining the concepts of mediation, governance and good governance, and examining their interaction, the article critically assesses the African Union’s (AU’s) peace agreement for Burundi to explain that the failure of good democratic governance in the country is actually resulting from the failure of African mediators to understand the role of good governance when conducting the mediation process. The article shows that post-mediation phases in Africa are characterised by the recurrence of armed conflicts and electoral violence because of the failure to bring principles of good governance to the negotiation table. It proves that African mediators are former African leaders whose democratic good governance while in power was lacking; therefore, they are unable to understand the interaction between good governance and mediation when involved in the mediation process. Hence, deploying such leaders to conduct a mediation process is a fatal mistake amounting to burying a conflict alive. The article shows that African conflicts are intrastate in nature, and are triggered by the presence of uneven institutions that protracted bad governance and by the rebels who fight the governments, which state of affairs is exacerbated by a lack of understanding of what good governance means. The article concludes by asserting that it is vital for the deployed mediators to understand the interaction between good governance and mediation, and to teach the parties to understand the principles of good governance, and persuade them to be bound by those principles. Unless this interaction is understood and brought on-board at the negotiation table, conflicts in Africa will remain an unfinished business.

International audience; Systems Engineering (SE) has been initially developed to manage large complex system development in the defence or aerospace industry. As the complexity of product increases, the product development approaches evolved accordingly. Complex architectures have to be developed including multiple disciplines of engineering (software, electronics, mechanics etc..). Automotive industry moved to SE about 15 years ago, medical devices industry had been implementing such models to meet accreditation agencies requirements and general industry is now transforming their processes to address complex solution that add value to their customers. Moreover, some companies started to apply Model Based System Engineering (MBSE) in their processes to validate requirements and architectures. MBSE tools have been progressing for a decade, yet MBSE value proposition is not fully agreed within industry and adoption remains slow. To face these challenges, it seems important to introduce industrial engineering students to a complete view of SE including the benefits, the challenges and the technics of MBSE. In this paper, we discuss the question of competencies in Systems Engineering to address within the Industrial Engineering curriculum of Grenoble school of Industrial Engineering and Management. Since many dimensions are already addressed within the curriculum, modifications of some courses have been implemented to introduce SE and MBSE. A mapping with Graduate Reference Curriculum for Systems Engineering students' outcomes is presented and pedagogical choices using projects and case studies are discussed. Lessons learnt from experience with students learning outcomes are given.

Performance and efficiency in R&D processes is a critical point for industry. Operational excellence in design and development is required to overcome the business challenges that companies face. It is the case in semiconductor industry where products have to be developed rapidly whilst maintaining a high level of quality. Study of design practices in aerospace have illustrated that only about 10% of design activity is spent on creating value [1]. If this number appears alarming for a great number of managers, many engineers participating in design activity agree that practices could be improved to address issues in efficiency and performance. Lean product development is viewed as a global approach that offers a framework to address design performance [2]–[4]. This approach has been chosen by a large microelectronics company to transform the practice of its process and product engineer on the scale of its global footprint. This paper will present how a collaboration between academics and Industry initiated in the context of local ecosystem partnership led to the design of a training program. The approach inspired from design thinking principles was developed by an interdisciplinary team of lean experts from the company, Researchers in R&D efficiency, Specialists in Pedagogy, Specialists in serious game design from academia, Project management experts and Engineers from the company. Intense collaboration within an interdisciplinary team, rapid prototyping including engineers from the company, observers from university, quick learning loop and feedback, allowed to develop the training program. This collaboration favoured discussion in terms of expectations of company and setting up the foundation of the training program including constraints of deployment up to 2000+ targeted people worldwide. The program include 2 days of face to face using experiential learning [5] and one accompanying day later with implementation progress monitoring and return and sharing on experience as a whole. Two serious games were designed, a case study and problem-based learning session were developed to introduce the main concepts chosen as the heart of the program. The last afternoon was used to workshop on participants own problems. A community of practice with a collaborative platform and in vivo sharing sessions supports the transformation. The paper discusses the training design process, hypothesis and objectives. All stakeholders learnt from this design thinking approach, leading to innovative training co-creation and demonstrating the richness of interdisciplinary teamwork and relevance of a user-centered approach for lifelong learning training design References [1] J. Oehmen and E. Rebentisch, “Waste in Lean Product Development,” LAI Pap. Ser., no. July, pp. 1–35, 2010. [2] M. S. Khan et al., “Towards lean product and process development,” Int. J. Comput. Integr. Manuf., vol. 26, no. 12, pp. 1105–1116, Dec. 2013. [3] J. M. Morgan and J. K. Liker, The Toyota Product Developement System: Integrating People Process and Technology. New York: Productivity press, 2006. [4] D. G. Reinertsen, The principles of Product Development Flow. Second Generation Lean Product Development. Celeritas Publishing, 2009. [5] D. A. Kolb, Experiential Learning: Experience as the Source of Learning and Development, 2nd editio. pearson education, 2014.

The importance of early phase cost estimation is presented and argued.Most appropriate literature cost models to the issue are identified and reviewed.The suitability of literature cost models is assessed and discussed.Relevant cost drivers are identified.A cost estimation outline is proposed to support assembly cost prediction. The aim of this research is to support early phase cost estimation for assembly systems design and automation decision. During this phase, various alternatives of assembly systems with different automation levels can be generated. The alternatives generation is performed using available information on product design, assembly sequences, and planned production information. The issue is to assess given alternatives, identify, and opt for the most appropriate one. Several criteria have to be considered in this decision. The economic aspect represents one of the most preponderant, including cost and profitability prediction. The importance and challenges of this complex issue are highlighted in this paper with feedbacks from manufacturers and the literature. The literature in the field is reviewed, presented, and analyzed. For this sake, a selection of cost models is performed covering a wide chronological range, journals, and fields including assembly and manufacturing models. Classification techniques of cost estimation works are presented and exploited in the proposed review. It is used to filter and discuss models suitability for the defined assembly automation decision issue. The most appropriate models are more thoroughly reviewed and discussed. Useful literature costing techniques, features, and relevant cost drivers are also identified. They cover multiple aspects as production information, resources features or performances. Finally, the review findings are illustrated by a cost estimation outline proposal to support early phase cost prediction for assembly systems design and automation decision.

The increasing of complexity of industrial products makes Verification and Validation procedures challenging. Model-Based Systems Engineering (MBSE) has been proposed as an approach to manage such complexity through the formalized application of models throughout the systems development life cycle to support verification activities. The purpose of this paper is to make a first step towards developing a verification strategy by performing a qualitative survey on current industrial practices against the state of the art in MBSE. Data had been collected through workshops of 16 engineering organizations located in the Rhone-Alpes region of France. Key success criteria for integrating model-based verification with MBSE are identified by industry respondent. These criteria allow to analyse the top verification methods presented in MBSE publications and compare them to current practices. To further validate the use of these presented methods, interviews and observations were conducted to analyse the methods through different industrial perspectives and identify their feasibility for successful application. The findings of this study gives a picture of current practices in integrating verification and MBSE in industry. The paper discusses the impact of implementing such practices in companies beginning to adopt MBSE approaches. It is concluded by identifying opportunities and barriers for Model-Based Verification adoption.

International audience; An approach for assembly time estimating following sequence and process modelling since the conceptual phase of new assembly systems design is proposed in this work. The purpose is to support the decision about their levels of automation (LoA) following a dedicated modelling language labeled ASML offering a better visibility about processes design and analyses. ASML provides an easy way of defining several systems alternatives based on an initial ASML model representing assembly motions using a standard vocabulary and structured executing architectures. The correlation of early phase modelling with time estimating proposed in this paper to support LoA decision is up to us new to the literature. The approach of modelling and time estimating was tested on assembly examples and a computerized tool was also developed and tested. Several related applications such as processes time performances evaluating, time savings, productivity assessment, lines balancing, and cost estimating are proposed as well as other possible future applications presented as perspectives and future works that can be supported by the defined environment dedicated to early phase assembly systems design and automation decision.