On How Metadata Enables Enriched File-Based Production Workflows

<span lang="EN-US">Network Function Virtualization (NFV) architectures are emerging to increase networks flexibility. However, this renewed scenario poses new challenges, because virtualized networks, need to be carefully verified before being actually deployed in production environments in order to preserve network coherency (e.g., absence of forwarding loops, preservation of security on network traffic, etc.). Nowadays, model checking tools, SAT solvers, and Theorem Provers are available for formal verification of such properties in virtualized networks. Unfortunately, most of those verification tools accept input descriptions written in specification languages that are difficult to use for people not experienced in formal methods. Also, in order to enable the use of formal verification tools in real scenarios, vendors of Virtual Network Functions (VNFs) should provide abstract mathematical models of their functions, coded in the specific input languages of the verification tools. This process is error-prone, time-consuming, and often outside the VNF developers’ expertise. This paper presents a framework that we designed for automatically extracting verification models starting from a Java-based representation of a given VNF. It comprises a Java library of classes to define VNFs in a more developer-friendly way, and a tool to translate VNF definitions into formal verification models of different verification tools.</span>

The relevance of animal breeding research in developing countries (LDC) is a function of benefit/cost in both economic and social terms. Under the assumption that it is economically cheaper, at least in the short term, to “import” technologies developed in other countries (vs domestically), the benefit/cost is conditioned by the research results available and the degree to which such results are applicable for developing technologies in the importing country. Basic research results and research techniques can be transported without loss of relevance. However, beef cattle production is a complex system in which interpretation of basic results for application may be obscured, and the net effect of any intervention on the total stream of inputs and outputs of the system cannot be estimated intuitively with accuracy. Developments in systems science and the current availability of modern computers provide a method of organizing disciplinary research findings into a coherent whole, a simulation model, so that these results can realistically be related to application (i.e., the simulation model is a vehicle for transporting research results). Animal breeding research in LDC is relevant, and priority should be directed toward characterizing the local breeds and production environment in order to utilize (import) research from other countries effectively. The most relevant research for exporting countries, in terms of LDC needs, is in application of systems science and basic or fundamental research in areas such as explication of genetic mediation of anatomical and physiological functions of growth, lactation, reproduction and adaptation.

This is not a book that claims to describe the detail of prerequisite programs (PRPs) but we do need to look at the essential role of PRPs in the context of supporting HACCP for effective food safety management. It is important to understand that hazard analysis must consider how hazards are managed (by CCPs or PRPs) and that there is a need to understand both the product and the production environment in order to do this.

Network Function Virtualization (NFV) architectures are emerging to increase networks flexibility. However, this renewed scenario poses new challenges, because virtualized networks, need to be carefully verified before being actually deployed in production environments in order to preserve network coherency (e.g., absence of forwarding loops, preservation of security on network traffic, etc.). Nowadays, model checking tools, SAT solvers, and Theorem Provers are available for formal verification of such properties in virtualized networks. Unfortunately, most of those verification tools accept input descriptions written in specification languages that are difficult to use for people not experienced in formal methods. Also, in order to enable the use of formal verification tools in real scenarios, vendors of Virtual Network Functions (VNFs) should provide abstract mathematical models of their functions, coded in the specific input languages of the verification tools. This process is error-prone, time-consuming, and often outside the VNF developers' expertise. This paper presents a framework that we designed for automatically extracting verification models starting from a Java based representation of a given VNF. It comprises a Java library of classes to define VNFs in a more developer-friendly way, and a tool to translate VNF definitions into formal verification models of different verification tools.

Combining conscious and unconscious knowledge within human-machine-interfaces to foster sustainability with decision-making concerning production processes

A number of real time enablements of production engineering workflows shows various degrees of success and uptake upon implementation. It is possible to extract from the various types of challenges and difficulties a number of guidelines to ensure that the real-time production workflow implementations, deployments and utilizations have the largest chance of successes. A number of real time project have resulted in surprising initial drop of production figures rather than being immediate successes is part of the explanation of the 30% drop of the implementations within a first couple of years of commissioning. With a larger number of implementations now available worldwide, green field operations are designed from day one with smart/digital capabilities. There is little discussion of the actual value of such massive data gathering capabilities, and its initial cost sunk into the overall project capital expenditure. The case implementation of smart/digital acquisition system in brown fields is much more challenging. The tight operational budgets associated with such operations require clear business and value case. The difference between opportunistic value and guaranteed value is a key element of the decision process and must be clearly identified. The paper offers a number of recommendations based on examples to establish the difference between the various approaches. The issue of initial cost of implementation is a clear showstopper to many of these implementations. They must be managed well and it is quite important that the total cost of ownership be well defined and funded initially. New web based services such as the remote monitoring of ESP pumps or multiphase flowmeters allows for low initial investments to demonstrate the true value of real time production workflows. The ability of experts to "see" and "act" on data put in the correct context is becoming more and more essential as equipment and measurements are becoming more and more sophisticated. Finally there starts to be a consensus on a new and essential job description of a breed of technicians and engineers who are willing and capable to attend to unscheduled notifications of events from remote production equipment in due time. These "surveillance" engineers are the basis of the success of the deployments of real time production and interpretation workflows.

This systematic literature review delves into the critical role of metadata in enhancing the explainability and interoperability of AI-based prediction models. As AI technologies permeate various sectors, the need for transparent and coherent predictive models becomes increasingly vital. Metadata, which refers to structured information that contextualizes data, serves as a pivotal component in achieving this transparency and coherence. This review synthesizes 50 existing literature to evaluate how different types of metadata—such as descriptive, structural, and administrative metadata—contribute to the understanding and integration of AI models, thereby facilitating better decision-making and trust in AI systems. The review identifies key themes related to the challenges of explainability, including the complexity of AI algorithms and the opacity of model outputs, and discusses how robust metadata frameworks can mitigate these issues by providing essential context and clarity about model decisions. Furthermore, it examines the significance of interoperability in AI applications, highlighting how standardized metadata can enable seamless integration across diverse systems and platforms. The findings underscore the necessity of developing comprehensive metadata strategies to enhance both the interpretability of AI predictions and the compatibility of AI systems across different environments. Ultimately, the review calls for continued research into metadata standards and practices that can promote a more reliable and user-friendly AI landscape.

Multimedia production is a resource-intensive task. Numerous media assets have to be produced, processed and composed to form a final application. Once the application is finalized the knowledge gained throughout the production process-and sometimes even the original media assets-are lost. Re-use of media assets in a computer-supported way does seldom take place. The Esprit project SIT-MOON aims at improving the multimedia production process by integrating media asset management systems and production tools. For this purpose the project defined interface specifications which developers can adopt to integrate their specific tools. Moreover, SIT-MOON provides additional services such as logging of the production process, managing user and project setups, and format conversion of media objects.

Creating compelling multimedia presentations is a complex task. It involves the capture of media assets, then editing and authoring these into one or more final presentations. Tools tend to concentrate on a single aspect to reduce the complexity of the interface. While these tools are tailored to support a specific task, very often there is no consideration for input requirements for the next tool down the line. Each tool has the potential for adding semantic annotations to the media asset, describing relevant aspects of the asset and why it is being used for a particular purpose. These annotations need to be included in the information handed on to the next tool.We specify inputs and outputs to a number of canonical processes we identify in multimedia production. We do not specify the intricate workings of the processes, but concentrate on the information flow between them. Our claim is that by specifying the inputs and outputs required for processes that occur in widely differing uses of media we can identify a small set of building blocks that can be supported in semantically aware media production tools.

Human capabilities to interact, interfere, support, supervise and take over different tasks in a production environment are often not considered in the context of automated and self-organizing factories (smart factories). Adaptive Task Sharing (ATS) is a method to combine the strengths of automation and human skills to provide flexible and resilient factories. ATS offers huge potential for improving and enhancing ergonomics and human factors in production. The assembly worker plays a vital role in such hybrid manufacturing as a partner and coordinator of production services. In recent years, techniques have been developed to efficiently compute production execution graphs optimized for various technical criteria, like minimum makespan or energy consumption. This paper shows how to use these techniques for a flexible production planning that incorporates human workers and investigates different scenarios of task allocation between humans and machines and their impact on production workflows. Such socio-technical interactions between humans and machines need to be at the core of resilient production systems to deal with unforeseen circumstances, provide the flexibility required in high-variability, low-volume production scenarios, and increase productivity and workplace quality of human workers.

Application domains such as bioinformatics and web technology represent complex objects as graphs where nodes represent basic objects (i.e. atoms, web pages etc.) and edges model relations among them. In biochemical databases proteins are naturally represented as labeled graphs: the nodes are atoms and the edges are chemical links. In computer vision, graphs can be used to represent images at different levels of abstraction. In a low-level representation (Pailloncy, Deruyver, & Jolion, 1999), the nodes of a graph correspond to pixels and the edges to spatial relations between pixels. At higher levels of description (Hong & Huang, 2001), nodes are image regions and edges are spatial relations among them. In a Web graph (Deutsch, Fernandez, Florescu, Levy, & Suciu, 1999) nodes are web pages and edges are links between them. In all these domains, substructure queries that search for all exact or approximate occurrences of a given query graph in the graphs of the database can be useful. Research efforts in graph searching have taken three directions: the first is to study matching algorithms for particular graph structures (planar graphs, bounded valence graphs and association graphs); the second is to use elaborate tricks to reduce the number of generated matching maps (Cordella, Foggia, Sansone, & Vento, 2004); and the third is, since graph searching problem is NP-complete, to provide polynomial approximate algorithms. In the context of querying in a database of graphs many of the existing methods are designed for specific applications. For example, several querying methods for semi-structured databases have been proposed. In addition, commercial products and academic projects (Kelley 2002) for subgraph searching in biochemical databases are available. These two examples have a different underlying data model (a web-page database is a large graph whereas a biochemical database is a collection of graphs). In these two applications regular path expressions and indexing methods are used during query time to respectively locate substructures in the database and to avoid unnecessary traversals of the database. In general graph databases, there are some searching methods where the data graph and the query graph must have the same size. Other methods allow the query to be considerably smaller than the database graphs. A common idea in the above algorithms is to index the subgraph matches in the database and organize them in suitable data structures.

The requirements for automatic content recognition are often drawn from security applications or from applications related to video or image libraries. As practices and cultures in audio visual media productions develop, the opportunities for using content-recognition systems change, but there is little published on what the specific needs of this industry are perceived to be. This paper describes a systematic approach taken to determine the perceived needs of the media industry based on a deep understanding of both the production workflow and the capabilities of content recognition systems. The results include a ranked list of the perceived usefulness of different capabilities and a better qualitative understanding of where, in the production workflow, such capabilities offer potential value.

Current financial education faces prominent challenges such as insufficient industry-education collaboration and lagging practical teaching, which constrain the cultivation of applied financial talents. This study innovatively proposes a “One Linkage, Two Integrations, and Three Synergies” construction paradigm: One Linkage: Precise alignment between teaching scenarios and professional scenarios to achieve seamless school-enterprise resource integration; Two Integrations: Dual integration of curriculum content with occupational standards, and teaching processes with production workflows, to restructure the practical teaching system; Three Synergies: A synergistic mechanism involving government, schools, and enterprises to consolidate multidimensional resources. This model aims to resolve the structural mismatch between talent supply and industry demands, providing theoretical innovation and practical guidance for the development of financial laboratories.

This article evaluates Bourdieu’s analysis of cultural production in terms of its effectiveness for understanding contemporary media production. I begin by outlining the main features of Bourdieu’s work on cultural production, with an emphasis on the potential advantages of his historical account over other, competing work. In particular, I stress the importance of his historical account of ‘autonomy’ and of the emphasis on the interconnectedness of the field of cultural production with other social fields. I then draw attention to two major problems in the work of Bourdieu and others who have adopted his ‘field theory’ for the media: first, that he offered only occasional and fragmented analyses of ‘large-scale’, ‘heteronomous’ (to use his terms) commercial media production, in spite of its enormous social and cultural importance in the contemporary world; second, that Bourdieu and his key associates provide only a very limited account of the relationships between cultural production and cultural consumption. In this latter context, I briefly discuss recent debates in cultural studies about cultural intermediaries. I refer to examples from recent media production to provide evidence for my arguments. The article argues that, as practised so far, Bourdieu’s field theory is only of limited value in analysing media production. However I close by discussing the potential fruitfulness of research based on a dialogue between, on the one hand, field theory’s analysis of cultural production and, on the other, Anglo-American media and cultural studies work on media production.

The push towards faster, denser VLSI device structures and eventually to ULSI devices means ever-decreasing design rules for IC manufacturers. In order to define patterns on silicon and gallium arsenide substrates with feature sizes of 0.25 microns, lithography, metallization, and electronic materials processing techniques will be pushed beyond current limitations. Of these technologies, lithography in the sub-0.5 micron region appears to be the main obstacle yet to be overcome. As deep-UV optical systems become more expensive and the useful field sized decrease in the attempt to achieve finer resolutions, the question of whether to switch to an alternate lithographic method becomes imminent. X-ray lithography is the leading candidate. In this paper, the question of whether x-ray lithography is economically superior to optical lithography and the cost-effectiveness of x-ray lithography are addressed. Also, the question of how x-ray lithography can be performed in a production environment is considered. First shown is that more elaborate optical systems are simply not going to match x-ray proximity system in terms of resolution because of the need to use exotic lens materials or complicated and ever finer reflection systems, none of which can correct for diffraction effects, yet must be corrected for every other aberration. The economic superiority of a synchrotron-based x- ray lithography beamline is demonstrated in a production facility using a processing-cost model based on Shinji Okazaki's cost-per-bit model. Considered, as well, is the strong possibility that exists for the use of an optically based production line which would use an anode or plasma x-ray stepper to define only the smallest geometries, such as the gate level on a DRAM chip. It is shown that it is unlikely, even pushing the limits of materials and optics, that deep-UV systems will be able to define patterns below 0.35 microns in a production environment. X-ray lithography systems could define 0.20 micron patterns in a production environment with a yield that promised to be better than that of optical systems.