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During the execution of large scale construction projects performed by Virtual Organizations (VO), relatively complex technical models have to be exchanged between the VO members. For linking the trade and transfer of these models, a…
Collaborative virtual environments (CVEs) are used for collaboration and interaction of possibly many participants that may be spread over large distances. Both commercial and freely available CVEs exist today. Currently, CVEs are used…
In this paper, we propose a novel approach (SAPEO) to support the survival selection process in multi-objective evolutionary algorithms with surrogate models - it dynamically chooses individuals to evaluate exactly based on the model…
We propose that designing a manufacturer's equipment-based service value proposition in outcome-based contracts is the design of a new business model capable of managing threats to the firm's viability that can arise from the contextual…
Sparse mixture of experts (SMoE) offers an appealing solution to scale up the model complexity beyond the mean of increasing the network's depth or width. However, we argue that effective SMoE training remains challenging because of the…
Mixture-of-Experts (MoE) models embody the divide-and-conquer concept and are a promising approach for increasing model capacity, demonstrating excellent scalability across multiple domains. In this paper, we integrate the MoE structure…
Choices in scientific research and management require balancing multiple, often competing objectives.Multiple-objective optimization (MOO) provides a unifying framework for solving multiple objective problems. Model selection is a critical…
Lack of resources is a challenge for small and medium enterprises (SMEs) in implementing an IT-based system to facilitate more efficient business decisions and expanding the market. A community system based on service-oriented architecture…
To meet the growing demand for smarter, faster, and more efficient embodied AI solutions, we introduce a novel Mixture-of-Expert (MoE) method that significantly boosts reasoning and learning efficiency for embodied autonomous systems.…
Service Oriented Architecture is a loosely coupled architecture designed to tackle the problem of Business Infrastructure alignment to meet the needs of an organization. A SOA based platform enables the enterprises to develop applications…
The first-stage retrieval aims to retrieve a subset of candidate documents from a huge collection both effectively and efficiently. Since various matching patterns can exist between queries and relevant documents, previous work tries to…
People can help other people find information in networked information seeking environments. Recently, many such systems and algorithms have proliferated in industry and in academia. Unfortunately, it is difficult to compare the systems in…
Currently, organizations are transforming their business processes into e-services and service-oriented architectures to improve coordination across sales, marketing, and partner channels, to build flexible and scalable systems, and to…
There is a pressing need for better development methods and tools to keep up with the growing demand and increasing complexity of new software systems. New types of user interfaces, the need for intelligent components, sustainability…
Service virtualization is an approach that uses virtualized environments to automatically test enterprise services in production-like conditions. Many techniques have been proposed to provide such a realistic environment for enterprise…
Network virtualization is an important concept to overcome the ossification of today's Internet as it facilitates innovation also in the network core and as it promises a more efficient use of the given resources and infrastructure. Virtual…
Digital ethics is being discussed worldwide as a necessity to create more reliable IT systems. This discussion, fueled by the fear of uncontrollable artificial intelligence (AI) has moved many institutions and scientists to demand a…
Developing multi-turn interactive tool-use agents is challenging because real-world user needs are often complex and ambiguous, yet agents must execute deterministic actions to satisfy them. To address this gap, we introduce \textbf{CoVe}…
Software process models need to be variant-rich, in the sense that they should be systematically customizable to specific project goals and project environments. It is currently very difficult to model Variant-Rich Process (VRP) because…
Algorithm selection and hyperparameter tuning remain two of the most challenging tasks in machine learning. Automated machine learning (AutoML) seeks to automate these tasks to enable widespread use of machine learning by non-experts. This…