Multitrip vehicle routing with delivery options: a data-driven application to the parcel industry

To make the last mile of parcel delivery more efficient, service providers offer an increasing number of modes of delivery as alternatives to the traditional and often cost-intensive home delivery service. Parcel lockers and pickup stations can be utilized to reduce the number of stops and avoid costly detours. To design smart delivery networks, service providers must evaluate different business models. In this context, a multitrip vehicle routing problem with delivery options and location-dependent costs arises. We present a data-driven framework to evaluate alternative delivery strategies, formulate a corresponding model and solve the problem heuristically using adaptive large neighborhood search. By examining large, real-life instances from a major European parcel service, we determine the potential and benefits of different delivery options. Specifically, we show that delivery costs can be mitigated by consolidating orders in pickup stations and illustrate how pricing can be applied to steer customer demand toward profitable, eco-friendly products

Using Semantic Web Services for AI-Based Research in Industry 4.0

The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI) methods find their way into manufacturing shop floors. For using AI methods in the context of Industry 4.0, semantic web services are indispensable to provide a reasonable abstraction of the underlying manufacturing capabilities. In this paper, we present semantic web services for AI-based research in Industry 4.0. Therefore, we developed more than 300 semantic web services for a physical simulation factory based on Web Ontology Language for Web Services (OWL-S) and Web Service Modeling Ontology (WSMO) and linked them to an already existing domain ontology for intelligent manufacturing control. Suitable for the requirements of CPS environments, our pre- and postconditions are verified in near real-time by invoking other semantic web services in contrast to complex reasoning within the knowledge base. Finally, we evaluate our implementation by executing a cyber-physical workflow composed of semantic web services using a workflow management system.Comment: Submitted to ISWC 202

Ethics and Morality in AI - A Systematic Literature Review and Future Research

Artificial intelligence (AI) has become an integral part of our daily lives in recent years. At the same time, the topic of ethics and morality in the context of AI has been discussed in both practical and scientific discourse. Either it deals with ethical concerns, concrete application areas, the programming of AI or its moral status. However, no article can be found that provides an overview of the combination of ethics, morality and AI and systematizes them. Thus, this paper provides a systematic literature review on ethics and morality in the context of AI examining the scientific literature between the years 2017 and 2021. The search resulted in 1,641 articles across five databases of which 224 articles were included in the evaluation. Literature was systematized into seven topics presented in this paper. Implications of this review can be valuable not only for academia, but also for practitioners

Transferring Trust, Risk and Security on Users’ Intention to Trade Cryptocurrency, Using PayPal as an Example

As one of the largest digital payment providers, PayPal has integrated the possibility to use cryptocurrency as a payment method and to buy cryptocurrency via the platform. Building on the considerations of trust-transfer theory and extending this model adding the trust-related attributes perceived risk and security, this paper therefore examines to what extent these attributes can be transferred from the payment service provider PayPal to cryptocurrency. In a second step, based on this transfer of attributes, the intention to use cryptocurrencies via PayPal will be examined, as well as the general intention to use cryptocurrencies. By conducting an online survey (N=398), a significant effect of the transfer of the examined attributes from PayPal to cryptocurrency if handled by PayPal was found. Furthermore, in the second step of the data analysis, significant effects for the attributes of cryptocurrency if handled by PayPal on the intention to use were found

Leightweight Urban Computation Interchange (LUCI) System

In this paper we introduce LUCI, a Leightweight Urban Calculation Interchange system, designed to bring the advantages of calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware.The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views.The described system architecture is accompanied by two exemplary use cases, that have been used to test and further develop our concepts and implementations

A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification

Reliable application of machine learning-based decision systems in the wild is one of the major challenges currently investigated by the field. A large portion of established approaches aims to detect erroneous predictions by means of assigning confidence scores. This confidence may be obtained by either quantifying the model's predictive uncertainty, learning explicit scoring functions, or assessing whether the input is in line with the training distribution. Curiously, while these approaches all state to address the same eventual goal of detecting failures of a classifier upon real-life application, they currently constitute largely separated research fields with individual evaluation protocols, which either exclude a substantial part of relevant methods or ignore large parts of relevant failure sources. In this work, we systematically reveal current pitfalls caused by these inconsistencies and derive requirements for a holistic and realistic evaluation of failure detection. To demonstrate the relevance of this unified perspective, we present a large-scale empirical study for the first time enabling benchmarking confidence scoring functions w.r.t all relevant methods and failure sources. The revelation of a simple softmax response baseline as the overall best performing method underlines the drastic shortcomings of current evaluation in the abundance of publicized research on confidence scoring. Code and trained models are at https://github.com/IML-DKFZ/fd-shifts

Lightweight urban computation interchange (LUCI) system

In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of a calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases that have been used to test and further develop our concepts and implementations