We use an application scenario that collects, transports and stores sensor data in a database. The data is gathered with a high frequency of 1000 datasets per second. In the context of this scenario, we analyze the performance of multiple popular database systems. The benchmark results include the load on the system writing the data and the system running the database.

In our previous work, we proposed a system which makes complex production machines more user-friendly by giving the recommendations to the operator. So, we assist the user working with a complex production machine. The recommen- dations are presented like: ”In the last 10 occurrences of this event the operators performed the following keystrokes”. While working on the project, we had problems with retrieving the correct recommendations from our knowledge base. Meanwhile, we gathered more data from our project partners. Now, we dive deeper into this data in order to improve our solutions. This work describes methods to preprocess the data. This preprocessing should help us building up the knowledge base. To achieve this automatically, we do not want to know much about the machine and the production process itself.

Complementing previous research, this paper addresses the challenge of exploring the drivers of customer dissatisfaction in buyer-manufacturer relationships in a B2B and a business-to-government (B2G) context, to enhance existing models of the outcomes of dissatisfaction. Based on qualitative data in a dyadic research setting, this paper collects and analyzes data from both the buying and manufacturing side in Germany, referring to internationally sold standard and customized product solutions. Customers are not limited to business clients, they include public institutions and partners. Embedding empirical observations and data in established theoretical frames, this paper enhances existing dissatisfaction research by adding its antecedents and suggests a new unified customer satisfaction and dissatisfaction model. Empirical results provide substantial implications for both B2B and B2G marketing management. Additionally, the implications for future academic research are outlined.

Critical Infrastructures (CIs) use Supervisory Control And Data Acquisition (SCADA) systems for remote control and monitoring. Sophisticated security measures are needed to address malicious intrusions, which are steadily increasing in number and variety due to the massive spread of connectivity and standardisation of open SCADA protocols. Traditional Intrusion Detection Systems (IDSs) cannot detect attacks that are not already present in their databases. Therefore, in this paper, we assess Machine Learning (ML) for intrusion detection in SCADA systems using a real data set collected from a gas pipeline system and provided by the Mississippi State University (MSU). The contribution of this paper is two-fold: 1) The evaluation of four techniques for missing data estimation and two techniques for data normalization, 2) The performances of Support Vector Machine (SVM), and Random Forest (RF) are assessed in terms of accuracy, precision, recall and F 1 score for intrusion detection. Two cases are differentiated: binary and categorical classifications. Our experiments reveal that RF detect intrusions effectively, with an F 1 score of respectively > 99%.

Laser cladding on 200 μm thin substrates is a challenge due to poor heat dissipation. Successful coatings were produced using Yb fiber laser with closed-loop controlled laser power. Samples were investigated by SEM and EDS.

Welcome to the Human Factors in Hypertext 2018 workshop (HUMAN'18) in Baltimore, Maryland, USA, the first workshop of a new series of workshops for the ACM Conference on Hypertext and Social Media. It has a strong focus on hypertext users and thus complements the machine analytics research that we experienced in previous conferences. The user-centric view on hypertext not only includes user interfaces and interaction, but also discussions about hypertext application domains. Furthermore, the workshop raises the question of how original hypertext ideas (e.g., Doug Engelbart's "augmenting human intellect" or Frank Halasz' "hypertext as a medium for thinking and communication") can improve today's hypertext systems. Historically, hypertext research is strongly connected to human factors. Hypertext pioneers, such as Doug Engelbart or Ted Nelson, focused on the usage of and interaction with hypertext. This workshop combines original hypertext research ideas with recent hypertext research trends. In addition, it consolidates different hypertext research areas from the viewpoint of human factors. Thus, HUMAN'18 fosters cross-cutting discussions and the development of new ideas.

The idea to associate information with so-called links was developed by hypertext pioneers in the 1960s. In the 1990s the Dexter Hypertext Reference Model was developed with the goal to provide a general model for node-link hypertext systems. In the 1990s and 2000s there were important steps made for hypertext infrastructures, which led to component-based open hypermedia systems (CB-OHS). In this paper we provide a detailed description of node-link structures. We argue that Dexter does not match the need of CB-OHS, as it supports a mix of multiple structure domains. Based on the implementation of link support in our system Mother we demonstrate how Dexter needs to be tailored accordingly. We further describe Mother's ability of node-link structures to interoperate with other available structure services and vice versa.

Wie die Blockchain-Technologie die Politik beeinflussen könnte und heute bereits tatsächlich beeinflusst.

Software applications become more and more dominant in our daily life and work. However, it is very difficult to provide sophisticated tools for all arising use cases. End-User Development (EUD) is a term that describes the development of applications by end users rather than professional developers. This enables them creating highly specialized solutions. End users are laypersons when it comes to building software, therefore they need appropriate tools for managing the whole development process. This includes designing, implementing and deploying applications. While there are already various tools available, we focus on a recommendation feature for graphical EUD tools, utilizing their spatial hypertext capabilities. In this paper we provide an overview of some common issues such tools are often struggling with. We explain how visually analyzing the workspace, parsing an implicit spatial hypertext and eventually presenting recommendations may tackle them. We further describe the project HEIMDALL in detail, especially the way of generating recommendations for software modules with the aim to raise users' awareness. Furthermore, we discuss the use of such a system that reaches a similar understanding of relationships between software modules as users have. Finally, we point to open issues that still need to be addressed to improve results and their presentation.

As of IEEE 802.11n, a wireless Network Interface Card (NIC) uses Channel State Information (CSI) to optimize the transmission over multiple antennas. CSI contain radio-metrics such as amplitude and phase. Due to scattering during hardware production these metrics exhibit unique properties. Since these information are transmitted unencrypted, they can be captured by a passive observer. We show that these information can be used to create a unique fingerprint of a wireless device, based on as little as 100 CSI packets per device collected with an off-the-shelf Wi-Fi card. For our proof of concept we captured data from seven smartphones including two identical models. We were able to identify more than 90% when using out-of-the-box Random Forrest (RF).

Blockchain ist derzeit ein Hype. Bekanntlich folgt nach dem Gipfel der überzogenen Erwartungen der Absturz in das Tal der Enttäuschungen. Das liegt unter anderem daran, dass bisher nur wenige der sinnvollen Anwendungsfälle auch tatsächlich praktisch umgesetzt werden konnten und viele existierende Szenarien auch mit herkömmlichen Technologien ohne Blockchain funktionieren würden. Und dennoch kann Blockchain sinnvoll eingesetzt werden, beispielsweise auf dem Katasteramt oder in einer elektronischen Patientenakte.

Various empirical studies are concerned with the success factors of the digital transformation process. However, a critical review of the literature shows that empirical studies in BtB sales management predominantly focus on company sizes as well as industries, but mostly neglect the relevance of business types. In the following paper, the results of an empirical study will be presented, which will fill the existing research gap. It will be demonstrated that the business type is having a major influence on the design of the various sales process steps as well as on the digitalization potential of the respective processes.