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To learn from the past, we analyse 1,088 "computer as a target" judgements for evidential reasoning by extracting four case elements: decision, intent, fact, and evidence. Analysing the decision element is essential for studying the scale of sentence severity for cross-jurisdictional comparisons. Examining the intent element can facilitate future risk assessment. Analysing the fact element can enhance an organization's capability of analysing criminal activities for future offender profiling. Examining the evidence used against a defendant from previous judgements can facilitate the preparation of evidence for upcoming legal disclosure. Follow the concepts of argumentation diagrams, we develop an automatic judgement summarizing system to enhance the accessibility of judgements and avoid repeating past mistakes. Inspired by the feasibility of extracting legal knowledge for argument construction and employing grounds of inadmissibility for probability assessment, we conduct evidential reasoning of kernel traces for forensic readiness. We integrate the narrative methods from attack graphs/languages for preventing confirmation bias, the argumentative methods from argumentation diagrams for constructing legal arguments, and the probabilistic methods from Bayesian networks for comparing hypotheses.
In this paper we provide a performance analysis framework for wireless industrial networks by deriving a service curve and a bound on the delay violation probability. For this purpose we use the (min,×)stochastic network calculus as well as a recently presented recursive formula for an end-to-end delay bound of wireless heterogeneous networks. The derived results are mapped to WirelessHART networks used in process automation and were validated via simulations. In addition to WirelessHART, our results can be applied to any wireless network whose physical layer conforms the IEEE 802.15.4 standard, while its MAC protocol incorporates TDMA and channel hopping, like e.g. ISA100.11a or TSCH-based networks. The provided delay analysis is especially useful during the network design phase, offering further research potential towards optimal routing and power management in QoS-constrained wireless industrial networks.
These days computer analysis of ECG (Electrocardiograms) signals is common. There are many real-time QRS recognition algorithms; one of these algorithms is Pan-Tompkins Algorithm. Which the Pan-Tompkins Algorithm can detect QRS complexes of ECG signals. The proposed algorithm is analysed the data stream of the heartbeat based on the digital analysis of the amplitude, the bandwidth, and the slope. In addition to that, the stress algorithm compares whether the current heartbeat is similar or different to the last heartbeat after detecting the ECG signals. This algorithm determines the stress detection for the patient on the real-time. In order to implement the new algorithm with higher performance, the parallel programming language CUDA is used. The algorithm determines stress at the same time by determining the RR interval. The algorithm uses a different function as beat detector and a beat classifier of stress.
Die Seewassernutzung weist ein beachtliches Potential zu Kühl- und Heizzwecken auf. Bereits seit längerem eingesetzte seewasserbetriebene Wärmepumpen in der Schweiz beweisen fortwährend ihre Praxistauglichkeit. In Deutschland wird diese Technik jedoch bislang kaum genutzt. Mit Hilfe eines interdisziplinären geowissenschaftlichen Ansatzes wird derzeit das bestehende Potential in Deutschland quantifiziert und dessen Nutzungshemmnisse identifiziert, um in einem weiteren Schritt Handlungsoptionen für einen verstärkten Einsatz dieser Technologie zu erarbeiten.
Realistic traffic modeling plays a key role in efficient Dynamic Spectrum Access (DSA) which is considered as enabler for the employment of wireless technologies in critical industrial automation applications (IAA). The majority of models of spectrum usage are not suitable for this specific use case as they are based on measurement campaigns conducted in urban or controlled laboratory environments. In this work we present a time-domain traffic model for industrial communication in the 2.4 GHz industrial, scientific, medical (ISM) band based on measurements in an industrial automotive production site. As DSA is usually implemented on Software Defined Radios (SDR), our measurement campaign is based on SDR platforms rather than sophisticated spectrum analyzers. We show through the estimation of the Hurst parameter that industrial wireless traffic possesses inherent self-similarity that could be exploited for efficient DSA. We also show that wireless traffic could be modeled as a semi-Markov model with channel on and off durations Log-normally and Pareto distributed, respectively. We finally estimate the parameters of the derived models using Maximum Likelihood estimation.
ERP systems integrate a major part of all business processes and organizations include them in their IT service management. Besides these formal systems, there are additional systems that are rather stand-alone and not included in the IT management tasks. These so-called ‘shadow systems’ also support business processes but hinder a high enterprise integration. Shadow systems appear during their explicit detection or during software maintenance projects such as enhancements or release changes of enterprise systems. Organizations then have to decide if and to what extent they integrate the identified shadow systems into their ERP systems. For this decision, organizations have to compare the capabilities of each identified shadow system with their ERP systems. Based on multiple-case studies, we provide a dependency approach to enable their comparison. We derive categories for different stages of the dependency and base insights into integration possibilities on these stages. Our results show that 64% of the shadow systems in our case studies are related to ERP systems. This means that they share parts or all of their data and/or functionality with the ERP system. Our research contributes to the field of integration as well as to the discussion about shadow systems.
adidas and Reebok
(2016)
Die ISO 26000 schafft einen international anerkannten Referenzrahmen für die Wahrnehmung gesellschaftlicher Verantwortung durch Organisationen aller Art (Unternehmen, staatliche Institutionen, Vereinigungen). Das EFQM-Modell ist ein geeigneter Referenzrahmen, um eine Organisation so zu gestalten, dass die Unternehmensziele nachhaltig erreicht werden unter Einhaltung der gesetzlichen Vorgaben und der Erfüllung legitimer Anforderungen relevanter Stakeholder.