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Scrum2kanban
(2018)
Using university capstone courses to teach agile software development methodologies has become commonplace, as agile methods have gained support in professional software development. This usually means students are introduced to and work with the currently most popular agile methodology: Scrum. However, as the agile methods employed in the industry change and are adapted to different contexts, university courses must follow suit. A prime example of this is the Kanban method, which has recently gathered attention in the industry. In this paper, we describe a capstone course design, which adds the hands-on learning of the lean principles advocated by Kanban into a capstone project run with Scrum. This both ensures that students are aware of recent process frameworks and ideas as well as gain a more thorough overview of how agile methods can be employed in practice. We describe the details of the course and analyze the participating students' perceptions as well as our observations. We analyze the development artifacts, created by students during the course in respect to the two different development methodologies. We further present a summary of the lessons learned as well as recommendations for future similar courses. The survey conducted at the end of the course revealed an overwhelmingly positive attitude of students towards the integration of Kanban into the course.
802.15.4 security protects against the replay, injection, and eavesdropping of 802.15.4 frames. A core concept of 802.15.4 security is the use of frame counters for both nonce generation and anti-replay protection. While being functional, frame counters (i) cause an increased energy consumption as they incur a per-frame overhead of 4 bytes and (ii) only provide sequential freshness. The Last Bits (LB) optimization does reduce the per-frame overhead of frame counters, yet at the cost of an increased RAM consumption and occasional energy-and time-consuming resynchronization actions. Alternatively, the timeslotted channel hopping (TSCH) media access control (MAC) protocol of 802.15.4 avoids the drawbacks of frame counters by replacing them with timeslot indices, but findings of Yang et al. question the security of TSCH in general. In this paper, we assume the use of ContikiMAC, which is a popular asynchronous MAC protocol for 802.15.4 networks. Under this assumption, we propose an Intra-Layer Optimization for 802.15.4 Security (ILOS), which intertwines 802.15.4 security and ContikiMAC. In effect, ILOS reduces the security-related per-frame overhead even more than the LB optimization, as well as achieves strong freshness. Furthermore, unlike the LB optimization, ILOS neither incurs an increased RAM consumption nor requires resynchronization actions. Beyond that, ILOS integrates with and advances other security supplements to ContikiMAC. We implemented ILOS using OpenMotes and the Contiki operating system.
The present work is part of a collaborative H2020 European funded research project called SENSKIN, that aims to improve Structural Health Monitoring (SHM) for transport infrastructure through the development of an innovative monitoring and management system for bridges based on a novel, inexpensive, skin-like sensor. The integrated SENSKIN technology will be implemented in the case of steel and concrete bridges, and tested, field-evaluated and benchmarked on actual bridge environment against a conventional health monitoring solution developed by Mistras Group Hellas. The main objective of the present work is to implement the autonomous, fully functional strain monitoring system based on commercially available off-the-shelf components, that will be used to accomplish direct comparison between the performance of the innovative SENSKIN sensors and the conventional strain sensors commonly used for structural monitoring of bridges. For this purpose, the mini Structural Monitoring System (mini SMS) of Physical Acoustics Corporation, a comprehensive data acquisition unit designed specifically for long-term unattended operation in outdoor environments, was selected. For the completion of the conventional system, appropriate foil-type strain sensors were selected, driven by special conditioners manufactured by Mistras Group. A comprehensive description of the strain monitoring system and its peripheral components is provided in this paper. For the evaluation of the integrated system’s performance and the effect of various parameters on the long-term behavior of sensors, several test steel pieces instrumented with different strain sensors configurations were prepared and tested in both laboratory and field ambient conditions. Furthermore, loading tests were performed aiming to validate the response of the system in monitoring the strains developed in steel beam elements subject to bending regimes. Representative results obtained from the above experimental tests have been included in this paper as well.
CurEx
(2018)
The integration of diverse structured and unstructured information sources into a unified, domain-specific knowledge base is an important task in many areas. A well-maintained knowledge base enables data analysis in complex scenarios, such as risk analysis in the financial sector or investigating large data leaks, such as the Paradise or Panama papers. Both the creation of such knowledge bases, as well as their continuous maintenance and curation involves many complex tasks and considerable manual effort. With CurEx, we present a modular system that allows structured and unstructured data sources to be integrated into a domain-specific knowledge base. In particular, we (i) enable the incremental improvement of each individual integration component; (ii) enable the selective generation of multiple knowledge graphs from the information contained in the knowledge base; and (iii) provide two distinct user interfaces tailored to the needs of data engineers and end-users respectively. The former has curation capabilities and controls the integration process, whereas the latter focuses on the exploration of the generated knowledge graph.
Beacon in the Dark
(2018)
The large amount of heterogeneous data in these email corpora renders experts' investigations by hand infeasible. Auditors or journalists, e.g., who are looking for irregular or inappropriate content or suspicious patterns, are in desperate need for computer-aided exploration tools to support their investigations.
We present our Beacon system for the exploration of such corpora at different levels of detail. A distributed processing pipeline combines text mining methods and social network analysis to augment the already semi-structured nature of emails. The user interface ties into the resulting cleaned and enriched dataset. For the interface design we identify three objectives expert users have: gain an initial overview of the data to identify leads to investigate, understand the context of the information at hand, and have meaningful filters to iteratively focus onto a subset of emails. To this end we make use of interactive visualisations based on rearranged and aggregated extracted information to reveal salient patterns.
The detection of all inclusion dependencies (INDs) in an unknown dataset is at the core of any data profiling effort. Apart from the discovery of foreign key relationships, INDs can help perform data integration, integrity checking, schema (re-)design, and query optimization. With the advent of Big Data, the demand increases for efficient INDs discovery algorithms that can scale with the input data size. To this end, we propose S-INDD++ as a scalable system for detecting unary INDs in large datasets. S-INDD++ applies a new stepwise partitioning technique that helps discard a large number of attributes in early phases of the detection by processing the first partitions of smaller sizes. S-INDD++ also extends the concept of the attribute clustering to decide which attributes to be discarded based on the clustering result of each partition. Moreover, in contrast to the state-of-the-art, S-INDD++ does not require the partition to fit into the main memory-which is a highly appreciable property in the face of the ever growing datasets. We conducted an exhaustive evaluation of S-INDD++ by applying it to large datasets with thousands attributes and more than 266 million tuples. The results show the high superiority of S-INDD++ over the state-of-the-art. S-INDD++ reduced up to 50 % of the runtime in comparison with BINDER, and up to 98 % in comparison with S-INDD.
One particular challenge in the Internet of Things is the management of many heterogeneous things. The things are typically constrained devices with limited memory, power, network and processing capacity. Configuring every device manually is a tedious task. We propose an interoperable way to configure an IoT network automatically using existing standards. The proposed NETCONF-MQTT bridge intermediates between the constrained devices (speaking MQTT) and the network management standard NETCONF. The NETCONF-MQTT bridge generates dynamically YANG data models from the semantic description of the device capabilities based on the oneM2M ontology. We evaluate the approach for two use cases, i.e. describing an actuator and a sensor scenario.
Live migration is an important feature in modern software-defined datacenters and cloud computing environments. Dynamic resource management, load balance, power saving and fault tolerance are all dependent on the live migration feature. Despite the importance of live migration, the cost of live migration cannot be ignored and may result in service availability degradation. Live migration cost includes the migration time, downtime, CPU overhead, network and power consumption. There are many research articles that discuss the problem of live migration cost with different scopes like analyzing the cost and relate it to the parameters that control it, proposing new migration algorithms that minimize the cost and also predicting the migration cost. For the best of our knowledge, most of the papers that discuss the migration cost problem focus on open source hypervisors. For the research articles focus on VMware environments, none of the published articles proposed migration time, network overhead and power consumption modeling for single and multiple VMs live migration. In this paper, we propose empirical models for the live migration time, network overhead and power consumption for single and multiple VMs migration. The proposed models are obtained using a VMware based testbed.
The electromagnetic coupling of molecular excitations to plasmonic nanoparticles offers a promising method to manipulate the light-matter interaction at the nanoscale. Plasmonic nanoparticles foster exceptionally high coupling strengths, due to their capacity to strongly concentrate the light-field to sub-wavelength mode volumes. A particularly interesting coupling regime occurs, if the coupling increases to a level such that the coupling strength surpasses all damping rates in the system. In this so-called strong-coupling regime hybrid light-matter states emerge, which can no more be divided into separate light and matter components. These hybrids unite the features of the original components and possess new resonances whose positions are separated by the Rabi splitting energy h Omega. Detuning the resonance of one of the components leads to an anticrossing of the two arising branches of the new resonances omega(+) and omega(-) with a minimal separation of Omega = omega(+) - omega(-).
The coupling between molecular excitations and nanoparticles leads to promising applications. It is for example used to enhance the optical cross-section of molecules in surface enhanced Raman scattering, Purcell enhancement or plasmon enhanced dye lasers. In a coupled system new resonances emerge resulting from the original plasmon (ωpl) and exciton (ωex) resonances as
ω±=12(ωpl+ωex)±14(ωpl−ωex)2+g2−−−−−−−−−−−−−−−√,
(1)
where g is the coupling parameter. Hence, the new resonances show a separation of Δ = ω+ − ω− from which the coupling strength can be deduced from the minimum distance between the two resonances, Ω = Δ(ω+ = ω−).