Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

A variational method based on weighted graph states

In a recent article [Phys. Rev. Lett. 97 (2006), 107206], we have presented a class of states which is suitable as a variational set to find ground states in spin systems of arbitrary spatial dimension and with long-range entanglement. Here, we continue the exposition of our technique, extend from spin 1/2 to higher spins and use the boson Hubbard model as a non-trivial example to demonstrate our scheme.Comment: 36 pages, 13 figure

Design and performance evaluation of a lightweight wireless early warning intrusion detection prototype

The proliferation of wireless networks has been remarkable during the last decade. The license-free nature of the ISM band along with the rapid proliferation of the Wi-Fi-enabled devices, especially the smart phones, has substantially increased the demand for broadband wireless access. However, due to their open nature, wireless networks are susceptible to a number of attacks. In this work, we present anomaly-based intrusion detection algorithms for the detection of three types of attacks: (i) attacks performed on the same channel legitimate clients use for communication, (ii) attacks on neighbouring channels, and (iii) severe attacks that completely block network's operation. Our detection algorithms are based on the cumulative sum change-point technique and they execute on a real lightweight prototype based on a limited resource mini-ITX node. The performance evaluation shows that even with limited hardware resources, the prototype can detect attacks with high detection rates and a few false alarms. © 2012 Fragkiadakis et al

Collaborating in the context of co-location: a grounded theory study

BACKGROUND: Most individuals with mental health concerns seek care from their primary care provider, who may lack comfort, knowledge, and time to provide care. Interprofessional collaboration between providers improves access to primary mental health services and increases primary care providers’ comfort offering these services. Building and sustaining interprofessional relationships is foundational to collaborative practice in primary care settings. However, little is known about the relationship building process within these collaborative relationships. The purpose of this grounded theory study was to gain a theoretical understanding of the interprofessional collaborative relationship-building process to guide health care providers and leaders as they integrate mental health services into primary care settings. METHODS: Forty primary and mental health care providers completed a demographic questionnaire and participated in either an individual or group interview. Interviews were audio-recorded and transcribed verbatim. Transcripts were reviewed several times and then individually coded. Codes were reviewed and similar codes were collapsed to form categories using using constant comparison. All codes and categories were discussed amongst the researchers and the final categories and core category was agreed upon using constant comparison and consensus. RESULTS: A four-stage developmental interprofessional collaborative relationship-building model explained the emergent core category of Collaboration in the Context of Co-location. The four stages included 1) Looking for Help, 2) Initiating Co-location, 3) Fitting-in, and 4) Growing Reciprocity. A patient-focus and communication strategies were essential processes throughout the interprofessional collaborative relationship-building process. CONCLUSIONS: Building interprofessional collaborative relationships amongst health care providers are essential to delivering mental health services in primary care settings. This developmental model describes the process of how these relationships are co-created and supported by the health care region. Furthermore, the model emphasizes that all providers must develop and sustain a patient-focus and communication strategies that are flexible. Applying this model, health care providers can guide the creation and sustainability of primary care interprofessional collaborative relationships. Moreover, this model may guide health care leaders and policy makers as they initiate interprofessional collaborative practice in other health care settings

Lifetime optimization of wireless sensor networks with sleep mode energy consumption of sensor nodes

International audienceThe energy constraint is a major issue in wireless sensor networks since battery cells that supply sensor nodes have a limited amount of energy and are neither replaceable nor rechargeable in most cases. A common assumption in previous work is that the energy consumed by sensors in sleep mode is negligible. With this hypothesis, the usual approach is to iteratively consider subsets of nodes that cover all the targets. These subsets, also called cover sets, are then put in the active mode whereas the others are in the low-power or sleep mode. The scheduling of the appropriate cover sets in order to maximize the network lifetime is a challenging problem known to be NP-hard. The consideration of non-zero energy consumption of sensor nodes in sleep mode is more realistic but significantly increases the complexity of the problem. In this paper, we address this question by proposing a greedy algorithm that gives priority to sensors with lowest energy, and uses a blacklist to limit the number of sensors covering critical targets. Simulations show that this algorithm outperforms the previously published solutions. We then propose for regular arrays, an analytical approach which shows that, for any optimal solution, all sensors’ remaining energies are zero. This theoretical approach sheds a new light on ring connected arrays of odd size, that are known to be rather tricky when non-disjoint cover sets are considered