TAN: A Distributed Algorithm for Dynamic Task Assignment in WSNs

We consider the scenario of wireless sensor networks where a given application has to be deployed and each application task has to be assigned to each node in the best possible way. Approaches where decisions on task execution are taken by a single central node can avoid the exchange of data packets between task execution nodes but cannot adapt to dynamic network conditions, and suffer from computational complexity. To address this issue, in this paper, we propose an adaptive and decentralized task allocation negotiation algorithm (TAN) for cluster network topologies. It is based on noncooperative game theory, where neighboring nodes engage in negotiations to maximize their own utility functions to agree on which of them should execute single application tasks. Performance is evaluated in a city scenario, where the urban streets are equipped with different sensors and the application target is the detection of the fastest way to reach a destination, and in random WSN scenarios. Comparisons are made with three other algorithms: 1) baseline setting with no task assignment to multiple nodes; 2) centralized task assignment lifetime optimization; and 3) a dynamic distributed algorithm, DLMA. The result is that TAN outperforms these algorithms in terms of application completion time and average energy consumption. Published in

Cooperative task assignment for distributed deployment of applications in WSNs

Nodes in Wireless Sensor Networks (WSNs) are becoming more and more complex systems with the capabilities to run distributed structured applications. Which single task should be implemented by each WSN node needs to be decided by the application deployment strategy by taking into account both network lifetime and execution time requirements. In this paper, we propose an adaptive decentralised algorithm based on noncooperative game theory, where neighbouring nodes negotiate among each other to maximize their utility function. We then prove that an increment of the nodes utility corresponds to the same increment of the utility for the whole network. Simulation results show significant performance improvement with respect to existing algorithms

A case of early neonate bovine tuberculosis in Ethiopia.

This report illustrates that calves may be infected with bovine tuberculosis at early age under natural conditions and progression can be rapid. Thus, testing of calves needs to be considered in any control program to reduce the risk of transmission

MBotCS: A mobile botnet detection system based on machine learning

As the use of mobile devices spreads dramatically, hackers have started making use of mobile botnets to steal user information or perform other malicious attacks. To address this problem, in this paper we propose a mobile botnet detection system, called MBotCS. MBotCS can detect mobile device traffic indicative of the presence of a mobile botnet based on prior training using machine learning techniques. Our approach has been evaluated using real mobile device traffic captured from Android mobile devices, running normal apps and mobile botnets. In the evaluation, we investigated the use of 5 machine learning classifier algorithms and a group of machine learning box algorithms with different validation schemes. We have also evaluated the effect of our approach with respect to its effect on the overall performance and battery consumption of mobile devices

Quantum-dot single-photon sources for entanglement enhanced interferometry

The authors acknowledge financial support from the Center for Integrated Quantum Science and Technology (IQST).Multiphoton entangled states such as “N00N states” have attracted a lot of attention because of their possible application in high-precision, quantum enhanced phase determination. So far, N00N states have been generated in spontaneous parametric down-conversion processes and by mixing quantum and classical light on a beam splitter. Here, in contrast, we demonstrate superresolving phase measurements based on two-photon N00N states generated by quantum dot single-photon sources making use of the Hong-Ou-Mandel effect on a beam splitter. By means of pulsed resonance fluorescence of a charged exciton state, we achieve, in postselection, a quantum enhanced improvement of the precision in phase uncertainty, higher than prescribed by the standard quantum limit. An analytical description of the measurement scheme is provided, reflecting requirements, capability, and restraints of single-photon emitters in optical quantum metrology. Our results point toward the realization of a real-world quantum sensor in the near future.PostprintPostprintPeer reviewe

Quantum-dot single-photon sources for entanglement enhanced interferometry

The authors acknowledge financial support from the Center for Integrated Quantum Science and Technology (IQST).Multiphoton entangled states such as “N00N states” have attracted a lot of attention because of their possible application in high-precision, quantum enhanced phase determination. So far, N00N states have been generated in spontaneous parametric down-conversion processes and by mixing quantum and classical light on a beam splitter. Here, in contrast, we demonstrate superresolving phase measurements based on two-photon N00N states generated by quantum dot single-photon sources making use of the Hong-Ou-Mandel effect on a beam splitter. By means of pulsed resonance fluorescence of a charged exciton state, we achieve, in postselection, a quantum enhanced improvement of the precision in phase uncertainty, higher than prescribed by the standard quantum limit. An analytical description of the measurement scheme is provided, reflecting requirements, capability, and restraints of single-photon emitters in optical quantum metrology. Our results point toward the realization of a real-world quantum sensor in the near future.PostprintPostprintPeer reviewe

Free Flaps for Advanced Oral Cancer in the Older Old and Oldest Old : A Retrospective Multi-Institutional Study

Introduction: Surgery followed by adjuvant therapy represents the most adequate treatment for advanced oral squamous cell carcinoma (OSCC). Free flaps are considered the best reconstructive option after major oral surgery. In the last decades, OSCC has increased in the elderly due to an augmented life span. The aim of this work is to evaluate the feasibility of microvascular surgery in patients older than 75 years, focusing on clinical and surgical prognosticators. Methods: "Older old" (aged >= 75) and "oldest old" (>85) patients who underwent microvascular reconstruction for OSCC from 2002 to 2018 were retrospectively evaluated in three referral Head and Neck Departments. Demographic, clinical, and surgical data were collected and analyzed. Pre-operative assessment was performed by ASA and ACE-27 scores. Complications were grouped as medical or surgical, an d major or minor according to the Clavien-Dindo scale. Results: Eighty-four patients (72 "older old" and 12 "oldest old") were treated with a free flap success rate of 94.1%. Thirty-seven (44.7%) and nine (10.7%) patients had minor and major medical complications, respectively; 18 (21.4%) and 17 (20.2%) had minor and major surgical complications, respectively. Twenty-one (25%) patients had both medical and surgical complications (with a statistically significant association, p = 0.018). Overall, 52 (61.9%) patients had at least one complication: ASA score, diabetes mellitus, and duration of general anesthesia (DGA) significantly impacted the complication rate at multivariate analysis. Conclusion: Our data confirm the feasibility of free flaps for OSCC reconstruction in appropriately selected elderly patients. Pre-operative assessment and aggressive management of glycemia in patients with diabetes is mandatory. DGA should be reduced as much as possible to prevent post-surgical complications. Comprehensive geriatric assessment is of paramount importance in this subset of patients

When Models Interact with their Subjects: The Dynamics of Model Aware Systems

A scientific model need not be a passive and static descriptor of its subject. If the subject is affected by the model, the model must be updated to explain its affected subject. In this study, two models regarding the dynamics of model aware systems are presented. The first explores the behavior of "prediction seeking" (PSP) and "prediction avoiding" (PAP) populations under the influence of a model that describes them. The second explores the publishing behavior of a group of experimentalists coupled to a model by means of confirmation bias. It is found that model aware systems can exhibit convergent random or oscillatory behavior and display universal 1/f noise. A numerical simulation of the physical experimentalists is compared with actual publications of neutron life time and {\Lambda} mass measurements and is in good quantitative agreement.Comment: Accepted for publication in PLoS-ON

A sentiment analysis software framework for the support of business information architecture in the tourist sector

In recent years, the increased use of digital tools within the Peruvian tourism industry has created a corresponding increase in revenues. However, both factors have caused increased competition in the sector that in turn puts pressure on small and medium enterprises' (SME) revenues and profitability. This study aims to apply neural network based sentiment analysis on social networks to generate a new information search channel that provides a global understanding of user trends and preferences in the tourism sector. A working data-analysis framework will be developed and integrated with tools from the cloud to allow a visual assessment of high probability outcomes based on historical data, to help SMEs estimate the number of tourists arriving and places they want to visit, so that they can generate desirable travel packages in advance, reduce logistics costs, increase sales, and ultimately improve both quality and precision of customer service