A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

A management architecture for active networks

In this paper we present an architecture for network and applications management, which is based on the Active Networks paradigm and shows the advantages of network programmability. The stimulus to develop this architecture arises from an actual need to manage a cluster of active nodes, where it is often required to redeploy network assets and modify nodes connectivity. In our architecture, a remote front-end of the managing entity allows the operator to design new network topologies, to check the status of the nodes and to configure them. Moreover, the proposed framework allows to explore an active network, to monitor the active applications, to query each node and to install programmable traps. In order to take advantage of the Active Networks technology, we introduce active SNMP-like MIBs and agents, which are dynamic and programmable. The programmable management agents make tracing distributed applications a feasible task. We propose a general framework that can inter-operate with any active execution environment. In this framework, both the manager and the monitor front-ends communicate with an active node (the Active Network Access Point) through the XML language. A gateway service performs the translation of the queries from XML to an active packet language and injects the code in the network. We demonstrate the implementation of an active network gateway for PLAN (Packet Language for Active Networks) in a forty active nodes testbed. Finally, we discuss an application of the active management architecture to detect the causes of network failures by tracing network events in time

Prognostic factors of survival in patients treated with nab-paclitaxel plus gemcitabine regimen for advanced or metastatic pancreatic cancer: A single institutional experience.

The objectives of this study were to evaluate the effectiveness of nab-paclitaxel plus gemcitabine (NAB-P/GEM) regimen in an unselected population of patients with advanced inoperable or metastatic pancreatic cancer (PC), and to identify the prognostic factors influencing overall survival (OS). EXPERIMENTAL DESIGN: Patients with age < 85 years, ECOG-performance status (PS) < 3, and adequate renal, hepatic and hematologic function were eligible. NAB-P (125 mg/m2) and GEM (1000 mg/m2) day 1,8,15 every 4 weeks were employed for 3-6 cycles or until highest response. RESULTS: Overall, 147 cycles (median 4, range 1-11 cycles) were administered on thirty-seven consecutive patients (median 66 years old, range 40-82) treated. The median overall progression-free survival and OS were 6.2 and 9.2 months, respectively. The G 3-4 dose-limiting toxicity were neutropenia (20.7%), severe anemia (17.2%), and cardiovascular toxicity (10.3%). PS, number of cycles, baseline CA 19-9 and LDH serum levels, were found to be significantly related to OS. The multivariate analysis showed that both number of cycles (HR = 9.14, 95% CI 1.84-45.50, p = 0.001) and PS (HR = 13.18, 95% CI 2.73-63.71, p = 0.001) were independently associated with OS. CONCLUSION: NAB-P/GEM regimen should be used in all patients with advanced or metastatic PC, with the exception of those with serious contraindications to chemotherapy, such as severe renal or hepatic impairment or major cardiovascular diseases

A mobile application for assessment of air pollution exposure

In this paper the architecture of a mobile air quality monitoring system is introduced. A mobile application will act as a personal assistant, monitoring and giving advices about gas pollutants daily exposure. Currently in development stage as part of a larger air quality monitoring system project, the application will enable users to monitor their daily exposure to gas pollutants by combining user location data and urban air quality information provided by the network of fixed monitoring stations of the city of Palermo

Simulation and Test of UAV Tasks with Resource-Constrained Hardware in the Loop

Simulations are indispensable to reduce costs and risks when developing and testing algorithms for unmanned aerial vehicles (UAV) especially for applications in high risk scenarios like search and rescue (SAR) operations and post-disaster damage assessment. Many UAV applications require real-time tasks for which the timeliness of computations is fundamental. However, standard simulation tools are not guaranteed to run in sync with real-time events, leading to unreliable assessments of the ability of the target hardware to perform specific tasks. In this work we present a simulation and test system able to run UAV tasks on resource-constrained target hardware possibly adopted in these applications. The system allows for hardware-in-the-loop simulations in which a virtual UAV provided with virtual sensors is controlled by the software under test (SUT) running on the target hardware, while simulated and real time are kept in sync. We provide experimental results from the execution of several increasingly difficult tasks in the system

A Smart Assistant for Visual Recognition of Painted Scenes

Nowadays, smart devices allow people to easily interact with the surrounding environment thanks to existing communication infrastructures, i.e., 3G/4G/5G or WiFi. In the context of a smart museum, data shared by visitors can be used to provide innovative services aimed to improve their cultural experience. In this paper, we consider as case study the painted wooden ceiling of the Sala Magna of Palazzo Chiaramonte in Palermo, Italy and we present an intelligent system that visitors can use to automatically get a description of the scenes they are interested in by simply pointing their smartphones to them. As compared to traditional applications, this system completely eliminates the need for indoor positioning technologies, which are unfeasible in many scenarios as they can only be employed when museum items are physically distinguishable. Experimental analysis aimed to evaluate the performance of the system in terms of accuracy of the recognition process, and the obtained results show its effectiveness in a real-world application scenario

Smart assistance for students and people living in a campus

Being part of one of the fastest growing area in Artificial Intelligence (AI), virtual assistants are nowadays part of everyone's life being integrated in almost every smart device. Alexa, Siri, Google Assistant, and Cortana are just few examples of the most famous ones. Beyond these off-the-shelf solutions, different technologies which allow to create custom assistants are available. IBM Watson, for instance, is one of the most widely-adopted question-answering framework both because of its simplicity and accessibility through public APIs. In this work, we present a virtual assistant that exploits the Watson technology to support students and staff of a smart campus at the University of Palermo. Some in progress results show the effectiveness of the approach we propose

Assisted labeling for spam account detection on twitter

Online Social Networks (OSNs) have become increasingly popular both because of their ease of use and their availability through almost any smart device. Unfortunately, these characteristics make OSNs also target of users interested in performing malicious activities, such as spreading malware and performing phishing attacks. In this paper we address the problem of spam detection on Twitter providing a novel method to support the creation of large-scale annotated datasets. More specifically, URL inspection and tweet clustering are performed in order to detect some common behaviors of spammers and legitimate users. Finally, the manual annotation effort is further reduced by grouping similar users according to some characteristics. Experimental results show the effectiveness of the proposed approach