Search results for: Gianni Izzo

Authors: Gianni Izzo

Abstract:

The relation of Islam to its legal precepts, reflected in the various jurisprudential 'schools of thought' (madhahib), is one expressed in a version of 'positivism' (fiqh) providing the primary theory for deducing Qurʾan rulings and those from the narrations (hadith) of the Prophet Muhammad. Scholars of Islam, including Patricia Crone (2004) and others chronicled by Anver Emon (2005), deny the influence of natural law theories as extra-scriptural indices of revelation’s content. This paper seeks to dispute these claims by reference to historical and canonical examples within Shiʿa legal thought that emphasize the salient roles of ‘aql (reason), fitrah (primordial human nature), and lutf (divine grace). These three holistic features, congenital to every human, and theophanically reflected in nature make up a mode of moral intelligibility antecedent to prophetic revelation. The debate between the 'traditionalist' Akhbaris and 'rationalist' Usulis over the nature of deriving legal edicts in Islam is well-covered academic ground. Instead, an attempt is made to define and detail the built-in assumptions of natural law revealed in the jurisprudential summa of Imami Shiʿism, whether of either dominant school, that undergird its legal prescriptions and methods of deduction.

Keywords: Islam, fiqh, natural law, legal positivism, aql

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

Abstract:

In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

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Authors: André Lages, Victor Dmitriev, Juliano Bazzo, Gianni Portela

Abstract:

This work evaluates the feasibility of the graphene application to perform as a wideband reconfigurable material for lens antennas in 5G/6G and satellite applications. Based on transformation optics principles, the electromagnetic waves can be efficiently guided by modifying the effective refractive index. Graphene behavior can range between a lossy dielectric and a good conductor due to the variation of its chemical potential bias, thus arising as a promising solution for electromagnetic devices. The graphene properties and a lens antenna comprising multiples layers and periodic arrangements of graphene patches were analyzed using full-wave simulations. A dipole directivity was improved from 7 to 18.5 dBi at 29 GHz. In addition, the realized gain was enhanced 7 dB across a 14 GHz bandwidth within the Ka/5G band.

Keywords: 5G/6G, graphene, lens, reconfigurable, satellite

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Authors: Mario Gianni, Federico Nardi, Federico Ferri, Filippo Cantucci, Manuel A. Ruiz Garcia, Karthik Pushparaj, Fiora Pirri

Abstract:

In this paper, we describe a Mixed-Initiative Operational Model (MIOM) which directly intervenes on the state of the functionalities embedded into a robot for Urban Search&Rescue (USAR) domain applications. MIOM extends the reasoning capabilities of the vehicle, i.e. mapping, path planning, visual perception and trajectory tracking, with operator knowledge. Especially in USAR scenarios, this coupled initiative has the main advantage of enhancing the overall performance of a rescue mission. In-field experiments with rescue responders have been carried out to evaluate the effectiveness of this operational model.

Keywords: mixed-initiative planning and control, operator control interfaces for rescue robotics, situation awareness, urban search, rescue robotics

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Authors: Albert Bou, Sebastian Dittert, Gianni de Fabritiis

Abstract:

Advancing reinforcement learning (RL) requires tools that are flexible enough to easily prototype new methods while avoiding impractically slow experimental turnaround times. To match the first requirement, the most popular RL libraries advocate for highly modular agent composability, which facilitates experimentation and development. To solve challenging environments within reasonable time frames, scaling RL to large sampling and computing resources has proved a successful strategy. However, this capability has been so far difficult to combine with modularity. In this work, we explore design choices to allow agent composability both at a local and distributed level of execution. We propose a versatile approach that allows the definition of RL agents at different scales through independent, reusable components. We demonstrate experimentally that our design choices allow us to reproduce classical benchmarks, explore multiple distributed architectures, and solve novel and complex environments while giving full control to the user in the agent definition and training scheme definition. We believe this work can provide useful insights to the next generation of RL libraries.

Keywords: deep reinforcement learning, Python, PyTorch, distributed training, modularity, library

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

Abstract:

The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Elena C. Tamaş, Grațiela M. Țârlea, Gianni Flamaropol, Dragoș Hera

Abstract:

This article is referring to a comparative study regarding the electrical energy consumption for lighting on diverse types of big sizes commercial buildings built in Romania after 2007, having 3, 4, 5 versus 8, 9, 10 operational years. Some buildings have installed building management systems (BMS) to monitor also the lighting performances starting with the opening days till the present days but some have chosen only local meters to implement. Firstly, for each analyzed building, the total required energy power and the energy power consumption for lighting were calculated depending on the lamps number, the unit power and the average daily running hours. All objects and installations were chosen depending on the destination/location of the lighting (exterior parking or access, interior or covering parking, building interior and building perimeter). Secondly, to all lighting objects and installations, mechanical counters were installed, and to the ones linked to BMS there were installed the digital meters as well for a better monitoring. Some efficient solutions are proposed to improve the power consumption, for example the 1/3 lighting functioning for the covered and exterior parking lighting to those buildings if can be done. This type of lighting share can be performed on each level, especially on the night shifts. Another example is to use the dimmers to reduce the light level, depending on the executed work in the respective area, and a 30% power energy saving can be achieved. Using the right BMS to monitor, the energy consumption depending on the average operational daily hours and changing the non-performant unit lights with the ones having LED technology or economical ones might increase significantly the energy performances and reduce the energy consumption of the buildings.

Keywords: commercial buildings, energy performances, lightning consumption, maintenance

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Authors: Gianni Blasi, Daniele Perrone, Maria Antonietta Aiello

Abstract:

The seismic vulnerability of non-structural components is nowadays recognized to be a key issue in performance-based earthquake engineering. Recent loss estimation studies, as well as the damage observed during past earthquakes, evidenced how non-structural damage represents the highest rate of economic loss in a building and can be in many cases crucial in a life-safety view during the post-earthquake emergency. The procedures developed to evaluate the seismic demand on non-structural components have been constantly improved and recent studies demonstrated how the existing formulations provided by main Standards generally ignore features which have a sensible influence on the definition of the seismic acceleration/displacements subjecting non-structural components. Since the influence of the infills on the dynamic behaviour of RC structures has already been evidenced by many authors, it is worth to be noted that the evaluation of the seismic demand on non-structural components should consider the presence of the infills as well as their mechanical properties. This study focuses on the evaluation of time-history floor acceleration in RC buildings; which is a useful mean to perform seismic vulnerability analyses of non-structural components through the well-known cascade method. Dynamic analyses are performed on an 8-storey RC frame, taking into account the presence of the infills; the influence of the elastic modulus of the panel on the results is investigated as well as the presence of openings. Floor accelerations obtained from the analyses are used to evaluate the floor response spectra, in order to define the demand on non-structural components depending on the properties of the infills. Finally, the results are compared with formulations provided by main International Standards, in order to assess the accuracy and eventually define the improvements required according to the results of the present research work.

Keywords: floor spectra, infilled RC frames, non-structural components, seismic demand

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