MCLab Group List of Papers -- Query Results

	MCLab Group List of Papers Home \| Show All \| Simple Search \| Advanced Search	Login Quick Search: Field: contains: ...
	121–130 of 143 records found matching your query (RSS):

Search & Display Options

Select All Deselect All

[1–10] << 11 12 13 14 15 >>

List View

Citations

Details

	Records
	Author	Fischer, S.; Ehrig, R.; Schaefer, S.; Tronci, E.; Mancini, T.; Egli, M.; Ille, F.; Krueger, T.H.C.; Leeners, B.; Roeblitz, S.
	Title	Mathematical Modeling and Simulation Provides Evidence for New Strategies of Ovarian Stimulation			Type	Journal Article
	Year	2021	Publication	Frontiers in Endocrinology	Abbreviated Journal
	Volume	12	Issue		Pages	117
	Keywords
	Abstract	New approaches to ovarian stimulation protocols, such as luteal start, random start or double stimulation, allow for flexibility in ovarian stimulation at different phases of the menstrual cycle. It has been proposed that the success of these methods is based on the continuous growth of multiple cohorts (“waves”) of follicles throughout the menstrual cycle which leads to the availability of ovarian follicles for ovarian controlled stimulation at several time points. Though several preliminary studies have been published, their scientific evidence has not been considered as being strong enough to integrate these results into routine clinical practice. This work aims at adding further scientific evidence about the efficiency of variable-start protocols and underpinning the theory of follicular waves by using mathematical modeling and numerical simulations. For this purpose, we have modified and coupled two previously published models, one describing the time course of hormones and one describing competitive follicular growth in a normal menstrual cycle. The coupled model is used to test ovarian stimulation protocols in silico. Simulation results show the occurrence of follicles in a wave-like manner during a normal menstrual cycle and qualitatively predict the outcome of ovarian stimulation initiated at different time points of the menstrual cycle.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1664-2392	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @ ref10.3389/fendo.2021.613048			Serial	189
Permanent link to this record



	Author	Chen, Q.M.; Finzi, A.; Mancini, T.; Melatti, I.; Tronci, E.
	Title	MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks			Type	Journal Article
	Year	2020	Publication		Abbreviated Journal	Fundamenta Informaticae
	Volume	174	Issue		Pages	229-258
	Keywords
	Abstract	In critical infrastructures like airports, much care has to be devoted in protecting radio communication networks from external electromagnetic interference. Protection of such mission-critical radio communication networks is usually tackled by exploiting radiogoniometers: at least three suitably deployed radiogoniometers, and a gateway gathering information from them, permit to monitor and localise sources of electromagnetic emissions that are not supposed to be present in the monitored area. Typically, radiogoniometers are connected to the gateway through relay nodes . As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper, we address the problem of computing a deployment for relay nodes that minimises the overall cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance ). We show that, by means of a computation-intensive pre-processing on a HPC infrastructure, the above optimisation problem can be encoded as a 0/1 Linear Program, becoming suitable to be approached with standard Artificial Intelligence reasoners like MILP, PB-SAT, and SMT/OMT solvers. Our problem formulation enables us to present experimental results comparing the performance of these three solving technologies on a real case study of a relay node network deployment in areas of the Leonardo da Vinci Airport in Rome, Italy.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1875-8681	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @			Serial	188
Permanent link to this record



	Author	Pappagallo, A.; Massini, A.; Tronci, E.
	Title	Monte Carlo Based Statistical Model Checking of Cyber-Physical Systems: A Review			Type	Journal Article
	Year	2020	Publication	Information	Abbreviated Journal
	Volume	11	Issue	558	Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @			Serial	181
Permanent link to this record



	Author	Tortora, L.; Meynen, G.; Bijlsma, J.; Tronci, E.; Ferracuti, S.
	Title	Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective			Type	Journal Article
	Year	2020	Publication	Frontiers in Psychology	Abbreviated Journal
	Volume	11	Issue		Pages	220
	Keywords
	Abstract	Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as Ã‚â€˜A.I. neuroprediction,Ã‚â€™ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1664-1078	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @ Neuroprediction-2020			Serial	180
Permanent link to this record



	Author	Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Sinisi, S.; Tronci, E.; Ehrig, R.; RÃ¶blitz, S.; Leeners, B.
	Title	Computing Personalised Treatments through In Silico Clinical Trials. A Case Study on Downregulation in Assisted Reproduction			Type	Conference Article
	Year	2018	Publication	25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018)	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @			Serial	175
Permanent link to this record



	Author	Mancini, T.; Tronci, E.; Scialanca, A.; Lanciotti, F.; Finzi, A.; Guarneri, R.; Di Pompeo, S.
	Title	Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network			Type	Conference Article
	Year	2018	Publication	25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018)	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @			Serial	174
Permanent link to this record



	Author	Driouich, Y.; Parente, M.; Tronci, E.
	Title	Model Checking Cyber-Physical Energy Systems			Type	Conference Article
	Year	2018	Publication	Proceedings of 2017 International Renewable and Sustainable Energy Conference, IRSEC 2017	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	Institute of Electrical and Electronics Engineers Inc.	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @ Driouich2018			Serial	177
Permanent link to this record



	Author	Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.; Hayes, B.; Prodanovic, M.; Elmegaard, L.
	Title	Parallel Statistical Model Checking for Safety Verification in Smart Grids			Type	Conference Article
	Year	2018	Publication	2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)	Abbreviated Journal
	Volume		Issue		Pages	1-6
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @ mancini-etal:2018:smartgridcomm			Serial	170
Permanent link to this record



	Author	Driouich, Y.; Parente, M.; Tronci, E.
	Title	A methodology for a complete simulation of Cyber-Physical Energy Systems			Type	Conference Article
	Year	2018	Publication	EESMS 2018 – Environmental, Energy, and Structural Monitoring Systems, Proceedings	Abbreviated Journal
	Volume		Issue		Pages	1-5
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @ Driouich20181			Serial	169
Permanent link to this record



	Author	Sinisi, S.; Alimguzhin, V.; Mancini, T.; Tronci, E.; Mari, F.; Leeners, B.
	Title	Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins			Type	Journal Article
	Year	2020	Publication		Abbreviated Journal	Fundamenta Informaticae
	Volume	174	Issue		Pages	283-310
	Keywords	Artificial Intelligence; Virtual Physiological Human; In Silico Clinical Trials; Simulation; Personalised Medicine; In Silico Treatment Optimisation
	Abstract	In Silico Clinical Trials (ISCT), i.e. clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulation-based experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine ). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1875-8681	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @			Serial	187
Permanent link to this record