DIGITAL SIGNAL PROCESSING
MULTIMEDIA & OPTICAL COMMUNICATIONS
Comlab is dedicated to the study of telecommunication and multimedia systems, with particular attention to the security and evaluation aspects of the Quality of Experience of the New Immersive Systems
It is part of the Department of Industrial, Electronic and Mechanical Engineering at University Roma TRE located in Roma, Italy
It is directed by Prof. Alessandro Neri
Machine learning is an expression used to describe systems that automatically learn to make predictions about some attributes of a data instance, such as the content of a picture or the evolution of the stock market, from a set of training data.
Deep learning describes a set of recent advancements in the fields of neural network, specifically referring to architectures and techniques leveraging an high number of hidden layers, thus described as deep neural networks.
Deep learning currently represents the state of the art in many machine learning tasks, especially in computer vision tasks, where deep architectures obtain super-human performances.
Deep neural networks have also enabled a number of surprising tasks, such as the generation of images from text descriptions and models that generate new deep architectures.
COMLAB’s publications about Deep Learning are:
In recent years, a huge amount of devices are connected to the Internet more than people. In 2020 there will be 50 billions of "things" connected to the Internet. It is then foreseen to have 7 devices per person. This has carried out to the evolution of a new emerging paradigm, namely the Internet of Things (IoT). In IoT scenarios, a large number of devices – and more in general objects – are seamlessly connected to each another for information sharing through the Internet.
Due to the huge amount of heterogeneous devices, information sharing among IoT devices is one of the biggest challenges. Classic Internet approaches need to be revised to address the complex requirements imposed by IoT. This asks for the development of intelligent algorithms for routing, information sharing security, novel network paradigms, new services, and advanced techniques for data fusion.
Among the main IoT applications we cite:
COMLAB’s publications about IoT are:
Multimedia quality
COMLAB’s publications about multimedia quality are:
Multimedia security
COMLAB’s publications about multimedia security are:
Molecular communications
In the past few years, nanotechnology has emerged as an evolution of technology enabling the design of miniaturized nanoscale devices, i.e., nanorobots and nanoparticles. The behaviors and characteristics of nanodevices distinguish them from the well-known features of devices at the macroscale level. A nanodevice is the most basic functional unit, allowed to perform very easy tasks, like sensing or actuation, due to the passive nature of these devices.
A set of nanodevices, sharing the same medium (e.g., the human blood flow) and collaborating on a common task (e.g., to deliver a drug concentration to a receptor), forms a nanonetwork. Nanonetworks are expected to expand the capabilities of single nanodevices and then to enable new nanotechnology applications in several fields.
Communication and signal transmission techniques occurring in nanonetworks are challenging topics, due to the limited computation skill of nanodevices. Molecular communication is largely exploited for nanonetworks. This is a novel communication paradigm, envisaged as the most practical way in which nanorobots can communicate with each other by the use of molecules as information carriers.
THz-band communications
Still in the context of nano-scale communications, the potentialities of the Terahertz (THz) frequency band are largely increasing, thanks to specific features that allow issues related to the spectrum scarcity and capacity limitation to be overcome.
The Terahertz band has been identified in the range (0.06 − 10) THz and represents one of the most promising spectrum bands to enable ultra-high-speed communications. Also, since existing channel models adopted for lower frequency bands are unsuitable for THz communications, the need of novel channel models specific for this frequency range is a challenge. Differently from traditional lower frequency bands, where the propagation is mainly influenced by the spreading loss only, the physical mechanisms in a THz-band wireless transmission are a very high molecular absorption loss, spreading loss and molecular absorption loss.
COMLAB is involved in several initiatives about nano-scale communications, such as:
COMLAB’s publications about nano-scale communications are:
In recent years, wireless communications have significantly evolved due to the advanced technology of smartphones, portable devices and the rapid growth of Internet of Things, e-Health, Intelligent Transportation Systems and social networking. Forecasted by Cisco, the wireless mobile traffic will be dominant over the data network towards a new connected world in 2020, with also the upcoming 5G systems.
Optical Wireless Communications (OWC) are a complementary wireless communications technology to the more established radio frequency (RF) based systems such as cellular, Wi-Fi and Bluetooth in order to overcome the spectrum crunch and provide high data rates. The OWC technology offers advantages such as free license, wide bandwidth, inherent security and no RF-based interference, which makes it very attractive for the emerging 5G wireless communications. Nevertheless, the widespread deployment of optical wireless systems, namely infra-red, ultra-violet and visible light communications (VLC), will face a number of challenged including the weather effects (mostly outdoor), eye and skin safety regulations, compatibility with existing networks, mobility (mostly in outdoor environment), cost per device and volume and device/system performance.
COMLAB is involved in several initiatives about OWC systems, such as:
COMLAB’s publications about OWC systems are:
Nowadays, several automotive manufacturers are looking forward to reach the goals envisioned by Vision 2020 action plan. Particularly, in 2012 the European Commission tabled the CARS 2020 Action Plan, aimed at reinforcing this industry’s competitiveness and sustainability heading towards 2020. The CAR 2020 Action Plan is supported by CARS 21 (Competitive Automotive Regulatory System for the 21 st century) Group, which provides recommendations to help car industry reaching new focuses, particularly those ones addressed to road safety. Indeed, it is known that worldwide more than one million people are killed, or injured in traffic accidents every year, mainly due to drivers’ misbehavior and bad road conditions.
Wireless ad hoc networks for vehicular environment i.e., the Vehicular Ad hoc NETworks (VANETs) are a particular class of Mobile Ad hoc NETworks (MANETs), characterized by high (variable) vehicle speed, hostile propagation environment and quickly changing network topologies. Opportunistic routing has been extended to VANETs in order to disseminate information and improve connectivity among vehicles. Message propagation occurs through (i) Vehicle-to-Vehicle (V2V) links built dynamically, where any vehicle can be used as next hop, so to form an end-to-end path toward a final destination and (ii) Vehicle-to-Infrastructure (V2I) links, assuming ubiquitous deployment of fixed road-side units.
COMLAB is involved in several initiatives about VANETs, such as:
COMLAB’s publications about VANETs are:
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.20
+39 06 5733 7017
81002
+39 06 5733 7026
alessandro.neriuniroma3.it
Alessandro Neri is full professor in Telecommunications at the Engineering Department of the University 'Roma Tre' of Rome, Italy.
He was born in Viterbo in 1954. In 1977 he received the Doctoral Degree cum laude in Electronic Engineering from the University of Rome 'La Sapienza'.
In 1978 he joined the Research and Development Department of Contraves Italiana S.p.A. where he gained a specific expertise in the field of radar signal processing and in applied detection and estimation theory, becoming the chief of the advanced systems group.
In 1987 he joined the INFOCOM Department of the University of Rome 'La Sapienza' as Associate Professor in Signal and Information Theory at the Engineering Faculty. In November 1992 he joined the Electronic Engineering Department of the University of Roma TRE as Associate Professor in Electrical Communications, and became full professor in Telecommunications in semptember 2001 (in 2012 the Electronic Engineering Department and the other Engineering Departments of Roma Tre merged into the Engineering Department).
Prof. Neri is also member of the board of the Doctoral School on Electronic Engineering of the University of Roma TRE.
Since December 2008, prof. Neri is the President of the RadioLabs Consortium (Consorzio Università Industria - Laboratori di Radiocomunicazioni), a not-for-profit Research Center created in 2001 to promote tight cooperation on applied research programs between universities and industries, and currently linking the University of Rome 'Tor Vergata', the University of Roma Tre, The University of Aquila, Ansaldo STS and Hitachi Systems CBT. He is currently teaching Digital Communications, Information Theory, and Navigation and Localization Systems, at the Engineering Department of Roma Tre.
His research activity has mainly been focused on Information Theory, Detection and Estimation Theory, Digital Signal Processing, and Image Processing and their applications to both telecommunications systems, navigation, and remote sensing including
He is author of more than 300 publications (Scopus h index: 20, Scopus citation index: 1830, Google Scholar h index: 29, Google Scholar citation index: 3690, id ORCID: orcid.org/0000-0002-5911-9490).
Since 2004 he is also Professor, by courtesy, at 'Scuola Superiore di Specializzazione in Telecomunicazioni', a Post Master Degree School in Telecommunications of The Ministry of Economic Development.
From 2006 to 2008 he was Professor, by courtesy, of 'Economics and Management of Communication Technologies', at the Business School of the LUISS University, Rome (Laurea Magistralis curriculum). Since 2008 to 2010 he was Professor, by courtesy, of 'Economics and Management of Communication Technologies', of the Master in Business Administration at the Business School of the LUISS University, Rome.
Since 1992, he is responsible for coordination and management of research and teaching activities in the Telecommunication fields at the University of Roma TRE, currently leading the COMLAB - Digital Signal Processing, Multimedia and Optical Communications Laboratory.
He is a member of IEEE and of the Institute of Navigation (ION).
International Journals
Books
Book Chapters and CDROM
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.22
+39 06 5733 7061
+39 06 5733 7026
marco.carliuniroma3.it
marcoskype5169
linkedin.com/in/mcarli
Marco Carli is Associate Professor with the Department of Engineering at the Università degli Studi 'Roma TRE', Roma, Italy. He received the Laurea degree in Telecommunication Engineering from the Università degli Studi di Roma 'La Sapienza', Roma, Italy and the Ph.D. degree from Tampere University of Technology, Tampere, Finland.
He was a Visiting Researcher with the Image Processing Laboratory, directed by prof. S.Mitra, UCSB, University of California, Santa Barbara, California, USA (2000-2004).
His research interests are in the area of digital signal and image processing with applications to multimedia communications. Specifically, he has been working on digital watermarking, multimedia quality evaluation, information security.
He is an Associate Editor of EURASIP Journal on Image and Video Processing (2011 - present) and Area Editor of Elsevier Signal Processing: Image Communication.
He is an IEEE Senior Member.
European projects
National projects
International Conferences
Journal publications
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 62 - Corpo B
00146, Roma - Italy
3rd floor - room 3.24
+39 06 5733 7356
federica.battistiuniroma3.it
Federica Battisti received the Laurea (Master of Science) in Electronic Engineering from Università degli Studi Roma Tre, Rome, Italy, in July 2006.
From August 2005 to February 2006 she worked as a Research Assistant at Tampere International Center for Signal Processing (TICSP) in Tampere University of Technology (TUT) located in Tampere, Finland. Her work in TICSP resulted in her master thesis titled 'Data hiding techniques in the Fibonacci domain'. During her staying in TICSP, she had been involved in a Human Visual System based image quality assessment project. This work was a part of a bigger research to obtain perceptually reliable objective image quality metrics.
From November 2006 to November 2009, she has been a Ph.D. student in Telecommunication Engineering at Università degli Studi Roma Tre. During this period, from June to July 2008 she was a visiting researcher in the Groupe Multimedia, in the Département Traitement du Signal et des Images of the Ecole Nationale Supérieure des Télécommunications in Paris under the supervision of Prof. B. Pesquet- Popescu.
From May to August 2009 she was a visiting researcher in the Departamento de Teoría de la Señal y las Comunicaciones of the Universidad de Vigo in Spain under the supervision of Prof. P. Comesana Alfaro.
In March 2010 she received the Ph.D. degree with a thesis titled 'Multimedia data hiding based on human perception characteristics'.
From December 2010 she is non-tenured Assistant Professor in the Department of Engineering at Università degli Studi Roma Tre.
She is an IEEE Senior member (2015 - present).
She is an Associate Editor of EURASIP Journal on Image and Video Processing (2017 - present).
She is an Associate Editor of ELSEVIER Signal Processing: Image Communication (2018 - present).
She is an Associate Editor of SPIE Journal of Electronic Imaging (JEI) (2018 - present).
She is member of the Visual Information Processing Special Area Team of EURASIP (2017 - present).
Her main research interests are signal and image processing with focus on subjective quality analysis of visual contents.
Her research activity started with the design and implementation of watermarking techniques for granting the ownership protection of images.
The investigation on this topic led to the study of quality issues related to the watermark invisibility that resulted in the definition of new image quality metrics and in the contribution to the creation of a widely used database for quality metrics benchmark.
The interest on image quality was later extended to video and multi-view imaging.
Currently, the area of interest is in the light-field imaging both for efficient depth map estimation and for quality assessment.
European projects
National projects
Journal publications
International Conferences
Books
a.a. 2017-2018
Contacts
Department of Industrial, Electronic and Mechanical Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 62 - Corpo B
00146, Roma - Italy
2nd floor - room 2.23
+39 06 5733 7357
+39 333 6570 348
+39 06 5733 7026
annamaria.vegniuniroma3.it
annamaria.vegni
Anna Maria Vegni is Associate Professor in Telecommunications at the Department of Industrial, Electronic and Mechanical Engineering (DIIEM) of Roma Tre University, since March 2023. She received the Laurea degree (cum laude) in Electronics Engineering and the Ph.D. degree in Biomedical Engineering, Electromagnetics, and Telecommunications from Roma Tre University, Rome, Italy, in 2006 and 2010, respectively. From 2010 to 2020, she was an Assistant Professor in Telecommunications at the Department of Engineering of Roma Tre University. From March 2020 to September 2021 she hold a Tenure-Track Assistant Professorship in Telecommunications at the Department of Engineering, Roma Tre University, and then was affiliated to DIIEM till today.
In 2009, she was a Visiting Researcher with the Prof. Thomas D.C. Little, at the Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA. Her research activity focused on vehicular networking and optical wireless communications (i.e., Visible Light Communications).
Since 2010, she has been in charge of the Telecommunications Networks Laboratory course, Roma Tre University. She is the author of more than 100 publications in journals, conferences, workshops, and book chapters. She co-edited the book Cognitive Vehicular Networks (CRC Taylor & Francis Group, 2016), and the book Vehicular Social Networks (CRC Taylor & Francis Group, 2017).
Her research interests include social networking, optical and RF wireless communications. She is involved in several European and National projects and organizing committees of international conferences. She is a member of ACM and IEEE, and a member of GTTI (Gruppo Telecomunicazioni e Tecnologie dell'Informazione).
Since September 2016, she is an IEEE Senior Member. She is also Award Co-chair of 2020-2021 N2WOMEN board, a discipline-specific community of researchers in the fields of networking and communications, supported by several major professional associations such as ACM SIGCOMM, ACM SIGMOBILE and IEEE ComSoc.
In March 2018, she got the Italian Habilitation (Abilitazione Scientifica Nazionale) for Associate Professorship in Telecommunication Engineering (SC: 09/F2; SSD: ING-INF/03).
In June 2021, she got the Italian Habilitation (Abilitazione Scientifica Nazionale) for Full Professorship in Telecommunication Engineering (SC: 09/F2; SSD: ING-INF/03).
Research interests:
Awards and recognitions:
Visiting Researchers at COMLAB:
Call for papers:
News and Events
Editorial Board - Associate Editor
Editorial Board - Guest Editor
Conference Chair
Technical program committees
European projects
National projects
Journal Papers
Conference Papers
Editorial Papers
Invited Talks
Books
Book Chapters
A.A. 2022-2023
A.A. 2021-2022
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7061
+39 331 6073 924
+39 06 5733 7026
massimo.massarouniroma3.it
massimo.massaro.uniroma3
linkedin.com/in/
Massimo Massaro received the Ph.D. degree in Applied Electronics from Università degli studi "Roma Tre" in May 2017 and the Laurea Degree summa cum laude in Electronics Engineering from Università degli studi di Roma "Tor Vergata", Rome, Italy, in July 1991
In 2007 he joined the Università degli studi "Roma Tre", Rome, Italy as a technician where he worked in several informatics projects.
From 2005 to 2006 he worked for Ericsson Lab Italy the R&D company of Ericsson Italy where he was responsible for the technology updating and adaptation to the new european directives RoHS of some electronic board mounted in the AXE telephone exchange.
From 2000 to 2004 he worked for Rima Recognition Products where he was responsible of the hardware development department.
From 1999 to 2000 he worked for ADtranz Italy (now Bombardier) as project engineer for the supply of the railway signaling equipment, the on-board computer system and the communication system for the new Porto underground transportation system.
In 1992 he joined Alenia Spazio (now Thales Alenia Space) as digital designer of satellite on-board equipments where he worked for several international projects, like:
His research interests are in the areas of smart environments, indoor positioning, sensor networks and internet of things.
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7370
+39 06 5733 7026
federico.colangelouniroma3.it
Federico Colangelo received the first level degree, Laurea in Electronic Engineering from Roma Tre University on October 2012, with a thesis on Quantum Cryptography.
He received the second level degree, Laurea Magistrale in Information and Communication Technology Engineering from Roma Tre University on October 2014, with a thesis about security of Software Defined Networks.
From november 2014 to november 2017 he has been a Ph.D. student in the Roma Tre University.
His main research interests are in Communication Security and Machine Learning-based Semantic Processing of multimedia data.
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7370
+39 06 5733 7026
pramit.mazumdaruniroma3.it
Pramit Mazumdar received his Bachelor of Technology (B.Tech) degree in Information Technology from West Bengal University of Technology (WBUT), Kolkata, India in 2008 and Master of Technology (M.Tech) degree in Information Technology from Jadavpur University (JU), Kolkata, India in 2012.
He has submitted Thesis for Doctor of Philosophy (Ph.D.) degree in Computer Science and Engineering from National Institute of Technology Rourkela (NITR), Rourkela, India in 2018.
From May 2018 he is Post Doc in Roma Tre University.
His research interests are Human-Computer Interaction, Machine Learning, Data Science and Information Retrieval.
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7026
giuliano.arruuniroma3.it
Giuliano Arru received the Bachelor's Degree in 2009 in Computer Science from Roma Tre University with a thesis on Semantic Web.
During the Master's Degree, in particular the following fields were investigated: software developing, machine learning, information retrieval, user modelling, and information extraction in intelligent system on web context.
He obtained the Master's Degree in Computer Science from Roma Tre University on October 2012, with a thesis about user modelling and information retrieval titled 'Signal-Based User Recommendation on Twitter'
After degree he started his professional career in software developing specialized in Microsoft technology.
He became Ph.D. student in November 2017 in the research field 'Machine Learning for light field processing'.
His research field is Machine Learning for light field processing.
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7026
sara.baldoniuniroma3.it
Sara Baldoni received her Bachelor degree in Electronics Engineering from Roma Tre University in 2016 and Master degree in Information and Communication Technology Engineering from Roma Tre University in 2018.
From november 2018 she is a Ph.D. student in Applied Electronics at the Engineering Department of Roma Tre University.
Her main research interests are in the area of Communication Security and Navigation and Localization Systems.
International Journals
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7026
michele.brizziuniroma3.it
Michele Brizzi received the Laurea (B.Sc.) in Electronics Engineering and the Laurea Magistrale (M.Sc) in Information and Communication Technology Engineering from Roma Tre University in 2016 and 2018, respectively.
Starting November 2018, he is a Ph.D. student in Applied Electronics at the Engineering Department of Roma Tre University.
His main reasearch interests are in the area of multimedia signal processing.
International Journals
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7370
+39 06 5733 7026
moses.mariajosephuniroma3.it
Moses Mariajoseph, received his bachelor degree (B.Eng) in Electronics and Communication from Sathyabama University, Chennai, India in 2010. Due to his great quest, he also did his dual bachelor degree (B.Eng) in Computer Science Engineering from Sathyabama University, Chennai, India in 2011. Through his motivation and self-interest he did his Master degree (M.Tech) in Mechatronics from VIT University, Vellore, India in 2013, with a thesis about System design and development of new machining setup for energy efficient turning process. During his master study in VIT University, he was a student’s representative.
In further he obtained an opportunity to do his second masters in Computational Engineering from University of Rostock, Rostock, Germany. During his master study, he has worked as a research assistant in clean room ISO class 5.
He worked as a student researcher in Celisca, Rostock, Germany with the research focus on localization of Mobile Robots. Later he was worked as System Design and Control research engineer, in TPRC, Enschede, the Netherlands with a project focus on Robotized feedback system for induction welding in the thermoplastic composite material.
From November 2018 he is PhD student in Roma Tre University.
His research interests are .
International Conferences
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7370
+39 06 5733 7026
Mr. Syed M. Umair Arif was born in Pakistan on 1988. In 2008, he completed his Diploma of Associate Engineering in Electrical Engineering from Science Institute of Technology, Pakistan. Major Subject
In 2012, he completed his Bachelor of Science in Computer Science with Specialization of Computer Network systems from Federal Urdu University Art Sciences and Technology, Pakistan. Major Subjects
In 2018, he completed his Masters of Science with Distinction in Bio Technical System & Technology with Bio Medical Engineering from Tomsk Polytechnic University Tomsk Russia. It was collaborative study between Siberian State Medical University and Tomsk Polytechnic University. He completed his 21 credit hours of study in Medical University
In Bachelors he studied Computer Science and chose his specialization computer networks and he have hand on experience on Cisco Systems, Juniper, Motorola, D-Link, Ericson, Huawei, ZTE, TP Link, Linksys, Netgear and NEC Routers and Switches. He also studied Cisco Courses CCNA Routing & Switching, Cisco Wireless, Cisco Introduction, and MCSE. Moreover he studied Computer Programming & Fundamentals, Data Structures & Algorithms, Operating System, Databases, Computer Networks & Advance computer networks, Network Programing, Network Management, Network Simulation & Modeling, Network Security & Encryption Algorithms, Telecommunication Protocol Network 1 & 2, Wireless Communication, Traffic forecast and network Planning. In bachelor I got experience used Network Simulator and Emulators
In Masters he studied Bio Medical Engineering and worked in Medical Hospital and Medical University during his practices and completed 60 Credit Hours of study. He also worked in Tomsk Polytechnic Research center & RASA Center in Tomsk almost one and half year and provided his voluntary services to automate Medical machines for remote uses
In Masters he worked on Telemedicine Application “Telemedicine application for remote hearing evaluation and speech therapy for deaf people after cochlear implantation”. In Master Project he built his own network for provide Online Classes & VoIP services with secure communication and connect Doctor to Patients, Doctors to Doctors through mobile phone devices and Personal Computers and record all audio sessions. Before using Audio Codecs he performed different simulations and he recorded live audio sessions and check different parameters of audio signals and analyze which codec is best for providing Telespeech therapy after cochlear implant surgery via internet. Same he simulated network all over the Russia and tested network on OPNET simulator which routing algorithm and which communication media is best for providing medical services on remote areas on low bandwidth internet
Graduate Research Engineer at Tomsk Polytechnic University (Tomsk Russia) February 2017 to June 2018
Technical Support Engineer at Future Now Technology Project May 2016 to November 2016 (Prime communications AT&T U.S) http://www.primecomms.com
Network Support Engineer at Inovedia Technology Project December 2014 to February 2106 (ULTRA MOBILE MVNO U.S) https://ultramobile.com
IT Admin at QATAR DESCON Engineering Doha, Qatar Feb 2014 to May 1st 2014
IT Support Engineer/Network Engineer at PRIME ENGINEERING & TESTING CONSULTANTS, Islamabad, Pakistan March 2013 to 26 Feb 2014
Cisco CCNA (NUST, Pakistan)
Work Management System (RasGas Qatar)
MCSE (F.U.U.A.S.T, Pakistan)
MTA (F.U.U.A.S.T, Pakistan)
Cisco Wireless (F.U.U.A.S.T, Pakistan)
SBC GENBAND QUANTIX Q20( INOVEDIA TECHNOLOGIES)
INGATE SIParator (INOVEDIA TECHNOLOGIES)
Best Performance certificate of the month ( RasGas Qatar)
Best Performance certificate for completing training (RasGas Qatar)
Scholarship from Russia educational ministry and science for Masters
3rd Prize Medal in Digital Hackthon in Tomsk Russia
Gold Medal in Masters studies from Tomsk Polytechnic University
1st prize in photography competition for capturing nature of Siberia
He got pedagogical practice for 6 months with one Professor to teach biocompatible materials subject to students
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7370
+39 06 5733 7026
pradip.paudyaluniroma3.it
pradip.paudyal
Pradip Paudyal received his PhD from Department of Engineering at the Università degli Studi 'Roma TRE', Roma, Italy in 2017 and M.Sc. in Information and Communication Engineering from Tribhuvan University, Kathmandu, Nepal in 2010.
He has also completed Masters in Business Administration (MBA-Executive) in 2014 from Ace Institute of Management, Kathmandu Nepal.
Now, he is serving as an Asst. Director at Nepal Telecommunications Authority (NTA), Kathmandu, Nepal.
Multimedia signal processing and communication, Perceptual quality assessment, and Quality of Experiance (QoE).
Contacts
Department of Engineering
Applied Electronics Section
Roma TRE University
via Vito Volterra, 60 - Corpo B
00146, Roma - Italy
3rd floor - room 3.3
+39 06 5733 7370
+39 06 5733 7026
Yiwei Liu, graduated from "Tianjin University" with bachelor degree in information engineering in 2008. In the same year she entered Huawei, wireless marketing department, working as product pre-sales engineer. After that, she moved to the New Land Group, working as overseas pre-sales engineer. Then she decided to go back to school for further study.
From October 2011 to October 2013, she studied in "Roma Tre University" for Master's degree. Later, from January 2014 to May 2017, she continuous her study in the same university, and received her PhD degree in November 2017.
She mainly involved her research in train control communication support system. During her Ph.D study, she finished two projects, including the MPTCP project and MPUDP project. Both of them is in partnership with Selex S.P.A.
The MPTCP project proposed a new train communication system architecture, which uses the public network and satellite communication technology under the umbrella of the MPTCP transmission protocol to realize the transmission of train control signaling data. The new architecture can achieve the same transmission reliability, availability level as the current dedicated GSM-R network.
The MPUDP solution uses multiple links to transmit the voice packets during train control using scenario. This solution, combined with RaptorQ encoding, can fulfill the system reliability and real-time transport requirements. Moreover, it can well solve packet loss and out-of-order issues during the transmission as well.
Journal Papers
Conference Papers
Deep learning is one of the fastest-growing segments of the machine learning or artificial intelligence field and a key area of innovation in computing. With researchers creating new deep learning algorithms and industries producing and collecting unprecedented amounts of data, computational capability is the key to unlocking insights from data
The DIGITS DevBox is a deep learning machine designed and built by NVIDIA to give researchers all the computational power they need in a compact box that fits easily under any desk
Hardware |
---|
Four TITAN X GPUs with 12GB of memory per GPU |
64GB DDR4 |
Asus X99-E WS workstation class motherboard with 4-way PCI-E Gen3 x16 support |
Core i7-5930K 6 Core 3.5GHz desktop processor |
Three 3TB SATA 6Gb 3.5" Enterprise Hard Drive in RAID5 |
512GB PCI-E M.2 SSD cache for RAID |
250GB SATA 6Gb Internal SSD |
1600W Power Supply Unit from premium suppliers including EVGA |
Software |
Ubuntu 14.04 |
NVIDIA-qualified driver |
NVIDIA® CUDA® Toolkit |
NVIDIA® DIGITS™ SW |
NVIDIA® cuDNN™ |
Caffe, Theano, Torch, BIDMach |
Once you put on the Vive headset, you are immersed in a world full of surprises
Walk around freely and explore everything while the Chaperone guidance system keeps you within the bounds of your play area. Stunning graphics make it feel so real and surreal simultaneously
The HTC VIVE VR system is composed by several parts:
Headset |
---|
110° field of view |
2160 x 1200 combined resolution and 90 Hz refresh rate |
Front camera to blend the real-world around you into the virtual world you are immersed in |
32 sensors for 360° motion tracking |
Controllers |
Multi-function hi-resolution trackpad with haptic feedback |
24 sensors for 360° motion tracking on each controller |
Tracker (optional) |
Sensors for 360° motion tracking |
Can be attached to any object you want to carry into the virtual world |
Base stations |
Laser coverage of the play area for 360° tracking of headset, controllers and tracker with millimeter accuracy |
Wireless connection, only a power cable is required |
The Leap Motion controller is a small USB peripheral device designed to be placed on a physical desktop, facing upward or onto a virtual reality headset, whose purpose is to determine the position and gestures of the user's hands
The device frames an approximately hemispherical area at a distance of about 1 meter through two IR cameras and three IR LEDs. The LEDs generate IR light, the two cameras capture reflected light and generate about 200 frames per second that are analyzed and processed by the software that produces a 3D map of user hands moving into space in front of the device with a precision of about 0.7 mm
The device can be used as a contactless Human-Machine-Interface which possible uses are:
Lytro ILLUM is a light field camera and software platform designed to redefine the way we portray the world around us. Harnessing the full power of the light field, the Lytro ILLUM gives photographers a unique way of capturing visual experiences - not as a static cross-section of reality but an interactive window into their world through Light Field Photography
Unlike a conventional digital camera, the Lytro ILLUM captures the light field, which includes the direction of light. Most recently, light field cameras lived only in academic labs - via a roomful of cameras tethered to a supercomputer. Lytro's scientists and engineers have optimized this technology so that the power of the light field can fit right in your hands
Capturing this fundamentally new data gives consumers unprecedented capabilities, including the ability to focus, change the perspective, change the aperture, and view in 3D - all after a picture is taken. Photographers using the Lytro ILLUM have new creative opportunities to tell stories and capture moments, delivering Living Pictures to friends, family, and clients
Weight and Dimensions |
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Height: 3.4 inches (86 mm) |
Width: 5.7 inches (145 mm) |
Depth: 6.5 inches (166 mm) |
Weight: 2.07 pounds (940 g) |
Display |
4" Back-lit LCD rear touchscreen with capacitive multi-touch |
480-by-800-pixel resolution at 235 ppi |
Adjustable Brightness |
Live View Rendering |
Dual hinge tilting articulation mechanism |
Articulated Angles: -10 to +90 degrees |
Angle of View: Up to 80 degrees |
Image sensor |
Light field sensor based on CMOS technology |
Light Field Resolution: 40 Megaray |
Sensor Format: 1/1.2" |
Active Area: 10.82 x 7.52 mm |
ISO Range: 80-3200 |
Processor |
Snapdragon® 800 processor by QUALCOMM® Incorporated |
Lens |
Focal Length: 9.5 - 77.8 mm (30 - 250 mm equivalent) |
Crop Factor: 3.19 |
Zoom: 8x optical |
Lens Aperture: Constant /2.0 |
Macro: Focus to 0 mm from lens front |
Macro Ratio: 1 : 3 |
Wireless |
Wi-Fi (802.11a/b/g/n/ac) |
Image format |
Light Field RAW Format (.lfr) |
3 : 2 Aspect Ratio |
2D export resolution: 2450 x 1634 pixels |
Shutter |
Focal Plane Shutter |
Fastest Shutter Speed: 1/4000 sec |
Longest Shutter Speed: 32 seconds |
Flash Sync Speed: 1/250 sec |
Drive Modes: Single, continuous or self-timer |
Self-Timer: Yes (2 or 10 seconds) |
Continuous Drive: 3 fps |
Power and battery |
Removable 3.7 V, 3760 mAH Li-ion battery |
Battery Charging via Standalone wall charger and USB |
The NI USRP-2943R software defined radio platform provides an integrated hardware and software solution for rapidly prototyping high-performance wireless communication systems
Each device is composed by one large digital motherboard, with a Xilinx Kintex-7 (410T) FPGA, and two RF transceivers, also called daughterboards, and it is housed in a half-1U rack-mountable form factor metallic case
The Kintex-7 FPGA is a reconfigurable LabVIEW FPGA target that incorporates DSP48 coprocessing for high-rate, low-latency applications. With the flexible hardware architecture and the LabVIEW unified design flow, researchers can prototype faster and significantly shorten time to results
It is used to prototype a wide range of advanced research applications that include multiple input, multiple output (MIMO); synchronization of heterogeneous networks; LTE relaying; RF compressive sampling; spectrum sensing; cognitive radio; beamforming; and direction finding
The NI USRP-2943R main characteristics are:
The device can be programmed with National Instruments LabVIEW, that is a graphical programming tool
Each device can be equipped with several daughterboards, depending on the needs and the system requirements. Comlab owns three different kind of daughterboards: the CBX-40, the CBX-120 and the WBX-120
Transmitter section | |
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Number of channels | 2 |
Frequency range (with the CBX daughterboards) | 1.2 GHz to 6 GHz |
Frequency range (with the WBX-120 daughterboard) | 50 MHz to 2.2 GHz |
Frequency step | <1 kHz |
Maximum output power (Pout) (with the CBX daughterboards) 1.2 GHz to 3.5 GHz 3.5 GHz to 6 GHz | 50 mW ÷ 100 mW (17 dBm ÷ 20 dBm) 5 mW ÷ 32 mW (7 dBm ÷ 15 dBm) |
Maximum output power (Pout) (with the WBX-120 daughterboard) 50 MHz to 1.2 GHz 1.2 GHz to 2.2 GHz | 50 mW ÷ 100 mW (17 dBm ÷ 20 dBm) 30 mW ÷ 70 mW (15 dBm ÷ 18 dBm) |
Gain range (with the CBX daughterboards) | 0 dB to 31.5 dB |
Gain range (with the WBX-120 daughterboard) | 0 dB to 31 dB |
Gain step (with the CBX daughterboards) | 0.5 dB |
Gain step (with the WBX-120 daughterboard) | 1.0 dB |
Frequency accuracy - based on temperature-compensated crystal oscillator (TCXO) - based on optional GPS receiver | 2.5 ppm 25 ppb |
Maximum instantaneous real-time bandwidth (with the CBX-120 and WBX-120 daughterboards) | 120 MHz |
Maximum instantaneous real-time bandwidth (with the CBX-40 daughterboard) | 40 MHz |
Maximum I/Q sample rate | 200 MS/s |
Digital-to-analog converter (DAC) - Resolution - Spurious-free dynamic range (sFDR) | 16 bit 80 dB |
Receiver section | |
Number of channels | 2 |
Frequency range (with the CBX daughterboards) | 1.2 GHz to 6 GHz |
Frequency range (with the WBX-120 daughterboard) | 50 MHz to 2.2 GHz |
Frequency step | <1 kHz |
Gain range | 0 dB to 37.5 dB |
Gain step | 0.5 dB |
Maximum input power (Pin) | -15 dBm |
Noise figure | 5 dB to 7 dB |
Frequency accuracy - based on temperature-compensated crystal oscillator (TCXO) - based on optional GPS receiver | 2.5 ppm 25 ppb |
Maximum instantaneous real-time bandwidth (with the CBX-120 and WBX-120 daughterboards) | 120 MHz |
Maximum instantaneous real-time bandwidth (with the CBX-40 daughterboard) | 40 MHz |
Maximum I/Q sample rate | 200 MS/s |
Digital-to-analog converter (DAC) - Resolution - Spurious-free dynamic range (sFDR) | 14 bit 88 dB |
Bringing innovation to the imaging experience. Record and recreate the real world in 360 degrees
High quality image with improved resolution delivers a more natural three-dimensional experience and coloring. 360º spatial audio lets you record sound from all directions. Realistically record images and audio of the world surrounding youto recreate inspiring moments
Image data recorded on THETA S can be played back in 360º on a monitor such as TV. The THETA S also functions as a remote control which can be used to select the image file and move displayed 360º image up, down, left, and right. It can also zoom-in and out
Enjoy high-sensitivity shooting from ISO 3200 (still images) to ISO 6400 (videos, live streaming). This range of sensitivity is highly effective for shooting in dark scenes
This model is equipped with a new gyro sensor in addition to the conventional acceleration sensor. Tilt detection precision has been significantly improved, along with top/bottom correction precision enhancements and the ability for Remote Playback
Advanced image processing technology cultivated over the years in camera development deliver image quality with minimal loss of shadow detail and highlight blowout even in scenes with varying levels of contrast. The white balance algorithm has been completely retuned to achieve natural hues for a wide range of scenes
This model supports 4K compatible 360 degree live streaming. Output the 4K (3840x1920 pixels), 360º image in real-time
RICOH THETA S is compatible with the Google Street View app. The app enables you to record and publish 360 video (as Street View) to Google Maps
Object distance | Approx. 10cm - ∞ (from front of lens) |
Shooting mode | Still image: Auto, shutter priority, ISO priority, manual Video: Auto Live streaming: Auto |
Exposure control mode | Program AE, Shutter speed priority AE, ISO sensitivity AE, Manual exposure |
Exposure compensation | Still image: Manual compensation (-2.0 - +2.0EV, 1/3EV step) |
ISO sensitivity (standard output sensitivity) | Still image: ISO 100 - 1600 Video: ISO 100 - 1600 Live streaming: ISO 100 - 1600 |
White balance mode | Still image: Auto, Outdoor, Shade, Cloudy, Incandescent light 1, Incandescent light 2, Daylight color fluorescent light, Natural white fluorescent light, White fluorescent light, Light bulb color fluorescent light, Color temperature specification shots Video: Auto Live streaming: Auto |
Shutter speed | Still image: (Excluding Mnual mode) 1/6400 - 1/8 seconds, (Manual mode) 1/6400 - 60 seconds Video: (L) 1/8000 - 1/30 seconds, (M) 1/8000 - 1/15 seconds Live streaming: (USB) 1/8000 - 1/15 seconds, (HDMI) 1/8000 - 1/30 seconds |
Click the images above to see them in Panoramic mode
Depth-Image-Based-Rendering (DIBR) techniques are essential for three dimensional (3D) video applications such as 3D Television (3DTV) and Free-Viewpoint Video.
However, this process is based on 3D warping and can induce serious distortions whose impact on the perceived quality is far different from the one experienced in the 2D imaging processes.
Since quality evaluation of DIBR-synthesized views is fundamental for the design of perceptually-friendly 3D video systems, an appropriate objective quality metric targeting the assessment of DIBR-synthesized views is momentous.
Most of 2D objective quality metrics fail in assessing the visual quality of DIBR-synthesized views because they have not been conceived for addressing the specificities of DIBR-related distortions.
In this paper, a new fullreference objective quality metric dedicated to artifacts detection in DIBR-synthesized view-points is presented.
The proposed scheme relies on a comparison of statistical features of wavelet subbands of two input images: the original image and the DIBR-based synthesized image.
A registration step is included before the comparison step so that best matching blocks are always compared to ensure "shifting-resilience".
In addition, a skin detection step weights the final quality score in order to penalize distorted blocks containing "skin-pixels" based on the assumption that a human observer is most sensitive to impairments affecting human subjects.
We are making the objective metric available to the research community free of charge.
If you use this database in your research, we kindly ask that you reference our paper listed below:
F. Battisti, E. Bosc, M. Carli, P. Le Callet, and S. Perugia 'Objective Image Quality Assessment of 3D Synthesized Views', Signal Processing: Image Communication, Volume 30, January 2015, Pages 78-88, doi:10.1016/j.image.2014.10.005.
The investigators in this research are:
16 Light Field (LF) images are included in the SMART LF dataset.
The images are from both indoor and outdoor category, and cover general image content related features (colorfulness, spatial information, and texture) but also LF specific aspects such as reflection, transparency and depth of field variation.
If you use this dataset please cite the following papers:
Download LF dataset
The investigators in this research are:
The cost is about 15 Euro.
By busIn Piazza dei Cinquecento, take bus 170 and get off at the stop Marconi/Bortolotti in Viale Guglielmo Marconi, 446.
Continue walking in the same direction for a few meters to reach via Corrado Segre, walk 50 meters until the end of the street and you will reach via Vito Volterra, 60 (see below).
The bus/subway ticket costs 1,50 Euro and it is valid for one subway trip and unlimited bus ride for 75 minutes.
Take linea B (direction Laurentina) and get off at Basilica S.Paolo.
From the subway station take the exit for via Ostiense and Basilica S.Paolo, walk through viale Giustiniano Imperatore (leaving the church San Paolo on your right).
At the second traffic-light turn left to via Tullio Levi-Civita and go straight to reach viale Guglielmo Marconi cross it and take via Corrado Segre, walk 50 meters until the end of the street and you will reach via Vito Volterra, 60 (see below).
The bus/subway ticket costs 1,50 Euro and it is valid for one subway trip and unlimited bus ride for 75 minutes.
The cost is about 45 Euro.
By train By busTake train FL1 and get off at Roma Trastevere railway station. Then bus 170 (follow the indication from Termini Station).
The one way train ticket costs 8 Euro.
At the gate (via Vito Volterra, 60) enter and continue straight following the internal pahway
The building we are in is the metal and glass modern building on the left
Enter the door, overpass the reception desk and take the elevator on the right
On the third floor, get off the elevator, turn right, go past the orange door and follow the corridor
The Comlab entrance (room 3.3) is on the right opposite room 3.21 and is immediately after the men's bathroom
Since Engineering Department is in one of the most touristic places in Rome, near the Basilica of St. Paul outside the Walls, there are several possibilities to stay in the immediate surroundings.