A Quantum Key Distribution (QKD) based Physical Layer Security (PLS) scheme (QKD-PLS) for optical fiber links is proposed and evaluated. In detail, a novel amplitude and phase scrambling technique for exploiting and seamlessly integrating high key rate QKD for the encryption of the modulation parameters of conventional complex modulation schemes like M-ary Quadrature Amplitude Modulation (M-QAM) and Orthogonal Frequency Division Multiplexing (OFDM) is described. The technique masks the information at the bit level and blocks unauthorized access to the higher layer encrypted bitstream. Scrambling is applied to both the preamble (pilot) and payload segments of the transmission frame, to prevent the eavesdroppers from performing vital receiver functions such as frame synchronization and channel estimation. Additionally, a practical Key Management System (KMS) which takes care of all synchronization processes is developed and introduced. Experimental transmission scenario in fiber links is also presented and depicts the efficacy of the QKD-PLS. Moreover, another advantage of QKD exploitation to the proposed solution comes from the application of kbps-rate QKD keys which feed pseudo-random number generators, to modify the broadband modulation symbols in one-time pad, therefore significantly improving data protection.

Over the last decade, blockchain technology has evolved from being a peer-to-peer implementation of digital currency into a framework for numerous applications. That is, blockchain is widely recognized as the technology behind cryptocurrencies, such as bitcoin, but recent research indicates that it can be exploited way more than that. Among the most notable characteristics of the blockchain technology are system decentralization, data immutability, transaction transparency, and user privacy. Thus, it becomes apparent that it can significantly benefit many consumer applications, where trust and security are crucial aspects of the implementation. In this paper, we review and present, in a tutorial manner, blockchain's fundamental postulates and characteristics, and we introduce a novel point of view, where we visualize a layered representation of the blockchain infrastructure, so as to analyze it as a framework. Thinking of blockchain technology as a framework may assist consumers to better understand its capabilities and limitations. In addition, we review emerging blockchain-based applications that span across many different scientific fields. We also discuss the relative merits and restrictions. Namely, we have identified applications in finance, smart contracts, Internet of Things, e-voting systems, storage and data protection, reputation systems, healthcare, and transportation, indicating that the blockchain technology is becoming a framework for endless applications.

Physical Layer Security (PLS) exploits characteristics and properties of the physical layer for data encryption and supplements conventional cryptography for enhanced overall security. Most of the PLS methodologies rely on the (statistical) characteristics of the transmission channel to either generate secure encryption keys, or to exploit them together with other physical layer characteristics (i.e. advanced modulation schemes) for secure transmission. However, these approaches often lead to increased complexity and therefore become impractical for actual system implementation. Recent advancements in Quantum Key Distribution (QKD) systems allow for the utilization of ultra-secure and robust high-rate key exchange. In this work, we propose and describe practical techniques for exploiting and seamlessly integrating highrate QKD keys to encrypt modulation parameters and quantities of conventional modulation schemes like M-QAM, DMT and OFDM of communication links. Moreover, we present transmission scenarios, integrating QKD-PLS in free space optics links, together with their numerical evaluation. The main advantage of QKD exploitation to the proposed solutions comes from the seamless and transparent integration and application of high-rate keys which can either be used in their original form or feed a pseudo-random number generator, to modify the modulation properties/symbols in very high rates, such that eavesdropping and decoding of the encrypted information becomes almost impossible. Additionally, we present the architecture of a real time practical system utilizing and seamlessly integrating the QKD keys into transceiver links to form a robust and ultra-secure PLS ecosystem.

Multicore fibers can be used for Radio over Fiber transmission of mmwave signals for phased array antennas in 5G networks. The inter-core skew of these fibers distorts the radiation pattern and has to be measured and compensated. We propose a method to accurately measure the differential delays remotely, after installation, without intervening heavily with the transmitter setup. The properties of the phase response measured at a distant receiver are exploited to acquire the differential delays among the antenna array elements.

In 5G networks, a Radio over Fiber architecture utilizing multicore fibers can be adopted for the transmission of mmwave signals feeding phased array antennas. The mmwave signals undergo phase shifts imposed by optical true time delay networks, to provide squint free beams. Multicore fibers are used to transfer the phase shifted optical signals. However, the inter-core static skew of these fibers, if not compensated, distorts the radiation pattern. We propose an efficient method to compensate the differential delays, without full equalization of the transmission path lengths, reducing the power loss and complexity. Statistical analysis shows that regardless of the skew distribution, the frequency response can be estimated with respect to the rms skew delays. Simulation analysis of the complete Radio over Fiber and RF link validates the method.

With the rise of the Internet of Things (IoT), applications have become smarter and connected devices give rise to their exploitation in all aspects of a modern city. As the volume of the collected data increases, Machine Learning (ML) techniques are applied to further enhance the intelligence and the capabilities of an application. The field of smart transportation has attracted many researchers and it has been approached with both ML and IoT techniques. In this review, smart transportation is considered to be an umbrella term that covers route optimization, parking, street lights, accident prevention/detection, road anomalies, and infrastructure applications. The purpose of this paper is to make a self-contained review of ML techniques and IoT applications in Intelligent Transportation Systems (ITS) and obtain a clear view of the trends in the aforementioned fields and spot possible coverage needs. From the reviewed articles it becomes profound that there is a possible lack of ML coverage for the Smart Lighting Systems and Smart Parking applications. Additionally, route optimization, parking, and accident/detection tend to be the most popular ITS applications among researchers.

With the rise of the Internet of Things (IoT), applications have become smarter and connected devices give rise to their exploitation in all aspects of a modern city. As the volume of the collected data increases, Machine Learning (ML) techniques are applied to further enhance the intelligence and the capabilities of an application. The field of smart transportation has attracted many researchers and it has been approached with both ML and IoT techniques. In this review, smart transportation is considered to be an umbrella term that covers route optimization, parking, street lights, accident prevention/detection, road anomalies, and infrastructure applications. The purpose of this paper is to make a self-contained review of ML techniques and IoT applications in Intelligent Transportation Systems (ITS) and obtain a clear view of the trends in the aforementioned fields and spot possible coverage needs. From the reviewed articles it becomes profound that there is a possible lack of ML coverage for the Smart Lighting Systems and Smart Parking applications. Additionally, route optimization, parking, and accident/detection tend to be the most popular ITS applications among researchers.

Over the recent years many modulation schemes were proposed for laser based high-speed short-range transmission over step-index plastic optical fiber (SI-POF). Among these schemes, CAP and DFT-Spread DMT demonstrated a good performance for intensity modulation direct-detection transmission via SI-POF. In this work, for the first time, we report on the progress and initial experimentation regarding the comparison of CAP and DFT-Spread DMT for transmission over 50m of 1-mm SI-POF. It is shown that CAP and DFT-Spread DMT achieve a comparable transmission rate for a given bit error rate over the same experimental configuration.

This paper describes INNOETICS' Speech Synthesis System entry for the Blizzard Challenge 2016, along with the corresponding results and some relevant discussion. We provide a description of the underlying system and techniques used in our TTS platform, as well as some detailed information regarding the voice building process. Based on the obtained results from the listening experiments, we attempt an evaluation of our system and the underlying methods.

This work explores affective word ratings as an auxiliary target cost for unit-selection-based concatenative speech synthesis. The method does not require task-specific crafted corpora, nor does it rely on additional annotations, making it ideal for found data. Following the general philosophy of our text-to-speech system, the approach does not enforce any explicit prosodic model, instead the affect information is implicitly modeled via its contribution to the unit-selection cost function. The auxiliary affective feature vector comprises of continuous ratings in three dimensions (valence, arousal and dominance), extracted at the word level via state-of-the-art sentiment analysis techniques. In this case study, speech data consists of several professionally-produced children's audiobooks totaling about 5 hours of speech. The affective dimensions are shown to correlate well with acoustic/prosodic features extracted from the speech data, highlighting their utility for the affective speech synthesis. This is further confirmed via a preference listening test between the baseline and the affective voice.

Microwave radiometers are instruments for resolving blackbody radiation of heated matter above absolute zero, with many applications including breast cancer diagnosis.In this work a prototype microwave radiometer including a controllable noise reference generator was designed.The design of this noise source is based on the NC303 noise diode that delivers symmetrical white Gaussian noise and flat output power versus frequency (10MHz -10GHz).An embedded PID control scheme is responsible for temperature stabilization of this sub-unit.The PID controller is designed to cope with disturbance rejection and set-point tracking problems.The first step in PID tuning involved extraction of the system's open loop transfer function.Then the internal model control (IMC) method was used for tuning the controller and the resulting control scheme was successfully applied to the real system.

Microwave Thermograph (MT) is based on measuring the electromagnetic field spontaneously emitted by a body in micro-wave frequency range. In microwave radiometers, temperature measurement is made by measuring the thermal noise power. The primary module that is used for detecting this thermal noise power is the RF Front-end, which must meet very challenging requirements in terms of accuracy for measuring the noise power at the input of the receiver. The work that will be presented here will exhibit the design approaches and specifications as well as the trade-offs and performance criteria towards the development and prototyping of the RF Front-end for a Multi-Channel Microwave Radiometer for internal body temperature measurements in the l-4GHz frequency bands. The RF Front-end is intended to be integrated and be a part of a full Microwave Radiometer device that targets early detection of malignant tumours. The latter relate with the increase of temperature in cancerous cells and the precise detection of the temperature difference, which is the goal of the radiometer.

The Long Term Evolution (LTE) and LTE-Advanced (LTE-A) wireless communication standards was postulated by 3GPP to realize the objectives of the International Mobile Telecommunications-Advanced (IMT-A) organization for 4G cellular systems. To achieve these goals, modern and sophisticated communication techniques such as OFDM and MIMO are utilized at the physical layer. To verify and make measurements on such standards, instrumentation equipment with high specifications together with specialized software is required. In this paper, an experimental framework for studying and measuring LTE and LTE-A is presented, consisting of high-end laboratory equipment and software tools. Using this experimental framework, demonstration experiments for the physical layer are performed for SISO, MISO, and MIMO transmission according to the LTE and LTE-A standards, verifying the 3GPP Reference Measurement Channels (RMCs) specifications and depicting the framework's functionality.

Emotion-aware computing presents one of the key challenges in contemporary natural human interaction research in which emotional speech is an essential modality in multimodal user interfaces. Speech modality relates mainly to speech emotion and affect recognition as well as near natural expressive speech synthesis, the latter being considered as one of the next significant milestones in speech synthesis technology. A common problem to recognizing as well as to generating affective and emotional speech content is the adopted methodology on emotion analysis and modeling. This work proposes a generalized framework for annotating, analyzing and modeling expressive speech in a data-driven machine learning approach, towards building expressive text to speech synthesis systems. To this end, the framework as well as the data driven methodology is described, comprised of the techniques and approaches for acoustic analysis and expression clustering. In addition, the deployment of online experimental tools for speech perception and annotation and the description of the utilized speech data together with initial experimental results are also given, depicting the potential of the proposed framework and providing encouraging indications for further research.

Emotion-aware computing presents one of the main challenges in contemporary natural human interaction research, with natural expressive speech synthesis being one of its next significant milestones. This paper describes ongoing work on developing a generalized framework for annotating, analyzing and modeling expressive speech in a data driven approach, towards building expressive text to speech synthesis systems. To this end, the data driven methodology is described, comprised of the acoustic analysis and expression clustering together with an online environment for speech perception and annotation. Preliminary results are also given, providing encouraging indications for further research.

This paper describes ILSP and INNOETICS Speech Synthesis System entry for the Blizzard Challenge 2013. A description of the underlying system and techniques used is provided, as well as information about the voice building process and discussion on the obtained evaluation results. Extra focus will be given on the new techniques we used this year in comparison to our previous participations, and we will also attempt a comparative analysis of this year’s results with the results of the Blizzard Challenge 2012, aiming to investigate the abilities and the progress performed as far as expressive speech synthesis is concerned.

Creating new voices for a TTS system often requires a costly procedure of designing and recording an audio corpus, a time consuming and effort intensive task. Using publicly available audiobooks as the raw material of a spoken corpus for such systems creates new perspectives regarding the possibility of creating new synthetic voices quickly and with limited effort. This paper addresses the issue of creating new synthetic voices based on audiobook data in an automated method. As an audiobook includes several types of speech, such as narration, character playing etc., special care is given in identifying the data subset that leads to a more neutral and general purpose synthetic voice. Part of the work described in this paper was carried out for the participation of our TTS system in the Blizzard Challenge 2013 where the developed TTS system was ranked top in overall impression in one of the two experimental hubs (Chalamandaris et al 2013). The main goal is to identify and address the effect the audiobook speech diversity on the resulting TTS system. Along with the methodology for coping with this diversity in the speech data, we also describe a set of experiments performed in order to investigate the efficiency of different approaches for automatic data pruning. Further plans for exploiting the diversity of the speech incorporated in an audiobook are also described in the fmal section and conclusions are drawn.

This paper presents an overview of the Text-to-Speech synthesis system developed at the Institute for Language and Speech Processing (ILSP). It focuses on the key issues regarding the design of the system components. The system currently fully supports three languages (Greek, English, Bulgarian) and is designed in such a way to be as language and speaker independent as possible. Also, experimental results are presented which show that the system produces high quality synthetic speech in terms of naturalness and intelligibility. The system was recently ranked among the first three systems worldwide in terms of achieved quality for the English language, at the international Blizzard Challenge 2013 workshop.

In this paper we describe the design and deployment of a real-time simplex wireless SISO- and MISO-OFDM transmission setup on 5GHz employing two TMS320C6713 DSP Starter Kits (DSKs) as the baseband transmitter and receiver. The baseband system level design is done using Matlab/Simulink and the deployment on the TMS320C6713 DSKs is performed by means of IDE link via automatic code generation directly from Simulink blocks, offering a flexible way from system level design and simulation to actual implementation and verification. The wireless part is built based on conventional components and employs two transmit and one receive antennas. For both SISO and MISO, all the basic building blocks are comprised also including Maximum Likelihood (ML) synchronization based on the cyclic prefix as well as sampling clock frequency offset estimation and compensation. The implemented test-bed is intended primarily for educational demonstration and experimentation purposes for highlighting and studying several concepts and phenomena not only regarding the modulation schemes but the wireless link as a whole. Typical results for the experimental demonstration and evaluation of the system are presented.