ABSTRACT. To the beginning of the next decade, the world community will shift towards a more digitalized, information-driven, and intelligently inspired ecosystem with needs for ubiquitous and instant connectivity. Next-generation mobile communications play a steering role in this evolution. Network slicing is an up-and-coming resource provisioning technique in the future cellular architecture, with the aim to meet heterogeneous service requirements. The integration of blockchain technology in mobile networks will allow more efficient and transparent resource management and utilization while reducing its administration costs and complexity of negotiation. Moreover, security aspects are of great importance, too. Motivated by these facts, this paper seeks to provide a comprehensive survey on the integration of blockchain with 5G and beyond systems in the network slicing domain. An efficient and realistic network slicing framework based on blockchain technology is proposed. Lastly, the survey is completed by shedding new light on future research directions in this emerging area.

ABSTRACT. Communication technologies will have tremendous presence in modern smart cities, providing means for massive data collection, plethora of services and technical management and control. However, as the complexity of the underlying complex communication systems increases, so do the security challenges and risks, which raises concerns about the smart city technology in general. Standard communication security approaches implemented in conventional wireless and wired networks are typically focused only on specific protocols and communication schemes, and, hence, are not well grounded for smart cities from the complexity and diversity point of view. In this paper, we provide an overview of physical layer communication security challenges and risks in smart cities. We argue that, besides higher-level information protection, an appropriate framework for intrusion detection and threat/attack classification and identification is of utmost importance. For this purpose, we propose to use methods based on applying automatic modulation classification (AMC) systems. We provide overview of the appropriate AMC schemes, and discuss their properties, advantages and disadvantages in tackling the security challenges.

ABSTRACT. The Radio Access Network openness enables innovative applications to access network functions and information. In this paper, an approach to define a mobile edge service for measurement configuration is proposed. Application-specific measurements may contribute to better decision making and to better flexibility and adaptability to services.

ABSTRACT. Ultra high-speed and reliable next-generation 6G mobile networks are recognized as key enablers for many innovative scenarios in smart cities – from vehicular use cases and surveillance to healthcare. However, deployment of such network requires tremendous amount of time and involves various costs. For that reason, optimal network planning is of utmost importance for development of 6G mobile networks in smart cities. In this paper, we explore the potential of multi-objective linear optimization in synergy with model-driven approach in order to achieve efficient network planning in smart cities. As outcome, a solution relying on pymoo is proposed and compared to previous works relying only on single objective implemented in AMPL. According to the achieved results, this approach speeds up the execution, while giving more flexibility when it comes to cost/performance trade-offs.

ABSTRACT. This article observes a mutual recognition mechanism that could be used to exchange cross-border data and documents needed for international trade. The authors focused on the description of data that should be interchanged across borders. The article describes the mutual recognition of e-documents and data mechanisms. A case study on creating a green corridor for trade-related data and e-documents exchanged across borders is presented.

ABSTRACT. In this paper, liquid-gated graphene field effect transistor (LG-GFET) biosensors are demonstrated for exosomes sensing. Since the exosome is negative charged and thus served as n-type doping effect to graphene, the conductivity of the LG-GFET will varied loading with different exosome concentration. Therefore, exosomes concentration can be distinguished by detecting drain-source current (Ids) variation of LG-GFETs. The experimental results show that, compared to the blank group without exosomes, the change of Dirac-point gate voltage (VCNP) by using static method and saturation Ids by using dynamic method is larger than 80% and 18.8%, receptively. Moreover, the change rates of VCNP and saturation Ids versus exosomes concentrations are also investigated, which shows more than 7% and 12.5%, respectively. It is worthy to find out that it is only 30 seconds for LG-GFET biosensors to detect exosomes concentrations using dynamic method. These results indicate that LG-GFET biosensors can achieve rapid and sensitive detection of exosomes and provide an effective tool for clinical application and medical diagnostics.

ABSTRACT. The development of a passive wetness sensor and its use case in creating a smart diaper is discussed in this paper. A touch-free means of probing the diaper for non-intrusive detection of urinary incontinence is also proposed. Additional report is about the development of a contactless activity monitor realized using a convolutional neural network model to classify activities recorded by a radar device into their respective activity classes. Both sensors are suitable for indoor use and can be operated under minimal supervision.

ABSTRACT. In this paper we propose a sensing platform for dielectric constant sensing based on a microwave spoof surface plasmon polaritons sensor and integrated chamber for liquid samples. The influence of different geometrical parameters on sensor response are analyzed, and the sensor performances are optimized for ultrasensitive detection of low dielectric constant in liquid samples.

ABSTRACT. As a minimally invasive tumor treatment method, microwave ablation (MWA) has received more and more attention in clinical applications. The challenge is to design an antenna that can generate a localized heating area, to kill all cancer cells while affecting normal cells as little as possible. An inexpensive balun-free antenna based on a coaxial line is designed in this paper. By adding a short-circuited sleeve at the end of coaxial line, the current on the outer conductor of the coaxial line is suppressed and, finally, the area of the ablation is located. The ablation experiment based on the simulation gel confirms the effectiveness of the designed antenna. Under the input power of 16 W at 2.45 GHz, the temperature of the tissue rises from 26℃ to 47℃, and a highly localized ablation zone is achieved.

ABSTRACT. Surface acoustic wave (SAW) resonators have found applications in different engineering applications, including bioengineering applications. In this paper a model of a SAW resonator based on the artificial neural networks (ANNs) has been proposed. ANNs are exploited to model the frequency dependence of the resonator admittance parameters. The results obtained for a two-port packaged SAW resonator with a nominal resonant frequency of 423.2 MHz are shown.

ABSTRACT. This paper describes a mobile application that uses a convolutional neural network to recognize objects and then communicate them to the user using a text to speech module. The application would primarily be used by visually impaired people as a tool for better understanding the immediate environment.

ABSTRACT. The Golgi apparatus (GA) is a cellular organelle involved in the processing and sorting of proteins in eukaryotic cells. Due to its numerous functions, structural complexity, and organizational dynamics, the role of the GA in normal and pathological processes is still under intensive research. In this work, we present an approach to automatic segmentation of the GA in electron microscopy volumetric data, consisting of i) a neural network trained on approximately labelled data, ii) active contours for refining the segmentation, and iii) filtering of the segmented regions. Evaluation on 3D volumes of a urinary bladder epithelial cell shows that the proposed algorithm is able to segment the GA with 89% sensitivity and 99% specificity. Using approximate labels reduced the time needed for manual annotation of the ground truth by a factor of five.

ABSTRACT. Walking droplets represent an ideal playground to explore wave-particle duality at the macroscopic scale. The proper control and measurement of such system requires several experimental tools that are not often easily affordable at undergraduate level. This paper proposes a complete low-cost and open-source experimental setup for walking droplets with a performance characterization. The setup is tested by examining the behaviour of droplets in the stadium billiard, a two-dimensional concave cavity that yields chaotic trajectories. Drastic differences between classical and quantum particles behaviour were observed in such geometry. In particular, the long-term evolution of walking droplets in a stadium billiard presents clear scarring patterns, informing on the existence of preferred "probable positions" within the billiard.

ABSTRACT. Due to digitization and the rapid evolution of technologies, cryptography is no longer sufficient to ensure a secure digital life.Hence, the need for steganography. In this article,the best-known methods are explained and a new steganography method is proposed and compared to other techniques to assess its performance.

ABSTRACT. This paper introduces the Next-Generation Network Intrusion Detection System (NG-NIDS) with intelligent capabilities based on the Artificial Neural Networks (ANN) and Machine Learning (ML) algorithms. The results have been achieved by training the model on a benign as well as malicious traffic. The proposed NG-NIDS achieved 99.9% accuracy of detecting the malicious traffic, which reflects the fact that this design is accurate and reliable.

ABSTRACT. Microfluidics represents a fascinating technological solution to conduct novel, reliable, reproducible, and massive biological experiments aimed at faster development of new drugs and vaccines and a greater understanding of the biological mechanisms underlying complex diseases [1,2]. The difficulty to extract and manage the amount of information available with this kind of device (often called Organ on Chip, OoC) however often precludes the wide potential offered. Then, we want to accelerate the uptake of microfluidics and lead to quantitative and reliable findings. One of the strengths of such systems is represented by the recently exploited synergy with sensors and machine learning, leading to a novel multidisciplinary discipline. This new branch comprises cell-culture and sample preparation, chip, and sensor design and implementation[3], time-lapse microscopy for optical acquisition [4], image analysis and machine learning for the extraction of synthetic descriptors from all the sensors, and the implementation of a mathematical model for automatic diagnostic, patient stratification, or personalized treatment[5-6]. In this talk, we will introduce the potentialities of the development and application of sensors and Machine Learning in the organ-on-chip platform through different case studies.

ABSTRACT. Acetone gas sensing find application in several fields such as biomedical applications, food industry, chemical manufacturing and environmental monitoring. Often, such applications requires good sensing performance and portability of the sensing devices. This paper proposes a conductometric gas sensor based on a thin-film of Nb2O5 able to detect acetone at the sub-ppm level with good selectivity and repeatability. The quite small dimensions and the low power consumption make the proposed sensor suitable for portable application.

ABSTRACT. A wearable, single-channel Brain-Computer Interface (BCI) based on Augmented Reality (AR) and Steady-State Visually Evoked Potentials (SSVEPs) for robot control is proposed as an innovative therapy for robot-based attention deficit hyperactivity disorder (ADHD) rehabilitation of children. The system manages to overcome the challenges regarding immersivity and wearability, providing a direct path between human brain and social robots, already successfully employed for ADHD treatment. Through the proposed system, even without training, the user can drive a robot, in real-time, by brain signals. A preliminary evaluation of the children adherence to the therapy was conducted as a case study on 18 subjects, at an accredited rehabilitation center. After investigating the children acceptance of the proposed system, different tasks were assigned to the volunteers aiming to observe their level of involvement. The experimental activity showed encouraging results, where almost all the participants were satisfied with the experience and keen to repeat it again in the future.

ABSTRACT. In recent years, sensors have seen a growing interest and a high development in terms of variety of application fields. Interesting biomedical applications use cooperative sensors to monitor the patients’ health status. Such set of cooperative sensors, sometimes equipping wearable or implantable devices, constitute the so called Biomedical Measurement Systems (BMS). In this context, the cooperation among sensors is possible only if they share a common sense of time and the synchronization accuracy is a key factor for the accuracy and the reliability of the monitoring. In this paper a consensus based algorithm to overcome two typical synchronization challenges are taken into account: the trade-off accuracy versus network lifetime and the degradation of the synchronization accuracy in the case a new sensor is added in the network.

ABSTRACT. In this work we present an electronic systems for the monitoring of dust in construction sites for the health of workers. A general presentation of the problem is first given in the paper. The battery powered systems is formed by a microcontroller and a commercial PM2,5 and PM10 commercial sensor. Preliminary measured results are presented and discussed showing the feasibility of the low cost monitoring system.

ABSTRACT. An accurate characterization of Gaussian stochastic electromagnetic (EM) fields can be achieved by auto- and cross correlation spectra. Multiple probes are required in a measurement setup for obtaining these correlation data. As the amount of data collected in such a measurement can be substantial, principal component analysis (PCA) can be utilized to reduce the complexity in the subsequent data processing and also for separating statistically independent sources. In cyclostationary problems, cycle frequencies need to be identified before formation of the correlation spectra. PCA is applied by an eigenvalue decomposition of the correlation matrix. Singular value decomposition of a Hankel matrix formed from the observed signal vector yields an identification of cycle frequencies.

ABSTRACT. We propose a methodology for extracting scattering parameters of optical interconnects comprised of dielectric slab waveguides. The proposed methodology is demonstrated by calculating the TE mode attenuation and phase delay of an example dielectric slab in 2D FDTD. Results show good correlation between the proposed FDTD-based methodology and analytic solutions. Work is currently under way to extend the proposed methodology to dielectric waveguides exhibiting stochastic surface roughness.

ABSTRACT. The paper analyzed the benefits obtained in the reverberation chamber performance when proper diffractors and tilted walls are added to the geometry. By destroying the regularity of the boundary conditions the chaoticity of the electromagnetic field is enhanced. A home made FDTD code, running on supercomputers, is adopted to compute the field inside the RC and for its statistical analysis. Performance indicators such as the field uniformity, the independent chamber state number, are improved in a chaotic RC. The narrowband uncorrelation drops, typical in non-chaotic RCs, are strongly mitigated.

ABSTRACT. In this paper, authors demonstrate different wave digital frameworks of branch-line couplers with three parallel lines. A novel model for analyzing complex multi-port structure through generalizing the wave digital approach, which is extensively applied for modeling the performance of different physical systems, is presented. The authors propose transmission line model versus earlier presented equivalent lumped circuit model, and demonstrate comprehensive analysis results. 

ABSTRACT. Satellite systems have been offering global and regional connectivity and IP access largely through Geostationary (GEO) space-based network platforms. Past few years, however, have witnessed an exponential growth in the satellite deployments with the traditional players and several new entrants developing and deploying multiple high throughput GEO, Low Earth Orbit (LEO) and Medium Earth Orbit (MEO) satellite systems. This wider and renewed interest in satellite systems is largely due to exponential growth in data traffic, M2M (Machine-to-Machine) communications, and emerging Internet of Things (IoT)/ 5G applications using advanced satellite systems and technologies.Rapid convergence between space based and terrestrial networks with flexible, on-demand data transfers between satellite and terrestrial network nodes is an emerging trend in telecom networks. This presentation will focus on market and system drivers in the evolution of space based fixed (FSS) and mobile (MSS) satellite services. System and technologies trends resulting in major capacity enhancements with frequency reuse, flexible signal routings , use of very narrow spot beams in the space-based satellite networks will be presented.

ABSTRACT. This paper describes Software Defined Radio (SDR) developments using an Ettus Research [1] Universal Software Radio Peripheral (USRP). This work follows the development of the GNU Radio Companion (GRC) to construct a transceiver for Direct Spread Spectrum communication. This transceiver is a component of a low-cost satellite modem being developed for Two-Way Satellite Time and Frequency Transfer (TWSTFT) [2] and ranging measurement experiments. Features that distinguish the GRC are described, and performance indicators provided.

ABSTRACT. In this paper we investigate whether application of an optimal pair-wise semi-orthogonal user selection (SUS) algorithm can provide throughput performance improvement in multiuser multiple-input multiple-output (MU-MIMO) system using block diagonalization (BD) at the transmit side and zero forcing (ZF) at the receive side. Presented simulation results are compared with results for the same designed MU-MIMO system applying multicarrier weighted capacity-based SUS algorithm.

ABSTRACT. In this paper, we discuss a hybrid communication system for transmitting information between end users which are located indoors. The transmission is conveyed through visible light communication (VLC) links and a power line communication (PLC) link connected via decode-and-forward relays. The performance of this three-hop hybrid system is analysed in term of average bit error rate (BER) and the impact of VLC and PLC channel parameters is investigated. In more details, the influence of light emitting diode lamp position (height, radiation angle), influence of the average signal-to-noise ratios from all links and fading presence on the average BER is considered.

ABSTRACT. Modern modulation schemes generate signals with high Peak to Average Power Ratio (PAPR). In order to achieve compliance of telecommunication infrastructure to standard specifications, enable distortion-free and energy-efficient operation of radio frequency (RF) power amplifiers (PA), the PAPR value of transmitted signals has to be reduced. We propose Peak Windowing (PW) as a method for PAPR reduction. The method is additionally improved to accommodate different Long-Term Evolution (LTE) signal bandwidths. The improvement is based on utilization of additional low-pass filter and also on signal interpolation. For large waveform bandwidths the data rate of signals entering the PAPR processing block is doubled. The method is validated using 5MHz, 10MHz, 15MHz and 20MHz LTE E-TM 3.1 test waveforms after it has been implemented in Software Defined Radio (SDR) board. In all these cases, we measured PAPR=8dB, EVM=2.0%, ACPR -52dBc at transmitter output.

ABSTRACT. 5G new radio (NR) represents the newest standard for mobile communications. It introduced LDPC channel coding which enables increased spectral efficiency in comparison to turbo codes used in LTE. It also specifies throughputs in the order of tens of Gb/s at lower latencies, putting a challenging constraint on all components in the data chain. In this paper, a parallel high throughput architecture of a joint deinterleaver and de-rate matcher for 5G NR is proposed. Efficient and scalable nature of the architecture allows easy tuning of throughput versus utilization over a large range of values. Proposed scheme for LLR value storage enables efficient memory utilization with full read and write throughput. The proposed architecture was implemented on a Zynq Ultrascale+ RFSoC FPGA from Xilinx in order to verify the functionality. Implementation achieves clock frequency close to the highest possible on the given architecture. To the best of our knowledge, this is currently the highest throughput implementation available.

ABSTRACT. In this work, we have designed a UV-LED with multiple-quantum-well of GaN/AlGaN to witness the effect of spontaneous polarization on its output characteristics and it shows some promising results. Using Silvaco TCAD it is observed that the influence of spontaneous polarization helps in improving the optical performance of the device. The built-in electric field induced by spontaneous polarization is considered at hetero-interfaces of GaN LED, which has a significant influence on its output power behavior. The simulation results suggest that the optical power in presence of spontaneous polarization is significantly greater than that compared to conventional LED; it is carried out at a temperature of 300 K. The output current, charge concentration, and the normalized power spectral densities for both cases are discussed in this paper.

ABSTRACT. The electrical conductivity, phase, and space group of property of the NMT substance, and grain boundary of samples were approximated from complex compound by Raman spectroscopy, X-ray, SEM, TEM and differential scanning calorimeter (DSC). Samples were prepared and analyzed in the laboratory in the frequency ranges from at room temperature. The powder ceramic was synthesized using the solid-state conventional method. Powder X-ray diffraction of all the samples are tested from to by increasing 50 degrees for every sample and cooling to the room temperature. The shrinkage of grains and grain boundaries impact did not happen even when temperature was very high. Increase Nd+ ion polarizability is compared to La+ rare elements material, which is 0.60, which contributes to change of perovskite cubic. This is the result of the smaller size of Nd+ cation compared to La+ which increases number of dipoles despite the reduction of dipoles and expands relative permittivity ( ). The single-phase material was produced, which shows quality factor which saturated at and temperature coefficient of .

ABSTRACT. The microstructures properties predicting are based on their materials characteristics. In ceramic materials, regarding higher miniaturization and integrations, the structure analysis is very important. The main contribution of this research is related to relation between perovscites ceramics electronic properties, especially BaTiO3 and NZT-ceramics and structural characteristics. We applied advanced analysis, based on fractal nature and introduced complex fractal correction in defining the very important electromagnetic parameter inductivity (L). The samples consolidation includes both, powder pressing (cold sintering) and hot sintering. The fractal characterization performs very important role from powders up to the final structures, through which exists structure influence on electro-physical and other ceramic properties. We report the experimental results of BaTiO3 and NZT-ceramics processing. Also, this is the first time that we apply complex fractal correction (influence of grains and pore surface and as well as particles Brownian motion) on fundamental thermodynamic temperature in Currie-Weiss law. This application includes the influence of Housdorff dimension (DH) from the microstructure images and connect fractal corrections in Currie-Weiss law, for relative dielectric constant ϵr and magnetic permeability μr. Through ϵr and μr, on this way, for the first time in this scientific area, we present direct relation to inductivity. This complex relation opens quit new advance understanding in structures and parameters in area of ferroelectic-magnetic applications in telecommunications, by introducing the fractals.

ABSTRACT. This paper presents one possible solution for building the propagation time extraction tool. Developed tool may help engineers to extract necessary parameters for the system level modeling of the propagation time when the integrated circuit, static CMOS, implementation is intended. Proposed Electronic Design Automation (EDA) solution is built using the free/open-source software which ensures zero cost and high flexibility. Two known concepts for extracting key parameters of propagation time model are presented. The set of parametric simulations has been performed in order to cross-compare presented concepts using the developed EDA tool.

ABSTRACT. In this paper, an algorithm for designing and estimating the cost-effectivectiveness of a medium size grid-on photovoltaic power plant by using program PVsyst is given. The considered photovoltaic power plant is planned for installation on the roof of the existing business facility. The program first defines the type of PV system, the location where the power plant will be built, meteorological database and orientation of PV modules. Then the components of the PV system as well as its configuration are defined. Finally, the obtained simulation results were analyzed and it was concluded that the investment in the construction of this power plant would be completely justified and profitable.

ABSTRACT. The main goal of this paper is to examine the possibility of using the 32-bit fixed-point format to represent the weights of neural networks (NN) instead of the standardly used 32-bit floating-point format in order to reduce the complexity of NN implementation. To this end, the performance of the 32-bit fixed-point format is analyzed, using an analogy between the fixed-point format and the uniform quantization that allows for the performance of the 32-bit fixed-point format to be expressed by an objective measure SQNR (Signal-to-Quantization Noise Ratio). In doing so, SQNR analysis is performed in a wide range of variance of NN weights, looking for a solution that maximizes the average SQNR in that range of variance. Also, an experiment is performed, applying the 32-bit fixed-point format to represent the weights of an MLP (Multilayer Perceptron) neural network trained for classification purposes. It is shown that the application of the 32-bit fixed-point representation of MLP weights achieves the same classification accuracy as in the case of the 32-bit floating-point representation of MLP weights, proving that the application of the 32-bit fixed-point representation of weights reduces the implementation complexity of neural networks without compromising the accuracy of classification.

ABSTRACT. The article deals with the problem of masking hidden messages under natural noise in highly undetectable stegosystems ±1HUGO and ⊕HUGO. According to the Arnold cat map algorithm, a preliminary discrete chaotic transformation of the hidden message is performed to ensure high resistance of stegosystems from hacking. Further, in their research, the authors effectively apply noise-tolerant coding for the covering object and stego using a self-orthogonal code. The model of a binary synchronous communication channel with interference is used to model the data transmission channel. The article also presents simulation modeling results, confirming the high resistance of the proposed stegosystems to hacking.

ABSTRACT. One of the most used approaches for application of deep learning on audio signals is to use spectrogram-based images as an input to a neural network. There are various spectrogram-based images including mel-spectrogram representing an option often used in practice. In such as case, it is worth knowing what are the intra-class and inter-class differences of the input images. These differences are studied here by analyzing the Pearson's correlation coefficient. They are calculated from the mel-spectrograms extracted from the audio signals containing sounds of DC motors. The recorded signals are classified into 8 classes used separately for intra-class difference, while specific pairs of classes are grouped into 12 binary sets of classes used for inter-class difference analysis.

ABSTRACT. In this paper, time series data forecasting was done by using a seasonal autoregressive integrated moving average (SARIMA) model in XLSTAT add-on for Excel and in MATLAB environment, as well as an artificial neural network (ANN) model. A long short-term memory (LSTM) network was used to construct the ANN model. Both approaches were used for forecasting the volume of express mail services (EMS) in international traffic in the Republic of Serbia and the obtained results were compared with the original data. Significantly better modelling results were obtained by using ANN approach.

ABSTRACT. This paper proposes a new VLSI algorithm for a inverse discrete cosine transform (IDCT) designed for an efficient implementation of obfuscation technique. The proposed algorithm is using quasi-circular correlation structures and is highly regular and modular, presents a low hardware complexity, a high throughput and it can be mapped using a low number of I/O channels and that requires a low bandwidth on linear systolic arrays and using the time-varying obfuscation method, it presents the additional advantage in the field of hardware security and, it can be efficiently implemented on a VLSI chip with a low power complexity due to its low hardware complexity and the fact that most of the parts of the architecture are working at a significantly lower frequency than the main systolic array.