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The employment of technology and digitization is crucial for cultural organizations to establish and sustain digital repositories for their cultural heritage artifacts. This exploitation is also essential in facilitating the presentation of cultural works and exhibits to a broader audience. Consequently, in this work, we propose a custom-developed digital repository that functions as software-as-a-service (SaaS), primarily promoting the safe storage, display, and sharing of cultural materials; enhancing accessibility; and fostering a deeper understanding and appreciation of cultural heritage. The proposed digital repository service is designed as a multitenant architecture, which enables organizations to expand their reach, enhance accessibility, foster collaboration, and ensure the preservation of their content. Moreover, our technology stack incorporates robust and reliable backend technologies, such as Django, to ensure data security and efficient management. Meanwhile, the frontend is powered by Angular, which guarantees a user-friendly and engaging interface for exploring and interacting with cultural materials. Specifically, this project aims to assist each cultural institution in organizing its digital cultural assets into collections and feeding other digital platforms, including educational, museum, pedagogical, and games, through appropriate interfaces. The creation of this digital repository offers a cutting-edge and effective open-access laboratory solution. It allows organizations to have a significant influence on their audiences by fostering cultural understanding and appreciation. Additionally, it facilitates the connection between different digital repositories and national/European aggregators, promoting collaboration and information sharing. By embracing this innovative solution, cultural institutions can benefit from shared resources and features, such as system updates, backup and recovery services, and data analytics tools, attributes that are currently provided by the platform. [ABSTRACT FROM AUTHOR]

This paper presents an extensive path loss measurement campaign carried out in rural areas at 3.7 GHz, including line-of-sight (LOS) and non-LOS conditions. For this purpose, a commercially established fixed wireless access (FWA) network is exploited, operating with time-division long term evolution configuration. Furthermore, various models are examined and validated regarding their ability to predict accurately the path loss. The results reveal that the standard propagation model (SPM) achieves the best performance, thus being an attractive option for planning rural FWA links. The WINNER II and 3GPP/ITU-R models exhibit very good performance, as well. From the statistical assessment, the shadow fading follows the Lognormal distribution with a standard between 4.6 and 5.4 dB. An almost excellent fit is obtained regardless of the diverse propagation conditions in the specific area. Finally, from the model evaluation was concluded that SPM is highly recommended as the best option for a precise network dimensioning and planning. [ABSTRACT FROM AUTHOR]

This paper presents an integrated system for emotion detection. In this research effort, we have taken into account the fact that emotions are most widely represented with eye and mouth expressions. The proposed system uses color images and it is consisted of three modules. The first module implements skin detection, using Markov random fields models for image segmentation and skin detection. A set of several colored images with human faces have been considered as the training set. A second module is responsible for eye and mouth detection and extraction. The specific module uses the HLV color space of the specified eye and mouth region. The third module detects the emotions pictured in the eyes and mouth, using edge detection and measuring the gradient of eyes’ and mouth’s region figure. The paper provides results from the system application, along with proposals for further research. [ABSTRACT FROM AUTHOR]

The present paper studies the prospective and the performance of a forthcoming high-speed third generation (3.5G) networking technology, called enhanced uplink, for delivering mobile health (m-health) applications. The performance of 3.5G networks is a critical factor for successful development of m-health services perceived by end users. In this paper, we propose a methodology for performance assessment based on the joint uplink transmission of voice, real-time video, biological data (such as electrocardiogram, vital signals, and heart sounds), and healthcare records file transfer. Various scenarios were concerned in terms of real-time, nonreal-time, and emergency applications in random locations, where no other system but 3.5G is available. The accomplishment of quality of service (QoS) was explored through a step-by-step improvement of enhanced uplink system's parameters, attributing the network system for the best performance in the context of the desired m-health services. [ABSTRACT FROM AUTHOR]

Two-way satellite broadband communication technologies, such as the Digital Video Broadcasting with Return Channel via Satellite (DVB-RCS) technology, endeavour to offer attractive wide-area broadband connectivity for telemedicine applications, taking into consideration the available data rates, Quality of Service (QoS) provision, survivability, flexibility and operational costs, even in remote areas and isolated regions where the terrestrial technologies suffer. This paper describes a wide-area tele-medicine platform, specially suited for homecare services, based on the DVB-RCS and Wi-Fi communication technologies. The presented platform combines medical data acquisition and transfer, patient remote monitoring and teleconference services. Possible operational scenarios concerning this platform and experimental results regarding tele-monitoring, videoconference and medical data transfer are also provided and discussed in the paper. [ABSTRACT FROM AUTHOR]

The investigation of spectrum overlay of a Spread Spectrum system on the existing narrowband FM broadcasting system is presented. The overlaid Spread Spectrum (SS) system is assumed to utilize direct sequence (DS) spreading, using maximal length pseudorandom sequences. We studied the performance degradation of the analog FM system due to the interference produced by the SS signal, through laboratory subjective and objective measurements, for various types of spreading scenarios and for different carrier frequency differences (δf). The RF protection ratios for the FM receivers are derived, along with SINAD measurements. Finally, these experimental results have been compared with the theoretical study of the FM receiver's audio frequency SNR output due to SS interference. [ABSTRACT FROM AUTHOR]

This paper presents and assesses various machine learning methods that aim at predicting path loss in rural environment. For this purpose, models such as artificial neural network (ANN), support vector regression (SVR), random forest (RF), and bagging with k-nearest neighbor (B-kNN) learners, are exploited and evaluated. They are trained and tested with path loss data collected from an extensive measurement campaign that have been carried out in diverse rural areas in Greece. The results demonstrate that all the proposed machine learning models outperform the empirical ones, exhibiting, in any case, root-mean-square-error (RMSE) values between 4.0 and 6.5 dB. The poorest prediction of the measured data is encountered for SVR with Polynomial kernel. Furthermore, B-kNN and RF algorithms preserve comparable path loss approximations with remarkably low RMSE on the order of 4.2–4.3 dB. The error metrics also reveal that increasing the number of hidden layers in ANNs, their performance is gradually enhanced. However, deeper layouts with more than three hidden layers do not markedly improve any further the prediction accuracy. Finally, the best prediction is achieved when employing a three-hidden layered ANN with 51 neurons evenly distributed among the layers. The specific layout exhibits the lowest RMSE value (4.0 dB), thus being highly recommended for accurate path loss predictions in rural locations. [ABSTRACT FROM AUTHOR]

This paper proposes the integration of non-orthogonal multiple access (NOMA) and broadcasting with buffer-aided (BA) full-duplex (FD) relaying to improve the spectral efficiency of a single-source two-user network. Furthermore, opportunistic relay selection is employed, activating one or two FD relays to support the end-to-end communication. The network performance is improved through buffers, allowing to switch to half-duplex (HD) transmission/reception when FD operation is not feasible. A hybrid BA FD/HD NOMA relay selection algorithm is proposed, herein called $\mathop {\mathrm{BAHyNOMA}}$ , orchestrating the three aforementioned techniques, towards a simple yet efficient and robust relay selection. $\mathop {\mathrm{BAHyNOMA}}$ is evaluated in terms of outage probability, average sum-rate and average delay, and it is observed that the average sum-rate can be doubled, while maintaining low latency. [ABSTRACT FROM AUTHOR]

This study presents building entry loss and capacity results obtained from an unmanned aerial vehicle (UAV)-toindoor narrowband dual-polarised multiple-input-multiple-output (MIMO) channel measurement campaign. Six different measurement scenarios were carried out with the transmitter (Tx) located on a low altitude platform (LAP) and the receiver (Rx) at various floors and distances from the external windows of a multi-storey building. An analytic and simple procedure is proposed for the calculation of entry loss. The results reveal that there is a strong dependence on the propagation geometry and the orientation of the receiver with respect to the moving LAP transmitter. The processed data for both entry loss and capacity indicate a two-state process that is closely related to the Tx-Rx relative azimuth and elevation angle. The average entry loss levels vary from 33 to 50 dB. The overall ergodic capacity varies between 3.1 and 4.1 b/s/Hz with insignificant variations with the floor level and the distance from the window. Finally, the K-factor of the channel lies below 6 dB tending to decrease with higher elevation angles. [ABSTRACT FROM AUTHOR]

In networks with multiple wireless nodes and especially in fast changing environments, the continuous acquisition of channel state information (CSI) may become infeasible. In this correspondence paper, we study the relay selection problem for a cooperative network, where full-duplex relays are equipped with buffers and only statistical CSI is available at the transmitters (CSIT). For this setting, a novel relay selection algorithm is proposed, named $\mathop {\mathrm{HyQoS}}$ , relying only on statistical CSIT and performing power adaptation. $\mathop {\mathrm{HyQoS}}$ solves an optimization problem for selecting the optimal set of relays. We consider two optimization approaches, first, minimization of the total power consumed in the network, and, second, maximization of the throughput per energy unit, while guaranteeing a specific quality of service, in terms of successful transmission probability. The power allocation problem is formulated as a nonlinear optimization one, taking into account inter-relay interference and residual loop interference. Numerical results show that $\mathop {\mathrm{HyQoS}}$ can reduce the power expenditure and increase the throughput, by using only statistical CSIT. [ABSTRACT FROM AUTHOR]

Buffer-aided relays can improve the diversity of multi-hop networks, however, they increase packet delays. Thus, various delay-aware protocols have been developed, but without considering the transmission diversity. Moreover, most works adopt ideal assumptions, such as symmetric links, perfect channel state information (CSI), and error-free feedback channels. So, we propose a low-complexity (LoCo) link selection algorithm, herein called $\mathop {\mathrm {LoCo\!\!-\!\!Link}}$. The proposed algorithm may experience delays during CSI updates, and hence, by using outdated CSI its performance may deteriorate. To alleviate this issue, we next propose a distributed version of $\mathop {\mathrm {LoCo\!\!-\!\!Link}}$ ($\mathop {\mathrm {d\!\!-\!\!LoCo\!\!-\!\!Link}}$) dealing with outdated CSI. In both algorithms, the source performs broadcasting toward multiple relays; when the packets are transmitted by a relay to the destination, they are discarded from all other relays. This coordination relies on feedback channels. For non error-free feedback channels, we propose a scheme in which the relays listen to the transmission of the best relay and drop duplicate packets. Results show that $\mathop {\mathrm {LoCo\!\!-\!\!Link}}$ surpasses other algorithms, by decreasing the delay in asymmetric networks. Moreover, $\mathop {\mathrm {d\!\!-\!\!LoCo\!\!-\!\!Link}}$ avoids diversity losses due to outdated CSI, while the effect of non error-free feedback channels is mitigated by taking advantage of the inter-relay channels. [ABSTRACT FROM AUTHOR]

The cooperative aerial and device-to-device (D2D) networks employing non-orthogonal multiple access (NOMA) are expected to play an essential role in next-generation wireless networks. Moreover, machine learning (ML) techniques, such as artificial neural networks (ANN), can significantly enhance network performance and efficiency in fifth-generation (5G) wireless networks and beyond. This paper studies an ANN-based unmanned aerial vehicle (UAV) placement scheme to enhance an integrated UAV-D2D NOMA cooperative network.The proposed placement scheme selection (PSS) method for integrating the UAV into the cooperative network combines supervised and unsupervised ML techniques. Specifically, a supervised classification approach is employed utilizing a two-hidden layered ANN with 63 neurons evenly distributed among the layers. The output class of the ANN is utilized to determine the appropriate unsupervised learning method—either k-means or k-medoids—to be employed. This specific ANN layout has been observed to exhibit an accuracy of 94.12%, the highest accuracy among the ANN models evaluated, making it highly recommended for accurate PSS predictions in urban locations. Furthermore, the proposed cooperative scheme allows pairs of users to be simultaneously served through NOMA from the UAV, which acts as an aerial base station. At the same time, the D2D cooperative transmission for each NOMA pair is activated to improve the overall communication quality. Comparisons with conventional orthogonal multiple access (OMA) and alternative unsupervised machine-learning based-UAV-D2D NOMA cooperative networks show that significant sum rate and spectral efficiency gains can be harvested through the proposed method under varying D2D bandwidth allocations. [ABSTRACT FROM AUTHOR]

In this paper, an airborne multi-user (MU) multiple-input multiple-output (MIMO) communication system is investigated, consisting of multiple users sources, multiple users destinations, and an aerial platform acting as a decode-and-forward (DF) relay. In this context, a novel three-dimensional (3-D) geometry-based optimization method for the relay location is proposed and expressions for the outage probability are presented. The results highlight the impact of the relay position, power allocation, fading severity, and number of antennas on the system performance. [ABSTRACT FROM AUTHOR]

Multicast-Broadcast over Single Frequency Network (MBSFN) technology, as introduced by the Long Term Evolution Advanced group, is expected to be part of the upcoming cellular systems offering resource efficiency to broadcast services. MBSFN transmission is suitable to serve multicast groups searching the same content. In addition, the fast emerging technology of femtocells networks and their hybrid nature can lead to efficient resource sharing between non-subscribed users when located inside their coverage. The focus of this manuscript is 2-fold; firstly, we have contacted simulation experiments to compare the MBSFN transmission with the traditional Point-To-Point transmission for various femtocell distributions and network topology changes; secondly, a novel multicast transmissions mechanism is proposed from non-subscribed users who exploit femtocells resources for broadcast services, without limiting user's data requirements. The simulation results lead to a significant system's performance in terms of average throughput, total capacity, and energy consumption. [ABSTRACT FROM AUTHOR]

In this paper, we present a relay selection scheme which combines the spectral efficiency of successive opportunistic relaying with the robustness of single-link relay selection. More specifically, we propose a scheme that minimizes the total energy expenditure per time slot under an inter-relay interference cancellation scheme. The new relay selection policy is analyzed in terms of outage probability and diversity by modeling the evolution of relay buffers as a Markov Chain. We construct the state transition matrix of the Markov Chain and obtain its stationary distribution, which in turn, yields the outage probability. The proposed scheme outperforms relevant state-of-the-art relay selection schemes in terms of throughput, diversity, energy efficiency and average delay, as demonstrated via representative numerical examples. [ABSTRACT FROM PUBLISHER]

Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless communication networks. Their adoption in various communication-based applications is expected to improve coverage and spectral efficiency, as compared to traditional ground-based solutions. However, this new degree of freedom that will be included in the network will also add new challenges. In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes. In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such as channel modeling, resource management, positioning, and security. [ABSTRACT FROM AUTHOR]