Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Fusion-Based Policy Search for Fast Robot Locomotion Learning

Deep reinforcement learning methods are developed to deal with challenging locomotion control problems in a robotics domain and can achieve significant performance improvement over conventional control methods. One of their appealing advantages is model-free. In other words, agents learn a control policy completely from scratches with raw high-dimensional sensory observations. However, they often suffer from poor sample-efficiency and instability issues, which make them inapplicable to many engineering systems. This paper presents a distributed fusion-based policy search framework to accelerate robot locomotion learning processes through variance reduction and asynchronous exploration approaches. An adaptive fusion-based variance reduction technique is introduced to improve sample-efficiency. A parametric noise is added to neural network weights, which leads to efficient exploration and ensures consistency in actions. Subsequently, the fusion-based policy gradient estimator is extended to a distributed decoupled actor-critic architecture. This allows the central estimator to handle off-policy data from different actors asynchronously, which fully utilizes CPUs and GPUs to maximize data throughput. The aim of this work is to improve sample-efficiency and convergence speed of deep reinforcement learning in robot locomotion tasks. Simulation results are presented to verify the theoretical results, which show that the proposed algorithm achieves and sometimes surpasses the state-of-theart performance.
Comparison of Optical Frequency Comb and Sapphire Loaded Cavity Microwave Oscillators

The single-sideband phase noise power spectral density and Allan deviation of a portable microwave oscillator system based on an optical frequency comb stabilized to an ultra-low expansion Fabry-Perot reference cavity is characterized at carrier frequencies of 4.0, 8.0, and 16.0 GHz. Compared to industry standard sapphire loaded cavity oscillators, the photonic microwave oscillator shows superior phase noise at offset frequencies < 100 Hz, and similar performance for offset frequencies from 100 Hz to 100 kHz. At 1-kHz offset, the phase noise power spectral density is better than −140 dBc/Hz at each carrier frequency. Relative frequency stability of $3.0 \times 10^{-14}$ obtains at an averaging time of 400 ms.
Interledger Approaches

While blockchains and more generally distributed ledger technologies (DLTs) are passing over their hype curve peak, their shortcomings are becoming more apparent. One relatively recent approach to address their performance, scalability, privacy, and other problems are to use multiple different DLTs instead of relying on just one. While there are no really established standards for combining several DLTs, a few repeating patterns can be observed. In this paper, we present a survey of interledger approaches, discussing and comparing their underlying mechanisms. A shared motivation for all of the discussed interledger solutions is to move away from the “one chain rules them all” model to one that allows the interconnection of multiple ledgers, with different features and advantages, while also supporting innovation. The interledger approaches discussed in this survey include 1) atomic cross-chain transactions, 2) transactions across a network of payment channels, 3) the W3C Interledger Protocol (ILP), 4) bridging, 5) sidechains, and 6) ledger-of-ledgers. The approaches are compared according to whether they support the transfer or the exchange of value, their interconnection trust mechanism, complexity, scalability, and transaction cost.
Miniaturized Spoof Surface Plasmon Polaritons Low-Pass Filter With a Novel Transition Structure

In this letter, a miniaturized spoof surface plasmon polaritons (SSPPs) low-pass filter with a novel transition structure is proposed. The novel transition structure is designed by two rectangular strips with an inclination of 17° and right-angled triangle patches. In this letter, we analyzed the normal and azimuthal components of the electric field perpendicular to the plane of the filter at different locations, verifying the effectiveness of the transitional structure. Besides, efficient conversion between quasi-transverse electromagnetic (TEM) waves and transverse magnetic (TM) polarized SSPPs waves are achieved by loading the novel transition structures. The designed filter can suppress unnecessary radiation loss and increase transmission efficiency. More importantly, the filter size is 47.52 mm $\times7.47$ mm and its length is reduced by at least 61% compared with the other low-pass filters with the same cutoff frequency. This letter has promoted the development and application of SSPPs low-pass filter and related equipment in microwave frequencies.
A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation

Kinematic calibration of manipulators is an efficient and fundamental way to ensure reliability and high performance of robots. Research on kinematic calibration has a long tradition, and a common strategy used for calibration is to guarantee the least errors in the sense of root-mean-square deviation. However, the absolute positioning accuracy is determined by the maximum error of manipulators, and it is a key indicator for evaluating performance. For example, using manipulators to print machine elements, obviously where the error is the most, may likely cause inaccurate fit. Hence, it is crucial to study a robust calibration strategy. Considering the calibration problem, both positioning and orientation accuracy are ensured by minimizing the maximum positioning errors of three spherical mounted retro-reflectors (SMRs) on the end effector of manipulators. Unfortunately, traditional optimization methods based on gradient cannot be directly employed to solve the minimax problem. Due to the recent progress on optimization, researchers found that the minimax can be transformed into sequence quadratic programming problems under inequality conditions, thus providing solutions for solving the robust calibration. This paper applied this method to convert the calibration problem into constrained quadratic subproblems, and the subproblems can be solved through the primal-dual subgradient method. Then, convexity and robustness analysis is given to prove that these subproblems can quickly converge to a local minimum. Finally, to verify the validity of the proposed algorithm, the experiments are conducted on an IRB 2600 manipulator, and the results show that, with the minimax search algorithm, both the positioning and orientation accuracy is enhanced by 67.34% and 73.14%, respectively, which is significantly higher than the performance of the single-SMR calibration algorithm widely used in the field of industry.
An Optimized Spatially Cooperative Caching Strategy for Heterogeneous Caching Network

Heterogeneous caching network consisting of edge servers and caching helpers is proposed to meet the huge amount of mobile traffic and provide low-latency caching services for users. The problem of caching redundancy caused by the overlapping of edge servers and caching helpers is neglected by most researchers. In this paper, we propose a spatially cooperative caching strategy to avoid the caching redundancy and improve the hit probability of the heterogeneous caching network. We analyze the performance of this caching strategy by using stochastic geometry, derive the optimal caching probability and make a comparison with available caching strategies. The numerical results show that, the proposed caching strategy has a better performance under the normal parameter settings.
Long-Term Prediction of Significant Wave Height Based on SARIMA Model in the South China Sea and Adjacent Waters

Nowadays, the world is facing the dual crisis of the energy and environment, and renewable energy, such as wave energy, can contribute to the improvement of the energy structure of the world, enhance energy supply and improve the environment in the framework of sustainable development. Long-term prediction of the significant wave height (SWH) is indispensable in SWH-related engineering studies and is exceedingly important in the assessment of wave energy in the future. In this paper, the spatial and temporal characteristics of wave energy in the South China Sea (SCS), and adjacent waters are analyzed. The results show that there are abundant wave energy resources in the waters around the Taiwan Strait, the Luzon Strait, and the north part of the SCS with annual average SWH (SWH) of over 1.4 m and obvious increasing trend. Then, the SARIMA approach considers the relationship between the current time and the values, residuals at some previous time and the periodicity of the SWH series are proposed to forecast the SWH in the SCS and adjacent waters. The results obtained are promising, showing good performance of the prediction of monthly average SWH in the SCS and adjacent waters.
Sub-Femtojoule Hybrid Plasmonic Optical Modulator

A highly compact optical modulator is proposed and analyzed. The modulator is based on the hybrid plasmonic waveguide platform. The structure of the modulator is built from silicon, silver, and electro-optical polymer layers. Hybrid plasmonic modes of symmetric and asymmetric natures excited in the structure were investigated. The symmetric mode is characterized by its lower propagation loss, so it was selected for the excitation of the device. The modulator's operation mechanism is based on the racetrack resonator configuration. Full three-dimensional electromagnetic analysis was performed around the 1.55-μm telecommunication wavelength. Different parameters such as the power coupling to the bus waveguide, the bend loss, the propagation loss, and the Q-factor of the resonances were studied in order to optimize the racetrack resonator design. The modulator is characterized by its extremely low energy consumption of 0.5 fJ/bit, high modulation depth of 10.5 dB, while the insertion losses were limited to 0.5 dB.
Cellular IoT Traffic Characterization and Evolution

The adoption of Internet of Things (IoT) technologies is increasing and thus IoT is seemingly shifting from hype to reality. However, the actual use of IoT over significant timescales has not been empirically analyzed. In other words the reality remains unexplored. Furthermore, despite the variety of IoT verticals, the use of IoT across vertical industries has not been compared. This paper uses a two-year IoT dataset from a major Finnish mobile network operator to investigate different aspects of cellular IoT traffic including temporal evolution and the use of IoT devices across industries. We present a variety of novel findings. For example, our results show that IoT traffic volume per device increased three-fold over the last two years. Additionally, we illustrate diversity in IoT usage among different industries with orders of magnitude differences in traffic volume and device mobility. Though we also note that the daily traffic patterns of all devices can be clustered into only three patterns, differing mainly in the presence and timing of a peak hour. Finally, we illustrate that the share of LTE-enabled IoT devices has remained low at around 2% and 30% of IoT devices are still 2G only.
Near-Field Monopulse DoA Estimation for Angle-Sensitive Proximity WiFi Readers

We study the effect of close-proximity in the estimation of the Direction-of-Arrival (DoA) using a monopulse antenna array system, with application to angle-sensitive proximity WiFi readers. It is shown that in this scenario, it is necessary to consider near-field radiative effects to make an accurate angular estimation at short distances between the mobile terminal and the DoA proximity sensor. As a result, we define a range-dependent angular monopulse function, which provides a better DoA estimation in a Field of View of 60° and for distances ranging from 3 m to 50 cm.
On the Reliability Function of Distributed Hypothesis Testing Under Optimal Detection

The distributed hypothesis testing problem with full side-information is studied. The trade-off (reliability function) between the two types of error exponents under limited rate is studied in the following way. First, the problem is reduced to the problem of determining the reliability function of channel codes designed for detection (in analogy to a similar result which connects the reliability function of distributed lossless compression and ordinary channel codes). Second, a single-letter random-coding bound based on a hierarchical ensemble, as well as a single-letter expurgated bound, are derived for the reliability of channel-detection codes. Both bounds are derived for a system which employs the optimal detection rule. We conjecture that the resulting random-coding bound is ensemble-tight, and consequently optimal within the class of quantization-and-binning schemes.
Evaluating the predictions of three syntactic frameworks for mixed determiner–noun constructions

Abstract This paper presents a comparative evaluation of three linguistic frameworks, the Minimalist Programme (MP), Word Grammar (WG) and the Matrix Language Frame Model (MLF), regarding their predictions of possible combinations in a corpus of 187 German–English code-switched (CS) determiner–noun constructions. The comparison revealed a significant difference in the accuracy of the predictions between the MP and WG, but not between the other frameworks. We draw attention to the fact that while WG and MP deal with the processes of feature agreement between determiner and noun, the MLF is concerned with a broader notion of agreement in language membership. We suggest that advances in our understanding of grammaticality in code-switching will be achieved by combining the insights of all three frameworks instead of considering them in isolation.
Evaluating QoS in SDN-Based EPC: A Comparative Analysis

Software Defined Networking (SDN) is an emerging paradigm in networking and of high interest to the mobile network operators due to its potential benefit in improving network performance. The idea of integrating SDN in mobile network architecture, such as in LTE-evolved packet core (EPC), has already been proposed by many researchers. The SDN-based EPC network offers better Quality of Service (QoS) which is critical to the successful delivery of real-time multimedia applications in the mobile operator networks. In this paper, we provide state-of-the-art work to evaluate and analyze the QoS metrics in real-time services. We conduct a comprehensive comparison between the performance of EPC and SDN-based EPC regarding latency, jitter, and packet loss. We inject active probe packets in the networks to collect statistical data about the metrics. Various levels of workload are applied to test the robustness and stability of both EPC and SDN-based EPC designs. Our results show that SDN-based EPC significantly outperforms its legacy counterpart in all three QoS metrics. To the best of our knowledge, our study is the first comparative analysis that evaluates QoS in EPC and SDN-based EPC for real-time applications.
Energy Efficiency Analysis of FeICIC in Dense Heterogeneous Networks

Although almost blank subframes (ABS) proposed in heterogeneous networks (HetNet) can enhance the performance of user equipments (UEs) in Pico-cell range expansion (CRE) area, it also significantly degrades the Macro-cell throughput. To address this issue, further-enhanced inter-cell interference coordination (FeICIC) scheme is considered in 3GPP Release 11, where low power ABS (LP-ABS) are adopted for the Macro-cell center region users to improve the Macro-cell throughput. However, LP-ABS power, Pico CRE bias and Pico base station (PBS) density will jointly affect on the system performance, which eventually deteriorates the network energy efficiency (EE) without careful configuration. In this paper, we first deduce the closed-form expression of network EE as a function of PBS density, Pico CRE bias and LP-ABS power based on stochastic geometry model. Then we provide Monte Carlo simulations to verify the accuracy of theoretical derivation of the network EE and analyze the impacts of these parameters on the network EE. The simulation results show that the reasonable PBS density, Pico CRE bias and LP-ABS power can improve the network EE obviously.
On Optimal Power Allocation for Downlink NOMA Transmissions under PHY QoS Constraints

Non-orthogonal multiple access (NOMA) is one of the fundamental techniques that have been actively investigated for the 5th generation (5G) of wireless communication systems, and will be adopted on a wider scale in the coming versions of beyond-5G networks. It presents the benefit of supporting a higher number of users; as compared to the conventional orthogonal multiple access (OMA) schemes, thanks to the successive interference cancellation (SIC) process. However, resources allocation optimization remains one of the main open research challenges in this area. In this paper, we are interested in the power allocation aspect in a downlink NOMA system. We first propose an efficient optimal power allocation strategy maximizing the system’s average sum rate, under physical layer (PHY) quality of service (QoS) conditions. Then, we derive the necessary system conditions to guarantee optimal SIC-stable NOMA schemes. This provides an insight on the operational regions where the use of NOMA is of interest. Various numerical results are presented to illustrate the analysis.
CLASS U-space drone test flight results for non-cooperative surveillance using an L-band 3-D staring radar

Non-cooperative surveillance of drones is an important consideration in the EU SESAR vision for the provision of U-space services. Aveillant Gamekeeper multiple beam staring radar utilises extended dwell to be able to detect small drones at the range of several kilometres. However, target discrimination is necessary with such surveillance system as the increased detection sensitivity against low RCS targets extenuates the problem of false reports of targets such as birds and surface objects such as vehicles etc. Machine learning classifiers are used to remove confuser targets such as birds to provide real-time tracks of drones. Field trials from SESAR CLASS project live drone flights against several test scenarios for U-space are used to train and test a decision tree classifier working on both trajectory and micro-doppler features. Results show that a high level of classifier accuracy is achieved across a range of flight profiles for a rotary wing drone.
On Building Cooperative Intelligent Transportation Systems over Public Transports

Cooperative Intelligent Transportation Systems (CITS) have gained an increasing interest in the last few years. Within these systems, vehicles use wireless communications to cooperatively exchange information in the perspective of enhancing traffic efficiency and comfort. Public transport represents an excellent candidate for C-ITS support. Indeed, unlike private cars, public transport vehicles are inherently cooperative and can be easily augmented with wireless communication capabilities. In this paper, we analyze the communication contact opportunities between public transport buses. Understanding these contacts is a basic building block towards the design and deployment of intelligent, distributed and cooperative applications on top of bus public transport systems. We particularly investigate bus-to-bus contacts in the actual bus public transport of the entire Luxembourg city over a whole day. This city is a representative example of many other European cities. Our study shows that both space and time are chief factors in the characterization of bus-to-bus contacts. Different geographical regions and daytimes show varied contacts properties. Our analysis thus stresses the importance of considering large-scale scenarios when evaluating C-ITS.
RSS-Based Localization of Multiple Directional Sources With Unknown Transmit Powers and Orientations

Received-signal-strength (RSS)-based localization has received widespread attention recently. Due to the simple acquisition of the RSS measurements, the adequate inexpensive sensors in sensor networks are capable of providing the information needed for the positioning of multiple target sources. However, few studies have focused on the RSS-based localization of multiple directional sources that are common in reality. Based on the deduced parametric Optimal Maximum Likelihood (OML) solution, this paper proposes three new grid search-based algorithms, namely Alternating Projection (i.e., OMLAP) algorithm, Expectation-Maximization like (i.e., OMLEM) algorithm, and Particle Swarm Optimization (i.e., OMLPSO) algorithm. They can be utilized for estimating the transmit powers, locations, and orientations of multiple directional sources. Combining the interpolation process and proposed power threshold setting method, the search space is obviously reduced. Moreover, the corresponding Cramer-Rao lower bounds (CRLB) are also derived to characterize the estimation accuracy of the algorithms. Both the scenarios with different Signal-to-Noise Ratios (SNRs) and the scenarios with different sensor quantities are considered in the simulation, and the results demonstrate the effectiveness of the proposed algorithms and indicate that they are suitable for the parameter estimation of multiple directional sources.
Identifying Indexes Affecting the Quality of E-Government Websites

With the development of new technologies in the world, governments have tendency to make a communications with people and business with the help of such technologies. Electronic government (e-government) is defined as utilizing information technologies such as electronic networks, Internet and mobile phones by organizations and state institutions in order to making wide communication between citizens, business and different state institutions.Development of e-government starts with making website in order to share information with users and is considered as the main infrastructure for further development. Website assessment is considered as a way for improving service quality. Different international researches have introduced various indexes for website assessment, they only see some dimensions of website in their research. In this paper, the most important indexes for website quality assessment based on accurate review of previous studies are "Web design", "navigation", services", "maintenance and Support", "Citizens Participation", "Information Quality", "Privacy and Security", "Responsiveness", "Usability". Considering mentioned indexes in designing the website facilitates user interaction with the e-government websites.
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