Miracle-dz/UniFAR-FTUs huggingface dataset:
Wideband User Grouping for Uplink Multiuser mmWave MIMO Systems With Hybrid Combining

Analog-digital hybrid precoding and combining schemes constitute an interesting approach to millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems due to the low hardware complexity and/or low power required for its deployment. However, the design of the hybrid precoders and combiners of a wideband multiuser (MU) mmWave MIMO system is challenging because the signal processing in the analog domain is constrained to be frequency flat. Furthermore, the number of radio frequency (RF) chains limits the number of individual streams that a common base station (BS) can simultaneously serve. This work jointly addresses the user scheduling, the user precoder design, and the BS hybrid combining design for the uplink of wideband MU mmWave MIMO systems. On the one hand, user precoding and BS hybrid combining are jointly designed to minimize the impact of having frequency-flat RF components. On the other hand, a number of users larger than the number of RF chains are served at the BS by employing a distributed quantizer linear coding (DQLC)-based non-orthogonal multiple access (NOMA) scheme. The use of this encoding strategy also allows exploiting the spatial correlation between the source information. Simulation results show remarkable performance gains of the proposed approaches for wideband mmWave MIMO hardware-constrained systems.
Intelligent Environment Enabling Autonomous Driving

Automated driving is expected to enormously evolve the transportation industry and ecosystems. Advancement in communications and sensor technologies have further accelerated the realization process of the autonomous driving goals. There are a number of autonomous driving initiatives around the world with varying objectives and scope, e.g. vehicle perception in a controlled environment or highway settings. Autonomous driving in a more complex environment with mixed traffic poses major challenges. The solutions for such environments is the focus of this paper. We start with a quick overview of current autonomous driving development activities worldwide. We then discuss the solution concept for autonomous driving in urban environments and its enabling components, e.g. road digitization and flexible communication infrastructure, to realize an urban autonomous driving testbed. We highlight the major challenges hindering the realization use-cases of Level 5 autonomous driving. Solution sketches to address these or similar changes are briefly discussed. We also implement some elements of the solution approaches on the real test-road. We demonstrate an artificial intelligence based approach for the analysis of real traffic data measured on the testbed. We implement approaches for predicting the network resource demands and allocation, which are crucial for realizing the use-cases of autonomous driving in complex environments. For the experiments, real data from the test-road is used. Results show that traffic patterns and resource demands are predicted accurately. These experiments are expected to instrumental for realizing other use-cases of autonomous driving.
Android Malware Detection using Convolutional Deep Neural Networks

Deep learning in general and convolutional architectures, in particular, have pushed the limits of the current state of the art in the field of computer vision and the processing of natural languages and speech. Recently, these techniques have been applied to detect mobile malware and have once again shown their ability to remedy this type of problem. However, the most suitable deep network architecture for malware detection remains an open issue. In this paper, we investigate the possibilities of convolutional neural networks for efficient detection of mobile malware. Specifically, we address the impact of using inception based and multichannel architectures on network performance. We achieve an accuracy of 92% using a multichannel model on a set of 50000 malware and 50000 benign applications.
Crowd Forecasting at Venues with Microblog Posts Referring to Future Events

Large events with many attendees cause congestion in the traffic network around the venue. To avoid accidents or delays due to this kind of unexpected congestion, it is important to predict the level of congestion in advance of the event. This study aimed to forecast congestion triggered by large events. However, historical congestion information alone is insufficient to forecast congestion at large venues when non-recurrent events are held there. To address this problem, we utilize microblog posts that refer to future events as an indicator of event attendance. We propose a regression model that is trained with microblog posts and historical congestion information to accurately forecast congestion at large venues. Experiments on next 24-hour congestion forecasting using real-world traffic and Twitter data demonstrate that our model reduces the prediction errors over those of the baseline models (autoregressive and long short term memory) by 20% – 50%.
Tetragonal superstructure and thermal history of Li0.3La0.567TiO3 (LLTO) solid electrolyte by neutron diffraction

High-resolution time-of-flight neutron powder diffraction data (ISIS facility, Rutherford Appleton Laboratory, U. K.) were collected on sample I, prepared by slow cooling from 1300 °C, of the Li0.3La0. 567TiO3 (LLTO) lithium ion conductor, and on sample II quenched in liquid N2. Patterns were obtained at room temperature (RT), 400 and 700 °C on sample I, and at 550 °C on sample II, studied at RT in previous work. The structure was resolved and Rietveld refined in the tetragonal P4/nbm space group with √2ap × √2ap × 2ap unit-cell [a = 5.48162(1), c = 7.74646(1) A at RT, Z = 4; ap is the cell edge of cubic perovskite] in all cases except 700 °C, where a P4/mmm (ap × ap × 2ap) structure was determined and refined [a = 3.89827(2), c = 7.8002(1) A, Z = 2]. In both space groups lanthanum ordering over two La1 and La2 sites is present, but only in P4/nbm can an additional anti-phase octahedral tilting of type a0a0c− be observed, similar to what occurs in the I4/mcm RT metastable phase of the quenched sample. The two distortions are associated to hkl superlattice reflections with h + k even, l odd, and h + k odd, l odd, respectively. Lithium atoms were located in highly disordered sites within the less populated La1 hollows, with short Li–Li′ distances accounting for the high ionic mobility. Possible ordering schemes indicate a mainly (001) two-dimensional mechanism of ion hopping among Li sites.
Bandpass NGD TAN of Symmetric H-Tree With Resistorless Lumped-Network

This paper introduces an innovative passive topology of bandpass (BP) negative group delay (NGD) electrical circuit implemented with symmetric H-tree network. The multi-port topology of BP NGD circuit is originally represented by a resistorless H-tree constituted by lumped LC-passive network. Until now, the NGD electronic circuits available in the literature are implemented by two-port circuits which are using either resistive elements or distributed microstrip topologies. In the present investigation, the feasibility of the modelling, design, fabrication and test of unfamiliar BP NGD original H-tree circuits. The main objective of the study is to identify analytically the existence of the BP NGD function with the resistorless H-tree circuit. Because of its simplicity and the analytical equation compactness, the uncommon approach of tensorial analysis of networks (TAN) is used in the paper. After the branch and mesh analyses, the impedance matrix of the resistorless H-tree is elaborated. Hence, the resistorless H-tree equivalent S-matrix is established by means of impedance to scattering matrix transform. The BP NGD analysis in function of the inductance and capacitance parameters constituting the H-tree circuit is presented. Then, the main steps of the BP NGD investigation are described. The existence of BP NGD behavior in function of the adequate transmission parameters is identified by the consideration of the canonical form. To validate the BP NGD behavior, a proof of concept (POC) of LC-network based resistorless and symmetrical tree prototype is designed, fabricated and measured. Comparison results between well-correlated TAN calculation, simulation and experimentation are discussed.
Dual-Path Mach—Zehnder Interferometers With Unequal Geometrical Path Length for Ultrasensitive Refractive Index Sensing

High-sensitivity fiber-optic interferometric refractive index sensors (FIRSs) have been of interest to researchers due to their potential to fabricate specific physical, chemical, and biological sensors. Fabricating interferometers working near the dispersion turning point (DTP) is an effective approach to improve the sensitivity of FIRSs. However, the group effective refractive index (RI) difference approaching 0 and the ratio of the variation of the effective RI difference to the external RI change being −1 cannot be simultaneously realized in low RI sensing, which restricts the further improvement of sensing sensitivity. Here, dual-path Mach-Zehnder interferometers (MZIs) with unequal geometrical path length are proposed for ultrasensitive RI sensing. The dual-path MZIs contain fiber path and sample path of different geometrical lengths to form the optical path difference. The dual-path MZIs can not only show a turning point where the sensing sensitivity tends to be infinite, which is similar to the previously reported DTP, but also get the constant value −1 for the RI response factor, leading to the result that the dips within an over-500-nm band width around the turning point can achieve high sensitivity reaching 105 nm/RIU level or higher. Ultrahigh sensitivity of −1.26 × 106 nm/RIU has been experimentally demonstrated at the RI around 1.35022. The dual-path MZIs proposed here may enlighten new ideas for developing high-sensitivity FIRSs.
Recognition of Human Characteristics Using Multiple Mobile Robots With 3D LiDARs

Mobile robots are gradually entering our human spaces. Apart from being able to accurately localize themselves, in populated environments robots also need to detect humans and recognize their characteristics. In this work we focused on using 3D LiDARs for sensing, and in particular on the question whether they can be used to classify characteristics of people around the robot. Moreover, since using sensors from multiple robots is expected to give more accurate recognition, we compared several ways how to combine multiple 3D LiDARs. We evaluated these methods using simulator data as well as actual real-world data. For the real-world data we created a novel dataset taken with multiple robots equipped with 3D LiDARs in a shopping center, which also includes manually labeled characteristics of the detected pedestrians. The results show that combining several 3D LiDARs makes the recognition more accurate. However, we were not able to achieve satisfactory accuracy with real-world data.
Urine Volume Estimation by Electrical Impedance Tomography with Fewer Electrodes: A Simulation Study*

Urinary incontinence is prevalent among elderly people. Recent studies have demonstrated the effectiveness of continence care based on bladder volume measurement in elderly people, who maintain the urinary storage function but have difficulty in feeling bladder fullness due to dementia or some neurological disorders. To help caregivers provide the bladder volume measurement-based care, our group is developing a wearable bladder volume sensor with an error $\mathrm{o}\mathrm{f} \lt 20\mathrm{m}\mathrm{L}$ (10% error around 200 mL). This study evaluated the performance of a bladder volume estimation by impedance measurement with fewer electrodes than ordinary electrical impedance tomography in finite element simulation. The result in simulation data by 8-electrode measurement showed a root mean square error of 27.7 (0.2) mL (mean (SD)) with the normal measurement noise, and this decreased to 15.2 (0.1) mL with a smaller noise. This study confirmed that the impedance measurement with eight electrodes accurately estimates the bladder volume. As the urine conductivity is subject to diurnal variation, we tested the model in the mixed urine conductivity condition. The root mean square error increased to 57.2 (0.3) mL and was not improved even with smaller noise. Further research will include the development of an estimation model that is robust to urine conductivity variations.
Roles of Gate Voltage and Stress Power in Self-Heating Degradation of a-InGaZnO Thin-Film Transistors

Roles of gate voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{G}$ </tex-math></inline-formula>) and stress power in self-heating (SH) degradation of amorphous InGaZnO thin-film transistors have been clarified. Normally observed positive threshold voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{th}$ </tex-math></inline-formula>) shift is attributed to the electron trapping mechanism, which is enhanced by both the effective <inline-formula> <tex-math notation="LaTeX">${V}_{G}$ </tex-math></inline-formula> and stress power. The effective <inline-formula> <tex-math notation="LaTeX">${V}_{G}$ </tex-math></inline-formula> plays a dominant role in most cases, while stress power takes control only if it is high enough. Following the positive <inline-formula> <tex-math notation="LaTeX">${V}_{th}$ </tex-math></inline-formula> shift, a second-stage negative <inline-formula> <tex-math notation="LaTeX">${V}_{th}$ </tex-math></inline-formula> backshift is also observed and is attributed to the water-related positive charges generation mechanism. It is enhanced by both stress power and effective <inline-formula> <tex-math notation="LaTeX">${V}_{G}$ </tex-math></inline-formula> for which stress power is found to be the dominant factor.
Diffuse Reflectance Spectra of Al Substituted Goethite: A Ligand Field Approach

Previous investigations of goethite revealed a substantial variation of color and diffuse reflectance spectra (DRS) in the extended visible range (350–2200 nm). To better understand the causes of this variability and to assess the potential of DRS as a mineralogical tool, we investigated the DRS of pure and Al-substituted goethite, α-Fe1−xAlxOOH with x from 0 to 0.33, and mean crystal lengths (MCL) from 170 to 1800 nm. The strongly overlapping ligand field bands were extracted by fitting the single-electron transitions 6A1 → 4T1, 6A1 → 4T2, 6A1 → (4E; 4A1), and 6A1 → 4E(4D) as functions of the ligand field splitting energy, 10 Dq, and the interelectronic repulsion parameters, Racah-B and -C. With x increasing from 0 to 0.33, 6A1 → 4T1 decreased from 10,590 to 10,150 cm−1 (944 to 958 nm), and 6A1 → 4T2 decreased from 15,310 to 14,880 cm−1 (653 to 672 nm), while 10 Dq increased from 15,770 to 16,220 cm−1. From the change of 10 Dq we calculated a decrease of the Fe-(O,OH) distances from 202.0 to 200.9 pm (−0.5%). This decrease is smaller than the average decrease of all (Al,Fe)-(O,OH) distances (−1.8%) calculated from the change of the unit-cell lengths (UCL). That is, there remains a substantial difference in size between the larger Fe- and the smaller Al-occupied octahedra in the solid solution which may indicate the existence of diaspore clusters within the goethite structure. The increasing strain in the crystal structure due to the size mismatch and limited contractibility of the oxygen cage around Fe may be the primary reason for Al substitution being restricted to x < 0.33. The bands 6A1 → (4E; 4A1) and 6A1 → 4E(4D) did not shift, indicating a constant covalency of the Fe-(O,OH) bonds with B = 628 cm−1 and C = 5.5B. Whereas variation of band energies could be explained in terms of the Fe-(O,OH) ligand field, the variation of color and band intensities was mainly determined by crystal size. Although our study confirmed the potential of DRS for mineralogical investigations, there is still a gap between the fundamental theory and the explanation of some spectral features.
Wi-Fi RTT-Based Active Monopulse RADAR for Single Access Point Localization

The purpose of this work is to implement a novel active radar system for single access point two-dimensional localization system based on 802.11 wireless local-area networks (WLAN). The active radar employes the 802.11 Fine Time Measurement (FTM) Round Trip Time (RTT) as specified in the 2016 update of WIFI Standard to calculate the ranging distance and acquires two channels of Received Signal Strength Indicator (RSSI) to estimate the azimuthal angle. In this way, real-time two-dimensional localization of Wi-Fi RTT-compatible mobile Internet of Things devices is demonstrated using a single access point operating in the 2.4GHz band. The experimental results performed in anechoic chamber and in a real environment point up a mean positioning error below one meter within a Field of View (FoV) of 60° and distances up to 14 meters, with an acquisition time below 0.5 seconds.
Die Strukturen von C‐Fluorocurin, C‐Mavacurin und Pleiocarpamin. 57. Mitteilung über Curare‐Alkaloide

Die Alkaloide C-Mavacurin, C-Fluorocurin und C-Alkaloid Y aus Calebassen-Curare und sudamerikanischen Strycknos-Arten sind mit dem Indolalkaloid Pleiocarpamin aus Pleiocarpa mutica BENTH. und Hunteria eburnea PICHON in Beziehung gesetzt worden. Diese Beziehungen erlauben die Festlegung der Natur der Hydroxyl-gruppe in den Curare-Alkaloiden und machen in den fruher abgeleiteten Formelneine Abanderung des Ringes E im Sinne der neuen Formeln 8,16 und 19 notwendig;daraus folgt auch die Strukturformel 1 fur Pleiocarpamin. Weitere chemische Um-wandlungen stutzen diese Formeln und ermoglichen die Ableitung der relativen Stereochemie der Alkaloide. 100-MHz-Protonenresonanz-Spektren zusammen mit Spin-Entkoppelungs-Experimenten erlaubten die Identifizierung aller fur das Ringgerust charakteristischen Protonen und eine unabhangige Ableitung der stereochemischen Verhaltnisse. Schliesslich werden noch die Massenspektren der Alkaloide und ihrer Derivate diskutiert.
Profiling Astroturfing Facebook Users During Three Contiguous Israeli Election Periods

Astroturfing is the practice of using a fake online social media (OSM) profile in order to influence public opinion, while giving the impression that the profile belongs to an authentic human user. The proliferation of such profiles in the political OSM scene is becoming more and more common, and as such, poses a threat to democratic processes, especially around election time. We present here a unique technique for exposing astroturfing profiles for what they are. This technique was developed and tested using a large dataset which we collected from Facebook, containing over four million comments, posted within a time span of 15 months, during which three rounds of elections took place in Israel. This political situation provided a rare opportunity to create and research what is—to the best of our knowledge—one of the largest datasets of authentic and fake profiles curated from Facebook to this day. These unique circumstances of three elections held contiguously within a short time span brought forth a set of previously unrecognized features, creating a temporal layer in the feature set, with regard to the date of elections, such as pre-election and post-election, which greatly improved classification results. By creating and selecting the right features, and using various machine learning algorithms, we are able to identify such profiles, with good precision and recall. This setup can serve as a platform for large scale astroturfing profiling in regular situations. Our unique dataset is planned to be made publicly available to the research community.
A Memory-Targeted Dynamic Reconfigurable Charge Pump to Achieve a Power Consumption Reduction in IoT Nodes

Targeting the more recently adopted low-power memories for data-logging operation in IoT nodes, this paper presents a simple reconfigurable dual-branch cross-coupled charge pump (CP) topology in which clock amplitude scaling and modulation of the number of stages are exploited to improve power efficiency and/or change the output voltage without degrading speed performance. The proposed solution allows a reduction of the power conversion losses, maintaining speed, maximum output voltage and silicon area unaltered as compared to the conventional charge pump. Post-layout simulation results confirm the effectiveness of the proposed topology which can be adapted to any other kind of linear charge pump.
Study of Frequency-dependent Parasitics' Effects on Resonance Frequencies of a Two-winding Medium/High-frequency Transformer

A medium/high-frequency (MF/HF) transformer has become an integral part of many high-power conversion systems. Therefore, it is important to study the frequency response analysis (FRA) of a MF/HF transformer to ensure a reliable and safe converter operation. In this paper, frequency-dependent behavior of the transformer parasitics and their effects on the natural resonance frequencies are analyzed. A transfer function based π-model is employed to compute the frequency-dependent FRA of a two-winding transformer and estimate its natural resonance frequencies. It concludes that at high frequency, increased winding ac resistance exhibits higher damping effect at the resonance frequencies; whereas reduced leakage inductance shifts the resonance frequencies towards the high-frequency region of frequency response. Analytical calculations are verified with the help of experimental results obtained from a 1.5 kW, 15 kHz ferrite core transformer. The predicted and measured values of the resonance frequencies agree well, indicating a good modeling accuracy and aptness of the proposed methodology.
RISC-V3: A RISC-V Compatible CPU With a Data Path Based on Redundant Number Systems

Redundant number systems (RNS) are a well-known technique to speed up arithmetic circuits. However, in a complete CPU, arithmetic circuits using RNS were only included on subcircuit level e.g. inside the Arithmetic Logic Unit (ALU) for realization of the division. Still, extending this approach to create a CPU with a complete data path based on RNS can be beneficial for speeding up data processing, due to avoiding conversions in the ALU between RNS and binary number representations. Therefore, with this paper we present a new CPU architecture called RISC-V3 which is compatible to the RISC-V instruction set, but uses an RNS number representation internally to speed up instruction execution times and therefore increase the system performance. RISC-V is very suitable for RNS because it does not have a flags register which is expensive to calculate when using an RNS. To present reliable performance numbers, arithmetic circuits using RNS were realized in different semiconductor technologies. Moreover, an instruction set simulator was used to estimate system performance for a benchmark suite (Embench). Our results show, that we are up to 81% faster with the RISC-V3 architecture compared to a binary one, depending on the executed benchmark and CMOS technology.