Miracle-dz/UniFAR-FTUs huggingface dataset:
UWB Antenna Vivaldi Based on Substrate Integrated Waveguide

A phased study of the characteristics of the printed antipodal Vivaldi antenna models based on a substrate integrated waveguide in the frequency band 18-42 GHz was carried out. It was found that both the dimensions of the aperture and the exciting segment significantly affect the gain of the antennas as well as their matching in the frequency band. Antenna models were analyzed in CST Microwave Studio. Matching characteristics and radiation patterns are presented.
Exploiting a Human-Aware World Model for Dynamic Task Allocation in Flexible Human-Robot Teams

We propose a highly flexible approach to human-robot cooperation, where a robot dynamically selects operations contributing to a shared goal from a given task model. Therefore, knowledge on the task progress is extracted from a world model constructed from eye-in-hand camera images. Data generated from such partial workspace observations is not reliable over time, as humans may interact with resources. We therefore use a human-aware world model maintaining a measure for trust in stored objects regarding recent human presence and previous task progress. Our contribution is an action selection algorithm that uses this trust measure to interleave task operations with active vision to refresh the world model. Large-scale experiments cover various sorts of human participation in different benchmark tasks through simulation of simplified, partially randomized human models. Results illuminate system behaviour and performance for different parametrizations of our human-robot teaming framework.
Exploitation of Environment Support Contacts for Manipulation Effort Reduction of a Robot Arm

Humans commonly exploit interaction with the environment constraints to assist the execution of the locomanipulation tasks they perform. One particular example is the exploration of contacts during manipulation to relax the loading of those arm joints that are not directly involved in the generation of the manipulation motions and forces, e.g. establishing a contact with the elbow joint to reduce the effort of the upper arm while executing wrist level manipulation.In this paper, we shall explore the possibility of actively (a) utilizing the environment for a non-end-effector support contact towards reducing the joints efforts during manipulation tasks. This is achieved by our proposed control scheme with a three-level hierarchical compliance controller. The highest priority task is assigned to an impedance control that regulates the interaction at the contact control point on the arm in the normal direction of the support plane prior to contact, and is switched to an optimal contact force control for minimizing the joint effort after the contact is built. The second priority task is an impedance control at the same point in the tangential directions of the plane to stabilize the contact. In the end, an impedance behavior at the end-effector is designed to deal with the interaction forces required by the manipulation tasks. The efficacy of the proposed control scheme was corroborated by simulations and experiments, where significant joint effort reduction was observed.
Circular Antenna Array for a Cell Sectoring Base Station

In SDMA (Space division multiple access) mobile communication systems, cell sectoring of the coverage area is used to increase frequency spectrum efficiency. Each sector is served by either a separate antenna or switched-beam antenna array. The report deals with the construction of such arrays based on the reflective type beam-forming networks (RBFN). The requirements for the scattering matrix of the RBFN are formulated. For the arrays rational using of geometrical symmetry properties allowed to propose a convenient algorithm for synthesis and the structure design of RBFN.
Mitigation of GPS Chirp Jammer Using a Transversal FIR Filter and LMS Algorithm

In this study, we present an experimental result of least mean squares (LMS)-based method for GPS chirp jammer mitigation. Because the chirp jamming signal has a time-varying frequency, the weight vector is calculated by iterative update rather than by solving the Wiener–Hopf equation. The computed weight vector is applied to the transversal finite impulse response (FIR) filter as filter coefficients. The experimental result demonstrates the anti-jamming performance of our approach with live GPS signals and synthetic jamming signals.
Optimization of Deep Neural Network for Neuromorphic System

In this paper, we propose a Deep Neural Network(DNN) to determine the status of a biosignal and explain the process of optimizing DNN for applying to a neuromorphic system. Biosignals are preprocessed using Fast Fourier Transform(FFT), Sampling, and quantization according to the characteristics of the neuromorphic cell. In the preprocessing, the input nodes are determined by the sampling size and the quantization bits. Perform mid-rise quantization on the weights and compare the accuracy with the input nodes.
FL-RuNS: A High-Performance and Runtime Reconfigurable Fault-Tolerant Routing Scheme for Partially Connected Three-Dimensional Networks on Chip

Three-dimensional networks on chip (3D-NoCs) have been proposed as an enormously scalable solution to address communication problems in modern systems on chip. Through-silicon via (TSV) is usually adopted as a viable technology enabling vertical connection among NoC layers. However, TSV-based architectures typically exhibit high vulnerability to transient and permanent faults caused by aging effects, thermal violations, manufacturing issues, or even transient fault sources. Therefore, TSV-based architectures call for robust routing schemes capable of sustaining operation under unpredictable failure patterns. In this paper, we introduce FL-RuNS, a fault-tolerant routing scheme for achieving 100% packet delivery under an unconstrained set of runtime and permanent vertical link failures. The proposed scheme uses the concept of vertical link announcement to inform nodes in the network of the health condition of vertical links. This mechanism is able to dynamically and progressively reconfigure the entire network without any packet loss. FL-RuNS requires a very low number of asymmetric virtual channels to achieve both deadlock freedom and reachability. Also, FL-RuNS introduces one-flit-dedicated virtual channels, which are used as an escape buffer in case of TSVs failures. The experimental results have confirmed that FL-RuNS shows better reliability when compared to the recently proposed fault-tolerant routing algorithm. Furthermore, the hardware synthesis performed using a commercial 28-nm technology library shows a reasonable area and power overhead with respect to the non-fault-tolerant baseline.
Robust object grasping in clutter via singulation

Grasping objects in a cluttered environment is challenging due to the lack of collision free grasp affordances. In such conditions, the target object touches or is covered by other objects in the scene, resulting in a failed grasp. To address this problem, we propose a strategy of singulating the object from its surrounding clutter, which consists of previously unseen objects, by means of lateral pushing movements. We employ reinforcement learning for obtaining optimal push policies given depth observations of the scene. The action-value function(Q-function) is approximated with a deep neural network. We train the robot in simulation and we demonstrate that the transfer of learned policies to the real environment is robust.
A-SLAM: Human in-the-loop Augmented SLAM

In this work, we are proposing an intuitive Augmented SLAM method (A-SLAM) that allows the user to interact, in real-time, with a robot running SLAM to correct for pose and map errors. We built an AR application that works on HoloLens and allows the operator to view the robot’s map superposed on the physical environment and edit it. Through map editing, the operator can account for errors affecting real environment’s representation by adding navigation-forbidden areas to the map in addition to the ability to correct errors affecting the localization. The proposed system allows the operator to edit the robot’s pose (based on SLAM request) and can be extended to sending navigation goals to the robot, viewing the planned path to evaluate it before execution, and teleoperating the robot. The proposed solution could be applied on any 2D-based SLAM algorithm and can easily be extended to 3D SLAM techniques. We validated our system through experimentation on pose correction and map editing. Experiments demonstrated that through A-SLAM, SLAM runtime is cut to half, post-processing of maps is totally eliminated, and high quality occupancy grid maps could be achieved with minimal added computational and hardware costs.
Novel Corrugated Microstrip Patch Antenna: Effects on Resonant Frequency, Coupling and Cross Polarization

Microstrip patch antennas are very often used in array configurations where there might be specific requirements such as antenna gain, beamwidth and polarization. In this paper, a single patch antenna element is corrugated in different ways and depths as a novel design geometry. As a building block in an array, the proposed geometry is studied in detail to investigate its effects on the well-known drawbacks of a microsrtip patch antenna, i.e. the fringing effects and the parasitic coupling arising between array elements. It is found that patch corrugations strongly affect the resonant frequency, so that, if properly controlled, they might compensate the arising fringing effect and almost eliminate the undesired coupling between antenna elements. And surprisingly, the cross-polarization levels in the H-plane (unacceptably high for some applications) are greatly reduced and can be eliminated to some extent on the cost of a slight reduction of the gain. Full-wave analysis simulations with HFSS (finite element) and Sonnet (MoM) software are used in the investigations.
On the Delay/Throughput-Security Tradeoff in Wiretap TDMA Networks With Buffered Nodes

In this paper, we investigate the tradeoff between security and throughput and between security and queuing delay in wiretap time-division multiple access (TDMA) networks. We derive a simple relationship, characterized by a single key system parameter, between the stable-throughput region, where there are no perfect secrecy constraints on the data transmissions, and the secure stable-throughput region, where there are perfect secrecy constraints. We quantify the impact of the perfect secrecy constraints on the network’s average queuing delay and propose a novel cross-layer security scheme for delay-limited applications. We establish an insightful link between computational security (i.e., upper-layer security implemented through cryptographic schemes) and physical-layer (information-theoretically proved) security. For the two-user case, we derive a closed-form expression for the network’s minimum average queuing delay under the proposed security scheme and provide a relationship between the network’s minimum queuing delay under perfect secrecy constraints and computational-only secrecy constraints. Moreover, we investigate the impact of cooperative jamming on achieving perfect secrecy, minimum network’s queuing delay, and maximum throughput. We verify our theoretical findings through simulations.
Active Contraints for Tool-Shaft Collision Avoidance in Minimally Invasive Surgery

Recent advances in teleoperation-based robotic-assisted Minimally Invasive Surgery (MIS) have made significant inroads in clinical adoption. However, such master-slave surgical systems create a physical separation between the surgeon and the patient. The concept of Active Constraints (ACs) provides guidance and sensory information to surgical robot operators in a form of haptic, visual or audible cues. This work proposes a novel ACs approach to avoid surgical tool-clashing and collision of the tool-shaft with delicate anatomy using elasto-plastic frictional force control. The presented framework is designed to reduce the occurence of direct coupling during electrocautery and to protect high-risk regions in Minimally Invasive Partial Nephrectomy (MIPN). Moreover, we combine aforementioned ACs methods and propose a solution when simultaneous penetration of both constraints occurs. The proposed methodology is implemented on the teleoperated da Vinci Surgical System using the da Vinci Research Kit (dVRK) and its performance is demonstrated through three types of user experiments. The experimental results show that the developed algorithms are of significant benefit in performing the tasks with ACs assistance.
A Novel Rotating Beam Link for Variable Stiffness Robotic Arms

In this paper, we present a novel design concept for a robot arm link with variable stiffness. Variable stiffness links are intended to grant a robot the safety benefits of compliance and the performance benefits of stiffness. Our compact design actively modulates stiffness via parallel, rotating beams actuated by simple servomotors. It achieves a lateral stiffness ratio greater than ten with a minimum stiffness under 0.2 N/mm. Our novel design offers many benefits over existing variable stiffness link solutions in its compactness, simplicity, and speed of actuation. One challenge of this research lies in the mechanics modeling of variable stiffness. Here we propose a comprehensive mechanics model that considers mechanical compliances due to deflections of parallel guided beams, column buckling, and bearing at the beam roots. By comparing with experimental testing data, we show that our analytical model accurately predicts the lateral stiffness of the robotic link. This model can be used as a design tool in future iterations, including for scaling the design.
Countermeasure for Identification of Controlled Data Injection Attacks in Networked Control Systems

Networked Control Systems (NCS) are widely used in Industry 4.0 to obtain better management and operational capabilities, as well as to reduce costs. However, despite the benefits provided by NCSs, the integration of communication networks with physical plants can also expose these systems to cyber threats. This work proposes a link monitoring strategy to identify linear time-invariant transfer functions performed by a Man-in-the-Middle during controlled data injection attacks in NCSs. The results demonstrate that the proposed identification scheme provides adequate accuracy when estimating the attack function, and does not interfere in the plant behavior when the system is not under attack.
INFORA: A Novel Inflatable Origami-based Actuator

Pneumatic actuators have gained huge popularity in the field of soft robotics. A class of this kind of devices exploits inflatable thin membranes which generate a desired displacement upon inflation, but often without providing sufficient force/torque to perform their task. In this paper, we propose a novel actuator combining a membrane and a rigid foldable structure. Experimental tests show that such INFlatable ORigami Actuator (INFORA) is characterized by relatively high stiffness compared to other actuators of the same class. We provide a mathematical model to be used for design purposes and we describe the fabrication process. In addition, we show how the INFORA can be used to build a tendril-like structure capable of performing grasping tasks.
Multimodal Unified Attention Networks for Vision-and-Language Interactions

Learning an effective attention mechanism for multimodal data is important in many vision-and-language tasks that require a synergic understanding of both the visual and textual contents. Existing state-of-the-art approaches use co-attention models to associate each visual object (e.g., image region) with each textual object (e.g., query word). Despite the success of these co-attention models, they only model inter-modal interactions while neglecting intra-modal interactions. Here we propose a general `unified attention' model that simultaneously captures the intra- and inter-modal interactions of multimodal features and outputs their corresponding attended representations. By stacking such unified attention blocks in depth, we obtain the deep Multimodal Unified Attention Network (MUAN), which can seamlessly be applied to the visual question answering (VQA) and visual grounding tasks. We evaluate our MUAN models on two VQA datasets and three visual grounding datasets, and the results show that MUAN achieves top-level performance on both tasks without bells and whistles.
LSTM-based Flow Prediction

This paper introduces an innovative approach for predicting continuous time series variables in the context of production or flow. The proposed method employs an LSTM algorithm enhanced through multivariate tuning. This algorithm refines the conventional LSTM by transforming time series data into supervised learning sequences, tailored to the distinctive features of industrial data. The primary novelty lies in incorporating the concepts of periodic measurement and time window into industrial prediction, particularly when dealing with time series characteristics in industrial data. Experimental results using real-world datasets demonstrate a notable improvement in prediction accuracy, achieving a 54.05% enhancement over the traditional LSTM algorithm.
1 2 A ug 2 01 9 Low depth quantum search algorithm

Grover’s quantum search algorithm provides a quadratic speedup over classical algorithm. The computational complexity is based on the number of queries to the oracle. However, depth is a more practical metric for quantum computer. Based on Grover’s algorithm, we propose several new quantum search algorithms which have lower depth. The algorithm can be divided into several steps. Each step consists of a new initialization of the input, which potentially decreases the error for limited coherent time quantum computer. Under some condition, the algorithm within measurements still reaches lower depth compared with Grover’s algorithm. We also consider several methods to parallel running the quantum search algorithm.
Successive Projection Algorithm Robust to Outliers

The successive projection algorithm (SPA) is a fast algorithm to tackle separable nonnegative matrix factorization (NMF). Given a nonnegative data matrix $X$, SPA identifies an index set $\mathcal{K}$ such that there exists a nonnegative matrix $H$ with $X\approx X(:,\ \mathcal{K})H$. SPA has been successfully used as a pure-pixel search algorithm in hyperspectral unmixing and for anchor word selection in document classification. Moreover, SPA is provably robust in low-noise settings. The main drawbacks of SPA are that it is not robust to outliers and does not take the data fitting term into account when selecting the indices in $\mathcal{K}$. In this paper, we propose a new SPA variant, dubbed Robust SPA (RSPA), that is robust to outliers while still being provably robust in low-noise settings, and that takes into account the reconstruction error for selecting the indices in $\mathcal{K}$. We illustrate the effectiveness of RSPA on synthetic data sets and hyperspectral images.
Good Motive but Bad Design: Why ARM MPU Has Become an Outcast in Embedded Systems

As more and more embedded devices are connected to the Internet, leading to the emergence of Internet-of-Things (IoT), previously less tested (and insecure) devices are exposed to miscreants. To prevent them from being compromised, the memory protection unit (MPU), which is readily available on many devices, has the potential to become a free lunch for the defenders. To our surprise, the MPU is seldom used by real-world products. The reasons are multi-fold. While there are non-technical reasons such as compatibility issues, more importantly, we found that MPU brings virtually no security enhancement at the expense of decreased performance and responsiveness. In this work, we investigate the MPU adoption in major real-time operating systems (RTOSs), in particular, the FreeRTOS, and try to pinpoint the fundamental reasons to explain why MPU is not favored. We hope our findings can inspire new remedial solutions to change the situation. We also review the latest MPU design and provide technical suggestions to build more secure embedded systems.
The Greenhouse Effect in Buried Galactic Nuclei and the Resonant HCN Vibrational Emission

Recent interferometric observations have shown bright HCN emission from the ν2 = 1 vibrational state arising in buried nuclear regions of galaxies, indicating an efficient pumping of the ν2 = 1 state through the absorption of 14 μm continuum photons. We modeled the continuum and HCN vibrational line emission in these regions, characterized by high column densities of dust and high luminosities, using a spherically symmetric approach, simulating both a central heating source (active galactic nucleus, AGN) and a compact nuclear starburst (SB). We find that when the H2 columns become very high, NH2 ≳ 1025 cm−2, trapping of continuum photons within the nuclear region dramatically enhances the dust temperature (Tdust) in the inner regions, even though the predicted spectral energy distribution as seen from the outside becomes relatively cold. The models thus predict a bright continuum at millimeter wavelengths for a luminosity surface brightness (averaged over the model source) of ∼108 L⊙ pc−2. This greenhouse effect significantly enhances the mean mid-infrared intensity within the dusty volume, populating the ν2 = 1 state to the extent that the HCN vibrational lines become optically thick. AGN models yield higher Tdust in the inner regions and higher peak (sub)millimeter continuum brightness than SB models, but similar HCN vibrational J = 3–2 and 4–3 emission owing to both optical depth effects and a moderate impact of high Tdust on these low-J lines. The observed HCN vibrational emission in several galaxies can be accounted for with an HCN abundance of ∼10−6 (relative to H2) and luminosity surface brightness in the range (0.5–2) × 108 L⊙ pc−2, predicting a far-infrared photosphere with Tdust ∼ 80–150 K, in agreement with the values inferred from far-infrared molecular absorption.
Tuning electronic and optical properties of free-standing Sn2Bi monolayer stabilized by hydrogenation

In this study, we systematically investigated the structural, mechanical, electronic and optical properties of Sn2Bi monolayer, a sheet experimentally synthesized recently [PRL, 121, 126801 (2018)] which has been hydrogenated (Sn2BiH2) to stabilize free-standing form using density functional theory (DFT). For tuning the band structure and electronic properties, the mechanical strain and electric field are used. Our investigations show that in this free-standing sample, there are electron flat bands and free hole bands like the recently synthesized sample on silicon wafer, which provide the possibility of having strongly localized electrons and free holes with high mobility. Also, the band gap of Sn2BiH2 monolayer has experienced a growth of 80% compared with the experimental sample. The relevant results to strain suggest that the band gap can be properly manipulated by biaxial strain (-13% to +21%) within a range from 0.2 to 1.6 eV. It should be mentioned that the stability and flexibility of the corresponding monolayer under tensile and compressive strain are due to the strong {\sigma} bonds between atoms. We also realized the strain can cause indirect-direct transition in the band gap. Furthermore, our optical findings indicate that the Sn2BiH2 monolayer has almost metallic properties in a specific range of UV spectrum and it is transparent in the IR and visible spectrum of electromagnetic radiation. All these tunable properties and nontrivial features portend that Sn2BiH2 monolayer has great potentials in applications as near-infrared detectors, thermoelectric devices, field-effect transistors, sensors, photocatalysis, energy harvesting, and optoelectronics.