Miracle-dz/UniFAR-FTUs huggingface dataset:
Dependability Modeling and Analysis of 5G Based Monitoring System in Distribution Grids

Due to large scale introduction of Distributed Energy Resources (DERs) in the next generation distribution grid, real time monitoring and control is increasingly needed to maintain a stable operation. In such scenario, monitoring systems and state estimation are key tools for getting reliable and accurate knowledge of the grid. These real time applications have strong requirements on communication latency, reliability and security. This paper presents a method, based on Stochastic Activity Network modeling, for analyzing the performance and dependability of advanced communication technologies, such as LTE and 5G, for supporting monitoring system applications. A novel software tool, based on Möbius linked to external libraries, is developed and employed to analyze the impact of communication failures on the state estimation of a distribution grid. The application of the tool and its capabilities are demonstrated through a case study. The approach is promising both with respect to strength as a modelling tool and the kind of results obtained.
A Hybrid of Deep Sentence Representation and Local Feature Representation Model for Question Answer Selection

Answer selection is a one of the critical tasks in natural lan-guage processing area and it is helpful in many practical applications. To better tackle this problem, the first challenge is to effectively extract the sentence information. In this research, we propose an advanced Re-Read-CNN model which can learn a deep sentence representation and meanwhile combine the local feature representation. The experiment results on commonly used datasets have shown its effectiveness and potential for answer selection.
Online Gait Transitions and Disturbance Recovery for Legged Robots via the Feasible Impulse Set

Gaits in legged robots are often hand tuned and time based, either explicitly or through an internal clock, for instance, in the form of central pattern generators. This strategy requires trial and error to identify leg timings, which may not be suitable in challenging terrains. In this letter, we introduce new concepts to quantify leg capabilities for online gait emergence and adaptation, without fixed timings or predefined foothold sequences. Specifically, we introduce the Feasible Impulse Set, a notion that extends aspects of the classical wrench cone to include a prediction horizon into the future. By considering the impulses that can be delivered by the legs, quantified notions of leg utility are proposed for coordinating adaptive lift-off and touch-down of stance legs. The proposed methods provide push recovery and emergent gait transitions with speed. These advances are validated in experiments with the MIT Cheetah 3 robot, where the framework is shown to automatically coordinate aperiodic behaviors on a partially moving walkway.
Investigating an Active Noise Cancellation System for Reducing the Sound of Car Horns in an Enclosed Cavity

Active Noise Cancellation (ANC) technology has been a tremendous challenge in modern science. This technology uses the basic interference principle of waves to cancel out a signal by superposition with its inverted signal. This paper presents the possible results of implementing an ANC system to reduce the sound level of car horns inside the room of a patient in a hospital in Bangladesh. The entire project was initially modelled using a designed wooden cavity in place of the desired room. After attempting the work using Analog methods, the researchers decided to explore digital solutions by designing a Digital Signal Processing (DSP) unit in MATLAB and Simulink. All real world signals were used which were captured using microphones. And speakers were used to generate noise and anti-noise for the modelled system.
A Survey on Various Threats and Current State of Security in Android Platform

The advent of the Android system has brought smartphone technology to the doorsteps of the masses. The latest technologies have made it affordable for every section of the society. However, the emergence of the Android platform has also escalated the growth of cybercrime through the mobile platform. Its open source operating system has made it a center of attraction for the attackers. This article provides a comprehensive study of the state of the Android Security domain. This article classifies the attacks on the Android system in four categories (i) hardware-based attacks, (ii) kernel-based attacks, (iii) hardware abstraction layer-based attacks, and (iv) application-based attacks. The study deals with various threats and security measures relating to these categories and presents an in-depth analysis of the underlying problems in the Android security domain. The article also stresses the role of Android application developers in realizing a more secure Android environment. This article attempts to provide a comparative analysis of various malware detection techniques concerning their methods and limitations. The study can help researchers gain knowledge of the Android security domain from various aspects and build a more comprehensive, robust, and efficient solution to the threats that Android is facing.
IMU-Based Active Safe Control of a Variable Stiffness Soft Actuator

Using soft pneumatic actuators is a feasible solution in the dynamic unstructed environment, thanks to their light weight and inherent compliance. It is commonly agreed that the passive compliance and adaptivity of soft robots make them much safer. However, under some special circumstances where stringent safety is requested (e.g., surgical operation), the passive compliance is far from meeting the demands. Therefore, active compliance control is still required to guarantee their operating safety. In this letter, a novel soft actuator is presented, whose stiffness is tunable in multiple ways, and more than a 10-fold stiffness enhancement is achievable, making it able to carry heavy loads while maintaining excellent dexterity and compliance. Meanwhile, we first proposed an active safe control strategy based on inertial measurement units. Through calibrating the load weight (i.e., weight of the end tools) and measuring vibration of soft structures, the collision can be detected in real time and the corresponding safe reaction is then adopted. We have validated its effectiveness on human body, the strategy still works at the speed of 200 mm/s with sharp tools. Furthermore, our control strategy can be applied to other soft or continuum robots, making them safer and more practical in actual applications.
Exploiting Idle Capacity in Optical Networks to Pre-Plan as Many Additional Paths as Possible for Enhancing Service Connection Availability

A network is not always fully loaded during operation and may have idle capacity which is neither carrying any network services nor providing protection for working capacities. This idle capacity may be used to pre-plan as many additional paths as possible to enhance service connection availability with only some extra pre-planning in the network central controller. Our proposed adaptive multi-path protection scheme pre-plans additional paths for failure recovery in an elastic optical network over currently idle capacity to improve the overall network service availability significantly.
Toward Practical Kramers-Kronig Receiver: Resampling, Performance, and Implementation

The Kramers-Kronig (KK) receiver has recently drawn a great deal of attention due to its capability of retrieving the phase information from the directly-detected intensity waveforms. However, a technical challenge associated with the implementation of this attractive receiver is the high sampling rate of digital signal processing (DSP). Since nonlinear operations (such as logarithm and exponential functions) included in the conventional KK algorithm broaden the signal spectrum significantly, digital upsampling is required at the beginning of DSP. To solve this problem, we have recently proposed and demonstrated a new KK algorithm operable without the digital upsampling. In this upsampling-free algorithm, we removed the exponential function by expressing the complex signal in the Cartesian form (i.e., real plus imaginary) and replaced the logarithm function with its mathematical approximation. In this paper, we present the detailed comparison between the conventional and upsampling-free KK algorithms through numerical simulations. We investigate the performance of the KK receivers when we employ orthogonal frequency-division multiplexing and Nyquist subcarrier multiplexing signals formatted in 16-quadrature amplitude modulation (16-QAM) and 64-QAM. Also investigated in this paper is the performance limitation of the upsampling-free KK algorithm. Finally, we propose the schematic diagrams of hardware implementation for the two KK algorithms, and study their complexity as well as their power consumption. The results show that the upsampling-free KK algorithm reduces the complexity and power consumption by a factor of 7 to 10, in comparison with the conventional algorithm at the expense of small sensitivity penalties. For example, the sensitivity difference between the two algorithms is shown to be < 1 dB for the 16-QAM formatted signals.
Reconfigurable Convolutional Kernels for Neural Networks on FPGAs

Convolutional neural networks (CNNs) gained great success in machine learning applications and much attention was paid to their acceleration on field programmable gate arrays (FPGAs). The most demanding computational complexity of CNNs is found in the convolutional layers, which account for 90% of the total operations. The fact that parameters in convolutional layers do not change over a long time interval in weight stationary CNNs allows the use of reconfiguration to reduce the resource requirements. This work proposes several alternative reconfiguration schemes that significantly reduce the complexity of sum-of-products operations. The proposed direct configuration schemes provide the least resource requirements and fast reconfiguration times of 32 clock cycles but require additional memory for the pre-computed configurations. The proposed online reconfiguration scheme uses an online computation of the LUT contents to avoid this memory overhead. Finally, a scheme that duplicates the reconfigurable LUTs is proposed for which the reconfiguration time can be completely hidden in the computation time. Combined with a few online reconfiguration circuits, this provides the same configuration memory and configuration time as a conventional parallel kernel but offers large resource reductions of up to 80% of the LUTs.
Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning

Legged robots have the potential to traverse diverse and rugged terrain. To find a safe and efficient navigation path and to carefully select individual footholds, it is useful to be able to predict properties of the terrain ahead of the robot. In this letter, we propose a method to collect data from robot-terrain interaction and associate it to images. Using sparse data acquired in teleoperation experiments with a quadrupedal robot, we train a neural network to generate a dense prediction of the terrain properties in front of the robot. To generate training data, we project the foothold positions from the robot trajectory into on-board camera images. We then attach labels to these footholds by identifying the dominant features of the force–torque signal measured with sensorized feet. We show that data collected in this fashion can be used to train a convolutional network for terrain property prediction as well as weakly supervised semantic segmentation. Finally, we show that the predicted terrain properties can be used for autonomous navigation of the ANYmal quadruped robot.
Design of 6 GHz High Efficiency Long Range Wireless Power Transfer System Using Offset Reflectors fed by Conical Horns

This paper presents a proposed design procedure of a Wireless Power Transfer (WPT) system based on high efficiency offset reflector antennas fed by conical horns. The system’s performance evaluation is also demonstrated. The antennas in the transmitter and receiver sides of the proposed WPT system are symmetric. The performance of the system is optimized by calibrating the feeding horns and the offset reflector’s dimensions to minimize the path and reflection losses of the proposed WPT system. The results show that correct line of sight alignment of the transmitter and receiver enhances the efficiency of the system. With an operating frequency of 6 GHz and 1 W of power transfer over a distance of 12 m between the transmitter and receiver, the system attains a total transfer efficiency of 62.9 %.
Deformation of West Sumatra Due to the 2016 Earthquake (M7.8) Based on Continuous GPS Data

Sumatra Island, one of the areas in Indonesia, has a very active tectonics in the world. It causes Sumatra to be prone to tectonic earthquake disaster due to the movement of the plates around it. On March 2nd, 2016, a Mw7.8 earthquake centered in the Wharton Indian Ocean Basin Zone, West of Sumatra island happened at a depth of 24 km. This earthquake was an intraplate earthquake that occurred due to the movement in the ocean plate as a type of left lateral strike-slip fault. The calculation of deformation in West Sumatra due to the earthquake was conducted through continuous GPS observation of SuGAr (Sumatran GPS Array) from January 1, 2015 until March 30, 2017 around west part of Sumatra areas. Data processing is done by using GAMIT/GLOBK 10.6 software and the results in daily solution shows that the horizontal component of co-seismic deformation of West Sumatra earthquake in 2016 ranged from 3,6 mm – 5,5 mm which moves toward to northwest. The difference in velocity movement of GPS observation before and after earthquake is used to calculate the strain of plate tectonic around West Sumatra region, where there is a compression pattern before earthquake equal to 2.72×10-8 strain and after earthquake equal to 5.98×10-8 strain. This indicates that there is an increase in compression value in the observation after the earthquake, and the observation area again show the interseismic deformation which means that there is still a considerable accumulation of energy and sometimes can cause the other earthquake.
Nine Cases of Methanogenic Archaea in Refractory Sinusitis, an Emerging Clinical Entity

The authors report the cases of 9 patients eventually diagnosed with methanogenic archaea refractory or recalcitrant chronic rhinosinusitis, a condition known to involve various anaerobic bacteria but in which the role of methanogenic archaea is unknown. The authors retrospectively searched these microorganisms by PCR in surgically-collected sinusal pus specimens from patients diagnosed with refractory sinusitis, defined by the persistance of sinus inflammation and related-symptoms for more than 12 weeks despite appropriate treatment. Of the 116 tested sinus surgical specimens, 12 (10.3%) from 9 patients (six females, three males; aged 20–71 years) were PCR-positive. These specimens were further investigated by fluorescence in-situ hybridization, PCR amplicon-sequencing and culture. Methanobrevibacter smithii was documented in four patients and Methanobrevibacter oralis in another four, one of whom was also culture-positive. They were associated with a mixed flora including Gram-positive and Gram-negative bacteria. In the latter patient, “Methanobrevibacter massiliense” was the sole microorganism detected. These results highlight methanogenic archaea as being part of a mixed anaerobic flora involved in refractory sinusitis, and suggest that the treatment of this condition should include an antibiotic active against methanogens, notably a nitroimidazole derivative.
On the Influence of Continuous Subject Rotation During High-Resolution Head-Related Transfer Function Measurements

In recent years, the required time for high resolution individual head-related transfer function (HRTF) measurements has been reduced by the use of microphone or loudspeaker arrays and with parallelization of measurement signals. While a short measurement time is beneficial during HRTF measurement of any resolution, it is essential for the acquisition of high resolution individual HRTF measurements since subjects cannot remain motionless over extended periods of time. This decrease in measurement time can be achieved by using continuous rotation during the measurement, instead of step-wise subject positioning. This paper examines the influence of such continuous measurement rotation with sine sweep measurements and the necessary subsequent post-processing. The goal is to identify a rotation speed, from a predefined set of speeds, that does not have an audible influence on the measured HRTF itself. To this end, a subjective and objective comparison between the two measurement modes is presented in this paper. Five HRTF measurements of an artificial head are acquired using different rotation speeds. They are compared objectively to a reference measurement of the same head performed with step-wise measurement rotation in the same measurement setup. A subjective listening experiment examines whether the found differences between the measurements do result in an audible difference. The objective evaluation showed expected trends regarding the dependency of the error on the measurement speed and is used to validate the used signal post-processing. The subjective evaluation showed that with a rotation of 3.8$^\circ$/s no audible differences to the reference are present.
On-line Planning on Active SLAM-Based Robot Olfaction for Gas Distribution Mapping

In this paper we develop Active SLAM-based on-line planning systems for mobile robot olfaction. This On-line planning system enables mobile robot olfaction to perform mapping tasks autonomously when a disaster occurs involving Chemical, Biological, Radiological or Nuclear (CBRN) materials. In this work the robot will be tasked with mapping gas distribution in contaminated unknown outdoor environments. Global and local planning is a major part of the on-line planning system. Global planning serves to provide global path planning and predict the best location to take measurements. The combination of frontier based exploration and Closest Location-Information Gain (CL-IG) methods is used to build global planning. Local planning controls robot navigation to avoid obstacles and evaluate every robot action when performing area coverage and gas distribution mapping. Local planning was developed using sensor path planning based on Bayesian Adaptive Exploration (BAE) and Vector Field Histograms (VFH) methods for obstacle avoidance. Online planning performance testing for robot navigation when exploring and mapping has been simulated using ROS, Gazebo and Rviz.
Oxidative Stress in the Poultry Gut: Potential Challenges and Interventions

The gastrointestinal tract (GIT) provides the biological environment for nutrient digestion and absorption, and protection from pathogens and toxins. Broilers are fast growing because of the great potential of intestinal epithelia for nutrient absorption, and efficient conversion of nutrient to muscle. Physiologically, reactive oxygen species (ROS) and reactive nitrogen species (RNS) are generated by GIT epithelial cells either from oxygen metabolism or by enteric commensal bacteria and regulate gut health. However, increased production of ROS elevates free radical production and antioxidant insults resulting in oxidative stress. Oxidative stress in poultry GIT is derived from nutritional, environmental heat stress, and pathological factors, which alters overall performance as well as meat and egg quality. Supplementation of exogenous vitamins, antioxidants, and plant extract having antioxidant properties scavenge ROS and are beneficial in mitigating oxidative stress in the GIT. This review highlights the involvement of oxidative stress in the gastrointestinal functionality of poultry and potential intervention strategies to maintain redox balance in the GIT.
Joint Data and Pilot Power Allocation for Massive MU-MIMO Downlink TDD Systems

This brief investigates the jointly optimal pilot and data power allocation among the users in a massive multiuser multiple-input multiple-output downlink system, in which the base station is equipped with a massive number of antennas and simultaneously serves single-antenna users in the same frequency band. First, a closed-form lower bound on the achievable rate is derived for each user where maximum-ratio transmission precoding is employed, and this closed form lower bound is used in defining the spectral efficiency (SE). Then, in order to maximize the SE, a method of power allocation among each of the pilot and data symbols of all the users is proposed, given the total power budget per coherence interval for all users. Numerical results show that the proposed power allocation scheme is superior to other existing methods in terms of higher SE.
Localization of Partially Visible Needles in 3D Ultrasound Using Dilated CNNs

Guidance of needles for interventions that involve percutaneous advancing of a needle to a target inside the patient's body is one of the key uses of ultrasound, such as for biopsies, ablations, and nerve blocks. During these procedures, image-based detection of the needle can circumvent complex needle-transducer alignment by ensuring an adequate visualization of the needle during the entire procedure. However, successful localization in the sector and curvilinear transducers is challenging as the needle can be invisible or partially visible, due to the lack of received beam reflections from parts of the needle. Therefore, it is necessary to explicitly model the global information present in the data for correct localization of the needle to compensate for the lost signal. We present a novel image-based localization technique to detect partially visible needles in phased-array 3D ultrasound volumes using dilated convolutional neural networks. The proposed algorithm successfully detects the needle plane with accuracy in the submillimeter domain in the 20 measured datasets, which also consists of the cases with mostly invisible needle shaft.
The Non-Smoothness Problem in Disturbance Observer Design: A Set-Invariance-Based Adaptive Fuzzy Control Method

This work removes the critical assumptions of continuity, differentiability, and state-independent boundedness, which are typical of compounded disturbances in disturbance observer-based adaptive designs. Crucial in removing such assumptions are a novel observer-based design with state-dependent gain in place of a constant one, and a novel set-invariance design. The designs use different a priori knowledge of the disturbance, but they can both handle state-dependent (e.g., possibly unbounded) disturbances, as well as non-smooth (e.g., non-differentiable and jump discontinuous) disturbances. The tracking error is proven to be as small as desired by appropriately choosing design parameters. For the second design, which uses the least a priori knowledge of the disturbance, stability is proven by enhancing Lyapunov theory with an invariant-set mechanism, so as to construct an appropriate compact set resulting an invariant set for the closed-loop trajectories.