Miracle-dz/UniFAR-FTUs huggingface dataset:
Perfect Digital Photography

Written by photography experts--including a Pulitzer-Prize winning National Geographic photographer--this full-color book is a must-have for amateur photographers serious about improving both the quality of their photographs and their proficiency in the digital darkroom. The book is the perfect combination of a technical treatise on digital imaging and an artistic exploration of light, composition, and form, allowing you to glean the essential techniques needed for digital photography without losing sight of the artistic and aesthetic aspects of the craft. Using an easy-to-follow approach, the authors explain the image conceptualization process through shooting, editing, and image correction to finished print. In addition, top photographers from a variety of disciplines offer real-world advice on how they use digital photography to create compelling images for high-profile magazine articles, advertising campaigns, and fine art prints.
2-D-Particle-in-Cell Simulation of Laser Wakefield in an Inhomogeneous Plasma

We performed the 2-D particle-in-cell simulation of the laser wakefield in an inhomogeneous plasma to study the dependence of the speed of the wakes to the electron density of the background plasma to search the condition of “accelerating flying mirror”. Acceleration of the plasma wakes is not observed in the simulations with the parameters that we have tested.
Review of Applications of Fuzzy Logic in Multi-Agent-Based Control System of AC-DC Hybrid Microgrid

High penetration of renewable energies to smart grid technologies has lead the traditional electrical transmission and distribution network to undergo a significant evolution. Here, advanced control strategies are required to ensure the load balance in order to keep the voltage and frequency variation within an acceptable range. With the integration of dc energy sources and storages, another control constraint would be added due to the limitations in a storage system. Among recent developments in control techniques, fuzzy logic and multi agent systems have emerged due to its strong control action in an uncertain environment. Researchers have made satisfactory efforts in optimizing hybrid renewable energy sources using these technologies. This paper strives to highlight the approaches of controlling the energy storage systems, dc voltage, frequency, and ac voltage with the aid of the fuzzy logic and multi agent systems related controllers.
A LOF-Based Method for Abnormal Segment Detection in Machinery Condition Monitoring

Machinery condition monitoring has entered the era of big data and some research has been done based on big data. Abnormal segments, such as missing segments and drift segments, are inevitable in big data acquired from harsh industrial environment due to temporary sensor failures, network segment transmission delays, or accidental loss of some collected data and so on. Being independent of the machinery condition, the abnormal segments not only reduce the quality of the data for condition monitoring and big data analysis, but also bring a heavy computation load. However, there are few reports to address abnormal segment detection for further data cleaning in the field of machinery condition monitoring. Therefore, an abnormal segment detection method is proposed to improve the quality of big data. First, a sliding window is used to separate the data into different segments. Then, 14 kinds of time-domain features are extracted from each segment and principle component analysis (PCA) is employed to extract the principle components from these features. In addition, local outlier factor (LOF) is calculated based on the principle components to evaluate the degree of being an outlier for each segment. Finally, the data, including a drift segment from a real wind turbine, are used to verify the effectiveness of the proposed method.
Circularly Polarized Substrate Integrated Dielectric Resonator Antenna

This paper proposes a novel circularly polarized (CP) substrate integrated dielectric resonator antenna (SIDRA). It is fed by a half-mode substrate integrated waveguide (HMSIW) through a pair of cross-slots. The feeding HMSIW and radiator of the proposed SIDRA can be fully integrated together based on the simple printed circuit board (PCB) technology. The proposed antenna has the merits of low profile, low cost, high efficiency, and easy integration.
Design and Experiments of a Novel Hydraulic Wheel-Legged Robot (WLR)

Wheel-legged hybrid robot with multi-modal locomotion can efficiently adapt to different terrain environments, as well as realize rapid maneuver on flat ground. We have developed a novel hydraulic wheel-legged robot (WLR) combined with a humanoid structural design. This robot can assist to emergency scenarios where the high mobility, adaptability and robustness are required. The paper introduces the details of the WLR, highlighting the innovative design and optimization of physical construction which is considered to maximize the mobile abilities, enhance the environmental adaptability and improve the reliability of hydraulic system. Firstly, maximizing the mobile abilities includes optimizing the configuration of each actuator and integrating them with the structure, so as to achieve a large range of movement and also reduce the mass and inertia of the legs. Secondly, the environmental adaptability can be ensured with a magnetorheological (MR) fluid-based damper and direct-drive wheels. Thirdly, improving the reliability of hydraulic system involves using the selective laser melting (SLM) technology to integrate hydraulic system and reducing the number of exposed tubes. The maneuverability of the WLR is demonstrated with a series of experiments. At present, the WLR can perform the following operations, including moving on the flat ground, squatting, and picking up a heavy load.
Predicting Part Affordances of Objects Using Two-Stream Fully Convolutional Network with Multimodal Inputs

For a robot to manipulate an object, it has to understand the functions and the actions that can be subjected to the object. This set of information is known as affordance of the object. Affordances are generally defined by the geometrical structures and physical properties of the objects. In this paper, we present an affordance detection network (ADNet) for detecting object affordances using multimodal input i.e., RGB-D data. The method is based on the state-of-the-art fully convolutional network with two encoding streams and one decoding stream. In the presented formulation, the network learns powerful discriminative features independently from the RGB and depth images, which enables it to abstract rich photometrical and geometrical properties of the objects. The multimodal encoding is combined at multiple stages of the network using the late-fusion strategy and used is for predicting the potential affordances of the objects.
Robotic Hand-Free-Stick for Walking Balance Assistance

This paper proposes a wearable robotic stick for walking assistance, called “Hand-Free-Stick” (HFS), for people with non-serious dysfunction in their gait. The basic idea of the proposed HFS is to enlarge ZMP (Zero moment point) area of a user under hands free conditions and to augment his/her body balance ability in walking. A boots type prototype of the HFS is developed with a lightweight robotic stick using a servomotor, in which the slider-link mechanism works to regulate the stick angle and length at the same time. The stick motion is controlled by a single-board computer based on the distribution of foot/feet pressures measured by the sensor system using eight load cells attached at the sole of boots. A set of walking tests with/without the prototype of HFS is carried out for four healthy subjects and demonstrates the effectiveness of the proposed HFS to expand the ZMP area leading to walking balance assistance.
Contact Force Control of an Aerial Manipulator in Pressing an Emergency Switch Process

The dangerous work situation in industrial leakage accidents urgently needs a flexible and small robot to help workers perform operations and to protect them from being injured. An aerial manipulator system consisting of a hexa-rotor UAV and a one-DOF manipulator is developed, and is used to press an emergency switch to shut off machinery in an emergency. In practical application, an aerial manipulator usually performs contact operations as the UAV platform is in hover flight. The hovering UAV acting as a spring-mass-damper system is firstly proved. Then, based on the derived spring-mass-damper system model and the impedance control algorithm, the force-sensorless contact force control method is presented. That is, the force is indirectly controlled through controlling the UAV's position error and pitch angle simultaneously. The practical operation experiment of pressing an emergency button shows that the proposed method is able to control the contact force as the aerial manipulator interacts with the external environment.
UVBond: Strong User Binding to VMs for Secure Remote Management in Semi-Trusted Clouds

In Infrastructure-as-a-Service (IaaS) clouds, remote users access provided virtual machines (VMs) via the management server. The management server is managed by cloud operators, but not all the cloud operators are trusted in semi-trusted clouds. They can execute arbitrary management commands to users' VMs and redirect users' commands to malicious VMs, which is called the VM redirection attack. The root cause is that the binding of users to VMs is weak. In other words, it is difficult to enforce the execution of only users' management commands to their VMs. In this paper, we propose UVBond for strongly binding users to their VMs to solve this problem. UVBond boots user's VM by decrypting its encrypted disk inside the trusted hypervisor. Then it issues a VM descriptor to securely identify that VM. To bridge the semantic gap between high-level management commands and low-level hypercalls, UVBond uses hypercall automata, which accept the sequences of hypercalls issued by commands. We have implemented UVBond in Xen and confirmed that a VM descriptor and hypercall automata prevented attacks and that the overhead was not large.
Skating with a Force Controlled Quadrupedal Robot

Traditional legged robots are capable of traversing challenging terrain, but lack of energy efficiency when compared to wheeled systems operating on flat environments. The combination of both locomotion domains overcomes the trade-off between mobility and efficiency. Therefore, this paper presents a novel motion planner and controller which together enable a legged robot equipped with skates to perform skating maneuvers. These are achieved by an appropriate combination of planned reaction forces and gliding motions. Our novel motion controller formulates a Virtual Model Controller and an optimal contact force distribution which takes into account the nonholonomic constraints introduced by the skates. This approach has been tested on the torque-controllable robot ANY mal equipped with passive wheels and ice skates as end-effectors. We conducted experiments on flat and inclined terrain, whereby we show that skating motions reduces the cost of transport by up to 80 % with respect to traditional walking gaits.
Rhonda: the architecture of a multilingual speech-to-speech translation pipeline

Speech-to-speech translation can be described as converting a speech signal from a source language into a speech signal of the same meaning or intent into a target language. This process is achieved by the coordinated cooperation of individual Human Language Technology components, where the most important components to a speech translation system are automatic speech recognition, machine translation and text-to-speech. In this paper we present and discuss the design and architectural building blocks of the Rhonda speech-to-speech translation system, as well as their interactions with each other to facilitate speech-to-speech translation in a reliable, scalable and possibly distributed manner.
Stability and robust stability of switched positive linear systems with all modes unstable

This paper is concerned with the stability and robust stability of switched positive linear systems ( SPLSs ) whose subsystems are all unstable. By means of the mode-dependent dwell time approach and a class of discretized co-positive Lyapunov functions, some stability conditions of switched positive linear systems with all modes unstable are derived in both the continuous-time and the discrete-time cases, respectively. The copositive Lyapunov functions constructed in this paper are time-varying during the dwell time and time-invariant afterwards. In addition, the above approach is extended to the switched interval positive systems. A numerical example is proposed to illustrate our approach.
Bit Error Rate Mitigation in VANETs Using FFH-OFDM Pre-coding Approach

VANET (Vehicular Ad-hoc Network) is based on IEEE 802.11p standard. It is designed for Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems purposely for safety, infotainment and traffic management. Nevertheless, due to mobility of communicating nodes, V2V and V2I networks are susceptible to higher errors rates. This is because of Doppler effects on signals caused by relative velocities between communicating vehicles (V2V) or between vehicles and fixed receivers along the pathways (V2I). This paper investigates and proposes the use of fast frequency hopping orthogonal frequency division multiplexing (FFH-OFDM) pre-coding approach to mitigate higher BER associated with Doppler spread in VANETs. FFH-OFDM communication system and Doppler spread channel are modeled and simulated using MATLAB MEX functions and Simulink subject to VANETs standard parameters. BER curves are used as performance metrics for comparison between conventional OFDM and FFH-OFDM models. Under same Doppler spread, simulation results depicted better error performance for FFH-OFDM Pre-coding approach compared to conventional OFDM.
Roughening Particle Filter Based Prognosis on Power MOSFETs Using ON-Resistance Variation

Prognosis on microelectronics devices has gained wide attention due to its usability in wide range of applications. In this work, we have explored the degradation of Power MOSFETs due to thermal cycling and used the ON-resistance variation as the failure precursor for prognosis. The particle filter algorithm has been adopted for this purpose and the drawbacks of these algorithms such as particle degeneracy and particle impoverishment have been dealt with. An independent Gaussian jitter noise is purposely added to the resampled particle with the intention of roughening. The results indicate an improvement in accuracy over the standard particle filter algorithm. The impact of different degrees of roughening on the accuracy of RUL prediction is explored and the performance is evaluated using prognostic metrics such as relative accuracy and computational time.
FallDroid: An Automated Smart-Phone-Based Fall Detection System Using Multiple Kernel Learning

Common fall occurrences in the elderly population pose dramatic challenges in public healthcare domain. Adoption of an efficient and yet highly reliable automatic fall detection system may not only mitigate the adverse effects of falls through immediate medical assistance, but also profoundly improve the functional ability and confidence level of elder people. This paper presents a pervasive fall detection system developed on smart phones, namely, FallDroid that exploits a two-step algorithm proposed to monitor and detect fall events using the embedded accelerometer signals. Comprising of the threshold-based method and multiple kernel learning support vector machine, the proposed algorithm uses novel techniques to effectively identify fall-like events (such as lying on a bed or sudden stop after running) and reduce false alarms. In addition to user convenience and low power consumption, experimental results reveal that the system detects falls with high accuracy (<inline-formula><tex-math notation="LaTeX">$97.8\%$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$91.7\%$</tex-math></inline-formula>), sensitivity (<inline-formula><tex-math notation="LaTeX">$99.5\%$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$95.8\%$</tex-math></inline-formula>), and specificity (<inline-formula><tex-math notation="LaTeX">$95.2\%$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$88.0\%$</tex-math></inline-formula>) when placed around the waist and thigh, respectively. The system also achieves the lowest false alarm rate of 1 alarm per 59 h of usage, which is best till date.
Remaining Useful Life Estimation in Prognostics Using Deep Bidirectional LSTM Neural Network

Remaining Useful Life (RUL) estimation plays a crucial role in Prognostics and Health Management (PHM). Traditional RUL estimation models are built on sufficient prior knowledge of critical components degradation process which is not easily available in most situation. With the development of integrated circuit and sensor technique, data-driven approaches show good potential on RUL estimation. This paper proposes a new data-driven approach with Bidirectional Long Short-Term Memory (BiLSTM) network for RUL estimation, which can make full use of the sensor date sequence in bidirection. By visualized analysis of the hidden layers, the model can expose hidden patterns with sensor data of multiple working conditions, fault patterns and degradation model. With experiment using C-MAPSS dataset, BiLSTM approach for RUL estimation outperforms other traditional approaches for RUL estimation.
Analytically-Guided Design of a Tailed Bipedal Hopping Robot

We present the first fully spatial hopping gait of a 12 DoF tailed biped driven by only 4 actuators. The control of this physical machine is built up from parallel compositions of controllers for progressively higher DoF extensions of a simple 2 DoF, 1 actuator template. These template dynamics are still not themselves integrable, but a new hybrid averaging analysis yields a conjectured closed form representation of the approximate hopping limit cycle as a function of its physical and control parameters. The resulting insight into the role of the machine's kinematic and dynamical design choices affords a redesign leading to the newly achieved behavior.
Simultaneous End-User Programming of Goals and Actions for Robotic Shelf Organization

Arrangement of items on shelves in stores or warehouses is a tedious, repetitive task that can be feasible for robots to perform. The diversity of products that are available in stores and the different setups and preferences of each store makes pre-programming a robot for this task extremely challenging. Instead, our work argues for enabling end-users to customize the robot to their specific objects and setup at deployment time by programming it themselves. To that end, this paper contributes (i) a task representation for shelf arrangements based on a large dataset of grocery store shelf images, (ii) a method for inferring goal configurations from user inputs including demonstrations and direct parameter specifications, and (iii) a system implementation of the proposed approach that allows simultaneously learning task goals and actions. We evaluate our goal inference approach with ten different teaching strategies that combine alternative user inputs in different ways on the large dataset of grocery configurations, as well as with real human teachers through an online user study $\pmb{(\text{N}=32)}$. We evaluate our full system implemented on a Fetch mobile manipulator on eight benchmark tasks that demonstrate end-to-end programming and execution of shelf arrangement tasks.
Defect Search Using the Input Signal Position Change And the Binary Diagnostic Sign1

Article deals with research problem of an algorithm for single defect search in a continuous dynamic system of an automatic control class with depth up to a dynamic block is considered on the basis of a position change of the input signal based on integral estimates of signal deviations of model and object using a binary diagnostic sign for the presence of a defect. This approach simplifies the implementation of the algorithm, especially in the diagnosis of non-linear objects. The use of position change of the input signal can reduce the hardware or software costs associated with the implementation of sensitivity functions or trial deviations of model parameters and simplicity of the algorithm calculating the normalized diagnostic sign. The results of the implementation of the algorithm, showing its effectiveness and to ensure high distinction of the defects.
The Multi-scale method for solving nonlinear time space fractional partial differential equations

In this paper, we present a new algorithm to solve a kind of nonlinear time space-fractional partial differential equations on a finite domain. The method is based on B-spline wavelets approximations, some of these functions are reshaped to satisfy on boundary conditions exactly. The Adams fractional method is used to reduce the problem to a system of equations. By multi-scale method this system is divided into some smaller systems which have less computations. We get an approximated solution which is more accurate on some subdomains by combining the solutions of these systems. Illustrative examples are included to demonstrate the validity and applicability of our proposed technique, also the stability of the method is discussed.
Design and Fabrication of Micro-Hall-Effect Sensors

The objective of this study was to design and fabricate Hall-effect sensors utilizing microelectromechanical system technology. The proposed sensor structure comprises a P-type silicon substrate, a SiO2 isolation layer, a phosphorus ion implanted layer, and gold wires. Three types of Hall-effect sensors were designed and fabricated: square, cross, and square-cross-end types. During the fabrication of the Hall-effect sensors, an ion implanter was first utilized to implant phosphorus ions in the silicon substrate. Subsequently, the defected atoms were restored by annealing. Finally, gold wires were deposited as electrical leads through electron beam evaporation. When the fabricated sensor was brought into the vicinity of a magnet, its magnetic field changed due to the Hall effect caused by moving carriers. A Hall voltage could thus be measured. As the magnetic field increased, the Hall voltage increased. The cross-type Hall-effect sensor outperformed the other types.
LiDAR-Based Object Tracking and Shape Estimation Using Polylines and Free-Space Information

Reliable object perception is a vital requirement for automated driving. Despite the availability of precise contour measurements, most state-of-the-art tracking systems still represent object geometry as bounding boxes. However, there are objects operating in public traffic for which the box assumption is highly inappropriate. We therefore propose to represent object contours using 2D polylines. Taking into account the mutual dependence of object poses and shape, our tracking framework targets at a simultaneous estimation of both states. Moreover, we propose to augment scan segments with free-space information at their boundaries and show how this knowledge can be incorporated into the tracking framework and beyond. Evaluation with real scan data shows that our method produces accurate dynamic estimates and consistent shape reconstructions.