Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization Method for Autonomous Car Using Virtual Sensing System

The combination of the Inertial Measurement Unit (IMU) and Global Navigation Satellite System (GNSS) is widely used in the localization of autonomous cars. However, GNSS is highly dependent on external conditions and has a low sampling rate. In order to make the localization of autonomous cars more reliable in various external conditions, a virtual sensing system using Error-state Kalman Filter (ESKF) and Diagonal Recurrent Neural Network (DRNN) approach is proposed in this paper. In this proposed system, DRNN served as a predictor for the location of an autonomous car. DRNN is applied due to its independency against the external conditions, the ability to learn, and also its faster sampling rate compared to the global navigation system. Implementation and testing of this new approach using the CARLA Simulator show that the proposed system could correct the deviation caused by the absence of absolute position measurement. With further developments and improvements, this alternative sensing method would be able to replace the existing GNSS and unlock the possibility for offline localization.
Low-Latency Interactive Sensing for Machine Vision

In this paper, we introduce the low-latency interactive sensing and processing solution for machine vision applications. The event-based vision sensor can compress the information of moving objects in a cost-effective way, which in turn, enables the energy-efficient and real-time processing in various applications such as person detection, motion recognition, and Simultaneous Localization and Mapping (SLAM). Our results show that the proposed technique can achieve superior performance than conventional methods in terms of accuracy and latency.
An innovative visuolocomotor training program for people on waiting list for vestibular rehabilitation

Dizziness and imbalance are debilitating symptoms of vestibular dysfunction (VD) that can be treated through vestibular rehabilitation. The C-Mill ForceLink treadmill (C-Mill) allows for the integration of virtual reality and cognitive dual-tasking during treatment. No research has been conducted on its use in vestibular rehabilitation. The purpose of this pilot study was to develop a visuolocomotor training protocol on the C-Mill for individuals with VD, and to establish feasibility of both future research on, and clinical use of, this protocol to improve symptoms of dizziness and imbalance in individuals with VD who were on the waiting list for vestibular rehabilitation to undergo 10 one-hour sessions on the C-Mill. The Dizziness Handicap Inventory (DHI), Visual Vertigo Analog Scale (VVAS), and Functional Gait Assessment (FGA) were used as outcome measures, in conjunction with subjective reports. Nine participants completed the study, 55% demonstrated improvement in all outcome measures as well as subjective reports, while 0% digressed. The average percent of improvement from defined baseline to follow-up was 42.43% for the DHI (standard deviation (SD)=23.82%), 54.59% for the VVAS (SD=31.95%) and 21.89% for the FGA (SD=33.64%). Results support the use of the C-Mill as an intervention for patients on a waiting list with VD under the supervision of a physiotherapist. A larger and more comprehensive study is feasible in order to further investigate the effects of this protocol on symptoms of dizziness and imbalance in individuals with VD.
Insight into the Importance of Fog Computing in Internet of Medical Things (IoMT)

Low latency, real-time interaction, geographical distribution, heterogeneity, and wireless access are some characteristics required in the medical/healthcare system for providing better Quality of Services (QoS). This was satisfied by the new emerging term Fog Computing. Internet of Technology (IoT) technology brings many challenges along with facilities it provides. Initially, Cloud computing was used to store data but due to many provocations an intermediate layer namely Fog layer is introduced. Fog computing is the joining layer between connected edge devices and the cloud in the IoT. Where Cloud services lack to provide enough benefits in IoT, Fog layer suffice all that services. This paper scrutinizes the implemented work based on the application, hardware, and software used.
Design of Virtual Reality Teleoperation System for Robot Complex Manipulation

With the expansion of robotics application fields, robot always faces unpredictable manipulation tasks in hazardous and unstructured environments. Compared to tradition programming and robot learning methods, teleoperation approaches shows great potential in assisting the operator to perform and accomplish complex and uncertain tasks. In order to achieve the goal of manipulating complicated tasks with high accuracy, stability, and convenience, in this paper, we design a robot teleoperation system based on virtual reality device. Our designed system converts the motion information of the VR hand controller into the motion information of the end-effector of a robot arm, realizing the goal of teleoperating robot arm to manipulate complicated tasks, and concurrently viewing the robot working scenarios in real time with headset. Experiments show that our designed system can efficiently perform complicated manipulation tasks with high accuracy and stability, which shows great potential in accomplishing complex tasks and expanding our teleoperation system in more application areas.
Three Phase Multi-Level Inverter Topologies and Modulation Techniques: A Short review

In this paper recently proposed three-phase multi-level inverter topologies and modulation techniques are discussed. Multilevel inverter topologies (MLIs) are more utilized in high-medium power applications due to their several benefits such as less harmonic contents, less power dissipation on power switches and less electromagnetic interference (EMI) outputs. For harmonic elimination, the chosen switching method for inverter control is also a plays a significant role to produce the ideal output voltage. In this, mainly three different topologies are categorized in MLIs; those are diode clamped, flying capacitors and cascaded H-Bridge. Similarly, different H-Bridge inverter topologies and control techniques also discoursed. In this paper mainly focused on three-phase inverter using a single DC source and transformers. The various carrier based modulation techniques such as phase disposition (PD), Phase Opposite Dispostion (POD) and Alternate Phase Opposite Dispostion (APOD) have been invstigated through MATLAB/Simulink environments.
Spreadsheet Smells: A Systematic Mapping Study

Spreadsheets provide a very flexible programming environment and are used by almost every organization, company, institution or business for data processing and data storage tasks. The main objectives of this research are: (1) to have an overview of the research that is being done related to spreadsheet smells; (2) to classify the spreadsheet smells research according to ten criteria: techniques, year of publication, publication venues, publication channels, datasets, countries, contribution type, research approaches, tools used, tools/techniques proposed; and (3) analyze studies from different perspectives like study objectives, methods, method accuracy and limitations. We performed a systematic mapping on the spreadsheet smells studies published in the time span of 2010-2019, and adopted proper methods to classify, review and analyze them. In total, we were able to identify 28 studies and map the results of these studies.
On Low Rank Approximation Of 3-Tensors Based On Regularized t-SVD

In recent applications, regularization becomes an increasing trend. Regularized SVD has been studied by many leading experts in machine learning. Recently, Misha E. Kilmer and Carla D. Martin introduced t-SVD of 3-tensors, which has many advantages than old definitions of tensor SVD. In this paper, we present a regularized t-SVD (Rt-SVD) for 3tensors, present a regularized t-SVD (Rt-SVD) and an efficient computational algorithm.
Multi-level Voltage Interaction Control in Active Distribution Network Based on MPC

With more and more photovoltaic generations integrated into different voltage level distribution networks, the interaction between the various voltage levels of the distribution network is more complicated. A multi-level voltage interaction control method for active distribution network based on model predictive control (MPC) is proposed in the paper. This method considers on-load tap changers (OLTC) and shunt capacitor banks (CB) future-time action plan, and the uncertainty exchange power and their mutual influence. Finally, a case study is carried out in MATLAB and the results verify the effectiveness and feasibility of the proposed approach
Field-Free Switching of Perpendicular Magnetization through Voltage-Gated Spin-Orbit Torque

We experimentally demonstrate the field-free and ultra-low-power switching of perpendicular magnetization by combination of spin-orbit torque (SOT), exchange bias (EB) and voltage-controlled magnetic anisotropy (VCMA) effect. Field-free SOT switching is achieved with the aid of an inplane exchange bias generated in the perpendicularly magnetized IrMn/CoFeB/MgO structure. By applying a gate voltage of 0.6 V, the SOT switching current can be reduced by 49% (to 6.2 MA/cm2). Finally, we successfully demonstrate the prototype of a high-density and ultra-low-power voltagegated spintronic memory by both experiments and simulations.
Premixed Calcium Phosphate Cement for Extrusion-based 3D Printing: Planetary Centrifugal Mixer and Homogeneity Evaluation

Self-setting calcium phosphate cement (CPC), used in orthopedic surgery for bone replacement, usually consists of the powder mixture and setting liquid (aqueous) or carrier liquid (non-aqueous). After mixing two-phase compounds, the injectable viscous solution was formed and able to mold into the desired shape of the bone. The heterogeneous mixture, however, affects the dissolution-precipitation reaction ending in the unwanted chemical products, the deformed shape of solidified materials, and the undesired mechanical properties. In addition, the debris of heterogeneity increased the clogged needle probability when extruding with the cartridge of the 3D printer. In order to overcome these sort of problems and refine the homogeneity of CPC, the blade-free planetary mixer was used. Herein, the planetary centrifugal mixer was developed to increase the homogeneity of the CPC mixtures in batch production. The preliminary study of characteristics of the mixer, the revolution speed, centrifugal acceleration (1-66G), and their relations, was reported. The homogeneity of a CPC mixture was tested into two parts: the mixings of the powder-powder compound, and the powder-liquid paste. ImageJ, Fiji bundles, was used to evaluate the homogeneity of the mixture. The centrifugal acceleration of 16G and 66G homogeneously mixed a 1.2g of CaCO3/Orange Red 735 and a 1.5g of αTCP/Glycerine respectively within 3 minutes. This study intentionally contributed to the fields of bio-printing and biofabrication, especially artificial bone, by improving the mixing process of the bone cement formula and demonstrating the idea for industrializing the bone cement into the commercial product.
Soft-VAN: Mobility-Aware Task Offloading in Software-Defined Vehicular Network

In this paper, we propose a mobility-aware task offloading scheme, named as Soft-VAN, with an aim to minimize task computation delay in a software-defined vehicular network. The proposed scheme consists of two phases — fog node selection and task offloading. In the first phase, we formulate an integer linear program (ILP), and solve the problem to get optimal number of fog nodes required for a given network. In the task offloading phase, we formulate an optimization problem to minimize overall delay in task computation, while considering associated constraints. As finding optimal solution to the problem is NP-hard, we propose a greedy heuristic approach in two phases — task offloading and computed task downloading — to solve it in polynomial time. The greedy solution for offloading takes into account network delay, flow-rule capacity, and link utilization. On the other hand, the solution for computed task downloading considers vehicle's mobility in addition to the parameters associated with the offloading decisions. Experimental results show that the proposed scheme, Soft-VAN, is capable of enhancing the performance approximately by 30%, 45%, and 50% in terms of delay compared to state-of-the-art schemes — Detour, DAGP, and SD2O, respectively.
Analysis of the Macroeconomic Uncertainty Based on the News-based Textual Data with Financial Market

The uncertainty in the financial market, whether US-China trade war will slow down global economy or not, Federal Reserve Board (FRB) policy to increase the interest rates, or other similar macroeconomic events can have a crucial impact on the purchase or sale of financial assets. In this study, we aim to build a model for measuring the macroeconomic uncertainty based on the news text. Further, we proposed an extended topic model which uses not only news text data but also numeric data as a supervised signal for each news article. Subsequently, we used our proposed model to construct four macroeconomic uncertainty indices. All these indices were similar to those observed in the historical macroeconomic events, and the correlation was higher with the volatility of the market index with respect to the uncertainty index. We also applied the impulse response function to analyze the impact of the uncertainty indices on financial markets.
Soft Sensor Method Based on Deep Belief Network for Rotor Thermal Deformation of Rotary Air Preheater

In this paper, to detect the rotor thermal deformation of rotary air preheater, a soft sensor method based on Deep Belief Network (DBN) is proposed. The rotor thermal deformation of rotary air preheater can be accurately detected by the proposed method, so the air leakage of rotary air preheater under the harsh working environment can be well controlled. In the study, latent variables which are closely related to rotor thermal deformation are obtained by grey relation analysis method. Then, DBN network is trained by using labeled data and unlabeled data, in which the features in the data set are extracted by DBN module. The features extracted by DBN module are input Support Vector Regression (SVR) as input data. At the same time, Particle Swarm Optimization (PSO) algorithm is used to select the appropriate parameters for SVR. SVR is used as the predictor of the continuous target change value in the soft sensor model. The new soft sensor model of rotor thermal deformation is obtained by the superiority of DBN and SVR algorithms. Simulation result shows that the identification accuracy of this new model is higher, and the prediction of rotor thermal deformation is accurate, so it can predict the output well.
Acoustic Source Tracking in Reverberant Environment Using A Novel PSO Particle Filter Framework

In this paper, several methods are combined together and applied to a Particle Filter based on Particle Swarm Optimization acoustic source tracking framework in order to solve some problems of sound source tracking. The Time Difference of Arrival (TDOA), which is extracted from the audio signal received by the microphone pair, makes observations. The Langevin Model is used to describe the speaker’s motion characteristics. The pseudo-likelihood function is constructed by using the Global Coherence Field (GCF) function to update the particle weight, in order to solve problem of the phenomenon of spurious source due to noise and reverberation. According to the iterative process and particle flight conditions, the inertial weights of the particles are adjusted nonlinearly and dynamically. The concepts of superior flight speed and inferior flight speed are introduced to Particle Swarm Optimization, which helps jump out of local optimum and solves the problem of lack of particle diversity. Thus, the faster tracking of sound source is realized. In the framework, with fewer particles, the robustness of tracking is enhanced and accuracy of tracking is improved. Finally, the effectiveness of this framework for acoustic source tracking is verified through several Monte Carlo simulation experiments.
Comparison of Permanent-Magnet Assisted Synchronous Reluctance Motors with Different Rotor Structures

This paper presents a comparison of synchronous reluctance motors with different rotor structures which are assisted with or without permanent magnets. Firstly, a conventional synchronous reluctance motor (SynRM) structure was designed in order to obtain a base motor structure for the other motors designed in this study. Then, three different motor types were designed by using the base motor structure which has 9 stator slots and 4 flux barriers on the rotor. The ceramic magnets were placed in different positions of the rotor flux barriers. The performances of the designed SynRM and PMa-SynRMs were analyzed in terms of torque, speed and efficiency. In addition, the flux distributions of designed motors were analyzed by using MotorSolve program. The effects of the position and amount of the magnets on the rotor flux barriers were analyzed for designed rotor structures.
State Feedback Regulation of Nonlinear Systems with Unmodeled Dynamics

This paper studies the state feedback control problem for a class of nonlinear systems with integral input-to-state stability (iISS) unmodeled dynamics and unknown control direction. By using the properties of iISS and the backstepping technique, the design function of the state feedback controller and the updating rule of parameters are selected to obtain the appropriate controller. Theoretical analysis proves that the designed controller can ensure that all signals of the system are bounded and the state can be gradually adjusted to zero. Simulation results show the effectiveness of the proposed method.
Future level of distribution system operator's involvement in spread of microgrid technologies: a review

The increasingly spreading household-scale renewable energy generation can create voltage problems, overloads, and other system operational issues mainly on the low voltage network. These problems cannot be handled economically effective with traditional network operation and maintenance solutions. Aim of this paper is to give an expert analysis in consideration of possible new technologies from system operator point of view bearing in mind the regulatory environment. Analytical methods and simulation were used to evaluate the effects of these technologies and trends. 14 network effects and 9 different technologies were examined. As a result a revised microgrid definition will be introduced and 5 proposed interventions are formulated.
Emotion Recognition Using EEG Signal Based on Support Vector Machine and Highly Reliable Validation Set

This work aims at building robust model for human mental state classification using EEG signals. We elaborated a highly reliable data validation set for emotion detection and chose support vector machine (SVM) as the classifier. The results of classification were evaluated by the characteristics observed on the output probability curve. The average accuracy and the maximum accuracy among the subjects of the proposed model achieved 78.28% and 97.50% respectively for the binary-class task.
High Throughput Hardware Implementation for Deep Learning AI Accelerator

In this paper, a high-throughput hardware accelerator for deep learning neural networks is proposed. Since deep learning operations require high data access from DRAM, we design a high data reuse architecture to reduce the data access directly from external DRAM and provide a pipeline scheme to achieve high throughput requirements. The architecture proposed in this paper uses INT8 precision computing, 128-bit AXI bus protocol, and parallel processing with 16 sets of processing units, and achieved real-time operation at 125 MHz operating frequency and 8GOPS throughput.
Compiler-Based High-Level Synthesis of Application-Specific Processors on FPGAs

In order to meet tight performance and/or energy constraints of embedded systems, the implementation of applications in hardware is often a must. However, mapping of algorithms to platforms, as for example Field-Programmable Gate Arrays (FPGAs), still requires comprehensive hardware knowledge and sometimes long design cycles. Modern High-Level Synthesis (HLS) offers a means to ease the generation of hardware implementations from a software specification of an application. Although these tools have improved greatly in recent years, they often do not provide full coverage of important programming constructs and are therefore of limited use when used with existing or automatically generated code. Soft-core processors implemented with FPGA-logic can circumvent this limitation. However, these come with drawbacks in terms of performance and resource requirements as a general-purpose architecture is used to implement the application in software rather than as a highly specialized circuit. As a remedy, our work presents a novel compiler-based synthesis methodology that generates networks of Application-Specific Instruction Set Processors (ASIPs) from unmodified C/C++ algorithms. We thereby bridge the gap between traditional soft-core processors and HLS. To show the practicability of our approach, we present a case study of a JPEG decoder application while investigating design objectives like resource costs and performance. Apart from the generality of the compiler-based approach, our approach also shows better results in terms of required hardware resources and execution times compared to Instruction Set Architecture (ISA)-fixed commercial Xilinx MicroBlaze soft-cores.
Study of Routing Protocols in MANET-A Review

MANET is an infrastructure less network. MANET is a multi-hop architecture, here nodes are connected with links and these nodes are mobile in nature. Therefore, the topology of the network is not fixed and communication between nodes appears as a real challenge. Due to lack of well-defined communication structure for an end to end communication in MANET, an appropriate communication structure is needed. Routing Protocols are used for an establishment of communication structure among nodes. Now days a number of researcher is attracted towards this field for their research. Therefore, many protocols are already introduced for MANET by researchers. Routing protocols are responsible for efficient delivery of messages among mobile nodes while focusing on the use of limited resources. Routing protocols are basically bifurcated as Table Driven (Proactive)routing protocols and On-Demand (Reactive) routing protocols. This review paper reviews the useof particular routing protocol according to an appropriate network. So it can use the limited resources efficiently. In this review paper comparison among different routing protocols is done, which helps researchers to take routing decision. This review paper also helps the new researchers to understand all existing protocols and provide important information that which protocol can be used under which network scenario.
E-Bike System Modeling and Simulation

A mathematical model of an electric bike (e-bike) developed in the MATLAB/Simulink environment is being discussed in this paper. The subsystem models, motor (permanent magnet synchronous motor), the controller(field oriented control) and battery (lithium ion) associated with the e-bike system has been separately detailed. Vehicle dynamics associated with the bicycle has also been studied to provide the required road reaction for correct simulation. The performance of the e-bike for two different slopes and different assist levels has been checked through simulation. The results show that the motor provides required assistance as set by the rider thereby providing both the advantages of exercise as well as extra aid from the motor.