Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fog-based Reputation Evaluation Model for VANETs

Fog computing can play an important role in Vehicular Ad Hoc Networks (VANETs) in enhancing the quality of fog-based services. The idea of partial reliance on fog computing to support the existing infrastructure has been explored in few research papers. Fog computing holds the promise of significant potential benefits to edge users. The capabilities of fog and its position (i.e., the proximity from edge users) give fog the power to play a vital role in employing the most competent node. In other words, fog can reduce the workload that is required to do by the vehicles (e.g., propagating the event’s details, and evaluating the trust of the sender). In this paper, we deploy fog nodes to gather the trust evaluations from the vehicles, which allow fog nodes to rely on their local vehicles to do certain tasks. Also, fog nodes are used in this work to keep the records of its local vehicles to reduce the need to communicate with the cloud. Also, we proposed a scheme using Task-based Experience Reputation (TER), which reflects the vehicle’s reputation in performing certain tasks. Finally, we shed the light on the issue of two commonly used trust updating methods and, we proposed applying the concept of TER to solve this issue. The proposed model reduces the message transmission overhead and workload on the vehicles compared to experience-based trust models.
Area Efficient Built-In Redundancy Analysis using Pre-Solutions with Various Spare Structure

Built in redundancy analysis (BIRA) with the various spare structure is proposed to achieve higher memory yield [1]. However, various spare structures have caused the large hardware overhead. In this paper, an area efficient BIRA is proposed which uses separate CAMs for fault collection to reduce the hardware overhead and the pre-solutions searching the most appropriate addresses of various spares for redundancy analysis. The experimental results show that the proposed BIRA can achieve the higher repair rate compared to the previous works.
Efficient Signal Processing Acceleration using OpenCL-based FPGA-GPU Hybrid Cooperation for Reconfigurable ECG Diagnosis

With the development of Internet of things (IoT), where humans and machines interact, healthcare that measures and diagnoses bio-signals is advancing. The electrocardiogram (ECG) signal has different normal beat characteristics for each person, and it requires long-term data for detecting abnormalities. In this paper, we increased the detection rate of the normal signals by learning the reference signal, which is the standard for diagnosing ECG signals, as individual-specific signals from existing fixed data. In addition, we proposed an OpenCL-based FPGA-GPU hybrid cooperative platform to efficiently diagnose long-term, large-capacity ECG signals.
Nonlinear Fault-Tolerant Control of a Quadrotor UAV Based on Sliding Mode Control Technique

Abstract In this paper, a sliding mode based fault-tolerant control (SM-FTC) is designed, implemented and tested in a quadrotor unmanned small helicopter under the propeller damage and actuator fault conditions. Based on the concept of sliding mode control, both passive and active fault-tolerant control laws have been designed and experimentally testbed on a quadrotor UAV (unmanned aerial vehicle) testbed available at Concordia University. These two types of controllers are carried out and compared through both theoretical analyses and experimental tests on the quadrotor UAV system.
Internet Information Security towards Various Advanced Needs Of Human Society

In this research paper we will discuss about Internet which has become the information super highway. The evolving Internet and its related technologies have allowed businesses to communicate in new and strategic ways with various types of people and organizations. Over the years, there have been additions of feature upon feature to the Internet connections. As the needs have changed, human beings have come across the need of more robust services, faster connections, and more flexibility in what can be done. In the beginning, services like simple POP3-style email and Web access were the extent of an Internet connection. Today we have site-to-site Virtual Private Networks (VPNs), client-side and home-user VPNs, streaming media, Web-based training, exciting Internet applications, e-commerce, and business-to- business extranets. Thus the Internet evolves towards fulfilling various advanced needs of human society.
Low Energy and Error Resilient SOT-MRAM based FPGA LUT Cell

As process technology scales down, large standby power has become one of the critical issues for SRAM-based Lookup-Table (LUT). Recently, spin-orbit torque magnetic random access memory (SOT-MRAM) has become a promising candidate to replace SRAM based LUT. Thanks to its non-volatile characteristic, SOT-MRAM is expected to reduce power consumption. But, high write energy and read reliability issue are still large concern. In this paper, we propose a novel SOT-MRAM-based LUT cell using two transistors and a shared inverter. By removing cascading MUX from both read and write paths, we can reduce the write energy and improve the read reliability. HSPICE circuit simulations using the 65nm process show over 50 % of write energy savings compared to the state-of-the-art SOT-MRAM-based LUT.
In-fiber Michelson interferometer based on double-cladding fiber for refractive index sensing

An in-fiber Michelson interferometer is proposed based on a double-cladding (DC) special fiber. With the DC special fiber, light wave can be partially coupled into outer cladding. The in-fiber Michelson interferometer can be constructed by splicing a length of DC fiber into standard single mode fiber (SMF). The interferometer is very sensitive to ambient refractive index change because fiber cladding is as one of interference arms. A sensitivity of 36nm/RIU has been achieved in the range of 1.33~1.40 in this work. The proposed technique has the dominant advantage of simple fabrication process, which can be expected to have wide applications in biosensors and chemical sensors.
A Review on Recent Development of Input Impedance Boosting for Bio-Potential Amplifiers

Bio-potential signals like Electrocardiogram(ECG) and Electroencephalogram(EEG) are recorded routinely in modern clinical practice and daily life, providing helpful information for early diagnosis of disease. A very high input impedance (Zin) of the readout is crucial in emerging applications, e.g. drivers’ monitoring, embedded smart home heath monitoring. This paper gives a review on existing techniques including 1) positive feedback technique; 2) auxiliary path feedforward technique; 3) current feedback topology. This paper focuses on the development on each Zin boosting technique in recent years, like auxiliary capacitor assisted input buffer and current feedback topology with parasitic capacitance shielding of the input transistors, which help to achieve a reliable Gohm input impedance with minimum power consumption.
REACH MODELLING FOR DRIVE-UP SELF-SERVICE

People using a self-service terminal such as an aut omated teller machine (ATM) tend to adjust their physical position throughout a transaction. This is particularly apparent with terminals that are designed to be use d from a vehicle (i.e. drive-up automated teller machines or ATMs). Existing predictive tools tend to focus on static reach and provide limited predictions for ho w far people are willing to stretch to complete a task. Drive-up self-service p roducts have 3 main challenges; the variability of vehicles, people and driver beha viour. Such conventional tools are therefore of limited use in understanding how m uch people are willing to move to use a self-service terminal. Work is described to build in-house predictive mode ls based on 2 large empirical studies of reach in a drive-up installation. These 2 studies assessed comfortable and extended reach from 10 vehicle categories. Exte nded reach was defined as stretching/leaning as far as participants would nor mally be willing to in order to complete a drive-up transaction. Findings from thes e studies indicated that participants are prepared to adopt more extreme pos tures at drive-up than in other situations with extended reach at drive-up being si gnificantly different to what might be seen at a walk-up kiosk.
A Self Synchronized-Switch Rectifier for Piezoelectric-Vibration Energy-Harvesting Systems

In this paper, a high efficiency rectifier using a self-synchronized-switch technique for piezoelectric-energy harvesting system is proposed. By using the multiplexer to control the power transistors, we can not only obtain the same extraction efficiency of synchronized switch rectifier but also eliminates the need for an additional a large switch. As a result, the chip area can be saved. Implemented in 0.35-μm CMOS process, the proposed rectifier can provide the power efficiency of 90%.
Automatic Visual Inspection Machine for Pharmaceutical Infusion Bags Implementing Cellular Neural Networks

Automation procedures and machines in the pharmaceutical field are required to implement a series of methodologies, designed parting from international standards, in order to ensure the high quality of the products. Regarding infusion bags, the standards require to thoroughly assess the conformity of the product before being used in patients. The inspection procedures are usually operator-based and therefore subject to human factor errors. A novel inspection machine has been designed and developed with the use of a specifically designed cellular neural network (CNN) coupled with an off-the-shelf neural network trainable solution. The novel machine, thanks to the computational versatility of the CNN, is capable of reaching high standards of assessment drastically decreasing the risk of operator-based errors in the procedure.
Development of a Hand-Arm Model to Emulate Tremor Handwriting Behavior

Patients with hand tremor may find difficulties in performing their routine task especially writing. The worse when the tremor becomes severe. In this paper, a hand-arm model has been developed to study the behavior of tremor while performing handwriting. Regarding the study, the hand of patient oscillates in a perpendicular direction to the forearm rather than other directions due to hand support while the handwriting is performed. A miniature accelerometer patched to the writing device and acceleration data recorded have then been examined by power spectral density (PSD). For hand-arm model setup, the DC motor was used to emulate the hand movement to draw a straight line by connecting the linear screw thread to the writing mechanism. For writing mechanism, there are two parts, holder to hold the pen and Linear Voice Coil Actuator (LVCA) to resemble hand tremor conditions. By injecting tremor data to the LVCA the acceleration is measured once again by attaching a miniature accelerometer to the writer device. The findings show that the model can emulates hand tremor by considering its acceleration and frequency range from PSD based on record actual tremor data as references. The hand-arm model furthers can be a research conduct to design a writing device that can be cancelled or at least suppress the tremor.
Arabic Sentiment Analysis towards Feelings among Covid-19 Outbreak Using Single and Ensemble Classifiers

The need to study and analyze public opinions about the Corona virus (COVID-19) pandemic or about those preventive measures that are imposed, led to the emergence of many studies. These conducted studies have concerned the analysis of public feelings and opinions, known as sentiment analysis (SA). Taking a benefit of social media platforms such as Twitter a dataset of Arab people feelings, especially fear and anxiety, towards Covid-19 was built through surveying the Arabic content in this platform. A machine learning (ML) model was applied to analyze and categorize the tweets related to fear and anxiety regarding Covid-19 outbreak. In this model, the word2vec was employed for word embedding to form the vector of features with two CBOW pre-trained models CC.AR. 300 and Arabic.news. Moreover, the effect of the sampling technique that is called Synthetic Minority Over-sampling Technique and Edited Nearest Neighbors (SMOTENN) was investigated in this study. In addition, the performance of several single-based and ensemble classifiers were evaluated and discussed. The experimental results show that applying word embedding and SMOTENN with both single and ensemble classifiers achieve a good improvement in terms of F1 average score compared to the baseline, single and ensemble classifiers without SMOTENN.
High-accuracy and Low-latency Hybrid Stochastic Computing for Artificial Neural Network

Artificial Neural Networks (ANN) have shown their superiority in many applications of academia and industry. However, the hardware architecture of ANN requires a lot of operation units, which results in a high area and high-power overhead. On the other hand, the Stochastic Computing (SC) method has been proven as an efficient way to achieve low-power computing with a small area overhead. Therefore, many SC-based ANNs have been proposed in recent years. However, due to stochastic bit-stream computing, the conventional SC-based ANN designs suffer from low computing accuracy. In this work, we use the parallel counter (PC) to replace the SC-based multiply-accumulator (MAC) to solve the accuracy problem in conventional SC-based ANN designs. Besides, we propose a finite state machine (FSM)-based activation function to improve the efficiency of the data representation change in SC-based ANN computing. Compared with the conventional SC-based ANN designs, our proposed architecture can improve computing accuracy by 82.2%. Besides, our proposed architecture can reduce 95.8% area cost and 94.2% power consumption over than non-SC-based ANN design, which achieves higher hardware efficiency.
An Estimation Method for Controlling Unstable Periodic Orbit Without Using Poincaré Map

A method for estimating unstable periodic orbits in switched dynamical system is proposed. The proposed method consists of a simple algorithm that does not require numerical calculations such as the Newton method. The proposed method is explained using a switched dynamical system that simulates the switching operation of a current-controlled DC-DC converter as an example, and an application example is shown based on numerical simulation results.
Fast Automatic Circuit Optimization Using Deep Learning

With recent advances in deep learning, a wide range of automatic circuit optimization techniques have been recently reported. While the optimization algorithms such as reinforcement learning can be effectively accelerated on GPU, they still require numerous SPICE simulations for training. Running SPICE simulation is a time-consuming process and hence becomes the bottleneck in circuit optimization. Therefore, it is crucial to find a way to reduce the number of SPICE simulations required for circuit optimization. In this paper, we propose a method to minimize SPICE simulations in the circuit design automation process. Specifically, we develop a data augmentation method to increase the amount of training data without additional SPICE simulations, which results in faster circuit optimization.
On controlling multistability in memristor circuits

One of the appealing properties of memristor circuits is multistability, i.e., the coexistence in the state space of a large variety of different attractors. Since each attractor belongs to one of the infinitely many invariant manifolds in which the state space is decomposed, switching between different attractors requires to address the problem of steering the memristor circuits dynamics from one invariant manifold to another in a given time interval. For a fairly general class of circuits containing an ideal memristor it is shown that it is always possible to solve this problem via a pulse programmed source.
Heteroclinic cycles in Chua-Yang ring networks

Heteroclinic equilibrium connections in Chua-Yang ring networks with two-parameter nearest-neighbor coupling are investigated. The dynamics is governed by the standard piecewise linear saturated activation function. We look for heteroclinic cycles created by terminating families of Hopf periodic orbits. Our approach is based on numerical experimentation supported by rigorous a posteriori mathematical arguments.
High Performance and Area Efficient Ferroelectric FET based Reconfigurable Logic Circuit

The emerging nonvolatile memory (NVM)-based logic in-memory (LiM) structure can reduce power consumption caused by data transfer since it integrates memory and logic units very closely. The ferroelectric field-effect transistor (FeFET) is one of the promising candidates for NVM-based LiM structure owing to its unique characteristics: three-terminal structure and high ION/OFF ratio. In this paper, we propose the FeFET based reconfigurable logic circuit which can provide AND/OR/XOR logic value in a single circuit. Simulation results show that it can achieve a 67% lower transistor number, 17% faster delay, and 54% less energy than STT-MTJ based reconfigurable logic circuit.
A Comparative Study on the Variants of R Metric for Network Robustness

Robust network infrastructures are essential for the delivery of vital services for our daily lives. With the widespread cyber-attacks on them, measuring the robustness of these networks has become an important issue. In recent years, many robustness metrics have been proposed for this purpose. Among them, a metric called ‘R’ has received wide attention, and several variants have been proposed. These variants include a metric called Communication Robustness (CR) and the betweenness and closeness variants to both R and CR. However, no evaluations about the correlations among these variants have been made to shed light on their necessity and effectiveness. Addressing this research gap, this paper makes the following contributions. First, we measure the correlations between R and CR to verify that CR is valid to exist due to its unique perspective although it correlates closely with R. Second, we measure the correlations between R and its betweenness/closeness variants to show that they are quite different, and the same is observed for CR and its betweenness/closeness variants. Finally, we propose a new robustness metric called Simplified Communication Robustness (SCR), which simplifies the calculation of CR while working almost the same as CR.
The mechanism of the asymmetric SET and RESET speed of graphene oxide based flexible resistive switching memories

Oxygen migration is reported as key factors of resistive switching in graphene oxide (GO) based memories by different groups. A flexible nonvolatile resistive switching memory based on GO was fabricated through a spin-coating process. The speed of the SET and RESET operations of the GO memories was found to be significant asymmetric. The RESET speed is in the order of 100 ns under a −5 V voltage while the SET speed is three orders of magnitude slower (100 μs) under a 5 V bias. The behavior of resistive switching speed difference is elucidated by voltage modulated oxygen diffusion barrier change.
Bandwidth Enhancement of Printed Monopole Element Quasi-Yagi antenna using a Parasitic Resonator

In this paper, a method to enhance the bandwidth (BW) of a monopole element quasi-Yagi antenna (PQYA) is presented. A closely spaced U-shaped resonator (U-SR) with unequal arms in the end-fire direction is used to generate a new resonance at the high frequency. The evolution of the broadband parasitic U-SR is described. The prototype of the designed antenna is fabricated and tested with the size of 86 mm × 76 mm. The measured results show that the achieved BW is 1.55-2.67 GHz (53.1%) for |S11| < -10 dB, and the gain is 4.05 ± 0.1 dBi for 91% of the BW. Measured and simulated results are in good agreement, which validates the proposed antenna.
Single-Layer Wide-band 45 Degree Phase Shifter with Filter Function

In this paper, a single-layer wide-band phase shifter is proposed, achieving 45 degree phase shift from 1.6GHz to 4.16GHz, and meanwhile exhibiting a band pass filter response. The proposed phase shifter is composed of a stub-loaded transmission line (SLTLs) with a delay line and an Open-circuited three-line MMR (OPTLMMR), both providing filter function. Constant phase shift is obtained by adjusting the phase slopes of main path and reference path.
Design of suboptimal H/sup /spl infin// excitation controllers

This paper presents a method to design power system suboptimal robust excitation controllers based on H/sup /spl infin// control theory. The suboptimal controller results from additional constraints that are imposed on the standard optimal H/sup /spl infin// solution. Global stability constraints are incorporated into the H/sup /spl infin// algorithm to ensure stability of the interconnected system under decentralized control. Furthermore, a Lyapunov-based index is used to evaluate the robustness properties of the closed loop. In order to obtain a reduced order controller, the method of balanced truncation is used. The suboptimal H/sup /spl infin// controllers are output feedback controllers. These controllers posses superior robustness as compared to a conventional PSS and optimal H/sup /spl infin// controllers.
Efficient Partial Sum Architecture and Memory Reduction Method for SC-Flip Polar Decoder

To improve the error correction performance of successive cancellation (SC) decoding of polar codes, SC-flip (SCF) decoding was proposed. However, it requires large additional memory to save the decoding history for hardware implementation. This paper proposes a partial sum (PS) memory reduction method and a PS architecture for SCF decoders. We analyze the fractal structure of the generator matrix and propose a logic circuit to decide the corresponding row of the generator matrix for an arbitrary bit-index. The proposed design was implemented on the Xilinx Virtex-7 FPGA, which can reduce the number of flip-flops by up to 47% and the PS history memory size by 94% compared to other PS architectures.
Pods-as-Volumes: Effortlessly Integrating Storage Systems and Middleware into Kubernetes

We present Pods-as-Volumes (PaV), a Kubernetes plugin that simplifies the implementation of storage volume provisioners by allowing all logic underlying the lifecycle and behavior of volumes to be specified as pod templates, which are then instantiated as needed to create, delete, and expose volumes to applications. PaV reduces the effort required to integrate storage systems into Kubernetes and enables the straightforward creation of storage middleware components, improving modularity and Kubernetes' ability to manage storage stacks.
PRINTED UWB ANTENNA FOR WIMAX /WLAN

Strong subscriber growth over the past year has demonstrated the appeal of WiMAX technology ( WiMAX-1 & WiMAX-2) . The IEEE 802.16 working group has been established a new operating band name as Worldwide Interoperability for Microwave access (WiMax). WiMax has three allocated frequency bands. The low band (2.5-2.69 GHz), the middle band (3.2-3.8 GHz) and the upper band (5.25.8 GHz). Printed antennas are attractive because their uniplanar architecture which helps to integrated with active devices or MMIC easily. In this paper, a printed small antenna fed by a microstrip line with a rotated square for bandwidth enhancement is proposed and discussed. Field distribution, gain and Impedance characteristics of this antenna are presented and discussed. A simple 50 ohm microstrip line is used to excite the slot. A rotated square slot resonator is considered as reference geometry. By embedding a parasitic patch into the center of the rotated square slot, the lower resonant frequency is decreased and the higher resonant frequency is increased. The measured results demonstrate that this structure exhibits a wide impedance bandwidth, s11 < -10 which is over ranging from 2.84 to 6.19 GHz. The parametric analysis of the antenna is done by using Method of Moment based available electromagnetic solver IE3D.