Miracle-dz/UniFAR-FTUs huggingface dataset:
Sampling and Comparator Speed-Enhancement Techniques for Near-Threshold SAR ADCs

This paper presents the sampling and comparator speed-enhancement techniques for SAR ADCs under near-threshold supply voltages. The proposed level-shifted boosting circuit generates sharp falling edges for the sampling clock, which is found a key factor limiting the sample speed under ultra-low voltages. Delayed cross-coupling comparator is introduced in this work, which enhances the comparator regeneration while keeping the noise comparable. A 0.35V 8b 12MS/s SAR ADC is designed in a 65nm CMOS technology to prove the proposed techniques. The post-layout simulated SAR ADC consumes only $6.71~\mu \text{W}$ and achieves SNDR of 48.8dB at Nyquist input, resulting in a figure-of-merit (FoM) of 2.47 fJ/convertion-step. Simulation results show the proposed speed-enhancement techniques improve the sampling rate of SAR ADC significantly under near-threshold supply voltages.
Exponential Stability of Neutral-Type Cohen-Grossberg Neural Networks With Multiple Time-Varying Delays

This paper deals with the problem for exponential stability of a more general class of neutral-type Cohen-Grossberg neural networks. This class of neutral-type Cohen-Grossberg neural networks involves multiple time-varying delays in the states of neurons and multiple time-varying neutral delays in the time derivatives of the states of neurons. Such neural system cannot be described in the vector-matrix forms due to the existence of the multiple delays. The linear matrix inequality approach cannot be applied to this class of neutral system to determine the stability conditions. This paper provides some sufficient conditions to guarantee the existence, uniqueness and exponential stability of the equilibrium point of the neural system by employing the homeomorphism theory, Lyapunov-Krasovskii functional and inequality techniques. The provided conditions are easy to validate and can also guarantee the global asymptotic stability of the neural system. Two remarks are given to show the provided stability conditions are less conservative than the previous results. Two instructive examples are also given to demonstrate the effectiveness of the theoretical results and compare the provided stability conditions to the previous results.
Lightning Measurement in Sarawak, Malaysia: First Results

Malaysia is one of the country with highest lightning activities in the world. Regrettably, studies on lightning characteristics is still lacking especially in the Eastern part of Malaysia, which is Sabah and Sarawak. In this study, the characteristics of electric field radiation recorded during lightning measurement campaign in Sarawak had been analyzed. The field measurement was done using parallel plate antenna attached with electronic buffer circuit. The data was recorded using a PicoScope and monitored in computer. Nineteen samples of negative first return strokes were successfully recorded during this measurement. Their electric fields waveform parameters namely peak amplitude, zero crossing time, zero to peak and 10%-90% rise time were thoroughly analyzed. All those values are 8% to 166% larger in comparison to the data obtained from lightning measurement done in the Peninsular Malaysia. It is suggested that various topology and meteorology pattern are among factors that contribute to the discrepancies.
A novel methodology to validate cyberattacks and evaluate their impact on power systems using real time digital simulation

The traditional power systems are rapidly digitalized and automated for increased monitoring and control. This automation of power system communication has made it possible to monitor and control operations remotely in a plant. However, this also opens up an exploitation vector for attackers, after they gain access to the substation network. This scenario can only be investigated through an in-depth study of communication protocols and control authority concepts associated with power system. IEC 61850 has emerged as the most popular protocol for power system communication. In this paper, we investigate realtime simulation of power systems with IEC 61850 based communication, in order to devise a testbed that can be used to validate false data injection cyberattacks and evaluate their impact. Based on the results, we discuss possible countermeasures to such attacks and outline future research directions.
A Fuzzy-based Image Segmentation on Diabetic Retinopathy Model

Clinical reports done suggested that more than ten percent patients with diabetes have a high risk of eye issues. The retinal fundus images are commonly used for detection and analysis in diabetic retinopathy disease. This work presents several state to extract the anatomic components and lesions in colored fundus photographs and some decision support methods to help early clinical diagnosis detection. It also introduces a model of detection in fundus images by automated segmentation of region of interest (ROI). Automatic segmentation of retinal blood vessels from retinal images is applied to make landmarks detection more efficient. The proposed model integrates adaptive Otsu's Threshold and Segmentation using FUZZY C-MEANS clustering for automated detection of hard yellow spots. The proposed hybrid fuzzy-based ROI extraction scheme integrates the effect of the local neighborhood and allow it to influence the membership value of each pixel. A new Hybrid FCM (H-FCM) algorithm is proposed, which integrates spatial information with a 2D adaptive noise removal SS-FCM model. Experiments have been conducted to verify the proposed model. Experiments showed that this proposed model produced high performance in ROI detection under different effects and on different types of retina images. Moreover, the results showed high sensitivity compared with recent researches.
Flexible resource provisioning of polarization independent coherent PONs based on non-orthogonal multiple access and multiCAP modulation

A combined non-orthogonal multiple access (NOMA) and multiband carrierless amplitude and phase modulation (multiCAP) scheme is proposed for flexible resource provisioning in coherent passive optical networks (PONs). While the proposed combination increases the data-rate and the number of users through the inclusion of NOMA and multiCAP, the coherent reception increases the range and splitting factor of the network through optical power budget enhancement. The proposed system is experimentally evaluated providing a 20 Gb/s aggregated data-rate per wavelength with 10G optoelectronics and applied in two main PON scenarios with four spectral configurations from full-band CAP to four-band multiCAP. The first PON scenario consists of an existing PON that the network operator requires to increase the number of users; NOMA with full-band CAP or multiCAP can be introduced replacing one or more users of the existing PON by one or several new sub-networks and multiplexing the sub-networks by NOMA. In the other PON scenario, several PONs can be nested sharing an initial splitter and achieving a larger number of users by the combination of NOMA and multiCAP. The proposed techniques are fully compatible with other multiplexing techniques such as dense wavelength division multiplexing, which should be considered to achieve higher numbers of users.
A Context-Aware IoT-Based Smart Wearable Health Monitoring System

Development in wearable health monitoring technology has been dramatically improved due to the increasing use of wireless technologies and the miniaturization of electronic sensors. It is the potential to change the future of healthcare services through the use of active health monitoring devices on the Internet of Things (IoT) to track patients and athletes through their regular daily routines. Medical applications such as remote monitoring, biofeedback and telemedicine build a completely new framework for controlling health quality and costs. This work aims to develop a low-cost, high-quality multipurpose wearable smart device for tracking the health care of patients with heart disease and fitness athletes. In this paper, we discuss our proposed system through three phases. In the first phase, we use the Raspberry-Pi as an open-source microcontroller with a HealthyPi hat serving as a conduit between the Raspberry-Pi and the HealthyPi-connected biomedical sensors with different parameters such as temperature, ECG, pulse, oximetry, … etc. We started our experiment with 15 different test subjects with various gender, ages and levels of fitness. We positioned the proposed wearable device and gathered data on readings for each test subject when sitting, walking and running. The second phase includes linking our device to an open-source IoT dashboard to display the data via an interactive IoT dashboard to be accessed remotely by doctors, as well as introducing rules for action that send alerts to patients and doctors in the event of problems. We developed and tested a Fuzzy Logic system in the third phase, which inputs the data collected from the experiments on the accelerometer, gyroscope, heart rate and blood oxygen level, and provides the physical state (resting, walking or running) as output that helps to determine the patient/athlete's health status. The results obtained from the proposed method show efficient remote health status monitoring of test subjects in real-time through the IoT dashboard, and identification of anomalies in their health status, as well as effective detection of physical motion mode using the proposed Fuzzy Logic system design.
Dominant Path Zero-Forcing Based on Low-Rank Matrix Approximation for Full-Dimensional Massive MIMO Systems

The conventional zero-forcing (ZF) precoding and the two dimensional (2D) ZF precoding are two popular schemes to cancel the interference in the downlink of the full-dimensional (FD) massive MIMO systems. However, the conventional ZF is of high complexity as a result of ignoring the structure of the FD massive MIMO channels while the 2D ZF has poor performance due to neglecting the elevation angular spread. In this correspondence, by exploiting the spatial correlation of the FD massive MIMO channels, we propose a dominant path zero-forcing precoding (DPZF) scheme based on the low-rank matrix approximation. The proposed DPZF scheme includes two stages. In the first stage, we obtain the elevation and the azimuth components of $r$ dominant paths for each user's channel by solving the rank-$r$ channel matrix approximation. In the subsequent stage, we reformulate the Gram matrix with the obtained components so as to zero force the most dominant path of each user's channel with low complexity. For the proposed DPZF, the upper bound of the performance gap to the conventional ZF is derived and the complexity is analyzed. The analysis and simulation results indicate that the proposed DPZF can yield a more elegant performance-complexity tradeoff than the existing precoding schemes.
Socio-Aware Recommendations Under Complex User Constraints

In this work, we consider the joint behavior of an information diffusion process integrated with a recommender system (RecSys) over an online social network (OSN), where the typical users’ resilience to information varies, leading to potential information overloads. We assume that each user has a threshold over the information that she can process in a meaningful way, and exceeding it could lead to user dissatisfaction or the user remaining idle. In order to efficiently tackle this issue, while considering complex user constraints, we consider two types of users’ capacity to information, that is, capacity for distinct items and capacity for duplicate items. In this setting, we aim to allocate the items in the OSN in order to maximize users’ total relevance to the former while ensuring that no user exceeds any type of capacity. We show that this problem is NP-complete and present various heuristic methods to address it. A novel framework, called socially constrained recommendations (SCoRe), is developed for the final assignment of items to users, consisting of a two-step procedure. We present and evaluate two different approaches for each step and discuss the usability of SCoRe for the efficient diffusion of items in the network while respecting the users’ constraints.
A 60-GHz Variable Gain Phase Shifter With 14.8-dB Gain Tuning Range and 6-Bit Phase Resolution Across −25 °C–110 °C

This article presents a 60-GHz variable gain phase shifter (VGPS) with orthogonal phase and gain control technique and linear phase control technique in 65-nm CMOS. Using the orthogonal phase and gain control technique, the proposed VGPS has the ability of gain tuning without extra variable gain block, significantly reducing the size of conventional phased arrays. The linear phase control technique is proposed to greatly improve the accuracy and robustness of phase control against temperature variation. As results, the VGPS achieves 6-bit phase resolution across −25 °C to 110 °C and continuous gain tuning range of 14.8 dB. The measured 3-dB bandwidth is 52–64 GHz. As the gain of VGPS is −22.4 to –dB, the measured root-mean-square (rms) phase errors are 1.3°–3.3°, while the measured rms gain errors are 0.2–0.5 dB in 3-dB bandwidth. Across −25 °C to 110 °C, the variations of rms phase and gain errors are below 1.2° and 0.1 dB, respectively. With supply voltage varying from 1.0 to 1.2 V, the variations of rms phase and gain errors are below 1.1° and 0.2 dB, respectively. During the measurement with different combinations of temperature and supply voltage, no gain and phase calibrations are conducted. The measured input-referred $P_{\mathrm {1\,dB}}$ at the maximum gain state (−7.6 dB) is about −3.8 dBm. The chip consumes 16.4 mA from a 1.1-V voltage supply and the core area of the VGPS is $720\,\,\mu \text {m} \times 560 \,\,\mu \text{m}$ .
A Scheduling Scheme for Autonomous Vehicle Highway Merging With an Outflow Traffic and Fairness Analysis

Recently, vehicle-to-infrastructure (V2I) communication-based scheduling schemes for connected and automated vehicles (CAVs) on highway on-ramps have received attention because the schemes assign optimal merging times to CAVs based on their criteria, such as first-in first-out order or minimizing CAV total travel time. However, these schemes cause traffic congestion due to the criteria when the vehicle inflow traffic becomes high. To mitigate traffic congestion, a scheduling scheme should assign merging times to CAVs to decrease road vehicle density. In this paper, we propose a scheduling scheme for autonomous vehicle highway merging with an outflow traffic and fairness analysis. We formulate a multiobjective function that achieves both outflow traffic maximization and fairness in assigned merging times. Since more vehicles pass a highway on-ramp as highway on-ramp outflow traffic increases, the proposed scheme decreases vehicle density on roads by maximizing the outflow traffic. Furthermore, the proposed scheme distributes the vehicle density on both the main and ramp roads by fairly assigning their merging times. Simulation results show that the proposed scheme mitigates the potential traffic congestion of previous scheduling schemes. Furthermore, the proposed scheme improves outflow traffic from highway on-ramps by more than 200 veh/h compared with the previous scheduling schemes.
Coded-MPMC: One-to-Many Transfer Using Multipath Multicast With Sender Coding

One-to-many transfers in a fast and efficient manner are essential to meet the growing need for duplicating, migrating, or sharing bulk data among servers in a datacenter and across geographically distributed datacenters. Some existing works utilize multiple multicast trees for a one-to-many transfer request to increase network link utilization and its transfer throughput. However, since those schemes do not fully utilize the max-flow value of transmission from a single sender to each recipient, there is room for each recipient to retrieve data more quickly. Therefore, assuming fully-controlled networks with full-duplex links, we pose a problem to find a set of multicast flows with an allocation of block-wise transmissions by which each of multiple recipients with diverse max-flow values from the sender can utilize its own max-flow value. Based on that, assuming a sender-side coding capability on file blocks, we design a schedule of block transmissions over multiple phases by which each recipient can achieve a lower-bound of its file retrieval completion time, i.e., the file size divided by its own max-flow value. This paper presents the coded Multipath Multicast (Coded-MPMC) for one-to-many transfers with heuristic procedures to find a desired set of multicast flows on which block transmissions are scheduled. Through extensive simulations on large-scale real-world network topologies and different types of randomly-generated synthetic topologies, the proposed method is shown to design a desired schedule efficiently. A preliminary implementation on OpenFlow is also reported to show the fundamental feasibility of Coded-MPMC.
Research on Compliance Supervision Data Analysis Model Based on Mass Chat Records in the Inter-Bank Market

This paper studies the data analysis model of compliance regulation based on massive chat records in the Inter- Bank Market. Considering the country’s urgent regulatory requirements to regulate bond market participants’ use of compliance chat tools to conduct financial transaction business and promote the stable and healthy development of the bond market, we use natural language processing (NLP) technology to analyze the Inter-Bank Market chat records. Based on this, it is proposed to use Event Detection and Style-aware NER technology to identify and extract the bond description information in the exchange group of traders. Using latest development in representation learning, this paper introduces BERT embedding as character based pretrained model and incorporates it with BiLSTM-CRF to transform the natural language text describing bond information into structured text to improve the work efficiency and system entry accuracy in bond information collection scenarios. Based on iDeal’s thousands of chat records, as well as QQ, enterprise QQ, RM, and IB platform conversation chat records collected through technical means, build the data foundation that the algorithm relies on and conduct experiments. The evaluation results based on Precision, Recall and F1-score show that the proposed method is more suitable for the task of bond information extraction than the traditional rule-based method, and has stable performance and strong generalization under different conditions.
Distortion Reduction in Fractional Delay Filters

As the digital version of a continuous-time delay, the concept of fractional delay (FD) is exploited to approximate a desired delay that is not a multiple of the sampling interval. However, in FD filters, there is always a severe distortion at the beginning of delayed signals, referred to as head distortion. This letter identifies the cause of head distortion and proposes a solution to this problem for reducing the overall distortion in FD filters. For the purpose of performance evaluation, relative root-mean-square (RMS) error is formulated as a metric to quantify the overall difference between the frequency-domain response of an FD filter and the ideal one. Moreover, illustrative numerical results on the proposed scheme applied in FD filters with classical sinc, Farrow and Lagrange interpolation substantiate the validity and feasibility of our solution.
RENDERING ECONOMICS IDIOMSWITH COLOUR NAMES: A CROSS-CULTURAL ASPECT

The present paper is focused on rendering colour names in the idioms of the Economics discourse. Colour names black, blue, gray, green, orange, red, white, and yellow in the idiomatic structures are retrieved from the Discourse of Economics and verified in the Ivestopedia, Business, and Finance dictionaries. Various aspects of colour names – etymological, lexical, functional, and cross-cultural – have been the object of analysis and discussion. The algorithm of rendering the economic idioms with the colour constituent has been suggested by the author.
Analysis of Process Variations in W-Band GaN MMIC PAs Using Nonparametric Statistics

This article presents an analysis of the effects of amplifier process-related performance variation on the radiation patterns of a <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-band active transmit antenna array. Based on measured on-wafer <inline-formula> <tex-math notation="LaTeX">$S$ </tex-math></inline-formula>-parameters for about 80 amplifier chips designed in an experimental 90-nm gallium nitride (GaN) on SiC process, a statistical analysis of the array patterns is performed. Several types of probability density functions (pdfs) are generated from measured data and compared to determine which statistical approach is most relevant. We find that a joint distribution that maintains the correlation structure between <inline-formula> <tex-math notation="LaTeX">$|S_{21}|$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\angle S_{21}$ </tex-math></inline-formula> is important for an accurate analysis. The monolithic microwave integrated circuits (MMICs) are connected to the waveguide-fed horn antenna elements in the array via microstrip-to-waveguide transitions fabricated on alumina. The transitions are analyzed in full-wave simulations with fabrication tolerances included in the analysis. Finally, the MMIC and transition statistical variations are cascaded, resulting in a quantitative evaluation of spatial power combining. Given a random choice of power amplifier chips in a <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> array, the EIRP is shown to vary by ±3 dB at 94 GHz.
Improving Motor Imagery of Gait on a Brain–Computer Interface by Means of Virtual Reality: A Case of Study

Motor imagery (MI) is one of the most common paradigms used in brain-computer interfaces (BCIs). This mental process is defined as the imagination of movement without any motion. In some lower-limb exoskeletons controlled by BCIs, users have to perform MI continuously in order to move the exoskeleton. This makes it difficult to design a closed-loop control BCI, as it cannot be assured that the analyzed activity is not related to motion instead of imagery. A possible solution would be the employment of virtual reality (VR). During VR training phase, subjects could focus on MI avoiding any distraction. This could help the subject to create a robust model of the BCI classifier that would be used later to control the exoskeleton. This paper analyzes if gait MI can be improved when VR feedback is provided to subjects instead of visual feedback by a screen. Additionally, both types of visual feedback are analyzed while subjects are seated or standing up. From the analysis, visual feedback by VR was related to higher performances in the majority of cases, not being relevant the differences between standing and being seated. The paper also presents a case of study for the closed-loop control of the BCI in a virtual reality environment. Subjects had to perform gait MI or to be in a relaxation state and based on the output of the BCI, the immersive first person view remained static or started to move. Experiments showed an accuracy of issued commands of 91.0± 6.7, being a very satisfactory result.
Research on Optimization of Fuzzing Technology Based on Hybrid Execution

In recent years, the rapid development of Internet of Things technology has brought many conveniences to human life. In order to realize the bright prospect of the Internet of Everything, various smart devices are emerging one after another. While a large number of application software is released, ensuring IoT software security has also become particularly important. This paper combines the current main automated software analysis technology and its ideas, and proposes a magic bytes matching strategy for seed generation. Finally, it is proved through experiments that the strategy proposed in this paper can find more crashes and achieve higher efficiency.