Miracle-dz/UniFAR-FTUs huggingface dataset:
Cache-Enabled Cooperative Edge Networks for Intelligent Connected Vehicles

This paper investigates the effects of outdated channel state information on cache-enabled cooperative networks for intelligent connected vehicles, where part of the relay nodes can cache the files requested from the destinations. As the performance benchmark, the system outage probability with perfect and outdated CSIs is derived. The impacts of the system parameters, such as the number of relay nodes, the correlation coefficient, the channel fading power as well as the target data rate are analyzed by deriving the closed-form expressions on the system outage probability. From the analysis, we conclude that the diversity order of system outage probability with perfect CSIs is equal to the total number of relay nodes. While with outdated CSIs the diversity order remains one, regardless of the number of relay nodes. Specifically, the large number of cached relay and large correlation coefficient can significantly improve the system performance. Simulation results are present to validate the theoretical analysis.
A Framework for Privacy-Preserving Multi-Party Skyline Query Based on Homomorphic Encryption

Nowadays, the management and analyses of ‘big data’ are becoming indispensable for numerous organizations all over the world. In many cases, multiple organizations want to perform data analyses on their combined databases. Skyline query is one of the popular operations for selecting representative objects from a large database, where any other object within the database does not dominate each of the representative objects, called ‘skyline’. Like other data analytics operations, the multi-party skyline query can provide benefits to the participating organizations by retrieving the skyline objects from their combined databases. Such a multi-party skyline query demands the disclosure of individual parties’ objects to others during the computation. But, owing to the data privacy and security concern of the present IT era, such disclosure of the individual parties’ databases is strictly prohibited. Considering this issue, we are proposing a new framework for the privacy-preserving multi-party skyline query, exploiting additive homomorphic encryption along with data anonymization, perturbation, and randomization techniques. The underlying protocols within our proposed framework ensure that every participating party can identify its multi-party skyline objects without revealing the objects to others during the multi-party skyline query. The detailed privacy and security analyses show that the proposed framework can achieve the desired computation goal without privacy leakage. Besides, the performance evaluation through complexity analyses, extensive simulations, and comprehensive comparison also demonstrate the utility and the efficiency of the proposed framework.
Time Delay Estimation Based Model Reference Adaptive Control for Robot Manipulators

Generally model-reference adaptive control (MRAC) is designed using known regression matrix. However, the formulation of regression matrix is difficult for more degree of freedoms (DOFs) of robot manipulator and sometime impossible to compute for many applications. In this work, MRAC using time delay estimation (TDE) named (MRAC-TDE) is proposed to avoid complex calculation of regression matrix and provides model-free control. Therefore, TDE is devised to estimate the unknown dynamics and MRAC is used to update the control gains. The closed-loop stability of system is investigated using the Lyapunov stability criterion. In the end, to validate the effectiveness of the proposed method, simulations are illustrated the appropriateness of proposed MRAC-TDE.
Iterative Learning Control for Linear Fractional-Order Distributed Parameter Systems with Variable Tracking Trajectory

This paper studies the problem of iterative learning control for a linear fractional-order distributed parameter systems with variable tracking trajectory. An improved P-type updating control law is employed to estimate the spatial-temporal varying curve surface iteratively. Then, the sufficient conditions of convergence for output error of the system in the sense of $L_{2}$ norm has been revised through rigorous analysis. The numerical results show the effectiveness of the proposed ILC scheme.
Multimode Photonic Biosensor Based on Cascaded Ring Resonator with Mach-Zehnder Interferometer for Vernier-Effect Refractive Index Sensing

In this paper, a novel photonic integrated biosensor based on the cascaded architecture of a Mach–Zehnder interferometer with a ring resonator, enhanced by the Vernier effect, is proposed employing a multimode waveguide. Some aspects of the silicon photonic sensors based on the evanescent field sensing principle are reviewed. The sensibility of the first four propagating modes (TE00, TE01, TM00, and TM01) is individually investigated in order to explain their influence on the overall device’s sensibility. Supported by results obtained from numerical simulations around the wavelength of 1.55 µm, the proposed sensor is demonstrated to reach a high refractive index (RI) sensing performance such as wavelength sensitivities of 10772.50 nm/RIU, 26500 nm/RIU, 26550 nm/RIU and 40883.33 nm/RIU for the TE00, TE01, TM00, and TM01, respectively, whose are better than the most performing state-of-the-art Vernier sensors characterized by cascaded RR and MZI (RR-MZI).
O-ADPI: Online Adaptive Deep-Packet Inspector Using Mahalanobis Distance Map for Web Service Attacks Classification

Most active research in Host and Network Intrusion Detection Systems are only able to detect attacks on the computer systems and at the network layer, which are not sufficient to counteract SOAP/REST or XML/JSON-related attacks. In dealing with the problem of anomaly detection in web service message datasets, this paper proposes an anomaly detection system called the Online Adaptive Deep-Packet Inspector (O-ADPI) for web service message attacks classification. The proposed approach relies on multiple statistical methods which use Unigram-based Weighting Scheme (UWS) that combines text mining techniques with a set of different statistical criteria for Feature Selection Engine (FSE) to effectively and efficiently explore optimal subspaces in detecting anomalies embedded deep in the high dimensional feature subspaces. We utilize a supervised intrusion detection algorithm based on Mahalanobis Distance Map classifier. As web service attacks can be classified into anomaly and normal, the task of anomaly detection can be modeled as a classification problem. The O-ADPI model was assessed for F-value, true positive rate (TPR), and false positive rate (FPR) in order to evaluate the detection performance of O-ADPI against different type of feature selections engines with corresponding PCs for each message-specific service. The experiments were performed using the REST-IDS Dataset 2015 and the results demonstrated that the proposed O-ADPI model achieved the best results in each message-specific service.
ICT gateway to simulation environment for electrical fault injection and recovery

Due to the advancements in the smart grid technologies, smart mechanisms are required within the Energy Management System (EMS) environments for microgrids. One of the functionalities of EMS is to ensure grid stability. In order to test and validate new mechanisms, appropriate simulation tools exist. Most of the existing validation strategies include modeling the target system in simulation environment and then deploying the mechanism in the real environment. When the validated mechanisms are implemented in real environment, they often do not work as intended and require modification due to the implementation difference within the EMS controller. An EMS should be able to communicate with the simulated model, inject faults in the simulated model and able to perform various control actions. In this paper, we propose a software-in-loop approach, where the grid stability mechanisms are implemented in the EMS, which is deployed in the real environment. EMS must operate exactly the way it does in the simulation environment. For such a capability, the simulation platform should be able to communicate with the EMS. In this work, we consider a 13-node radial distribution grid with one solar panel as a generation unit. The 13-node distribution grid has been modeled using Apros simulation software. SMG2.0, a software application for microgrid is used to monitor, inject electrical faults and trigger recovery mechanisms in the Apros model. A communication architecture called ICT gateway has been developed between Apros and the EMS (SMG2.0). Two fault scenarios (line-breakage and under-voltage) are considered as the fault injection scenarios to evaluate the performance of the communication architecture. When the SMG2.0 detects a line fault, it triggers network reconfiguration as the recovery strategy for the line-breakage scenario in the simulation environment. This approach not only helps in designing fault handling strategies in the electrical network but also helps in designing an effective software application targeted to control the physical entities.
Balancing between centralized vs. edge processing in IoT platforms with applicability in advanced people flow analysis

Understanding consumer behavior has always been a major concern for any business. Although in the last decades there has been a steep rise in online shopping and online marketing, a big chunk of the revenue for retailers still comes from traditional, in-store shopping. As such, analyzing and understanding the flow of customers inside supermarkets and stores can offer invaluable insights regarding their business and customer behavior to retailers. With the rise of smart IoT devices that allow live recording of video streams and even processing these streams on-edge, analyzing people flows in the hyperspace of crowd size, person categories (by sex and age), person location and time can prove to be an essential tool for decision makers. This paper presents a method for performing people flow analysis using deep learning for person recognition and profiling. The proposed method is encapsulated in a platform that can analyze the people flow on-edge or on a central server with powerful GPUs. The platform also encompasses several business intelligence graphical dashboards for presenting and analyzing the resulted time series data. Our preliminary findings show that on-edge processing, on embedded devices, is a plausible alternative to central processing with GPUs. Despite having lower performance, both in term of mean average precision and frames per second, embedded devices and the corresponding algorithms still manage to achieve reasonable results, while being cheaper and significantly more power efficient. Having this said, the most reasonable conclusion is to combine the two solutions mentioned above into a hybrid approach.
Performance Analysis of Grant-Free Multiple Access for Supporting Sporadic Traffic in Massive IoT Networks

Grant-free multiple access (GFMA) protocol has been regarded as a key element to support sporadic traffic generated from massive internet-of-things (IoT) networks. In GFMA protocol, each IoT device transmits data packets without grant from a base station (BS) via pre-reserved uplink resources. Packet collisions inherently occur when multiple IoT devices transmit packets by using the same radio resource, but the collision effect can be alleviated with multi-packet reception (MPR) capability of the BS. Since a number of studies have focused on improving the physical layer performance such as bit error rate, they may be hard to provide intuitions from the MAC layer perspective when a number of IoT devices sporadically generate uplink packets and attempt the GFMA. In this paper, we thoroughly investigate the GFMA from the MAC layer perspective. We provide an analytical framework based on a Markov chain to capture the performance of the GFMA in terms of packet transmission success probability, ergodic throughput, and access delay. Through simulations, we validate our analytical framework and verify the necessity of adopting MPR technique for supporting a massive number of IoT devices generating sporadic traffic.
Graphene diodes for 5G energy harvesting: design, simulations and experiments

In this paper, we propose a rectenna based on a graphene self-switching diode for Ka band applications in view of the upcoming 5G and internet-of-things telecommunication systems. A 4-element patch antenna array has been designed, simulated, and fabricated using a high-resistivity silicon/silicon dioxide/graphene multi-layer and tested on-wafer. By using analytical formulas to optimize the number of parallel channels for the diode, we have achieved highly improved DC current values (average value of ±2mA at ±3V). The diode has been integrated with the array in coplanar waveguide technology using a matching open stub, in order to maximize the array-to-diode power transfer. The rectenna has then been measured by using a 28GHz RF source: at 0V DC bias, a maximum DC voltage VDC of 2.4mV has been obtained, with a maximum DC current IDC of 1. 2µA and a maximum DC power PDC of 2.9nW; when applying a small DC bias (1.2V), VDC reaches 71mV, IDC=35. 5µA and PDC=2. 5µW.
Cancer-related fatigue in breast cancer patients under chemotherapy

Introduction: Fatigue is a common and frequently disabling symptom in cancer patients. Fatigue may be caused by the disease itself, by treatment for the disease, by physical symptoms or conditions resulting from the disease or its treatment. The aim of this study was to assess fatigue and related factors in breast cancer patients. Material and Methods: We conducted a cross-sectional study on 119 random samples of breast cancer patients. The Iranian version of QLQ-C30 and QLQ-BR23 questionnaires were used. Univariate methods and multiple regression analysis were performed to identify predictors of fatigue. Results: Overall, 78% of the patients indicated that they were experiencing fatigue to some degree. The mean score on the fatigue subscale was 41.74±26.91. Of all functional subscales, fatigue showed the strongest influence on social functioning. Linear regression analyses showed that total fatigue was best predicted by pain, appetite loss, body image and type of treatment. Conclusion: Our results support the notion that fatigue in cancer patients is a major problem, which deserves yet more attention from health professionals, and that quality of life in cancer patients might be improved markedly by interventions that effectively reduce fatigue.
Non-Intrusive Load Monitoring: A Multi-Agent Architecture and Results

Non-intrusive Load Monitoring (NILM) is a technology that allows the identification of individual electrical loads from a single aggregated measurement of voltage/current, hence, useful for diagnostic of the consumption of electrical energy. This is performed by means of load detection and disaggregation techniques, as there are several different power signatures from the active loads. This paper proposes a multi-agent architecture and evaluates its performance. Four detection methods were selected: Discrete Wavelet Transform (DWT); Kalman Filter; Derivatives, and Half Cycle Active Power. For the power signature recognition agents, different feature extractors and machine learning methods were evaluated: Discrete Fourier Transform, DFT with Exponential Damping, V-I Trajectories, Wavelet and Power Envelope; these were combined with four classifiers: k-Nearest Neighbors, Ensemble Method, Support Vector Machine and Decision Tree. The detection, feature extractors and classifiers methods were tested using waveforms sampled in real situations of the electric network available at the COOL and LIT datasets. The results for the proposed multi-agent architecture indicates improvements in the event detection, lower occurrences of false positives, better feature extractions and better classification results.
Design and Implementation of A New Topology for Multilevel Inverter with Reduced Count of IGBTs and DC Voltage Sources Based on Developed HBridge

In this paper, a new combination for multilevel inverters based on developed H-bridge cells is proposed which produces more voltage levels with a specified number of switches and DC voltage sources. Four different algorithms are proposed to determine the magnitudes of the DC voltage sources. In order to find the optimum algorithm and investigation of the advantages and disadvantages of the proposed topology, these algorithms are compared to the presented topologies from different aspects and results are investigated. After that, the proposed topology is implemented and results are shown to verify the correct performance of the proposed topology.
Exploring the Taxonomy of USB-Based Attacks

A variety of USB-based attacks is being increased rapidly. Researchers manage to identify more and more threats and vulnerabilities, often with proof-of-concept practical demonstrations. USB-based vulnerabilities’ databases are being updated constantly. There are plenty of publications, including threat models and corresponding analysis, but attacks taxonomy is rarely being a goal of investigation. Furthermore, the great majority of such investigations and papers refers to cyberattacks in whole, in such cases USB-based attacks remain to be unreviewed. In this paper we aim to review current state of the USB-based attacks taxonomy studies. An attempt to summarize all well-known investigations and the additional material to create an enhanced taxonomy is represented.
Wideband Metal-Dielectric Multilayer Microwave Absorber based on a Single Step FDM Process

Thanks to the growing development of printable materials dedicated to microwave applications, 3D printing technology is bringing new opportunities to RF engineering. In this paper, a fully 3D-printed metasurface absorber with a pyramidal shape and operating in a wide frequency band of 7.6-17.4 GHz was designed, fabricated using the FDM method, and characterized. The proposed structure permits the absorption of more than 90% of the energy of an impinging electromagnetic wave in normal incidence. The measurement setup was validated on a PCB-based structure used as a benchmark. The 3D-printed metasurface absorber yields an absorption close to the simulation results with a slight shift towards lower frequencies.
Broadband Connected Slots Phased Array Feeding a High Gain Lens Antenna at 60 GHz

This paper presents a 60 GHz connected slots linear phased array feeding a high gain semi-symmetric lens antenna. This novel design provides high gain, broadband and beam-steering capabilities for gigabits rate access and backhaul communications. The 16 x connected slots are fed periodically to allow ± 45 ° beam-steering in the H-plane. The results show more than 33% impedance bandwidth, 24.6 dBi maximum gain and 3 dB gain bandwidth covering the full band 57–66 GHz. Besides, the half power beamwidth (HPBW) is 6° and 10° in E-and H-plane, respectively.
A High-Accuracy Spatial Localization Methodology for Partial Discharge by UHF-Signal Sensor-Arrays

Inspired by the idea of mobile targets localization by the antenna array, a novel localization methodology for the partial discharge (PD) source in power systems is proposed by using ultra-high frequency (UHF) sensor-arrays in this paper. Due to the broadband feature of UHF-signals emitted from PD source, a focusing algorithm, i.e., two-sided correlation transformation (TCT) algorithm, is utilized to transform the PD signals to the narrowband ones, which improves the accuracy of the direction-of-arrival (DoA) estimation at the sensor-array under the severe electromagnetic surroundings. Then, with the DoAs obtained from multiple sensor-arrays, a spatial localization paradigm for the PD source is introduced. Finally, the PD source can be localized within a spatial sphere formed by the multiple skew DoA-lines from these sensor-arrays. Based on the simulation with the experimental PD UHF-signal data, it is shown that the proposed methodology accurately localizes the PD source within the a small range of sphere under the severe testing situations, which improves the accuracy of PD source localization compared with the classic time-difference-of-arrival (TDoA) method.
Comparison between Mixer and Track and Hold UWB receivers for SATCOM applications

An innovative and more integrated architecture for SATCOM receiver is presented. Track and Hold Amplifier (THA) technology is used to sub-sample a microwave signal over a very wide frequency band [1 - 13 GHz]. The reception of the SATCOM signals is based on the principle of direct microwave sub-sampling implemented with the THA. The demodulation of these received signals is performed by a Digital Quadrature Demodulation (DQD). The THA output is digitized in the first Nyquist area $[0-\frac{f_{s}}{2}]$ using an Analog to Digital Converter (ADC). The THA performances are studied in terms of dynamic, Signal to Noise Ratio (SNR) and Spurious Free Dynamic Range (SFDR). They are also compared to the dynamic, SNR and SFDR performances measured with an equivalent frequency band mixer. A non-linear circuit model of the provided THA has been extracted from measurements. This non-linear circuit model has been implemented in Harmonic Balance (HB) simulations to compare simulated and measured SFDR performances. These comparisons show that THAs are potential candidate for designing very wideband SATCOM receivers with performances close to a mixer solution.
A 2.4 GHz-Band Enhancement-Mode GaAs HEMT Rectifier with 19% RF-to-DC Efficiency for 1 μW Input Power

An RF-to-DC conversion efficiency of 19% has been achieved for a 1-μW input power at the 2.4-GHz band by using an enhancement-mode GaAs pHEMT rectifier. The enhancement-mode GaAs HEMT was suitable for the rectifier operation due to its moderate gate-drain feedback capacitance, a strong nonlinearity, and a large transconductance. The gate-drain capacitance generates a sufficient gate-switching signal for a very low input power. In addition, the circuit loss must be reduced to as low as possible, especially for the gate-side circuit to keep the gate switching signal.
Unified Feedback Beamforming Digital Predistorter

A novel digital predistortion (DPD) architecture for amplitude- and phase- weighted beamforming (BF) transmitter is proposed. Based on the analysis of BF nonlinear radiation characteristics over-the-air, the proposed DPD with a simple unified feedback circuit can reduce nonlinear radiation in every direction. The performance of proposed DPD is evaluated through computer simulation assuming Chebyshev-weighed BF arrays. The results show that the proposed architecture can suppress nonlinear radiation to less than -45 dB in all direction, which is similar to the full DPD architecture that requires individual feedback circuit for each antenna element.
Collision Avoidance for Continuum Robot Using FABRIK Algorithm

Continuum robots are manipulators able to bend at any point along their structure. This feature allows continuum robots to work in areas with complex geometry. In this regard, they are used as instruments and endoscopes in industry and medicine. Inverse kinematics for continuum robots is using for control and path planning. Recently, Forward And Backward Reaching Inverse Kinematics (FABRIK) algorithm has been used for solving inverse kinematics issue for continuum robots. For this, arcs of continuum robot are simplified to virtual links. But virtual links can not be used to define the distance between continuum robot body and obstacle without restoring whole robot section. In this paper, we propose a method for obstacle avoidance for multi-section continuum robot using FABRIK algorithm. The simulation results for the planar case show that the proposed method is able to avoid unwanted collisions.