Miracle-dz/UniFAR-FTUs huggingface dataset:
Transformation to Advanced Mechatronics Systems Within New Industrial Revolution: A Novel Framework in Automation of Everything (AoE)

The recent advances in cyber-physical domains, cloud, cloudlet, and edge platforms along with the evolving Artificial Intelligence (AI) techniques, big data analytics, and cutting-edge wireless communication technologies within the Industry 4.0 (4IR) are urging mechatronics designers, practitioners, and educators to further review the ways in which mechatronics systems are perceived, designed, manufactured, and advanced. Within this scope, we introduce the service-oriented cyber-physical advanced mechatronics systems (AMSs) along with current and future challenges. The objective in AMSs is to create remarkably intelligent autonomous products by 1) forging effective sensing, self-learning, Wisdom as a Service (WaaS), Information as a Service (InaaS), precise decision making, and actuation using effective location-independent monitoring, control and management techniques with products and 2) maintaining a competitive edge through better product performances via immediate and continuous learning, while the products are being used by customers and are being produced in factories within the cycle of Automation of Everything (AoE). With the advanced wireless communication techniques and improved battery technologies, the AMSs are capable of getting independent and working with other massive AMSs to construct robust, customizable, energy-efficient, autonomous, intelligent, and immersive platforms. In this regard, rather than providing technological details, this paper implements philosophical insights into 1) how mechatronics systems are being transformed into AMSs; 2) how robust AMSs can be developed by both exploiting the wisdom created within cyber-physical smart domains in the edge and cloud platforms and incorporating all the stakeholders with diverse objectives into all phases of the product life-cycle; and 3) what essential common features AMSs should acquire to increase the efficacy of products and prolong their product life. Against this background, an AMS development framework is proposed in order to contextualize all the necessary phases of AMS development and direct all stakeholders to rivet high-quality products and services within AoE.
Intrusion Prevention System Against Denial of Service Attacks Using Genetic Algorithm

Software-Defined Networking technology that separates the control plane and data plane can also be the target of Denial of Service attacks. Denial of Service attacks tries to damage the network architecture by weakening the Software-Defined Networking controller. Intrusion Prevention System as a solution to the prevention of this attack has an application called Snort that can detect every incoming data packet and block the attacking host. However, Snort cannot adapt to the frequency and type of attack. In this research Snort on Intrusion Prevention System was integrated with the Genetic Algorithm so that the duration of the block can adapt to the attack. Intrusion Prevention System utilizing Genetic Algorithm was able to overcome Denial of Service attacks by blocking attack hosts with an average speed of 0.0278 seconds in one execution. Blocking that is done can also adapt to the frequency and type of attack so that the Software-Defined Networking controller can work properly.
Machine learning-based pre-impact fall detection model to discriminate various types of fall.

Preimpact fall detection can send alarm service faster to reduce long-lie conditions and decrease the risk of hospitalization. Detecting various types of fall to determine the impact site or direction prior to impact is important because it increases the chance of decreasing the incidence or severity of fall-related injuries. In this study, a robust preimpact fall detection model was developed to classify various activities and falls as multi-class and its performance was compared with the performance of previous developed models. Twelve healthy subjects participated in this study. All subjects were asked to place an inertial measuring unit module by fixing on a belt near the left iliac crest to collect accelerometer data for each activity. Our novel proposed model consists of feature calculation and infinite latent feature selection algorithm, auto labeling of activities, application of machine learning classifiers for discrete and continuous time series data. Nine machine-learning classifiers were applied to detect falls prior to impact and derive final detection results by sorting the classifier. Our model showed the highest classification accuracy. Results for the proposed model that could classify as multi-class showed significantly higher average classification accuracy of 99.57 ± 0.01% for discrete data-based classifiers and 99.84 ± 0.02% for continuous time series-based classifiers than previous models (p < 0.01). In the future, multi-class preimpact fall detection models can be applied to fall protector devices by detecting various activities for sending alerts or immediate feedback reactions to prevent falls.
ISAR Tomography for Full-Polarimetric 3-D Radar Cross-Section Measurements

Radar cross-section (RCS) images are valuable for understanding the 3-D target scattering center distribution of objects. However, 3-D RCS imaging requires more complex measurement systems and much more data points compared to conventional 2-D methods. A reduction of measurement effort can be achieved by using a tomographic technique based on amplitude-phase-spectrum estimation, scale-invariant feature transform image registration, and constant false alarm rate detection. Besides an amplitude spectrum, the proposed method also obtains the phase spectrum of the scattering center distribution, which allows the application of polarimetric decompositions. The generation of full-polarimetric 3-D images is demonstrated based on measurement data obtained in a compact antenna test range. Since all relevant scattering mechanisms can be identified, the approach proved to be useful for an advanced understanding of the scattering mechanisms occuring at radar targets.
Physical Layer Biometrics Using Antennas for Secure Wearable Wireless Communication

This paper combines a study of human body morphology with physical layer characteristics to introduce a novel biometric identity feature for security in wearable communication applications. The physical layer characteristics of close fitting wearable devices are shown to vary in a unique manner through electromagnetic interactions between the tissue morphology and the antenna. Experimental measurement results demonstrate the new biometric concept using return loss characteristics to identify individuals on multiple body parts. An optimized directional coupler design is implemented with the antenna to optimize the characteristic feature detection range for human identification. Experiments conducted on human subjects using a prototype standalone test-bed and sensing circuitry at 2.45 GHz show that classification accuracies of over 98% are achieved for stationary subjects and 93% for mobile subjects. The new physical layer biometric has the potential to be used for authentication and authorization by using return loss as an indicator for secure user applications, using circuitry already implemented in wireless wearable communication systems.
On Quotient Structures of Fuzzy Multiset Finite Automata

The objective of this paper is to characterize the quotient structures of fuzzy multiset ﬁnite automata. We introduce different congruence relation on multiset associated with fuzzy multiset ﬁnite automata and show that each congruence relation associates a semigroup with the fuzzy multiset ﬁnite automata. We also discuss the charaterization of fuzzy multiset ﬁnite automata by deﬁning an admissible relation.
An Intelligent Cognitive System Design for Mobile Robot based on Optimization Algorithm

in this paper, a cognitive system based on a nonlinear neural controller and an intelligent algorithm is used to guide an autonomous mobile robot during continuous path-tracking. The controller will navigate over solid obstacles with avoidance. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment in order to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization and Artificial Bee Colony algorithms are used for finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths. The algorithms are used for finding the reference path equation of the optimal path, as well as finding and tuning the neural control gains values online for the nonlinear neural controller. The goal is to obtain the best torques actions of the wheels for the mining autonomous mobile robot. Simulation results are done by using MATLAB which showed that the proposed cognitive system is more accurate in terms of planning a reference path to avoid obstacles, online finding, and tuning parameters of the controller which generates smooth control actions without saturation for tracking the reference path equation, as well as minimizing the mobile robot tracking pose error.
3D Object Manipulation Techniques in Handheld Mobile Augmented Reality Interface: A Review

Handheld mobile devices referring to mobile phones and tablets become the major output medium for augmented reality (AR), which have seen significant growth in popularity and usage among the public due to the growing release of consumer-oriented communication products nowadays, especially touchscreen smartphones. Unlike traditional desktop or tabletop AR (large display-based) and head-mounted display-based AR systems, small display-based AR (handheld mobile display) requires different interaction techniques that mostly utilize single-hand interaction as well as the limitation of small screen display and limited activity time due to the battery operation hour of handheld mobile devices. However, in handheld mobile AR, research is still lacking, especially research that focuses on 3D interaction in handheld mobile AR for virtual object manipulation. Thus, this paper provides an overview of 3D interaction techniques in handheld mobile AR with critical analysis. First, we describe three main interaction technique categories that applicable in handheld mobile AR, which is touch-based interaction, mid-air gestures-based interaction, and device-based interaction techniques, of their basic concepts on 3D object manipulation. Then, we classify and systematize the highlighted techniques and discuss the advantages and drawbacks of each. Previous studies for widely used techniques have been studied comprehensively. We then draw up a comparison among the different techniques based on the important elements considered in handheld mobile AR. The aim of this paper is to provide researchers with background information on AR and those who are interested in the field of 3D interaction, realizing each technique category.
Design and Optimization for Double-Sided Interdigital Transducer with Piezoelectric Substrate

The interdigital transducer (IDT) is the most basic unit of the surface acoustic wave device. The optimization design of double sides IDT can make contribution to the improvement of driving performance. In this paper, the finite element analysis method was used to calculate the influence between the geometry parameters and the driving performance of double-sided IDT based on a piezoelectric substrate utilizing COMSOL Multiphysics. And the effect of electrode width and electrode gap on the driving strain under IDT unit voltage was also analyzed. The results show that the smaller the thickness of the substrate, the more helpful of improving the driving sensitivity of the IDT. The driving voltage was reducing with the decreasing of the electrode gap. And the optimal piezoelectric driving performance can be obtained when w / t =0.33. This work provides theoretical guidance for the optimal design of double-sided IDT.
Broadband Circularly Polarized Planar Monopole Antenna With G-Shaped Parasitic Strip

The design of a broadband circularly polarized compact monopole antenna is proposed in this letter. By protruding a G-shaped parasitic strip into a C-shaped monopole antenna structure, two orthogonal modes are created with equal amplitude and 90° phase difference for circular polarization. A 3 dB axial-ratio bandwidth (ARBW) of the antenna is greatly extended by using a modified ground plane. With the help of these features, a compact broadband circularly polarized antenna is designed and fabricated. Experimental results show that the proposed antenna realizes –10 dB impedance bandwidth of 62.94% (3.92–7.52 GHz) and ARBW of 53.92% (4.28–7.44 GHz). Overall size of the proposed monopole antenna is <inline-formula><tex-math notation="LaTeX">$0.57{\lambda _0} \times 0.61{\lambda _0} \times 0.03{\lambda _0}$</tex-math></inline-formula>, where <inline-formula><tex-math notation="LaTeX">${\lambda _{0\;}}$</tex-math></inline-formula> is the free-space wavelength at the center frequency of the operating bandwidth. The proposed antenna is desirable for WLAN (5.15–5.85 GHz) applications and various wireless communication systems.
A Compact Tri-Band Horizontally Polarized Omnidirectional Antenna for UAV Applications

A compact tri-band horizontally polarized (HP) omnidirectional antenna is proposed. The HP omnidirectional antenna consists of a folded patch inside a metal box with a vertical slot. The tri-band antenna operates in the first-order resonant mode of the folded patch for the lower band, while it works in the second-order mode for the upper band, featuring a compact size of 0. 32λ<sub>0</sub> × 0. 16λ<sub>0</sub> × 0. 08λ<sub>0</sub>. For the middle band, a slot mode is excited by the folded patch. Two slits on the folded patch are introduced to enhance the bandwidths of the tri-band antenna. It is shown by experiment that the tri-band HP antenna covers three frequency bands 840.5–845, 1430–1444, and 2408–2440 MHz specified by the Ministry of Industry and Information of China for unmanned aerial vehicle systems with good omnidirectionality.
Boundary Extraction Enhanced Distorted Born Iterative Method for Microwave Mammography

This letter focuses on improving the accuracy of the distorted Born iterative method (DBIM)-based inverse scattering algorithm, using accurate boundary extraction in microwave mammography. It is well known that the accuracy of inverse scattering algorithms depends on the initial estimate of the region of interest (ROI). The Envelope algorithm is one of the promising algorithms for accurate ROI estimation. However, in the near-field breast imaging scenario, the coupling effect between an antenna and the breast surface incurs a nonnegligible error for Envelope-based boundary extraction, which is mainly caused by the mismatching between the reference and measured waveforms. To address this problem, this letter introduces the finite-difference time-domain-based waveform reconstruction for improving the accuracy of DBIM-based microwave imaging. The two-dimensional numerical simulations, using realistic breast phantoms derived from magnetic resonance images, demonstrate that our proposed algorithm remarkably enhances the accuracy of the DBIM, even in highly heterogeneous cases.
Miniaturized Double-patch Antenna Design for WLAN Communication with CSRR DGS

In this paper, a microstrip double patch antenna is designed using CST microwave studio suite 2016. The designed antenna is constructed of two square patches on the top layer and a Complementary Split Ring Resonator (CSRR) as a Defected Ground Structure (DGS) on the grounded bottom layer. The antenna is set to operate at the frequency 5.8 GHz using an FR4 material as the substrate with a dielectric constant of 4.3 and a height of 1.5 mm (h). The proposed antenna can be utilized for the Industrial, Scientific, and Medical (ISM) band and Wireless Local Area Network (WLAN) applications. The proposed antenna can be fabricated at a low cost since it is compact with a low profile and good isolation. The size of the antenna is 64.5×36.25×1.5 mm3. The integration of the CSRR at the ground plane results in a size reduction of 35% and a better impedance matching (S11 = -39.6 dB), while it was -23 dB without CSRR. The parameters of the antenna such as input reflection coefficient, VSWR, far field characteristics and radiation pattern has been simulated and analyzed.
Location-Aware Network of Drones for Consumer Applications: Supporting Efficient Management Between Multiple Drones

Drones or Unmanned Aerial Vehicles (UAVs) are being deployed in numerous consumer applications to provide an enhanced quality of experience (QoE). Drone-assisted consumer applications are classified into three domains: data relaying, monitoring and data collection, and product delivery. We present a network of drones (NoDs)-based architecture to support efficient management between multiple drones for sensing, analyzing and processing data, and we summarize the open issues and future directions. This multi-UAV network utilizes the extended concept of a mobile ad hoc network for efficient packet transfer. Using this architecture, the use of location-aware drones has been presented as a product delivery and quality-of-service (QoS) enhancement agent for Internet services.
Breast Phantom Imaging Using Iteratively Corrected Coherence Factor Delay and Sum

In this paper, a system for microwave breast tumor detection is presented using iteratively corrected coherence factor delay and sum (CF-DAS) algorithm. CF-DAS is data independent, which makes it stable in a noisy environment. However, data adaptive techniques have made significant progress by enhancing the image quality in microwave tomography. Thus, a novel data adaptive iterative variant of CF-DAS is proposed in this paper to produce stable and accurate images. The microwave imaging (MI) system contains a rotatable array of nine modified antipodal Vivaldi antennas in a circular arrangement, an array-mounting stand based on the stepper motor, the flexible phantom mounting podium, a control system for RF switching of the transceivers, and signal processing unit based on personal computer involved in the reconstruction of the image. The impedance bandwidth of the modified antenna is recorded from 2.5 to 11 GHz with stable directional radiation pattern. For performing the transmission and reception of the microwave signals, an SP8T nine port RF switch is used ranging from 2.5 to 8.0 GHz, and the switching is controlled by MATLAB software. Several low-cost lab-based homogenous and heterogeneous phantoms containing the dielectric property of human breast and tumor tissue are prepared to test the system efficiency. Since typical data independent radar-based techniques are ill-equipped for multiple reflection scenarios, an iteratively corrected variant of CF-DAS algorithm is used for processing the recorded backscattered signals to reconstruct the image of the breast phantom and to identify the existence and locate the area of the multiple breast tumors. The proposed method achieves more than 10-dB improvement over conventional CF-DAS in terms of signal to mean ratio for four different phantoms measured in this study.
Compact Dominant Synergistic Excitation Pattern Learning for Illumination-Insensitive Image Representation With Boosting

Illumination-insensitive image representation is a great challenge in the computer vision field. Illumination variations considerably obstruct the effectiveness of image feature extraction. In this paper, we present a novel and generalized learning framework for illumination-insensitive image representation, which can learn the discriminative features through maximizing the inter-difference and minimizing intra-difference of the images with boosting. Particularly, we enhance the discriminative capacity of illumination-insensitive image representation in three aspects. First, we learn a subset of different synergistic Weber excitation patterns (SWEP) to generate the dominant SWEP (DSWEP) and DSWEP codebook for exploring optimal illumination-insensitive patterns. Second, a compact DSWEP (C-DSWEP) is learned with a boosted set of weight to generate C-DSWEP codebook. Discriminative learning is aimed at robustness and compactness. Third, the discriminative histogram learning model is established for encoding CDSEP to further improve the discriminative ability and reduce redundancy. The extensive experiments on CMUPIE, FERET, Yale B, Yale B ext. , LFW, and PhoTex databases have highlighted the superiority and the robustness of our method compared with some other state-of-the-art methods.
UAS application for urban planning development

The application of emerging technologies and robotics incites the growth of productivity on repetitive and exhaustive tasks. An example of emerging technology is the Unmanned Aerial Systems (UAS). It presents opportunities to contribute and carry out urban planning tasks in less time and risks. However, the field of UAS is still under development by the challenge of regulation and UAS capabilities. Therefore, a case study is presented to illustrate the process of UAS data collection to make better decisions in urban communities.
A Case Study of Multi-view News Exploration:Shanghai World Expo

In this paper, we introduce our system named multi-view news exploration system—NewsInsight. The system can help people to understand and explore news information from different views. We run the system on the 2010 Shanghai World Expo news data. Analysis result has been visualized and published on the web1. Through it, people can know important events and entities reported during 2010 Shanghai World Expo from multi-view, and read the news of their interest.
A Novel Biologging Tag that Minimizes the Hydrodynamic Loading on Marine Animals

Although biologging tags, which are externally attached sensor packages deployed on marine animals, have become essential conservation tools, a core issue with current tag designs is that they are rarely tested for hydrodynamics and may generate substantial hydrodynamic loading (drag and lift forces) on animals. This may cause tags to impede animal physiology, give rise to injuries at the site of attachment, and cause tags to relay unrepresentative data. This study aims to design a new biologging tag form that houses the DTAG3 electronics and reduces the total drag and lift induced on marine animals. One starting model (GPS Phone Tag referred to as Model 0), three iterations, and the final design (Model D), were constructed using CAD software. They were tested with Computational Fluid Dynamics (CFD) simulations to obtain and analyze the drag and lift force. All models were tested at speeds between 1-5 m/s, with 400 trials. The Model D includes a narrow elliptical shape to maintain laminar boundary layers, a pointed tail shape to avoid flow separation, canards for frontal downforce, tabs to reduce form drag, streamlined hydrophones, and dimples to delay flow separation. The CFD simulation results demonstrated that Model D reduced drag by up to 56% and lift by upto 86% compared to Model 0. These results show the potential benefit of this design in reducing the impact of biologging tags on the behavior and energetics of marine animals, and in providing an unbiased and holistic view of the animal behavior for conservation management actions.