Miracle-dz/UniFAR-FTUs huggingface dataset:
Fixed-Time Synergetic Approach for Biological Pest Control Based on Lotka-Volterra Model

Biological pest control has a strong advantage in its non-chemical effects on the environment. In this study, a fixed-time synergetic control scheme for the biological pest control problems represented by the $n$ -dimensional Lotka-Volterra model was proposed. The proof of stability shows that the proposed controller can regulate the biological pest control systems with the characteristic of fixed-time convergence. The performance of the proposed scheme was demonstrated through simulation studies. The simulation results show that the pre-specified bound of the settling time can be satisfied regardless of the initial conditions, confirming a desired fixed-time convergence characteristic. Moreover, unlike the existing control policy based on the sliding mode control, the control inputs of the proposed policy are free from chattering.
Foam Evolution Inspired Modeling for Staged Construction of Ultra-Dense Small Cell Networks

Small cells (SCs) are expected to be ultra-densely deployed in or close to the traffic hot-spots in the fifth generation (5G) mobile networks to provide wireless capacity cost-effectively. Traffic hot-spots change over time, which means SCs cannot be deployed in a one-off manner as macrocells normally do, rather they should be constructed in a staged process. Hence, mathematical models that capture the time-varying staged-construction process, are urgently needed for operators to effectively predict the construction period, but are currently lacking. In this paper, inspired by the foam bursting process-a natural phenomenon that can be observed in daily life such as hand-washing, we first propose a novel model that can predict the time-varying expectation and logarithmic variance of SC coverage areas. Then, we verify the model by real network deployment cases. Additionally, in order to extract parameters from historical base station deployment data, a parameter estimation algorithm is designed and verified. The findings of the paper reveal that mobile operators should construct ultra-dense SC networks in a staged manner like how larger foams split into smaller ones.
Machine-Learning-Based Self-Tunable Design of Approximate Computing

Approximate computing (AC) is an emerging computing paradigm suitable for intrinsic error-tolerant applications to reduce energy consumption and execution time. Different approximate techniques and designs, at both hardware and software levels, have been proposed and demonstrated the effectiveness of relaxing the average output quality constraint. However, the output quality of AC is highly input-dependent, i.e., for some input data, the output errors may reach unacceptable levels. Therefore, there is a dire need for an input-dependent tunable approximate design. With this motivation, in this article, we propose a lightweight and efficient machine-learning-based approach to build an input-aware design selector, i.e., quality controller, to adapt the approximate design in order to meet the target output quality (TOQ). For illustration purposes, we use a library of 8-bit and 16-bit energy-efficient approximate array multipliers with 20 different settings, which are commonly used in image and audio processing applications. The simulation results, based on two sets of images, including an 8 Scene Categories Dataset, which is a benchmark of images data set, demonstrate the effectiveness of the lightweight selector where the proposed tunable design achieves a significant reduction in quality loss with relatively low overhead.
Integration of Forming Manufacturing Technology into the Component Production of Innovative Electric Motor Concepts

Constantly increasing demands on production technology, such as sustainability and climate protection, require continuous optimization or even new development of production processes and designs, including in the field of electrical engineering. For this reason, it is also necessary to exploit the potential of various manufacturing technologies in order to achieve higher efficiency of the running machines. One way to achieve this goal is the application-optimized use of forming technology, which is less material-intensive due to its characteristics compared to, for example, cutting technology. Its use also allows better utilization of the special properties of electrical steel used in electrical machine construction or increases the so-called slot filling factor of electrical coils.Usually, motor stators consist of axially stacked, non-grain-oriented electrical steel (ngo), in whose motor slots coils of wound round wire are placed. The grain orientation of the sheets used has an influence on the amount of iron losses of the motor. With the use of round wire for the electric coils, only a slot filling factor of approx. 65 % can be achieved and thus potential for increasing the magnetic field of the coil is available. In order to achieve a higher slot filling factor, it is necessary to adapt the cross-sectional shape of the conductor material to the corresponding installation position by means of forming.In the present paper a novel approach for stator design with so-called flux barriers and thus the possibility of using radially laminated, grain-oriented plates are presented and the latest research results are shown. In addition current measurement results for the forming technical optimization of the increase of the slot filling factor of electrical coils with adapted conductor cross sections are presented and discussed.
Hybrid Reference Governor-Based Adaptive Robust Control of a Linear Motor Driven System

The linear motor driven system has been widely used in the manufacturing industry, where high motion tracking accuracy is required, including fast dynamic response and high steady-state tracking accuracy. However, the improvement of the motion control performances is limited by parametric uncertainties and uncertain nonlinearities, such as nonlinear friction, varying load mass, etc. In addition, the system constraints owing to input saturation and speed/space limitations also challenge the improvement of the motion control performances. In this paper, a hybrid reference governor-based adaptive robust control (HRGARC) algorithm is proposed for the constrained motion control of the linear motor driven system. The proposed approach is composed of two reference governor (RG)-based adaptive robust controllers (RGARC) and a switching strategy. For each RGARC, the RG is utilized to deal with input/state constraints, and the adaptive robust control (ARC) algorithm is used to cope with parametric uncertainties and uncertain nonlinearities. These two RGARCs are specifically designed to achieve fast dynamic response and high steady-state tracking accuracy, respectively. Furthermore, a switching strategy is designed to coordinate these two RGARCs according to the system states and the input reference. Therefore, the high transient and steady-state motion control performances of the linear motor driven system can be achieved by the proposed HRGARC in the presence of parametric uncertainties, uncertain nonlinearities, and input/state constraints. Comparative experiments conducted on the linear motor driven system validate the effectiveness of the proposed HRGARC algorithm.
A Review on Movie Recommendation System Using Machine Learning

System which gives recommendations usually filters the given data using various methodology and suggests the relevant one to the customer benefit. In day-to-day life people usually use a powered recommendation system in many areas like movies, books, music, news, items etc. In this paper a wide range of work is reviewed in the field of a recommender system for movies where dataset source, methods used and accuracy are compared to deduce best one and future scope for improvement in this area are analyzed.
SYN Flood Attack Detection and Mitigation using Machine Learning Traffic Classification and Programmable Data Plane Filtering

Distributed Denial of Service (DDoS) attacks are widely used by malicious actors to disrupt network infrastructures/services. A common attack is TCP SYN Flood that attempts to exhaust memory and processing resources. Typical mitigation mechanisms, i.e. SYN cookies require significant processing resources and generate large rates of backscatter traffic to block them. In this paper, we propose a detection and mitigation schema that focuses on generating and optimizing signature-based rules. To that end, network traffic is monitored and appropriate packet-level data are processed to form signatures i.e. unique combinations of packet field values. These are fed to machine learning models that classify them to malicious/benign. Malicious signatures corresponding to specific destinations identify potential victims. TCP traffic to victims is redirected to high-performance programmable XDPenabled firewalls that filter off ending traffic according to signatures classified as malicious. To enhance mitigation performance malicious signatures are subjected to a reduction process, formulated as a multi-objective optimization problem. Minimization objectives are (i) the number of malicious signatures and (ii) collateral damage on benign traffic. We evaluate our approach in terms of detection accuracy and packet filtering performance employing traces from production environments and high rate generated attack traffic. We showcase that our approach achieves high detection accuracy, significantly reduces the number of filtering rules and outperforms the SYN cookies mechanism in high-speed traffic scenarios.
Design of Filtering Power Divider Based on Half Mode Substrate Integrated Waveguide

A design method for broadband filtering power divider (FPD) based on half mode substrate integrated waveguide (HMSIW) is proposed in this paper. Fourth-order Chebyshev bandpass filter is employed to achieve wide bandwidth and good frequency selectivity. Isolation resistors is optimized to improve the isolation performance of the FPD without extra circuits. The equivalent circuit of the FPD and a simple corresponding analysis are given. Finally, an FPD with Fourth-order wide bandpass response has been designed and fabricated with center frequency of 3 GHz and 3-dB fractional bandwidth is 31.1%. The measured results show good agreement with the simulated ones.
Eco-Platooning for Cooperative Automated Vehicles Under Mixed Traffic Flow

The mixed traffic flow, which comprises both cooperative automated vehicles (CAVs) and human-driven vehicles, is becoming more common in modern urban areas. CAVs can expand the capabilities such as that can be achieved with automation and vehicular communication individually. However, the energy-saving benefits may be one of the exceptions when three or more vehicles drive in a row under the mixed traffic scenarios. The undesired driving behaviors of human-driven vehicles can introduce a high level of randomness to traffic flow, which results in energy-inefficient driving profiles for CAVs with aggressive operations or even vehicle crashing. In this paper, we investigate an eco-platooning problem for CAVs under the mixed traffic flow. This is a challenging problem due to both of the platoon-wide energy-saving and driving security requirements. To address this problem, an ecological and string stable platooning scheme, called E-CACC, is provided. First, novel spacing policies are presented to enforce that all platoon members track energy-efficient driving profiles. Then, control laws are designed to ensure the tracking performances of the proposed spacing policies. Furthermore, the theoretical proof is provided to prove the platoon string stability of the proposed strategy. Finally, performance evaluation is conducted. Results have illustrated the energy efficiency of the proposed E-CACC scheme.
Polymer Optical Fiber Sensors for Treadmill Instrumentation

This work proposes the development of two systems formed by POF-based sensors for simultaneous monitoring of breathing rate and ground reaction force (GRF) during walking on a treadmill. The breathing rate sensors are allocated in a elastic band while the GRF sensors are allocated below a treadmill belt. The proposed system is flexible, robust against electromagnetic interference, has simple implementation and presents low cost. Results showed similarity with the literature, presenting curve similar with gait pattern found in other works. In addition, results showed the ability of breathing rate long-term monitoring under static and dynamic conditions.
Ultra-Wide Band Terahertz Filter using Dendritic Cell-Cluster Metasurfaces

In this paper, we have proposed an ultra-wideband filtering structure based on dendritic Cell-Cluster Metasurfaces in THz regime. The proposed structure consists of Metal-Dielectric-Metal (MDM) array which consists of a dendritic cell to enhance the bandwidth due to multiple resonances. The basic dendritic structure consists of a rod which is split into four rods in the first step. Each split rod is further split into 3 rods. The procedure of splitting is done three times. Numerical simulation results reveal that the proposed structure performs wideband filtering from 2.15 THz to 3.46 THz with transmission efficiency better than 77% at the centre frequency and better than 94% and 86% at band edges. Physical mechanisms involved in broadband filtering characteristics were thoroughly considered. Compared to previous designs, the proposed filter is widest and has the highest transmission efficiency. Such filters have potential applications in THz communication, imaging and astronomical observation systems.
High-Performance GeSn Photodetector Covering All Telecommunication Bands

We report the design and fabrication of a high-speed GeSn normal-incidence p-i-n photodetector. To realize high-speed detection in all telecommunication bands, we optimize the Sn content in the absorption layer, the absorption-layer thickness, and the device size. The responsivity of the 18-μm-diameter device at 1550 nm reaches 0.32 A/W with an extended cutoff wavelength of 1700 nm and a 3-dB bandwidth as high as 28 GHz under −3 V bias, clear open eye diagrams are also obtained under zero bias at 1630 nm. All the results indicate that the device has a significant potential for applications in Si-based optical telecommunication in all telecommunication bands.
Experimental performance analysis of an electromagnetic impact-drive microrobot

Embedding a wireless power source in a microrobot rises several constraints that can make the system non-functional: limited power, limited energy, or varying voltage or current. To avoid this situation, the robot should be able to work efficiently under varying voltage/current. We then propose a methodology that helps predicting if a given microrobot can meet these requirements. This methodology is applied on a microrobot that integrates a single two-dimensional digital electromagnetic actuator used for an impact-drive locomotion. We designed a prototype of the robot, qualitatively demonstrated its two-dimensional displacement and characterized it in one dimension. This characterization is used to demonstrate that the performance and the operating range of the microrobot are sufficiently adaptable to consider the integration of a wireless power supply.
High Gain Array Antenna Based on Odd Higher Order Mode

In this paper, a high gain array antenna based on odd higher order mode is proposed. Different from traditional microstrip array antennas, elements of this array are square patches of resonating at TM30 mode with large side lobes. In order to avoid the influence of the element side lobes on the directivity of array antenna, by controlling the array element spacing and number, the grating lobes of array factor can avoid the element side lobes and coincide with the null region of element pattern, which allows the TM30 mode can be used in array antenna designs. Simulated results show that the gain of the 8-element array antenna is 19.5dBi and the grating lobes level are lower than −15dB.
BALS: Blocked Alternating Least Squares for Parallel Sparse Matrix Factorization on GPUs

Matrix factorization on sparse matrices has been proven to be an effective approach for data mining and machine learning. However, the prior parallel implementations for matrix factorization fail to capture the internal social property embedded in real-world use cases. This article presents an efficient implementation of the alternative least squares (ALS) algorithm called BALSbuilt on top of a new sparse matrix format for parallel matrix factorization. The BALS storage format organizes the sparse matrix into 2D tiles to avoid repeated data loads and improve data reuses. We further propose a data reordering technique to sort sparse matrices according to nonzeros. The experimental results show that BALS can yield a superior performance than state-of-the-art implementations, i.e., our BALS generally runs faster than Gates’ implementation over different latent feature sizes, with a speedup of up to 2.08× on K20C, 3.72× on TITAN X and 3.13× on TITAN RTX. When compared with alternative matrix factorization algorithms, our BALS consistently outperforms CDMF, cuMF_CCD, and cuMF_SGD over various latent feature sizes and datasets. The reordering technique can provide an extra improvement of up to 23.68 percent on K20C, 19.87 percent on TITAN X and 20.38 percent on TITAN RTX.
Intrusion Detection System Through Advance Machine Learning for the Internet of Things Networks

Network security is the main issue in the Internet of Things networks because most manufacturers do not focus on security standards during design. The performance of firewalls, intrusion prevention systems, and intrusion detection systems depend upon accuracy, thus its essentials, to enhance the detection rate to lessen false alarms. The objective of the firewall is to find violations as per predefined rules and block the incoming risky traffic. However, it is very tough to differentiate between malicious and regular traffic due to advanced techniques of attack. To address these issues, a two-stage hybrid method is proposed. First, the genetic algorithm (GA) is applied to select appropriate features to improve the accuracy of the proposed framework. Next, the well-known machine learning (ML) algorithm, including the support vector machine (SVM), ensemble classifier, and decision tree are employed. The achieved accuracy is 99.8% through 10-fold cross-validation using a multiclass NSL-KDD database.
Circularly Polarized Substrate Integrated Waveguide Leaky-Wave Antenna with High Efficiency and Consistent Gain

This paper presents a compact circularly polarized (CP) substrate-integrated waveguide (SIW) leaky-wave antenna (LWA) with consistent gain and high total efficiency at millimeter-wave frequencies. The proposed antenna consists of two layers. The lower layer is a conventional slotted SIW LWA, while the upper layer is an S-dipole array. The S-dipole layer is introduced to achieve circular polarization and improve the total efficiency of the antenna. Simulated results demonstrate that the proposed antenna operates from 24.5 to 29.5 GHz and exhibits a continuous 32° CP beam scan with a realized gain variation between 13 and 14.2 dBic. Moreover, the axial ratio is maintained below 3 dB throughout the operating frequency band. The average realized gain and total efficiency are about 13.7 dB and 93%, respectively.
Study of Separation of Tungsten and Molybdenum from High W-containing Molybdate Acid Sodium Solution by Fe(OH)_3 Adsorption

Study is made of the possibility and technical requirements of separating tungsten from high W-containing Na_2MO_4 solution by Fe (OH)_3 adsorption.The results showed that each absorption resulted in 70%～80% tungsten separation from molybdenum at pH =7.0 and with consumption 2～4 times more than that of WO~(2-)_4. When WO_3/Mo=(0.445),WO_3/Mo is reduced down to 0.17～0.18 through the first absorption.A new method is developed to neutralize sodium molybdate solution with HCl and NH_4Cl as neutralizer,which can notably improve recovery and separating effect.
Gaped Two-Loop Antenna-Based Magnetic Transceiver With an Empirical Model for Wireless Underground Communication

This paper presents a practical low-power, low-frequency magnetic induction (MI) transceiver based on symmetrical gaped two-loop antennas with an empirical circuit model for wireless underground communication. Because of the quasi-two-dimensional loop antennas for the transmitter (Tx) and the receiver (Rx), the tailored hardware platform is not only simple, but can be readily extended to a mutually orthogonal 3-D scheme. Through a mixed model of actual measurement data and theoretical parameters, we developed the two-loop antenna with the space of the antenna radius optimized for energy efficiency. The Tx power almost doubles that of the single Tx one, which provides channel expansion as well as system stability in terms of the Tx current level. Accordingly, the Rx signal is considerably increased by 9.5 dB in contrast with a typical single-Tx single-Rx configuration. Moreover, we used empirical-based modeling for a reliable electrical model. The empirical mutual inductance, which was modeled in a 25 m corridor, resulted in a channel correction factor of 0.86, showing that the signal intensity was reduced by 14% in the underground corridor compared to the free space. A maximum range of 68 m under a SNR of 9.5 dB and a path loss of 100.7 dB on a load of $50~\Omega $ at 34.5 dBm were predicted from the model. In addition, this study confirmed the system feasibility by a SNR of 8.7 dB in a practical lossy environment between two floors, where its value was converted into a MI channel at a distance of 70 m in the underground corridor.
A Novel Wireless Communication System using Programmable Metasurface Operating at 28 GHz

In communication technology, a programmable metasurface (PM) is a promising antenna array concept to overcome the severe path loss at millimeter-wave (mmW) frequencies. It enables electronically steerable beamforming by using a normal feeding antenna without the need of parallel radio frequency (RF) chains as conventional multiple input multiple output (MIMO) and phased array structures. These advantages offer PM the chance to be a part of future communication developments. In this work, a novel communication system using a PM operating at 28 GHz is presented. In order to prove the system performance, communication signal transmission as well as an exhaustive channel estimation algorithm have been implemented. The measurement results show great system performances, which nicely match with theoretic results.
Essential oil composition of different parts of endemic species Seseli gracile Waldst. & Kit. (Apiaceae) from natural and cultivated conditions

The chemical composition of the essential oils of Seseli gracile Waldst. & Kit. from natural habitat (Đerdap gorge, Serbia) and from cultivated plants (Belgrade, Serbia) were characterized. The essential oils of the root, aerial parts, inflorescence and fruit were analyzed by GC/MS and GC/FID. Monoterpene hydrocarbons were the main compounds in the essential oil of aerial parts (45.2-93.0 %), inflorescences (84.1 % and 90.0 %) and fruit (85.0%). Polyacetylenes (38.8% and 87.6 %) were dominant in the essential oil of root. The cluster analysis revealed that there were significant differences in the chemical composition of the S. gracile oils at different phenological stages. On the other hand, essential oils from the aerial parts from natural and cultivated plants showed quite uniform qualitative composition. The aerial parts essential oil from natural habitat contained higher content of para -cymene (mean values 17.3 % vs . 6.5 %) and lower amounts of terpinolene (mean values 23.1 % vs . 49.9 %). Also polyacetylene falcarinol was present only in the aerial parts samples from natural habitat. The essential oil of inflorescences from natural habitat contained higher concentration of terpinolene, quite similar amount of para -cymene and lower content of α-pinene.