Miracle-dz/UniFAR-FTUs huggingface dataset:
Ubiquitous Face-Ear Recognition Based on Frames Sequence Capture and Analysis

Unimodal biometric systems performance is known to be easily affected by intra-class variations, noisy samples, spoofing techniques and environmental conditions. These problems get even more challenging whenever biometric data acquisition is performed "in-the-wild". Some of these limitations can notably be addressed by means of multi-biometric approaches, exploiting different biometric traits, multiple samples and multiple algorithms to establish the identity of an individual. To this regard, the present study describes a face+ear biometric system requiring just a single combined video capture of the subject's face to work in a ubiquitous operative scenario. Exploiting the video capture capabilities provided by most smartphones' built-in cameras, the proposed method acquires subject's face both frontally and sideways within a single video sample. The resulting frames sequence is then analyzed to find the ones most suited, quality wise, to feed the two parallel biometric pipelines. Different data-fusion strategies, working either at score level with quality-based adaptive weighting or at decision level, have been applied to the output of face and ear matching stages to the aim of improving system's accuracy and reliability. Preliminary experimental results show good recognition accuracy coupled to an unusual easiness of operation for a ubiquitous multimodal biometric system.
An Efficient Authentication Scheme for Intra-Vehicular Controller Area Network

Communication in modern cars is managed by a controller area network (CAN) bus protocol and its extensions for electronic control units (ECUs). The CAN bus is a preferred method for reliable real-time broadcast communication. However, unprotected CAN communications make the vehicles vulnerable to a variety of practical malicious wired/wireless attacks. In this work, we analyze the existing frame-level authentication protocol and identify weaknesses and limitations. To address this, we provide a protocol suite for entity authentication, key management, a secure message flow for remote transmission request frames and session key update to be applied for vehicle connection with external devices. We prove the security of our protocol in the random oracle model and assess its resistance against known attacks. We formally verify the security of our protocol using the Tamarin tool. Our simulation results indicate that our protocol improves efficiency.
Delay dependent Stability analysis of Teleoperation Systems via input output approach

In this paper the stability analysis problem of bilateral teleoperation systems with time varying delay is studied. By using the scaled small gain theorem (SSG) with three therms approximation of delayed state, and choosing adequate Lyapunov-Krasovskii (L-K) functional a new stability criterion is expressed in terms of linear matrix inequalities. The criterion can be easily examined using standard numerical simulation.
Accelerated Zone-2 Protection Scheme for Transmission Lines using Traveling Waves

The acceleration of zone-2 distance protection scheme typically depend on the use of a communication channel. Communication based zone-2 protection scheme may not be feasible in case of degradation or failure of communication channel. This paper presents an accelerated distance relay zone-2 protection scheme using traveling wave arrival time information available at local terminal. Acceleration of distance protection zone-2 is done by using the information of faulted line. Faulted line is identified using first three arrival times traveling waves recorded at local terminal. The proposed technique is tested with PSCAD/EMTDC simulations with different fault types, fault resistances, and locations. The performance study confirms that the technique accurately identifies the faulted zone. This method is used as accelerated zone-2 distance protection scheme for EHV transmission lines when the communication link is failed or not available.
A Quasi-Elliptic Foot Trajectory Planning Approach Based on the Stochastic Linear Complementarity Problem for Electrical Quadruped Robots

Energy efficiency has been the focus of the quadruped robots since the appearance of this field. Most approaches have focused on the quadrupedal mechanisms or the actuation like series elastic actuation (SEA). This work aims to develop an optimal energy efficiency method to plan a quasi-elliptic motion trajectory for the quadruped robots. The energy efficiency of the DC motors in the electric quadruped robot is formulated as an optimization problem. The Stochastic Linear Complementarity Problem (SLCP) and sinusoidal pulse force are proposed to minimize the energy loss at the impact collisions. The stability and energy efficiency of the proposed algorithm is verified with the computer simulation.
Security Experiences in IoT based applications for Building and Factory Automation

Industry 4.0 and Industrial Internet of Things (IIoT) are promoting the connection of millions of devices, that once were seen as unconnectable, into a huge network, to be used in a large number of applications, from autonomous vehicles to industrial control systems, passing through building automation systems. These paradigm rely on the adoption of Cyber Physical Systems complemented with Internet of Things (IoT) technologies and artificial intelligence techniques. These type of systems are responsible for collecting, processing and exchanging a vast amount of data, and for that reason, it is imperative to assure data integrity and protection against malicious modifications and attacks to ensure a safe and reliable operation. Data thefts and cyber attacks in general represent a significant danger, however, cyber attacks on IoT systems can be specially critical due to their proximity with humans, enhancing the risk of physical damage. This paper highlights the importance of securing these systems, pursuing a safer operation, having in mind the amount of security vulnerabilities found in embedded devices. For this purpose, this article studies possible security threats and weakness in two case studies coming from different IoT domains, i.e. building automation and factory automation, while seeking for solutions to improve these systems' security.
3-Phase Multi-Functional Grid-Tied Inverter for Compensation of Oscillating Instantaneous Power

The primary objective of this paper is to present the basic terms of Conservative Power Theory (CPT) and its applications for compensating instantaneous power oscillations in three-phase three-wire systems. The reference signals for a three-phase multi-functional grid-tied inverter are derived using the instantaneous power and the instantaneous reactive energy terms defined by CPT, having the oscillating power components defined directly in a-b-c coordinates. The compensation method proposed in this study is validated through simulations based on practical power system modeling. The results presented here show the feasibility and singularities of the proposed method.
Summarizing the Slices: Sample-Based Core-Periphery Classification on Complex Networks

Core-periphery structure refers to a prevalent property exhibited by many real-world complex networks. The formulation and identification of a network core-periphery structure have been a challenging problem. A classical framework (BE) proposed by Borgatti and Everett defines a core-periphery partition of the network by aligning its nodes with a block model and has been a standard method for this task. This method, however, suffers from high computational costs which make it inapplicable to large networks. Realizing this limitation, we proposed a new framework, which aims to efficiently evaluate core-ness of nodes. Our framework builds a model for core-periphery classification by integrating small samples. The experimental results of six real-world networks shows that our methods can efficiently and effectively identify network core, achieving a running time of less than three hours for a network with about 220,000 nodes.
Optimization Design of a Novel 4-DOF Parallel Manipulator

This paper deals with optimization design of a novel 4-DOF parallel manipulator with 4 chains and 2 moving platforms. The linear motion between the moving platforms can be transformed into the rotary motion of the end effector. Based on the kinematic model, the dynamic model is derived by using the principle of virtual work. The workspace volume, error transfer characteristic, dexterity and stiffness evaluation indexes are investigated. Using univariate search technique, the multi-objective optimization is conducted and the optimal structure size ratio is solved.
Stress Identification during Sustained Mental Task and Brain Relaxation Modeling with $\beta/\alpha$ Band Power Ratio

Stress is the non-specific response of human brain which changes according to the demand of day to day life. In this paper stress and relaxation of brain is identified from the activation of alpha ($\alpha$) and beta ($\beta$) EEG bands depending on their power spectral density (PSD). Stress occurs due to sustained mental task in a test (Bengali, English, Math) environment and the work has been performed in to Reading, Writing and Mathematical problem-solving stages. When $\beta/\alpha$ power ratio is 1.5 or more it indicates stress. The relaxation of the brain is estimated taking the PSD at different time interval after the brain activity and when the $\beta/\alpha$ ratio returns to the value of relax state then it is determined that relaxation is obtained. Finally brain relaxation is modeled with mathematical formulation based on $\beta/\alpha$ power ratio.
Vision-based Follow-up Tracking of Random Moving Beam Target for Underwater Vehicle

For unknown underwater environment, longtime tracking of a moving beam target is a critical problem for autonomous operations of underwater vehicles. A vision-based method of tracking a random moving beam is proposed. The method consists of three steps. First, we let the underwater vehicle carry a binocular camera to acquire the laser beam target information. Then, we use the feature channel fusion and a Line Segment Detector (LSD) algorithm to extract the target information from the background, and build the motion model of the beam target. Second, a Kalman filter is used to realize the two-dimensional tracking of the laser beam. A binocular model is adopted to measure the three-dimensional motional state of the beam target. Third, we perform the motion control of underwater vehicle to achieve the follow-up tracking of the beam target. Simulations and experimens are established on a bionic fish platform. The results have shown that in an underwater environment with low flow velocity and little impurities, the proposed method can effectively track the random moving beam target with continuous stability.
Online Atlas as Decision Support System for Biomass Potential Assessment

This paper shows how to integrate data from enterprise database with spatial data, publish them together to online interactive map, and enable public users to perform analysis in simple web interface. The fact, that this is a public site, where users are not known in advanced and not trained, calls for importance of usability and intuitive user interface design. Also, system administrators are not willing to invest a lot of time in learning the basics of a system, and data providers need effective geoportals to enable access to spatial data and services via the Internet. All these needs should be reconciled during the implementation of the solution. Due to increasing interest of forestry and agricultural organizations in spatial data infrastructure (SDI) development and public users' needs for biomass data web presentation and analysis in Bosnia and Herzegovina, as case study is used the project of Biomass Potential Database with Online Atlas development. Additionally, here is proposed application of the geoportal using online atlas as spatial decision support tool.
Optimization of the PI controller to improve the dynamic performance of grid-connected photovoltaic system

Optimizing the Proportional–Integral (PI) controller parameters can enhance the photovoltaic (PV) operation when it is connected to the grid. In this work, optimization is carried out through using two optimization techniques. First one is Harmony Search (HS) approach. While the second optimization technique is the Teaching-Learning-Based approach (TLBO). MATLAB/SIMULINK is utilized to simulate a grid-connected photovoltaic (PV) model which is consisted of four arrays with maximum power of 100 kW each. Finally, this study presents comparison with four cases i.e. without PI controller, with manual tuning of PI controller, value of the PI controller by HS and value of the PI controller by TLBO. The comparison showed enhancing of Maximum overshot by around 20% and steady state error by around 65 % than manual tuning.
A Sound Source-based Intelligent Context Awareness System using CNN

A sound source-based intelligent context awareness system using convolutional neural network (CNN) is proposed and the sound recognition ratio was analyzes in this paper. The sound recognition rate was found to be proportional to the distance between the smartphone and the microphone. It is confirmed that the sound source is difficult to be detected when the distance between the microphone and the sound source is far greater than 1m on 1st experiment. However when the distance between the sound source and the microphone is 1m, the performance of the sound recognition rate is 40%-55% on 2nd experiment.
SICNN: Spatial Interpolation with Convolutional Neural Networks for Radio Environment Mapping

This paper addresses the spatial interpolation problem in measurement-based radio environment estimation. For accurate interpolation, we need to extract global and local radio features, i.e., path loss and shadowing features. To this end, we propose a novel convolutional neural network structure, referred to as SICNN, for interpolation problems. We also investigate the impact of kernel design in SICNN on the interpolation accuracy to demonstrate that there exists an optimal kernel size. Extensive simulations show that SICNN learns the global and local features to construct an accurate radio environment map from a few measurement data.
ESetStore: An Erasure-Coded Storage System With Fast Data Recovery

Erasure codes have been used extensively in large-scale storage systems to reduce the storage overhead of triplication-based storage systems. One key performance issue introduced by erasure codes is the long time needed to recover from a single failure, which occurs constantly in large-scale storage systems. We present ESetStore, a prototype erasure-coded storage system that aims to achieve fast recovery from failures. ESetStore is novel in the following aspects. We proposed a data placement algorithm named ESet for our ESetStore that can aggregate adequate I/O resources from available storage servers to recover from each single failure. We designed and implemented efficient read and write operations on our erasure-coded storage system via effective use of available I/O and computation resources. We evaluated the performance of ESetStore with extensive experiments on a cluster with 50 storage servers. The evaluation results demonstrate that our recovery performance can obtain linear performance growth by harvesting available I/O resources. With our defined parameter recovery I/O parallelism under some mild conditions, we can achieve optimal recovery performance, in which ESet enables minimal recovery time. Rather than being an alternative to improve recovery performance, our work can be an enhancement for existing solutions, such as Partial-parallel-repair (PPR), to further improve recovery performance.
Prediction of Heart Disease by Mining Frequent Items and Classification Techniques

These days immense abstraction of data yields and collected in every instance of time. So to analyze them is the toughest task to do. This immense volume of data has been generated from unlike sources like health care, social media, business applications, manufacturing industries and many more. HealthCare plays a pivotal role in Big Data. Spotting and safeguarding of the diseases at a primitive stage are very much crucial. Heart disease specifically implies the condition of the heart that contracts or obstructs blood vessels which result in pain in chest and heart attack. This paper emphasizes on the diagnosis of heart diseases at a primitive stage so that it will lead to a successful cure of the diseases. In this paper, frequent item mining is used for filtering the attributes and diverse data mining classification method like Decision tree classification, Naive Bayes classification, Support Vector Machine classification, and k-NN classification are used for determination and safeguard of the diseases at an early stage so that it can be treated and preventable.
Virtual Node Based Distribution Network Reliability Evaluation and Its Implementation on Parallel Computing Platform

Reliability evaluation is one of the most important assessments of the distribution network in its planning, which requires the usage of topology models and parameters from the distribution network automation system. To accelerate the reliability evaluation process of large-scale distribution networks, this paper proposes a virtual node-based reliability evaluation algorithm, which divides a feeder into feeder domains, load blocks, and virtual nodes. A virtual node based forward/ backward sweep algorithm is used to replace the minimum cut set based traditional approach, so the computation scale is reduced significantly. Based on the proposed evaluation algorithm, its parallel implementation on Apache Spark platform is given. The experiment result proved the effeteness and performance of the proposed approaches.
Optimized First-order s-to-z Mapping Function for IIR Filter Designing

The Bilinear transform is widely used in IIR filter designing for the mapping of s and z planes. This transforms gives a stable first-order s-to-z mapping function. However, it suffers from frequency warping which deteriorates the digitally transformed system. In this work, an attempt has been made to develop an efficient first-order s-to-z mapping using PSO (particle swarm optimization) algorithm. The proposed s-to-z mapping function gives better linear mapping from s-to-z plane than the existing Bilinear transform. Therefore, proposed mapping function is less prone to frequency warping effect in IIR filter designing. Several mathematical simulations have been done to see the authenticity and merits of the proposed s-to-z mapping function.
An Optimization Deployment Scheme for Static Charging Piles Based on Dynamic of Shared E-Bikes

Shared e-bikes are popular because of their green, eco-friendly and efficient features. Due to the limited battery capacity of the e-bikes, the energy problem has become one of the main factors limiting its further development. The energy problem can be solved by using static charging piles (SCP) to replenish the batteries of shared e-bike. The location of the shared e-bike is time-varying, resulting in the optimal deployment of SCP as a complex location problem. In this paper, we propose an optimal Deployment algorithm for Maximum Coverage combined the Dynamic Changes of nodes (max-DCDC) based on the known number of SCP. This method first quantitatively analyzes the dynamic change process of the shared e-bike to reduce the deployment scope of the SCP. Then, according to the geometric characteristics of the e-bike distribution within the deployment scope to optimizes the deployment location of the SCP. Simulation experiments show that max-DCDC has better performance in terms of deployment stability and e-bike coverage compared with the other algorithms.
Speed Regulation for PMSM Drives Based on a Novel Sliding Mode Controller

This paper develops a novel sliding mode control technology and a comprehensive evaluation methodology for speed control of permanent magnet synchronous motor (PMSM). In most of the existing literature, only control precision of the speed corrector is investigated. However, the control strategy should be stable to the noise and disturbance caused by the environment and parameter uncertainties. In order to possessing faster dynamic response, stronger anti-interference ability and high stability of input, a highly stable sliding surface is proposed for siding mode control. Unlike most of reaching laws that requires the variation of designed sliding surfaces, this method takes state vectors in consideration. In addition, a comprehensive evaluation algorithm is presented to obtain reasonable assessment on speed control for synchronous PMSMs in different operating phases (starting, transient, steady-state rating). Finally, the simulation results verify the effectiveness and validity of the proposed sliding mode speed controller.
Performance Analysis of N-CAM, P-CAM and TG-CAM Using 45-nm Technology

Content addressable memory (CAM) is widely used in many applications, wherever we need fast memory access CAM provides a provision. CAM is faster due to the arrangement of core cells that allows parallel access, it searches total memory array in single clock cycle. CAM plays a crucial role in network applications because of its parallel access. In this paper, we explored and described about CAM architectures based on N-type, P-type and TG-type comparison circuitry. For faster memory search, we used a latch-type match-line (ML) sensing scheme. Search operations and results of the CAM designs have been verified using a 45-nm CMOS process at 27°C with 1 V supply in SPECTRE simulator. Based on the post-layout results of 32×32-bit arrays, the P-CAM provides the best performance comparatively.
Ultra Low Power High Gain High Speed OTA

In this paper, we present a push-pull Inverter based fully differential operational trans-conductance amplifier (OTA) working at 1V power supply with reduced power consumption and high speed performance. Authors have used a modified feed-forward compensated technique to achieve high DC gain and minimum power consumption. The circuit is simulated in standard CMOS 180nm technology. Simulation results obtained are as follows: 57.87dB of DC gain and 82°of phase margin with Unity Gain Bandwidth (UGB) of 4.32MHz for a capacitive load of 0.01pf, a slew rate of 14.13V/μsec and settling time of 93.17nsec have been achieved. The proposed design shows average power consumption of 253.3nWatt. Simulation results are same after post layout simulation. The maximum propagation delay calculated with parasitic capacitances is 65.68nsec. Along with 180nm technology the same OTA has been simulated on 90nm and 45nm technology and a comparative study by analyzing performance in all three technologies have been presented by the authors.