Miracle-dz/UniFAR-FTUs huggingface dataset:
Super twisting control algorithm for Velocity Control of Mobile Wheeled Inverted Pendulum Systems

This paper deals with the design and verification of a nonlinear control algorithm for the Mobile Wheeled Inverted Pendulum (MWIP) systems. The algorithm is based on the second-order sliding mode control known as Super-Twisting Algorithm (STA) which is able to eliminate the “chattering” phenomenon and ensure robustness with respect to bounded disturbances. The stability of the closed-loop system can be guaranteed according to Lyapunov theorem. In order to show the effectiveness of the proposed controller, a simulation was carried out to make the basic MWIP model move at a constant speed. Additional simulation-testings considering model uncertainties and external disturbances were also provided to verify the effectiveness and robustness of the STA. Comparisons with the Sliding Mode Control (SMC) were given to demonstrate the superiorities of the STA and the results show the favorable performance of the proposed controller in terms of chattering elimination and robustness.
Stress Response Index for Adverse Childhood Experience Based on Fusion of Biomarkers

Adverse childhood experiences has been suggested to cause change in physiological processes and can determine the magnitude of stress response which might have significant impact on health later in life. For this reason, detection of this altered stress response can be used as an indicator for future health. To detect the altered stress response, biomarkers that represent both autonomic nervous system (ANS) and hypothalamic-pituitary-adrenocorticol (HPA) is proposed. This study fuses the biomarker that represents both ANS and HPA as a single measure to classify the stress response based on adverse childhood experience and propose a stress response index as an future health indicator. Electrocardiograph (ECG), blood pressure, pulse rate and salivary cortisol (SCort) were collected from 12 participants who had adverse childhood experience while the remaining 11 acted as the control group. The recording session was done during a Paced Auditory Serial Addition Test (PASAT). HRV was then computed from the ECG and the HRV features were extracted. Next, the selected HRV features were combined with other biomarkers and the performance of the fused features were compared. From the result, fused feature by the parallel fusion; known as Euclidean distance (ed) demonstrated the highest performance with 80.0% accuracy, 83.3% sensitivity and 78.3% specificity. This performance was achieved using Support Vector Machine. Finally, the fused feature was fed into SVM in order to model the stress response index as an indicator for future health.
A Deep Convolutional Neural Network for Food Detection and Recognition

In this paper, we propose a new deep convolutional neural network (CNN) configuration to detect and recognize local food images. Various types of food with different color and texture reflect the fact that the food image recognition is considered a challenging task. However, deep learning has been widely used as an efficient image recognition method, and CNN is the contemporary approach for deep learning to be implemented. CNN has been optimized to the tasks of food detection and recognition with few modifications. We present a new dataset of the most consumed local Malaysian food items which was collected from publicly available Internet sources including but not limited to, image search engines. For evaluation of recognition performance, CNN achieved significantly higher accuracy than traditional approaches with manually extracted features. Additionally, it was found out that convolution masks show that the features of food color dominate the features map. For the process of food detection, CNN also exhibited considerably higher accuracy than other conventional methods.
Photovoltaic system grid-connected with active power filter functions for mitigate current harmonics feeding nonlinear loads

In this article a photovoltaic system with active power filter functions is proposed in order to mitigate current harmonics generated by a nonlinear load, connected to the point of common coupling. The modeling and control of the photovoltaic system is developed. It is used the proportional resonant controller to control the current injected into the electrical grid. Also, the THD of grid current is analyzed to verify the effect of compensating current generated by the photovoltaic inverter. The simulations were performed using the Matlab/Simulink software considering three different loads: R load, rectifier with RL and RC load, and these results validate the proposed system.
Tuning A Three-Phase Separator Level Controller via Particle Swarm OptimizationAlgorithm

Three-Phase Separators are used to separate well crudes into three portions; water, oil, and gas. A suitable control system should be in place to ensure the optimum function of the Three-Phase Separator. The current PID tuning technique does not provide an optimum system response of the separator. Overshoot response, offset, steady-state error and system instability are some of the problems faced. Besides, the current method used is purely based on trial and error which is time consuming. There is room for improvement of the current PID tuning technique. An artificial intelligence (AI) PID tuning technique called Particle Swarm Optimization (PSO) is introduced to improve the system response of the Three-Phase Separator. The PSO algorithm mimics the behaviour of bird flocking and fish schooling striving for its global best position. In our case, the global best position is replaced with the optimized PID tuning parameters for the separator. The PSO algorithm has been used in several other applications such as the Brushless DC motor and in the Control Ball & Beam system. It has proven to be an effective tuning technique. Tuning of the Three-Phase Separator via PSO could prove to be an effective solution for Oil & Gas industries.
One More Reason to Reject Manuscript about Machine Learning for Structural Health Monitoring

Two major journals in mechanical engineering field put forward a special note for author(s) of articles discussing structural health monitoring. Only contributing new classifiers or new features without applying engineering knowledge or principle is considered insufficient. This article intends to provide empirical evidence to support the decision. This work shows the classification accuracy of a machine learning approach strongly depends on the number of training data. A high accuracy can simply be obtained by training the classifier with a large dataset, which is hardly realizable in practice. Meanwhile, the features and classifier that based on a sound engineering principle can provide a level of classification accuracy independent of the number of training data.
Internet of Things: Concepts, Architectures and Technologies

Internet of Things – IoT – has opened up opportunities for the development of new applications in various segments, being one of the drivers of the revolutions that are occurring in cities and industries. Smart cities and Industry 4.0 represent these revolutions. Given the breadth of concepts and technologies related to IoT, this work seeks to present an overview of these different aspects that support the development of solutions for IoT. In this work, we present a literature review and identify the primary hardware and communication technologies, protocols, algorithms, and security and privacy services for IoT.
Small Size Inverters: Development Challenges for PV, Renewable Energy Applications, as Well IoT, EMC, Lightning and Robustness Tradeoffs

This work discusses the main design issues for small size inverters (implemented as micro and mini inverters) as an alternative approach to the central inverter targeted for small to medium size photovoltaic (PV) applications. Topological and architectural aspects besides the cost are discussed based on the current markets and manufacturers products. With the natural technology advancement, including newer semiconductor switches and smart power integrated circuits (ICs), a compromise between the topology and cost will define how new products will become more competitive, as a single or a multiple module micro inverter. This scenario gives to its advantages yet in comparison with central approach, considering technical/cost gap reduction due to this technology advancement. Modern electromagnetic compatibility (EMC), robustness and lightning tradeoffs that always have heavy impact on development, as well as newer Internet of Things (IoT) implementation needs are discussed also in order to stabilize a development road map to near future.
Intelligence of Things: Opportunities & Challenges

The Internet of Things (IoT) is a promising technology that can connect and communicate virtual and physical objects globally. It allows billions of devices to be connected and communicate with each other to share information that creates new application and services. These services result in improving our quality of life. On the other hand, Artificial Intelligence (AI) is applied in many fields of science. It aims to understand techniques that require an intelligent action and solve complex problems. Integrating IoT with AI will create a powerful technology that can solve many of IoT problems that relate to the huge amount of data created by different IoT devices. With the huge analytic capabilities of AI, IoT data can be analysed efficiently to extract meaningful information. In addition, AI can help IoT devices to interact with humans and other objects intelligently and make autonomous decisions. This paper provides an overview of the integration of the IoT with AI by highlighting the integration benefits and opportunities of AI in different IoT applications. Challenges standing in the way of successful convergence of IoT with AI are also discussed. We can conclude that the integration of AI with IoT will generate a robust technology that can help companies to avoid unplanned downtime, increase operating efficiency, and enable new IoT applications and services.
Complex network dynamics in self-assembled atomic-switch networks: prospects for neuromorphic computation

The inherent power of the biological brain, with regard to pattern recognition, is unparalleled and cannot even be matched by multi-million dollar supercomputers. Inspired from this, neuromorphic computation, where ideas originating from the complex structure and functionality of the biological brain are utilized for advanced computation has shown great potential. In this regard, we are developing on-chip pattern classification capabilities via inexpensive self-assembly of nanoparticles (NPs). The formation of percolating microstructure of Sn NPs and tunnel junctions leads to a complex atomic-switch network (ASN) poised near criticality. Voltage stimulation is utilized for modulating the synaptic structure of the network, which shows potential for utilization as a ‘reservoir’ in reservoir computing (RC).
A modified bow-tie antenna for Universal UHF RFID application

In this paper, a modified bow-tie antenna is proposed for the universal UHF RFID hand-held reader application. The proposed antenna consists of three parasitic elements which is placed on the edge of the structure and one in front of the bow-tie to enhance the gain. The parasitic strip placed in front of the radiating element, act as a director improve the gain. The proposed antenna is fabricated and tested. The measured reflection coefficient bandwidth is 44.97% (810 MHz to 1280 MHz), which covers all the UHF RFID systems.
Crosstalk Reduction Design and Analysis of the Planar Meander Transmission Lines

In this paper, crosstalk reduction of parallel planar meander transmission lines (PMTLs) is investigated and analyzed in detail. The performance of the transmission characteristic, reflection characteristic and crosstalk characteristic of the PMTLs with different bending angles are discussed to understand the crosstalk design in high speed printed circuit board (PCB) design. Then, defected microstrip structure (DMS) method is used and etched on a microstrip transmission lien for crosstalk reduction. The proposed PMTLs and DMS-PMTLs are verified by using the HFSS which is based on FEM. The simulation results show that the crosstalk is minimal when the bending angles of the PMTL equals to 135 degree. For bending angle of 105 degree, the far-end crosstalk and the near-end crosstalk of the DMS-PMTL is reduced by about 24dB and 22dB, respectively. Moreover, equivalent circuit model of the DMS-PMTLs for bending angle of 105 degree is also extracted and given to provide an effective analysis method for analyzing the crosstalk, and the circuit simulation of the ADS agrees well with the full wave analysis.
Characteristic Modes Analysis to Integrate a Feeding Network in a Wideband Superdirective Array

In this paper we present the integration of a feeding network in a compact endfire array to insure a wideband superdirectivity. The integration of the feeding network is done with the help of the characteristic modes analysis (CMA). The CMA provides guidelines concerning the placement of the feeding network on the antenna structure in a way to minimize its effect on the radiating modes and hence maintaining a stable radiation pattern over frequency. Several examples are presented to demonstrate this approach. The best integrated feeding network provides a wideband directivity over the desired frequency with a matched impedance
Implementation of Secure Communication With Modbus and Transport Layer Security protocols

Industrial Control Systems (ICS) and Supervisory Control systems and Data Acquisition (SCADA) networks implement industrial communication protocols to enable their operations. Unfortunately, wide used protocols, such as Modbus and DNP3, lack basic security mechanisms that lead to multiple vulnerabilities. The exploitation of such flaws may greatly impact companies and the general population, especially for attacks targeting critical infrastructural assets such as power plants, water distribution, and railway transportation systems. Such problem gets worse in the context of photovoltaic Distributed Energy Resources (DER), where devices are commonly located in customers facilities, making difficult to enforce appropriate security policies. This paper addresses the security problems of the Modbus protocol, proposing a new secure version based on the Transport Layer Security protocol. Experimental results shows that the proposed solution achieves request/response times way below the 16.67 ms period of the power grid 60 Hz cycle, revealing a negligible impact in power grids applications.
Identification of in vivo Essential Genes of Vibrio vulnificus for Establishment of Wound Infection by Signature-Tagged Mutagenesis

Vibrio vulnificus can cause severe necrotic lesions within a short time. Recently, it has been reported that the numbers of wound infection cases in healthy hosts are increasing, for which surgical procedures are essential in many instances to eliminate the pathogen owing to its rapid proliferation. However, the mechanisms by which V. vulnificus can achieve wound infection in healthy hosts have not been elucidated. Here, we advance a systematic understanding of V. vulnificus wound infection through genome-wide identification of the relevant genes. Signature-tagged mutagenesis (STM) has been developed to identify functions required for the establishment of infection including colonization, rapid proliferation, and pathogenicity. Previously, STM had been regarded to be unsuitable for negative selection to detect the virulence genes of V. vulnificus owing to the low colonization and proliferation ability of this pathogen in the intestinal tract and systemic circulation. Alternatively, we successfully identified the virulence genes by applying STM to a murine model of wound infection. We examined a total of 5418 independent transposon insertion mutants by signature-tagged transposon mutagenesis and detected 71 clones as attenuated mutants consequent to disruption of genes by the insertion of a transposon. This is the first report demonstrating that the pathogenicity of V. vulnificus during wound infection is highly dependent on its characteristics: flagellar-based motility, siderophore-mediated iron acquisition system, capsular polysaccharide, lipopolysaccharide, and rapid chromosome partitioning. In particular, these functions during the wound infection process and are indispensable for proliferation in healthy hosts. Our results may thus allow the potential development of new strategies and reagents to control the proliferation of V. vulnificus and prevent human infections.
The Role of Prior Achievement as an Antecedent to Student Homework Engagement

The benefits of homework on student learning and academic achievement, to a large extent, depend on the degree of student engagement. Motivational engagement (my intention or why I do the homework), cognitive engagement (how I get involved in homework), and behavioral engagement (how much homework I do, how much time I devote to it, how I manage that time) are key aspects that condition the quality of the process of doing homework, learning, and academic achievement. Prior academic achievement is one of the variables that seems to be positively related to student engagement (both due its motivational component and to the training to do homework). The main purpose of this work was to study in detail this relationship in students of the last stage of Primary Education (N = 516). The results showed that (i) as achievement levels rise, the use of a shallow focus to doing homework decreases (and the use of a deep approach increases); (ii) there is also a progressive increase in the amount of homework done and in the management of the time dedicated to homework. On another hand, as in previous research, (iii) no relationship was observed between the levels of prior achievement and the amount of time spent doing homework.
Measurement of thickness of oxygen lance skull in LD converters using artificial vision

In the steelmaking process by conversion of pig iron into an LD converter, it is necessary to inject oxygen through a metal lance. During this process, part of the slag accumulates in the body of the lance, forming the so-called skull. The presence of this skull on the copper nozzle of the lance or on its body is critical, because in the stage of its own use, there will be a heating and possible fusion of the skull, helping to make the fusion of the copper possible, causing in crevices where the water would flow into the converter, thus increasing the risk of explosion. The skull on the surface of the lance can also create a layer of enough volume to prevent the movement of the lance through the flanges located on the converters. Such occurrence and practice of removal impair operator safety, the environment and productivity. In this project, a system for measuring the thickness of the oxygen lance skull of LD converters by computational vision was developed, then the actions related to the maintenance of the lance can be taken in a timely manner, thus avoiding possible problems.
Zero Sequence Power Contribution on BLDC Motor Drives. Part II: A FCS-MPC Current Control of Three-Phase Four-Leg Inverter Based Drive

This Part II paper presents a three-phase four-leg inverter based Brushless direct current (BLDC) drive able to extract smooth torque with the contribution of most of the back-EMF harmonic components, through the injection of the 3D petal-wave current. The proposed system allows the reduction of power loss in the stator winding at the same time it does not degrade the dynamic performance. To deal with the harmonic current injections, it is implemented a current control loop based on the finite control-set model based predictive control strategy (FCS-MPC). The presented control loop uses the discrete nature of the four-leg inverter to generate the appropriate switching states according to the online optimization of a cost function. The proposed high efficiency drive offers excellent reference tracking with no gain design effort in the inner current control loop while producing smooth mutual torque. The feasibility of the proposed strategy is verified by simulation results.
Awareness of Emotional Expressions in Cannabis Users: An Event-Related Potential Study

Cannabis use has been associated with anxiogenic effects when used in low frequency for a short duration, but cannabis can also have anxiogenic effects when used heavily for a long duration. Animal studies have indicated the neurobiological mechanisms related to cannabis and anxiety; however, research has been limited on the related neurocognitive mechanisms. Previous research has indicated that cannabis use is associated with alterations in event-related potentials (ERPs). The purpose of the current study was to examine anxiety related attentional processing of emotional expressions using ERP methods. We used a backward masking paradigm to restrict awareness of facial expressions (i.e., fearful, happy, and neutral). The results indicated that cannabis use was associated with differences in emotional processing. Specifically, the results suggested cannabis users had increased P1 amplitudes toward happy facial expressions compared to fearful and neutral. Additionally, cannabis users seemed to have reduced N170 hemisphere lateralization.
Business Intelligence for Construction Company Acknowledgement Reporting System

As the one of Indonesian association of construction service companies, the association ensure to recommend and record every construction service company (their members) to works according to valid Indonesian law and constitution. The problem in this association, as the job is to give detailed reports to government, investor either domestic or international, and every institutions that need information such as market needs, resource developments, and improvement of construction technologies, is to create queries for every data from tables in MySQL to create reports quickly, efficiently, and automatic. Example of reporting needs are: In what month construction project done at the most within 1 year; Project duration, project cost, and experience at the most for each construction company; or amount of projects based on source of funds (APBN, APBD, LOAN PEMERINTAH, BUMN, or SWASTA) for each construction companies. Recommended solution is using Data Warehouse where it has structured storage and can analyze data with OLAP that has capability to process and visualize data at high speed. To construct the Data Warehouse, the design used Kimball Method so this association company will have capability to generate report according to every instances' needs.
Multi-Port Single-Phase Converter Applied to Residential Microgeneration

This paper presents a multi-port, single-phase isolated converter applied to residential microgeneration, employing one ac port and multiple dc ones. The proposed system consists of solar photovoltaic (PV) modules, a battery bank, and two full-bridge converters working as a single integrated structure. A strategy is also proposed aiming at improved utilization of the ac utility grid through the power flow control between the electronic converter ports, which is performed according to some system parameters such as power levels generated by the PV modules and weather conditions. In order to achieve high power processing capability with low losses at high frequency, three-state switching cells and interleaved converters are employed. The main characteristics and operating stages regarding the system are introduced. Simulation results are presented to validate the control strategy, while the rms ac voltage is 220 V (60 Hz) and the voltages across the dc are 400 V, 96 V and 48 V, considering that the switching frequency is 50 kHz and the rated power is 1500 W.