Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of tourist demand, from COVID-19, on the sustainable Inca infrastructure of Ollantaytambo, Urubamba – Cusco – Peru

The objective of the study is to analyze how tourism demand impacts, in the sustainable Inca infrastructure of Ollantaytambo in Cusco during 2020 in COVID-19. Based on bibliographic reviews presented in other research, regulations, and registration of updated data from the last 10 years in the tourism sector, such as the registration of visitors, flights, and others. There was relying on GIS tools to determine its location and accessibility. For its development, there were stages of recognition and description of the study area, characterization of the physical and demographic aspects, analysis of the data collected and tourist demand, and identifying the impacts from COVID-19. It was found that By 2020, a considerable increase in the tourist demand of Ollantaytambo was expected. However, the repercussion caused by the COVID-19 pandemic, the visitor registration in Ollantaytambo fell by 73% compared to 2019 and flights fell by 71, 7%, thus concluding that tourism has had a significant drop, with uncertain prognostic. A change in the current tourist dynamics allows controlling the capacity, respecting the spaces, taking care of the visitor, and generating a greater organization for developing the tourist activity.
Multilayer Perceptron-based Skew-Angle Estimation for Bit-Patterned Magnetic Recording

Bit-patterned magnetic recording (BPMR) is the potential future recording technology that can increase an areal density (AD) of hard disk drives over 1 terabit per square inch (Tbit/in2). Several challenging problems are causing the reduction of a recording system's performance. One of them is a skew angle effect that is depended on the reading and writing position of a reader on a platter. Therefore, this paper proposes the skew-angle (SA) estimation method based on multilayer perceptron using readback signals. The accuracy percentage of the proposed SA estimation method provides above 80% when it was investigated under medium-high signal-to-noise ratio levels.
A New Regressive RBF Neural Network Model for Rate-Dependent Hysteresis in Reluctance Actuators

This paper presents a novel hysteresis approximation method for the rate-dependent hysteresis effect in reluctance actuators. The method is described by a regressive radial basis function (RRBF) neural network model, and its parameters are trained by a global optimization algorithm named dynamic opposite learning teaching learning based optimization (DOLTLBO). The regressive structure is adopted for solving the multivalued problem between the input and the output of the hysteresis nonlinearity, and the DOLTLBO algorithm fully exploits the approximation capability of the RRBF model, thus guaranteeing the low complexity of the neural network. Experiments were performed on reluctance actuators, and results show that the new model has high performance in hysteresis approximations for reluctance actuators when compared to previous models such as the RPI Model and the Chua model.
Toward Applying Fuzz Testing Techniques on the SUCHAI Nanosatellites Flight Software

The success of the CubeSat nanosatellites space missions depends on all systems ability to perform properly in a harsh environment. A key component in every space mission is the flight software, which manages all the processes that must be performed by the satellite on its onboard computer. Literature shows that CubeSat missions suffer high infant mortality and many spacecraft failures are related to flight software errors, some of them resulting in a complete mission loss. Extensive software testing is the primary tool used by flight software developers, to ensure code quality and avoid such failures. Nevertheless, CubeSat developers tend to use COTS or flight-proven solutions which usually have low testing coverage. Nowadays, there is still some pending matter in the field of testing nanosatellites flight software and some of the most used solutions do not even report unit tests. To overcome the agile CubeSat development versus delivering quality software trade-off, we propose the use of fuzz testing techniques applied to the SUCHAI series of nanosatellites, being developed at the University of Chile. The successful application of this technique allowed us to find and solve many bugs not covered by classic strategies, such as unit testing and software in the loop simulation.
Power Balancing in Cascaded H-Bridge and Modular Multilevel Converters Under Unbalanced Operation: A Review

Multilevel Voltage-Source Converters (VSC) based on modular structures are envisioned as a prominent alternative for grid and industry applications. Foremost among these are the Cascaded H-Bridge (CHB) and the Modular Multilevel Converter (MMC). In this context, depending on the application and the power conversion structure, unbalanced operating conditions can be asked to the converter. Previous investigations regarding the operation and the solutions for modular structures under unbalanced conditions have already addressed this topic, but information is dispersed over a wide number of sources. This paper identifies, classifies, and analyzes the intercluster active power balancing strategies for the adequate operation of the most commonly used modular structures in some typical unbalanced operating scenarios: the Static Synchronous Compensator (STATCOM) under unbalanced voltage and/or current conditions, the unequal power generation in large-scale photovoltaic (PV) power plants, and the uneven power distribution in a battery energy storage system (BESS). Each of the applications has been independently studied so as to provide a comprehensive analysis of the alternative techniques found in the specialized literature, clearly explaining their respective strengths and drawbacks. Several future challenges have been identified during the study, which will involve greater research effort in this key research topic.
SGedge: Stochastic Geometry-Based Model for Multi-Access Edge Computing in Wireless Sensor Networks

Multi-access edge computing (MEC) is used to provide low-latency computing services for users and offload computation-intensive tasks from users. The MEC network has two parts, a server and wireless sensor access networks, with the latter all independently connected to the server. In this study, the limited latency performance of a MEC network—namely, the communication and computation latency under coverage of the sensor access networks, as well as the stability of the server—is investigated. Moreover, referring to network constraints, the scaling laws are determined, which are for both communication and computation latency regarding network loads and resource parameters. The deduced scaling laws quantify the trade-offs between computing latency, network coverage, and stability.
Mycobacterium Tuberculosis Detection using Support Vector Machine Classification Approach

Tuberculosis (TB) is a transferable malady caused by Mycobacterium Tuberculosis (MTB) and invades when the infected people sneeze, cough and speak without mask. The germs can exist in the air for some hours that consequence persons who breathe in the air may become infected that mainly influence the lungs; it also influenced other limbs of the body such as spine, kidneys and brain. TB malady is very common due to the weakening of the immune system and the possibility of patient’s death enhances with time if left undiagnosed. Conventional TB diagnosis requires much time and money because of microscopic examination of sputum, so automatic recognition is more valuable to prevent serious consequences rather than manually. In this framework, we present an efficient approach for automatic identification of Tuberculosis using some image processing techniques. The role of DIP in medical is more prominent. Usually, most of the methods may deform the authentic information that generates false recognition but proposed scheme is dexterous enough to identify the TB infection automatically with very little execution instant and high accuracy. A learning model- Support Vector Machine (SVM) is useful for classifying impairment lungs. Before classifying the cells, image requires some enhancements i.e. Adaptive Histogram Equalization and Embossing that directionally compute the color differences. The novel system has been tested with 286 lung CT scan samples and on the basis of correct prediction; the system accuracy is 96.50%.
Institutional Research: Issue-Oriented Data Integration and System Construction

This study proposes an issue-oriented data integration and system-building model to promote institutional research. In direction of the issues, we advance the idea of grouping university stakeholders into the university, students, and the public. In the aspect of data integration and system construction, five steps are proposed: issue confirmation, information system and data inventory, data model establishment, data warehouse and data dictionary establishment, and system construction and data analysis. Finally, this study proposes several preliminary conclusions and suggestions on the promotion of institutional research for universities or researchers.
MIMO-Array Antenna With Beamforming for 5G Applications

A 5G MIMO-array antenna is designed on a Rogers’ RT/Duroid 5880 substrate (thickness= 0.25 mm) and proposed to resonate at 28.0 GHz, for the coverage in the intended directions. CST-Microwave studio is used to design and simulate the antenna. The presented MIMO-array achieved a gain of 7.58 dBi and an overall efficiency of 92.36% at the resonating frequency. Two beams pointing in two different directions are obtained at ± 200. The bandwidth of 570 MHz and ECC of less than 10-3 are achieved in the band. Very low value of channel capacity loss is observed in the operating band here.
Human-in-the-Loop Stability Analysis of Haptic Rendering With Time Delay by Tracking the Roots of the Characteristic Quasi-Polynomial: The Effect of arm Impedance

The uncoupled stability of haptic rendering has been analyzed extensively, predominantly using passivity considerations. Yet, the role of the operator in improving the stability of haptic systems has received less attention. Here, towards a human-in-the-loop stability analysis of haptic rendering with delay, we study the effect of the operator impedance on the stability boundaries. We employ a method that tracks the $j\omega$ crossings of the roots of a characteristic second order equation of a coupled system that includes the impedance of the operator, the haptic device, the rendered virtual stiffness and damping, and the time delay. We found that the consideration of a realistic operator impedance leads to significantly less conservative stable time delay margins. Moreover, for certain arm impedance parameters, the coupled system may allow for: (1) assuring delay-independent stability, and (2) being stabilized by increasing the delay. These results indicate that a human-centered approach can push the boundaries of safe haptic feedback, especially in applications where the delays are substantial and unavoidable, such as in teleoperation.
First Prototype of 2×2 SCARLET: Readout ASIC for Bump-bonded SDD Array for Large Event Throughput

SCARLET is a novel readout ASIC implemented for integration with monolithic Silicon Drift Detectors (SDD) arrays with bump bonding scheme, i.e. within hybrid pixel assembly, suitable for high-rate high-density energy-dispersive X-ray detection system in synchrotron beamlines or many industrial applications. The first version of the readout ASIC integrates complete pulse processing channel in a pixel structure, consisting of reset-type CSA with PMOS input stage, 7th order semi-Gaussian shaping amplifier, peak stretcher equipped with independent peak detector circuit and optimum pile up rejection scheme, analog memory to enhance throughput, and on-chip SAR ADC, shared between two pixels with sparse multiplexing scheme. The chip layout is compatible for bump bonding assembly with 2×2, 2mm-pitch, square SDD. The first prototype occupies a total area of 7.15mm × 3.31mm. Its static power consumption is 53.38mW/pixel, resulting in power density of 1.33W/cm2. For spectroscopic performance, SCARLET is expected to reach an output count rate density of 25Mcps/cm2 simultaneously with an ENC below 20e-RMS. The first prototype of such chip has been fabricated, functionalities are confirmed and impact of digital-driven disturbances are under evaluation.
Design and Control of an Omni-Directional Robotic Walker Based on Human–Machine Interaction

A cornerstone of the rehabilitative regime for people diagnosed with dyskinesia is walking assist and gait training, however, prolonged care, provided by relatives or professionals, serves as a massive financial burden to patients. The proposed novel robotic walker seeks to address this concern. The walker incorporates human motion intention recognition to facilitate lower limb rehabilitation training and daily walking. The walker design places strong emphasis on patient safety and quality of life by providing omni-directional walking assist, four key pelvic motions that support hip rotations and comfortable body weight support (BWS). Additionally, five sensors were installed to identify the user’s motion intention from the interaction forces surrounding the pelvis and dead zone. Furthermore, Kalman filtering was used to guarantee the quality of the interactive signal while kinematic and dynamic models were derived to generate appropriate driving velocities to support patient’s body weight and improve mobility. To validate our design, the MATLAB simulations and exploratory clinical trials using healthy subjects were performed. Preliminary results demonstrate satisfactory kinematic performance and suggest the walker as a promising therapeutic avenue for individuals suffering from dyskinesia and other associated movement disorders.
Vector Control Strategy of Permanent Magnet Synchronous Linear Motor Based on Sliding Mode Speed Controller and Model Reference Adaptive

Aiming at the problems of poor stability and low system accuracy in the vector control of permanent magnet synchronous linear motor (PMSLM), a vector control strategy for PMSLM based on model reference adaptive system (MRAS) is proposed. Improve the accuracy of speed and mover position estimation by selecting the appropriate adaptive law, and introduce a sliding mode control (SMC) strategy in the speed loop to optimize the vector control system. The simulation results shows that this method can effectively reduce the overshoot and chattering, and improve the stability of the system.
Detection, Classification and Location of Sources of Partial Discharges Using the Radiometric Method: Trends, Challenges and Open Issues

In this article, it is provided a comprehensive survey on the most relevant research in the area of detection, classification and location of partial discharge (PD) sources using the radiometric or ultra high frequency (UHF) method, focusing mainly on the works related to the use of antennas. To the best of the authors knowledge, this is the first review paper that focuses on the application of antennas based on UHF method in the complete diagnosis of PD. Specifically, it is first presented the main contributions to the development and optimization of UHF sensors for application in the detection of PD sources. Second, articles that used the UHF method to identify different types of PD in high voltage equipment are described. Finally, the main contributions regarding the location of sources of defects using the radiometric method are presented. Summary of works in the area of UHF detection sensors, PD classification and PD location, with their respective contributions, are shown. Finally, research trends, challenging and open issues are discussed. The purpose of this article is to provide important information about the complete diagnosis of PD, which could be used to guide the development of more efficient techniques in this research area.
Long Stator Linear Doubly-Fed Motor for High-Speed Maglev Integrated Suspension, Propulsion and Contactless Power Supply

The power rails for onboard power supply are needed for TR high-speed maglev based on liner synchronous motor, which bring up the cost increase and decrease of reliability. Aiming to realize the contactless onboard power supply at low cost, a maglev based on Long Stator Linear Doubly-Fed Motor (LDFM) is proposed in this paper, which can integrate the contactless onboard power supply, suspension and propulsion force generation together. The structure, principle and the decoupled control strategy of the LDFM based maglev is presented. The 2D Finite Element Method (FEM) results verify the effectiveness of the proposed prototype.
The atmospheric corrosion of 304L and 316L stainless steels under conditions relevant to the interim storage of intermediate level nuclear waste

The atmospheric corrosion of 304L and 3 16L austenitic stainless steels was investigated in conditions relevant to the storage of intermediate level nuclear waste (I L W). Thin electrolyte films were created via automated droplet deposition, allowing multiple tests to be conducted in parallel. In-situ monitoring of droplet arrays on stainless steel samples was conducted with the use of a flat-bed document scanner, allowing large-scale, automated monitoring of corrosion processes. The initiation time for individual corrosion processes was established, showing that corrosion was slower to initiate under less aggressive conditions, and allowing 'true corrosion site lifetimes to be recorded, and compared with their depths. The presence of precipitated species within an electrolyte film was shown to affect the corrosion processes within that film. Both NaCl precipitates and glass shards acted as barriers to ion transport. This affected both the propagation of corrosion, and the electrochemical potential within the droplets; a higher precipitate content decreased the average corrosion depth and the extent of corrosion. The presence of nitrate and sulphate salts, both known corrosion inhibitors in full- immersion conditions, was shown to inhibit atmospheric corrosion when the inhibitor:chloride ratio was above a certain value. This was independent of the absolute amounts of salts, but dependent on the exposure humidity of the test.
Joint Sparse Coding-Based Super-Resolution PET Image Reconstruction

This paper presents a comparative study of the effects of using joint sparse coding (JSC) for regularized super-resolution (SR) PET reconstruction. With an assumption that a limited number of high-resolution (HR) PET images are available for a joint training dataset for JSC, we attempt to improve the accuracy of sparse coding (SC) based SR reconstruction in conventional non-HR PET imaging. Here we also assume that the anatomical (CT or MR) and PET images acquired from the same patient lie in coupled feature spaces. The images in one feature space can be transformed into corresponding images in the other feature space by a common mapping function. In this case, the images in the coupled feature spaces have a common sparse representation in terms of the specific dictionaries that are jointly trained, which is the main key to the JSC method. We implemented the penalized-likelihood SR reconstruction algorithm whose penalty term is modeled as JSC and compared with our previous method using the single dictionary-based SC penalty. The experimental results demonstrate that our proposed JSC method clearly outperforms the standard SC method by more accurately restoring the fine details that are often missed by the standard SC method.
Fusion of Thepade SBTC and GLCM Features for Recognizing Gender from Facial Images.

Due to noise and blurring effect while image capturing, poses, changes in the face due to jewelry, glasses, and age of the person gender classification is quite a difficult task. It is a very crucial topic for research in image processing. Many classification systems are designed by using various methods. In this paper, the classification system is created by machine learning. TSBTC algorithm is used for feature extraction. This paper compares the various feature extraction algorithms like TSBTC and GLCM etc. This experimentation is carried out using Matlab.
An Adaptive Machine Learning-based Threat Detection Framework for Industrial Communication Networks

The development in sophisticated sensory devices has largely revolutionized industrial control systems (ICS). With the popularity of the fourth industrial revolution, which is also referred to as Industry 4.0, more large-scale industrial communication systems are being interconnected by leveraging information communication technology (ICT) paradigms. These new paradigms have resulted in a sustainable improvement in the conventional production systems by facilitating timely and enhanced production rates. The ICS embeds service oriented architecture (SOA), which comprise of supervisory control and data acquisition (SCADA) systems as its backbone. However, such systems have often fallen prey to cyber-attacks leading to temporary failures or complete physical damage to the ICS. In this perspective, this work suggests the adoption of particle swarm optimization (PSO) method and artificial neural network (ANN) model for identifying cyber-attacks associated with ICS. This work considers the gas pipeline control system data to assess the efficacy of the proposed approach in conjunction with other models. It is observed that the proposed approach provides a prediction accuracy of 98.87 % and respective precision and recall values of 97.80 % and 95.79 %.
Model Predictive Thrust Force Control for Modular Permanent Magnet Synchronous Linear Motor Based on Multi-branch Inverter Topology

This paper presents the model predictive thrust force control (MPTFC) based on the multi-branch inverter for the modular permanent magnet synchronous linear motor (PMSLM). It focuses on the thrust force coordinated control of the modular PMSLM drive system for industry assembly line applications. The topology of the drive system and operating principle is investigated, and a discrete-time model of the modular PMSLM is established. Considering the multiple operating mode, the different multi-mode cost functions are designed by adopting optimal active voltage vector dwell time. The multiple weight coefficients are analyzed and chosen to optimize the operating demand of the drive system. The results indicate that the proposed MPTFC method reduces the thrust force ripple significantly, and the drive system has high efficiency and better steady performance compared to the conventional drive system.
Component Interfaces with Loosely Synchronous Communication

Interface automata have been introduced as a way to advance from value and domain descriptions of type systems to temporal interface descriptions. The original introduction of interface automata used a notion of buffered communication with infinite buffer size. This communication model is suitable to abstract the behaviour of many computing aspects with asynchronous communication between components. In this paper we present Loosely Synchronous Interface Automata (LSIA) to describe interfaces of components with loosely synchronised communication. Loosely synchronised communication facilitates a blocking semantics of communication for both sender and receiver. With loosely synchronisation it is possible to describe systems where a precise order of events is necessary. For example, cyber-physical systems often include control tasks where the exact order of events is necessary for a safe operation. With LSIAs it is possible to check compatibility of interface models including safety-relevant properties like lifeness. In this paper we describe the composition of LSIAs and show examples.