Miracle-dz/UniFAR-FTUs huggingface dataset:
Mastery of Technological Pedagogical And Content Knowledge (TPACK) Prospective Teacher In ICT Expertise Brawijaya University

The Information Technology Education (ITE) study program, Faculty of Computer Science, Universitas Brawijaya requires its students to take part in Pengenalan Lapangan Persekolahan (PLP) 2 according to Permenristekdikti No. 55 of 2017 in order to be able to produce prospective teachers who have the competence of educators. This study describes the gap in mastery of competencies with the TPACK framework based on the results of PLP 2 activities which are compared with standard values using a discrepancy evaluation model. The results of the gap are mapped using the method Importance Performance Analysis (IPA) to determine the priority scale for improvement of variables according to positions in certain quadrants. Through the IPA method, the variables that are prioritized to improve their mastery are TPK and PCK because they have very small gaps. Recommendations are given for the TPK variable to be given a pretest and posttest on the material for preparing teaching tools and training in the preparation of lesson plans. For the PCK variable, should be given pretest and posttest to the study material for theoretical and practical learning scenarios, the activities are needed lesson study which is carried out at least twice.
Modeling of dielectric relaxation spectra of polymers in the condensed phase

Discusses models and their possible implication in the interpretation of the relaxation spectra of polymers, particularly involving the concept of order/disorder systems. Furthermore, some examples of the application of the Dissado-Hill model have been provided in this work to explain quasi-dc (QDC) conduction processes, which have been observed in crosslinked polyethylene (XLPE) and low density polyethylene (LDPE), showing an ageing behavior with continuing use with an ac field in a humid environment. It is also shown in this paper how a measurement of dielectric relaxation properties on a wide frequency range may be used as a tool to investigate the ageing of polymeric power distribution cables with an ac field in a humid environment. Equivalent electrical analog circuits of dielectric relaxation spectra are also shown.
Analyzing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks

Vietnam has experienced a tourism expansion over the last decade, proving itself as one of the top tourist destinations in Southeast Asia. The country received more than 18 million international tourists in 2019, compared to only 1.5 million twenty-five years ago. Tourist spending has translated into rising employment and incomes for Vietnam’s tourism sector, making it the key driver to the socio-economic development of the country. Following the COVID-19 pandemic, only 3.8 million international tourists visited Vietnam in 2020, plummeting by 78.7% year-on-year. The latest outbreak in early summer 2021 made the sector continue to hit bottom. Although Vietnam’s tourism has suffered extreme losses, once the contagion is under control worldwide, the number of international tourists to Vietnam is expected to rise again to reach pre-pandemic levels in the next few years. First, the paper aims to provide a summary of Vietnam’s tourism characteristics with a special focus on international tourists. Next, the predictive capability of artificial neural network (ANN) methodology is examined with the datasets of international tourists to Vietnam from 2008 to 2020. Some ANN architectures are experimented with to predict the monthly number of international tourists to the country, including some lockdown periods due to the COVID-19 pandemic. The results show that, with the correct selection of ANN architectures and data from the previous 12 months, the best ANN models can be forecast for next month with a MAPE between 7.9% and 9.2%. As the method proves its forecasting accuracy, it would serve as a valuable tool for Vietnam’s policymakers and firm managers to make better investment and strategic decisions.
A Single-Layer Low-Profile Broadband Metasurface-Inspired Antenna With Monopole-Like Radiation Characteristics

This communication presents a novel single-layer, low-profile broadband metasurface (MTS)-inspired antenna with monopole-like radiation characteristics. To excite symmetric surface waves propagating along an MTS consisting of an array of 4 × 4 metal square patches, a horizontal center-fed monopole structure is used at the center of the MTS. The proposed antenna is further embedded within a square ring to improve the gain and H-plane patterns roundness at the upper-frequency band. The presented antenna achieved a -10 dB bandwidth of 32.62% (5.08-7.06 GHz) and a low-profile of 0. 06λ0(λ0 is the free space wavelength at the center of the operating band) distinctive features due, respectively, to the effective excitation of different TM surface wave resonant modes that are close to each other and the in-phase reflection property of the MTS. The planar structure, single-layer, and low-profile merits make the proposed antenna an ideal candidate for various wireless communications systems, such as wireless local area network (WLAN) at 5.2/5.8 GHz, WiMAX at 5.5 GHz, and car to car (C2C) at 5.85-5.925 GHz.
Computer-aided design of beam forming networks for modern satellite antennas

Multicontoured and reconfigurable beam spacecraft antennas rely on sophisticated beam forming networks (BFNs). Accurate and efficient CAD tools are required to meet the stringent requirements on the power division, while avoiding any tuning or trimming of the BFN. Advanced field theoretical techniques for the analysis and optimization of microwave BFNs realized in both waveguide and square coaxial cable technologies are presented. Such advances consist in new segmentation techniques of the microwave components associated with efficient mode-matching formulations for the modeling of isolated as well as coupled discontinuities. The achieved numerical efficiency allows sophisticated synthesis procedures, based on repeated full-wave analysis in wide frequency bands, to be performed on small machines such as a 386 PC. The design tools developed have been widely validated through a comprehensive test campaign. >
Rainfall Prediction Using Machine Learning Algorithms for the Various Ecological Zones of Ghana

Accurate rainfall prediction has become very complicated in recent times due to climate change and variability. The efficiency of classification algorithms in rainfall prediction has flourished. The study contributes to using various classification algorithms for rainfall prediction in the different ecological zones of Ghana. The classification algorithms include Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), Extreme Gradient Boosting (XGB) and K-Nearest Neighbour (KNN). The dataset, consisting of various climatic attributes, was sourced from the Ghana Meteorological Agency spanning 1980 – 2019. The performance of the classification algorithms was examined based on precision, recall, f1-score, accuracy and execution time with various training and testing data ratios. On all three training and testing ratios: 70:30, 80:20 and 90:10, RF, XGB and MLP performed well, whereas KNN performed least across all zones. In terms of the execution time of the models, Decision Tree is consistently portrayed as the fastest, whereas MLP used the most run time.
WRF Rainfall Modeling Post-Processing by Adaptive Parameterization of Raindrop Size Distribution: A Case Study on the United Kingdom

Raindrop size distribution (RSD) is a key parameter in the Weather Research and Forecasting (WRF) model for rainfall estimation, with gamma distribution models commonly used to describe RSD under WRF microphysical parameterizations. The RSD model sets the shape parameter (μ) as a constant of gamma distribution in WRF double-moment bulk microphysics schemes. Here, we propose to improve the gamma RSD model with an adaptive value of μ based on the rainfall intensity and season, designed using a genetic algorithm (GA) and the linear least-squares method. The model can be described as a piecewise post-processing function that is constant when rainfall intensity is <1.5 mm/h and linear otherwise. Our numerical simulation uses the WRF driven by an ERA-interim dataset with three distinct double-moment bulk microphysical parameterizations, namely, the Morrison, WDM6, and Thompson aerosol-aware schemes for the period of 2013–2017 over the United Kingdom at a 5 km resolution. Observations were made using a disdrometer and 241 rain gauges, which were used for calibration and validation. The results show that the adaptive-μ model of the gamma distribution was more accurate than the gamma RSD model with a constant shape parameter, with the root-mean-square error decreasing by averages of 23.62%, 11.33%, and 22.21% for the Morrison, WDM6, and Thompson aerosol-aware schemes, respectively. This model improves the accuracy of WRF rainfall simulation by applying adaptive RSD parameterization and can be integrated into the simulation of WRF double-moment microphysics schemes. The physical mechanism of the RSD model remains to be determined to improve its performance in WRF bulk microphysics schemes.
Compact voltage-mode multi-valued literal gate using nanoscale ballistic MOSFETs

A CMOS voltage-mode multi-valued literal gate is presented. The ballistic electron transport characteristic of nanoscale MOSFETs is smartly used to compactly achieve universal radix-4 literal operations. The proposed literal gates have small numbers of transistors and low power dissipations, which makes them promising for future nanoscale multi-valued circuits. The gates are simulated by HSPICE.
One class support vector machine for anomaly detection in the communication network performance data

Anomaly detection refers to the automatic identification of the abnormal behaviors from a large amount of normal data. Anomaly detection is more and more required in the communication network due to the increasing number of the unauthorized activities occurring in the network. This paper presents a method based on one class support vector machine (OCSVM) to detect the network anomalies. The communication network performance data are used for the investigation and the raw data are firstly preprocessed in order to produce the vector sets required by the OCSVM algorithm. The training data are used to train the OCSVM anomaly detector, and the trained detector is applied on the test data to detect the anomalies. In addition, the results are compared with the results obtained from the rule-based system which is currently used in the communication network. The algorithm shows the promising performance on the network anomaly detection and provides a great reduction on the volume of the alarms than the rule-based system.
Process tolerance allocation in angular tolerance charting

The paper deals with the process tolerance allocation problem for manufacturing a product with angular features in two-dimensional angular tolerance charting. First, a discrete interval cost–tolerance model is investigated to represent the relationship between manufacturing cost and tolerance. Then a multichoice knapsack model is formulated to allocate systematically the best tolerance to each individual machining dimension in both radial and axial directions with the objective of minimizing the total manufacturing cost. Furthermore, a genetic algorithm is developed to obtain the optimal solution to the multichoice knapsack model. Finally, a numerical example is presented to illustrate the model and the approach developed.
Tunable photodetectors based on amorphous Si/SiC heterostructures

We describe a novel family of two-color photodetectors based on p-i-n-i-p heterostructures in hydrogenated amorphous Si/SiC. The devices operate as bias-controlled light detectors with enhanced absorption in either the blue or the red regions. Compared to other two-color sensors based on amorphous Si/SiC n-i-p-i-n structures, they exhibit sharper wavelength selection and higher rejection ratios with excellent quantum efficiencies: full width at half maximum (FWHM) less than 130 mm, suppression up to 27 dB, and peak responsivity of about 150 mA/W are reported for both the blue and the red window. Simulation of the photoresponse of the device under steady-state and time-dependent voltage bias and under continuous illumination is also presented. >
Development of a Time-Domain Simulation Tool for Offshore Wind Farms

A time-domain simulation tool to predict the dynamic power output of wind turbines in an offshore wind farm was developed in this study. A wind turbine model consisting of first or second order transfer functions of various wind turbine elements was combined with the Ainslie’s eddy viscosity wake model to construct the simulation tool. The wind turbine model also includes an aerodynamic model that is a look up table of power and thrust coefficients with respect to the tip speed ratio and pitch angle of the wind turbine obtained by a commercial multi-body dynamics simulation tool. The wake model includes algorithms of superposition of multiple wakes and propagation based on Taylor’s frozen turbulence assumption. Torque and pitch control algorithms were implemented in the simulation tool to perform max-Cp and power regulation control of the wind turbines. The simulation tool calculates wind speeds in the two-dimensional domain of the wind farm at the hub height of the wind turbines and yields power outputs from individual wind turbines. The NREL 5MW reference wind turbine was targeted as a wind turbine to obtain parameters for the simulation. To validate the simulation tool, a Danish offshore wind farm with 80 wind turbines was modelled and used to predict the power from the wind farm. A comparison of the prediction with the measured values available in literature showed that the results from the simulation program were fairly close to the measured results in literature except when the wind turbines are congruent with the wind direction.
Current and SAR induced in a human head model by the electromagnetic fields irradiated from a cellular phone

The near field finite-difference time-domain method was used to calculate the current and specific absorption rate (SAR) distributions in an inhomogeneous model of a human head exposed to the electromagnetic waves irradiated from a cellular phone. The human head was simulated by a model of 57,263 block cells with inhomogeneous dielectric constant and conductivity. The cellular phone was modeled by an equivalent dipole antenna with an equivalent resistor of 120 ohms located at the center gap between the two arms of this dipole antenna. The transmitted power of the cellular phone was assumed to be 0.6 watts at a frequency of 835 MHz. For the head near the dipole antenna in the range of 1.0/spl sim/2.5 cm, the maximum currents and SAR's induced in the head were found in the ranges of 356/spl sim/551 mA and 1.23/spl sim/2.63 W/kg, respectively. It was also found that the maximum SAR induced in the head was below the IEEE's upper safety limit of 1.6 W/kg for the head to keep a distance from the dipole antenna by longer than 2.0 cm. >
Non-Linear Predictive Control of Multi-Input Multi-Output Vehicle Suspension System

A new predictive control approach is employed to control a non-linear 4 degrees of freedom vehicle suspension model including pitch and bounce motions. The front and rear suspension actuator forces are considered as control inputs. These are determined by minimizing a performance index defined as a weighted combination of conflicting objectives, namely ride comfort and road holding. In this way, the suspension deflection and the control forces should be restricted to admissible practical ranges. In this paper, an optimization process is used to develop a multi-input multi-output (MIMO) non-linear control law in a closed-form which is mathematically tractable and suitable for implementation. To investigate special features of the derived control law, the closed-loop system dynamics are first evaluated analytically and then the corresponding simulation results are presented. The results show that a compromise between mentioned objectives and control energy, even in the presence of uncertainties, can be easily made by regulating the control weighting factors.
Analysis of TCR Repertoire by High-Throughput Sequencing Indicates the Feature of T Cell Immune Response after SARS-CoV-2 Infection

Coronavirus disease 2019 (COVID-19) is a global infectious disease caused by the SARS-CoV-2 coronavirus. T cells play an essential role in the body’s fighting against the virus invasion, and the T cell receptor (TCR) is crucial in T cell-mediated virus recognition and clearance. However, little has been known about the features of T cell response in convalescent COVID-19 patients. In this study, using 5′RACE technology and PacBio sequencing, we analyzed the TCR repertoire of COVID-19 patients after recovery for 2 weeks and 6 months compared with the healthy donors. The TCR clustering and CDR3 annotation were exploited to discover groups of patient-specific TCR clonotypes with potential SARS-CoV-2 antigen specificities. We first identified CD4+ and CD8+ T cell clones with certain clonal expansion after infection, and then observed the preferential recombination usage of V(D) J gene segments in CD4+ and CD8+ T cells of COVID-19 patients with different convalescent stages. More important, the TRBV6-5-TRBD2-TRBJ2-7 combination with high frequency was shared between CD4+ T and CD8+ T cells of different COVID-19 patients. Finally, we found the dominant characteristic motifs of the CDR3 sequence between recovered COVID-19 and healthy control. Our study provides novel insights on TCR in COVID-19 with different convalescent phases, contributing to our understanding of the immune response induced by SARS-CoV-2.
A transformerless modular step-up dc–dc converter for high power applications

This study presents a new step-up dc-dc converter topology suitable for medium voltage, megawatt scale applications. The proposed converter interconnects unipolar or bipolar dc networks using a single inductor and a modular active switching network. The active switching network contains multiple series-connected identical converter modules. Each module consists of four switches and one capacitor. The modular nature of the switching network allows scalable implementation of the converter, and utilisation of low-voltage switches and capacitors. The proposed converter avoids the use of medium-frequency isolation transformers. Soft switching is utilised to reduce the converter's switching losses. An analytical model of the converter is developed to facilitate converter design. Theoretical predictions are supported by a 7.6 kW scaled laboratory prototype achieving an efficiency of as high as 93.2%.
State of research and development of small spacecraft with optical communication

The current state of scientific and technical research and development of small space vehicles using optical communication systems is considered. The problems standing in the way of creating intersatellite optical communication are discussed as well as the mutual position of satellites determination and it tracking. Scientific tasks for the implementation of the development of an optimal reliable control system for satellite communication are defined.
Vertebral morphology in extant porpoises: Radiation and functional implications

Vertebral morphology has profound biomechanical implications and plays an important role in adaptation to different habitats and foraging strategies for cetaceans. Extant porpoise species (Phocoenidae) display analogous evolutionary patterns in both hemispheres associated with convergent evolution to coastal versus oceanic environments. We employed 3D geometric morphometrics to study vertebral morphology in five porpoise species with contrasting habitats: the coastal Indo‐Pacific finless porpoise (Neophocaena phocaenoides); the mostly coastal harbor porpoise (Phocoena phocoena) and Burmeister's porpoise (Phocoena spinipinnis); and the oceanic spectacled porpoise (Phocoena dioptrica) and Dall's porpoise (Phocoenoides dalli). We evaluated the radiation of vertebral morphology, both in size and shape, using multivariate statistics. We supplemented data with samples of an early‐radiating delphinoid species, the narwhal (Monodon monoceros); and an early‐radiating delphinid species, the white‐beaked dolphin (Lagenorhynchus albirostris). Principal component analyses were used to map shape variation onto phylogenies, and phylogenetic constraints were investigated through permutation tests. We established links between vertebral morphology and movement patterns through biomechanical inferences from morphological presentations. We evidenced divergence in size between species with contrasting habitats, with coastal species tending to decrease in size from their estimated ancestral state, and oceanic species tending to increase in size. Regarding vertebral shape, coastal species had longer centra and shorter neural processes, but longer transverse processes, while oceanic species tended to have disk‐shaped vertebrae with longer neural processes. Within Phocoenidae, the absence of phylogenetic constraints in vertebral morphology suggests a high level of evolutionary lability. Overall, our results are in accordance with the hypothesis of speciation within the family from a coastal ancestor, through adaptation to particular habitats. Variation in vertebral morphology in this group of small odontocetes highlights the importance of environmental complexity and particular selective pressures for the speciation process through the development of adaptations that minimize energetic costs during locomotion and prey capture.
Does entrepreneurial orientation encourage Pakistani SMEs to participate in China-Pakistan economic corridor?

ABSTRACT Small and Medium Enterprises (SMEs) operating in China and Pakistan have shown great interest to participate in China-Pakistan Economic Corridor (CPEC). However, there is a dearth of reliable evidence on how SMEs can easily participate and get maximum benefits of the corridor. This research fills the gap by examining the influence of entrepreneurial orientation on the participation of CPEC through a sample of 211 Pakistani SMEs. The emphasis is placed on entrepreneurial orientation, rather than statutory regulations and governmental invention, to meet the desired objectives of CPEC. The results indicate that innovativeness, pro-activeness and risk-taking significantly facilitate SMEs towards CPEC while autonomy and competitive aggressiveness do not influence the perception of top managers/owners about CPEC. Our research recommends SMEs create entrepreneurial culture (specifically innovative, proactive and risk-taking) to gain benefits from export/imports arising CPEC. The findings also recommend policymakers initiate entrepreneurship programs and minimize regulations on internationalization among the SMEs.