Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Structural and Magnetic Properties of Nanocrystalline Mechanically Alloyed Fe-Ni Powders Using Multi-Gene Genetic Programming Approach

In this paper, a theoretical model based on multi-gene genetic programming (MGGP) approach has been applied to predict the structural and magnetic properties in nanocrystalline Fe–Ni powders prepared by mechanical alloying (MA) using a planetary ball mill. The MGGP model was used to correlate the input parameters (milling speed, chemical composition, and milling time), to output parameters (crystallite size and coercivity) of nanocrystalline Fe–Ni powders. The model obtained was tested with additional data to demonstrate its performance and prediction ability. The MGGP model is a robust and efficient method to find an accurate mathematical relationship between input and output data. A sensitivity analysis study was applied to determine the most influential milling parameters on the crystallite size and coercivity.
Exploring enablers of health and safety knowledge transfer from construction companies to project host communities

Abstract The importance of knowledge transfer as a strategic asset for organisations has long been recognised by researchers and practitioners. Therefore, this study aims to identify factors that will enable the transfer of health and safety knowledge from construction companies to project host communities in Ghana. In total, 250 contractors comprising 155 building contractors and 95 road contractors took part in the survey. Stratified simple random sampling technique was adopted in selecting the companies in the survey, and principal component analysis was the analytical method employed. Six enablers of knowledge transfer from a construction company to the community were established. Namely, individuals' ability to use knowledge, collaboration, networking, communication, trust, and local content inclusion. It is expected that this study's findings would help contractors transfer valuable knowledge to communities in which they operate. It would also inform policymakers in dealing with external knowledge transfer from the construction industry. This study is the first attempt in a developing country like Ghana to provide the construction industry with the enablers of knowledge transfer from the construction industry to a different social system (project host communities).
Design of an SSVEP-based BCI Stimuli System for Attention-based Robot Navigation in Robotic Telepresence*

Brain-computer interface (BCI)-based robotic telepresence provides an opportunity for people with disabilities to control robots remotely without any actual physical movement. However, traditional BCI systems usually require the user to select the navigation direction from visual stimuli in a fixed background, which makes it difficult to control the robot in a dynamic environment during the locomotion. In this paper, a novel SSVEP-based BCI stimuli system is proposed for robotic telepresence. The novel system utilized the live video streamed from the robot onboard camera as the input. By altering and flickering the detected objects in the scene with different frequencies predefined based on their relative positions on the screen, the robot can be navigated based on the user’s attention in a dynamic manner. In order to better differentiate multiple objects (more than the number of frequencies predefined), the task-related component analysis (TRCA) model was trained with a priori offline experimental data to select the front objects with priority. Experiments were conducted to validate the proposed system. Using the system, four human subjects are able to control a humanoid robot to navigate through multiple objects to reach the desired goal. The success rate reaches 87.5% in average.
A Computer Science Unplugged Activity: CityMap

The purpose of this study is to examine the process of writing algorithms using step by step instructions of students through computer science unplugged activity. Accordingly, CityMap activity which is related to daily life and scenario based was developed. The aim of this activity is to write algorithms of going from one place to another using step by step instructions. The rules are also to reach the destination with the shortest way and the least number of steps using correct instructions. The study group consists of 15 sixth grade students. The case study was used as a research method. For the activity, a map and a worksheet designed by the researchers were used as data collection tools and an answer key was used for the analysis. Both individual and group evaluation were made and for this process gamification components were used. The findings revealed that students could wrote algorithms step by step instructions for the tasks determined in the activity. In addition, it was concluded that using of the gamification components made the activity more enjoyable and the students be motivated towards learning of computer science.
Optimisation of the Nonlinear Suspension Characteristics of a Light Commercial Vehicle

The optimum functional characteristics of suspension components, namely, linear/nonlinear spring and nonlinear damper characteristic functions are determined using simple lumped parameter models. A quarter car model is used to represent the front independent suspension, and a half car model is used to represent the rear solid axle suspension of a light commercial vehicle. The functional shapes of the suspension characteristics used in the optimisation process are based on typical shapes supplied by a car manufacturer. The complexity of a nonlinear function optimisation problem is reduced by scaling it up or down from the aforementioned shape in the optimisation process. The nonlinear optimised suspension characteristics are first obtained using lower complexity lumped parameter models. Then, the performance of the optimised suspension units are verified using the higher fidelity and more realistic Carmaker model. An interactive software module is developed to ease the nonlinear suspension optimisation process using the Matlab Graphical User Interface tool.
An integrated CMOS PLL for low-jitter applications

This brief presents a fully integrated integer-N frequency synthesizer with a frequency-tuning range from 2.4 to 2.9 GHz and root-mean-square (rms) jitter below 2.5 ps over 350 MHz. The employed architecture using an inductance-capacitance (L-C) oscillator with two control inputs combines a wide tuning range with a low noise sensitivity. Potential applications include clock generation in microprocessors and clock recovery in fiberoptic receivers.
Map Compressibility Assessment for LiDAR Registration

We aim to assess the performance of LiDAR-to-map registration on compressive maps. Modern autonomous vehicles utilize pre-built HD (High-Definition) maps to perform sensor-to-map registration, which recovers pose estimation failures and reduces drift in a large-scale environment. However, sensor-to-map registration is usually realized by registering the sensor to a dense 3D model, which occupies massive storage space in the HD map and requires much data processing overhead. Although smaller 3D models are preferable, the optimal compressive map format for preservation of the best registration performance remains unclear.In this paper, we propose a novel and challenging benchmark to evaluate existing LiDAR-to-map registration methods from three perspectives: map compressibility, robustness, and precision. We compared various map formats, including raw points, hierarchical GMMs, and feature points, and show their performance trade-offs between compressibility and robustness on real-world LiDAR datasets: KITTI Odometry Dataset and Argoverse Tracking Dataset. Our benchmark reveals that state-of-the-art deep feature point based methods outperform traditional methods significantly when the map size budget is high. However, when map size budget is low, deep methods are outperformed by the methods using simpler models in Argoverse Tracking Dataset due to poor spatial coverage. In addition, we observe that the recently published TEASER++ significantly outperforms RANSAC for the feature point methods. Our analysis provides a valuable reference for the community to design budgeted real-world systems and find potential research opportunities. We will release the benchmark for public use.
Investigation of Noise Sources on a Series Hybrid Transmission

Abstract Advanced hydrostatic transmissions and hydraulic hybrids show potential in new market segments such as commercial vehicles and passenger cars. Such new applications regard low noise generation as a high priority, thus, demanding new quiet hydrostatic transmission designs. The aim of this paper is to investigate noise sources on a series hybrid transmission through simulation and measurements. A model has been developed to capture the interaction of a pump and motor working in a hydrostatic transmission and to predict overall noise sources. The model describes dynamics of the system by coupling lumped parameter pump and motor models with a one-dimensional unsteady compressible transmission line model including a dynamic model of an accumulator. A semi-anechoic chamber has been designed and constructed for sound intensity measurements that can be used to derive sound power. Sound power measurements were conducted on a series hybrid transmission test bench inside the semi-anechoic chamber in order to study the relationship between sound power and two types of noise sources, fluid and structure borne. The focus of these measurements was to investigate the impact of an accumulator in the high pressure line as well as the influence of varying high pressure line length. Results show a strong influence of changing line length and the addition of an accumulator on pressure ripple, but with little impact on sound power. A high correlation was found between sound power levels and control moment amplitudes on the swash plate. This study demonstrates the usefulness of predicting transmission noise sources, and how this information is beneficial in the design process of a transmission.
Ability Dispersion and Team Performance: A Field Experiment

This paper studies the impact of diversity in cognitive ability among members of a team on their performance. We conduct a large field experiment in which teams start up and manage real companies under identical circumstances. Exogenous variation in – otherwise random – team composition is imposed by assigning individuals to teams based on their measured cognitive abilities. The setting is one of business management practices in the longer run where tasks are diverse and involve complex decision-making. We propose a model in which greater ability dispersion generates greater knowledge for a team, but also increases the costs of monitoring necessitated by moral hazard. Consistent with the predictions of our model, we find that team performance as measured in terms of sales, profits and profits per share first increases, and then decreases, with ability dispersion. Teams with a moderate degree of ability dispersion also experience fewer dismissals due to fewer shirking members in those teams.
Minimum Manufacturing Costs, National Prices, and Estimated Global Availability of New Repurposed Therapies for Coronavirus Disease 2019

Abstract Background Currently, only dexamethasone, tocilizumab, and sarilumab have conclusively been shown to reduce mortality of coronavirus disease 2019 (COVID-19). Safe and effective treatments will need to be both affordable and widely available globally to be used alongside vaccination programs. This analysis will estimate and compare potential generic minimum costs of a selection of approved COVID-19 drug candidates with available international list prices. Methods We searched for repurposed drugs that have been approved by at least one of the World Health Organization, US Food and Drug Administration, or the United Kingdom National Institute of Health and Care Excellence organizations or at least given emergency use authorization or recommended for off-label prescription. Drug prices were searched for dexamethasone, budesonide, baricitinib, tocilizumab, casirivimab, and imdevimab, and sarilumab, using active pharmaceutical ingredients (APIs) data extracted from global shipping records. This was compared with national pricing data from a range of low-, medium-, and high-income countries. Annual API export volumes from India were used to estimate the current availability of each drug. Results Repurposed therapies can be generically manufactured for some treatments at very low per-course costs, ranging from US $2.58 for intravenous (IV) dexamethasone (or US $0.19 orally) and US $4.34 for inhaled budesonide. No export price data were available for baricitinib, tocilizumab, casirivimab, and imdevimab, or sarilumab, but courses of these treatments have higher prices, ranging from US $6.67 for baricitinib to US $875.5 for sarilumab. When comparing international list prices, we found wide variations between countries. Conclusions Successful management of COVID-19 will require equitable access to treatment for all populations, not just those able to pay high prices. Dexamethasone and budesonide are widely available and affordable, whereas monoclonal antibodies and IV treatment courses are more expensive.
Multi-objective fuzzy-based adaptive memetic algorithm with hyper-heuristics to solve university course timetabling problem

The university course timetabling is an NP-hard (non-deterministic polynomial-time hard) optimization problem to create a course timetable without conflict. It must assign a set of subject classes to a fixed number of timeslots with physical resources, including rooms and teachers. Avoiding hard constraints creates an executable timetable, whereas the removal of different soft constraints creates a satisfactory timetable. The most common way to resolve this problem is through the use of a hybrid genetic algorithm. The multi-objective fuzzy-based adaptive memetic algorithm, a population-based hybrid genetic approach, is proposed by combining genetic algorithm with local search with tabu search and various artificial intelligence techniques. It starts with generating a random population by using the hyper-heuristics and initial repairing method. By using the hill-climbing algorithm, it iteratively generates new offspring from the population by applying fuzzy-based adaptive crossover and mutation operations. If the solution still contains some conflicts, then the tabu search improves it by applying the most appropriate candidate repeatedly. While getting the workable solution, the algorithm tries to maximize multiple objective functions to get manageable solutions with different perspectives. It efficiently allocates all the required resources to subject classes and generates optimal solutions for the datasets provided by the University of Management & Technology, Lahore. It shows 96.29% accuracy in resolving conflicts compare with that of the simple and hybrid genetic algorithms. A web-based dynamic timetable manager visually represents a timetable and also provides options to adjust conflicts manually.
Simplified Digitizing Interface-Architectures for Three-Wire Connected Resistive Sensors: Design and Comprehensive Evaluation

This article describes the design, analysis, and performance verification of simple digitizing interfaces for different types of three-wire resistive sensors. The proposed interface uses an efficient resistance-to-time conversion technique that charges an internal capacitor, between two reference levels, through selected resistive-sensor paths. A simple analog circuit controlled using a digital timing unit realizes the aforementioned technique. This approach is adaptable for various resistive sensor configurations and does not depend on the effect of connecting wire resistances and various other non-ideal parameters (e.g., threshold voltage and pin resistance of microcontroller, offset voltage of comparator, etc.). In addition, the proposed schemes utilize its digital unit (e.g., microcontroller) only for control and timing operations, thus saving on power. The detailed working principle of the proposed interfaces and their error analysis are discussed in the article. Later, performance verification is carried out using simulation as well as emulation studies. These studies clearly show that the presented digitizing interfaces provide linear digital transfer characteristics with maximum nonlinearity of 0.17% and wire resistance compensation. Further, tests are conducted with various remotely located commercial sensors. The outcomes of these studies are reported and compared with the state-of-the-art works.
Proposed Method for Shoot-Through in Three Phase ZSI and Comparison of Different Control Techniques

This paper presented the new methodology for different control techniques applied to three phase Z-source inverter for minimisation of switching losses. The procedure for proposed control techniques and its effects on the performance of operation of three phase Z-source inverter are analyzed. The graphs for voltage gain and voltage stress are drawn for different control methods. The flow-chart for the symmetrical and unsymmetrical control techniques for creating pulse signals for switches of three phase inverter are shown . All the methods are studied and compared with each other. The Total harmonic distortion (THD) of output voltage of both the control methods has been analyzed using FFT analysis. The experiments done and the results shown for capacitor voltage, load current and load line voltage for simple boost and constant boost control techniques are presented using MATLAB/ Simulink. DOI: http://dx.doi. org/10.11591/ijpeds.v5i1. 6180 Full Text: PDF
Sensing Cd(II) Using a Disposable Optical Sensor Based on a Schiff Base Immobilisation on a Polymer-Inclusion Membrane. Applications in Water and Art Paint Samples

A disposable colour-changeable optical sensor based on an interesting polymer inclusion-membrane (PIM) was designed to determine Cd(II) ions in aqueous medium. The Schiff base 2-acetylpyridine benzoylhydrazone (2-APBH) immobilised on the polymer membrane was used as a sensing molecule. The amounts of the PIM components were optimised by a 32 fractional factorial design with two central points and two blocks. The best optical sensor composition consisted of 2.5 g of poly(vinylchloride) (PVC) as a base polymer, 3 mL of tributyl phosphate (TBP) as a plasticiser, and 0.02 g of 2-APBH as a reagent. The sensor showed a good linear response in the range from 0.02 mg L−1 (limit of detection) to 1 mg L−1 of Cd(II) under the following experimental conditions: pH 9.5 (adjusted using ammonium chloride buffer solution at 0.337 mol L−1), 60 min of exposure time plus 2 min of sonication (pulses at 2 s intervals), and 10 min of short-term stability. The relative standard deviation of the method was determined to be 4.04% for 0.4 mg L−1 of Cd(II). The optical sensor was successfully applied to the determination of Cd(II) in natural-water and art-paint samples.
An Enhanced Trust Management Framework for MANET using Fuzzy Prediction Mechanism

A Mobile Ad hoc Network (MANET) is a self-sufficient arrangement of portable switch and related hosts associated by remote connections. It is a gathering of autonomous versatile hubs that can speak with one another through radio waves. These systems are completely disseminated, and work at wherever without help of any framework. MANETS are substantially more helpless to assault than the wired system. Because of the rapidly changing system topology, versatile hubs frequently comes in and goes out of the system, along these lines permitting any vindictive hub to join the system without being located . Subsequently, Ad Hoc system needs extremely particular security systems. But there is no single approach fitting all the networks, as the nodes can be any devices. Therefore, in this paper, an Enhanced Trust management framework using Adaptive Fuzzy Logic mechanism is proposed to provide detection of malicious node. The proposed model will be incorporated over Ad hoc On-demand Distance Vector (AODV) routing protocol to pick the most limited course that meets the security prerequisites of information bundle transmission. Investigations have been led to assess the productivity and viability of the proposed component in malignant node identification attack resistance.
An Algorithm for Simultaneous Optimization of Parameters of Condition-based Preventive Maintenance:

A new condition-based preventive maintenance model for a system, subject to deterioration-failures and to random failures with increasing intensity, is presented. Deterioration is modeled as discrete stages. After an inspection, based on the degree of deterioration, a minimal maintenance or a major maintenance is performed, or no action is taken. Deterioration failures are restored by complete replacements; Random failures are restored by minimal repair. Major maintenance restores the system to `τ' deterioration stages younger (τ > 1), while minimal maintenance restores the system one stage. The proposed model considers an accumulated deterioration based increasing intensity for the random failures. A continuously increasing failure rate (for example Weibull) is converted into a stepwise increasing failure rate using stair-step approximation. An exact recursive algorithm computes the steady-state probabilities of the system. Based on maximization of the system availability or minimization of total cost, a.
Evaluation of power system cascading outages

The indices, models and algorithms of evaluating cascading outages in power systems are proposed in this paper. At first, four deterministic and two probabilistic indices are defined for evaluating the cascading outages. These indices can reflect the practical distribution of the loss load and the severity of the failure. Uniting the network configuration with bus schemes of power substations, the cascading model of power systems is set up subsequently. In order to take into account the effect of protection systems, a new reliability model of protection systems is presented based on the fact that faults of protection systems can be reflected by the actions of breakers. An efficient algorithm is developed based on the above models, which incorporates all causes of cascading faults and achieves quantitative evaluation of power systems cascading faults. The algorithm includes five parts: fault analysis of bus station, trace of the network topology, judgment of the network connectivity, evaluation of system states and statistic of indices. In order to improve the computation efficiency, several techniques are adopted in the assessment. Cases study indicates that the presented approach can find the bottleneck of the network and discover the hidden failure of power systems.