Miracle-dz/UniFAR-FTUs huggingface dataset:
AgriTech Innovators: A Study of Initial Adoption and Continued Use of a Mobile Digital Platform by Family-Operated Farming Enterprises

While information technology is playing a significant transformative role in virtually every industry, within the agriculture sector, family-operated farming enterprises have been slow to adopt IT solutions to manage their operations. This study adopts a sequential mixed-methods research design to examine the pre- and post-adoption phases of farmers’ use of a mobile digital platform for farm management. Our findings show that farmers’ initial acceptance of a mobile digital platform for farm management is shaped by social influence, which mediates the impact of performance and effort expectancy. Post-adoption continued use of the digital platform is influenced directly by performance and effort expectancy and indirectly by trust beliefs and social influence. Perceived work impediment indirectly influences post-adoption acceptance via effort expectancy. Our study untangles the direct and indirect influences of positive and negative perceptions on farmers’ acceptance of a new innovative AgriTech digital platform in these different phases.
Practical Sagnac interferometer based fibre optic current sensor

A theoretical and experimental investigation of a practical new Sagnac interferometric optical fibre current sensor using a 3*3 fibre coupler is presented. A simple analytical expression for the output response of the sensor has been derived in the presence of bend-induced linear birefringence and twist-induced circular birefringence in the fibre sensing coil. This represents the first analytic formulation for this type of current sensor. The effects of the bend-induced linear birefringence and twist-induced circular birefringence on the phase bias and scale factor have been analysed in detail. Numerical simulation was also carried out to study the effect of various disturbances and imperfections such as intrinsic linear birefringence and localised birefringence in the sensing fibre. It is shown that our proposed structure minimises the effects of variations, as might be caused by temperature changes, for example, in the bend-induced linear birefringence and twist-induced circular birefringence, on the sensor stability. Preliminary experimental results show good temperature stability without the use of any passive or active compensation arrangement.
An Implantable Umbo Microphone For Fully-Implantable Assistive Hearing Devices

This paper presents an implantable microphone for sensing the displacement of the umbo, the end of the malleus where it attaches to the center tip of the cone-shaped tympanic membrane. The sensor comprises a piezoelectric polyvinylidene fluoride (PVDF) film with copper-nickel electrodes suspended across a brass cylinder. The cylinder is oriented so that the umbo pushes on the film center, causing a static and acoustically-driven dynamic film displacement. An amplifier filters the resulting piezoelectric charge to produce an output signal. The sensor enables the full implantation of assistive hearing devices, which can restore hearing without inhibiting the user’s lifestyle, while enabling better sound localization in noisy environments.
Dynamic-based RCM Torque Controller for Robotic-Assisted Minimally Invasive Surgery

In this paper we propose a novel flexible and optimization-free controller for standard torque-controlled manipulator for Robotic-Assisted Minimally Invasive Surgery. A novel method has been developed to model the constraint introduced by the laparoscopic tool, i.e. the remote center of motion, exploiting closed chain manipulators theory, and the final controller was synthesized considering the effects the constraint produces at a dynamic level. A set of simulations has been performed in a trajectory tracking task to validate the performances of the proposed controller. Performances have been also tested in a real experimental scenario with a KUKA LWR 4+ with 7 degrees of freedom endowed with a laparoscopic-like tool. Results show the effectiveness of the proposed controller and its capability of modifying the trajectory in order to preserve the RCM constraint.
Political Attacks in 280 Characters or Less: A New Tool for the Automated Classification of Campaign Negativity on Social Media

Negativity in election campaign matters. To what extent can the content of social media posts provide a reliable indicator of candidates' campaign negativity? We introduce and critically assess an automated classification procedure that we trained to annotate more than 16,000 tweets of candidates competing in the 2018 Senate Midterms. The algorithm is able to identify the presence of political attacks (both in general, and specifically for character and policy attacks) and incivility. Due to the novel nature of the instrument, the article discusses the external and convergent validity of these measures. Results suggest that automated classifications are able to provide reliable measurements of campaign negativity. Triangulations with independent data show that our automatic classification is strongly associated with the experts’ perceptions of the candidates’ campaign. Furthermore, variations in our measures of negativity can be explained by theoretically relevant factors at the candidate and context levels (e.g., incumbency status and candidate gender); theoretically meaningful trends are also found when replicating the analysis using tweets for the 2020 Senate election, coded using the automated classifier developed for 2018. The implications of such results for the automated coding of campaign negativity in social media are discussed.
Applying Pareto meta-analysis in location selection for photovoltaic plant

In decision-making situations, it is common to have a set of alternatives and to choose the best among them or to establish a ranking. Multi-criteria decision methods can be applied to obtain different rankings, even though the set of alternatives and criteria are the same. Considering this, the idea of Pareto analysis is discussed to process the results obtained by different methods and reach a consensus. Those alternatives that are non-dominated will be considered the best set. That reduces the number of alternatives to be chosen because only the best set of alternatives should be taking into account.
Capsule Networks based Acoustic Emotion Recognition using Mel Cepstral Features

Emotions of human plays an important role in personal and work life. Performance at workplace is mostly dependent on the varying emotions and they can be captured through facial expressions, body language and acoustics. Identifying the basic emotions through speech has its own advantages and is progressive these days. Acoustic based emotion recognition can be either linguistic or non-linguistic and the latter is more flexible as it is language independent. Most of the work in this area till date has been done through machine learning algorithms and accuracy is almost compromised. The deep neural networks on the other hand have proven to be achieving more accuracy. The convolution neural networks used for feature extraction has limitations on capturing both temporal and spatial features. Capsule nets is one of the improvised solutions to tackle the situation. The proposed work has used capsule networks with dynamic routing in combination with convlD layer. The proposed model is experimented on RAVDESS, SAVEE, CREMA-D, EMODB, IEMOCAP corpora and is found successful. An improved test accuracy has been achieved on every data corpus.
Hierarchical reactive power regulation strategies for high‐penetration photovoltaic distribution systems

This paper proposes a hierarchical reactive power regulation system for distribution systems with photovoltaics (PV) connected. The proposed approach includes both central control level and local control level for decisions involving optimal reactive power compensation and dynamic control of reactive power regulation, respectively. Through local control level, based on the PV inverter controllers and central control level compensation command, the overvoltage and voltage variation problems can be highly relieved. In addition to possible reductions in PV generation curtailment, the grid voltage can also be well regulated with minimal line loss via the proposed PV system operation strategies. Accordingly, added value for PV systems is created, conferring win‐win solutions for both PV system owners and utilities. Numerical results tested on a practical Taipower company distribution system verified the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.
Polymeric Optical Fiber Fabrics for Illumination and Sensorial Applications in Textiles

An ever increasing number of publications, reviews, and books are written about polymer optical fibers (POFs). Articles of POFs for a wide range of applications especially for networks in buildings, automobiles, railways, aviation, or in industrial plants are numerous, while publications where POFs are used in textiles are rather rare. In this review, we want to present the different techniques to produce textile-based POFs and the possibilities and applications offered by these textiles. They have been produced for a wide range of implementations in illumination and sensing. Special attention will be given to the features of differences in textile structures resulting in flexible and lightweight structures. Recent applications in the field of optical textiles given in this report demonstrate practicability and usefulness for flexible 2D illumination areas. This article provides an overview of the current polymeric optical fiber fabrics and textile constructions for optical textiles and the main applications where these innovative textiles are of great benefit.
Multitask Variational Autoencoding of Human-to-Human Object Handover

Assistive robots that operate alongside humans require the ability to understand and replicate human behaviours during a handover. A handover is defined as a joint action between two participants in which a giver hands an object over to the receiver. In this paper, we present a method for learning human-to-human handovers observed from motion capture data. Given the giver and receiver pose from a single timestep, and the object label in the form of a word embedding, our Multitask Variational Autoencoder jointly forecasts their pose as well as the orientation of the object held by the giver at handover. Our method is in large contrast to existing works for human pose forecasting that employ deep autoregressive models requiring a sequence of inputs. Furthermore, our method is novel in that it learns both the human pose and object orientation in a joint manner. Experimental results on the publicly available Handover Orientation and Motion Capture Dataset show that our proposed method outperforms the autoregressive baselines for handover pose forecasting by approximately 20% while being on-par for object orientation prediction with a runtime that is 5x faster. a
Electromagnetic Characteristics Analysis of IPMSM for xEV Compressor using Vector Control

In general, interior permanent magnet synchronous motors are analyzed using the finite element method (FEM) by assuming that the input current is sinusoidal at a specific speed. However, in reality, it is operated through a drive system composed of a controller, compensator, and inverter. Therefore, the harmonic current is generated by an inverter that uses the pulse-width modulation method. The harmonic current increases the torque ripple and electromagnetic loss, and reduces the efficiency. Herein, the harmonic current is obtained from the simulation of a vector control system. Subsequently, FEM analysis was performed using the harmonic current, and the results were compared with those of a sinusoidal current.
CCRobot-IV-F: A Ducted-Fan-Driven Flying-Type Bridge-Stay-Cable Climbing Robot

A Flying-type cable climbing robot, CCRobot-IV-F, is presented in this paper. It is a climbing precursor of the fourth version of CCRobot, designed to surpass the abilities of previous robots with high climbing speed and obstacle-crossing capability. CCRobot-IV-F weighs less than 10 kg and a no-load speed of up to 4.5 m/s, which significantly exceeds that of other climbing robots. A dynamic model integrated with a cable-fixed coordinate system is developed, and a cascaded controller designed for stabilizing hover and climb with grippers, when a Global Positioning System and magnetometer are unavailable, is shown to work reliably in practice. Experimental results show that CCRobot-IV-F significantly improves the locomotive performance of CCRobot-IV, exhibiting fast speed, good payload capacity, and excellent obstacle-crossing capability. Moreover, CCRobot-IV-F is applied to a cable-stayed bridge in the field.
Hydraulic Hybrid Heavy Duty Vehicles - Challenges and Opportunities

The consumption of fossil fuels is one of the largest problems facing humankind. One of the heaviest users of non-renewable energy sources is the transport industry. Tightening worldwide legislation aims to place restrictions on the transport industry to reduce its use of fossil fuels and reduce the levels of pollution being released to the atmosphere. Although several different alternatives to the vehicles only powered by internal combustion engine (ICEs) have been investigated, none have as yet become equally widespread. Alternative research into development of hybrid vehicles was specifically concerned with electric hybrids especially for passenger vehicles. Currently there is a resurgence of interest in the Hybrid Hydraulic Vehicle (HHV) in application to commercial and to a lesser degree to passenger vehicles. This paper gives an overview of hydraulic hybrid technology.
Design and Flow Simulation of an Open Circuit Wind Tunnel

Summary In this study, a suction-type subsonic open circuit wind tunnel was designed and simulated in computer environment. The design and development of the wind tunnel model was performed using the 3D solid modeling program, SolidWorks. The computer aided simulation was done using the Fluent 6.0 program; the theoretical ideal experimental conditions have been created on this model and made the simulation of the flow through the tunnel. The simulation results were interpreted and the necessary improvements were defined.
Data Augmentation for Deep Neural Networks Model in EEG Classification Task: A Review

Classification of electroencephalogram (EEG) is a key approach to measure the rhythmic oscillations of neural activity, which is one of the core technologies of brain-computer interface systems (BCIs). However, extraction of the features from non-linear and non-stationary EEG signals is still a challenging task in current algorithms. With the development of artificial intelligence, various advanced algorithms have been proposed for signal classification in recent years. Among them, deep neural networks (DNNs) have become the most attractive type of method due to their end-to-end structure and powerful ability of automatic feature extraction. However, it is difficult to collect large-scale datasets in practical applications of BCIs, which may lead to overfitting or weak generalizability of the classifier. To address these issues, a promising technique has been proposed to improve the performance of the decoding model based on data augmentation (DA). In this article, we investigate recent studies and development of various DA strategies for EEG classification based on DNNs. The review consists of three parts: what kind of paradigms of EEG-based on BCIs are used, what types of DA methods are adopted to improve the DNN models, and what kind of accuracy can be obtained. Our survey summarizes the current practices and performance outcomes that aim to promote or guide the deployment of DA to EEG classification in future research and development.
State of the art and present trends in nonlinear microwave CAD techniques

The authors present a survey of modern nonlinear CAD (computer-aided design) techniques as applied to the specific field of microwave circuits. A number of fundamental aspects of the nonlinear CAD problem, including simulation, optimization, intermodulation, frequency conversion, stability, and noise, are addressed and developed. For each one it is shown that either well-established CAD solutions are available, or at least a solution approach suitable for implementation in a general-purpose CAD environment can be outlined. Also, the discussion shows that the various subjects are not just separate items, but rather can be chained in a strictly logical sequence. Finally, an elementary treatment of vector processing is given, to show that supercomputers can handle the involved large-size numerical problems efficiently. >
Sensorless Control of Switched Reluctance Motor Based on the Flux-Linkage Characteristics from Finite Element Method

To upgrade the application of switched reluctance motors (SRMs) for more electric aircraft (MEA), this paper presents a method which uses sensorless control based on the flux-linkage data from the finite element method. First, a calibration strategy based on the finite-element method (FEM) is employed to obtain the flux-linkage characteristics. Then, this paper uses sliding-mode observer (SMO) to realize the sensorless control of the SRM. Based on the flux-linkage characteristics and the SMO, a sensorless control technique for SRM in dynamic modes for high speed is implemented to minimize the bulk and cost. Experimental results verify the accuracy and effectiveness of the calibration and SMO strategy.
Productividad y Función de Producción de Ingeniería para la Producción de Glucosiltransferasa por Fermentación

Se presenta un modelo de función de producción de ingeniería para modelar la producción de glucosiltransferesa por fermentación, con el objetivo de determinar la máxima producción, máxima productividad y elasticidad unitaria. A los datos del primer DOE publicados por Kawaguti et al. (2005) se les aplicó el método de regresión estadística restringida (con R2 =0.981, P=001) y optimización restringida en el software Excel® Solver®. Para fermentar, se utilizó melaza de caña (X1 gL-1), licor de maíz (X2 gL-1) y levadura (X3 gL-1) Erwinia Sp. en cantidades identificadas por el vector de insumos X=(X1, X2, X3). Para cada combinación óptima seleccionada, los pronósticos para producción de glucosiltransferasa, costo por experimento y productividad son: producción óptima en (129.39, 72.897, 16.77) con 5.78 UmL-1, $0.74 y 7.75 UmL-1$-1 respectivamente; para productividad máxima en (118.39, 42,14, 4) con 4.56, $0.31 y 14.48; para productividad óptima (elasticidad unitaria y rendimientos constantes) en (102.44, 36.48, 3.46) con 4.01, $0.27 y 14.73. Los rendimientos de escala y elasticidad inducen a explorar el vector (102.56, 36.52, 3.47) como centro del próximo diseño experimental secuencial, tal que en este diseño se logre una mejor aproximación a los rendimientos constantes y una productividad óptima global.
On-state transient electrothermal modeling of large area power components and multichip power modules

This paper presents an original method specifically intended for transient electrothermal simulation of large area power modules. A simple on-state electrical modeling is associated with a heat-flow equation solver, which is able to predict temperature distributions over the whole active area of the module by taking into account transient 3D heat diffusion effects in chips and their common package. The method permits one to predict the electrothermal behavior of large area power components or modules when the waveform of the load current is known and has been implemented in a new software tool.
State Feedback Speed Controller for Turbocharged Diesel Engine and Its Robustness

In this paper, the full state feedback controllers capable of regulating and tracking the speed trajectory are presented. A fourth order nonlinear mean value model of a 448 kW turbocharged diesel engine published earlier is used for the purpose. For designing controllers, the nonlinear model is linearized and represented in state-space form. Full state feedback controllers capable of meeting varying speed demands of drivers are presented. Main focus here is to investigate sensitivity of the controller to the perturbations in the parameters of the original nonlinear model. Suggested controller is shown to be highly insensitive to the parameter variations. This indicates that the controller is likely perform with same accuracy even after significant wear and tear of engine due to its use for years. Keywords—Diesel engine model, Engine speed control, State feedback controller, Controller robustness.
Loop Shaping Control of a Model-Story Building Using Smart Materials

This research concerns active vibration control of a two-story model structural frame by using the method of loop shaping. Piezoceramic smart materials, in particular the PZT (Lead Zirconate Titanate) in the form of patches, are surface-bonded on the structure and function as actuators and sensors. Sensitivity charts are introduced to assist the control system design. A nonparametric system identification is performed to obtain the frequency response function of the model building. A loop-shaped controller is designed using sensitivity charts. The effectiveness of the designed controller is demonstrated by shaker table tests where data from four earthquakes is used for excitation of the structure. The experimental results clearly show that the loop shaping based controller reduces the vibrations experienced by the structure during seismic activities.
Who kept travelling and where did they go? Domestic travel by residents of SE Queensland, Australia

Abstract This paper presents a longitudinal study of domestic travel by residents of Southeast Queensland, Australia. It is framed within the distance decay concept. Two major findings emerged from the study. First, people who were most likely to forsake travel as a result of COVID-19 generally did not value it very highly, while those who continued to travel saw it as an important part of their lifestyles. Second, applying the distance decay concept revealed no change in destination choice in intra-destination movements over time, although the volume of tourists was substantially lower as a result of COVID-19. This findings suggests a degree of habit persistence prevails even in times of crisis.
Finite Element Modelling of Prestressed Concrete Piles in Soft Soils, Case Study: Northern Jakarta, Indonesia

Jakarta is faced with limited land resources due to its position as the capital city of Indonesia. Therefore, numerous high-rise buildings are being constructed to solve this problem and provide accommodations for a large number of Jakarta residents. Studies have shown that prestressed concrete piles (spun piles) are commonly used as the foundations of high-rise buildings in metropolitan cities across Indonesia, especially in the Northern Jakarta Coastal area, which is predominant with deep soft soils deposit. To further assess and verify the ultimate capacity of the pile, a static loading test was conducted. However, not all results from the field test produced ideal, accurate, precise, and reliable load-settlement curve (until failure) results. Therefore, this study aims to determine the soil properties for the analysis of prestressed concrete spun piles with a diameter of 600 mm in the Northern Jakarta coastal area based on the standard penetration test values (SPT-N). It is a case study of a well-documented static pile load test using the kentledge system. Back analyses were performed by the finite element method to obtain the extrapolated load-settlement curve. Furthermore, the effect of interface strength between pile and soil on the load-settlement curve was also investigated. The results showed that a reduction of interface strength leads to a smaller load–settlement curve. In addition, several geotechnical engineering parameters of soil, such as the undrained shear strength and effective young's modulus, were established using data from an in-situ soil site investigation and empirical correlations with SPT-N.