bluuebunny/crossref_metadata_2025_split huggingface dataset:
The agency of CLIL primary school teachers in Austria
Authors: Gruber Marie-Theres , Mercer Sarah 
Published: August 2021

AbstractAlthough recent years have seen a growth in studies examining teacher agency, educators working in the primary sector remain a relatively under-researched population. One specific group of teachers in primary education are those who teach Content and Language Integrated Learning (CLIL). In this study, we wanted to understand how CLIL primary teachers’ sense of agency helped them to navigate this professional role, considering factors in their ecologies which supported or inhibited their agency. Based on semi-structured, in-depth interviews with six primary school CLIL teachers, this study shows that even though these teachers were initially passionate about CLIL, they all ultimately exercised their agency as teachers in giving up on CLIL due to a limited sense of agency in the particular role as a CLIL educator.
Contact-induced grammatical change?
Authors: Kosmata Eva , Schlücker Barbara 
Published: August 2021

AbstractThe paper discusses how language contact and borrowing can be established as a critical factor of quantitative and/or qualitative changes of abstract grammatical patterns, in particular if languages are genetically and areally closely related and thus structurally similar. More specifically, it deals with the question of whether the word-formation pattern of proper name compounding in German and Dutch is an instance of grammatical borrowing from English, as is often claimed in the literature. To this end, we conduct a structural analysis of the pattern in the three languages based on original and translation corpus data. We show that the pattern which, at first glance, seems to be identical in all three languages has in fact different properties in each language. Although this does not necessarily preclude transfer from English, we conclude that there is no evidence in favour of such an influence.
La Figurante de François de Curel. Comédie des apparences ou jeu de rôles
Authors: Kaczmarek Tomasz 
Published: August 2021

Abstract
François de Curel, mistakenly regarded as an author of the “problem play”, enjoyed a reputation of an innovator in
dramaturgy during his lifetime. By rejecting the canonical form of the drama, he proposes works in which psychological analysis prevails
over the dramatic progression of the action. In fact, in La Figurante, the French writer paints a portrait of the
characters who resemble “marionettes” operated by unknown forces. In order to survive in bourgeois society, they assume the “masks” that
social conventions demand of them and conscientiously play the comedy. However, under the facade and the artifices, the protagonists keep
their existential anxieties which express their inner sincerity. In this context, the analysis of this play will lead us to seek affinities
with the grotesque dimension of the Pirandello theater.
Identification and characterization of nested-abbreviated terms in scientific discourse
Authors: Rivas Natalia , Quiroz Gabriel , Giraldo John Jairo 
Published: August 2021

Abstract
This paper analyzes nested-abbreviated terms from a linguistic perspective by describing their morphological,
syntactic, and semantic features for terminology purposes. Nested-abbreviated terms can be considered as abbreviated
forms, either initialisms or acronyms, which have within their meaning another abbreviated term. To carry out the
analysis, 433 nested-abbreviated terms were extracted from two specialized dictionaries in English. Data analysis showed that,
from the morphological and semantic perspective, nested-abbreviated terms behave like typical abbreviations. Important differences
were found from a syntactic standpoint where nested abbreviated terms behave as premodifiers in the noun phrase (NP) in 98.93% of
the cases. As this is the first time nested-abbreviated terms are studied, they were not only described but also analyzed and
defined. Although the percentage of nested-abbreviated terms obtained from the dictionaries is relatively low, less than 1% of
total abbreviations, it was found that it is highly relevant to study this growing phenomenon in specialized languages for
terminology extraction, as well as for other purposes.
Acute affective responses to high‐intensity interval exercise: Implications on the use of different stimulus‐recovery amplitudes
Authors: Oliveira Bruno Ribeiro Ramalho , Santos Tony Meireles , de Carvalho Guerreiro Renato , D'Amorim Igor , Lattari Eduardo , Deslandes Andréa Camaz 
Published: August 2021

ABSTRACTThe effect of high‐intensity interval exercise (HIIE) on affective responses is unclear due to the several variables of HIIE, which may be minimized by using derived variables (e.g. amplitude). The amplitude reflects the difference between stimulus and recovery intensities, being more representative of the physiological changes than central tendency variables such as average intensity. This study aimed to compare the affective responses in HIIE sessions in different amplitudes with a vigorous‐intensity continuous exercise (VICE) session. Eleven participants completed five sessions. The peak oxygen consumption (VO2Peak) and peak power (Wpeak) were measured. Participants performed one VICE and three HIIE sessions (10x[1min‐90%WPeak/1min‐50%WPeak]; 10x[1min‐100%WPeak/1min‐40%WPeak]; and 10x[1min‐110%WPeak/1min‐40%WPeak]). The exercise sessions were performed at the same average intensity (70%WPeak) and duration (20 min). The Feeling Scale (FS) was applied in each minute throughout the exercise sessions. Regarding the FS responses, a two‐way repeated‐measures ANOVA showed no significant interaction for FS (P=0.093) or main effect for condition (P=0.206) and time (P=0.078), indicating that irrespective of the amplitude of the HIIE, FS results were similar between conditions. The effect size (ES) analysis showed a small effect in favour of HIIE‐90/50 (ES=0.30) and HIIE‐100/40 (ES=0.26) and a null effect on HIIE‐110/30 (ES=0.08) when compared to VICE. Chi‐squared analysis showed no significant differences between conditions in the number of participants that reduced, maintained, or increased the FS from pre‐exercise to last stimulus and recovery indicating a high variability of the affective responses. HIIE sessions provide similar affective responses when performed at the same average intensity, even with different amplitudes.Highlights
HIIE amplitude reflects the difference between stimulus and recovery intensities and seems not to modulate the affective responses to HIIE sessions configured with different amplitudes.
HIIE sessions performed at the same average intensity and different amplitudes result in similar affective responses.
High inter‐individual variability of affective responses occurs in HIIE sessions configured based on the amplitude.
Microsphere structure application for supercapacitor in situ temperature monitoring
Authors: Listewnik Paulina , Bechelany Mikhael , Szczerska Małgorzata 
Published: August 2021

Abstract
Constant, real-time temperature monitoring of the supercapacitors for efficient energy usage is in high demand and seems to be crucial for further development of those elements. A fiber-optic sensor can be an effective optoelectronic device dedicated for in-situ temperature monitoring of supercapacitors. In this work, the application of the fiber-optic microstrucutre with thin zinc oxide (ZnO) coating fabricated in the atomic layer deposition process applied as a temperature sensor is reported. Such a structure was integrated with supercapacitors and used for the temperature measurements. Described sensors are built with the utility of the standard optical telecommunication fibers. The inner temperature of the supercapacitor was investigated in the range extending from 30 °C to 90 °C with a resolution equal to 5 °C. The sensitivity of temperature measurement is about 109.6 nW °C−1. The fitting of the sensor was achieved with a correlation coefficient R
2 = 0.97.
Observation of source/drain bias-controlled quantum transport spectrum in junctionless silicon nanowire transistor
Authors: Guo Yang-Yan , Han Wei-Hua , Zhang Xiao-Di , Chen Jun-Dong , Yang Fu-Hua 
Published: August 2021

Abstract
We investigate the influence of source and drain bias voltages (V
DS) on the quantum sub-band transport spectrum in the 10-nm width N-typed junctionless nanowire transistor at the low temperature of 6 K. We demonstrate that the transverse electric field introduced from V
DS has a minor influence on the threshold voltage of the device. The transverse electric field plays the role of amplifying the gate restriction effect of the channel. The one-dimensional (1D)-band dominated transport is demonstrated to be modulated by V
DS in the saturation region and the linear region, with the sub-band energy levels in the channel (E
channel) intersecting with Fermi levels of the source (E
fS) and the drain (E
fD) in turn as V
g increases. The turning points from the linear region to the saturation region shift to higher gate voltages with V
DS increase because the higher Fermi energy levels of the channel required to meet the situation of E
fD = E
channel. We also find that the bias electric field has the effect to accelerate the thermally activated electrons in the channel, equivalent to the effect of thermal temperature on the increase of electron energy. Our work provides a detailed description of the bias-modulated quantum electronic properties, which will give a more comprehensive understanding of transport behavior in nanoscale devices.
Experimental study of three in-line bubbles rising in still water by means of a three-dimensional (3D) shadowgraphy technique
Authors: F Di Nunno , Granata F , Miozzi M , Gargano R , Marinis G de , Pereira F Alves , Felice F Di 
Published: August 2021

Abstract
The dynamics of rising bubbles in still water can be influenced by the wake characteristics of the neighbouring bubbles. An experimental study was conducted on individual rising bubbles rising in still water by means of volumetric shadowgraphy technique. Results highlighted a phase opposition relationship between the volumes and rising velocities and between the minor semi-axis and the two semi-axes median and major of the three air bubbles. The cross-correlation function applied on the eccentricities of the three bubbles highlighted similar positive peaks but also a negative peak between eccentricities of the second and third bubbles. Frequency spectra of the three bubbles eccentricities exhibited some common features, with peaks around 10 Hz for the first and third bubbles and around 5 Hz for the second and third bubbles. In addition, cross-correlation applied on the rising velocities showed negative correlations between the three bubbles, with each bubble that reduces its rising velocity while another accelerates. The application of the volumetric shadowgraphy allowed a simultaneous measurement of the geometry and rising velocities of the in-line bubbles, leading to identify common and different features among them.
Experimental Fluid Dynamic Characterization of Serrated Rotors for Drone Propulsion
Authors: Candeloro Paolo , Nargi Ranieri Emanuele , Grande Edoardo , Ragni Daniele , Pagliaroli Tiziano 
Published: August 2021

Abstract
The present study reports an experimental investigation regarding one of the most effective and most studied passive control technique in literature to mitigate the noise pollution radiating by a small drone: the Serrated Trailing Edge (STE). 23 quiet propellers have been designed and manufactured in order to identify the most silent configuration. An aeroacoustic pre-qualification of the designed propellers has been performed by means of microphone measurements within the anechoic chamber of Niccolò Cusano University. Then, an aeroacoustic and fluid dynamic characterization of the most performing configuration has been carried out by means of load cell, microphone and PIV measurements in the anechoic wind tunnel facility of TUDelft University of Technology in order to investigate the mechanism that stands behind the noise mitigation. With this purpose, the aerodynamic and aeroacoustic performance and even the velocity and vorticity field along the blade of STE propellers have been characterized. Particular attention is devoted to the fluid-dynamic aspects related to the low Reynolds number flow regime. Results show that serrations seems to modify the wake velocity and the tip voretx intensity resulting in a lower acoustic emission.
Defocusing PIV and ridge-detection algorithm for the analysis of flows laden with non-spherical particles
Authors: Capone Alessandro , Romano Giovanni Paolo , Felice Fabio Di , Pereira Francisco Alves 
Published: August 2021

Abstract
In this preliminary work, the feasibility of the combination of a volumetric velocimetry technique such as Defocusing Particle Image Velocimetry and a particle phase-discrimination methodology based on ridge detection algorithm for the analysis of turbulent multiphase flows with non-spherical fiber-like particles is discussed. Experimental results of a dilute suspension of fibers in an open-channel apparatus are provided.
Automatic Detection of Learning Styles: A Decade Review on Data-driven Approaches
Authors: Ngatirin Nor Rahayu , Zainol Zurinahni 
Published: August 2021

Abstract
Different approaches or ways of learning are referred to as learning styles. Learning styles are identified to help educators understand how students learn and to help students become more self-aware of their learning strengths and weaknesses. Students, on the other hand, are unaware of their learning patterns and preferences. The traditional method of determining learning styles has been characterized as a questionnaire-based approach. However, it has various flaws that prohibit learning style identification, such as students' lack of motivation to complete a questionnaire, their reluctance to offer information, and the questionnaire's measurement of learning styles is limited to a single point in time. As a result, an automated approach for automatically detecting students' learning styles has been proposed to overcome these restrictions. The goal of this research is to give a review of existing research in the field of learning styles detection. A total of 36 papers were considered in the study, which was published between 2010 and 2020. Thus, this research highlights the review's findings, which are likely to assist researchers and practitioners in better understanding the theoretical and technical challenges surrounding automatic detection of learning styles.
RapidMiner and Machine Learning Techniques for Classifying Aircraft Data
Authors: Marzukhi Syahaneim , Awang Norfatimah , Alsagoff Syed Nasir , Mohamed Hassan 
Published: August 2021

Abstract
Machine learning is an important technique that helps companies, organizations and individuals to improve the quality of decision making. In today scenario, especially with the emerged of data science, it can see how machine learning techniques are used for data analytics. There are various machine learning techniques for data science tasks that can be categorized as follows: classification, prediction, regression, association analysis, clustering, time series forecasting, and many others. As there are many different free tools available for machine learning, the selection of the appropriate analysis technique is crucial to solve problem in hand. This study compares the performance of machine learning algorithms especially Naïve Bayes, Decision Tree, Random Forest and ID3 for classification task (i.e. classifying aircraft to certain category and into country of origin) using RapidMiner tool. Those algorithms are compared based on their accuracy rate, error rates, precision and recall for classifying aircraft. The results reveal that that Random Forest and ID3 algorithms given good classification accuracy due to the nature of the algorithms that is progressively improved apart from Decision Tree.
Performance Analysis of GreedLea Routing Protocol in Internet of Vehicle (IoV) Network
Authors: Omar N , Yaakob N , Saidahmed M E E , Husin Z 
Published: August 2021

Abstract
The Internet of Vehicles (IoV) network transforms smart life on the wheels through several connections between vehicles, highways, people and networks, providing a safer, more effective and more energy-efficient driving experience. In a specific field, the reliable arrival of independent vehicles and the typical enhancement of traffic safety change through a fast and consistent distribution of messages. It is important to disseminate messages between vehicles that make up the IoV network and to be exploit of the quick and effective transmission of multi-hop communication for the information broadcasting. This study introduces the standardization method and summarizes the primary technologies of IoV network. This study provides a set of traditional research developments, analyses key innovations to date and, eventually, proposes solutions to common use cases that could provide valuable references for the development and implementation of potential IoVs network. The simulation has been done using OMNET++ platform to evaluate the GreedLea routing protocol with the standard Greedy Perimeter Stateless Routing (GPSR) and Ad-hoc On-demand Distance Vector (AODV) routing protocol in IoV network scenario. In the performance analysis varied parameters for example direction, node and speed has been take into account. This study also proposed to evaluate GreedLea in a crowded city situation and in a highway situation to provide further realistic simulations. From the simulation results, it shown that the GreedLea presented better performance compared to the traditional GPSR and AODV in term of end-to-end latency, packet loss rate and path loss.
Harmonic analysis in modified cascaded multilevel inverter with nature-inspired switching-angle optimization algorithm
Authors: Sea Y W , Chew W T , Ong J S , Leong J H 
Published: August 2021

Abstract
Selective harmonic elimination pulse width modulation (SHEPWM) is a fundamental frequency switching angles calculation technique that eliminates the undesired low order harmonics while maintaining the desired fundamental component. A natured-inspired optimization algorithm, grasshopper optimization algorithm (GOA), is applied in SHEPWM to obtain the optimized switching angles. Compared to Newton Raphson (NR), GOA is able to provide wider range of solutions. Optimize switching angles obtained from MATLAB analysis are applied to a 5-phase 7-level modified cascaded multilevel inverter (MCMLI). This paper presents the performance of GOA applied to the MCMLI. The 3rd and 7th harmonics are chosen to be eliminated while the desired fundamental component is maintained.
Performance of Supervised Learning Algorithms on Imbalanced Class Datasets
Authors: Ramli Nur Anisah Binti , Jamil Maria Jasmin Binti Mohamed , Zhamri Nur Nazifa Binti , Abuzaraida Mustafa Ali 
Published: August 2021

Abstract
In this paper, we measure the performance of supervised learning algorithms on imbalanced class datasets. Supervised learning is considered to be the most advanced and mature from other types of learning in machine learning. On the other hand, imbalanced class data sets refer to an unequal amount of data for each class in the data sets. Many real-world datasets exhibit an imbalanced class distribution. Hence, this paper aims to compare the supervised learning algorithms in classifying the output for imbalanced dataset. This paper also focused on finding the significance of balancing the dataset to the results. This study is conducted by using three different datasets and made a comparison with three supervised learning algorithms chosen which are Logistic Regression, Random Forest and k-Nearest Neighbours. In the experiments, all three datasets used are labelled data with imbalanced class. Due to the imbalanced class for all datasets chosen, a sampling technique with combination of under-sampling and oversampling is implemented to all datasets in data preparation steps. The performance of the algorithms is measured through Classification Accuracy (CA) value. From the experiments, it is proven that Random Forest shown the best results, for both imbalanced and balanced datasets.
Towards Building eco-friendly and emission less Electric Scooter
Authors: Lokitha T , Venkatesh B , Kumar S Arun , Sasikala S 
Published: August 2021

Abstract
Electric vehicles are becoming more important, as not only to reduce carbon emission but also to reduce the dependency on normal combustion engine vehicles. Most of the universities have really big campuses. To make the mobility in campus easier, the harmless and power-controlled vehicle with safety technologies is introduced. Besides, it also reduces time consumption. Further, it aids differently abled persons and aged professors. This paper presents the design and development of a compact, portable and weightless electric skating scooter. The vehicle body design is inspired from the sea cartilaginous fish ‘String Ray’. It also includes mechanical features like front shock absorber, handlebar break control, portable and handle bar height adjustment. The electrical and electronic features such as obstacle detector, fingerprint and RFID (Radio-frequency identification) access, battery management system (BMS) etc., help towards building a smart vehicle. Besides, it also provides a vehicle management system for tracking the user details, location and condition of the vehicle through a server. The proposed system with addition of mechanical, electrical and electronic features will help towards enhancing the performance of an electric scooter for easy mobility. The results obtained from the on-road test, CADD software and the implementation of vehicle management system has been discussed.
Semantic Segmentation of Surgical Instruments based on Enhanced Multi-scale Receptive Field
Authors: Dong Yu , Wang Hongbo , Luo Jingjing , Lai Zhiping , Wang Fuhao , Wang Jiawei 
Published: August 2021

Abstract
With the rapid development of robot assisted surgery, the segmentation of surgical instruments becomes more and more important. However, compared with the natural scene segmentation, surgical instrument segmentation is more difficult. To solve this problem, we improve a high and low resolution fusion module, which aims to extract detail information and context information from the fusion feature map of high and low resolution. Then, in the last layer of the encoder, we propose the Enhanced Multi-scale Receptive Field module to generate more available receptive fields. Our method is validated on 2017 MICCAI EndoVis Robotic Instrument Segmentation Challenge dataset, and the result is better than the other methods. The extended experiment is carried out on the dataset of our surgical soft robot which has a content implementation.
Emerging and Disruptive Technologies for Urban Farming: A Review and Assessment
Authors: Ng Andrew Keong , Mahkeswaran R 
Published: August 2021

Abstract
Increasing food demand in urban areas compounded with unsustainable conventional farming practices and reducing arable land has led to the development of urban farming. Urban farming techniques include vertical farming, indoor farming, hydroponics, aeroponics, aquaculture, and aquaponics. However, these methods alone cannot revolutionise farming; hence, they need to be coupled with technological innovations to reap their full potential and benefits. This paper reviews a variety of emerging and disruptive technologies introduced to urban farming, namely internet of things, automation, artificial intelligence, robotics, blockchain, digital twins, renewable energy, genetic modification, additive manufacturing, and nanotechnology. Each technology is discussed with regard to its applications, advantages, and disadvantages. Recommendations are also provided for future research and development.