Miracle-dz/UniFAR-FTUs huggingface dataset:
Technologies in higher education ( face-to-face teaching ) : An analysis of the variables that influence its adoption

Information technology, once used only as a distance learning modality, is increasingly present in face-to-face teaching, making it hybrid. Research on the variables that influence the adoption of these technological innovations by students, identifying the relationship between these variables can contribute to the creation of more effective teaching and management strategies in higher education institutions. The aim of this article was to identify the variables that contribute to technological innovation in the virtual learning environment AVA / Webaula, taking into account the aspects that may contribute to its adoption as a tool to support higher education in person. The study used Rogers’s Theory of Diffusion and Adoption of Innovation (1983), improved by Moore and Benbasat (1991) and contextualized by Perez (2006) as a theoretical basis. The research was exploratory, bibliographical and empirical. We conducted a case study with 122 students from the Administration and Law courses of Faculdade Estácio de Vila Velha. We collected data through a questionnaire with 25 closed questions and the model structured in SPSS software. The research concluded that the variables relative advantage, image, compatibility, demonstration of results affected significantly in the adoption / use of Webaula. © 2017 Departamento de Administração, Faculdade de Economia, Administração e Contabilidade da Universidade de São Paulo – FEA/USP. Published by Elsevier Editora Ltda. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).
A HIGH-PERFORMANCE SVPWM CONTROLLER FOR THREE-PHASE UPS SYSTEMS OPERATING UNDER HIGHLY NONLINEAR LOADS

This paper presents the design of a high-performance space-vector pulse width modulation (SVPWM) controller for three phase uninterruptible power supply (UPS) systems that are operating under highly nonlinear loads. The classical SVPWM method is quite effective in controlling the RMS magnitude of the UPS output voltages. However, it is not good enough in compensating the harmonics and the distortion caused specifically by the nonlinear currents drawn by the rectifier loads. The distortion becomes more severe at high power where the switching frequency has to be reduced due to the efficiency concerns. This study proposes a new design strategy that overcomes the limitations of the classical RMS control. It adds inner loops to the closed-loop control system effectively that enables successful reduction of harmonics and compensation of distortion at the outputs. Simulink is used to analyze, develop, and design the fuzzy logic controller. The controller is implemented and the performance is evaluated by using MATLAB/SIMULINK. In conclusion, the simulation results demonstrate that the fuzzy logic controller successfully achieves the steady-state RMS voltage regulation specifications as well as the total harmonic distortion and the dynamic response requirements of major UPS standards.
Measurement and Modeling of Solubility of Galactose in Aqueous Ionic Liquids, 1-Butyl-3-Methyl Imidazolium Bromide, 1-Hexyl-3-Methyl Imidazolium Bromide and 1-Butyl-3-Methylimidazolium Chloride at T = (298.15 And 308.15) K

Background: Saccharides are considered as abundant, cheap and renewable starting materials for chemicals and fuels. Recently, ionic liquids have been used as green solvents for saccharides. The solubility values of galactose in aqueous ionic liquid solutions are not available. Thus, the main objective of this research was to determine the solubility of galactose in aqueous solutions containing ionic liquids, 1-butyl-3-methyl imidazolium bromide, [BMIm]Br, 1-butyl-3-methylimidazolium chloride [BMIm]Cl and 1-hexyl-3-methyl imidazolium bromide, [HMIm]Br at different mole fractions of ionic liquids at T = (298.15 and 308.15) K. Methods: In this study, the gravimetric method was used to measure the solubility of galactose in aqueous ionic liquids solutions. Results: The solubility values of galactose in water and aqueous ionic liquid solutions were correlated with the activity coefficient models of Wilson, NRTL, modified NRTL, NRF-NRTL, and UNIQUAC. Conclusion: It was concluded that with increasing the mole fraction of ionic liquids, the solubility values of galactose decrease and in fact all of these ionic liquids show salting-out effect on aqueous galactose solutions and this behavior is stronger in ionic liquid 1-butyl-3-methylimidazolium chloride.
COGNITIVE FIELD OF BLOOM’S TAXONOMY AND GEOGRAPHY TEACHING

The aim of this paper is to present Bloom’s Taxonomy of educational objectives, especially its cognitive field and its importance for the quality improvement of Geography teaching during curriculum reforms in Bosnia and Herzegovina. In this paper, we will use the method of theoretical analysis. By the analysis of different methodical, didactic and psychological references, we have concluded that Bloom’s Taxonomy can be used in creation of Geography syllabuses, for aim operationalization in Geography teaching (outcome), as well as to make the process of verification easier for teachers. Usage of Bloom’s Taxonomy can contribute to overcoming the lack of traditional teaching through development of critical and creative thinking as well as active learning/teaching.
CENTERIS-International Conference on ENTERprise Information Systems / ProjMAN-International Conference on Project MANagement / HCist-International Conference on Health and Social Care Information Systems and Technologies , CENTERIS / ProjMAN / HCist 2018 Designing an Interactive Exhibitor for Assist

Blind and visually impaired visitors experience a lot of constraints when visiting museums exhibitions, giving the ocular centricity of these institutions, the lack of cognitive, physical and sensorial access to exhibits or replicas, increased by the inaccessibility to use the digital media technologies designed to provide different experiences, among other constraints. This paper aims to present the design and implementation of an exhibitor to communicate original museum samples to blind and visually impaired patrons, without the need to be replicated, that interactively "tell stories about their lives" whenever picked up. Tests performed with 13 partially sighted and blind participants at the main exhibition museum space, demonstrated very positive evaluations regarding pragmatic and hedonic qualities of the interaction, a positive capacity to mentally conceptualize the exhibits according to the audio descriptions, and how to enhance the experience of using more exhibitors like this one during a future visit to the museum. 2018 he uthors. ublished by lsevier td. i i rti l r t s: /creativeco mons.org/lic nses/by-nc-nd/4.0/) l ti fi rise Information Systems / ProjMAN Inter ational Conference on Project MANagement / HCist International Conference on Health and Social Care Information Systems and Technologies. * Corresponding author. Tel. : +351 273303103; fax: +351 273313050. E-mail address: pof@ipb.pt Available online at www.sciencedirect. com
Characterization of Ni 3 Al Alloy Fabricated by Thermal Explosion / Hot Extrusion Technique

In the present paper, the trace B doped Ni3Al alloy was prepared by the thermal explosion and hot extrusion (TH/HE) technique. Its microstructure characterization and mechanical properties were carried out by OM, XRD, TEM, compression and microhardness tests. Microstructure examinations exhibit that the TH/HE technology has transformed the powders into Ni3Al alloy with less porosity. In the synthesized part, coarse and ultrafine Ni3Al grains constitute the dual-scale grain structure with segregated Al2O3 particles along grain boundary. TEM observations reveal that γ-Ni, Al2O3 and Ni3Al phases coexist in the synthesized part. Moreover, the Al2O3 particles in the synthesized part have αAl2O3 and γ-Al2O3 two crystal structures. In addition, there is a transition region along the interface of Al2O3 and Ni3Al grain. The subsequent hot extrusion optimizes the microstructure of the extruded part by homogenizing the Ni3Al grain, uniformly distributing Al2O3 and generating massive substructures. The great deformation results in the pile-up of dislocations, intersected dislocations and substructures. Moreover, the movement of dislocation promotes the formation of micro-twinning in the Ni3Al grain, which is accompanied with the stacking faults and nano-structure. The mechanical properties exhibit that the microstructure optimization caused by the TE/HE technique improves the compressive ductility and strength of the Ni3Al alloy obviously.
THE INFLUENCE OF POLYPHENOLS ON THE FORMATION OF FREE RADICALS DETECTED IN MAILLARD REACTION MODEL SYSTEMS

The formation of pyrazine cation radicals was detected in model systems consisted of D(+)-glucose (1.0 mol L) and structural isomers of aminobutanoic acid (1.0 mol L) heated at the temperature of 98 °C for 20 minutes using electron spin resonance (ESR) spectrometry. Based on the analyses of hyperfine structure of ESR spectra of reaction mixtures of model systems, the presence of 1,4-disubstituted pyrazine cation radicals was found. Different polyphenols (gallic, caffeic, ferulic, chlorogenic acid, and tannic acid) were added in the model systems to investigate their influence on the formation of pyrazine cation radicals. It was found that tannic acid was the most efficient in inhibiting the formation of free radicals followed by gallic > caffeic  chlorogenic > ferulic acid.
The Rheology and Processing of Carbon Nanotubes for Polymer Composite Applications

This presentation first highlights experimental observations on the rheology of: (1) non-functionalized CNTs that aggregate and (2) functionalized CNTs that do not aggregate in flow. The shear and extensional flow behavior of these two types of CNTs are compared and contrasted. Extensional flow is of particular relevance to fiber spinning and inkjet printing of CNT-containing “fluids”. In the second part of the presentation, two different rheological models are presented and discussed. These models connect the viscosity data with the orientation and the aggregation state of CNTs, offering insights into controlling CNT dispersion, alignment, and the final properties of CNT polymer composites.
SIMPLIFYING THE DESIGN PROCESS OF A MEMS-BASED NANOSCALE MATERIAL TESTING DEVICE

Micro Electro Mechanical Systems (MEMS) are increasingly used to investigate the mechanical properties of nanoscale structures; however, their design, analysis, and layout are often difficult processes. We present the details of an online tool that simplifies these processes for particular nanomechanical testers. Our test case is based on a MEMS nanoscale material testing system previously created and tested by Espinosa and Zhu. Our tool allows users to easily explore a parameterized design space, simulate resulting performances, and export the designs as parameterized layout arrays in GDS-II format for direct manufacture. The performance attributes of the resulting sensor depend on the properties of the nanoscale sample under examination. We therefore integrate our parameterized lumped model of a carbon nanotube (CNT) together with the MEMS for a more complete representation of a micro/nanosystem. Our results show that our model agrees well with previously reported results and show that such a M/NEMS can be explored and laid-out by novices in minutes. Our tool is accessed online at nanoHub.org.
Decision-Making under Uncertainty for Social Robots

In this thesis, we explore the problem of learning social behaviour for a semi-autonomous telepresence robot. We extract social cost functions from instantaneous and delayed feedback obtained from realworld experiments, so as to establish a performance metric for the behaviour of our autonomous agent in a social setting. Based on the identified social cost functions, we extract additional insight regarding the normative behaviour of the agent as a response to perceived social cues, and discuss the relevant state features to be used for autonomous control in the task of social positioning during conversation. We also propose a discretized proxemics-based state space representation for this task given the feedback collected during our experiments, and perform a statistical analysis on the relevance of the state features in a group conversation setting. In the second part of this work, we compare and discuss different approaches to the problem of obtaining a control policy for our task of positioning of the robot during social conversation. This is a challenging task due to the limited information available to the agent during execution. Specifically, we study the performance as well as the ease of implementation of Partially Observable Markov Decision Processes (POMDPs) against a Long Short Term Memory (LSTM) recurrent neural network. We show by validating both methods on real world experiments that the LSTM outperforms the POMDP in our task, and offer explanations for that result which can help guide the deployment of these frameworks for more general problems of decision-making under uncertainty in the field of Robotics.
A Higher-Order Generalized Ghost Fluid Method for the Poor for the Three-Dimensional Two-Phase Flow Computation of Underwater Explosions and Implosions

The ghost fluid method for the poor (GFMP) is an elegant, computationally efficient, and nearly conservative method for the solution of two-phase flow problems. It was developed in one dimension for the stiffened gas equation of state (EOS) and one-step time-discretization algorithms. It naturally extends to three dimensions but its extension to higher-order, multi-step time-discretization schemes is not straightforward. Furthermore, the original GFMP and many other ghost fluid methods fail to handle the large density and pressure jumps that are encountered in underwater explosions and implosions. Therefore, the GFMP is generalized in this work to arbitrary EOS and multi-fluid problems with multiple EOSs. It is also extended to three dimensions and developed for higher-order, multi-step time-discretization algorithms. Furthermore, this method is equipped with an exact two-phase Riemann solver for computing the fluxes across the material interface in order to address the stiff nature of the two-phase air/water problem and handle the large discontinuity of the density at the air/water interface. As the original GFMP, the resulting method is computationally efficient and nearly conservative. Its superior performance in the presence of large density and pressure jumps is demonstrated for shock-tube problems. Its practicality and accuracy are also highlighted with the simulation of the growth, collapse, and rebound of an underwater bubble and the comparison of the obtained numerical results to experimental data.
Temporal Flow Characteristics of High-Frequency Supersonic Actuators Integrated in REM-Nozzle Assembly

Temporal flow characteristics of a high-frequency supersonic actuator integrated to a nozzle-injector assembly designed for high-speed flow mixing is presented in this paper. This resonance enhanced microactuator nozzle system (REM-Nozzle) injects a fluid through four micro-nozzles (each 400 μm diameter) positioned symmetrically around a 1.0 mm nozzle through which a high-frequency supersonic actuation jet pulses out in the frequency range of 13 21 kHz. Compressed CO2 is used as mixing fluid and compressed nitrogen is used for generating the actuation jet. The pulsed flow generates strong compressible vortex in the shear layer of steadily injected fluid that entrain and grows downstream enhancing microscale mixing of the injected fluid and nitrogen at very high-speed, and at a designated frequency. This paper summarizes the design details and characteristics of REM-nozzles, and reports the ongoing studies on temporal characteristics of pulsed actuator flowfield using high-speed microschlieren imaging technique.
Deep Q Learning for Self Adaptive Distributed Microservices Architecture (in press)

One desired aspect of a self-adapting microservices architecture is the ability to continuously monitor the operational environment, detect and observe anomalous behavior, and provide a reasonable policy for self-scaling, self-healing, and self-tuning the computational resources in order to dynamically respond to a sudden change in its operational environment. The behaviour of a microservices architecture is continuously changing overtime, which makes it a challenging task to use a statistical model to identify both the normal and abnormal behaviour of the services running. The performance of the microservices cluster could fluctuate around the demand to accommodate scalability, orchestration and load balancing demands. To achieve the desired high levels of self-adaptability, this research implements microservices architectures model following the MAPE-K model. Our proposed architecture employs Markov decision process (MDP) to identify the transition from one cluster state to another. Our proposed architecture employs a deep Qlearning network (DQN) for dynamically selecting the adaptation action that yield the highest reward. This paper evaluates the effectiveness of using DQN and MDP agent to achieve high level of self-adaptability of microservice architecture. We argue in this paper that such integration between DQN and MDP in MAPE-K model offers microservice architecture with self-adaptability against the contextual changes in the operational environment. The self-adaptation property is achieved by allowing the MDP agent to explore the observation space and lets the DQN to select the adaptation policy with the highest reward, then the MDP agent executes the adaptation action and observes the changes. We believe integrating DQN into the adaptation action selection process improves the effectiveness of the adaptation and reduces the adaptation risk including resources over-provisioning and thrashing. The proposed model preserves the cluster state and preventing multiple actions to taking place at the same time. Our model also guarantees that the executed adaptation action fits the current execution context and achieves the adaptation goals. INDEX TERMS Anomaly detection, Microservices architecture, Q learning, runtime configuration, self healing, reinforcement learning, policy approximation.
Neural Network Modeling of Cutting Force and Chip Thickness Ratio For Turning Aluminum Alloy 7075-T 6 Mohanned

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).
Parametric study of anchored earth wall by finite difference method

This parametric study was undertaken to investigate the behavior of a new type of anchored earth wall system using a three dimensional explicit finite difference program, FLAC 3D. A 5m high and 4m wide anchored earth wall supporting a simultaneously constructed roadway was considered as standard wall and modeled using FLAC 3D. The wall system consists of reinforced soil and retained soil, four layer of reinforcing steel in both horizontal and vertical direction as cable element and concrete block as anchor. The parameters studied were (i) cable spacing (ii) fill soil property. Emphasis was placed to investigate the variation of (i) mid section deflection of the wall (ii) stress in the cable (iii) pull in the anchor with the above mentioned parameter. The study revealed that deflection of the wall, stress in cable and pull in the anchor depend, to a large extent, on cable spacing and soil stiffness. It was evident from the study that soil with elastic modulus of 20 MPa and cohesion of 40 kPa, provide better economy and serviceability.
ESTIMATION OF CARBON EMISSION IN THE EX-MEGA RICE PROJECT, INDONESIA BASED ON SAR SATELLITE IMAGES

This paper aims to estimate the extent of the burned area in ex-Mega Rice Project (MRP) (Block A and Block E), Central Kalimantan and quantify the carbon emission as a result of peat fires in this area. A Synthetic Aperture Radar TerraSAR-X image was the main input in this study. Preprocessing included radiometric calibration, geometric reprojection and speckle filtering (Gamma MAP 7 × 7 kernel size). Maximum Likelihood (ML) classification was used for classifying burned areas. The classification result was validated based on data from the Kalimantan Forests and Climate Partnership report (KFCP). The burned area in 2010 as estimated by the TerraSAR-X satellite image HH/HV polarization was 47.6113 km (4761.13 ha). Main pollutants (carbon dioxide (CO2), carbon monoxide (CO), particulate matter (PM), black carbon (BC) and organic carbon (OC)) emissions were estimated based on an empirical equation. The average annual carbon releases into the atmosphere from this area were estimated to be 173,019.46 ton CO2, 11,388.62 ton CO, 1,149.81 ton PM10, 996.50 ton PM2.5 569.43 ton OC and 72.27 ton BC. This study suggests that the methodology proposed based on Earth Observation data can be used to locate burned areas in tropical environment and quantify carbon emissions.
Job Duration in Small and Large Firms: The Roles of Skills and Knowledge Intensity

@ @ a「ウエイ。 」エ w・@ャッッォ@。 エ@エィ・@ェッ「@、オイ。 エゥッョ@ッヲ@キッイォ・イウ@ゥョ@ヲゥイュウ@ッヲ@、ゥヲヲ・イ・ョエ@ウゥコ・ウ@。 ョ、@。 ョ。 ャケコ・@ィッキ@エィ・@ォョッキャ・、ァ・Mウォゥャャ 」ッューャ・ュ・ョエ。 イゥエケ@イ・ャ。 エ・ウ@エッ@ェッ「@ウ・ー。 イ。 エゥッョN@l。 イァ・イ@ヲゥイュウ@ィ。 カ・@ィゥァィ・イ@ウォゥャャ@イ・アオゥイ・ュ・ョエウ@キィゥ」ィ@ュ。 ケ@エイ。 ョウャ。 エ・@ゥョエッ 。 @「・エエ・イ@オウ・@ッヲ@エ・」ィョッャッァケ@。 ョ、@ォョッキャ・、ァ・L@。 ョ、@。 @イ・キ。 イ、@ゥョ@ェッ「@、オイ。 エゥッョ@ヲッイ@ウォゥャャ・、@キッイォ・イウN@w・@・ウエゥュ。 エ・ 、ゥウ」イ・エ・Mエゥュ・@、オイ。 エゥッョ@ュッ、・ャウ@キゥエィ@オョッ「ウ・イカ・、@ィ・エ・イッァ・ョ・ゥエケ@ヲッイ@ウ。 ューャ・ウ@ッヲ@キッイォ・イウ@ゥョ@ウュ。 ャャL@ュ・、ゥオュL@。 ョ、 ャ。 イァ・@ヲゥイュウN@tッ@ュゥエゥァ。 エ・@エィ・@ウッイエゥョァ@ッヲ@ィゥァィMウォゥャャ・、@キッイォ・イウ@ゥョエッ@ャ。 イァ・@ヲゥイュウL@エィ・@、オイ。 エゥッョ@ュッ、・ャウ@。 イ・@キ・ゥァィエ・、 キゥエィ@エィ・@ゥョ、ゥカゥ、オ。 ャ@ーイッー・ョウゥエケ@ッヲ@・ューャッケュ・ョエ@ゥョ@・。 」ィ@ウゥコ・@」。 エ・ァッイケN@oオイ@イ・ウオャエウ@ウィッキ@エィ。 エ@ウォゥャャ・、@キッイォ・イウ@。 イ・ ュッイ・@ャゥォ・ャケ@エッ@「・@・ューャッケ・、@ゥョ@ャ。 イァ・イ@ヲゥイュウL@。 ョ、@エィ。 エ@ャ。 イァ・@ヲゥイュウ@ーャ。 」・@。 @ィゥァィ・イ@ーイ・ュゥオュ@ッョ@ウォゥャャウ@ゥョ@エ・イュウ@ッヲ@ェッ「 、オイ。 エゥッョN@w・@ヲゥョ、@・カゥ、・ョ」・@ッヲ@ォョッキャ・、ァ・Mウォゥャャ@」ッューャ・ュ・ョエ。 イゥエケL@・ウー・」ゥ。 ャャケ@ゥョ@ャ。 イァ・@ヲゥイュウ@キィ・イ・@エィ・ 。 」」オュオャ。 エゥッョ@ッヲ@ヲゥイュMウー・」ゥヲゥ」@ィオュ。 ョ@」。 ーゥエ。 ャ@ーャ。 ケウ@。 @ュッイ・@ゥューッイエ。 ョエ@イッャ・@ゥョ@、・エ・イュゥョゥョァ@エィ・@ィ。 コ。 イ、@ッヲ@ェッ「 ウ・ー。 イ。 エゥッョN