Search

This study aims to determine the effect of the interaction of CTL learning strategies and motivation on student learning outcomes on living things and their environment. This research was conducted at SD Negeri 02 Rantau Selatan, Labuhanbatu Regency. The instruments used were tests and questionnaires on learning motivation. The test instruments consist of 9 items of multiple choice, 9 items of essay test and 42 items of questionnaire. All instruments have been validated. The study used a quasi-experimental method with a 2 x 2 factorial design. The data analysis technique used ANOVA at the significance level α = 0.05. The results showed that student learning outcomes on living things and their environment materials taught using the CTL strategy were higher than student learning outcomes on living things and their environment taught using the Direct model Fcount 58.508 > Ftable 4.12, there is a difference. There is a significant difference between student learning outcomes in the material of living things and their environment that has high learning motivation with students who have low learning motivation Fcount 13.396 > Ftable 4.12, there is an interaction between learning strategies and learning motivation on student learning outcomes in the material living things and their environment Fcount 23.053 > Ftable 4.12. The results of the study can be concluded that the CTL strategy is better than direct learning. The CTL strategy is better used to teach students who have high learning motivation while direct learning is better used for students who have low learning motivation.

A numerical study on thermal energy storage systems with parallel plates to collect sensible heat is conducted with porous and direct model approaches. The simulations in a two-dimensional domain are performed with COMSOL Multiphysics commercial software. For the equivalent porous medium, the permeability and effective thermal conductivity as well as the specific area, and interfacial convective coefficient are numerically evaluated, considering a thermally and hydrodynamically fully developed flow. A stack of parallel plates is the system with assigned length and height, and the external heat losses effect is considered. The analysis allows to evaluate an optimized configuration as Channels Per Length (CPL) by means of a balance in the channels between pressure drop and heat transfer. Moreover, the effect of CPL values and heat loss from the parallel plate system is estimated in terms of charging time and heating capacity. The results exhibit that as the CPL increases, the time required for the charging process decreases while heat accumulation inside the system increases significantly. In fact, at the highest CPL, charging time is 2.7 times faster and the amount of heat accumulation is approximately 20% higher in adiabatic case. It is illustrated that the amount of heat accumulation inside the system varies considerably for different heat loss values. Ultimately, this study shows that porous model is more practical and accurate to be used for higher CPL cases.

The purpose of this study is to investigate the relationship between official development assistance (ODA) on CO2 emissions based on both direct and indirect frameworks, using the annual panel data of 30 recipient countries of Korea from 1993 to 2017. It employs a modified impact, population, affluence, and technology (IPAT) model and a simultaneous equation framework for the direct model and indirect model, respectively. The empirical results suggest that ODA has both a direct and an indirect mitigation impact in the recipient countries. Compared to the direct impact, a small indirect mitigation impact of ODA on CO2 emissions is derived. However, the estimation results of the environmental Kuznets curve (EKC) equation imply that economic growth has the potential of mitigating the environmental degradation when the economic development in recipient countries of Korea reaches a certain level. Therefore, the bilateral cooperation, through ODA and the supportive policy, should make an effort to promote economic development and mitigation of environmental degradation in developing countries.

A composite specimen, made of two slabs and an interface A is heated through one of its sides S, in order to evaluate the thermal conductance H of A. The direct model consists of a system of Initial Boundary Value Problems completed by suitable transmission conditions. Thanks to the properties of multilayer diffusion, we reduce the problem to the slab between A and S only. In this case evaluating the thermal resistance of A means to identify a coefficient in a Robin boundary condition. We evaluate H numerically by means of Thin Plate Approximation.

Direct model predictive control applications for nonlinear systems can result in non-convex minimisation problems, which is additionally complicated if systems are non-minimum phase. In this paper,...

Optical ultrasound imaging uses light to both generate and detect pulse-echo ultrasound. Recently, we presented a fibre-optic optical ultrasound imaging probe comprising 64 sources and a single receiver that allowed for video-rate, freehand imaging. However, its low number of sources limited the image contrast when using Delay-and-Sum reconstruction. Here, we present an alternative image formation paradigm for optical ultrasound based on model-based inversion, where the low number of sources allows for direct (i.e., non-iterative) inversion under modest hardware requirements. The model accurately incorporates the aperture geometry, frequency-dependent source directivity, and performance variation across the aperture, thereby reducing image artefacts associated with these properties. The method achieves a 15 dB gain in image contrast compared to Delay-and-Sum, at a similar image formation time.

— This study reported the discovery and identification of behavioral syndrome of students’ indiscipline in teaching and learning process. For this purpose, researcher used qualitative approach of phenomenology. The study involved 9 subjects determined by purposive sampling for the phenomenon of indiscipline were more dominated by those subjects. Four techniques have been used to collect the data: participation-observation, in-depth interviews, field notes, and documentation. The results indicated that the behavioral syndrome of indiscipline is influenced by premature (imature) self-concept, determination of multidimensional environment, keeping and building a societal relationship in communities, as well as teachers’ attitude and behavior as a direct model. Therefore, teachers should give the exemplary cognition, affection, psychomotor, as well as should be truthful and orderly socially so that the students’ behaviour of indiscipline can be reduced to a good quality of learning. Keywords—S tudent’s behaviuor, indiscipline

This paper presents an efficient direct-model predictive control (EDMPC) technique for surface-mounted permanent-magnet synchronous generators (PMSGs) in variable-speed wind energy conversion systems. The proposed control technique is based on directly computing the reference voltage vector (VV) from the demanded currents using a deadbeat (DB) function. Then, a discrete-time integral action (DTIA) is added to this DB function to enhance the robustness of the proposed EDMPC scheme against variations of the machine parameters and to achieve a good steady-state response. The proposed DTIA is simple and easy to implement. Finally, according to the location of this reference VV, two evaluations of the quality function are only required. Accordingly, the proposed EDMPC technique with DTIA overcomes the following drawbacks of the conventional direct-model predictive control (DMPC): high calculation burden, sensitivity to parameters mismatches, and non-zero steady-state error. The performance of the proposed EDMPC technique with DTIA has been experimentally investigated and compared with that of the EDMPC with time delay control approach and with the performance of the convention DMPC using a $\text{14.5}\,\text{kW}$ PMSG.

This study indicates important factors in related to Chinese international students who graduated from Malaysia have better ‘employability’ upon returning to China employment market. Total survey of 160 samples collected from the target group, the Chinese graduates who study in Malaysia and now working in China. The direct model result found that educational and learning activities (H1) and soft skills (H2) have a significant impact on graduate’s employability. Moreover, the findings also found the mediation role of graduate’s English proficiency scored at 0.1595 (H3) and 0.1293 (H4) between educational and learning activities, soft skills and employability. The findings enable education service providers and policy-makers identify more competitive variables in enhancing graduate employability in China market. Additionally, the result of this study also justified the important of English proficiency toward the employability of Chinese graduates in China.

Nine-Switch Inverter (NSI) is composed of two conventional inverters with three common switches. Two sets of three phase ac loads can be connected to the outputs of NSI and independently controlled without any undesirable interaction. In conventional multi-step Model Predictive Control (MPC) of a nine-switch inverter, the prediction steps of both load stages must be equal. Unfortunately, this results in losing the freedom of selecting independent prediction horizon for individual loads. To overcome this problem, a novel asymmetrical multi-step direct model predictive control method is presented in this paper. The proposed method finds two independent optimum solutions for each load to match with their utilization profile. It is assumed that two individual loads are controlled by two separate virtual inverters, and two separate model predictive control problems with their own prediction steps are solved to identify optimum control actions. The control calculations are performed in a Cyclone IV Field Programmable Gate Array (FPGA) by using a pipelined architecture. The system stability is analyzed using Lyapunov stability method. To highlight the effectiveness of introduced strategy, mathematical proof for controlling two separate loads with an asymmetrical prediction step is validated in experimentally.

A discrete direct (DD) model calibration and uncertainty propagation approach is explained and demonstrated on a 4-parameter Johnson-Cook (J-C) strain-rate dependent material strength model for an aluminum alloy. The methodology's performance is characterized in many trials involving four random realizations of strain-rate dependent material-test data curves per trial, drawn from a large synthetic population. The J-C model is calibrated to particular combinations of the data curves to obtain calibration parameter sets which are then propagated to “Can Crush” structural model predictions to produce samples of predicted response variability. These are processed with appropriate sparse-sample uncertainty quantification (UQ) methods to estimate various statistics of response with an appropriate level of conservatism. This is tested on 16 output quantities (von Mises stresses and equivalent plastic strains) and it is shown that important statistics of the true variabilities of the 16 quantities are bounded with a high success rate that is reasonably predictable and controllable. The DD approach has several advantages over other calibration-UQ approaches like Bayesian inference for capturing and utilizing the information obtained from typically small numbers of replicate experiments in model calibration situations—especially when sparse replicate functional data are involved like force–displacement curves from material tests. The DD methodology is straightforward and efficient for calibration and propagation problems involving aleatory and epistemic uncertainties in calibration experiments, models, and procedures.

International audience; Model-checking intends to verify whether a property is satisfied by a model, or not. Model-checking of high-level models, e.g. SysML models, usually first requires a model transformation to a low level formal specification. The present papers proposes a new model-checker that can be applied (almost) directly to the SysML model. The paper first explains how this model-checker works. Then, we explain how it can efficiently check CTL-like properties. Finally, the paper discusses the performance of this model-checker integrated in the TTool framework.

Spectral CT is an emerging modality that permits material decomposition and density estimation through the use of energy-dependent information in measurements. Direct model-based material decomposition algorithms have been developed that incorporate statistical models and advanced regularization schemes to improve density estimates and lower exposure requirements. However, understanding and control of the relationship between regularization and image properties is complex with interactions between spectral channels and material bases. In particular, regularization in one material basis can affect the image properties of other material bases, and vice versa. In this work, we derived a closed-form set of local impulse responses for the solutions to a general, regularized, model-based material decomposition (MBMD) objective. These predictors quantify both the spatial resolution in each material image as well as the influence of regularization of one material basis on other material images. This information can be used prospectively to tune regularization parameters for specific imaging goals.

Data efficient voice cloning aims at synthesizing target speaker's voice with only a few enrollment samples at hand. To this end, speaker adaptation and speaker encoding are two typical methods based on base model trained from multiple speakers. The former uses a small set of target speaker data to transfer the multi-speaker model to target speaker's voice through direct model update, while in the latter, only a few seconds of target speaker's audio directly goes through an extra speaker encoding model along with the multi-speaker model to synthesize target speaker's voice without model update. Nevertheless, the two methods need clean target speaker data. However, the samples provided by user may inevitably contain acoustic noise in real applications. It's still challenging to generating target voice with noisy data. In this paper, we study the data efficient voice cloning problem from noisy samples under the sequence-to-sequence based TTS paradigm. Specifically, we introduce domain adversarial training (DAT) to speaker adaptation and speaker encoding, which aims to disentangle noise from speech-noise mixture. Experiments show that for both speaker adaptation and encoding, the proposed approaches can consistently synthesize clean speech from noisy speaker samples, apparently outperforming the method adopting state-of-the-art speech enhancement module., Comment: Accepted to INTERSPEECH 2020

In this paper, a flux linkage-based direct model predictive current control approach is presented for small permanent magnet synchronous motor (PMSM) drives. The method aims to minimize the current ripples at steady state by deciding on the optimal switching instant, while exhibiting fast dynamic behavior during transients. To this end, the future trajectory of the stator current is not computed based on the machine inductances or inductance look-up tables, but on the changes of the magnetic flux linkage by utilizing flux linkage maps. As shown, the proposed method can be particularly advantageous for electric drives with a noticeable nonlinearity in terms of saturation and/or cross-coupling effects since it allows for a significantly increased prediction accuracy, which leads to an improved steady-state performance as indicated by the reduced current distortions. acceptedVersion

Fortunately, extreme temperatures reaching 50 &deg, C are not common on our planet. The capability of the consortium for small-scale modelling regional climate model (COSMO-CLM), with 0.44&deg, resolution, to project future trends of an extremely hot environment with direct model output (DMO) is questioned. The temperature distribution of COSMO-CLM output driven by reanalysis and RCP4.5 scenario in southern Iraq was remarkably good, with a slight temperature overestimation, compared to the overlapping observations from Basra airport. An attempt to enhance the DMO with a statistical downscaling method did not improve the results. The COSMO-CLM projection indicates that a very sharp increase in the number of consecutive hours and days with the temperature reaching 50 &deg, C or higher will occur. During 1951&ndash, 1980, consecutive hours and days reaching 50 &deg, C were rare events. By the end of the century, the projected climate in southern Iraq contains up to 13 consecutive hours and 21 consecutive days reaching 50 &deg, C or higher. As the average projected temperature will increase by ~2 &deg, C compared to the recent climate, new records may be expected. However, the major climate change feature is the increase in consecutive hours and days of very high temperatures. These findings require adaptation measures to support future habitation of the region.

Next-generation sequencing (NGS) represents a powerful tool to unravel the genetic make-up of the HIV reservoir, but limited data exist on its use in vitro. Moreover, most NGS studies do not separate integrated from unintegrated DNA, even though selection pressures on these two forms should be distinct. We reasoned we could use NGS to compare the infection of resting and activated CD4 T cells in vitro to address how the metabolic state affects reservoir formation and dynamics. To address these questions, we obtained HIV sequences 2, 4, and 8 days after NL4-3 infection of metabolically activated and quiescent CD4 T cells (cultured with 2 ng/ml interleukin-7). We compared the composition of integrated and total HIV DNA by isolating integrated HIV DNA using pulsed-field electrophoresis before performing sequencing. After a single-round infection, the majority of integrated HIV DNA was intact in both resting and activated T cells. The decay of integrated intact proviruses was rapid and similar in both quiescent and activated T cells. Defective forms accumulated relative to intact ones analogously to what is observed in vivo. Massively deleted viral sequences formed more frequently in resting cells, likely due to lower deoxynucleoside triphosphate (dNTP) levels and the presence of multiple restriction factors. To our surprise, the majority of these deleted sequences did not integrate into the human genome. The use of NGS to study reservoir dynamics in vitro provides a model that recapitulates important aspects of reservoir dynamics. Moreover, separating integrated from unintegrated HIV DNA is important in some clinical settings to properly study selection pressures. IMPORTANCE The major implication of our work is that the decay of intact proviruses in vitro is extremely rapid, perhaps as a result of enhanced expression. Gaining a better understanding of why intact proviruses decay faster in vitro might help the field identify strategies to purge the reservoir in vivo. When used wisely, in vitro models are a powerful tool to study the selective pressures shaping the viral landscape. Our finding that massively deleted sequences rarely succeed in integrating has several ramifications. It demonstrates that the total HIV DNA can differ substantially in character from the integrated HIV DNA under certain circumstances. The presence of unintegrated HIV DNA has the potential to obscure selection pressures and confound the interpretation of clinical studies, especially in the case of trials involving treatment interruptions.

The moisture diffusivity of food is a very important physical parameter to model baking processes. Unfortunately, specific moisture diffusivity values are not easily found in literature, especially measured or calculated during the baking processes. The main methods used to estimate the moisture diffusivity are based on the second Fick's law, but there are significant differences in the way of applying these laws. The aim of this work is to estimate the effective moisture diffusivity in baking of a small flat cake by using the inversion of a numerical model based on the coupling of heat and mass transfer. The temperature and moisture dependency of the diffusivity is evaluated. Results are compared with those obtained by using a fitting method. The inverse method allows to estimate the effective moisture diffusivity close to those reported in literature for similar bakery products (constant values). The impact of the moisture concentration appears to be very restricted and it tends to decrease with increasing the oven temperature. Subsequently, the obtained effective diffusivity was implemented on a direct Finite Element (FE) model simulating a whole cake for different baking temperatures. The direct model validation (mean moisture content and temperature) shows determination coefficients ranging from 0.921 to 0.996 confirming the robustness of the diffusivity parameters obtained by the inverse method.

International audience; In this article, a multilayer artificial neural network (ANN) identification model is developed to simultaneously identify the thermal conductivity and the effective absorption coefficient of semitransparent materials from flash-type experimental measurements. Firstly, the ANN is trained by means of data generated by a 2-D axisymmetric heat transfer model whose radiative part is treated via the P1 approximation. A sensitivity study is then used to prove the theoretical feasibility of the identification strategy. Several training data distributions (uniform or Gaussian types) are tested on synthetic data, and on noisy ones for checking the robustness. Finally, the efficiency of this estimation approach is investigated using experimental data obtained by flash method on a PMMA sample. The estimated thermal conductivity and the effective absorption coefficient are compared with values obtained from the literature and othermeasurements.

In this paper a 2D pollution water model with an improved numerical method is considered. In order to reduce the approximation errors of the numerical scheme, a new approximation method is introduced to calculate the concentration flux between two cells (j-cell and l-cell) in the direction of the normal vector \(\vec {n}\) orthogonal to their common side. The advantage of this approximation is that the concentration flux \({\partial C}/{\partial \vec {n}}\) from j-cell to l-cell and the other one from l-cell to j-cell are only different by their signs but not by their absolute values. Therefore, the errors of concentration simulated by this scheme are reduced and less than those obtained by a normal differential implicit discretization. This improvement of the scheme will be illustrated by two test cases. In the numerical tests we will display the difference between the exact solution, the classical scheme and the proposed scheme. Numerical results demonstrate the improvement of this approach.

The 2 m-temperature anomalies from the reforecasts of the CNR-ISAC and ECMWF monthly prediction systems have been combined in a multimodel super-ensemble. Tercile probability predictions obtained from the multimodel have been constructed using direct model outputs (DMO) and model output statistics (MOS), like logistic and nonhomogeneous Gaussian regression, for the 1990–2010 winter seasons. Verification with ERA-Interim reanalyses indicates that logistic regression gives the best results in terms of ranked probability skill scores (RPSS) and reliability diagrams for low–medium forecast probabilities. Also, it is argued that the logistic regression would not yield further improvements if a larger dataset was used.