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Micro-credentials are increasingly being adopted across a variety of industries and countries, including the kindergarten through grade 12 education system in the United States, as a way to identify workers with specific skills, knowledge, and competencies. This report presents the results of a study conducted by RAND researchers who investigated the implementation and impact of teacher micro-credentials intended to improve high school science, technology, engineering, and math teaching and learning in Louisiana. The creation, design, and implementation of micro-credentials was undertaken through a collaboration between the Louisiana Department of Education, Louisiana State University, and BloomBoard. RAND researchers designed and executed a randomized controlled trial of the effectiveness of micro-credentials and an implementation study. The study indicated that teachers' engagement with micro-credentials was relatively low and that micro-credentials did not lead to an increase in student achievement. That said, participating teachers reported that the micro-credentials were well aligned with their courses and supported their teaching practice. Study implications include that micro-credential providers and stakeholders should clearly communicate the value proposition and time requirements of micro-credentials to teachers, as well as provide ample peer and asynchronous supports to teachers for undertaking them.

Micro-credentials are increasingly being adopted across a variety of industries and countries, including the kindergarten through grade 12 education system in the United States, as a way to identify workers with specific skills, knowledge, and competencies. This report presents the results of a study conducted by RAND researchers who investigated the implementation and impact of teacher micro-credentials intended to improve high school science, technology, engineering, and math teaching and learning in Louisiana. The creation, design, and implementation of micro-credentials was undertaken through a collaboration between the Louisiana Department of Education, Louisiana State University, and BloomBoard. RAND researchers designed and executed a randomized controlled trial of the effectiveness of micro-credentials and an implementation study. The study indicated that teachers' engagement with micro-credentials was relatively low and that micro-credentials did not lead to an increase in student achievement. That said, participating teachers reported that the micro-credentials were well aligned with their courses and supported their teaching practice. Study implications include that micro-credential providers and stakeholders should clearly communicate the value proposition and time requirements of micro-credentials to teachers, as well as provide ample peer and asynchronous supports to teachers for undertaking them.

Predicting the future motion of observed vehicles is a crucial enabler for safe autonomous driving. The field of motion prediction has seen large progress recently with state-of-the-Art (sotA) models achieving impressive results on large-scale public benchmarks. However, recent work revealed that learning-based methods are prone to predict off-road trajectories in challenging scenarios. These can be created by perturbing existing scenarios with additional turns in front of the target vehicle while the motion history is left unchanged. We argue that this indicates that SotA models do not consider the map information sufficiently and demonstrate how this can be solved by representing model inputs and outputs in a Frenet frame defined by lane centreline sequences. To this end, we present a general wrapper that leverages a Frenet representation of the scene, and that can be applied to SotA models without changing their architecture. We demonstrate the effectiveness of this approach in a comprehensive benchmark using two SotA motion prediction models. Our experiments show that this reduces the off-road rate on challenging scenarios by more than 90% without sacrificing average performance.

In this study, the four joint time-frequency (TF) moments; mean, variance, skewness, and kurtosis of TF matrix obtained from Multivariate Synchrosqueezing Transform (MSST) are proposed as features for hand gesture recognition. A publicly available dataset containing surface EMG (sEMG) signals of 40 subjects performing 10 hand gestures, was used. The distinguishing power of the feature variables for the tested gestures was evaluated according to their p values obtained from the Kruskal-Wallis (KW) test. It is concluded that the mean, variance, skewness, and kurtosis of TF matrices can be candidate feature sets for the recognition of hand gestures., Comment: Conference Paper, 5 pages, Translated Title (TR): El Hareketi Siniflandirmasi icin Cok-Degiskenli Senkrosikistirma Donusumune Dayali Zaman-Frekans Ozniteliklerinin Istatistiksel Analizi Proceedings: https://www.tipcih.com/books/ICMD2022_Proceedings-DRAFT.pdf Website: https://www.tipcih.com/

Since the advent of chatbots in the commercial sector, they have been widely employed in the customer service department. Typically, these commercial chatbots are retrieval-based, so they are unable to respond to queries absent in the provided dataset. On the contrary, generative chatbots try to create the most appropriate response, but are mostly unable to create a smooth flow in the customer-bot dialog. Since the client has few options left for continuing after receiving a response, the dialog becomes short. Through our work, we try to maximize the intelligence of a simple conversational agent so it can answer unseen queries, and generate follow-up questions or remarks. We have built a chatbot for a jewelry shop that finds the underlying objective of the customer's query by finding similarity of the input to patterns in the corpus. Our system features an audio input interface for clients, so they may speak to it in natural language. After converting the audio to text, we trained the model to extract the intent of the query, to find an appropriate response and to speak to the client in a natural human voice. To gauge the system's performance, we used performance metrics such as Recall, Precision and F1 score.

Instruction plays a critical role in student success. However, most studies of teachers' effects on student learning focus on face-to-face settings. Some aspects of online courses, such as the choice of synchronous or asynchronous instruction and the course structure, might reduce teachers' influence on their students. This study of an online high school biology course offered by Florida Virtual School examined the variation in students' course segment (similar to semester) completion rates, end-of-segment exam scores, and time to segment completion that is attributable to the influence of teachers. Students' scores on the end-of-segment exam varied only slightly across teachers, while completion rates and time to completion varied more. [For the appendixes, see ED609865; for the study snapshot; see ED609866.]

In this report, the authors provide a preliminary look at the Improving Pre-Engineering and Computer Science Education Through Micro-Credentialing project to develop and implement micro-credentials as a means of providing scalable, competency-based certification of science, technology, engineering, and mathematics (STEM) teaching skills in Louisiana. For this project, the RAND Corporation partnered with the Louisiana Department of Education, Louisiana State University (LSU), and BloomBoard, Inc. (BBI), to develop 18 micro-credentials giving teachers the opportunity to demonstrate competency in STEM instructional topics related to pre-engineering, digital design and emergent media, and computer science. The ultimate goal of this project is to improve teaching and learning of science, technology, engineering, and mathematics (STEM) courses and to expand this micro-credential model across Louisiana. The authors provide a comprehensive overview of the development of these micro-credentials (beginning in fall 2019) and the first year of the implementation of the micro-credentials with participating teachers in the 2021-2022 school year, as well as lessons learned to support those who are developing or implementing micro-credentials in other settings.

The dynamics of waveguide-QED systems involving coherent time-delayed feedback give rise to a hierarchy of multi-time correlations within the Heisenberg picture due to the induced non-Markovianity. We propose to perform a projection onto a complete set of states in the Hilbert space to decompose the multi-time correlations into single-time matrix elements. To illustrate the procedure, we consider the paradigmatic example of a two-level system that couples to a semi-infinite waveguide and interacts with quantum light pulses. Our approach complements the range of available methods as it allows calculating the dynamics under the inclusion of additional dissipation channels in a numerically exact and efficient manner for multiphoton pulses of arbitrary shape where memory requirements are known in advance.

Multi-modal magnetic resonance imaging (MRI) is a crucial method for analyzing the human brain. It is usually used for diagnosing diseases and for making valuable decisions regarding the treatments - for instance, checking for gliomas in the human brain. With varying degrees of severity and detection, properly diagnosing gliomas is one of the most daunting and significant analysis tasks in modern-day medicine. Our primary focus is on working with different approaches to perform the segmentation of brain tumors in multimodal MRI scans. Now, the quantity, variability of the data used for training has always been considered to be crucial for developing excellent models. Hence, we also want to experiment with Knowledge Distillation techniques.

The visibility of the two-photon interference in the Franson interferometer serves as a measure of the energy-time entanglement of the photons. We propose to control the visibility of the interference in the second-order coherence function by implementing a coherent time-delayed feedback mechanism. Simulating the non-Markovian dynamics within the matrix product state framework, we find that the visibility for two photons emitted from a three-level system (3LS) in ladder configuration can be enhanced significantly for a wide range of parameters by slowing down the decay of the upper level of the 3LS.

Within the matrix product state framework, we study the non-Markovian feedback dynamics of a two-level system interacting with the electromagnetic field inside a semi-infinite waveguide where the excitation of an atom-photon bound state is possible. Taking the steady-state excitation of the emitter as a figure of merit, we compare the trapped excitation for an initially excited quantum emitter and an emitter prepared via quantized pulses containing up to four photons. In the latter case, we find that for large feedback delay times, multi-photon pulses can yield a significantly higher steady-state excitation than possible with an initially excited emitter since the stimulated emission process can enhance the trapping probability in comparison to the spontaneous decay of an initially excited emitter.

A semiconductor quantum dot (QD) is an attractive resource to generate polarization-entangled photon pairs. We study the excitonic spin precession (flip-flop) in a family of QDs with different excitonic fine-structure splitting (FSS) and its impact on the entanglement of photons generated from the excitonic-biexcitonic radiative cascade. Our results reveal that coherent processes leave the time post-selected entanglement of QDs with finite FSS unaffected while changing the eigenstates of the system. The flip-flop's precession is observed via quantum tomography through anomalous oscillations of the coincidences in the rectilinear basis. A theoretical model is constructed with the inclusion of an excitonic flip-flop rate and is compared with a two-photon quantum tomography measurement on a QD exhibiting the spin flip-flop mechanism. A generalization of the theoretical model allows estimating the degree of entanglement as a function of the FSS and the spin-flip rate. For a finite temporal resolution, the negativity is found to be oscillating with respect to both the FSS and the spin-flip rate. This oscillatory behavior disappears for perfect temporal resolution and maximal entanglement is retrieved despite the flip-flop process.

Coherent time-delayed feedback allows the control of a quantum system and its partial stabilization against noise and decoherence. The crucial and externally accessible parameters in such control setups are the round-trip-induced delay time $\tau$ and the frequencies $\omega$ of the involved optical transitions which are typically controllable via global parameters like temperature, bias or strain. They influence the dynamics via the amplitude and the phase $\phi = \omega \tau$ of the feedback signal. These quantities are, however, not independent. Here, we propose to control the feedback phase via a microwave pump field. Using the example of a $\Lambda$-type three-level system, we show that the Rabi frequency of the pump field induces phase shifts on demand and therefore increases the applicability of coherent quantum feedback control protocols.

This work investigates segmentation approaches for sentiment analysis on informal short texts in Turkish. The two building blocks of the proposed work are segmentation and deep neural network model. Segmentation focuses on preprocessing of text with different methods. These methods are grouped in four: morphological, sub-word, tokenization, and hybrid approaches. We analyzed several variants for each of these four methods. The second stage focuses on evaluation of the neural model for sentiment analysis. The performance of each segmentation method is evaluated under Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model proposed in the literature for sentiment classification., Comment: 39 pages

A variety of factors have converged in the last decade to focus attention on the need for more rigorous designs of professional development (PD). Teacher development is increasingly viewed as one of the primary levers for improving teaching quality and ultimately student achievement. The authors present data from the Teacher Knowledge Assessment System (TKAS), which is designed to administer the Learning Mathematics for Teaching (LMT) measures. TKAS is being widely adopted in the evaluation of PD programs with over 500 separate program administrations and 16,000 teachers representing every major region in the country. The study findings provided potential guidance for the design of studies using teacher knowledge as an outcome measure. Also, the results provide context relevant guidelines (e.g., test outcome, characteristics of teachers, school or program) that researchers may use individually or in combination to design studies and/or assess the practical impact of teacher PD interventions.

Glasses of Li2O.2SiO2 (LS2), and LS2 doped with 0.001wt% platinum (LS2 + 0.001 wt% Pt) compositions were melted, cooled and reheated at controlled rates while levitated (containerless) inside an Electrostatic Levitator (ESL) furnace at the NASA Marshall Space Flight Center, Huntsville, AL. The experiments were conducted in vacuum (approximately 10(exp -5) Pa) using spherical, 2.5 to 3 millimeter diameter, glass samples. The measured critical cooling rate for glass formation, R(sub c), for the LS2 and LS2+0.001 wt% Pt glasses processed at ESL were 14 plus or minus 2 Celsius per minute and 130 plus or minus 5 Celsius per minute, respectively. The values of R(sub c), for the same LS2 and LS2 + 0.001 wt% Pt glasses processed in a container were 62 plus or minus 3 Celsius per minute and 162 plus or minus 5 Celsius per minute, respectively. The effective activation energy for crystallization, E, for this LS2 glass processed without a container at ESL, 392 plus or minus 15 kiloJoules per mole, was higher than that, 270 plus or minus 15 kiloJoules per mole, for an identical glass processed in a container. These results suggest that the glass formation tendency for a containerless LS2 melt is significantly increased compared to an identical melt in contact with a container. The absence of heterogeneous nucleation sites that are inherently present in all melts held in containers, and or a change in the surface composition due to evaporation of Li2O during processing at ESL are likely reasons for the increased glass forming tendency of this containerless LS2 melt.

Numerical simulation of compressible viscous flow fields is performed for a transonic transport configuration. A single structured grid system is constructed using analytical transformations such as conformal mapping, shearing/twisting/rotating/clustering/stretching transformations. The Reynolds-averaged, thin-layer Navier-Stokes equations are solved on a supercomputer, FACOM VP-400, using the LU-ADI factorization method.

The slightly supersonic viscous flow about the space-plane under development at the National Aerospace Laboratory (NAL) in Japan was simulated numerically using the LU-ADI algorithm. The wind-tunnel testing for the same plane also was conducted with the computations in parallel. The main purpose of the simulation is to capture the phenomena which have a great deal of influence to the aerodynamic force and efficiency but is difficult to capture by experiments. It includes more accurate representation of vortical flows with high angles of attack of an aircraft. The space-plane shape geometry simulated is the simplified model of the real space-plane, which is a combination of a flat and slender body and a double-delta type wing. The comparison between experimental results and numerical ones will be done in the near future. It could be said that numerical results show the qualitatively reliable phenomena.