Tracking Procedure Research Articles

Tracking Procedures and Criteria and the SES Bias in Teacher Track Recommendations

The allocation of students to ability tracks is often based on teacher recommendations. These recommendations tend to be biased in favor of students from higher socioeconomic status (SES) backgrounds. While tracking procedures and criteria have been proposed to play a role herein, empirical research is lacking. Using a survey experiment and information from 221 teachers in 69 Dutch schools, I find that teachers in the same school vary in their interpretation of their school’s procedure and (relatedly) their own tracking criteria. Teachers who perceive the school procedure to put more weight on students’ home environment, and/or (relatedly) put more weight on this themselves, show a stronger SES bias in track recommendations in the survey experiment.

Development of a Storm-Tracking Algorithm for the Analysis of Radar Rainfall Patterns in Athens, Greece

This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the tracking procedure on the basis of their geometrical characteristics and the distance within the weather radar image. A sensitivity analysis was performed to evaluate the preferable thresholds for each case and test the algorithm’s ability to perform in different time step resolutions. Following this, we applied the algorithm to 54 rainfall events recorded by the National Technical University X-Band weather radar, the rainscanner system, from 2018 to 2023 in the Attica region of Greece. Testing of the algorithm demonstrated its efficiency in tracking storm cells over various time intervals and reflecting changes such as merging or dissipation. The results reveal the predominant southwest-to-east storm directions in 40% of cases examined, followed by northwest-to-east and south-to-north patterns. Additionally, stratiform storms showed slower north-to-west trajectories, while convective storms exhibited faster west-to-east movement. These findings provide valuable insights into storm behavior in Athens and highlight the algorithm’s potential for integration into nowcasting systems, particularly for flood early warning systems.

Stereological Investigation of the Effects of Hypericum Perforatum L. Plant on Skin Tissue in Second Degree Burns in Rats

The aim of this study was to examine stereologically the effect of Hypericum perforatum L. oil on skin injuries resulting from burns. Experimental groups were selected 18 healthy rats with an average weight of 250-300 grams as material. The rats were divided into 3 groups: control, burn and burn+treatment, with 6 in each group. In the control group, second-degree burns were created and the rats were perfused. Control group rats were kept in formaldehyde for a week. Burns were applied to the burn and burn+treatment groups with 100ºC water. 4gr/kg of Hypericum perforatum L. oil was given via gavage to the burn+treatment group only for 21 days. The burn group was not intervened. At the end of the process, rats in both the burn and burn+treatment groups were perfused. The skin of the animals, which were kept in formaldehyde for a week, and where second-degree burns occurred were dissected. After tissue tracking and tissue embedding procedures for all animals in the group, 5µm thick sections were taken to obtain 8-10 sections at a ratio of 1/75. Volume values were calculated using stereological methods from the sections photographed with an x4 objective. Calculations were made using the Shtereom I program in accordance with the Cavalieri Principle. Non-parametric tests and Kruskal Wallis test were used in statistical evaluations. When the results were analyzed, it was observed that the administration of Hypericum Perforatum L. oil by gavage had an effect on the healing process of second degree burn wounds.

The Audible Contrast Threshold (ACT) test: A clinical spectro-temporal modulation detection test

Over the last decade, multiple studies have shown that hearing-impaired listeners’ speech-in-noise reception ability, measured with audibility compensation, is closely associated with performance in spectro-temporal modulation (STM) detection tests. STM tests thus have the potential to provide highly relevant beyond-the-audiogram information in the clinic, but the available STM tests have not been optimized for clinical use in terms of test duration, required equipment, and procedural standardization. The present study introduces a quick-and-simple clinically viable STM test, named the Audible Contrast Threshold (ACT™) test. First, an experimenter-controlled STM measurement paradigm was developed, in which the patient is presented bilaterally with a continuous audibility-corrected noise via headphones and asked to press a pushbutton whenever they hear an STM target sound in the noise. The patient's threshold is established using a Hughson-Westlake tracking procedure with a three-out-of-five criterion and then refined by post-processing the collected data using a logistic function. Different stimulation paradigms were tested in 28 hearing-impaired participants and compared to data previously measured in the same participants with an established STM test paradigm. The best stimulation paradigm showed excellent test-retest reliability and good agreement with the established laboratory version. Second, the best stimulation paradigm with 1-second noise “waves” (windowed noise) was chosen, further optimized with respect to step size and logistic-function fitting, and tested in a population of 25 young normal-hearing participants using various types of transducers to obtain normative data. Based on these normative data, the “normalized Contrast Level” (in dB nCL) scale was defined, where 0 ± 4 dB nCL corresponds to normal performance and elevated dB nCL values indicate the degree of audible contrast loss. Overall, the results of the present study suggest that the ACT test may be considered a reliable, quick-and-simple (and thus clinically viable) test of STM sensitivity. The ACT can be measured directly after the audiogram using the same set up, adding only a few minutes to the process.

Adaptive topology optimization for enhancing resistance to brittle fracture using the phase field model

Computational cost is one of the challenges in the field of fracture resistance topology optimization. An efficient topology optimization approach is proposed for enhancing resistance to structural fracture based on the adaptive isogeometric–meshfree method. The mesh can be adaptively refined in the computational and design domains simultaneously to capture the fracture and structural boundary delicately, which significantly reduces the degree of freedom and improves the efficiency of the topology optimization problems related to crack propagation. The proposed approach naturally inherits the advantages of both the computer-aided design and continuity of the higher-order basis functions, where the geometry and the analysis models in the process of topology optimization are integrated. The problem is formulated to maximize the absorbed energy throughout the crack process using the solid isotropic material with penalization method under volume constraints. The phase field method is used for modeling crack propagation, thereby eliminating the need of an explicit representation of the crack surface and complex tracking procedures, while a delicate mesh is still required. With this approach, the external work required during the fracture process is maximized, and the crack growth is delayed remarkably. Several representative examples are demonstrated to verify the effectiveness of the present approach in fracture-resistance-enhanced topology optimization, and the computational cost shows remarkable improvement.

Impact evaluation of development plans in the Egyptian harbors on morphological changes using numerical simulation (case study: Damietta harbor, northeastern coast of Egypt)

The Egyptian government is grappling with the challenge of sedimentation in Damietta Harbor (DH), leading to expensive and recurring dredging operations for safe vessel navigation. This research examined the changes in the region's coastline, both before and after the port was established between 1977 and 1995. The impact of the government's policy to halt backfilling in the navigation lane on adjacent beaches until 2023 was also assessed using remote sensing (RS) and the Digital Shoreline Analysis System (DSAS) program, revealing varying yearly accretion and erosion rates. Following a shoreline movement tracking procedure, in the period from 1985 to 2023, the total areas undergoing erosion and accretion amounted to −1.36 km2 and +2.21 km2, respectively.To address the issue, the research team developed scenarios reflecting regional realities and conducted a numerical simulation using the Coastal Modeling System (CMS). Morphological alterations in the approach channel and pre- and post-port regions were monitored to assess the scenarios. The study also explored how deepening the navigation channel affected the annual sediment volume. Results showed that Scenario 5, involving breakwaters extension and the new western breakwater (NWBW), effectively controlled sediment. However, sedimentation increased with the deepening of the navigation channel. Scenario 7, with a 19 m deepening, exhibited slightly higher sediment volume by 21.75% but stood out for its capacity to handle large vessels. Additionally, the sedimentation in the navigation channel experienced a notable 72.1% decrease in Scenario 8, which portrays the anticipated final state of DH compared to the benchmark case.The study noted morphological changes from planned coastal constructions on the eastern side, including detached breakwaters (DBW) and Y-groins (Y-gs). Despite significant development costs, these structures were deemed insufficient to stabilize the shoreline. In summary, the research highlights the complexity of addressing sedimentation in DH, emphasizing the need for nuanced approaches in coastal management, and considering the consequences of deepening navigation channels.

Assessing The Potential Of PIV Data To Resolve Hidden Frequency Scales

The present work investigates the performance of an advection-based flow reconstruction model to increase the temporal resolution of PIV measurements recorded in a turbulent, planar jet. Using a semi-Lagrangian technique in combination with Rapid Distortion Theory, a modified trajectory tracking procedure is implemented. The method introduces a specification for a two-dimensional convective velocity based on the least squares minimization of the linearized advection equation, in contrast to the previously introduced one-dimensional mean velocity profile outlined in Vocke et al. (2023). The new implementation is based on local flow measurements, making it well-suited towards streamwise heterogeneity and spatially developing flows. With this, the flow at some unknown time can be estimated from the know flow measurements at the forward and backward time. Spectral analysis illustrates the model's proficiency in recovering spatiotemporal information far exceeding the Nyquist frequency, with spectral reconstruction errors of less than 5% for the most extreme case. It is demonstrated that the spectral content can be estimated at least two orders of magnitude beyond the sampling frequency of the original recording. Improved performance compared to alternative methods is demonstrated with only minor impact on computational time. This indicates the approach may be used as a tool for experimental researchers a) having no access to a high-speed PIV or b) with high-speed PIV to increase the spectral resolution even further.

Dynamic SNR, Spectral Efficiency, and Rate Characterization in 5G/6G mmWave/sub-THz Systems with Macro- and Micro-Mobilities

The performance of 5G/6G cellular systems operating in millimeter wave (mmWave, 30–100 GHz) and sub-terahertz (sub-THz, 100–300 GHz) bands is conventionally assessed by utilizing the static distributions of user locations. The rationale is that the use of the beam tracking procedure allows for keeping the beams of a base station (BS) and user equipment (UE) aligned at all times. However, by introducing 3GPP Reduced Capability (RedCap) UEs utilizing the Radio Resource Management (RRM) Relaxation procedure, this may no longer be the case, as UEs are allowed to skip synchronization signal blocks (SSB) to improve energy efficiency. Thus, to characterize the performance of such UEs, methods explicitly accounting for UE mobility are needed. In this paper, we will utilize the tools of the stochastic geometry and random walk theory to derive signal-to-noise ratio (SNR), spectral efficiency, and rate as an explicit function of time by accounting for mmWave/sub-THZ specifics, including realistic directional antenna radiation patterns and micro- and macro-mobilities causing dynamic antenna misalignment. Different from other studies in the field that consider time-averaged performance measures, these metrics are obtained as an explicit function of time. Our numerical results illustrate that the macro-mobility specifies the overall trend of the time-dependent spectral efficiency, while local dynamics at 1–3 s scales are mainly governed by micro-mobility. The difference between spectral efficiency corresponding to perfectly synchronized UE and BS antennas and time-dependent spectral efficiency in a completely desynchronized system is rather negligible for realistic cell coverages and stays within approximately 5–10% for a wide range of system parameters. These conclusions are not affected by the utilized antenna array at the BS side. However, accounting for realistic radiation patterns is critical for a time-dependent performance analysis of 5G/6G mmWave/sub-THz systems.

Artificial intelligence-assisted ultrasound-guided regional anaesthesia: An explorative scoping review.

The present study reviews the available scientific literature on artificial intelligence (AI)-assisted ultrasound-guided regional anaesthesia (UGRA) and evaluates the reported intraprocedural parameters and postprocedural outcomes. A literature search was performed on 19 September2023, using the Medline, EMBASE, CINAHL, Cochrane Library and Google Scholar databases by experts in electronic searching. All study designs were considered with no restrictions regarding patient characteristics or cohort size. Outcomes assessed included the accuracy of AI-model tracking, success at the first attempt, differences in outcomes between AI-assisted and unassisted UGRA, operator feedbackand case-report data. A joint adaptive median binary pattern (JAMBP) has been applied to improve the tracking procedure, while a particle filter (PF) is involved in feature extraction. JAMBP combined with PF was most accurate on all images for landmark identification, with accuracy scores of 0.83, 0.93and 0.93 on original, preprocessedand filtered images, respectively. Evaluation of first-attempt success of spinal needle insertion revealed first-attempt success in most patients. When comparing AI application versus UGRA alone, a significant statistical difference (p < 0.05) was found for correct block view, correct structure identificationand decrease in mean injection time, needle track adjustments and bone encountersin favour of having AI assistance. Assessment of operator feedback revealed that expert and nonexpert operator feedback was overall positive. AI appears promising to enhance UGRA as well as to positively influence operator training. AI application of UGRA may improve the identification of anatomical structures and provide guidance for needle placement, reducing the risk of complications and improving patient outcomes. Level IV.

Mindfulness and Emotional Intelligence: A Study on Millennials on Hospitality

In software development, dependability and quality are critical. A Bug Tracking System (BTS) designed specifically for large-scale software projects is introduced in this significant project with the goal of streamlining bug tracking, reporting, detection, and resolution. The system provides secure authentication, a backend database that is reliable, and an easy-to-use web interface. Using cutting-edge web technologies, it offers critical features including automated notifications, progress tracking, severity assignment, and thorough bug reporting together with user-friendly interfaces for a range of user roles. Tools for data visualization help identify defect patterns and monitor projects. The project follows best practices recommended by the industry for requirements analysis, design, implementation, testing, and deployment, and it solicits ongoing input. The result is a thorough BTS that addresses defect management difficulties. Thorough testing and assessment in comparison to standards confirms its efficacy. This approach could have a big impact on software development, improving user satisfaction and quality. Furthermore, issues with bug tracking are covered, including distributed team communication, scalability, and automation balancing. Proposals for strategies to address these issues are grounded in scholarly research and professional opinions. This summary highlights the critical role that bug tracking systems play in contemporary software development, making it an invaluable tool for researchers, practitioners, and teams looking to improve bug tracking procedures and raise the caliber and effectiveness of the software development lifecycle. Keywords— Bug Tracking System, Software Development, Defect Management, Quality Assurance, Automation, Collaboration, Large-scale Projects.

Approaches for Maximizing Maximum Power Point Tracking and Evaluating Operational Constraints in Photovoltaic Systems

Abstract: Optimization techniques have broad utility in multiple engineering fields, including activities such as modeling, system identification, parameter estimation, forecasting, and control of intricate systems. This innovation emphasizes the use of optimization approaches to control the performance of Photo-voltaic (PV) array systems. The main difficulty lies in the nonlinear correlation between current and voltage (I-V) characteristics of PV arrays, resulting in variations in the location of the Maximum Power Point under varied climatic circumstances. It is crucial to track this Maximum electricity Point efficiently in order to collect the highest amount of electricity possible from the photovoltaic devices. Maximum Power Point Tracking is a tracking procedure that optimizes power generation by dynamically altering the operating voltage to coincide with the MPP. In order to tackle this difficulty, the paper suggests a unique two-stage Maximum Power Point Tracking technique. The initial phase applies the Weightless Swarm Algorithm to evaluate the Maximum Power Point in an offline manner. The subsequent phase employs an online Adaptive Perturb &amp; Observe technique to continuously track the MPP in real-time. In addition, an Approximate Single Diode Model is created to quickly assess the output power. In order to verify the suggested method, computer simulations are performed utilizing a Maximum Power Point Tracking system that is combined with a Single-Ended PrimaryInductor Converter

Wired Fingerprint-Based Classroom Attendance System for Secured Student Attendance Archiving Using Arduino UNO Microcontroller

This study, which successfully addresses the shortcomings of traditional attendance-checking methods, such as human error, that are inevitable in manual attendance systems given the fact that it is time-consuming. Paper-based systems can be susceptible to forgery, as students may attempt to sign in on behalf of absent classmates. This undermines the integrity of attendance records. Introduces a fingerprint-based classroom attendance system designed using the Arduino Uno microcontroller. The research explores the feasibility of fingerprint biometrics for identity verification in educational settings. Using Arduino Uno, Fingerprint Sensor, RTC Module, and the LCD Monitor the researchers successfully developed a working prototype for the Wired Fingerprint-Based Classroom Attendance. 600 tests were applied to collect the (1.0) lowest and (2.0) highest time of the fingerprint sensor and calculate its average (1.7). The developed system operates offline, storing data securely on an SD card, making it particularly suitable for institutions in areas with restricted internet access. Comparative performance evaluations against conventional pen-and-paper methods highlight the fingerprint-based system's notable capacity, accuracy, positioning it as a transformative tool to enhance attendance tracking procedures and eliminates attendance-related issues to improve overall classroom operations.

Scan-Free and Fully Automatic Tracking of Native Knee Anatomy from Dynamic Stereo-Radiography with Statistical Shape and Intensity Models.

Kinematic tracking of native anatomy from stereo-radiography provides a quantitative basis for evaluating human movement. Conventional tracking procedures require significant manual effort and call for acquisition and annotation of subject-specific volumetric medical images. The current work introduces a framework for fully automatic tracking of native knee anatomy from dynamic stereo-radiography which forgoes reliance on volumetric scans. The method consists of three computational steps. First, captured radiographs are annotated with segmentation maps and anatomic landmarks using a convolutional neural network. Next, a non-convex polynomial optimization problem formulated from annotated landmarks is solved to acquire preliminary anatomy and pose estimates. Finally, a global optimization routine is performed for concurrent refinement of anatomy and pose. An objective function is maximized which quantifies similarities between masked radiographs and digitally reconstructed radiographs produced from statistical shape and intensity models. The proposed framework was evaluated against manually tracked trials comprising dynamic activities, and additional frames capturing a static knee phantom. Experiments revealed anatomic surface errors routinely below 1.0 mm in both evaluation cohorts. Median absolute errors of individual bone pose estimates were below 1.0 or mm for 15 out of 18 degrees of freedom in both evaluation cohorts. Results indicate that accurate pose estimation of native anatomy from stereo-radiography may be performed with significantly reduced manual effort, and without reliance on volumetric scans.

Design and analysis of shadow detection and removal scheme in real-time still images

This research’s main objective is to study and evaluate the detection and removal of undesired shadows from still images since these shadows might mask important information caused by light sources and other obstructions. A variety of methods for detecting and eliminating shadows as well as object tracking approaches based on movement estimation and identification are investigated. This includes shadow removal methods like background subtraction, which are intended to improve obstacle recognition of the source item and increase the accuracy of shadow removal from objects. When new items enter the frame, they are first distinguished from the background using a reference frame. The tracking procedure is made more difficult by the merging of the shadow with the foreground object. The approach highlights the difficulties in object detection owing to frequent occurrences of obstacles by using morphological procedures for shadow identification and removal. The proposed approach uses feature extraction is also discussed, highlighting its importance in image processing research and the use of suggested methods to get over obstacles in image sequences. The proposed method for shadow identification and removal offers a novel approach to improve image processing when dealing with still images. The purpose of this technique is to better detect and remove shadows from images, which will increase the precision of object tracking and detection. Depending on the type of images being processed, the process begins with initializing a background model, which is based on a static image background.

Behavioral evidence of the modulation filterbank in an avian animal model of complex-sound perception

Behavioral detection of amplitude modulation (AM) can be adversely affected by competing AM “noise” present in the acoustic environment. Called AM masking, human studies suggest the existence of a modulation filterbank that separates sounds (signal from noise) based on differences in AM frequency. The modulation filterbank is an important theoretical advancement in hearing science because in addition to explaining AM masking, the model successfully predicts differences in speech perception across noisy listening environments with different AM statistics. Currently, there are no behavioral animal models of the modulation filterbank, presenting a serious impediment to understanding neural underpinnings. We trained budgerigars, a parakeet species, to detect AM frequencies from 64 to 400 Hz in the presence of narrowband AM maskers applied to a 2.8-kHz carrier signal. AM masker center frequencies spanned a &amp;gt;2 octave range centered on the target AM frequency. Behavioral AM sensitivity was evaluated with operant conditioning, a single-interval two-alternative discrimination task, and two-down one-up adaptive threshold tracking procedures. Budgerigar AM masking functions had a band-pass characteristic, consistent with the modulation filterbank and with human AM masking results for the same stimuli. To our knowledge, these are the first behaviorally estimated modulation filter shapes in a nonhuman species. [Funding: NIDCD R01-DC017519.]

Screening and Retaining Adolescents Recruited Through Social Media: Secondary Analysis from a Longitudinal Clinical Trial.

Social media has become a popular method to recruit participants, particularly for studies with hard-to-reach populations. These studies still face challenges in data quality and, for longitudinal studies, sample retention. However, in addition to aiding in recruitment, social media platforms can help researchers with participant verification and tracking procedures during the study. There is limited previous research describing how longitudinal studies can use social media to screen and retain participants. This paper describes strategies implemented to screen and retain a nationwide sample of sexual minority youth who were recruited through social media platforms for a longitudinal study testing a drug abuse prevention program. Our screening strategies for participants included collecting necessary demographic information (name, phone, email, and social media accounts), verifying this information using publicly available web-based records, and sending confirmation emails to ensure working email addresses and correct dates of birth. Retention strategies included communications designed to develop positive participant relationships, incentives for survey completion, regular updating of participant contact information, targeting hard-to-reach participants, and using social media as an alternative means of contacting participants. During enrollment, although the only demographic data required were a phone number and an email address, 87.58% (1065/1216) of participants provided their Instagram as an alternative means of contact. This form of alternative communication remains the most preferred with 87.40% (1047/1198) of participants continuing to provide an Instagram username as of January 2023, about 3 years after recruitment began. In comparison, other alternative means of contact (eg, Facebook and alternative email) were provided by only 6.43% (77/1198) to 56.18% (673/1198) of participants. Direct messaging on Instagram was used to successfully confirm participant identity, remind participants to take annual follow-up surveys, and update lost participant contact information. Screening and retention strategies used in the study have helped achieve 96.30% (1171/1216) to 96.79% (1177/1216) sample retention across 3 waves of data collection. Though social media can be a helpful tool to recruit participants, attrition and participant authenticity difficulties may be associated with this method. Screening and retention strategies can be implemented to improve retention. Internet searches are effective for screening youth to ensure they meet eligibility requirements. Additionally, social media-Instagram in this study-can help to track and locate participants who do not respond to traditional contact methods. ClinicalTrials.gov NCT03954535; https://clinicaltrials.gov/study/NCT03954535.

The DECam Ecliptic Exploration Project (DEEP). VI. First Multiyear Observations of Trans-Neptunian Objects

We present the first set of trans-Neptunian objects (TNOs) observed on multiple nights in data taken from the DECam Ecliptic Exploration Project. Of these 110 TNOs, 105 do not coincide with previously known TNOs and appear to be new discoveries. Each individual detection for our objects resulted from a digital tracking search at TNO rates of motion, using two-to-four-hour exposure sets, and the detections were subsequently linked across multiple observing seasons. This procedure allows us to find objects with magnitudes m VR ≈ 26. The object discovery processing also included a comprehensive population of objects injected into the images, with a recovery and linking rate of at least 94%. The final orbits were obtained using a specialized orbit-fitting procedure that accounts for the positional errors derived from the digital tracking procedure. Our results include robust orbits and magnitudes for classical TNOs with absolute magnitudes H ∼ 10, as well as a dynamically detached object found at 76 au (semimajor axis a ≈ 77 au). We find a disagreement between our population of classical TNOs and the CFEPS-L7 three-component model for the Kuiper Belt.

A novel sequential endocardial mapping strategy for locating atrial fibrillation sources based on repetitive conduction patterns: An in-silico study

BackgroundIn persistent atrial fibrillation (AF), localized extra-pulmonary vein sources may contribute to arrhythmia recurrences after pulmonary vein isolation. This in-silico study proposes a high-density sequential mapping strategy to localize such sources. MethodCatheter repositioning was guided by repetitive conduction patterns, moving against the prevailing conduction direction (upstream) toward the sources. Sources were found either by locally identifying conduction patterns or by encircling the region harboring them. We simulated source tracking in an in-silico atrial model, comparing random vs. upstream-guided catheter repositioning (with and without encircling). To assess performance in increasing AF complexities, we simulated AF in 3 groups: atria with reentry-anchoring scars, without fibrosis, and with severe endomysial fibrosis. ResultsCompared to random mapping, the upstream-guided approach successfully located sources more often (anchored reentries: 70.6% vs. 10.6%; no fibrosis: 87.9% vs. 22.1%; with fibrosis: 95.0% vs. 60.9% of tracking procedures, all p<0.001), using fewer steps (median [IQR]: 11 [7;23] vs. 26 [13;35]; 10 [6;19] vs. 19 [10;27]; 11 [7;19] vs. 16 [8;30], respectively, all p<0.05). Adding source encircling increased source detection (98.1 %, 100 %, and 99.5 %, all p<0.01 vs. local detection only), reducing required steps (9 [6;12], 8 [6;12], and 9 [6;13], all p<0.05). In some cases (11.9 %, 17.1 %, and 10.5 % of procedures), the algorithm encircled regions >15 mm from the source. ConclusionMoving mapping catheters upstream improves source detection efficiency, even in the presence of severe fibrosis. Encircling sources may help find regions of interest in fewer steps.

Development of the Children's English and Spanish Speech Recognition Test: Psychometric Properties, Feasibility, Reliability, and Normative Data.

The Children's English and Spanish Speech Recognition (ChEgSS) test is a computer-based tool for assessing closed-set word recognition in English and in Spanish, with a masker that is either speech-shaped noise or competing speech. The present study was conducted to (1) characterize the psychometric properties of the ChEgSS test, (2) evaluate feasibility and reliability for a large cohort of Spanish/English bilingual children with normal hearing, and (3) establish normative data. Three experiments were conducted to evaluate speech perception in children (4-17 years) and adults (19-40 years) with normal hearing using the ChEgSS test. In Experiment 1, data were collected from Spanish/English bilingual and English monolingual adults at multiple, fixed signal-to-noise ratios. Psychometric functions were fitted to the word-level data to characterize variability across target words in each language and in each masker condition. In Experiment 2, Spanish/English bilingual adults were tested using an adaptive tracking procedure to evaluate the influence of different target-word normalization approaches on the reliability of estimates of masked-speech recognition thresholds corresponding to 70.7% correct word recognition and to determine the optimal number of reversals needed to obtain reliable estimates. In Experiment 3, Spanish/English bilingual and English monolingual children completed speech perception testing using the ChEgSS test to (1) characterize feasibility across age and language group, (2) evaluate test-retest reliability, and (3) establish normative data. Experiments 1 and 2 yielded data that are essential for stimulus normalization, optimizing threshold estimation procedures, and interpreting threshold data across test language and masker type. Findings obtained from Spanish/English bilingual and English monolingual children with normal hearing in Experiment 3 support feasibility and demonstrate reliability for use with children as young as 4 years of age. Equivalent results for testing in English and Spanish were observed for Spanish/English bilingual children, contingent on adequate proficiency in the target language. Regression-based threshold norms were established for Spanish/English bilingual and English monolingual children between 4 and 17 years of age. The present findings indicate the ChEgSS test is appropriate for testing a wide age range of children with normal hearing in either Spanish, English, or both languages. The ChEgSS test is currently being evaluated in a large cohort of patients with hearing loss at pediatric audiology clinics across the United States. Results will be compared with normative data established in the present study and with established clinical measures used to evaluate English- and Spanish-speaking children. Questionnaire data from parents and clinician feedback will be used to further improve test procedures.

Particle tracking in snow avalanches with in situ calibrated inertial measurement units

Abstract In the course of an artificially triggered avalanche, a particle tracking procedure is combined with supplementary measurements, including Global Navigation Satellite System (GNSS) positioning, terrestrial laser scanning and Doppler radar measurements. Specifically, an intertial measurement unit is mounted inside a rigid sphere, which is placed in the avalanche track. The sphere is entrained by the moving snow, recording translational accelerations, angular velocities and the flux density of Earth's magnetic field. Based on the recorded data, we present a threefold analysis: (i) a qualitative data interpretation, identifying different particle motion phases which are associated with corresponding flow regimes, (ii) a quantitative time integration algorithm, determining the corresponding particle trajectory and associated velocities on the basis of standard sensor calibration, and (iii) an improved quantitative evaluation relying on a novel in situ sensor calibration technique, which is motivated by the limitations of the given dataset. The final results, i.e. the evolution of the angular orientation of the sensor unit, translational and rotational velocities and estimates of the sensor trajectory, are assessed with respect to their reliability and relevance for avalanche dynamics as well as for future design of experiments.