Real-time Scoring Research Articles

App-Based Volleyball Scoreboard Performance Evaluation

Study purpose. This research aims to develop and evaluate an application-based volleyball scoreboard game device designed to facilitate the process of recording and managing scores in real time. Materials and methods. This research uses the R&D development method which aims to develop a device-based volleyball game scoreboard application. This research involved 3 IT experts, 5 referees who acted as evaluators of the initial product that had been developed. In addition, there were 5 samples in the small-scale test and 30 samples in the large-scale test. Results. The results of the analysis of the development of application-based volleyball scoreboard game devices by conducting feasibility / justification tests involving economic, technical, business and environmental aspects by refereeing experts, which obtained an average value of 91.60%, where the value was included in the very good category. While the results of the analysis of IT experts obtained an average value of 90.89%, where the value is included in the very good category. The results of the analysis of the effectiveness of the media development of the application-based volleyball scoreboard game device through a small scale test, which obtained an average value of 92.63%, which means it can be concluded that the development model of the application-based volleyball scoreboard game device that has been developed can be implemented/applied with a very good category. Meanwhile, the results of the large-scale test or broad-scale test obtained an average value of 90.94%, which means it can be concluded that the development model of the application-based volleyball scoreboard game device that has been developed is in the excellent category. Conclusion. In conclusion, this application-based volleyball scoreboard game device can be an effective solution to overcome the obstacles of manual score recording, while improving the quality of organising volleyball matches

The effect of the US Child Tax Credit advance payments in 2021 on adolescent mental health: Changes in depression symptoms and suicidality

ObjectiveChild poverty is associated with poor adolescent mental health. Changes to the Child Tax Credit (CTC) in 2021 in the U.S. were historic and introduced a new model of distributing the credit in advance of tax filing, providing families with stable, supplemental monthly income. This policy shift offers a unique opportunity to examine the mental health effects for adolescents. MethodsWe use electronic health record data from a large pediatric primary care network in Columbus, Ohio, which collected adolescent depression screening scores in real time as the CTC advance payments were introduced. We utilized differences in age of eligibility for the CTC to examine the changes in the probability of depression screening outcomes (positive depression screen, any depression symptom, any suicidal ideation), for adolescents eligible for the credit (turned 18 first quarter of 2022), relative to those not eligible (turned 18 last quarter of 2021) (n = 1,423). ResultsWe did not observe a significant association between the policy change and study outcomes in the overall sample. However, the percentage of adolescents with a positive depression screen significantly declined for Non-Hispanic Black (13.4 percentage point reduction, p = 0.01) and publicly insured (9.7 percentage point reduction, p = 0.04) adolescents. ConclusionsOur findings suggest reductions in depression symptoms for subgroups of adolescents who were age-eligible for the CTC compared to their counterparts who were not eligible. The CTC advance payments were a brief experiment in universal basic income and may offer a policy solution for addressing both poverty and a growing adolescent mental health crisis.

The Feasibility of Using Net Promoter Score to Measure Real-Time Employee Engagement

This study aims to determine the feasibility of using a digital tool and net promoter scores to measure real-time employee engagement. Participation rates with the digital tool had a statistically significant improvement when teams were able to see their engagement score in real time. The team's interaction with the digital tool may have served as a positive distraction during the pandemic.

Relationship between judges' scores and dive attributes from a video recording of a diving competition.

Sports such as diving, gymnastics, and ice skating rely on expert judges to score performance accurately. Human error and bias can affect the scores, sometimes leading to controversy, especially at high levels. Instant replay or recorded video can be used to assess judges’ scores, or sometimes update judges’ scores, during a competition. For diving in particular, judges are trained to look for certain characteristics of a dive, such as angle of entry, height of splash, and distance of the dive from the end of the board, to score each dive on a scale of 0 to 10, where a 0 is a failed dive and a 10 is a perfect dive. In an effort to obtain objective comparisons for judges’ scores, a diving meet was filmed and the video footage used to measure certain characteristics of each dive for each participant. The variables measured from the video were height of the dive at its apex, angle of entry into the water, and distance of the dive from the end of the board. The measured items were then used as explanatory variables in a regression model where the judge’s scores were the response. The measurements from the video are gathered to provide a gold standard that is specific to the athletic performances at the meet being judged, and supplement judges’ scores with synergistic quantitative and visual information. In this article we show, via a series of regression analyses, that certain aspects of an athlete’s performance measured from video after a meet provide similar information to the judges’ scores. The model was shown to fit the data well enough to warrant use of characteristics from video footage to supplement judges’ scores in future meets. In addition, we calibrated the results from the model against those of meets where the same divers competed to show that the measurement data ranks divers in approximately the same order as they were ranked in other meets, showing meet to meet consistency in measured data and judges’ scores. Eventually, our findings could lead to use of video footage to supplement judges’ scores in real time.

Examining spoken words and acoustic features of therapy sessions to understand family caregivers’ anxiety and quality of life

BackgroundSpeech and language cues are considered significant data sources that can reveal insights into one’s behavior and well-being. The goal of this study is to evaluate how different machine learning (ML) classifiers trained both on the spoken word and acoustic features during live conversations between family caregivers and a therapist, correlate to anxiety and quality of life (QoL) as assessed by validated instruments. MethodsThe dataset comprised of 124 audio-recorded and professionally transcribed discussions between family caregivers of hospice patients and a therapist, of challenges they faced in their caregiving role, and standardized assessments of self-reported QoL and anxiety. We custom-built and trained an Automated Speech Recognition (ASR) system on older adult voices and created a logistic regression-based classifier that incorporated audio-based features. The classification process automated the QoL scoring and display of the score in real time, replacing hand-coding for self-reported assessments with a machine learning identified classifier. FindingsOf the 124 audio files and their transcripts, 87 of these transcripts (70%) were selected to serve as the training set, holding the remaining 30% of the data for evaluation. For anxiety, the results of adding the dimension of sound and an automated speech-to-text transcription outperformed the prior classifier trained only on human-rendered transcriptions. Specifically, precision improved from 86% to 92%, accuracy from 81% to 89%, and recall from 78% to 88%. InterpretationClassifiers can be developed through ML techniques which can indicate improvements in QoL measures with a reasonable degree of accuracy. Examining the content, sound of the voice and context of the conversation provides insights into additional factors affecting anxiety and QoL that could be addressed in tailored therapy and the design of conversational agents serving as therapy chatbots.

Improving Psychosocial Risk Assessment and Service Provision for Craniofacial Team Patients: A Quality Improvement Project.

To improve psychosocial risk assessment and service provision for children with craniofacial conditions presenting for annual interdisciplinary team visits. Institute for Healthcare quality improvement model. U.S. pediatric academic medical center. Caregivers of children ages 0-17 years with craniofacial conditions presenting for 1692 team visits between August 2017 and July 2019. Key drivers included: (1) standardizing pre-visit triage processes; (2) administering the Psychosocial Assessment Tool-Craniofacial Version (PAT-CV); (3) utilizing PAT-CV scores in real time to add patients to psychosocial provider schedules; and (4) family education. Interventions included improving patient screening, increasing PAT-CV completion rate, altering clinic flow, providing patient and parent education about psychosocial services, and altering team member roles to fully integrate PAT-CV administration and scoring in the clinic. The primary outcome was the percentage of patients identified for psychosocial consultations via nurse triage, PAT-CV score, family or provider request who completed consultations. The secondary outcome was the percentage of patients completing needed psychosocial consultations based on elevated PAT-CV scores. Use of the PAT-CV resulted in an increase in the percentage of patients with elevated psychosocial risk who received a psychosocial consultation from 86.7% to 93.4%. The percentage of children receiving psychosocial consultation at their annual team visit due to elevated PAT-CV scores increased from 72% to 90%. Integrating a validated psychosocial risk screening instrument can improve risk identification and psychosocial consultation completion. A combination of risk screening approaches may be indicated to identify patients in need of psychosocial services.

Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules.

Guidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time within electronic health records (EHRs) would overcome a major impediment. This requires an automated mechanism to accurately identify ("phenotype") patients with GIB at the time of presentation. The goal is to identify patients with acute GIB by developing and evaluating EHR-based phenotyping algorithms for emergency department (ED) patients. We specified criteria using structured data elements to create rules for identifying patients and also developed multiple natural language processing (NLP)-based approaches for automated phenotyping of patients, tested them with tenfold cross-validation for 10 iterations (n=7144) and external validation (n=2988) and compared them with a standard method to identify patient conditions, the Systematized Nomenclature of Medicine. The gold standard for GIB diagnosis was the independent dual manual review of medical records. The primary outcome was the positive predictive value. A decision rule using GIB-specific terms from ED triage and ED review-of-systems assessment performed better than the Systematized Nomenclature of Medicine on internal validation and external validation (positive predictive value=85% confidence interval:83%-87% vs 69% confidence interval:66%-72%; P<0.001). The syntax-based NLP algorithm and Bidirectional Encoder Representation from Transformers neural network-based NLP algorithm had similar performance to the structured-data fields decision rule. An automated decision rule employing GIB-specific triage and review-of-systems terms can be used to trigger EHR-based deployment of risk stratification models to guide clinical decision making in real time for patients with acute GIB presenting to the ED.

The Landing Error Scoring System Real-Time test as a predictive tool for knee injuries: A historical cohort study

PurposeTo assess the value of the Landing error score system - real time test as a predictive tool for knee injuries among combat soldiers in the Israeli defense forces. MethodsAll 2474 Israeli defense forces' combat soldiers enrolled at the Israeli defense forces Injury Prevention and Rehabilitation Center were included. A retrospective cohort study was conducted. The predictive variable assessed was the landing error score system – real time score. The three main outcome variables were the incidence of overuse knee injuries, the meniscal injury, and the anterior cruciate ligament injury. Receiver operator characteristic analysis was performed to evaluate the test's potential as a predictive tool and in order to establish optimal cutoff scores. ResultsThe area under the curve of the receiver operation curves demonstrated no predictive value of the landing error score system – real time test for all three outcome variables (knee injuries: area under the curve 0.526, 95% confidence interval 0.498, 0.554, anterior cruciate ligament injuries: area under the curve 0.496, 95% confidence interval 0.337, 0.656, meniscus injuries: area under the curve 0.515, 95% confidence interval 0.454, 0.576). InterpretationBased on the results of this study, the landing error score system – real time test has no predictive value for knee overuse injuries, meniscal injuries, and anterior cruciate ligament injuries. However, due to the small number of cases of anterior cruciate ligament injuries, the predictive value for anterior cruciate ligament injuries of this test should be further investigated.

Interrater Reliability, Accuracy, and Triage Time Pre- and Post-implementation of a Real-Time Electronic Triage Decision-Support Tool

The electronic Canadian Triage and Acuity Scale (eCTAS) is a real-time electronic triage decision-support tool designed to improve patient safety and quality of care by standardizing the application of the Canadian Triage and Acuity Scale (CTAS). The objective of this study is to determine interrater agreement of triage scores pre- and post-implementation of eCTAS. This was a prospective, observational study conducted in 7 emergency departments (EDs), selected to represent a mix of triage documentation practices, hospital types, and patient volumes. A provincial CTAS auditor observed triage nurses in the ED pre- and post-implementation of eCTAS and assigned an independent CTAS score in real time. Research assistants independently recorded triage time. Interrater agreement was estimated with κ statistics with 95% confidence intervals (CIs). A total of 1,491 individual triage assessments (752 pre-eCTAS, 739 post-implementation) were audited during 42 7-hour triage shifts (21 pre-eCTAS, 21 post-implementation). Exact modal agreement was achieved for 567 patients (75.4%) pre-eCTAS compared with 685 patients (92.7%) triaged with eCTAS. With the auditor's CTAS score as the reference, eCTAS significantly reduced the number of patients over-triaged (12.0% versus 5.1%; Δ 6.9; 95% CI 4.0 to 9.7) and under-triaged (12.6% versus 2.2%; Δ 10.4; 95% CI 7.9 to 13.2). Interrater agreement was higher with eCTAS (unweighted κ 0.89 versus 0.63; quadratic-weighted κ 0.93 versus 0.79). Median triage time was 312 seconds (n=3,808 patients) pre-eCTAS and 347 seconds (n=3,489 patients) with eCTAS (Δ 35 seconds; 95% CI 29 to 40 seconds). A standardized, electronic approach to performing triage assessments improves both interrater agreement and data accuracy without substantially increasing triage time.

42 Advancements in silage management and technology for beef and dairy cattle

Abstract In 2017, 2.6 million ha of American farmland were destined for corn silage production, which was estimated at 116.5 million tons. Data for 2018 are yet to be compiled but field observations provide insight of a difficult year for growing and harvesting conditions. In recent years, there has been a renewed interest in making the most efficient use of forage resources. Since corn silage is a predominant forage for beef and dairy cattle, most advances have focused on improving harvesting, storage and feeding methods of this crop. The harvesting process has been modified with the introduction of various designs of kernel processors; commercial laboratory data show a trend towards greater and more uniform processing score since 2010. Furthermore, the degree of processing can now be objectively evaluated by combining hydrodynamic separation and image processing software to obtain a kernel processing score in real time in field conditions. Applications of plastic film technology, such as oxygen barriers, to seal and maintain an anaerobic environment, have aroused interest due to the possibility of reducing spoilage with a concomitant increase in recovery of dry matter from the uppermost layer of a silage pile. Throughout the storage phase, it has been recognized that starch digestibility increases over time due to prolamin solubilization. Recent work with reconstituted high-moisture corn demonstrated that bacterial proteolytic activity contributes 60% to protein solubilization and that fermentation acids play a minor role in this process. The field of inoculants has also seen innovations in terms of application equipment and species and strain selection, with Lactobacillus buchneri becoming relevant for certain conditions that require longer aerobic stability. During feed-out, dry matter monitoring can be done with instant measurements using NIR technology in various applications ranging from tractor-mounted instruments to hand-held devices. Even though silage making has been a longstanding practice, specific aspects of the process have evolved over time and are worthy of consideration to improve forage management and quality in support of ruminant nutrition.

Phone Addiction Monitoring : An android Application for Smartphones

Phone Addiction Monitor is application which is based on android platform. The “Phone Addiction Monitor” is to developed for manage the time of phone usage and overcome the spending time on social media. Using an advanced algorithm, the app studies your phone usage and calculates addiction score in real time. Show the graph on daily, weekly &amp; monthly basis, so it is easy to analyse the data and manage time. Application show the Analysis application wise so you can see how much time you spend on each application. An adult checks his phone a taping 110 times a day. That makes it once every 14 minutes. And for most people this peak to once every 6 seconds in the evenings. So, people easily track the phone usage

Pharmacist-driven initiative for management of Staphylococcus aureus bacteremia using a clinical decision support system.

The development and implementation of a clinical decision support system (CDSS) for pharmacists to use for identification of and intervention on patients with Staphylococcus aureus bacteremia (SAB) are described. A project team consisting of 3 informatics pharmacists and 2 infectious diseases (ID) pharmacists was formed to develop the CDSS. The primary CDSS component was a scoring system that generates a score in real time for a patient with a positive blood culture for S. aureus. In addition, 4 tools were configured in the CDSS to facilitate pharmacists' workflow and documentation tasks: a patient list, a patient list report, a handoff note, and a standardized progress note. Pharmacists are required to evaluate the patient list at least once per shift to identify newly listed patients with a blood culture positive for S. aureus and provide recommendations if necessary. The CDSS was implemented over a period of 2.5 months, with a pharmacy informatics resident dedicating approximately 200 hours in total. An audit showed that the standardized progress note was completed for 100% of the patients, with a mean time to completion of 8.5 hours. Importantly, this initiative can be implemented in hospitals without specialty-trained ID pharmacists. This study provides a framework for future antimicrobial stewardship program initiatives to incorporate pharmacists into the process of providing real-time recommendations. A pharmacist-driven patient scoring system was successfully used to improve adherence to quality performance measures for management of SAB. A pharmacist-driven CDSS can be utilized to assist in the management of SAB.

Design of Real-time Disease Warning System Based on Storm Technology

With the improvement of the quality of clinical diagnosis and treatment, the traditional scheduled "ward round" mode cannot meet the demands for real-time monitoring of acute and critically ill patients. This paper introduces the Storm, a real-time data stream processing technology and its application in the real time disease early warning system. By collecting the clinical data flow and calculating the MEWS scores in real time, the system can identify the potential deterioration of the disease, and promptly notify the medical staff. Score calculation results can be stored for further analysis and presentation as well.

392 Disposition Destination Does Not Affect Patient Experience Ratings in Real-Time in an Urban Academic Emergency Department

Patient experience surveys are becoming an increasing portion of merit-based incentive programs, alternative payment models and improved patient outcomes. As such, the ability to sustain “high” scores has gained prominence as many programs focus on broad initiatives to improve patient experience. These programs often lack specificity and use delayed survey results for assessment. The ability to target initiatives to patients in real time may provide a real innovation as timely discovery of patients at risk for low experience scores may allow for targeted service recovery efforts prior to the official survey ratings. This study sought to assess if real-time ratings of patient experience are affected by projected disposition destination in the emergency department. This study is a subset analysis of a single center, IRB-approved, pilot study to evaluate if emergency physicians can predict actual patient satisfaction scores in real time in an urban academic ED. The goal was to assess for any differences in patient experience based on projected disposition in real time. During randomly assigned time blocks, a research assistant performed anonymous tablet-based patient experience surveys on both physicians and patients as they presented to an urban academic emergency department. The survey consisted of several questions directed at the treating physician including projected disposition of the patient (likely admit, likely discharge or unknown at this time) and 4 questions directed to the patient designed to assess standard patient experience ratings of physician performance (“Courtesy of the Doctor,” “Degree to which doctor took time to listen to you,” “Degree to which doctor kept you informed of your care,” and “Doctor’s concern for comfort while treating you”), using a 5-point Likert scale from 1 (“very poor”)-5(“very good”). Participation was voluntary and confidential. Differences in mean satisfaction scores and percentage of “top box” scores for patients were stratified by disposition for t-test and Chi square analysis. Total n=62 for the full pilot study, with n=52 (19= admit vs 33=discharge) for this subset analysis (9 responses were removed as disposition was “unknown” and 1 patient refused participation for all questions and removed from analysis); overall 98% response rate. Patients’ means scores for physician performance on admitted vs discharged were compared (t-test): “Courtesy” (4.68 ± 0.11 vs 4.64 ± 0.10, p=.76), “Listen” (4.79 ± 0.10 vs 4.58 ± 0.13, p=.26), “Informed” (4.48 ± 0.14 vs 4.58 ± 0.12, p=0.6) and “Comfort” (mean =4.26 ± 0.20 vs 4.48 ± 0.13, p=0.34). Chi square values on the % top box scores on admitted vs discharged patients were: “Courtesy” (68.4% vs 69.7%, p=.92), “Listen” (79% vs 69.7%, p=.47) m “Informed” (52.6% vs 69.7%, p=.22), and “Comfort” (47.4% vs 60.6%, p=0.35). This study is a first to assess patient experience, in real time, as stratified by projected disposition. While this small analysis showed no significant differences between mean satisfaction and “top box” scores across experience ratings, patients likely to be admitted did have slightly higher mean scores with respect to listening, while simultaneously rating physicians lower on keeping patients informed and with respect to comfort for both mean and % “top box” scores. Expanding on this pilot study may provide insight into the needs and failings that prevent improvements in the patient experience in the emergency department.

Disposable Music

This article introduces the concept of real-time composition and composition as a “dispositif” in the sense of Foucault and Deleuze, defining it as a heterogeneous ensemble of pieces that together form an apparatus. The introduction situates the dispositif in the context of cultural developments, most notably its slow but steady shift away from textualization in digital media. As musicians are adapting to ensuing cultural and, above all, economic changes, new musical forms emerge that rely to a lesser degree on fully notated scores, such as “comprovisation” or laptop performance. Antithetically, the computer also allows the creation of “authorless” notated scores in real time to be sight-read by capable musicians—a practice for which special software has been developed in recent years. Because these scores are not meant to be kept and distributed, they are ephemeral and, therefore, disposable. Three examples by the author are given to illustrate the interwovenness of this approach, where carefully selected narratives and dramaturgies make up for the inherent unpredictability of the outcome.

Hamilton Early Warning Score: predict, prevent and protect

This study determined the pattern of decline prior to an inpatient arrest. We implemented the Hamilton Early Warning Score (HEWS) within our electronic vital signs documentation to track and trigger care for deteriorating patients. Other EWS have been described in the literature with varying success [1]. In contrast to previous observational studies, we chose to implement a score modified from published EWS using the consensus opinion of a steering committee and evaluate the score in real time.

Do Desenho e do Som: Harmonising screen scores and listening

Do Desenho e do Som is a software application that creates graphical screen scores in real time. Fascinated by the theoretical discussions concerning improvisation, composition and real-time composition, the author endeavours to conceive an interactive environment to induce controlled improvisation contexts, using real-time scores. Do Desenho e do Som makes use of real-time screen scores to facilitate the communication of formalised musical ideas, which due to their ambiguous graphical nature create an interesting interaction between a composer, an assistant and performers. It also grants a real-time control over form as the notation, and consequently the music, unfolds at runtime. With a focus on the underlying importance of listening, the author based this article on his own experience designing the Do Desenho e do Som software and using it for composition.

Hacking Choreography: Dance and Live Coding

This article explores the intersection of live coding and choreography, discussing the “practice as research” project Hacking Choreography. It examines the use of computer programming languages within dance scores, the creation of scores in real time, and the transparency of these scores to the audience during performance. Four pieces created by the author are discussed in terms of these elements and compared to live-coding practices for computer music. Through this, not only does live coding emerge as a performance practice related to sound or visuals, but it also continues its trajectory as a transdisciplinary approach to live performance events.

The Systems Concepts Digital Synthesizer: An Architectural Retrospective

In the mid 1970s, specialized hardware for synthesizing digital audio helped computer music research move beyond its early reliance on software synthesis running on slow mainframe computers. This hardware allowed for synthesis of complex musical scores in real time and for dynamic, interactive control of synthesis. Peter Samson developed one such device, the Systems Concepts Digital Synthesizer, for Stanford University's Center for Computer Research in Music and Acoustics. The “Samson Box” addressed the classical problems of digital audio synthesis with an elegance that still rewards study. This article thoroughly examines the principles underlying the Box's design—while considering how it was actually employed by its users—and describes the architecture's advantages and disadvantages. An interview with Samson is included.

Development of new measurement system of thoracic excursion with biofeedback: reliability and validity

BackgroundRespiratory rehabilitation reduces breathlessness from patient with respiratory dysfunction. Chest expansion score, which represents the circumference magnitude of the thoracic cage, is used for a target when treating patients with respiratory disease. However, it is often difficult for patients to understand the changes in the respiratory status and be motivated for therapy continuously. We developed a new measurement system with biofeedback named BREATH which shows chest expansion scores in real time. The purpose of this study was to determine the reliability and validity of the novel system in advance of clinical application.MethodsThree evaluators measured chest expansion in 33 healthy individuals using tape measure, which is used for the measurement traditionally, and BREATH. The wire for BREATH system was threaded over the thoracic continuously and the data was recorded automatically; whereas the tape was winded and measured each maximal expiration and inspiration timing by evaluator. All participants were performed both measurement simultaneously for three times during deep breath. In this study, we studied chest expansion score without using biofeedback data of BREATH to check the validity of the result. To confirm intra- and inter-evaluator reliability, we computed intra-class correlations (ICCs). We used Pearson’s correlation coefficient to evaluate the validity of measurement result by BREATH with reference to the tape measure results.ResultsThe average (standard deviation) chest expansion scores for all, men and women by the tape measure were 5.53 (1.88), 6.40 (1.69) and 5.22 (1.39) cm, respectively, and those by BREATH were 3.89 (2.04), 4.36 (1.83) and 2.89 (1.66) cm, respectively. ICC within and among the three evaluators for BREATH and the tape measure were 0.90-0.94 and 0.85-0.94 and 0.85 and 0.82, respectively. The correlation coefficient between the two methods was 0.76-0.87.ConclusionThe novel measurement system, BREATH, has high intra- and inter-evaluator reliabilities and validity; therefore it can lead us more effective respiratory exercise. Using its biofeedback data, this system may help patients with respiratory disease to do exercises more efficiently and clinicians to assess the respiratory exercise more accurately.