Data Collection Software Research Articles

A hierarchical model of the information environment for railway power supply system critical objects control

It is proposed to consider the hierarchical model of the information environment as a structure according to its functions (implemented by the software part) and architecture (responsible for effective implementation of functional capabilities). It is proposed to improve the information management system of Ukrzaliznytsia’s critical power supply facilities, based on the developed hierarchical model of the information environment, which takes into account the presence of Ukrzaliznytsia’s own generation sources by integrating the appropriate control subsystem into the information system structure. The model emphasizes the integration of software and hardware components for data collection, pre-processing, and decision-making, contributing to a highly automated and intelligent control system. It proposes a multi-level structure incorporating artificial intelligence and advanced technologies to optimize electricity consumption and improve operational efficiency within the railway power supply system.

Streamlining Acute Stroke Processes and Data Collection: A Narrative Review

(1) Background: Acute ischemic stroke treatment has been thoroughly studied to identify strategies to reduce treatment times. However, many centers still struggle to achieve fast treatment times. Additionally, studies primarily focus on larger, more advanced centers; yet, smaller centers often face longer treatment times. (2) Objectives: The aim of this study is to analyze the existing literature reviewing stroke treatment processes in primary and comprehensive stroke centers that investigated or reduced treatment times. The articles identified were categorized based on the focus areas and approaches used. (3) Results: Three main categories of improvements were identified in the literature: (1) standardization of processes, (2) resource management, and (3) data collection. Both primary and comprehensive stroke centers were able to reduce treatment times through standardization of the processes. However, challenges such as variations in hospital resources and difficulties incorporating data collection software into workflow were highlighted. Additionally, many strategies to optimize resources and data collection that can benefit primary stroke centers were only conducted in comprehensive stroke centers. (4) Conclusions: Many existing strategies to improve stroke treatment times, such as pre-notification and mass stroke team alerts, have been implemented in both primary and comprehensive stroke centers. However, tools such as simulation training are understudied in primary stroke centers and should be analyzed. Additionally, while data collection and feedback are recognized as crucial for process improvement, challenges persist in integrating consistent data collection methods into clinical workflow. Further development of easy-to-use software tailored to clinician needs can help improve stroke center capabilities to provide feedback and improve treatment processes.

How do Startups use AI? A Q-methodology approach to understanding adoption patterns.

Artificial Intelligence (AI) can move beyond mere task automation and can actively foster the very process of innovation. As startups are the organizational entities which rely heavily on creativity and innovation, it is intriguing to evaluate the use of AI in startups and in the entrepreneurship field. As AI is already becoming increasingly pervasive and indispensable in the startup ecosystem, the question arises, how exactly startups are using AI. We used the Q-methodology to investigate this topic empirically. This methodology was chosen because it combines the strengths of both qualitative and quantitative methods. The Q-samples (i.e., set of statements) were developed from secondary sources like literature and primary sources like interviews. In this context three in-depth-interviews with entrepreneurs were conducted to comprehensively cover the topic. The concourse comprised a set of 43 statements, that each provided one aspect of “How do startups use AI?”. The collection of the Q-Samples was then followed by the Q-sorting, in which participants were asked to rank the items according to their degree of agreement. In this study 30 entrepreneurs from different startups in Germany were interviewed. The interviews were conducted online via a video chat to give participants the chance to comment on their ranking. We used the QMethod Software for data collection and analysis. The research illuminates current AI practices among startups, identifies common fields and highlights areas for further development. The findings of this study reveal the prioritization of operational efficiency as the driving force behind AI implementation. However, it is quite concerning that ethical considerations are largely ignored, posing risks of potential ethical oversights in AI utilization. Furthermore, most startups see AI as a facilitator of human creativity rather than a replacement. Overall, this paper is relevant to a diverse audience interested in understanding the current landscape, challenges, and opportunities associated with the usage of AI technologies within the startup ecosystem. This audience includes entrepreneurs, investors, researchers, educators, and policy makers.

Actor-Network theory and a methodology for inquiring the online/offline of education

The paper explores what the methodological considerations are for a study of educational practice and networked learning in technologically dense classrooms. The approach of the discussed study is informed by Actor-Network Theory (ANT) (Latour, 2005) and the paper outlines the methodological consequences for adopting principles associated with ANT and post-humanist critiques of representational epistemology. The discussion is organised around overcoming an offline/online binary of educational practice and the use of screen recording software for data collection in ethnographic fieldwork in upper secondary classrooms. In this example, ethical ramifications are brought to the fore in relation to post-humanist traditions (Barad, 2003). The paper argues that the uncertainties exposed by troubling the two categories of human and language, by way of ethno-graphy, can serve as resource for a research practice informed by ANT.

Epidemiology and clinical profile of sports injuries treated in the Douala General and Laquintinie Hospitals, in Cameroon

ObjectivesTo describe the epidemiological patterns and clinical characteristics of sports injuries treated at two hospitals in Douala.MethodsThis was a cross-sectional study conducted at the Douala General Hospital and Douala Laquintinie...

Bridging an Education Gap: Ultrasound-guided Peripheral IVs

PurposeTo provide ultrasound (US) education to anesthesia providers to increase usage for peripheral intravascular (IV) cannulation on difficult IV access patients. DesignThis project reflects a qualitative descriptive quality improvement project with outcomes measured. Data in this project include the overall knowledge and competency scores from the provider’s US survey before and after education and training were provided. MethodsA presentation was developed and provided to 38 certified registered nurse anesthetists (CRNA) via the hospital’s online platform. Next, in-person simulations were conducted to facilitate the skills of US utilization. Each CRNA participating in simulations successfully performed the skill. The impact and success of the education bundle were collected via the disbursement of a Likert-scale survey via an automated data collection software. FindingsSeventeen of the 38 (45%) participants responded to the survey. Of these respondents, 88% of providers indicated that their US skills and confidence had increased following the intervention, and 100% of participants stated that the intervention was helpful in learning US-guided peripheral IV insertion. ConclusionsEducation and hands-on skills sessions increased provider confidence in US use. While this project focused on educational training of CRNAs, this is applicable to all health care providers who are responsible for IV cannulation. The project team members will disseminate these findings and plan to improve perioperative nurses’ confidence in US-guided peripheral IV insertions; thus, improving efficiency in the operative setting.

Assessing physiological arousal and emotional valence during behavioral intervention for pediatric feeding difficulties: A pilot study

AbstractThis study's purpose is to introduce a new measurement system that objectively assesses the social validity of behavioral feeding intervention from the child's perspective via the concurrent measurement of two dimensions of emotion. To date, the primary measures of social validity for behavioral feeding intervention are caregiver treatment acceptability and satisfaction surveys. This is the first study to objectively measure two dimensions of emotion, physiological arousal and emotional valence, while children received behavioral intervention for feeding difficulties. Data collectors used a new open‐source data collection software, cometrics, developed to synchronize and record physiological and observational data. Physiological data was collected using a wearable biosensor and observers recorded an index of child happiness, unhappiness, or neither using definitions by Phipps et al. (2022) for six children with a pediatric feeding disorder. Two out of six children needed programmed habituation to the device before data collection. All children assented to wearing the device during data collection. Recorded indices mapped to separable physiological states using electrodermal activity and its constituent components, skin conductance responses and skin conductance level, in addition to skin temperature. Findings demonstrated the feasibility of measuring two dimensions of child emotions during behavioral feeding intervention and revealed that children's physiological responses were distinctly different during intervals scored as happy, unhappy, or neither. This new data collection system has implications for future research on the child's emotional experience of behavioral feeding treatment and increases the possibilities for improving clinical practice.

Analysing the impact of the 50:22 kick law changes in South African rugby tournaments between 2021 and 2022

ABSTRACT Tactical kicking plays a crucial role in rugby union, influencing both attacking and defensive strategies and potentially impacting a team’s overall success. The introduction of the 50:22 law requires defensive teams to reposition players to anticipate and counter kicks, thereby reducing the number of players in their defensive front line. This study investigated the impact of the 50:22 kicking law on kicking profiles by comparing the 2021 and 2022 seasons, as well as examining the success rate of 50:22 kicks during the 2022 season in South African rugby union tournaments. A retrospective research design was employed, utilising video-based performance analysis software (Nacsport Scout Plus) for data collection. The analysis encompassed all general play kicks from 177 matches spanning two seasons and tournaments, amounting to a total of 6,479 kicks. Within this dataset, there were 53 successful 50:22 kicks out of 162 attempts. Key findings revealed an upswing in kicks by scrum halves (2021: 20%, 2022: 26%; p = 0.00) and a concurrent decline in kicks by fullbacks (2021: 21%, 2022: 18%; p = 0.01). Notably, there was a significant increase in the percentage of kicks occurring in the fourth quarter of the match (2021: 20%, 2022: 22%; p = 0.01). Furthermore, the study identified a noteworthy increase in the percentage of kicks following a turnover (2021: 2%, 2022: 3%; p < 0.01). In conclusion, this research contributes valuable insights into how the 50:22 law shapes kicking strategies in South African rugby union, shedding light on the shifts in player roles and temporal patterns of kicking within the context of this specific law.

Challenges and Issues in Implementing & Operationalising Big Data Analytics Capabilities in a major Australian Railway Organisation: A Case Study

This study examines the implementation of a Big Data Analytics (BDA) project within a major Australian freight and railway organisation. It also identifies the issues and challenges with data collection, data cleaning, data modelling, and data science software, and implements these models to deliver tangible business results. In addition, the project highlights the potential gains that a data analytics project, integrated with a data-driven culture, can provide through significant operational efficiencies and financial gains. Prior to 2019, the company had little exposure to Predictive Analytics. This study shows how the development of data science capability enables the creation of advanced predictive models, particularly in this case study, for the prediction of train wheel wear, and therefore a significant reduction in maintenance expenses Furthermore, a Data Analytics Maturity Assessment was conducted to determine the requirements to become a data-driven organisation. The outcome of the assessment was compared to recent global studies, and it was found that the organisation examined was significantly behind its counterparts in the areas of resources and analytic capabilities, and therefore required investment in these areas. Further studies to examine the degree of Data Analytics maturity within the Australian context are suggested. Organisations striving to become more data-driven need to plan and allocate resources for capability development in infrastructure, data management, employee quantitative skills, and governance.

The validation of inertial measurement units in upper limb movement during wheelchair activity

Introduction: 3D motion capture is accepted to be the gold standard approach to all data collection for the production of accurate data, however, in recent literature the ecological validity of 3D systems has come into question. This has brought about the use of Inertial measurement units (IMU’s) and the investigation into their accuracy in enabling accurate real life scenario data collection. The depth of research on IMU’s in wheelchair data collection is limited, and at current there is limited attempts at a validation in comparison to an established data collection software. This research aims to validate basic upper body motions seen within wheelchair propulsion in an attempt to identify the current limitations of IMU’s. Methods: numerous IMU placements and calibration stances were investigated for the collection of elbow flexion and shoulder flexion. IMU’s for elbow flexion were placed at the wrist and central on the forearm. For shoulder flexion the IMU was placed 1 cm above the elbow joint. During the calibration phase, standing anatomical position with thumbs forwards, palms outwards, bent elbow and straight arms outwards at 90° for elbow and shoulder flexion, respectively. For both shoulder and elbow flexion, the participant started at a neutral position and moved through to 90° of flexion and returned to starting position. Quintic was used as the validated software. Results: the wrist placed IMU determined elbow flexion more accurately than the forearm placed IMU. Range of motion for both shoulder and elbow flexion were well calculated within several degrees when using the anatomical thumbs forwards calibration pose; with 99.97 and 89.69°, respectively compared to 88.48 and 97.32°. However, the degree of elbow flexion was overestimated with a difference of 27.78°, with the IMU being 91.11° and quintic being 63.33°. Similar results were also seen for the prediction of elbow flexion during the starting phase with a difference of 26.58°. Discussion: with range of motion accurately calculated in comparison to quintic, and shoulder flexion maximum and minimum values also being similar when segment angle was calculated. Then the differences are likely due to error in the calculation of joint angle using a calculation of global coordinate system from the IMU coordinate system during data processing. Therefore, future research should target alternate approaches to data processing in order to reduce the errors seen.

Analysis of Restitution Coefficient Value on the Ball Using Tracker Software by Utilizing Video Based Laboratory

Performing experimental activities in a laboratory using the available equipment is not as straightforward as it may seem. In practice, conducting experiments can be challenging, and various factors can contribute to erroneous measurement results. One such factor is systematic errors, which occur due to inaccuracies in the measurement tools used. Additionally, error sources from external factors can also influence the measurement results. It is important to be aware of these potential errors and take appropriate measures to minimize their impact during experimental procedures. Tracker software is a valuable tool that can enhance the accuracy of experimental activities conducted in laboratories. This software assists in generating more precise data by tracking and analyzing various elements of the experiment. By utilizing tracker software, researchers can closely monitor the movement and behavior of objects, making it easier to measure and record data accurately. This technology plays a significant role in improving the reliability and efficiency of experimental procedures in the laboratory setting. From the study's objectives, it can be deduced that the restitution coefficient values obtained through manual data collection for the bekel ball are 𝑒 = 0.5136 ± 0.004214, and for the ping pong ball, it is 𝑒 = 0.4566 ± 0.01736. On the other hand, when using tracker software for data collection, the restitution coefficient value for the bekel ball is 𝑒 = 0.5397 ± 0.0008731, and for the ping pong ball, it is 𝑒 = 0.5115 ± 0.001154.

Revising data collection methodology - evidence from the Australian financial sector

Time requirements of data collection account for a significant portion of the total time required to provide financial advice. This research applies data collection software to the financial planning process seeking to identify benefits that may assist to reduce rising barriers of accessing financial advice. Experimental two-phase study seeks qualitative input surrounding problematic themes before quantitative input records impacts of data collection software use. The research seeks to evidence beneficial impacts that software use may have on the data collection requirements by way of comparison between traditional and software methodologies in Australian professional practice. Respondents were asked to complete data collection inputs using both traditional and digital methods with metrics recorded throughout the process. Input from 112 consumers and 71 practising advisers were recorded. Results suggest the use of software may decrease time taken to complete task and often results in higher levels of data accuracy. Traditional methods were affiliated with extended time periods and lower levels of data accuracy. Results aim to evolve methods of traditional practise within the financial sector. The research provides original contributions to financial planning literature by examining the potential impact data collection methodologies may have on reducing barriers to accessing financial services in Australia.

Applying 3D ED/MicroED workflows toward the next frontiers.

We report on the latest advancements in Microcrystal Electron Diffraction (3D ED/MicroED), as discussed during a symposium at the National Center for CryoEM Access and Training housed at the New York Structural Biology Center. This snapshot describes cutting-edge developments in various facets of the field and identifies potential avenues for continued progress. Key sections discuss instrumentation access, research applications for small molecules and biomacromolecules, data collection hardware and software, data reduction software, and finally reporting and validation. 3D ED/MicroED is still early in its wide adoption by the structural science community with ample opportunities for expansion, growth, and innovation.

IJCM_87A: Immunization status among children living in streets of Chennai - A cross sectional study

Background: The homeless population of Chennai is the people who are living in the platforms, bus stands and other unused buildings in Chennai for more than three generations. Many of them lack basic amenities for their living, which makes them a vulnerable population especially the women and children. The children especially are prone to many communicable diseases as a result of their way of living Objective: To estimate the immunization status among the children of homeless population in Chennai. Methodology: The information about the clusters of homeless population is obtained from the Greater Chennai Corporation enumeration. Individual clusters are mapped in Zone 5 of Greater Chennai Corporation. Almost all the mothers of children of age up to 5 years are interviewed. Data collected using Epicollect5 data collection software. Results: The mean age of the children was 34.59 + 17.73 months. 45.4% were male children and 54.6% were female children.98.9% of the mothers registered their pregnancy and 100% delivered in the public facility. 93.4% registered their birth. 87.4 % of the children got enrolled in Anganwadis. 90.5% of the children were immunized up to age. Only one child (0.4%) didn’t get the birth dose of BCG. 18 children (6.6%) didn’t get their Measles Rubella vaccine not even once. 28 children (10.3%) didn’t get their second dose of Measles Rubella vaccine and Diptheria Pertussis Tetanus vaccine. Conclusion: The immunization coverage among homeless children upto 5 years is 90.5%. The coverage has to be strengthened in order to improve their quality of life

Optimal 3D angular sampling with applications to cryo-EM problems

The goal of cryo-EM experiments in the biological sciences is to determine the atomic structure of a molecule and deduce insights into its functions and mechanisms. Despite improvements in instrumentation for data collection and new software algorithms, in most cases, individual atoms are not resolved. Model building of proteins, nucleic acids, or molecules in general, is feasible from the experimentally determined density maps at resolutions up to the range of 3–4 Angstroms. For lower-resolution maps or parts of maps, fitting smaller structures obtained by modelling or experimental techniques with higher resolution is a way to resolve the issue. In practice, we have an atomic structure, generate its density map at a given resolution, and translate/rotate the map within a region of interest in the experimental map, computing a measure-of-fit score with the corresponding areas of the experimental map. This procedure is computationally intensive since we work in 6D space. An optimal ordered list of rotations will reduce the angular error and help to find the best-fitting positions faster for a coarse global search or a local refinement. It can be used for adaptive approaches to stop fitting algorithms earlier once the desired accuracy has been achieved. We demonstrate how the performance of some fitting algorithms can be improved by grouping sets of rotations. We present an approach to generate more efficient 3D angular sampling, and provide the computer code to generate lists of optimal orientations for single and grouped rotations and the lists themselves.

Biobehavioral survey using time location sampling among female sex workers living in Ghana in 2020.

The HIV epidemic in Ghana is characterized as a mix of a low-level generalized epidemic with significant contributions from transmission among female sex workers (FSW) and their clients. This study seeks to identify and describe key characteristics and sexual behaviors of FSW and estimate the prevalence of HIV, syphilis, gonorrhea, chlamydia, and hepatitis B virus (HBV) among FSW in Ghana. A total of 7,000 FSW were recruited for the study using Time Location Sampling (TLS) approach with 5,990 (85.6%) participants completing both biological and the behavioral aspects of the study. A structured questionnaire was administered to respondents to assess several factors, such as background characteristics, sexual risk behaviors, condom usage, HIV/AIDS knowledge, opinions, and attitudes. Trained staff conducted face-to-face interviews using mobile data collection software (REDCap) after provision of specimens for HIV and STI testing. Descriptive statistics such as medians, ranges, charts, and percentages are performed and presented. Also included, are bivariate analyses to establish relationships between FSW type and other relevant characteristics of the study. Among the 7,000 (100%) FSW sampled from all regions, 6,773 took part in the behavioral and 6,217 the biological. There were 783 (11.2%) respondents who took part only in the behavioral and 227 (3.2%) only in the biological. Most were young, with a median age of 26 years, majority had never been married or were widowed/divorced and a quarter had no education or had only primary education. Majority (74.8%) of FSW first sold sex at age 25 years or less with a median age of 20 years. Most (84.8%) of the FSW indicated that they entered sex work for money, either for self or family and had an average of eleven (11) sexual partners per week. More than half (55.2%) of the FSW were new entrants who had been in sex work for less than 5 years before the study. Consistent condom use with paying clients was generally unsatisfactory (71%), and was however, very low (24%) with their intimate partners or boyfriends. Only about half (54.6%) of FSW have been exposed to HIV prevention services in the last three months preceding the survey, and this varies across regions. Overall, comprehensive knowledge about HIV and AIDS was low. Only 35% of FSW had comprehensive knowledge. HIV prevalence was 4.6% and was higher among seaters (brothel-based) and older FSW who had been sex work for a longer period. The HIV prevalence from the previous bio-behavioral survey (BBS) in 2015 and 2011 were estimated to be 6.9 and 11.1%, respectively. Compared to the results from the previous studies, the findings give an indication that Ghana is making significant progress in reducing the burden of HIV among FSW in the country. However, risky behaviors such as low consistent condom use, low coverage of HIV services across the regions, and low comprehensive knowledge could reverse the gains made so far. Immediate actions should be taken to expand coverage of HIV services to all locations. Efforts must be made to reach out to the new entrants while also addressing strongly held myths and misconceptions about HIV.

Exploring Mental Health Outcome Variables in Outdoor Adventure and Experiential Education

Background: The COVID-19 pandemic has changed many facets of outdoor adventure and experiential education (OAEE) programs. Using past literature, four variables represent important student outcome variables associated with OAEE programs. Purpose: This study examined the effects of participation in an OAEE program on levels of anxiety, depression, hope, and resilience. Methods: This study used online data collection software with a 30-item inventory to measure the selected variables. Using a retrospective predesign, data were collected and analyzed using repeated measure t-tests. Findings: Results suggest that OAEE programs can effectively enhance an individual's ability to cope with anxiety and hopelessness while enhancing their levels of resilience.

ЭЛЕКТРОННЫЕ СИСТЕМЫ ДЛЯ МОНИТОРИНГА И КОНТРОЛЯ ОКРУЖАЮЩЕЙ СРЕДЫ

The article discusses modern electronic systems for environmental monitoring and control. It describes the historical development of technologies, modern sensors, wireless networks and IoT, satellite technologies, as well as software for data collection and analysis. Examples of the use of such systems for monitoring air, water and soil are given. Technical, economic and legal problems and challenges, as well as prospects for further development and integration of these technologies are considered.

Life, death, and statins: association of statin prescriptions and survival in older general practice patients.

This study serves as an exemplar to demonstrate the scalability of a research approach using survival analysis applied to general practice electronic health record data from multiple sites. Collection of these data, the subsequent analysis, and the preparation of practice-specific reports were performed using a bespoke distributed data collection and analysis software tool. Statins are a very commonly prescribed medication, yet there is a paucity of evidence for their benefits in older patients. We examine the relationship between statin prescriptions for general practice patients over 75 and all-cause mortality. We carried out a retrospective cohort study using survival analysis applied to data extracted from the electronic health records of five Australian general practices. The data from 8025 patients were analysed. The median duration of follow-up was 6.48 years. Overall, 52015 patient-years of data were examined, and the outcome of death from any cause was measured in 1657 patients (21%), with the remainder being censored. Adjusted all-cause mortality was similar for participants not prescribed statins versus those who were (HR 1.05, 95% CI 0.92-1.20, P = 0.46), except for patients with diabetes for whom all-cause mortality was increased (HR = 1.29, 95% CI: 1.00-1.68, P = 0.05). In contrast, adjusted all-cause mortality was significantly lower for patients deprescribed statins compared to those who were prescribed statins (HR 0.81, 95% CI 0.70-0.93, P < 0.001), including among females (HR = 0.75, 95% CI: 0.61-0.91, P < 0.001) and participants treated for secondary prevention (HR = 0.72, 95% CI: 0.60-0.86, P < 0.001). This study demonstrated the scalability of a research approach using survival analysis applied to general practice electronic health record data from multiple sites. We found no evidence of increased mortality due to statin-deprescribing decisions in primary care.

Deep belief networks in understanding and predicting changes in students’ political attitudes

Abstract Leveraging data collection software, this study gathered and preprocessed text data reflecting students’ political attitudes across five dimensions: political cognition, ruling party cognition, positive political emotion, negative political emotion, and political behavioral tendency. The processed data were subsequently stored in Excel format. These dimensions of change in students’ political attitudes served as inputs for a deep belief network (DBN) model, with the changes in attitudes being the outputs. The model’s parameters were meticulously tuned to optimize its predictive capabilities, aimed at effectively constructing a prediction model for shifts in students’ political attitudes using the deep belief network. To refine the model’s parameters and minimize errors during inverse fine-tuning, the chimpanzee algorithm (ChOA) was employed. This novel approach, termed ChOA-DBN, facilitated the successful construction of the predictive model for students’ political attitude changes. The model’s efficacy was assessed using the collected data on students’ political attitudes. Notably, the DBN model optimized via the chimpanzee algorithm demonstrated robust predictive performance, particularly when processing sample points exhibiting significant changes in students’ political attitudes (ranging from 20 to 45). The model’s predictions predominantly fell within a ±15% error margin. This research not only showcases the accuracy of the ChOA-DBN model in predicting alterations in students’ political attitudes but also underscores its potential contribution to fostering the development of accurate political perspectives among students.