bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementation of nurse’s clinical competency: A scoping review
Authors: Suarmayasa I Nengah , Swarjana I Ketut , Adi Satriani Ni Luh , Noviana Sagitarini Putu
Published: April 2024

Background: Nursing care provided to patients, especially in hospitals, is expected to be of high quality, and its implementation is in accordance with the nurse's clinical competence.

Objectives: This scoping review aimed to assess the implementation of the clinical competence of nurses in hospitals so that a clear picture of the implementation of these competencies is obtained. In addition, this study can be evidence-based and related to implementing these clinical competencies.

Methods: This literature review used PICO framework to develop articles questions (P: nurses, I: not applicable, C: not applicable, and O: application of clinical nursing competency). Articles search for literature review was conducted during April and May 2023.

This study used Pubmed and ScienceDirect Databases and other sources. The keywords that used in this scoping review was “nursing competency” OR “clinical nursing competency” AND “evaluation” OR “implementation” AND “hospital”.

Results: There were 1,150 articles from the search results, but only seven were included for review. One article is a descriptive comparative study using a qualitative approach, and six articles are cross-sectional studies. The articles are publications within five years (2019-2023). In its implementation, the average clinical competency of nurses is at a low to moderate level, and only one study found was at high nurse competency. The results of the supervisor's clinical competency assessment were significantly lower than those assessed by oneself and the group. In addition, the nurse competency level was moderate, and there was no significant difference in the clinical competency of nurses before and during the COVID-19 pandemic.
Conclusions: The implementation of nurses' clinical competence has yet to be optimal, so hospital management needs to improve nurses' clinical competence so that nurses can provide higher quality and professional nursing care in the hospital.
Evaluation of a New Telemedicine System for Early Detection of Cardiac Instability in Patients With Chronic Heart Failure: Real-Life Out-of-Hospital Study
Authors: Urien Jean Marie , Berthelot Emmanuelle , Raphael Pierre , Moine Thomas , Lopes Marie Emilie , Assayag Patrick , Jourdain Patrick
Published: April 2024

Background

For a decade, despite results from many studies, telemedicine systems have suffered from a lack of recommendations for chronic heart failure (CHF) care because of variable study results. Another limitation is the hospital-based architecture of most telemedicine systems. Some systems use an algorithm based on daily weight, transcutaneous oxygen measurement, and heart rate to detect and treat acute heart failure (AHF) in patients with CHF as early on as possible.

Objective

The aim of this study is to determine the efficacy of a telemonitoring system in detecting clinical destabilization in real-life settings (out-of-hospital management) without generating too many false positive alerts.

Methods

All patients self-monitoring at home using the system after a congestive AHF event treated at a cardiology clinic in France between March 2020 and March 2021 with at least 75% compliance on daily measurements were included retrospectively. New-onset AHF was defined by the presence of at least 1 of the following criteria: transcutaneous oxygen saturation loss, defined as a transcutaneous oxygen measurement under 90%; rise of cardiac frequency above 110 beats per minute; weight gain of at least 2 kg; and symptoms of congestive AHF, described over the phone. An AHF alert was generated when the criteria reached our definition of new-onset acute congestive heart failure (HF).

Results

A total of 111 consecutive patients (n=70 men) with a median age of 76.60 (IQR 69.5-83.4) years receiving the telemonitoring system were included. Thirty-nine patients (35.1%) reached the HF warning level, and 28 patients (25%) had confirmed HF destabilization during follow-up. No patient had AHF without being detected by the telemonitoring system. Among incorrect AHF alerts (n=11), 5 patients (45%) had taken inaccurate measurements, 3 patients (27%) had supraventricular arrhythmia, 1 patient (9%) had a pulmonary bacterial infection, and 1 patient (9%) contracted COVID-19. A weight gain of at least 2 kg within 4 days was significantly associated with a correct AHF alert (P=.004), and a heart rate of more than 110 beats per minute was more significantly associated with an incorrect AHF alert (P=.007).

Conclusions

This single-center study highlighted the efficacy of the telemedicine system in detecting and quickly treating cardiac instability complicating the course of CHF by detecting new-onset AHF as well as supraventricular arrhythmia, thus helping cardiologists provide better follow-up to ambulatory patients.
Digital Self-Management Platform for Adult Asthma: Randomized Attention-Placebo Controlled Trial (Preprint)
Authors: Kandola Aaron , Edwards Kyra , Straatman Joris , Dührkoop Bettina , Hein Bettina , Hayes Joseph
Published: April 2024

BACKGROUND

Asthma is one of the most common chronic conditions worldwide, with a substantial individual and health care burden. Digital apps hold promise as a highly accessible, low-cost method of enhancing self-management in asthma, which is critical to effective asthma control.

OBJECTIVE

We conducted a fully remote randomized controlled trial (RCT) to assess the efficacy of juli, a commercially available smartphone self-management platform for asthma.

METHODS

We conducted a pragmatic single-blind, RCT of juli for asthma management. Our study included participants aged 18 years and older who self-identified as having asthma and had an Asthma Control Test (ACT) score of 19 or lower (indicating uncontrolled asthma) at the beginning of the trial. Participants were randomized (1:1 ratio) to receive juli for 8 weeks or a limited attention-placebo control version of the app. The primary outcome measure was the difference in ACT scores after 8 weeks. Secondary outcomes included remission (ACT score greater than 19), minimal clinically important difference (an improvement of 3 or more points on the ACT), worsening of asthma, and health-related quality of life. The primary analysis included participants using the app for 8 weeks (per-protocol analysis), and the secondary analysis used a modified intention-to-treat (ITT) analysis.

RESULTS

We randomized 411 participants between May 2021 and April 2023: a total of 152 (37%) participants engaged with the app for 8 weeks and were included in the per-protocol analysis, and 262 (63.7%) participants completed the week-2 outcome assessment and were included in the modified ITT analysis. Total attrition between baseline and week 8 was 259 (63%) individuals. In the per-protocol analysis, the intervention group had a higher mean ACT score (17.93, SD 4.72) than the control group (16.24, SD 5.78) by week 8 (baseline adjusted coefficient 1.91, 95% CI 0.31-3.51; P=.02). Participants using juli had greater odds of achieving or exceeding the minimal clinically important difference at 8 weeks (adjusted odds ratio 2.38, 95% CI 1.20-4.70; P=.01). There were no between group differences in the other secondary outcomes at 8 weeks. The results from the modified ITT analyses were similar.

CONCLUSIONS

Users of juli had improved asthma symptom control over 8 weeks compared with users of a version of the app with limited functionality. These findings suggest that juli is an effective digital self-management platform that could augment existing care pathways for asthma. The retention of patients in RCTs and real-world use of digital health care apps is a major challenge.

CLINICALTRIAL

International Standard Randomised Controlled Trial Number (ISRCTN) registry ISRCTN87679686; https://www.isrctn.com/ISRCTN87679686
Effectiveness of a Smartphone App–Based Intervention With Bluetooth-Connected Monitoring Devices and a Feedback System in Heart Failure (SMART-HF Trial): Randomized Controlled Trial (Preprint)
Authors: Yoon Minjae , Lee Seonhwa , Choi Jah Yeon , Jung Mi-Hyang , Youn Jong-Chan , Shim Chi Young , Choi Jin-Oh , Kim Eung Ju , Kim Hyungseop , Yoo Byung-Su , Son Yeon Joo , Choi Dong-Ju
Published: April 2024

BACKGROUND

Current heart failure (HF) guidelines recommend a multidisciplinary approach, discharge education, and self-management for HF. However, the recommendations are challenging to implement in real-world clinical settings.

OBJECTIVE

We developed a mobile health (mHealth) platform for HF self-care to evaluate whether a smartphone app–based intervention with Bluetooth-connected monitoring devices and a feedback system can help improve HF symptoms.

METHODS

In this prospective, randomized, multicenter study, we enrolled patients 20 years of age and older, hospitalized for acute HF, and who could use a smartphone from 7 tertiary hospitals in South Korea. In the intervention group (n=39), the apps were automatically paired with Bluetooth-connected monitoring devices. The patients could enter information on vital signs, HF symptoms, diet, medications, and exercise regimen into the app daily and receive feedback or alerts on their input. In the control group (n=38), patients could only enter their blood pressure, heart rate, and weight using conventional, non-Bluetooth devices and could not receive any feedback or alerts from the app. The primary end point was the change in dyspnea symptom scores from baseline to 4 weeks, assessed using a questionnaire.

RESULTS

At 4 weeks, the change in dyspnea symptom score from baseline was significantly greater in the intervention group than in the control group (mean –1.3, SD 2.1 vs mean –0.3, SD 2.3; P=.048). A significant reduction was found in body water composition from baseline to the final measurement in the intervention group (baseline level mean 7.4, SD 2.5 vs final level mean 6.6, SD 2.5; P=.003). App adherence, which was assessed based on log-in or the percentage of days when symptoms were first observed, was higher in the intervention group than in the control group. Composite end points, including death, rehospitalization, and urgent HF visits, were not significantly different between the 2 groups.

CONCLUSIONS

The mobile-based health platform with Bluetooth-connected monitoring devices and a feedback system demonstrated improvement in dyspnea symptoms in patients with HF. This study provides evidence and rationale for implementing mobile app–based self-care strategies and feedback for patients with HF.

CLINICALTRIAL

ClinicalTrials.gov NCT05668000; https://clinicaltrials.gov/study/NCT05668000
Marital Self-Disclosure Intervention for the Fear of Cancer Recurrence in Chinese Patients With Gastric Cancer: Protocol for a Quasiexperimental Study (Preprint)
Authors: Zhao Haiyan , Zhou Ye , Che Chong Chin , Chong Mei Chan , Zheng Yu , Hou Yuzhu , Chen Canjuan , Zhu Yantao
Published: April 2024

BACKGROUND

Patients with gastric cancer experience different degrees of fear of cancer recurrence. The fear of cancer recurrence can cause and worsen many physical and psychological problems. We considered the “intimacy and relationship processes in couples’ psychosocial adaptation” model.

OBJECTIVE

The study aims to examine the effectiveness of a marital self-disclosure intervention for improving the level of fear of cancer recurrence and the dyadic coping ability among gastric cancer survivors and their spouses.

METHODS

This is a quasiexperimental study with a nonequivalent (pretest-posttest) control group design. The study will be conducted at 2 tertiary hospitals in Taizhou City, Jiangsu Province, China. A total of 42 patients with gastric cancer undergoing chemotherapy and their spouses will be recruited from each hospital. Participants from Jingjiang People’s Hospital will be assigned to an experimental group, while participants from Taizhou People’s Hospital will be assigned to a control group. The participants in the experimental group will be involved in 4 phases of the marital self-disclosure (different topics, face-to-face) intervention. Patients will be evaluated at baseline after a diagnosis of gastric cancer and reassessed 2 to 4 months after baseline. The primary outcome is the score of the Fear of Progression Questionnaire-Short Form (FoP-Q-SF) for patients. The secondary outcomes are the scores of the FoP-Q-SF for partners and the Dyadic Coping Inventory.

RESULTS

Research activities began in October 2022. Participant enrollment and data collection began in February 2023 and are expected to be completed in 12 months. The primary results of this study are anticipated to be announced in June 2024.

CONCLUSIONS

This study aims to assess a marital self-disclosure intervention for improving the fear of cancer recurrence in Chinese patients with gastric cancer and their spouses. The study is likely to yield desirable positive outcomes as marital self-disclosure is formulated based on evidence and inputs obtained through stakeholder interviews and expert consultation. The study process will be carried out by nurses who have received psychological training, and the quality of the intervention will be strictly controlled.

CLINICALTRIAL

ClinicalTrials.gov NCT05606549; https://clinicaltrials.gov/study/NCT05606549

INTERNATIONAL REGISTERED REPORT

DERR1-10.2196/55102
Challenges to rehabilitation services in Sub-Saharan Africa from a user, health system and service provider perspective: A scoping review (Preprint)
Authors: Cyuzuzo Callixte , Dukuzimana Marie Josee , Muhire Clement , Sheldon Ames Mathew , Ngwakongnwi Emmanuel
Published: April 2024

BACKGROUND

Rehabilitation aims to restore and optimize the functioning of impaired systems. It is an integral part of universal health coverage and access to it is a human right for people with disabilities. It is important to identify the key challenges to rehabilitation services in Sub-Saharan Africa (SSA) from a user, health system and service provider perspective

OBJECTIVE

To identify the key challenges to rehabilitation services in Sub-Saharan Africa (SSA) from a user, health system and service provider perspective

METHODS

This scoping review was conducted in accordance with the five steps framework proposed by Arksey and O'Malley and a comprehensive electronic search was run to identify published articles on rehabilitation services in Sub-Saharan Africa. Of all 131 articles retrieved in the searches, 83 articles were assessed for eligibility and 15 papers met the inclusion criteria were considered

RESULTS

The results showed that people with disabilities in Sub-Saharan Africa face multifactorial challenges to access rehabilitation services. Poor access to rehabilitation services is associated with less attention given to rehabilitation by governments which led to less funding, cultural and social beliefs, less and poorly equipped rehabilitation centers, failure of the health systems, lack of trainings to professionals, logistical and financial constraints.This review also revealed that digital rehabilitation reduced costs and improved access to services in hard-to-reach geographical areas. However, it faced connectivity issues, inaccessibility to technology and lack of technical knowledge, lack of privacy and ethical challenges

CONCLUSIONS

This review concludes that people with disabilities face multifactorial challenges to access rehabilitation services in SSA. It is therefore critical to address these challenges to optimize patients’ health outcomes and offer better rehabilitation services.
Information Regarding Dermatology as Seen on Social Media Platform TikTok (Preprint)
Authors: Nigro Alexandra Rose , Osman Alim , Saal Ryan Charles , Smith Robert James
Published: April 2024

UNSTRUCTURED

Introduction: With Americans spending over two hours daily on social media, platforms like TikTok have become prevalent sources for healthcare information. This study evaluates the quality and quantity of dermatology-related content on TikTok.

Methods: In November 2022, TikTok was searched using dermatology-related keywords. Accounts with ≥50% dermatology content were selected. An engagement score was calculated for each account, and the top 10 were further analyzed using DISCERN criteria. The Kruskal-Wallis and Mann-Whitney U tests, along with a two-tailed independent t-test, were employed for statistical analysis.

Results: Out of 22,411 videos, 17,085 (76.3%) were informational. Dermatologists led in paid sponsorship videos (65% of 502 videos). Significant differences in engagement scores were found across different provider types, with medical clinics and aestheticians receiving the highest scores. Dermatologist-run accounts had higher views and comments but similar overall DISCERN scores to non-dermatologist accounts. However, dermatologists better referenced treatment uncertainty and explanations, while non-dermatologists more frequently discussed treatment risks.

Discussion: The substantial engagement with dermatology content on TikTok highlights its role as a significant information source, albeit with generally low educational quality. Given the high consumer trust in TikTok, dermatologists face an ethical obligation to improve the accuracy and quality of their online content to counteract potential misinformation.
A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review (Preprint)
Authors: Wang Zhaoxin , Yang Wenwen , Li Zhengyu , Rong Ze , Wang Xing , Han Jincong , Ma Lei
Published: April 2024

BACKGROUND

Stroke is a leading cause of death and disability worldwide. Rapid and accurate diagnosis is crucial for minimizing brain damage and optimizing treatment plans.

OBJECTIVE

This review aims to summarize the methods of artificial intelligence (AI)–assisted stroke diagnosis over the past 25 years, providing an overview of performance metrics and algorithm development trends. It also delves into existing issues and future prospects, intending to offer a comprehensive reference for clinical practice.

METHODS

A total of 50 representative articles published between 1999 and 2024 on using AI technology for stroke prevention and diagnosis were systematically selected and analyzed in detail.

RESULTS

AI-assisted stroke diagnosis has made significant advances in stroke lesion segmentation and classification, stroke risk prediction, and stroke prognosis. Before 2012, research mainly focused on segmentation using traditional thresholding and heuristic techniques. From 2012 to 2016, the focus shifted to machine learning (ML)–based approaches. After 2016, the emphasis moved to deep learning (DL), which brought significant improvements in accuracy. In stroke lesion segmentation and classification as well as stroke risk prediction, DL has shown superiority over ML. In stroke prognosis, both DL and ML have shown good performance.

CONCLUSIONS

Over the past 25 years, AI technology has shown promising performance in stroke diagnosis.
The First Look at Code-Free Custom GPTs in Medicine: An Ophthalmology Perspective (Preprint)
Authors: Aykut Aslan , Sarigul Sezenoz Almila
Published: April 2024

BACKGROUND

OpenAI recently introduced the ability to create custom GPTs in its advanced model (GPT-4). They do not need any coding knowledge; therefore, clinicians can easily create them without any programming experience. Since they have plain text customization functionality and information expansion capabilities with file upload, they can overcome some drawbacks of the standard GPT-4.

OBJECTIVE

Our aim was to use ophthalmologic GPTs as a base and examine their general properties, advantages and disadvantages, and potential practical uses in detail.

METHODS

Data collection took place on January 20 and 21, 2024, and custom GPTs were found by entering ophthalmology keywords into the “Explore GPTS” section of the website. General and specific features of custom GPTs were recorded, such as knowledge other than GPT-4 training data. The instruction and description sections, where users can get the most information about a custom GPT, were analyzed for compatibility using the Likert scale. We analyzed two custom GPTs with the highest Likert score in detail. We attempted to create a malicious GPT to test security features.

RESULTS

We analyzed 22 ophthalmic custom GPTs, of which 55% were for general use and the most common subspecialty was glaucoma (18%). Over half (55%) contained knowledge other than GPT-4 training data. The representation of the instructions through the description was between “Moderately representative” and “Very representative” with a median Likert score of 3.5 (IQR 3.0 – 4.0). The instruction word count was significantly associated with Likert scores (P = 0.03, 95% CI, 0.050-0.739). Instruction length for high Likert score description was generally between 241 and 338 words. Tested custom GPTs demonstrated potential for specific conversational tone, information, retrieval and combining knowledge from an uploaded source. With these security settings creating a malicious GPT was possible.

CONCLUSIONS

This is the first study to examine the GPT store for a medical field. Publicly available custom GPTs for ophthalmology are available in the GPT store. Studies are needed to see their use in other medical areas. Custom GPTs can be put into practice immediately. Reliable GPTs can be more useful for a specific aim than classical GPT-4. However, more detailed studies are needed to test their capabilities. The security features currently appear to be rather limited. It may be helpful for the user to review the instruction section before using a custom GPT.

CLINICALTRIAL

this is not a trial study
Large Language Models May Help Patients Understand Peer-Reviewed Scientific Articles About Ophthalmology: Development and Usability Study (Preprint)
Authors: Kianian Reza , Sun Deyu , Rojas-Carabali William , Agrawal Rupesh , Tsui Edmund
Published: April 2024

BACKGROUND

Adequate health literacy has been shown to be important for the general health of a population. To address this, it is recommended that patient-targeted medical information is written at a sixth-grade reading level. To make well-informed decisions about their health, patients may want to interact directly with peer-reviewed open access scientific articles. However, studies have shown that such text is often written with highly complex language above the levels that can be comprehended by the general population. Previously, we have published on the use of large language models (LLMs) in easing the readability of patient-targeted health information on the internet. In this study, we continue to explore the advantages of LLMs in patient education.

OBJECTIVE

This study aimed to explore the use of LLMs, specifically ChatGPT (OpenAI), to enhance the readability of peer-reviewed scientific articles in the field of ophthalmology.

METHODS

A total of 12 open access, peer-reviewed papers published by the senior authors of this study (ET and RA) were selected. Readability was assessed using the Flesch-Kincaid Grade Level and Simple Measure of Gobbledygook tests. ChatGPT 4.0 was asked “I will give you the text of a peer-reviewed scientific paper. Considering that the recommended readability of the text is 6th grade, can you simplify the following text so that a layperson reading this text can fully comprehend it? - Insert Manuscript Text -”. Appropriateness was evaluated by the 2 uveitis-trained ophthalmologists. Statistical analysis was performed in Microsoft Excel.

RESULTS

ChatGPT significantly lowered the readability and length of the selected papers from 15th to 7th grade (P<.001) while generating responses that were deemed appropriate by expert ophthalmologists.

CONCLUSIONS

LLMs show promise in improving health literacy by enhancing the accessibility of peer-reviewed scientific articles and allowing the general population to interact directly with medical literature.
Current Status of Transcranial Magnetic Stimulation for Treating Depression: A Visualization and Bibliometric Analysis (Preprint)
Authors: Zhang Anren , xing Jia-jia , wang Junyu , Liu Xingyu , xiang Wu , Liu Jiancheng
Published: April 2024

BACKGROUND

Background: Depression is the most disabling and prevalent psychiatric disorder; transcranial magnetic stimulation (TMS) is widely used in the treatment of depression because of its remarkable efficacy.

OBJECTIVE

Objective: To investigate the current status, hotspots and frontiers of this research field, and advance the research on TMS for treating depression, this paper provides a visualization and bibliometric analysis of studies related to TMS for depression.

METHODS

Methods: Literature related to TMS for depression was searched based on the Web of science core database from database creation to November 19, 2023. Cite Space 6.2.R4 and VOS viewer 1.6.20 were used to analyze the relevant literature in terms of annual publications, authors, institutions and international collaborations, co-cited literature, co-cited authors, co-cited journals, and keywords.

RESULTS

Results: A total of 4218 papers were included. The overall trend of the number of publications in this research area is increasing year by year. Research fervor is expected to continue to increase. The United States is in the top position both in terms of the number of publications and centrality. Although Canada ranks third in terms of the number of articles published, its centrality is not high. Based on the keyword co-occurrence analysis, the research hotspots in this field were clarified as efficacy, dorsolateral prefrontal cortex, prefrontal cortex, motor cortex and so on. In recent years, the keywords that have burst out and have continued until now are the treatment effectiveness, reliability, frequency, and theta burst treatment modality of TMS. These keywords may become hot spots for future research.

CONCLUSIONS

Conclusion: Our findings suggested that studies related to the field of TMS depression are increasingly emphasized by researchers, and the United States is an international leader in this research area. In the future, cooperation between countries should be strengthened. Meanwhile, it is important to use various imaging-assisted localization tools to carry out multi-center and large-sample clinical studies of individualized treatment parameters for TMS.
Obesitas sebagai faktor risiko penurunan aktivitas fisik vs. penurunan aktivitas fisik sebagai faktor risiko obesitas
Authors: Burhan Fatimah Zahra , Susetyowati Susetyowati , Julia Madarina
Published: April 2024

Obesity as a risk factor for decreased physical activity vs. decreased physical activity as a risk factor for obesityBackground: The worldwide prevalence of obesity keeps increasing. The increase is closely associated with the worldwide increase in physical inactivity. Obesity and inactivity have formed a vicious cycle that is difficult to disentangle, inactivity precedes obesity or the other way around. Objective: This study aimed to assess the association between obesity and physical inactivity in Indonesian population aged 18-65 years. Methods: This was a longitudinal study using the Indonesian Family Life Survey data in 2007 (IFLS 4) and 2014 (IFLS 5). The sample was 16,166 respondents aged 18-65 years who had data on physical activity, age, sex, weight, and height in both IFLS 4 and 5. Results: The prevalence of obesity increased as our subjects became older, from 25.5% in 2007 to 38.9% in 2014. At the same time, the prevalence of sedentary lifestyles increased from 29.8% to 43.0%. Obese individuals had a higher risk of decreasing their activity level, with RR (95%CI) of 1.27 (1.23-1.31), p<0.001. Compared to women, men were less likely to decrease their activity level, RR (95%CI) of 0.91 (0.89-0.94), p<0.001. Individuals with lower education were also less likely to decrease their activity level, RR (95%CI) of 0.94 (0.90-0.98), p<0.001. The decrease in physical activity was a risk factor for obesity observed in later IFLS, OR (95%CI) of 1.21 (1.13-1.29), p<0.001. Conclusions:  Obesity was a risk factor for the decrease in physical activity, while the decrease in physical activity was also a risk factor for later obesity. Both conditions indeed formed a vicious cycle
Architectural Patterns in Android Development: Comparing MVP, MVVM, and MVI
Authors: Vijaywargi Ayush , Boddapati Uchinta Kumar
Published: April 2024

Abstract: This technical article provides an in-depth exploration of three prominent architectural patterns in Android development: Model-View-Presenter (MVP), Model-View-ViewModel (MVVM), and the more recent Model-View-Intent (MVI). By dissecting the core components, advantages, and trade-offs of each pattern through the lens of a hypothetical "Jetpack Composer" app, the article aims to provide developers with a comprehensive understanding of their suitability for different application scenarios. The MVP pattern separates the application's data layer from the UI, promoting maintainability and testability. The MVVM pattern, tailored for frameworks supporting two-way data binding, facilitates cleaner UI code and simplifies unit testing. The MVI pattern, well-suited for reactive programming environments, enforces a unidirectional data flow, aiding in predictable state management while introducing additional complexity. Through comparative analysis and examination of real-world examples, this article equips developers with the knowledge and insights necessary to navigate the architectural landscape of Android development, enabling informed decisions that align with project requirements and development philosophies, ultimately leading to more maintainable, scalable, and robust Android applications.
Advances in Speech Emotion Recognition and Analysis: A Review of Applied Machine Learning Methodologies
Authors: Kumar Ankit , Singh Kshitiz , Sharma Anmol , Gupta Sachi
Published: April 2024

Abstract: The most important marketing tactics in the current environment is emotion detection based on individual’s interests, allowing extensive customization to cater to the varied needs of customers. For instance, contact centers may start playing music while a caller is on the line if they are agitated. A smart car that slows down when the driver is angry or scared is another illustration.The recognition of speech emotion has become a vital task in the field of computer science department . A very important aspect of human emotional state information is speech emotion that is the source of communication between human and computer interactions . The recognition of speech emotion is currently a very hot topic in the field of machine learning and deep learning and many systems have been build and are currently working on the recognition of these speech emotions using deep learning and neural networks algorithms. In this paper, various types of models and features like Mel-frequency Cepstral Coefficients (MFCC), Modulation spectral features (MSFs), Low-Level Descriptors(LLDs) for speech emotion recognition are categorized. Ultimately, the algorithms like recurrent neural network(RNN), support vector machine(SVM) used in different models are tabulated presenting their advantages and disadvantages along with their features and efficiency.
Enhanced Surveillance: Developing a Computer Vision-based CCTV Footage Analysis Tool for Improved Vehicle Number Plate Recognition
Authors: Khanna Ravi , Sahoo Shreyash Kumar , Maggu Mr. Sunil , Kalonia Ms. Seema , Kaushik Mr. Ajay Kumar
Published: April 2024

Abstract: Smart parking systems serve as integral components in augmenting the efficiency and sustainability of modern urban environments. Nonetheless, prevailing systems predominantly rely on sensors to monitor parking space occupancy, entailing substantial installation and maintenance costs while offering limited functionality in tracking vehicle movement within parking lots. To confront these challenges head-on, our solution introduces a multistage learning-based approach, capitalizing on the existing surveillance infrastructure within parking facilities and a meticulously curated dataset of Saudi license plates. Our approach amalgamates YOLOv5 for license plate detection, YOLOv8 for character detection, and a novel convolutional neural network architecture tailored for enhanced character recognition. We illustrate the superiority of our approach over single-stage methods, achieving an impressive overall accuracy of 96.1%, a notable advancement from the 83.9% accuracy of single-stage approaches. Furthermore, our solution seamlessly integrates into a web-based dashboard, facilitating real-time visualization and statistical analysis of parking space occupancy and vehicle movement, all accomplished with commendable time efficiency. This endeavor underscores the potential of leveraging existing technological resources to bolster the operational efficiency and environmental sustainability of smart cities. By harnessing the power of machine learning and computer vision, our work exemplifies a paradigm shift towards smarter and more adaptive urban infrastructure
Smart Automated Irrigation System using Wireless Technology
Authors: Ghadigaonkar Rajas , Barai Vedant , Kukreja Prof. Amit
Published: April 2024

Abstract: The need for agricultural output has surged due to the exponential rise of the world population, resulting in a strain on water supplies and a need for more effective irrigation systems. The goal of this project is to optimize water utilization in agricultural settings by presenting an automated and intelligent irrigation system. Based on current soil moisture levels, the system monitors and regulates irrigation using soil moisture sensors, an Arduino Nano, and a Raspberry Pi 3B+. By converting analog signals from the soil moisture sensor into digital data, the Arduino Nano serves as an analog-to-digital converter. This digital data is sent to the Raspberry Pi 3B+, which acts as the central control unit. A MOSFET is then triggered to activate a relay that is coupled to a 5V DC water pump when the moisture levels drop below a certain threshold. The system also has wireless connection, which enables remote control and monitoring via an Android application. Users have the ability to manually override the automatic system if needed, monitor the moisture content of the soil, and turn on or off the water pump. This feature improves the usability and flexibility of the system.
Borrow Barter Bridge - Hostel Necessities Web Platform
Authors: Garg Dr Rishabh , Mehra Yash , Singh Nand , Rathi Yash
Published: April 2024

Abstract: We propose the creation of a hostel sharing platform for such necessities in response to the previously described issue of frequent access to necessities in the two aforementioned hostel environments. This platform would fulfill demands ranging from laptops and hair straighteners to belts and kettles, allowing for borrowing and lending of things with a maximum 48-hour return time. In order to begin, each user must first create an account with their personal information, agree to a user policy stating that they are liable for any borrowed stuff, and take pictures of any lent or borrowed objects during the meeting. To penalize offenders, trust points will be awarded for adhering to the policy and banned for breaking it. The number of points taken will increase with each infraction, and offenders will be subject to a justification and fine period after being reinstated. By maximizing resource use and guaranteeing timely meeting of urgent requirements, this platform seeks to promote a culture of accountability and mutual aid while protecting user interests.
Master Face Generation Using Latent Variable Evolution in Face Recognition System
Authors: P Sumathi. , N Aravindh , M Aravinth , S Paari , Anto Ashik
Published: April 2024

Abstract: Face authentication is now widely used, especiallyon mobile devices, rather than authentication using a personal identification number or an unlock pattern, due to its convenience. It has thus become a tempting target for attackers using a presentation attack. Traditional presentationattacks use facial images or videos of the victim. Previous work has proven the existence of master faces, i.e., faces that matchmultiple enrolled templates in face recognition systems, and their existence extends the ability of presentation attacks. In this paper, we perform an extensive study on latent variable evolution (LVE), a method commonly used to generate master faces. We run an LVE algorithm for various scenarios and with more than one database and/or face recognition system tostudy the properties of the master faces and to understand inwhich conditions strong master faces could be generated. Moreover, through analysis, we hypothesize that master faces come from some dense areas in the embedding spaces of theface recognition systems. Last but not least, simulated presentation attacks using generated master faces generally preserve the false-matching ability of their original digital forms, thus demonstrating that the existence of master facesposes an actual threat.
The Mediating Effect of Social Capital in the Relationship between the Elderly's Efficacy in Using Digital Devices and Digital Information Capabilities
Authors:   Korean Association For Learner-Centered Curriculum And Instruction, Jang Kyungmi
Published: April 2024

Objectives The purpose of this study is to understand the effect of the elderly's efficacy in using digital devices on digital information capabilities and to empirically analyze the moderating effect of social capital on this effect.
Methods To this end, the second data of the 2022 Digital Information Gap Survey surveyed by the Korea Intelligence Information Society Agency were used, and the data of a total of 2,300 elderly people aged 55 or older were used. The analysis was conducted as follows using the IBM SPSS 26.0 statistical program. First, descriptive statistical analysis such as frequency, percentage, mean, standard deviation, skewness, and kurtosis was used to find out the distribution of survey respondents. Second, Pearson's moment correlation coefficient was analyzed to confirm the correlation between major variables. Third, multiple regression analysis was performed to analyze the moderating effect.
Results The results derived through the analysis are as follows. First, it was found that the elderly's efficacy in using digital devices had a positive effect on digital information capabilities. Second, it was found that social capital had a positive effect on digital information capabilities. Third, it was found that the social capital of the elderly controls the relationship between the efficacy of using digital devices and digital information capabilities.
Conclusions In this study, it was confirmed that social capital plays a control and buffer role in the effect of the elderly's efficacy in using digital devices on digital information capabilities. Based on the research results of this study, interest in social capital that controls the efficacy of using digital devices and digital information capabilities, and measures to strengthen them were discussed.
A study on the Experience and Recognition of Early Childhood Teachers in the Graduate School of Education in Global Citizenship Education
Authors:   Korean Association For Learner-Centered Curriculum And Instruction, Kwon Kyung-sook , Hwang In-ae , Lee Seung-suk
Published: April 2024

Objectives This study is about how the recognition of early childhood teachers enrolled in the graduate schools of education has changed throughout global citizenship education(GCE) classes and to explore GCE experience in teacher community activities.
Methods For this study, ‘A seminar to empowerment early childhood educations’ Global Citizenship Education’ had opened for 15 weeks in the first semester of 2022. This seminar was targeting 24 early childhood teachers who are studying S University graduate school of education, which is in the metropolitan area. All the data had been collected and analyzed by individual student reviews of a group interview, a field trip, a special lecture, and an open questionnaire made by previous students.
Results The global citizenship education(GCE) class experience is divided into ‘Start to change from me first’, ‘Recognition of togetherness’, and ‘Reciting diversity and putting oneself in someone else’s shoes. The meaning of GCE has been defined in three sections through this study: essential training for growth and mutual responsibility; basic education, which needs to be taught since infancy; and education for making a better world.
Conclusions The global citizenship education targeting early childhood teachers had the meaningful output of improving understanding of GCE and encouraging a global citizen mindset. Therefore, graduate school of education and higher education institutions need to organize a lecture to reinforce global citizenship education for current and future children’s educators. Additionally, there is a need for a support plan from various perspectives so that children’s educators can keep practicing GCE in the education field, such as training teachers and running a teacher community for GCE.
The Effects of Character Strength Journaling Program on Resilience and Subjective Well-being in Elementary School Students
Authors:   Korean Association For Learner-Centered Curriculum And Instruction, Lee Ji Hye , Kim Kwang Soo , Yang Gon Sung
Published: April 2024

Objectives The objective of this study is to investigate the effect of the character strength journaling program on resilience and subjective well-being in elementary school students.
Methods Pretest of resilience and subjective well-being was given out for two different classes of fifth grade in elementary school, located in Seoul. The researcher’s class of 19 students was set as experimental group and the other class of 19 students was set as control group. In the experimental group, the character strength journaling program was applied over 7 sessions for 6 weeks, and no treatment was given to the control group. After program both groups were subjected to resilience and subjective well-being post test. To verify the effectiveness of the program, analysis of Covariance(ANCOVA) was performed on the pre and post test. In addition to satisfaction of whole program and each session and observations of the researcher were analyzed to make up for the validity of the statistical analysis.
Results First, the character strength journaling program has a significant effect on improving resilience and subjective well-being. The experimental group showed a significant improvement in resilience and subjective well-being. Second, As a result of analyzing the program satisfaction and researchers' observations, children explored and recognized their signature strengths and were gradually able to use them in various situations in their daily lives through the character strength journaling program. In addition it was observed that subjective well-being and resilience were improved by experiencing positive results, recognizing themselves and those around them positively, and increasing confidence through utilizing signature strengths.
Conclusions The results of this study demonstrated that the character strength journaling program which focuses on the utilizing signature strengths can be a effective intervention to develop internal resources of students to overcome, prevent various difficulties occurring at school and improve well-being of students.
Exploring influential factors on elementary and middle school students’ reading practice using random forests
Authors:   Korean Association For Learner-Centered Curriculum And Instruction, Choi Jiyoun
Published: April 2024

Objectives The purposes of this study factors affecting elementary and middle school students’ reading practice were explored using the random forest technique.
Methods For this purpose, data from the 13th year (sixth grade of elementary school) and the 14th year (first year of middle school) of the Korean Children's Panel were used. Using reading practice as a response variable and 111 explanatory variables from household, parent, child, and school/private education surveys, factors affecting their reading practice were explored based on the importance index, and a partial dependence plot (PDP) was used. We used this to understand the relationship of influence.
Results As a result of examining the top 10 Mean Decrease Accuracy (MDA) predicting reading performance, in the case of 6th grade elementary school students, the results were achievement pressure, learning activities, teacher relationship, strict rules and directive atmosphere, overall happiness, academic stress, peer relationships, and school rules. , physical self-image, and self-esteem appeared in that order. In the case of first-year middle school students, the order was learning activities, achievement pressure, school rules, peer relationships, overall happiness, academic stress, strict rules and directive atmosphere, teacher relationship, physical self-image, and teacher support.
Conclusions Factors that affect elementary and middle school students' reading practice are generally more influenced by the school environment than their parents, and the fact that parents' achievement pressure, school adaptation, and strict rules and directive atmosphere are predicted to affect reading practice. It can be seen that coercion has an effect to some extent. As for other variables, there was a difference in what was predicted by ‘self-esteem’ in the 6th grade of elementary school and ‘teacher’s support’ in the 1st grade of middle school.
A Study on the Development of Conceptual Model of Career Savvy for General High School Students
Authors:   Korean Association For Learner-Centered Curriculum And Instruction, Cho Eunhye , Byun Jooyoung , Lee Yoonjoo
Published: April 2024

Objectives The purposes of this study were to investigate the definition of career savvy that fits general high school students and its components and variables for the conceptual model.
Methods For the purpose of this study, a conceptual model draft of career savvy was derived based on a comprehensive review of literature in business administration and pedagogy as well as two main theories which are trait-factor theory and cognitive information processing theory. With a conceptual model draft, Delphi surveys were conducted three times on eight career education experts.
Results As a result of the Delphi survey, a conceptual model of career savvy was made and it was agreed upon by the expert panel and its validity was secured. Carrer savvy is the concept that consists of 3 components (career information collecting competence, career strategic formulation ability, and career meta-cognition ability). Specifically, career information collecting competence has 3 factors(technological ability, Networking ability, and critical acceptance ability). Career strategic formulation ability includes 4 factors(finding the gaps, analysis, synthesis, and executing). Career meta-cognition ability forms 2 factors(knowledge meta-cognition, process meta-cognition).
Conclusions Career savvy consists of three components which are the ability to collect career information, the ability to formulate career strategies, and the ability of career meta-cognition and these components also contain more specific variables. The Career savvy conceptual model of this study can be used as a foundation for customized career education to improve the future career competency of general high school students.